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A. Ronald Gallant

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:

    Mentioned in:

    1. H-Index for Journals
      by Francis Diebold in No Hesitations on 2018-03-08 17:47:00
  1. Eric M. Aldrich & Jesús Fernández-Villaverde & Ronald Gallant & Juan F. Rubio-Ramírez, 2010. "Tapping the Supercomputer Under Your Desk: Solving Dynamic Equilibrium Models with Graphics Processors," PIER Working Paper Archive 10-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Mentioned in:

    1. Tapping the Supercomputer Under Your Desk: Solving Dynamic Equilibrium Models with Graphics Processors
      by Christian Zimmermann in NEP-DGE blog on 2010-04-18 21:57:12

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Ravi Bansal & A. Ronald Gallant & George Tauchen, 2007. "Rational Pessimism, Rational Exuberance, and Asset Pricing Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 74(4), pages 1005-1033.

    Mentioned in:

    1. Rational Pessimism, Rational Exuberance, and Asset Pricing Models (REStud 2007) in ReplicationWiki ()

Working papers

  1. A. Ronald Gallant & Mohammad Jahan-Parvar & Hening Liu, 2018. "Does Smooth Ambiguity Matter for Asset Pricing?," International Finance Discussion Papers 1221, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Chiaki Hara, 2023. "Arrow-Pratt-Type Measure of Ambiguity Aversion," KIER Working Papers 1097, Kyoto University, Institute of Economic Research.
    2. Cosmin L. Ilut & Martin Schneider, 2022. "Modeling Uncertainty as Ambiguity: a Review," NBER Working Papers 29915, National Bureau of Economic Research, Inc.
    3. Jin, Yurong & Yan, Jingzhou & Yan, Qianhui, 2024. "Unraveling ESG Ambiguity, Price Reaction, and Trading Volume," Finance Research Letters, Elsevier, vol. 61(C).
    4. David Alaminos & Ignacio Esteban & M. Belén Salas, 2023. "Neural networks for estimating Macro Asset Pricing model in football clubs," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 30(2), pages 57-75, April.
    5. Danilo Cascaldi-Garcia & Cisil Sarisoy & Juan M. Londono & Bo Sun & Deepa D. Datta & Thiago Ferreira & Olesya Grishchenko & Mohammad R. Jahan-Parvar & Francesca Loria & Sai Ma & Marius Rodriguez & Ilk, 2023. "What Is Certain about Uncertainty?," Journal of Economic Literature, American Economic Association, vol. 61(2), pages 624-654, June.
    6. Yacine Aït-Sahalia & Felix Matthys & Emilio Osambela & Ronnie Sircar, 2021. "When Uncertainty and Volatility Are Disconnected: Implications for Asset Pricing and Portfolio Performance," NBER Working Papers 29195, National Bureau of Economic Research, Inc.
    7. Sujoy Mukerji & Han N. Ozsoylev & Jean‐Marc Tallon, 2023. "Trading Ambiguity: A Tale Of Two Heterogeneities," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 1127-1164, August.
    8. Guillemin, François, 2020. "Governance by depositors, bank runs and ambiguity aversion," Research in International Business and Finance, Elsevier, vol. 54(C).
    9. Makarov, Dmitry, 2021. "Optimal portfolio under ambiguous ambiguity," Finance Research Letters, Elsevier, vol. 43(C).
    10. Hening Liu & Yuzhao Zhang, 2022. "Financial Uncertainty with Ambiguity and Learning," Management Science, INFORMS, vol. 68(3), pages 2120-2140, March.
    11. Yang, Shuwen & Aretz, Kevin & Liu, Hening & Zhang, Yuzhao, 2022. "Consumption risks in option returns," Journal of Empirical Finance, Elsevier, vol. 69(C), pages 285-302.
    12. Fulop, Andras & Heng, Jeremy & Li, Junye & Liu, Hening, 2022. "Bayesian estimation of long-run risk models using sequential Monte Carlo," Journal of Econometrics, Elsevier, vol. 228(1), pages 62-84.
    13. Patrick Schmidt, 2019. "Eliciting ambiguity with mixing bets," Papers 1902.07447, arXiv.org, revised Aug 2024.
    14. Chiaki Hara & Toshiki Honda, 2022. "Implied Ambiguity: Mean-Variance Inefficiency and Pricing Errors," Management Science, INFORMS, vol. 68(6), pages 4246-4260, June.
    15. Liu, Liu, 2022. "Learning about the persistence of recessions under ambiguity aversion," Finance Research Letters, Elsevier, vol. 47(PA).
    16. Andras Fulop & Jeremy Heng & Junye Li, 2022. "Efficient Likelihood-based Estimation via Annealing for Dynamic Structural Macrofinance Models," Papers 2201.01094, arXiv.org.

  2. A. Ronald Gallant & Mohammad Jahan-Parvar & Hening Liu, 2015. "Measuring Ambiguity Aversion," Finance and Economics Discussion Series 2015-105, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Fabrice Collard & Sujoy Mukerji & Kevin Sheppard & Jean-Marc Tallon, 2018. "Ambiguity and the historical equity premium," Post-Print halshs-01886571, HAL.
    2. Chen, Heng & Li, Xu & Pei, Guangyu & Xin, Qian, 2024. "Heterogeneous overreaction in expectation formation: Evidence and theory," Journal of Economic Theory, Elsevier, vol. 218(C).
    3. Katsutoshi Wakai, 2018. "A Factor Pricing Model under Ambiguity," Discussion papers e-17-012, Graduate School of Economics , Kyoto University.

  3. Ron Gallant & Raffaella Giacomini & Giuseppe Ragusa, 2013. "Generalized method of moments with latent variables," CeMMAP working papers CWP50/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Drew Creal & Siem Jan Koopman & André Lucas & Marcin Zamojski, 2015. "Generalized Autoregressive Method of Moments," Tinbergen Institute Discussion Papers 15-138/III, Tinbergen Institute, revised 06 Jul 2018.
    2. Rubio-Ramírez, Juan Francisco & Schorfheide, Frank & Fernández-Villaverde, Jesús, 2015. "Solution and Estimation Methods for DSGE Models," CEPR Discussion Papers 11032, C.E.P.R. Discussion Papers.
    3. Ramis Khabibullin & Sergei Seleznev, 2022. "Fast Estimation of Bayesian State Space Models Using Amortized Simulation-Based Inference," Papers 2210.07154, arXiv.org.

  4. William Barnett & A. Ronald Gallant & Melvin J. Hinich & Jochen A. Jungeilges & Daniel T. Kaplan & Mark J. Jensen, 2012. "A Single-Blind Controlled Competition Among Tests For Nonlinearity And Chaos," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201219, University of Kansas, Department of Economics, revised Sep 2012.

    Cited by:

    1. Sun, Yunpeng & Gao, Pengpeng & Raza, Syed Ali & Shah, Nida & Sharif, Arshian, 2023. "The asymmetric effects of oil price shocks on the world food prices: Fresh evidence from quantile-on-quantile regression approach," Energy, Elsevier, vol. 270(C).
    2. William Barnett & Apostolos Serletis & Demitre Serletis, 2012. "Nonlinear and Complex Dynamics in Economics," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201238, University of Kansas, Department of Economics, revised Sep 2012.
    3. Kian-Ping Lim & M. Azali & M.S. Habibullah & Venus Khim-Sen Liew, 2003. "Are Non-Linear Dynamics a Universal Occurrence? Further Evidence From Asian Stock Markets," Finance 0308001, University Library of Munich, Germany.
    4. William A. Barnett & Giovanni Bella & Taniya Ghosh & Paolo Mattana & Beatrice Venturi, 2020. "Shilnikov Chaos, Low Interest Rates, and New Keynesian Macroeconomics," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202001, University of Kansas, Department of Economics, revised Jan 2020.
    5. Christophe C. Gouel, 2012. "Agricultural price instability: a survey of competing explanations and remedies," Post-Print hal-01001218, HAL.
    6. Stan Hurn & Ralf Becker, 2006. "Testing for nonlinearity in mean in the presence of heteroskedasticity," Stan Hurn Discussion Papers 2006-02, School of Economics and Finance, Queensland University of Technology.
    7. Ahn, Eun S. & Lee, Jin Man, 2012. "The Performance Of Nonlinearity Tests On Asymmetric Nonlinear Time Series," The Journal of Economic Asymmetries, Elsevier, vol. 9(2), pages 11-44.
    8. Potzelberger, Klaus & Sogner, Leopold, 2003. "Stochastic equilibrium: learning by exponential smoothing," Journal of Economic Dynamics and Control, Elsevier, vol. 27(10), pages 1743-1770, August.
    9. William Barnett & Apostolos Serletis, 2012. "Martingales, Nonlinearity, And Chaos," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201225, University of Kansas, Department of Economics, revised Sep 2012.
    10. William A. Barnett & Melvin J. Hinich & Piyu Yue, 2011. "The Exact Theoretical Rational Expectations Monetary Aggregate," World Scientific Book Chapters, in: Financial Aggregation And Index Number Theory, chapter 2, pages 53-84, World Scientific Publishing Co. Pte. Ltd..
    11. Matilla-García, Mariano & Marín, Manuel Ruiz, 2010. "A new test for chaos and determinism based on symbolic dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 76(3), pages 600-614, December.
    12. Mendy, David & Widodo, Tri, 2018. "Two Stage Markov Switching Model: Identifying the Indonesian Rupiah Per US Dollar Turning Points Post 1997 Financial Crisis," MPRA Paper 86728, University Library of Munich, Germany.
    13. Hinich Melvin J & Mendes Eduardo M & Stone Lewi, 2005. "Detecting Nonlinearity in Time Series: Surrogate and Bootstrap Approaches," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(4), pages 1-15, December.
    14. Kyrtsou, Catherine & Malliaris, Anastasios G. & Serletis, Apostolos, 2009. "Energy sector pricing: On the role of neglected nonlinearity," Energy Economics, Elsevier, vol. 31(3), pages 492-502, May.
    15. Evzen Kocenda & Lubos Briatka, 2004. "Advancing the iid Test Based on Integration across the Correlation Integral: Ranges, Competition, and Power," Econometrics 0409001, University Library of Munich, Germany.
    16. Bildirici, Melike E. & Turkmen, Ceren, 2015. "Nonlinear causality between oil and precious metals," Resources Policy, Elsevier, vol. 46(P2), pages 202-211.
    17. Chihwa Kao & Yongmiao Hong, 2004. "Detecting Neglected Nonlinearity in Dynamic Panel Data with Time-Varying Conditional Heteroskedasticity," Econometric Society 2004 Far Eastern Meetings 753, Econometric Society.
    18. Holmes Mark J. & Panagiotidis Theodore, 2009. "Cointegration and Asymmetric Adjustment: Some New Evidence Concerning the Behavior of the U.S. Current Account," The B.E. Journal of Macroeconomics, De Gruyter, vol. 9(1), pages 1-25, June.
    19. Petre CARAIANI, 2015. "Testing For Nonlinearity In Unemployment Rates Via Delay Vector Variance," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 81-92, March.
    20. Chen, Shu-Heng & Yeh, Chia-Hsuan, 2002. "On the emergent properties of artificial stock markets: the efficient market hypothesis and the rational expectations hypothesis," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 217-239, October.
    21. Theodore Panagiotidis, 2010. "Market efficiency and the Euro: the case of the Athens stock exchange," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 37(3), pages 237-251, July.
    22. Kyrtsou, Catherine & Serletis, Apostolos, 2006. "Univariate tests for nonlinear structure," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 154-168, March.
    23. Scott C. Linn & Nicholas S. P. Tay, 2007. "Complexity and the Character of Stock Returns: Empirical Evidence and a Model of Asset Prices Based on Complex Investor Learning," Management Science, INFORMS, vol. 53(7), pages 1165-1180, July.
    24. Caraiani, Petre, 2013. "Testing for nonlinearity and chaos in economic time series with noise titration," Economics Letters, Elsevier, vol. 120(2), pages 192-194.
    25. Zacharias Psaradakis & Marián Vávra, 2015. "Portmanteau Tests for Linearity of Stationary Time Series," Birkbeck Working Papers in Economics and Finance 1514, Birkbeck, Department of Economics, Mathematics & Statistics.
    26. Saeed Moshiri & Faezeh Foroutan, 2006. "Forecasting Nonlinear Crude Oil Futures Prices," The Energy Journal, , vol. 27(4), pages 81-96, October.
    27. Panagiotidis, Theodore & Pelloni, Gianluigi, 2007. "Nonlinearity In The Canadian And U.S. Labor Markets: Univariate And Multivariate Evidence From A Battery Of Tests," Macroeconomic Dynamics, Cambridge University Press, vol. 11(5), pages 613-637, November.
    28. Chen, Shu-Heng & Lux, Thomas & Marchesi, Michele, 2001. "Testing for non-linear structure in an artificial financial market," Journal of Economic Behavior & Organization, Elsevier, vol. 46(3), pages 327-342, November.
    29. Daniela Federici & Giancarlo Gandolfo, 2011. "The Euro/Dollar Exchange Rate: Chaotic or Non-Chaotic?," DEGIT Conference Papers c016_035, DEGIT, Dynamics, Economic Growth, and International Trade.
    30. William Barnett, 2005. "Comment on 'Chaotic Monetary Dynamics with Confidence'," Macroeconomics 0505017, University Library of Munich, Germany.
    31. Serletis, Apostolos & He, Mingyu & Chowdhury, M.M. Islam, 2023. "Chaos in long-maturity real rates," Economics Letters, Elsevier, vol. 225(C).
    32. Matilla-Garcia, Mariano, 2007. "A non-parametric test for independence based on symbolic dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 31(12), pages 3889-3903, December.
    33. William A. Barnett & Fredj Jawadi & Zied Ftiti, 2020. "Causal Relationships Between Inflation and Inflation Uncertainty," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202010, University of Kansas, Department of Economics, revised Jul 2020.
    34. Reidar Hagtvedt, 2009. "Stock return dynamics and the CAPM anomalies," Applied Economics Letters, Taylor & Francis Journals, vol. 16(16), pages 1593-1596.
    35. Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada-Félix, "undated". "Testing Chaotic Dynamics via Lyapunov Exponents," Working Papers 2000-07, FEDEA.
    36. Mariano Matilla-Garcia & Paloma Sanz & Francisco Vazquez, 2005. "The BDS test and delay time," Applied Economics Letters, Taylor & Francis Journals, vol. 12(2), pages 109-113.
    37. Sandubete, Julio E. & Escot, Lorenzo, 2020. "Chaotic signals inside some tick-by-tick financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    38. Mariano Matilla-García & Manuel Ruiz Marín & Mohammed Dore & Rina Ojeda, 2014. "Nonparametric correlation integral–based tests for linear and nonlinear stochastic processes," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 37(1), pages 181-193, April.
    39. Jorge Belaire-Franch & Kwaku Opong, 2013. "A Time Series Analysis of U.K. Construction and Real Estate Indices," The Journal of Real Estate Finance and Economics, Springer, vol. 46(3), pages 516-542, April.
    40. T Tang, 2009. "Testing for Non-linearity in the Balancing Item of Balance of Payments Accounts: The Case of 20 Industrial Countries," Economic Issues Journal Articles, Economic Issues, vol. 14(2), pages 107-124, September.
    41. Oliver Linton & Mototsugu Shintani, 2001. "Is There Chaos in the World Economy? A Nonparametric Test Using Consistent Standard Errors," FMG Discussion Papers dp383, Financial Markets Group.
    42. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2013. "Some thoughts on accurate characterization of stock market indexes trends in conditions of nonlinear capital flows during electronic trading at stock exchanges in global capital markets," MPRA Paper 49921, University Library of Munich, Germany.
    43. Lyu, Xiaoyi & Hu, Hao, 2024. "The dynamic impact of monetary policy on stock market liquidity," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 388-405.
    44. William Barnett & Yijun He, 2012. "Center Manifold, Stability, and Bifurcations in Continuous Time Macroeconometric Systems," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201227, University of Kansas, Department of Economics, revised Sep 2012.
    45. Serletis, Apostolos & Shintani, Mototsugu, 2006. "Chaotic monetary dynamics with confidence," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 228-252, March.
    46. Shintani, Mototsugu & Linton, Oliver, 2002. "Nonparametric neural network estimation of Lyapunov exponents and a direct test for chaos," LSE Research Online Documents on Economics 2093, London School of Economics and Political Science, LSE Library.
    47. M. Matilla-GarcÍa & R. Queralt & P. Sanz & F. VÁzquez, 2004. "A Generalized BDS Statistic," Computational Economics, Springer;Society for Computational Economics, vol. 24(3), pages 277-300, September.
    48. Caraiani, Petre, 2014. "What drives the nonlinearity of time series: A frequency perspective," Economics Letters, Elsevier, vol. 125(1), pages 40-42.
    49. Barry E. Jones & Travis D. Nesmith, 2006. "Linear cointegration of nonlinear time series with an application to interest rate dynamics," Finance and Economics Discussion Series 2007-03, Board of Governors of the Federal Reserve System (U.S.).
    50. Ammermann, Peter A. & Patterson, Douglas M., 2003. "The cross-sectional and cross-temporal universality of nonlinear serial dependencies: Evidence from world stock indices and the Taiwan Stock Exchange," Pacific-Basin Finance Journal, Elsevier, vol. 11(2), pages 175-195, April.
    51. Marisa Faggini, 2011. "Chaotic Time Series Analysis in Economics: Balance and Perspectives," Working papers 25, Former Department of Economics and Public Finance "G. Prato", University of Torino.
    52. Oliver Moritz, 2001. "Is the German Stock Market Chaotic ? Some NEGM- and BDS-test results for the DAX," CeNDEF Workshop Papers, January 2001 3A.2, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    53. Kian-Ping Lim & Robert Brooks, 2009. "Are Chinese stock markets efficient? Further evidence from a battery of nonlinearity tests," Applied Financial Economics, Taylor & Francis Journals, vol. 19(2), pages 147-155.
    54. Ralf Becker & Walter Enders & A. Stan Hurn, 2001. "Testing for Time Dependence in Parameters," Research Paper Series 58, Quantitative Finance Research Centre, University of Technology, Sydney.
    55. Psaradakis Zacharias & Spagnolo Nicola, 2002. "Power Properties of Nonlinearity Tests for Time Series with Markov Regimes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(3), pages 1-16, November.
    56. Theodore Panagiotidis & David Chappell, 2004. "Using the Correlation Dimension to Detect non-linear dynamics," Discussion Paper Series 2004_17, Department of Economics, Loughborough University, revised Nov 2004.
    57. K.P. Lim & M.J. Hinich & K.S. Liew, 2003. "GARCH Diagnosis with Portmanteau Bicorrelation Test: An Application on the Malaysia's Stock Market," Finance 0307013, University Library of Munich, Germany.
    58. Adrian Pagan & Hashem Pesaran, 2007. "Econometric Analysis of Structural Systems with Permanent and Transitory Shocks. Working paper #7," NCER Working Paper Series 7, National Centre for Econometric Research.
    59. Caraiani, Petre, 2012. "Nonlinear dynamics in CEE stock markets indices," Economics Letters, Elsevier, vol. 114(3), pages 329-331.
    60. David, S.A. & Machado, J.A.T. & Quintino, D.D. & Balthazar, J.M., 2016. "Partial chaos suppression in a fractional order macroeconomic model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 122(C), pages 55-68.
    61. Suresh K. G. & Aviral Kumar Tiwari & Anto Joseph, 2012. "Are the emerging bric stock markets efficient?," Economics Bulletin, AccessEcon, vol. 32(2), pages 1261-1271.
    62. Barnett, William A., 1997. "Fellow's opinion: Econometrics, data, and the world wide web," Journal of Econometrics, Elsevier, vol. 77(2), pages 297-302, April.
    63. David Chappell & Theodore Panagiotidis, 2005. "Using the correlation dimension to detect non-linear dynamics: Evidence from the Athens Stock Exchange," Econometrics 0504005, University Library of Munich, Germany.
    64. Huang Xiaowei & Yu Mei & Ban Chengwei, 2014. "Nonlinear Dynamics of International Gold Prices: Conditional Heteroskedasticity or Chaos?," Journal of Systems Science and Information, De Gruyter, vol. 2(5), pages 411-427, October.
    65. Barnett, William A. & Ronald Gallant, A. & Hinich, Melvin J. & Jungeilges, Jochen A. & Kaplan, Daniel T. & Jensen, Mark J., 1995. "Robustness of nonlinearity and chaos tests to measurement error, inference method, and sample size," Journal of Economic Behavior & Organization, Elsevier, vol. 27(2), pages 301-320, July.
    66. Di Sanzo Silvestro & Bella Mariano, 2015. "Public debt and growth in the euro area: evidence from parametric and nonparametric Granger causality," The B.E. Journal of Macroeconomics, De Gruyter, vol. 15(2), pages 631-648, July.
    67. Belaire-Franch, Jorge, 2004. "Testing for non-linearity in an artificial financial market: a recurrence quantification approach," Journal of Economic Behavior & Organization, Elsevier, vol. 54(4), pages 483-494, August.
    68. William A. Barnett & Hajar Aghababa, 2016. "Dynamic Structure of the Spot Price of Crude Oil: Does Time Aggregation Matter?," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201602, University of Kansas, Department of Economics, revised Aug 2016.
    69. Lucía Inglada-Pérez & Pablo Coto-Millán, 2021. "A Chaos Analysis of the Dry Bulk Shipping Market," Mathematics, MDPI, vol. 9(17), pages 1-35, August.
    70. Semei Coronado & Rebeca Jim'enez-Rodr'iguez & Omar Rojas, 2015. "An empirical analysis of the relationships between crude oil, gold and stock markets," Papers 1510.07599, arXiv.org, revised May 2016.
    71. Phillip Wild & John Foster, 2012. "On testing for non-linear and time irreversible probabilistic structure in high frequency ASX financial time series data," Discussion Papers Series 466, School of Economics, University of Queensland, Australia.
    72. Psaradakis Zacharias, 2000. "p-Value Adjustments for Multiple Tests for Nonlinearity," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 4(3), pages 1-8, October.
    73. William A. Barnett & Yijun He & ., 1999. "Stabilization Policy as Bifurcation Selection: Would Keynesian Policy Work if the World Really were Keynesian?," Macroeconomics 9906008, University Library of Munich, Germany.
    74. Olmedo, Elena, 2011. "Is there chaos in the Spanish labour market?," Chaos, Solitons & Fractals, Elsevier, vol. 44(12), pages 1045-1053.
    75. Ioannis Andreadis & Athanasios D. Fragkou & Theodoros E. Karakasidis & Apostolos Serletis, 2023. "Nonlinear dynamics in Divisia monetary aggregates: an application of recurrence quantification analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-17, December.
    76. Wymer Clifford R., 2012. "Continuous-Tme Econometrics of Structural Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(2), pages 1-28, April.
    77. Elsinger, Helmut, 2013. "Comment on: A new test for chaos and determinism based on symbolic dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 91(C), pages 131-138.
    78. Chaudhry, Muhammad Imran & Miranda, Mario J., 2018. "Complex price dynamics in vertically linked cobweb markets," Economic Modelling, Elsevier, vol. 72(C), pages 363-378.
    79. Kian-Ping Lim & Venus Khim-Sen Liew, 2003. "Testing for Non-Linearity in ASEAN Financial Markets," Finance 0308002, University Library of Munich, Germany.
    80. Yu, Hui & Ding, Yinghui & Sun, Qingru & Gao, Xiangyun & Jia, Xiaoliang & Wang, Xinya & Guo, Sui, 2021. "Multi-scale comovement of the dynamic correlations between copper futures and spot prices," Resources Policy, Elsevier, vol. 70(C).
    81. Nusair, Salah A. & Olson, Dennis, 2019. "The effects of oil price shocks on Asian exchange rates: Evidence from quantile regression analysis," Energy Economics, Elsevier, vol. 78(C), pages 44-63.
    82. Serletis, Apostolos & Uritskaya, Olga Y., 2007. "Detecting signatures of stochastic self-organization in US money and velocity measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(1), pages 281-291.
    83. Manfred M. Fischer & Wolfgang Koller, 2001. "Testing for Non-Linear Dependence in Univariate Time Series: An Empirical Investigation of the Austrian Unemployment Rate," ERSA conference papers ersa01p233, European Regional Science Association.
    84. Kian-Ping Lim, 2009. "Weak-form market efficiency and nonlinearity: evidence from Middle East and African stock indices," Applied Economics Letters, Taylor & Francis Journals, vol. 16(5), pages 519-522.
    85. neifar, malika, 2020. "Efficiency-Market Hypothesis: case of Tunisian and 6 ‎Asian stock markets ‎," MPRA Paper 103232, University Library of Munich, Germany.
    86. William A. Barnett & Barry E. Jones & Milka Kirova & Travis Nesmith & Meenakshi Pasupathy, 2004. "The Nonlinear Skeletons in the Closet," Econometrics 0405003, University Library of Munich, Germany.
    87. Lubos Briatka, 2006. "How Big is Big Enough? Justifying Results of the iid Test Based on the Correlation Integral in the Non-Normal World," CERGE-EI Working Papers wp308, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    88. Karagianni Stella & Kyrtsou Catherine, 2011. "Analysing the Dynamics between U.S. Inflation and Dow Jones Index Using Non-Linear Methods," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(2), pages 1-25, March.
    89. Semei Coronado & Rebeca Jimnez-Rodrguez & Omar Rojas, 2018. "An Empirical Analysis of the Relationships between Crude Oil,Gold and Stock Markets," The Energy Journal, , vol. 39(1_suppl), pages 193-208, June.
    90. Federici, Daniela & Gandolfo, Giancarlo, 2012. "The Euro/Dollar exchange rate: Chaotic or non-chaotic? A continuous time model with heterogeneous beliefs," Journal of Economic Dynamics and Control, Elsevier, vol. 36(4), pages 670-681.
    91. Pena, Daniel & Rodriguez, Julio, 2005. "Detecting nonlinearity in time series by model selection criteria," International Journal of Forecasting, Elsevier, vol. 21(4), pages 731-748.
    92. Catherine Kyrtsou & Walter C. Labys & Michel Terraza, 2004. "Noisy chaotic dynamics in commodity markets," Empirical Economics, Springer, vol. 29(3), pages 489-502, September.
    93. Evzen Kocenda & Lubos Briatka, 2005. "Optimal Range for the iid Test Based on Integration Across the Correlation Integral," Econometric Reviews, Taylor & Francis Journals, vol. 24(3), pages 265-296.
    94. Lucía Inglada-Pérez & Sandra González y Gil, 2024. "A Study on the Nature of Complexity in the Spanish Electricity Market Using a Comprehensive Methodological Framework," Mathematics, MDPI, vol. 12(6), pages 1-21, March.
    95. Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada-Félix, "undated". "A New Test for Chaotic Dynamics Using Lyapunov Exponents," Working Papers 2003-09, FEDEA.
    96. Shangkun Deng & Kazuki Yoshiyama & Takashi Mitsubuchi & Akito Sakurai, 2015. "Hybrid Method of Multiple Kernel Learning and Genetic Algorithm for Forecasting Short-Term Foreign Exchange Rates," Computational Economics, Springer;Society for Computational Economics, vol. 45(1), pages 49-89, January.
    97. Biswal, P.C. & Jain, Anshul, 2019. "Should central banks use the currency futures market to manage spot volatility? Evidence from India," Journal of Multinational Financial Management, Elsevier, vol. 52.
    98. William A. Barnett, 1997. "The Current State of Research on Dynamic Economics, A Review Article of Giancarlo Gandolfo's, Economic Dynamics, third edition," Macroeconomics 9702004, University Library of Munich, Germany.

  5. Han Hong & Ahmed Khwaja & A. Ronald Gallant, 2010. "Dynamic Entry with Cross Product Spillovers: An Application to the Generic Drug Industry," Working Papers 10-59, Duke University, Department of Economics.

    Cited by:

    1. A. Ronald Gallant & Han Hong & Ahmed Khwaja, 2012. "Bayesian Estimation of a Dynamic Game with Endogenous, Partially Observed, Serially Correlated State," Working Papers 12-01, Duke University, Department of Economics.
    2. Arnaud Doucet & Neil Shephard, 2012. "Robust inference on parameters via particle filters and sandwich covariance matrices," Economics Papers 2012-W05, Economics Group, Nuffield College, University of Oxford.
    3. Mitsukuni Nishida & Nathan Yang, 2014. "Better Together? Retail Chain Performance Dynamics in Store Expansion Before and After Mergers," Working Papers 14-08, NET Institute.

  6. Eric M. Aldrich & A. Ronald Gallant, 2010. "Habit, Long-Run Risks, Prospect? A Statistical Inquiry," Working Papers 10-60, Duke University, Department of Economics.

    Cited by:

    1. Raymond Kan & Cesare Robotti, 2016. "The Exact Distribution of the Hansen–Jagannathan Bound," Management Science, INFORMS, vol. 62(7), pages 1915-1943, July.
    2. David Alaminos & Ignacio Esteban & M. Belén Salas, 2023. "Neural networks for estimating Macro Asset Pricing model in football clubs," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 30(2), pages 57-75, April.
    3. Grammig, Joachim & Küchlin, Eva-Maria, 2017. "A two-step indirect inference approach to estimate the long-run risk asset pricing model," CFR Working Papers 17-01, University of Cologne, Centre for Financial Research (CFR).
    4. Friederike Mengel & Ronald Peeters, 2022. "Do markets encourage risk-seeking behaviour?," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1474-1480, October.
    5. Favero, Carlo A. & Tamoni, Andrea & Ortu, Fulvio & Yang, Haoxi, 2016. "Implications of Return Predictability across Horizons for Asset Pricing Models," CEPR Discussion Papers 11645, C.E.P.R. Discussion Papers.
    6. Grammig, Joachim & Küchlin, Eva-Maria, 2018. "A two-step indirect inference approach to estimate the long-run risk asset pricing model," Journal of Econometrics, Elsevier, vol. 205(1), pages 6-33.
    7. A. Ronald Gallant & Mohammad Jahan-Parvar & Hening Liu, 2015. "Measuring Ambiguity Aversion," Finance and Economics Discussion Series 2015-105, Board of Governors of the Federal Reserve System (U.S.).
    8. Andrew Y. Chen & Rebecca Wasyk & Fabian Winkler, 2017. "A Likelihood-Based Comparison of Macro Asset Pricing Models," Finance and Economics Discussion Series 2017-024, Board of Governors of the Federal Reserve System (U.S.).
    9. Grammig, Joachim & Küchlin, Eva-Maria, 2017. "A two-step indirect inference approach to estimate the long-run risk asset pricing model," CFS Working Paper Series 572, Center for Financial Studies (CFS).

  7. Eric M. Aldrich & Jesús Fernández-Villaverde & Ronald Gallant & Juan F. Rubio-Ramírez, 2010. "Tapping the Supercomputer Under Your Desk: Solving Dynamic Equilibrium Models with Graphics Processors," PIER Working Paper Archive 10-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

    Cited by:

    1. Hull, Isaiah, 2017. "Amortization requirements and household indebtedness: An application to Swedish-style mortgages," European Economic Review, Elsevier, vol. 91(C), pages 72-88.
    2. Hui Chen & Antoine Didisheim & Simon Scheidegger, 2021. "Deep Structural Estimation:With an Application to Option Pricing," Cahiers de Recherches Economiques du Département d'économie 21.14, Université de Lausanne, Faculté des HEC, Département d’économie.
    3. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Parallel Sequential Monte Carlo for Efficient Density Combination: The Deco Matlab Toolbox," CREATES Research Papers 2013-09, Department of Economics and Business Economics, Aarhus University.
    4. Oancea, Bogdan, 2014. "Parallel Computing in Economics - An Overview of the Software Frameworks," MPRA Paper 72039, University Library of Munich, Germany.
    5. Robert Kirkby, 2024. "Computing Quantiles of Functions of the Agent Distribution Using t-Digests," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 1199-1218, August.
    6. Arefiev, Nikolay & Khabibullin, Ramis, 2018. "Bayesian identification of structural vector autoregression models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 49, pages 115-142.
    7. Rubio-Ramírez, Juan Francisco & Schorfheide, Frank & Fernández-Villaverde, Jesús, 2015. "Solution and Estimation Methods for DSGE Models," CEPR Discussion Papers 11032, C.E.P.R. Discussion Papers.
    8. Yongyang Cai & Kenneth L. Judd, 2012. "Dynamic Programming with Hermite Approximation," NBER Working Papers 18540, National Bureau of Economic Research, Inc.
    9. Zha, Tao & Rubio-Ramírez, Juan Francisco & , & Foerster, Andrew, 2013. "Perturbation Methods for Markov-Switching DSGE Models," CEPR Discussion Papers 9464, C.E.P.R. Discussion Papers.
    10. Doug J. Chung & Kyoungwon Seo & Reo Song, 2023. "Efficient computation of discrete games: Estimating the effect of Apple on market structure," Production and Operations Management, Production and Operations Management Society, vol. 32(7), pages 2245-2263, July.
    11. Grey Gordon, 2020. "Computing Dynamic Heterogeneous-Agent Economies: Tracking the Distribution," Economic Quarterly, Federal Reserve Bank of Richmond, issue 2Q, pages 61-95.
    12. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    13. Eric Aldrich, 2012. "Trading Volume in General Equilibrium with Complete Markets," 2012 Meeting Papers 36, Society for Economic Dynamics.
    14. Olaf Posch & Timo Trimborn, 2011. "Numerical Solution of Dynamic Equilibrium Models under Poisson Uncertainty," DEGIT Conference Papers c016_044, DEGIT, Dynamics, Economic Growth, and International Trade.
    15. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2015. "Dynamic predictive density combinations for large data sets in economics and finance," Working Paper 2015/12, Norges Bank.
    16. Fernández-Villaverde, Jesús & Zarruk Valencia , David, 2018. "A Practical Guide to Parallelization in Economics," CEPR Discussion Papers 12890, C.E.P.R. Discussion Papers.
    17. Aldrich, EM, 2014. "GPU Computing in Economics," Santa Cruz Department of Economics, Working Paper Series qt8p12748g, Department of Economics, UC Santa Cruz.
    18. Tjaden, Volker, 2013. "Foreign Customer Accumulation and Export Dynamics," Bonn Econ Discussion Papers 06/2013, University of Bonn, Bonn Graduate School of Economics (BGSE).
    19. Morozov, Sergei & Mathur, Sudhanshu, 2009. "Massively parallel computation using graphics processors with application to optimal experimentation in dynamic control," MPRA Paper 30298, University Library of Munich, Germany, revised 04 Apr 2011.
    20. Andrew Blake, 2012. "DSGE Modeling on an iPhone/iPad Using SpaceTime," Computational Economics, Springer;Society for Computational Economics, vol. 40(4), pages 313-332, December.
    21. Kyle Klein & Julian Neira, 2014. "Nelder-Mead Simplex Optimization Routine for Large-Scale Problems: A Distributed Memory Implementation," Computational Economics, Springer;Society for Computational Economics, vol. 43(4), pages 447-461, April.
    22. Roberto Casarin & Stefano Grassi & Francesco Ravazzolo & Herman K. van Dijk, 2020. "A Bayesian Dynamic Compositional Model for Large Density Combinations in Finance," Working Paper series 20-27, Rimini Centre for Economic Analysis.
    23. Robert Kirkby, 2017. "A Toolkit for Value Function Iteration," Computational Economics, Springer;Society for Computational Economics, vol. 49(1), pages 1-15, January.
    24. Sergei Morozov & Sudhanshu Mathur, 2012. "Massively Parallel Computation Using Graphics Processors with Application to Optimal Experimentation in Dynamic Control," Computational Economics, Springer;Society for Computational Economics, vol. 40(2), pages 151-182, August.
    25. Waggoner, Daniel F. & Wu, Hongwei & Zha, Tao, 2016. "Striated Metropolis–Hastings sampler for high-dimensional models," Journal of Econometrics, Elsevier, vol. 192(2), pages 406-420.
    26. Michael C. Hatcher & Eric M. Scheffel, 2016. "Solving the Incomplete Markets Model in Parallel Using GPU Computing and the Krusell–Smith Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 48(4), pages 569-591, December.
    27. John Gibson & James P Henson, 2016. "Getting the most from MATLAB: ditching canned routines and embracing coder," Economics Bulletin, AccessEcon, vol. 36(4), pages 2519-2525.
    28. Nalan Baştürk & Stefano Grassi & Lennart Hoogerheide & Herman K. Van Dijk, 2016. "Parallelization Experience with Four Canonical Econometric Models Using ParMitISEM," Econometrics, MDPI, vol. 4(1), pages 1-20, March.
    29. Matt P. Dziubinski & Stefano Grassi, 2012. "Heterogeneous Computing in Economics: A Simplified Approach," CREATES Research Papers 2012-15, Department of Economics and Business Economics, Aarhus University.
    30. Nalan Baştürk & Roberto Casarin & Francesco Ravazzolo & Herman K. Van Dijk, 2016. "Computational Complexity and Parallelization in Bayesian Econometric Analysis," Econometrics, MDPI, vol. 4(1), pages 1-3, February.
    31. Gonzalo F. de-Córdoba & Benedetto Molinari & José L. Torres, 2021. "Public Debt Frontier: A Python Toolkit for Analyzing Public Debt Sustainability," Sustainability, MDPI, vol. 13(23), pages 1-25, November.
    32. Lilia Maliar, 2015. "Assessing gains from parallel computation on a supercomputer," Economics Bulletin, AccessEcon, vol. 35(1), pages 159-167.
    33. Robert Kirkby Author-Email: robertkirkby@gmail.com|, 2017. "Convergence of Discretized Value Function Iteration," Computational Economics, Springer;Society for Computational Economics, vol. 49(1), pages 117-153, January.
    34. Peri, Alessandro, 2020. "A hardware approach to value function iteration," Journal of Economic Dynamics and Control, Elsevier, vol. 114(C).
    35. Yongyang Cai & Kenneth L. Judd & Greg Thain & Stephen J. Wright, 2013. "Solving Dynamic Programming Problems on a Computational Grid," NBER Working Papers 18714, National Bureau of Economic Research, Inc.
    36. Theodosios Dimopoulos & Stefano Sacchetto, "undated". "Technological Heterogeneity and Corporate Investment," GSIA Working Papers 2012-E48, Carnegie Mellon University, Tepper School of Business.
    37. Duarte, Victor & Duarte, Diogo & Fonseca, Julia & Montecinos, Alexis, 2020. "Benchmarking machine-learning software and hardware for quantitative economics," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    38. Bongers, Anelí & Molinari, Benedetto & Torres, José L., 2022. "Computers, Programming and Dynamic General Equilibrium Macroeconomic Modeling," MPRA Paper 112505, University Library of Munich, Germany.

  8. Ravi Bansal & A. Ronald Gallant & George Tauchen, 2007. "Rational Pessimism, Rational Exuberance, and Asset Pricing Models," NBER Working Papers 13107, National Bureau of Economic Research, Inc.

    Cited by:

    1. Fabrice Collard & Sujoy Mukerji & Kevin Sheppard & Jean-Marc Tallon, 2018. "Ambiguity and the historical equity premium," Post-Print halshs-01886571, HAL.
    2. Ravi Bansal & Dana Kiku & Amir Yaron, 2012. "Risks For the Long Run: Estimation with Time Aggregation," NBER Working Papers 18305, National Bureau of Economic Research, Inc.
    3. Kim, Kun Ho, 2014. "Counter-cyclical risk aversion," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 384-401.
    4. James Staveley-O'Carroll & Olena M. Staveley-O'Carroll, 2016. "Impact of Pension System Structure on International Financial Capital Allocation," Working Papers 1601, College of the Holy Cross, Department of Economics.
    5. Drew D. Creal & Jing Cynthia Wu, 2020. "Bond risk premia in consumption‐based models," Quantitative Economics, Econometric Society, vol. 11(4), pages 1461-1484, November.
    6. Dalderop, Jeroen, 2023. "Semiparametric estimation of latent variable asset pricing models," Journal of Econometrics, Elsevier, vol. 236(1).
    7. Sönksen, Jantje & Grammig, Joachim, 2021. "Empirical asset pricing with multi-period disaster risk: A simulation-based approach," Journal of Econometrics, Elsevier, vol. 222(1), pages 805-832.
    8. Mathias S. Kruttli, 2016. "From Which Consumption-Based Asset Pricing Models Can Investors Profit? Evidence from Model-Based Priors," Finance and Economics Discussion Series 2016-027, Board of Governors of the Federal Reserve System (U.S.).
    9. Jianfeng Yu, 2009. "The Long and the Short of Asset Prices: Using Long Run Consumption-Return Correlations to Test Asset Pricing Models," 2009 Meeting Papers 56, Society for Economic Dynamics.
    10. David Alaminos & Ignacio Esteban & M. Belén Salas, 2023. "Neural networks for estimating Macro Asset Pricing model in football clubs," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 30(2), pages 57-75, April.
    11. Mariano Croce & Mohammad R. Jahan-Parvar & Samuel Rosen, 2022. "SONOMA: a Small Open ecoNOmy for MAcrofinance," International Finance Discussion Papers 1349, Board of Governors of the Federal Reserve System (U.S.).
    12. Hanno Lustig & Stijn Van Nieuwerburg & Adrien Verdelhan, 2007. "The Wealth-Consumption Ratio: A Litmus Test for Consumption-based Asset Pricing Models¤," Boston University - Department of Economics - Working Papers Series WP2007-030, Boston University - Department of Economics.
    13. Grammig, Joachim & Küchlin, Eva-Maria, 2017. "A two-step indirect inference approach to estimate the long-run risk asset pricing model," CFR Working Papers 17-01, University of Cologne, Centre for Financial Research (CFR).
    14. Dario Caldara & Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez & Wen Yao, 2009. "Computing DSGE Models with Recursive Preferences," NBER Working Papers 15026, National Bureau of Economic Research, Inc.
    15. Berg Cui & Yoosoon Chang & Joon Park, 2017. "Evaluating Consumption CAPM under Heterogeneous Preferences," CAEPR Working Papers 2017-013, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    16. George M. Constantinides & Anisha Ghosh, 2008. "Asset Pricing Tests with Long Run Risks in Consumption Growth," NBER Working Papers 14543, National Bureau of Economic Research, Inc.
    17. Luca Benzoni & Pierre Collin-Dufresne & Robert S. Goldstein, 2011. "Can standard preferences explain the prices of out-of-the-money S&P 500 put options?," Working Paper Series WP-2011-11, Federal Reserve Bank of Chicago.
    18. Zhang, Jian & Kong, Dongmin & Liu, Hening & Wu, Ji, 2019. "Asset pricing with time varying pessimism and rare disasters," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 165-175.
    19. Ravi Bansal & Robert Dittmar & Dana Kiku, 2007. "Cointegration and Consumption Risks in Asset Returns," NBER Working Papers 13108, National Bureau of Economic Research, Inc.
    20. Bollerslev, Tim & Xu, Lai & Zhou, Hao, 2015. "Stock return and cash flow predictability: The role of volatility risk," Journal of Econometrics, Elsevier, vol. 187(2), pages 458-471.
    21. McMillan, David G., 2014. "Stock return, dividend growth and consumption growth predictability across markets and time: Implications for stock price movement," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 90-101.
    22. Frank Schorfheide & Dongho Song & Amir Yaron, 2014. "Identifying Long-Run Risks: A Bayesian Mixed-Frequency Approach," NBER Working Papers 20303, National Bureau of Economic Research, Inc.
    23. Fatih Guvenen & Anthony Smith, 2013. "Inferring labor income risk and partial insurance from economic choices," Staff Report 485, Federal Reserve Bank of Minneapolis.
    24. Xiaohong Chen & Jack Favilukis & Sydney Ludvigson, 2012. "An estimation of economic models with recursive preferences," CeMMAP working papers 32/12, Institute for Fiscal Studies.
    25. Hirshleifer, David & Li, Jun & Yu, Jianfeng, 2015. "Asset pricing in production economies with extrapolative expectations," Journal of Monetary Economics, Elsevier, vol. 76(C), pages 87-106.
    26. Jungshik Hur & Vivek Singh, 2013. "Does long-term disequilibrium in stock price predict future returns?," Review of Quantitative Finance and Accounting, Springer, vol. 41(4), pages 753-767, November.
    27. Wang, Qin & Ren, Yu & Zou, Yiheng, 2016. "Uninsured expense shocks and equity premia," Economic Modelling, Elsevier, vol. 58(C), pages 64-74.
    28. Na Guo & Peter N. Smith, 2012. "Durable Consumption, Long-Run Risk and The Equity Premium," Discussion Papers 12/37, Department of Economics, University of York.
    29. Jianfeng Yu, 2012. "Online Appendix to "Using Long-Run Consumption-Return Correlations to Test Asset Pricing Models"," Online Appendices 10-230, Review of Economic Dynamics.
    30. Rolf Golombek & Arvid Raknerud, 2015. "Exit Dynamics of Start-up Firms: Does Profit Matter?," CESifo Working Paper Series 5172, CESifo.
    31. Pakos, Michal, 2013. "Long-Run Risk and Hidden Growth Persistence," MPRA Paper 47217, University Library of Munich, Germany.
    32. Shigeta, Yuki, 2022. "Quasi-hyperbolic discounting under recursive utility and consumption–investment decisions," Journal of Economic Theory, Elsevier, vol. 204(C).
    33. Luca Benzoni & Pierre Collin-Dufresne & Robert S. Goldstein, 2010. "Explaining asset pricing puzzles associated with the 1987 market crash," Working Paper Series WP-2010-10, Federal Reserve Bank of Chicago.
    34. Anthony M. Diercks, 2015. "The Equity Premium, Long-Run Risk, & Optimal Monetary Policy," Finance and Economics Discussion Series 2015-87, Board of Governors of the Federal Reserve System (U.S.).
    35. TAKAMIZAWA, Hideyuki & 高見澤, 秀幸, 2018. "An Equilibrium Model of Term Structures of Bonds and Equities," Working Paper Series G-1-19, Hitotsubashi University Center for Financial Research.
    36. Bonomo, Marco & Garcia, René & Meddahi, Nour & Tédongap, Roméo, 2010. "Generalized Disappointment Aversion, Long Run Volatility Risk and Asset Prices," TSE Working Papers 10-187, Toulouse School of Economics (TSE).
    37. Lars Ljungqvist & Harald Uhlig, 2009. "Optimal Endowment Destruction under Campbell-Cochrane Habit Formation," NBER Working Papers 14772, National Bureau of Economic Research, Inc.
    38. Fulop, Andras & Heng, Jeremy & Li, Junye & Liu, Hening, 2022. "Bayesian estimation of long-run risk models using sequential Monte Carlo," Journal of Econometrics, Elsevier, vol. 228(1), pages 62-84.
    39. Sydney Ludvigson & Jack Favalukus & Xiaohong Chen, 2007. "An Estimation of Economic Models with Recursive Preferences," 2007 Meeting Papers 543, Society for Economic Dynamics.
    40. Forneron, Jean-Jacques, 2024. "Detecting identification failure in moment condition models," Journal of Econometrics, Elsevier, vol. 238(1).
    41. Grammig, Joachim & Schaub, Eva-Maria, 2014. "Give me strong moments and time - Combining GMM and SMM to estimate long-run risk asset pricing models," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100607, Verein für Socialpolitik / German Economic Association.
    42. Ravi Bansal & Dana Kiku & Amir Yaron, 2010. "Long Run Risks, the Macroeconomy, and Asset Prices," American Economic Review, American Economic Association, vol. 100(2), pages 542-546, May.
    43. Ludvigson, Sydney C., 2013. "Advances in Consumption-Based Asset Pricing: Empirical Tests," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 799-906, Elsevier.
    44. Max Gillman & Michal Kejak & Michal Pakos, 2014. "Learning about Disaster Risk: Joint Implications for Consumption and Asset Prices," CERGE-EI Working Papers wp507, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    45. Sing, Tien Foo & Zou, Yiheng, 2022. "Mortgage payments and equity premium puzzle," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 376-388.
    46. Verdelhan, Adrien & Van Nieuwerburgh, Stijn & Lustig, Hanno, 2012. "The Wealth-Consumption Ratio," CEPR Discussion Papers 9022, C.E.P.R. Discussion Papers.
    47. Anthony Diercks, 2016. "The Equity Premium, Long-Run Risk, and Optimal Monetary Policy," 2016 Meeting Papers 207, Society for Economic Dynamics.
    48. Grammig, Joachim & Küchlin, Eva-Maria, 2018. "A two-step indirect inference approach to estimate the long-run risk asset pricing model," Journal of Econometrics, Elsevier, vol. 205(1), pages 6-33.
    49. Bansal, Ravi & Kiku, Dana & Yaron, Amir, 2012. "An Empirical Evaluation of the Long-Run Risks Model for Asset Prices," Critical Finance Review, now publishers, vol. 1(1), pages 183-221, January.
    50. Andrew Y. Chen, 2013. "External Habit in a Production Economy," 2013 Papers pch1244, Job Market Papers.
    51. Santiago Budría, 2008. "An Exploration of Asset Returns in a Production Economy with Relative Habits," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 36(3), pages 261-274, September.
    52. Golombek, Rolf & Raknerud, Arvid, 2018. "Exit dynamics of start-up firms: Structural estimation using indirect inference," Journal of Econometrics, Elsevier, vol. 205(1), pages 204-225.
    53. Branger, Nicole & Rodrigues, Paulo & Schlag, Christian, 2018. "Level and slope of volatility smiles in long-run risk models," Journal of Economic Dynamics and Control, Elsevier, vol. 86(C), pages 95-122.
    54. Andrew Y. Chen, 2014. "Precautionary Volatility and Asset Prices," Finance and Economics Discussion Series 2014-59, Board of Governors of the Federal Reserve System (U.S.).
    55. Branger, Nicole & Rodrigues, Paulo & Schlag, Christian, 2017. "Level and slope of volatility smiles in Long-Run Risk Models," SAFE Working Paper Series 186, Leibniz Institute for Financial Research SAFE.
    56. Grammig, Joachim & Schaub, Eva-Maria, 2014. "Give me strong moments and time: Combining GMM and SMM to estimate long-run risk asset pricing," CFR Working Papers 14-05, University of Cologne, Centre for Financial Research (CFR).
    57. Max Gillman & Michal Kejak & Michal Pakos, 2014. "Learning about Rare Disasters: Implications for Consumptions and Asset Prices," CEU Working Papers 2014_2, Department of Economics, Central European University.
    58. Wayne E. Ferson & Suresh K. Nallareddy & Biqin Xie, 2012. "The "Out of Sample" Performance of Long-run Risk Models," NBER Working Papers 17848, National Bureau of Economic Research, Inc.
    59. A. Ronald Gallant & Mohammad Jahan-Parvar & Hening Liu, 2015. "Measuring Ambiguity Aversion," Finance and Economics Discussion Series 2015-105, Board of Governors of the Federal Reserve System (U.S.).
    60. Massimiliano Croce, Mariano, 2014. "Long-run productivity risk: A new hope for production-based asset pricing?," Journal of Monetary Economics, Elsevier, vol. 66(C), pages 13-31.
    61. Andrew Y. Chen & Rebecca Wasyk & Fabian Winkler, 2017. "A Likelihood-Based Comparison of Macro Asset Pricing Models," Finance and Economics Discussion Series 2017-024, Board of Governors of the Federal Reserve System (U.S.).
    62. Ravi Bansal & Marcelo Ochoa, 2011. "Welfare Costs of Long-Run Temperature Shifts," NBER Working Papers 17574, National Bureau of Economic Research, Inc.
    63. Grammig, Joachim & Schaub, Eva-Maria, 2014. "Give me strong moments and time: Combining GMM and SMM to estimate long-run risk asset pricing models," CFS Working Paper Series 479, Center for Financial Studies (CFS).
    64. Grammig, Joachim & Küchlin, Eva-Maria, 2017. "A two-step indirect inference approach to estimate the long-run risk asset pricing model," CFS Working Paper Series 572, Center for Financial Studies (CFS).
    65. Ferson, Wayne & Nallareddy, Suresh & Xie, Biqin, 2013. "The “out-of-sample” performance of long run risk models," Journal of Financial Economics, Elsevier, vol. 107(3), pages 537-556.
    66. Qin Wang & Yiheng Zou & Yu Ren & Zhuo Huang, 2015. "The Spirit of Capitalism and the Equity Premium," Annals of Economics and Finance, Society for AEF, vol. 16(2), pages 493-513, November.
    67. Andras Fulop & Jeremy Heng & Junye Li, 2022. "Efficient Likelihood-based Estimation via Annealing for Dynamic Structural Macrofinance Models," Papers 2201.01094, arXiv.org.
    68. Maio, Paulo & Silva, André C., 2020. "Asset pricing implications of money: New evidence," Journal of Banking & Finance, Elsevier, vol. 120(C).
    69. Lee, Ji Hyung & Phillips, Peter C.B., 2016. "Asset pricing with financial bubble risk," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 590-622.
    70. Du, Du, 2013. "General equilibrium pricing of currency and currency options," Journal of Financial Economics, Elsevier, vol. 110(3), pages 730-751.
    71. Ruan, Xinfeng & Zhang, Jin E., 2018. "Equilibrium variance risk premium in a cost-free production economy," Journal of Economic Dynamics and Control, Elsevier, vol. 96(C), pages 42-60.

  9. Gallant, A. Ronald & Tauchen, George, 2002. "Simulated Score Methods and Indirect Inference for Continuous-time Models," Working Papers 02-09, Duke University, Department of Economics.

    Cited by:

    1. Peter Fuleky & Eric Zivot, 2010. "Indirect Inference Based on the Score," Working Papers UWEC-2010-08, University of Washington, Department of Economics.
    2. Francisco Peñaranda & Jón Daníelsson, 2007. "On the impact of fundamentals, liquidity and coordination on market stability," Economics Working Papers 1003, Department of Economics and Business, Universitat Pompeu Fabra, revised Mar 2010.
    3. Manuel S. Santos, 2007. "Consistency Properties of a Simulation-Base Estimator for Dynamic Processes," Working Papers 0613, University of Miami, Department of Economics.
    4. In Kim & In-Seok Baek & Jaesun Noh & Sol Kim, 2007. "The role of stochastic volatility and return jumps: reproducing volatility and higher moments in the KOSPI 200 returns dynamics," Review of Quantitative Finance and Accounting, Springer, vol. 29(1), pages 69-110, July.
    5. Michael S. Johannes & Nicholas G. Polson & Jonathan R. Stroud, 2009. "Optimal Filtering of Jump Diffusions: Extracting Latent States from Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 22(7), pages 2559-2599, July.
    6. Torben G. Andersen & Tim Bollerslev & Nour Meddahi, 2002. "Analytic Evaluation of Volatility Forecasts," CIRANO Working Papers 2002s-90, CIRANO.
    7. Ravi Bansal & A. Ronald Gallant & George Tauchen, 2007. "Rational Pessimism, Rational Exuberance, and Asset Pricing Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 74(4), pages 1005-1033.
    8. Michael Creel, 2008. "Estimation of Dynamic Latent Variable Models Using Simulated Nonparametric Moments," UFAE and IAE Working Papers 725.08, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 02 Jun 2008.
    9. Marcel Rindisbacher & Jérôme Detemple & René Garcia, 2004. "Asymptotic Properties of Monte Carlo Estimators of Diffusion Processes," Econometric Society 2004 North American Winter Meetings 483, Econometric Society.

  10. Mikhail Chernov & A. Ronald Gallant & Eric Ghysels & George Tauchen, 2002. "Alternative Models for Stock Price Dynamics," CIRANO Working Papers 2002s-58, CIRANO.

    Cited by:

    1. Siddiqi, Hammad, 2014. "Analogy Making and the Structure of Implied Volatility Skew," MPRA Paper 60921, University Library of Munich, Germany.
    2. Hounyo, Ulrich & Varneskov, Rasmus T., 2020. "Inference for local distributions at high sampling frequencies: A bootstrap approach," Journal of Econometrics, Elsevier, vol. 215(1), pages 1-34.
    3. Tim Bollerslev & Michael Gibson & Hao Zhou, 2007. "Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities," CREATES Research Papers 2007-16, Department of Economics and Business Economics, Aarhus University.
    4. Christophe M. Boucher & Bertrand B. Maillet, 2013. "Learning by Failing: A Simple VaR Buffer," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 22(2), pages 113-127, May.
    5. Xavier Calmet & Nathaniel Wiesendanger Shaw, 2020. "An analytical perturbative solution to the Merton–Garman model using symmetries," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(1), pages 3-22, January.
    6. Turan G. Bali & Armen Hovakimian, 2009. "Volatility Spreads and Expected Stock Returns," Management Science, INFORMS, vol. 55(11), pages 1797-1812, November.
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    1. Hoi Wong & Tsz Wong, 2007. "Reduced-form Models with Regime Switching: An Empirical Analysis for Corporate Bonds," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(3), pages 229-253, September.
    2. Michael Creel, 2021. "Inference Using Simulated Neural Moments," Econometrics, MDPI, vol. 9(4), pages 1-15, September.
    3. Monica Gentile & Roberto Renò, 2002. "Which Model for the Italian Interest Rates?," LEM Papers Series 2002/02, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

  12. Gallant, A. Ronald & Hsu, Chien-Te & Tauchen, George, 2000. "Using Daily Range Data to Calibrate Volatility Diffusions and Extract the Forward Integrated Variance," Working Papers 00-04, Duke University, Department of Economics.

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    1. Narayan, Paresh Kumar & Mishra, Sagarika & Sharma, Susan Sunila & Liu, Ruipeng, 2013. "Determinants of stock price bubbles," Working Papers fe_2013_06, Deakin University, Department of Economics.
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    3. Dark Jonathan Graeme, 2010. "Estimation of Time Varying Skewness and Kurtosis with an Application to Value at Risk," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(2), pages 1-50, March.
    4. Hjalmarsson, Erik, 2003. "Does the Black-Scholes formula work for electricity markets? A nonparametric approach," Working Papers in Economics 101, University of Gothenburg, Department of Economics.
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    6. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    7. Manabu Asai & Michael McAleer, 2013. "Leverage and Feedback Effects on Multifactor Wishart Stochastic Volatility for Option Pricing," KIER Working Papers 840, Kyoto University, Institute of Economic Research.
    8. René Garcia & Richard Luger & Eric Renault, 2001. "Asymmetric Smiles, Leverage Effects and Structural Parameters," CIRANO Working Papers 2001s-01, CIRANO.
    9. Suk Joon Byun & Jung‐Soon Hyun & Woon Jun Sung, 2021. "Estimation of stochastic volatility and option prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(3), pages 349-360, March.
    10. Gilles Dufrenot & Dominique Guegan & Anne Peguin-Feissolle, 2008. "Changing-regime volatility: A fractionally integrated SETAR model," Post-Print halshs-00185369, HAL.
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    12. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
    13. Liao, Yin, 2013. "The benefit of modeling jumps in realized volatility for risk prediction: Evidence from Chinese mainland stocks," Pacific-Basin Finance Journal, Elsevier, vol. 23(C), pages 25-48.
    14. Asai, Manabu & Brugal, Ivan, 2013. "Forecasting volatility via stock return, range, trading volume and spillover effects: The case of Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 202-213.
    15. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    16. Huber, Christoph & Huber, Juergen & Kirchler, Michael, 2021. "Volatility shocks and investment behavior," OSF Preprints jr4eb, Center for Open Science.
    17. Evarist Stoja & Richard D. F. Harris & Fatih Yilmaz, 2010. "A Cyclical Model of Exchange Rate Volatility," Bristol Economics Discussion Papers 10/618, School of Economics, University of Bristol, UK.
    18. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range‐Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, June.
    19. Igor Kliakhandler, 2007. "Execution edge of pit traders and intraday price ranges of soft commodities," Applied Financial Economics, Taylor & Francis Journals, vol. 17(5), pages 343-350.
    20. Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018. "Risk Everywhere: Modeling and Managing Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2729-2773.
    21. Aït-Sahalia, Yacine & Li, Chenxu & Li, Chen Xu, 2021. "Closed-form implied volatility surfaces for stochastic volatility models with jumps," Journal of Econometrics, Elsevier, vol. 222(1), pages 364-392.
    22. Abel Rodriguez & Henryk Gzyl & German Molina & Enrique ter Horst, 2009. "Stochastic Volatility Models Including Open, Close, High and Low Prices," Papers 0901.1315, arXiv.org.
    23. Christensen, Bent Jesper & Varneskov, Rasmus Tangsgaard, 2017. "Medium band least squares estimation of fractional cointegration in the presence of low-frequency contamination," Journal of Econometrics, Elsevier, vol. 197(2), pages 218-244.
    24. Vladimir Tsenkov, 2009. "Financial Markets Modelling," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 5, pages 87-96.
    25. Angela He & Alan Wan, 2009. "Predicting daily highs and lows of exchange rates: a cointegration analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(11), pages 1191-1204.
    26. Nour Meddahi, 2003. "ARMA representation of integrated and realized variances," Econometrics Journal, Royal Economic Society, vol. 6(2), pages 335-356, December.
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    1. Christoph Breunig, 2018. "Varying Random Coefficient Models," Papers 1804.03110, arXiv.org, revised Aug 2020.
    2. Giuseppe De Luca & Franco Peracchi, 2010. "Estimating Engel curves under unit and item nonresponse," EIEF Working Papers Series 1004, Einaudi Institute for Economics and Finance (EIEF), revised Nov 2010.
    3. Xiaohong Chen & Yanqin Fan & Victor Tsyrennifov, 2004. "Efficient Estimation of Semiparametric Multivariate Copula Models," Vanderbilt University Department of Economics Working Papers 0420, Vanderbilt University Department of Economics.
    4. Chen, Xiaohong & Hong, Han & Shum, Matthew, 2007. "Nonparametric likelihood ratio model selection tests between parametric likelihood and moment condition models," Journal of Econometrics, Elsevier, vol. 141(1), pages 109-140, November.
    5. Gallant, A. Ronald & Tauchen, George, 2002. "Simulated Score Methods and Indirect Inference for Continuous-time Models," Working Papers 02-09, Duke University, Department of Economics.
    6. Veiga, Helena, 2006. "Are feedback factors important in modelling financial data?," DES - Working Papers. Statistics and Econometrics. WS ws060101, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Xiaohong Chen & Yingyao Hu, 2006. "Identification and Inference of Nonlinear Models Using Two Samples with Arbitrary Measurement Errors," Cowles Foundation Discussion Papers 1590, Cowles Foundation for Research in Economics, Yale University.
    8. Ai, Chunrong & Linton, Oliver & Zhang, Zheng, 2022. "Estimation and inference for the counterfactual distribution and quantile functions in continuous treatment models," Journal of Econometrics, Elsevier, vol. 228(1), pages 39-61.
    9. Chen, Xiaohong, 2007. "Large Sample Sieve Estimation of Semi-Nonparametric Models," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 76, Elsevier.
    10. Breunig, Christoph, 2021. "Varying random coefficient models," Journal of Econometrics, Elsevier, vol. 221(2), pages 381-408.
    11. Kevin Hasker & Robin Sickles, 2010. "eBay in the Economic Literature: Analysis of an Auction Marketplace," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 37(1), pages 3-42, August.
    12. Foster, Joshua, 2022. "Semi-nonparametric estimation of secret reserve prices in auctions," Economics Letters, Elsevier, vol. 220(C).
    13. Erik Vogt, 2014. "Option-implied term structures," Staff Reports 706, Federal Reserve Bank of New York.
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    17. Schwiebert, Jörg, 2012. "Analyzing the Composition of the Female Workforce - A Semiparametric Copula Approach," Hannover Economic Papers (HEP) dp-503, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
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    19. Garcia, René & Renault, Eric & Veredas, David, 2011. "Estimation of stable distributions by indirect inference," Journal of Econometrics, Elsevier, vol. 161(2), pages 325-337, April.
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  14. Mikhail Chernov & A. Ronald Gallant & Eric Ghysels & George Tauchen, 1999. "A New Class of Stochastic Volatility Models with Jumps: Theory and Estimation," CIRANO Working Papers 99s-48, CIRANO.

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    1. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 1999. "Range-Based Estimation of Stochastic Volatility Models or Exchange Rate Dynamics are More Interesting Than You Think," Center for Financial Institutions Working Papers 00-28, Wharton School Center for Financial Institutions, University of Pennsylvania.
    2. Göncü, Ahmet & Karahan, Mehmet Oğuz & Kuzubaş, Tolga Umut, 2016. "A comparative goodness-of-fit analysis of distributions of some Lévy processes and Heston model to stock index returns," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 69-83.
    3. Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
    4. John M. Maheu & Thomas McCurdy, 2001. "Nonlinear Features of Realized FX Volatility," CIRANO Working Papers 2001s-42, CIRANO.
    5. Jing-zhi Huang & Liuren Wu, 2004. "Specification Analysis of Option Pricing Models Based on Time-Changed Levy Processes," Econometric Society 2004 North American Winter Meetings 405, Econometric Society.
    6. Luca Benzoni & Pierre Collin-Dufresne & Robert S. Goldstein, 2011. "Can standard preferences explain the prices of out-of-the-money S&P 500 put options?," Working Paper Series WP-2011-11, Federal Reserve Bank of Chicago.
    7. Torben G. Andersen & Luca Benzoni & Jesper Lund, 2001. "An Empirical Investigation of Continuous-Time Equity Return Models," NBER Working Papers 8510, National Bureau of Economic Research, Inc.
    8. Gallant, A. Ronald & Tauchen, George, 2002. "Simulated Score Methods and Indirect Inference for Continuous-time Models," Working Papers 02-09, Duke University, Department of Economics.
    9. Pan, Jun, 2002. "The jump-risk premia implicit in options: evidence from an integrated time-series study," Journal of Financial Economics, Elsevier, vol. 63(1), pages 3-50, January.
    10. Meddahi, N., 2001. "An Eigenfunction Approach for Volatility Modeling," Cahiers de recherche 2001-29, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    11. Kyriakos Chourdakis, 2002. "Continuous Time Regime Switching Models and Applications in Estimating Processes with Stochastic Volatility and Jumps," Working Papers 464, Queen Mary University of London, School of Economics and Finance.
    12. Daal, Elton & Naka, Atsuyuki & Yu, Jung-Suk, 2006. "Volatility Clustering, Leverage Effects, and Jump Dynamics in the US and Emerging Asian Equity Markets," Working Papers 2005-03, University of New Orleans, Department of Economics and Finance.
    13. Rodrigue Oeuvray & Pascal Junod, 2013. "On time scaling of semivariance in a jump-diffusion process," Papers 1311.1122, arXiv.org.
    14. Alexander Tsyplakov, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models (in Russian)," Quantile, Quantile, issue 8, pages 69-122, July.
    15. R. Oeuvray & P. Junod, 2015. "A practical approach to semideviation and its time scaling in a jump-diffusion process," Quantitative Finance, Taylor & Francis Journals, vol. 15(5), pages 809-827, May.
    16. Stefano Galluccio & Yann Le Cam, 2005. "Implied Calibration of Stochastic Volatility Jump Diffusion Models," Finance 0510028, University Library of Munich, Germany.
    17. René Garcia & Eric Ghysels & Eric Renault, 2004. "The Econometrics of Option Pricing," CIRANO Working Papers 2004s-04, CIRANO.
    18. Tyler J. VanderWeele, 2007. "The volatility effects of nontrading for stock market returns," Applied Financial Economics, Taylor & Francis Journals, vol. 17(13), pages 1037-1041.
    19. Uppal, Raman & Das, Sanjiv Ranjan, 2002. "Systemic Risk and International Portfolio Choice," CEPR Discussion Papers 3305, C.E.P.R. Discussion Papers.
    20. Rodríguez Nava Abigail & Francisco Venegas Martínez, 2010. "Efectos del tipo de cambio sobre el déficit público: modelos de simulación Monte Carlo," Contaduría y Administración, Accounting and Management, vol. 55(3), pages 11-40, septiembr.
    21. Choi, Yongok & Jacewitz, Stefan & Park, Joon Y., 2016. "A reexamination of stock return predictability," Journal of Econometrics, Elsevier, vol. 192(1), pages 168-189.
    22. Carl Chiarella & Christina Nikitopoulos-Sklibosios & Erik Schlogl & Hongang Yang, 2016. "Pricing American Options under Regime Switching Using Method of Lines," Research Paper Series 368, Quantitative Finance Research Centre, University of Technology, Sydney.
    23. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2002. "Markov chain Monte Carlo methods for stochastic volatility models," Journal of Econometrics, Elsevier, vol. 108(2), pages 281-316, June.

  15. Gallant, A. Ronald & Tauchen, George, 1997. "Reprojecting Partially Observed Systems with Application to Interest Rate Diffusions," Working Papers 97-09, Duke University, Department of Economics.

    Cited by:

    1. Hideyuki Takamizawa, 2007. "A Simple Measure for Examining the Proxy Problem of the Short-Rate," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(4), pages 341-361, December.
    2. Torben G. Andersen & Luca Benzoni & Jesper Lund, 2001. "An Empirical Investigation of Continuous-Time Equity Return Models," NBER Working Papers 8510, National Bureau of Economic Research, Inc.
    3. Ramos, Sofia B. & Veiga, Helena, 2009. "Risk factors in oil and gas industry returns: international evidence," DES - Working Papers. Statistics and Econometrics. WS ws096920, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Boswijk, H. Peter & Lucas, André & Taylor, Nick, 1998. "A comparison of parametric, semi-nonparametric, adaptive and nonparametric tests," Serie Research Memoranda 0062, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    5. H. Peter Boswijk & Andre Lucas & Nick Taylor, 1999. "A Comparison of Parametric, Semi-nonparametric, Adaptive, and Nonparametric Cointegration Tests," Tinbergen Institute Discussion Papers 99-012/4, Tinbergen Institute.
    6. J. Jimenez & R. Biscay & T. Ozaki, 2005. "Inference Methods for Discretely Observed Continuous-Time Stochastic Volatility Models: A Commented Overview," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 12(2), pages 109-141, June.
    7. Ravi Bansal & A. Ronald Gallant & George Tauchen, 2007. "Rational Pessimism, Rational Exuberance, and Asset Pricing Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 74(4), pages 1005-1033.

  16. Gallant, A. Ronald & Long, Jonathan R., 1996. "Estimating Stochastic Differential Equations Efficiently by Minimum Chi-Square," Working Papers 96-32, Duke University, Department of Economics.

    Cited by:

    1. Liu, Ming & Zhang, Harold H., 1998. "Overparameterization in the seminonparametric density estimation," Economics Letters, Elsevier, vol. 60(1), pages 11-18, July.
    2. Ming Liu & Harold H. Zhang, "undated". "Specification Tests in the Efficient Method of Moments Framework with Application to the Stochastic Volatility Models," Computing in Economics and Finance 1997 93, Society for Computational Economics.
    3. Liu, Ming, 2000. "Modeling long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 99(1), pages 139-171, November.

  17. Victor Fenton & Gallant, A. Ronald, 1996. "Qualitative and Asymptotic Performance of SNP Density Estimators," Working Papers 96-17, Duke University, Department of Economics.

    Cited by:

    1. Pieter J. van der Sluis, 1997. "Post-Sample Prediction Tests for the Efficient Method of Moments," Tinbergen Institute Discussion Papers 97-054/4, Tinbergen Institute.
    2. Cooper, Joseph C., 2002. "Flexible Functional Form Estimation of Willingness to Pay Using Dichotomous Choice Data," Journal of Environmental Economics and Management, Elsevier, vol. 43(2), pages 267-279, March.
    3. Thomas D. Tallarini & Harold H. Zhang, 2005. "External habit and the cyclicality of expected stock returns," Finance and Economics Discussion Series 2005-27, Board of Governors of the Federal Reserve System (U.S.).
    4. Antonio Merlo & Áureo de Paula, 2015. "Identification and estimation of preference distributions when voters are ideological," CeMMAP working papers CWP50/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Gallant, A. Ronald & Hsieh, David & Tauchen, George, 1995. "Estimation of Stochastic Volatility Models with Diagnostics," Working Papers 95-36, Duke University, Department of Economics.
    6. Kimhi, Ayal & Nachlieli, Noga, 1998. "Intergenerational Succession In Israeli Family Farms," 1998 Annual meeting, August 2-5, Salt Lake City, UT 20811, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. Xu, Chang & Katchova, Ani, 2018. "Predicting Soybean Yield with NDVI using a Flexible Fourier Transform Model," 2018 Annual Meeting, February 2-6, 2018, Jacksonville, Florida 266693, Southern Agricultural Economics Association.
    8. Dias, Ronaldo & Garcia, Nancy L., 2007. "Consistent estimator for basis selection based on a proxy of the Kullback-Leibler distance," Journal of Econometrics, Elsevier, vol. 141(1), pages 167-178, November.
    9. Cooper, Joseph, 2009. "Payments under the Average Crop Revenue Program: Implications for Government Costs and Producer Preferences," Agricultural and Resource Economics Review, Cambridge University Press, vol. 38(1), pages 49-64, April.
    10. Cooper, Joseph C. & Delbecq, Benoit A. & Davis, Christopher G., 2012. "Fiscal and Farm Level Consequences of “Shallow Loss” Commodity Support," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124199, Agricultural and Applied Economics Association.
    11. Pieter J. Van Der Sluis, 1998. "Computationally attractive stability tests for the efficient method of moments," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages 203-227.
    12. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Effects on the Riskless Yield Curve with Regime Switching Nelson†Siegel Models," Working Papers 639, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    13. Jose Luis Moraga-Gonzalez & Zsolt Sandor & Matthijs R. Wildenbeest, 2008. "Nonparametric Estimation of the Costs of Non-Sequential Search," Tinbergen Institute Discussion Papers 07-102/1, Tinbergen Institute.
    14. Ming Liu & Harold H. Zhang, "undated". "Specification Tests in the Efficient Method of Moments Framework with Application to the Stochastic Volatility Models," Computing in Economics and Finance 1997 93, Society for Computational Economics.
    15. Per Bjarte Solibakke, 2003. "Validity of discrete-time stochastic volatility models in non-synchronous equity markets," The European Journal of Finance, Taylor & Francis Journals, vol. 9(5), pages 420-448.
    16. Pieter J. van der Sluis, 1998. "Structural Stability Tests with Unknown Breakpoint for the Efficient Method of Moments with Application to Stochastic Volatility Models," Tinbergen Institute Discussion Papers 98-055/4, Tinbergen Institute.
    17. Liesenfeld, Roman & Breitung, Jörg, 1998. "Simulation based methods of moments in empirical finance," Tübinger Diskussionsbeiträge 136, University of Tübingen, School of Business and Economics.
    18. Liesenfeld, Roman & Richard, Jean-Francois, 2003. "Univariate and multivariate stochastic volatility models: estimation and diagnostics," Journal of Empirical Finance, Elsevier, vol. 10(4), pages 505-531, September.
    19. Andersen, Torben G. & Lund, Jesper, 1997. "Estimating continuous-time stochastic volatility models of the short-term interest rate," Journal of Econometrics, Elsevier, vol. 77(2), pages 343-377, April.
    20. Vladimir Yankov, 2014. "In Search of a Risk-free Asset," Finance and Economics Discussion Series 2014-108, Board of Governors of the Federal Reserve System (U.S.).
    21. Ángel León & Javier Mencía & Enrique Sentana, 2007. "Parametric properties of semi-nonparametric distributions, with applications to option valuation," Working Papers 0707, Banco de España.
    22. León, Angel & Moreno, Manuel, 2017. "One-sided performance measures under Gram-Charlier distributions," Journal of Banking & Finance, Elsevier, vol. 74(C), pages 38-50.
    23. Dante Jara, 2004. "Un Modelo Estadístico Flexible para la Estructura Intertemporal de Tasas en Chile," Econometrics 0412010, University Library of Munich, Germany.
    24. Min Zhang & Marie Davidian, 2008. "“Smooth” Semiparametric Regression Analysis for Arbitrarily Censored Time-to-Event Data," Biometrics, The International Biometric Society, vol. 64(2), pages 567-576, June.
    25. Cooper, Joseph C., 2008. "A Revenue-Based Alternative to the Counter-Cyclical Payment Program," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6197, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    26. Ifft, Jennifer & Cooper, Joseph C. & Kuethe, Todd H., 2012. "The Impact of Risk and Farm Program Design on Cash Rents," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124334, Agricultural and Applied Economics Association.
    27. Cooper, Joseph C., 2009. "ACRE: A Revenue-Based Alternative to Price-Based Commodity Payment Programs," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49180, Agricultural and Applied Economics Association.
    28. Mikhail Chernov & A. Ronald Gallant & Eric Ghysels & George Tauchen, 1999. "A New Class of Stochastic Volatility Models with Jumps: Theory and Estimation," CIRANO Working Papers 99s-48, CIRANO.
    29. Coppejans, Mark & Gallant, A. Ronald, 2000. "Cross Validated SNP Density Estimates," Working Papers 00-10, Duke University, Department of Economics.
    30. Javier Mencía & Enrique Sentana, 2018. "Volatility-Related Exchange Traded Assets: An Econometric Investigation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(4), pages 599-614, October.
    31. Guidolin, Massimo & Ono, Sadayuki, 2006. "Are the dynamic linkages between the macroeconomy and asset prices time-varying?," Journal of Economics and Business, Elsevier, vol. 58(5-6), pages 480-518.
    32. Gilleskie, Donna B. & Mroz, Thomas A., 2004. "A flexible approach for estimating the effects of covariates on health expenditures," Journal of Health Economics, Elsevier, vol. 23(2), pages 391-418, March.
    33. Ghysels, Eric & Guay, Alain, 2004. "Testing For Structural Change In The Presence Of Auxiliary Models," Econometric Theory, Cambridge University Press, vol. 20(6), pages 1168-1202, December.
    34. Del Brio, Esther B. & Ñíguez, Trino-Manuel & Perote, Javier, 2008. "Multivariate Gram-Charlier Densities," MPRA Paper 29073, University Library of Munich, Germany.
    35. Foster, Joshua, 2022. "Semi-nonparametric estimation of secret reserve prices in auctions," Economics Letters, Elsevier, vol. 220(C).
    36. Scolas, Sylvie & El Ghouch, Anouar & Legrand, Catherine, 2016. "The SNP representation in mixture cure models with interval-censoring: estimation and goodness-of-fit testing," LIDAM Discussion Papers ISBA 2016049, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    37. Massimo Guidolin & Giovanna Nicodano, 2009. "Small caps in international equity portfolios: the effects of variance risk," Annals of Finance, Springer, vol. 5(1), pages 15-48, January.
    38. Massimo Guidolin & Manuela Pedio, 2019. "Forecasting and Trading Monetary Policy Switching Nelson-Siegel Models," BAFFI CAREFIN Working Papers 19106, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    39. Mikhail Chernov & Eric Ghysels, 1998. "What Data Should Be Used to Price Options?," CIRANO Working Papers 98s-22, CIRANO.
    40. Ronald Gallant, A. & Tauchen, George, 1999. "The relative efficiency of method of moments estimators1," Journal of Econometrics, Elsevier, vol. 92(1), pages 149-172, September.
    41. Massimo Guidolin & Carrie Fangzhou Na, 2007. "The economic and statistical value of forecast combinations under regime switching: an application to predictable U.S. returns," Working Papers 2006-059, Federal Reserve Bank of St. Louis.
    42. Solibakke, Per Bjarte, 2001. "A stochastic volatility model specification with diagnostics for thinly traded equity markets," Journal of Multinational Financial Management, Elsevier, vol. 11(4-5), pages 385-406, December.
    43. Ronald Gallant, A. & Tauchen, George, 2018. "Exact Bayesian moment based inference for the distribution of the small-time movements of an Itô semimartingale," Journal of Econometrics, Elsevier, vol. 205(1), pages 140-155.
    44. Massimo Guidolin & Stuart Hyde, 2008. "Equity portfolio diversification under time-varying predictability and comovements: evidence from Ireland, the US, and the UK," Working Papers 2008-005, Federal Reserve Bank of St. Louis.
    45. Kyoo il Kim, 2006. "Uniform Convergence Rate of the SNP Density Estimator and Testing for Similarity of Two Unknown Densities," Labor Economics Working Papers 22451, East Asian Bureau of Economic Research.
    46. Teruko Takada, 2001. "Nonparametric density estimation: A comparative study," Economics Bulletin, AccessEcon, vol. 3(16), pages 1-10.

  18. Gallant, A. Ronald & Hsieh, David & Tauchen, George, 1995. "Estimation of Stochastic Volatility Models with Diagnostics," Working Papers 95-36, Duke University, Department of Economics.

    Cited by:

    1. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 1999. "Range-Based Estimation of Stochastic Volatility Models or Exchange Rate Dynamics are More Interesting Than You Think," Center for Financial Institutions Working Papers 00-28, Wharton School Center for Financial Institutions, University of Pennsylvania.
    2. Kanaya, Shin & Kristensen, Dennis, 2016. "Estimation Of Stochastic Volatility Models By Nonparametric Filtering," Econometric Theory, Cambridge University Press, vol. 32(4), pages 861-916, August.
    3. Mark J. Jensen & John M. Maheu, 2008. "Bayesian semiparametric stochastic volatility modeling," FRB Atlanta Working Paper 2008-15, Federal Reserve Bank of Atlanta.
    4. Arvanitis Stelios & Demos Antonis, 2018. "On the Validity of Edgeworth Expansions and Moment Approximations for Three Indirect Inference Estimators," Journal of Econometric Methods, De Gruyter, vol. 7(1), pages 1-38, January.
    5. Sofia Anyfantaki & Antonis Demos, 2012. "Estimation and Properties of a Time-Varying EGARCH(1,1) in Mean Model," DEOS Working Papers 1228, Athens University of Economics and Business.
    6. Paolo Girardello & Orietta Nicolis & Giovanni Tondini, 2003. "Comparing Conditional Variance Models: Theory and Empirical Evidence," Multinational Finance Journal, Multinational Finance Journal, vol. 7(3-4), pages 177-206, September.
    7. Christos Floros & Konstantinos Gkillas & Christoforos Konstantatos & Athanasios Tsagkanos, 2020. "Realized Measures to Explain Volatility Changes over Time," JRFM, MDPI, vol. 13(6), pages 1-19, June.
    8. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    9. Andersen, Torben G & Bollerslev, Tim, 1997. "Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long-Run in High Frequency Returns," Journal of Finance, American Finance Association, vol. 52(3), pages 975-1005, July.
    10. Lombardi, Marco J. & Calzolari, Giorgio, 2009. "Indirect estimation of [alpha]-stable stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2298-2308, April.
    11. Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
    12. Zhang, Xibin & King, Maxwell L., 2008. "Box-Cox stochastic volatility models with heavy-tails and correlated errors," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 549-566, June.
    13. Lux, Thomas & Morales-Arias, Leonardo, 2010. "Relative forecasting performance of volatility models: Monte Carlo evidence," Kiel Working Papers 1582, Kiel Institute for the World Economy (IfW Kiel).
    14. Bauwens, Luc & Veredas, David, 2004. "The stochastic conditional duration model: a latent variable model for the analysis of financial durations," Journal of Econometrics, Elsevier, vol. 119(2), pages 381-412, April.
    15. Font, Begoña, 1998. "Modelización de series temporales financieras. Una recopilación," DES - Documentos de Trabajo. Estadística y Econometría. DS 3664, Universidad Carlos III de Madrid. Departamento de Estadística.
    16. Charilaos Mertzanis, 2013. "Risk Management Challenges after the Financial Crisis," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 42(3), pages 285-320, November.
    17. Antonis Demos, 2023. "Estimation of Asymmetric Stochastic Volatility in Mean Models," DEOS Working Papers 2309, Athens University of Economics and Business.
    18. Wang, Joanna J.J. & Chan, Jennifer S.K. & Choy, S.T. Boris, 2011. "Stochastic volatility models with leverage and heavy-tailed distributions: A Bayesian approach using scale mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 852-862, January.
    19. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range‐Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, June.
    20. Hafner, C. & Preminger, A., 2010. "Deciding between GARCH and Stochastic Volatility via Strong Decision Rules," LIDAM Reprints ISBA 2010032, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    21. Antonis Demos, 2002. "Moments and dynamic structure of a time-varying parameter stochastic volatility in mean model," Econometrics Journal, Royal Economic Society, vol. 5(2), pages 345-357, June.
    22. Tsiotas, Georgios, 2012. "On generalised asymmetric stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 151-172, January.
    23. Vo, Minh, 2011. "Oil and stock market volatility: A multivariate stochastic volatility perspective," Energy Economics, Elsevier, vol. 33(5), pages 956-965, September.
    24. Jonathan Wright, 2002. "Log-Periodogram Estimation Of Long Memory Volatility Dependencies With Conditionally Heavy Tailed Returns," Econometric Reviews, Taylor & Francis Journals, vol. 21(4), pages 397-417.
    25. In Kim & In-Seok Baek & Jaesun Noh & Sol Kim, 2007. "The role of stochastic volatility and return jumps: reproducing volatility and higher moments in the KOSPI 200 returns dynamics," Review of Quantitative Finance and Accounting, Springer, vol. 29(1), pages 69-110, July.
    26. Liu, Ming & Zhang, Harold H., 1998. "Overparameterization in the seminonparametric density estimation," Economics Letters, Elsevier, vol. 60(1), pages 11-18, July.
    27. Hautsch, Nikolaus & Ou, Yangguoyi, 2008. "Discrete-time stochastic volatility models and MCMC-based statistical inference," SFB 649 Discussion Papers 2008-063, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    28. Eduardo Rossi & Paolo Santucci de Magistris, 2018. "Indirect inference with time series observed with error," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(6), pages 874-897, September.
    29. Torben G. Andersen & Luca Benzoni & Jesper Lund, 2001. "An Empirical Investigation of Continuous-Time Equity Return Models," NBER Working Papers 8510, National Bureau of Economic Research, Inc.
    30. Elise COUDIN, Jean-Marie DUFOUR, 2008. "Hodges-Lehmann Sign-based Estimators and Generalized Confidence Distributions in Linear Median Regressions with Moment-free Heterogenous Errors and Dependence of Unknown Form," Working Papers 2008-33, Center for Research in Economics and Statistics.
    31. Pyun, Chong Soo & Lee, Sa Young & Nam, Kiseok, 2000. "Volatility and information flows in emerging equity market: A case of the Korean Stock Exchange," International Review of Financial Analysis, Elsevier, vol. 9(4), pages 405-420.
    32. Ming Liu & Harold H. Zhang, "undated". "Specification Tests in the Efficient Method of Moments Framework with Application to the Stochastic Volatility Models," Computing in Economics and Finance 1997 93, Society for Computational Economics.
    33. Per Bjarte Solibakke, 2003. "Validity of discrete-time stochastic volatility models in non-synchronous equity markets," The European Journal of Finance, Taylor & Francis Journals, vol. 9(5), pages 420-448.
    34. G Sandmann & Siem Jan Koopman, 1996. "Maximum Likelihood Estimation of Stochastic Volatility Models," FMG Discussion Papers dp248, Financial Markets Group.
    35. María-Dolores, Ramón & Vázquez Pérez, Jesús, 2005. "How Does the New Keynesian Monetary Model Fit in the U.S. and the Eurozone? an Indirect Inference Approach," DFAEII Working Papers 1988-088X, University of the Basque Country - Department of Foundations of Economic Analysis II.
    36. Liesenfeld, Roman & Breitung, Jörg, 1998. "Simulation based methods of moments in empirical finance," Tübinger Diskussionsbeiträge 136, University of Tübingen, School of Business and Economics.
    37. Eddie Chi-man Hui & Xian Zheng, 2012. "The dynamic correlation and volatility of real estate price and rental: an application of MSV model," Applied Economics, Taylor & Francis Journals, vol. 44(23), pages 2985-2995, August.
    38. Senteney, David L. & Bazaz, Mohammad S. & Senteney, Michael H., 2016. "Cross-market information transfers of ADR firms: An investigation of emerging market economies," Research in International Business and Finance, Elsevier, vol. 37(C), pages 655-677.
    39. Berument, Hakan & Yalcin, Yeliz & Yildirim, Julide, 2009. "The effect of inflation uncertainty on inflation: Stochastic volatility in mean model within a dynamic framework," Economic Modelling, Elsevier, vol. 26(6), pages 1201-1207, November.
    40. Gallant, A. Ronald & Tauchen, George, 2002. "Simulated Score Methods and Indirect Inference for Continuous-time Models," Working Papers 02-09, Duke University, Department of Economics.
    41. Marcel Aloy & Gilles Dufrenot & Charles Lai-Tong & Anne Peguin-Feissolle, 2012. "A Smooth Transition Long-Memory Model," Working Papers halshs-00793680, HAL.
    42. Chen, Bin & Hong, Yongmiao, 2012. "Testing For The Markov Property In Time Series," Econometric Theory, Cambridge University Press, vol. 28(1), pages 130-178, February.
    43. Benjamin Cheng & Christina Nikitopoulos-Sklibosios & Erik Schlogl, 2016. "Empirical Pricing Performance in Long-Dated Crude Oil Derivatives: Do Models with Stochastic Interest Rates Matter?," Research Paper Series 367, Quantitative Finance Research Centre, University of Technology, Sydney.
    44. Tauchen, George, 1997. "The Objective Function of Simulation Estimators Near the Boundary of the Unstable Region of the Parameter Space," Working Papers 97-14, Duke University, Department of Economics.
    45. Liesenfeld, Roman & Richard, Jean-Francois, 2003. "Univariate and multivariate stochastic volatility models: estimation and diagnostics," Journal of Empirical Finance, Elsevier, vol. 10(4), pages 505-531, September.
    46. Ramón María-Dolores & Jesús Vázquez, 2008. "Term structure and the estimated monetary policy rule in the Eurozone," Spanish Economic Review, Springer;Spanish Economic Association, vol. 10(4), pages 251-277, December.
    47. Neil Shephard & Torben G. Andersen, 2008. "Stochastic Volatility: Origins and Overview," OFRC Working Papers Series 2008fe23, Oxford Financial Research Centre.
    48. Renner, Ch. & Peinke, J. & Friedrich, R., 2001. "Evidence of Markov properties of high frequency exchange rate data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 298(3), pages 499-520.
    49. Oliver de Groot, 2014. "Solving asset pricing models with stochastic volatility," Finance and Economics Discussion Series 2014-71, Board of Governors of the Federal Reserve System (U.S.).
    50. Ramón Maria-Dolores & Jesus Vazquez, 2006. "The relative importance of Term Spread, Policy Inertia and Persistent Monetary Policy Shocks in Monetary Policy Rules," Computing in Economics and Finance 2006 6, Society for Computational Economics.
    51. Dufour, Jean-Marie & Valéry, Pascale, 2009. "Exact and asymptotic tests for possibly non-regular hypotheses on stochastic volatility models," Journal of Econometrics, Elsevier, vol. 150(2), pages 193-206, June.
    52. Jung-Bin Su, 2014. "How to mitigate the impact of inappropriate distributional settings when the parametric value-at-risk approach is used," Quantitative Finance, Taylor & Francis Journals, vol. 14(2), pages 305-325, February.
    53. Frédéric Karamé, 2018. "A new particle filtering approach to estimate stochastic volatility models with Markov-switching," Post-Print hal-02296093, HAL.
    54. María-Dolores, Ramón & Vázquez Pérez, Jesús, 2008. "Term Structure and the Estimated Monetary Policy Rule in the Eurozone," DFAEII Working Papers 1988-088X, University of the Basque Country - Department of Foundations of Economic Analysis II.
    55. Jacquier, Eric & Polson, Nicholas G. & Rossi, P.E.Peter E., 2004. "Bayesian analysis of stochastic volatility models with fat-tails and correlated errors," Journal of Econometrics, Elsevier, vol. 122(1), pages 185-212, September.
    56. Mikhail Chernov & A. Ronald Gallant & Eric Ghysels & George Tauchen, 2002. "Alternative Models for Stock Price Dynamics," CIRANO Working Papers 2002s-58, CIRANO.
    57. David T. Frazier & Eric Renault, 2019. "Indirect Inference: Which Moments to Match?," Econometrics, MDPI, vol. 7(1), pages 1-17, March.
    58. Benjamin Tin Chun Cheng, 2017. "Pricing and Hedging of Long-Dated Commodity Derivatives," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2017, January-A.
    59. G. Dhaene, 2004. "Indirect Inference for Stochastic Volatility Models via the Log-Squared Observations," Review of Business and Economic Literature, KU Leuven, Faculty of Economics and Business (FEB), Review of Business and Economic Literature, vol. 0(3), pages 421-440.
    60. Fulvia Focker & Umberto Triacca, 2006. "A new proxy of the average volatility of a basket of returns: A Monte Carlo study," Economics Bulletin, AccessEcon, vol. 3(15), pages 1-14.
    61. Mauro Bernardi & Leopoldo Catania, 2016. "Comparison of Value-at-Risk models using the MCS approach," Computational Statistics, Springer, vol. 31(2), pages 579-608, June.
    62. Carmen Broto & Esther Ruiz, 2004. "Estimation methods for stochastic volatility models: a survey," Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 613-649, December.
    63. Juan Hoyo & Guillermo Llorente & Carlos Rivero, 2020. "A Testing Procedure for Constant Parameters in Stochastic Volatility Models," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 163-186, June.
    64. Grammig, Joachim & Schaub, Eva-Maria, 2014. "Give me strong moments and time - Combining GMM and SMM to estimate long-run risk asset pricing models," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100607, Verein für Socialpolitik / German Economic Association.
    65. Denis Heng-Yan Leung & Dylan S. Small & Jing Qin & Min Zhu, 2013. "Shrinkage Empirical Likelihood Estimator in Longitudinal Analysis with Time-Dependent Covariates—Application to Modeling the Health of Filipino Children," Biometrics, The International Biometric Society, vol. 69(3), pages 624-632, September.
    66. M. Berument & Yeliz Yalcin & Julide Yildirim, 2011. "The inflation and inflation uncertainty relationship for Turkey: a dynamic framework," Empirical Economics, Springer, vol. 41(2), pages 293-309, October.
    67. Roland Langrock & Théo Michelot & Alexander Sohn & Thomas Kneib, 2015. "Semiparametric stochastic volatility modelling using penalized splines," Computational Statistics, Springer, vol. 30(2), pages 517-537, June.
    68. Ludvigson, Sydney C., 2013. "Advances in Consumption-Based Asset Pricing: Empirical Tests," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 799-906, Elsevier.
    69. van der Sluis Pieter J., 1997. "EmmPack 1.01: C/C++ Code for Use with Ox for Estimation of Univariate Stochastic Volatility Models with the Efficient Method of Moments," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(3), pages 1-20, October.
    70. Kim Christensen & Martin Thyrsgaard & Bezirgen Veliyev, 2018. "The realized empirical distribution function of stochastic variance with application to goodness-of-fit testing," CREATES Research Papers 2018-19, Department of Economics and Business Economics, Aarhus University.
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    2. Andersen, Torben G. & Chung, Hyung-Jin & Sorensen, Bent E., 1999. "Efficient method of moments estimation of a stochastic volatility model: A Monte Carlo study," Journal of Econometrics, Elsevier, vol. 91(1), pages 61-87, July.

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    36. Carl Chiarella & Hing Hung & Thuy-Duong To, 2005. "The Volatility Structure of the Fixed Income Market under the HJM Framework: A Nonlinear Filtering Approach," Research Paper Series 151, Quantitative Finance Research Centre, University of Technology, Sydney.
    37. Carmen Broto & Esther Ruiz, 2004. "Estimation methods for stochastic volatility models: a survey," Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 613-649, December.
    38. Li Chen & Guang Zhang, 2021. "Hermite Polynomial-based Valuation of American Options with General Jump-Diffusion Processes," Papers 2104.11870, arXiv.org.
    39. Chernov, Mikhail, 2003. "Empirical reverse engineering of the pricing kernel," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 329-364.
    40. James Doran & Ehud Ronn, 2005. "The bias in Black-Scholes/Black implied volatility: An analysis of equity and energy markets," Review of Derivatives Research, Springer, vol. 8(3), pages 177-198, December.
    41. Doran, James S. & Ronn, Ehud I., 2008. "Computing the market price of volatility risk in the energy commodity markets," Journal of Banking & Finance, Elsevier, vol. 32(12), pages 2541-2552, December.
    42. Lars Stentoft, 2008. "Option Pricing using Realized Volatility," CREATES Research Papers 2008-13, Department of Economics and Business Economics, Aarhus University.
    43. Seungmoon Choi, 2015. "Maximum Likelihood Estimation of Continuous-Time Diffusion Models for Korean Short-Term Interest Rates," Economic Analysis (Quarterly), Economic Research Institute, Bank of Korea, vol. 21(4), pages 28-58, December.
    44. Mikhail Chernov & A. Ronald Gallant & Eric Ghysels & George Tauchen, 1999. "A New Class of Stochastic Volatility Models with Jumps: Theory and Estimation," CIRANO Working Papers 99s-48, CIRANO.
    45. Monfort, A. & Renne, J.-P. & Roussellet, G., 2014. "A Quadratic Kalman Filter," Working papers 486, Banque de France.
    46. Turan G. Bali, 2007. "An Extreme Value Approach to Estimating Interest-Rate Volatility: Pricing Implications for Interest-Rate Options," Management Science, INFORMS, vol. 53(2), pages 323-339, February.
    47. Kawakatsu, Hiroyuki, 2007. "Specification and estimation of discrete time quadratic stochastic volatility models," Journal of Empirical Finance, Elsevier, vol. 14(3), pages 424-442, June.
    48. Chen, Bin & Hong, Yongmiao, 2011. "Generalized spectral testing for multivariate continuous-time models," Journal of Econometrics, Elsevier, vol. 164(2), pages 268-293, October.
    49. Ghysels, Eric & Guay, Alain, 2004. "Testing For Structural Change In The Presence Of Auxiliary Models," Econometric Theory, Cambridge University Press, vol. 20(6), pages 1168-1202, December.
    50. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    51. J. Jimenez & R. Biscay & T. Ozaki, 2005. "Inference Methods for Discretely Observed Continuous-Time Stochastic Volatility Models: A Commented Overview," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 12(2), pages 109-141, June.
    52. Ravi Bansal & A. Ronald Gallant & George Tauchen, 2007. "Rational Pessimism, Rational Exuberance, and Asset Pricing Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 74(4), pages 1005-1033.
    53. Mardi Dungey & Vance L Martin & Adrian R Pagan, 2000. "A multivariate latent factor decomposition of international bond yield spreads," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 697-715.
    54. Veiga, Helena, 2006. "A two factor long memory stochastic volatility model," DES - Working Papers. Statistics and Econometrics. WS ws061303, Universidad Carlos III de Madrid. Departamento de Estadística.
    55. Ronald Gallant, A. & Tauchen, George, 1999. "The relative efficiency of method of moments estimators1," Journal of Econometrics, Elsevier, vol. 92(1), pages 149-172, September.
    56. Robert Engle, 2002. "New frontiers for arch models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 425-446.
    57. A. Ronald Gallant & Mohammad Jahan-Parvar & Hening Liu, 2015. "Measuring Ambiguity Aversion," Finance and Economics Discussion Series 2015-105, Board of Governors of the Federal Reserve System (U.S.).
    58. George J. Jiang & Pieter J. van der Sluis, 1998. "Pricing Stock Options under Stochastic Volatility and Stochastic Interest Rates with Efficient Method of Moments Estimation," Tinbergen Institute Discussion Papers 98-067/4, Tinbergen Institute.
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    60. Suresh M. Sundaresan, 2000. "Continuous‐Time Methods in Finance: A Review and an Assessment," Journal of Finance, American Finance Association, vol. 55(4), pages 1569-1622, August.
    61. Stentoft, Lars, 2011. "American option pricing with discrete and continuous time models: An empirical comparison," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 880-902.
    62. Liu, Ming, 2000. "Modeling long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 99(1), pages 139-171, November.
    63. Caterina Schiavoni & Siem Jan Koopman & Franz Palm & Stephan Smeekes & Jan van den Brakel, 2021. "Time-varying state correlations in state space models and their estimation via indirect inference," Tinbergen Institute Discussion Papers 21-020/III, Tinbergen Institute.
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Articles

  1. Aldrich, Eric M. & Fernández-Villaverde, Jesús & Ronald Gallant, A. & Rubio-Ramírez, Juan F., 2011. "Tapping the supercomputer under your desk: Solving dynamic equilibrium models with graphics processors," Journal of Economic Dynamics and Control, Elsevier, vol. 35(3), pages 386-393, March.
    See citations under working paper version above.
  2. Gallant, A. Ronald & McCulloch, Robert E., 2009. "On the Determination of General Scientific Models With Application to Asset Pricing," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 117-131.

    Cited by:

    1. Ron Gallant & Raffaella Giacomini & Giuseppe Ragusa, 2013. "Generalized method of moments with latent variables," CeMMAP working papers CWP50/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Ramis Khabibullin & Sergei Seleznev, 2022. "Fast Estimation of Bayesian State Space Models Using Amortized Simulation-Based Inference," Papers 2210.07154, arXiv.org.
    3. Mohammad R. Jahan-Parvar & Xuan Liu & Philip Rothman, 2013. "Equity Returns and Business Cycles in Small Open Economies," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(6), pages 1117-1146, September.
    4. Christian Matthes, 2015. "Figuring Out the Fed—Beliefs about Policymakers and Gains from Transparency," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(1), pages 1-29, February.
    5. Gallant, A. Ronald & Giacomini, Raffaella & Ragusa, Giuseppe, 2017. "Bayesian estimation of state space models using moment conditions," Journal of Econometrics, Elsevier, vol. 201(2), pages 198-211.
    6. A. Ronald Gallant & Mohammad Jahan-Parvar & Hening Liu, 2015. "Measuring Ambiguity Aversion," Finance and Economics Discussion Series 2015-105, Board of Governors of the Federal Reserve System (U.S.).
    7. Man Chon Iao & Yatheesan J. Selvakumar, 2024. "Estimating HANK with Micro Data," Papers 2402.11379, arXiv.org.

  3. Cheng, Ai-ru (Meg) & Gallant, A. Ronald & Ji, Chuanshu & Lee, Beom S., 2008. "A Gaussian approximation scheme for computation of option prices in stochastic volatility models," Journal of Econometrics, Elsevier, vol. 146(1), pages 44-58, September.

    Cited by:

    1. Xinyu WU & Hailin ZHOU, 2016. "GARCH DIFFUSION MODEL, iVIX, AND VOLATILITY RISK PREMIUM," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(1), pages 327-342.

  4. Ravi Bansal & A. Ronald Gallant & George Tauchen, 2007. "Rational Pessimism, Rational Exuberance, and Asset Pricing Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 74(4), pages 1005-1033.
    See citations under working paper version above.
  5. Ahn, Dong-Hyun & Dittmar, Robert F. & Gallant, A. Ronald & Gao, Bin, 2003. "Purebred or hybrid?: Reproducing the volatility in term structure dynamics," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 147-180.

    Cited by:

    1. Breach, Tomas & D’Amico, Stefania & Orphanides, Athanasios, 2020. "The term structure and inflation uncertainty," Journal of Financial Economics, Elsevier, vol. 138(2), pages 388-414.
    2. Gourieroux, Christian & Sufana, Razvan, 2011. "Discrete time Wishart term structure models," Journal of Economic Dynamics and Control, Elsevier, vol. 35(6), pages 815-824, June.
    3. Qiang Dai & Kenneth Singleton, 2003. "Term Structure Dynamics in Theory and Reality," The Review of Financial Studies, Society for Financial Studies, vol. 16(3), pages 631-678, July.
    4. Nour Meddahi, 2003. "ARMA representation of integrated and realized variances," Econometrics Journal, Royal Economic Society, vol. 6(2), pages 335-356, December.
    5. Perignon, Christophe & Smith, Daniel R., 2007. "Yield-factor volatility models," Journal of Banking & Finance, Elsevier, vol. 31(10), pages 3125-3144, October.
    6. Torben G. Andersen & Luca Benzoni, 2007. "Do Bonds Span Volatility Risk in the U.S. Treasury Market? A Specification test for Affine Term Structure Models," NBER Working Papers 12962, National Bureau of Economic Research, Inc.
    7. Meddahi, N., 2001. "An Eigenfunction Approach for Volatility Modeling," Cahiers de recherche 2001-29, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    8. Collin-Dufresne, Pierre & Goldstein, Robert S. & Jones, Christopher S., 2009. "Can interest rate volatility be extracted from the cross section of bond yields?," Journal of Financial Economics, Elsevier, vol. 94(1), pages 47-66, October.
    9. Yixiao Jiang, 2020. "A Hausman Test for Partially Linear Models with an Application to Implied Volatility Surface," JRFM, MDPI, vol. 13(11), pages 1-12, November.
    10. Peter Feldhütter & Christian Heyerdahl-Larsen & Philipp Illeditsch, 2018. "Risk Premia and Volatilities in a Nonlinear Term Structure Model [Quadratic term structure models: theory and evidence]," Review of Finance, European Finance Association, vol. 22(1), pages 337-380.
    11. Sergei Levendorskii, 2002. "Pseudo-diffusions and Quadratic term structure models," Papers cond-mat/0212249, arXiv.org, revised Apr 2004.
    12. Bates, David S., 2003. "Empirical option pricing: a retrospection," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 387-404.

  6. Chernov, Mikhail & Ronald Gallant, A. & Ghysels, Eric & Tauchen, George, 2003. "Alternative models for stock price dynamics," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 225-257.
    See citations under working paper version above.
  7. Durham, Garland B & Gallant, A Ronald, 2002. "Numerical Techniques for Maximum Likelihood Estimation of Continuous-Time Diffusion Processes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 297-316, July.

    Cited by:

    1. Golightly Andrew & Wilkinson Darren J., 2015. "Bayesian inference for Markov jump processes with informative observations," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 14(2), pages 169-188, April.
    2. Jun Yu & Peter C. B. Phillips, 2001. "A Gaussian approach for continuous time models of the short-term interest rate," Econometrics Journal, Royal Economic Society, vol. 4(2), pages 1-3.
    3. Umberto Picchini & Andrea De Gaetano & Susanne Ditlevsen, 2010. "Stochastic Differential Mixed‐Effects Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(1), pages 67-90, March.
    4. Jun Yu & Zhenlin Yang & Xibin Zhang, 2002. "A Class of Nonlinear Stochastic Volatility Models and Its Implications on Pricing Currency Options," Monash Econometrics and Business Statistics Working Papers 17/02, Monash University, Department of Econometrics and Business Statistics.
    5. Lubrano, Michel, 2004. "Modélisation bayésienne non linéaire du taux d’intérêt de court terme américain : l’aide des outils non paramétriques," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(2), pages 465-499, Juin-Sept.
    6. Nina Munkholt Jakobsen & Michael Sørensen, 2015. "Efficient Estimation for Diffusions Sampled at High Frequency Over a Fixed Time Interval," CREATES Research Papers 2015-33, Department of Economics and Business Economics, Aarhus University.
    7. Kyoung-Kuk Kim & Sojung Kim, 2016. "Simulation of Tempered Stable Lévy Bridges and Its Applications," Operations Research, INFORMS, vol. 64(2), pages 495-509, April.
    8. S. Bordignon & D. Raggi, 2008. "Volatility, Jumps and Predictability of Returns: a Sequential Analysis," Working Papers 636, Dipartimento Scienze Economiche, Universita' di Bologna.
    9. Eric Ghysels & Jean-Pierre Florens & Mikhail Chernov & Marine Carrasco, 2003. "Efficient Estimation of Jump Diffusions and General Dynamic Models with a Continuum of Moment Conditions," CIRANO Working Papers 2003s-02, CIRANO.
    10. Sun, Libo & Lee, Chihoon & Hoeting, Jennifer A., 2015. "A penalized simulated maximum likelihood approach in parameter estimation for stochastic differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 84(C), pages 54-67.
    11. A. Hurn & J. Jeisman & K. Lindsay, 2007. "Teaching an Old Dog New Tricks: Improved Estimation of the Parameters of Stochastic Differential Equations by Numerical Solution of the Fokker-Planck Equation," NCER Working Paper Series 9, National Centre for Econometric Research.
    12. Kalogeropoulos, Konstantinos & Roberts, Gareth O. & Dellaportas, Petros, 2010. "Inference for stochastic volatility models using time change transformations," LSE Research Online Documents on Economics 31421, London School of Economics and Political Science, LSE Library.
    13. Siem Jan Koopman & Rutger Lit & Thuy Minh Nguyen, 2012. "Fast Efficient Importance Sampling by State Space Methods," Tinbergen Institute Discussion Papers 12-008/4, Tinbergen Institute, revised 16 Oct 2014.
    14. Flávio B. Gonçalves & Gareth O. Roberts, 2014. "Exact Simulation Problems for Jump-Diffusions," Methodology and Computing in Applied Probability, Springer, vol. 16(4), pages 907-930, December.
    15. Choi, Seungmoon, 2013. "Closed-form likelihood expansions for multivariate time-inhomogeneous diffusions," Journal of Econometrics, Elsevier, vol. 174(2), pages 45-65.
    16. Ruijun Bu & Ludovic Giet & Kaddour Hadri & Michel Lubrano, 2009. "Modeling Multivariate Interest Rates using Time-Varying Copulas and Reducible Stochastic Differential Equations," Working Papers halshs-00408014, HAL.
    17. Hao Zhou, 2003. "Itô conditional moment generator and the estimation of short rate processes," Finance and Economics Discussion Series 2003-32, Board of Governors of the Federal Reserve System (U.S.).
    18. Giuliano De Rossi, 2010. "Maximum Likelihood Estimation of the Cox–Ingersoll–Ross Model Using Particle Filters," Computational Economics, Springer;Society for Computational Economics, vol. 36(1), pages 1-16, June.
    19. Paul Fearnhead & Omiros Papaspiliopoulos & Gareth O. Roberts, 2008. "Particle filters for partially observed diffusions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(4), pages 755-777, September.
    20. Peter C.B. Phillips & Jun Yu, 2007. "Maximum Likelihood and Gaussian Estimation of Continuous Time Models in Finance," Cowles Foundation Discussion Papers 1597, Cowles Foundation for Research in Economics, Yale University.
    21. Pascal St-Amour, 2005. "Direct Preference Wealth in Aggregate Household Portfolios," FAME Research Paper Series rp136, International Center for Financial Asset Management and Engineering.
    22. Kalogeropoulos, Konstantinos & Dellaportas, Petros & Roberts, Gareth O., 2007. "Likelihood-based inference for correlated diffusions," MPRA Paper 5696, University Library of Munich, Germany.
    23. Ruijun Bu & Jie Cheng & Kaddour Hadri, 2014. "Reducible Diffusions with Time-Varying Transformations with Application to Short-Term Interest Rates," Economics Working Papers 14-01, Queen's Management School, Queen's University Belfast.
    24. Mengheng Li & Siem Jan (S.J.) Koopman, 2018. "Unobserved Components with Stochastic Volatility in U.S. Inflation: Estimation and Signal Extraction," Tinbergen Institute Discussion Papers 18-027/III, Tinbergen Institute.
    25. Aleksandar Mijatovic & Paul Schneider, 2009. "Empirical asset pricing with nonlinear risk premia," Papers 0911.0928, arXiv.org.
    26. Song, Xinyu & Wang, Yazhen, 2020. "GARCH quasi-likelihood ratios for SV model and the diffusion limit," Statistics & Probability Letters, Elsevier, vol. 165(C).
    27. Kalogeropoulos, Konstantinos, 2007. "Likelihood-based inference for a class of multivariate diffusions with unobserved paths," LSE Research Online Documents on Economics 31423, London School of Economics and Political Science, LSE Library.
    28. Dennis Kristensen & Young Jun Lee & Antonio Mele, 2023. "Closed-form approximations of moments and densities of continuous-time Markov models," Papers 2308.09009, arXiv.org.
    29. Richard Anton Braun & Huiyu Li & John Stachurski, 2009. "Computing Densities: A Conditional Monte Carlo Estimator," CARF F-Series CARF-F-181, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    30. Neil Shephard & Torben G. Andersen, 2008. "Stochastic Volatility: Origins and Overview," OFRC Working Papers Series 2008fe23, Oxford Financial Research Centre.
    31. Federico M. Bandi & Peter C.B. Phillips, 2005. "A Simple Approach to the Parametric Estimation of Potentially Nonstationary Diffusions," Cowles Foundation Discussion Papers 1522, Cowles Foundation for Research in Economics, Yale University.
    32. Choi, Hwan-sik & Jeong, Minsoo & Park, Joon Y., 2014. "An asymptotic analysis of likelihood-based diffusion model selection using high frequency data," Journal of Econometrics, Elsevier, vol. 178(P3), pages 539-557.
    33. Paul Fearnhead & Vasilieos Giagos & Chris Sherlock, 2014. "Inference for reaction networks using the linear noise approximation," Biometrics, The International Biometric Society, vol. 70(2), pages 457-466, June.
    34. Bakshi, Gurdip & Ju, Nengjiu & Ou-Yang, Hui, 2006. "Estimation of continuous-time models with an application to equity volatility dynamics," Journal of Financial Economics, Elsevier, vol. 82(1), pages 227-249, October.
    35. Czellar, Veronika & Karolyi, G. Andrew & Ronchetti, Elvezio, 2005. "Indirect Robust Estimation of the Short-term Interest Rate Process," Working Paper Series 2005-4, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    36. Choi, Hwan-sik, 2016. "Information theory for maximum likelihood estimation of diffusion models," Journal of Econometrics, Elsevier, vol. 191(1), pages 110-128.
    37. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
    38. Phenyo E. Lekone & Bärbel F. Finkenstädt, 2006. "Statistical Inference in a Stochastic Epidemic SEIR Model with Control Intervention: Ebola as a Case Study," Biometrics, The International Biometric Society, vol. 62(4), pages 1170-1177, December.
    39. Pastorello, S. & Rossi, E., 2010. "Efficient importance sampling maximum likelihood estimation of stochastic differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2753-2762, November.
    40. A. Golightly & D. J. Wilkinson, 2005. "Bayesian Inference for Stochastic Kinetic Models Using a Diffusion Approximation," Biometrics, The International Biometric Society, vol. 61(3), pages 781-788, September.
    41. Peter C. B. Phillips & Jun Yu, 2009. "Simulation-Based Estimation of Contingent-Claims Prices," The Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3669-3705, September.
    42. Yuan Shen & Dan Cornford & Manfred Opper & Cedric Archambeau, 2012. "Variational Markov chain Monte Carlo for Bayesian smoothing of non-linear diffusions," Computational Statistics, Springer, vol. 27(1), pages 149-176, March.
    43. Kleppe, Tore Selland & Yu, Jun & Skaug, Hans J., 2014. "Maximum likelihood estimation of partially observed diffusion models," Journal of Econometrics, Elsevier, vol. 180(1), pages 73-80.
    44. Ming‐Chi Chen & Chia‐Chien Chang & Shih‐Kuei Lin & So‐De Shyu, 2010. "Estimation of Housing Price Jump Risks and Their Impact on the Valuation of Mortgage Insurance Contracts," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 77(2), pages 399-422, June.
    45. Varughese, Melvin M., 2013. "Parameter estimation for multivariate diffusion systems," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 417-428.
    46. Zhao-Hua Lu & Sy-Miin Chow & Nilam Ram & Pamela M. Cole, 2019. "Zero-Inflated Regime-Switching Stochastic Differential Equation Models for Highly Unbalanced Multivariate, Multi-Subject Time-Series Data," Psychometrika, Springer;The Psychometric Society, vol. 84(2), pages 611-645, June.
    47. Lars Josef Hook & Erik Lindstrom, 2015. "Efficient Computation of the Quasi Likelihood function for Discretely Observed Diffusion Processes," Papers 1509.07751, arXiv.org.
    48. Beskos, Alexandros & Kalogeropoulos, Konstantinos & Pazos, Erik, 2013. "Advanced MCMC methods for sampling on diffusion pathspace," Stochastic Processes and their Applications, Elsevier, vol. 123(4), pages 1415-1453.
    49. Theodore Simos & Mike Tsionas, 2018. "Bayesian inference of the fractional Ornstein–Uhlenbeck process under a flow sampling scheme," Computational Statistics, Springer, vol. 33(4), pages 1687-1713, December.
    50. Pascal St-Amour, 2005. "Direct Preference for Wealth in Aggregate Household Portfolio," Cahiers de Recherches Economiques du Département d'économie 05.04, Université de Lausanne, Faculté des HEC, Département d’économie.
    51. Cheng, Ai-ru (Meg) & Gallant, A. Ronald & Ji, Chuanshu & Lee, Beom S., 2008. "A Gaussian approximation scheme for computation of option prices in stochastic volatility models," Journal of Econometrics, Elsevier, vol. 146(1), pages 44-58, September.
    52. C.S. Bos & S.J. Koopman & M. Ooms, 2007. "Long Memory Modelling of Inflation with Stochastic Variance and Structural Breaks," Tinbergen Institute Discussion Papers 07-099/4, Tinbergen Institute.
    53. Florent MCISAAC, 2017. "Testing Goodwin with a Stochastic Differential Approach – The United States (1948-2017)," Working Paper b9367a07-3c34-4bca-83a2-f, Agence française de développement.
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    59. Florent McIsaac, 2021. "Testing Goodwin with a stochastic differential approach—The United States (1948–2019)," Metroeconomica, Wiley Blackwell, vol. 72(4), pages 696-730, November.
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    71. Osnat Stramer & Jun Yan, 2007. "Asymptotics of an Efficient Monte Carlo Estimation for the Transition Density of Diffusion Processes," Methodology and Computing in Applied Probability, Springer, vol. 9(4), pages 483-496, December.
    72. Yijie Peng & Michael C. Fu & Jian-Qiang Hu, 2016. "Gradient-based simulated maximum likelihood estimation for stochastic volatility models using characteristic functions," Quantitative Finance, Taylor & Francis Journals, vol. 16(9), pages 1393-1411, September.
    73. Michael Sørensen, 2008. "Efficient estimation for ergodic diffusions sampled at high frequency," CREATES Research Papers 2007-46, Department of Economics and Business Economics, Aarhus University.
    74. Martin J. Lenardon & Anna Amirdjanova, 2006. "Interaction between stock indices via changepoint analysis," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 22(5‐6), pages 573-586, September.
    75. Stan Hurn & J.Jeisman & K.A. Lindsay, 2006. "Teaching an old dog new tricks: Improved estimation of the parameters of SDEs by numerical solution of the Fokker-Planck equation," Stan Hurn Discussion Papers 2006-01, School of Economics and Finance, Queensland University of Technology.
    76. Alexandra Chronopoulou & Samy Tindel, 2013. "On inference for fractional differential equations," Statistical Inference for Stochastic Processes, Springer, vol. 16(1), pages 29-61, April.
    77. Siem Jan Koopman & Charles S. Bos, 2002. "Time Series Models with a Common Stochastic Variance for Analysing Economic Time Series," Tinbergen Institute Discussion Papers 02-113/4, Tinbergen Institute.
    78. J. Jimenez & R. Biscay & T. Ozaki, 2005. "Inference Methods for Discretely Observed Continuous-Time Stochastic Volatility Models: A Commented Overview," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 12(2), pages 109-141, June.
    79. Bu Ruijun & Cheng Jie & Hadri Kaddour, 2017. "Specification analysis in regime-switching continuous-time diffusion models for market volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(1), pages 65-80, February.
    80. Beatris Adriana Escobedo-Trujillo & José Daniel López-Barrientos & Carmen Geraldi Higuera-Chan & Francisco Alejandro Alaffita-Hernández, 2023. "Robust Statistic Estimation in Constrained Optimal Control Problems of Pollution Accumulation (Part II: Markovian Switchings)," Mathematics, MDPI, vol. 11(4), pages 1-22, February.
    81. Eva María Ramos-Ábalos & Ramón Gutiérrez-Sánchez & Ahmed Nafidi, 2020. "Powers of the Stochastic Gompertz and Lognormal Diffusion Processes, Statistical Inference and Simulation," Mathematics, MDPI, vol. 8(4), pages 1-13, April.
    82. Erik Lindström, 2007. "Estimating parameters in diffusion processes using an approximate maximum likelihood approach," Annals of Operations Research, Springer, vol. 151(1), pages 269-288, April.
    83. Eckhard Platen & Hardy Hulley, 2008. "Hedging for the Long Run," Research Paper Series 214, Quantitative Finance Research Centre, University of Technology, Sydney.
    84. James E. Griffin & Mark F.J. Steel, 2002. "Inference With Non-Gaussian Ornstein-Uhlenbeck Processes for Stochastic Volatility," Econometrics 0201002, University Library of Munich, Germany, revised 04 Apr 2003.
    85. Libo Sun & Chihoon Lee & Jennifer A. Hoeting, 2019. "A penalized simulated maximum likelihood method to estimate parameters for SDEs with measurement error," Computational Statistics, Springer, vol. 34(2), pages 847-863, June.
    86. Beatris Adriana Escobedo-Trujillo & José Daniel López-Barrientos & Carmen Geraldi Higuera-Chan & Francisco Alejandro Alaffita-Hernández, 2023. "Robust Statistic Estimation of Constrained Optimal Control Problems of Pollution Accumulation (Part I)," Mathematics, MDPI, vol. 11(4), pages 1-19, February.
    87. Michael Sørensen, 2008. "Parametric inference for discretely sampled stochastic differential equations," CREATES Research Papers 2008-18, Department of Economics and Business Economics, Aarhus University.
    88. Siddhartha Chib & Michael K Pitt & Neil Shephard, 2004. "Likelihood based inference for diffusion driven models," Economics Papers 2004-W20, Economics Group, Nuffield College, University of Oxford.
    89. Alcock, Jamie & Burrage, Kevin, 2004. "A genetic estimation algorithm for parameters of stochastic ordinary differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 255-275, September.
    90. Gutiérrez, R. & Gutiérrez-Sánchez, R. & Nafidi, A., 2009. "The trend of the total stock of the private car-petrol in Spain: Stochastic modelling using a new gamma diffusion process," Applied Energy, Elsevier, vol. 86(1), pages 18-24, January.
    91. Giuliano De Rossi, 2004. "Maximum likelihood estimation of the Cox-Ingersoll-Ross model using particle filters," Computing in Economics and Finance 2004 302, Society for Computational Economics.
    92. Xiaohu Wang & Peter C.B. Phillips & Jun Yu, 2011. "Bias in Estimating Multivariate and Univariate Diffusions," Cowles Foundation Discussion Papers 1778, Cowles Foundation for Research in Economics, Yale University.
    93. Giovanni Caggiano & Leone Leonida, "undated". "A note on the empirics of the neoclassical growth model," Working Papers 2006_2, Business School - Economics, University of Glasgow.
    94. Peavoy, Daniel & Franzke, Christian L.E. & Roberts, Gareth O., 2015. "Systematic physics constrained parameter estimation of stochastic differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 83(C), pages 182-199.
    95. Alejandra López-Pérez & Manuel Febrero-Bande & Wencesalo González-Manteiga, 2021. "Parametric Estimation of Diffusion Processes: A Review and Comparative Study," Mathematics, MDPI, vol. 9(8), pages 1-27, April.
    96. Amilcar A. Menichini, 2017. "On the value and determinants of the interest tax shields," Review of Quantitative Finance and Accounting, Springer, vol. 48(3), pages 725-748, April.
    97. Marcel Rindisbacher & Jérôme Detemple & René Garcia, 2004. "Asymptotic Properties of Monte Carlo Estimators of Diffusion Processes," Econometric Society 2004 North American Winter Meetings 483, Econometric Society.
    98. Peter C. B. Phillips & Jun Yu, 2005. "Comments on “A Selective Overview of Nonparametric Methods in Financial Econometrics” by Jianqing Fan," Working Papers 08-2005, Singapore Management University, School of Economics.
    99. Niu Wei-Fang, 2013. "Maximum likelihood estimation of continuous time stochastic volatility models with partially observed GARCH," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 421-438, September.
    100. Stan Hurn & J.Jeisman & K.A. Lindsay, 2006. "Seeing the wood for the trees: A critical evaluation of methods to estimate the parameters of stochastic differential equations," Stan Hurn Discussion Papers 2006, School of Economics and Finance, Queensland University of Technology.
    101. Stan Hurn & J.Jeisman & K.A. Lindsay, 2006. "Seeing the Wood for the Trees: A Critical Evaluation of Methods to Estimate the Parameters of Stochastic Differential Equations. Working paper #2," NCER Working Paper Series 2, National Centre for Econometric Research.
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    103. Giet, Ludovic & Lubrano, Michel, 2008. "A minimum Hellinger distance estimator for stochastic differential equations: An application to statistical inference for continuous time interest rate models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2945-2965, February.
    104. Höök, Lars Josef & Lindström, Erik, 2016. "Efficient computation of the quasi likelihood function for discretely observed diffusion processes," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 426-437.
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    106. Pitt, Michael K. & Silva, Ralph dos Santos & Giordani, Paolo & Kohn, Robert, 2012. "On some properties of Markov chain Monte Carlo simulation methods based on the particle filter," Journal of Econometrics, Elsevier, vol. 171(2), pages 134-151.
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    109. Quentin Clairon & Adeline Samson, 2020. "Optimal control for estimation in partially observed elliptic and hypoelliptic linear stochastic differential equations," Statistical Inference for Stochastic Processes, Springer, vol. 23(1), pages 105-127, April.
    110. Ruijun Bu & Ludovic Giet & Kaddour Hadri & Michel Lubrano, 2009. "Modelling Multivariate Interest Rates using Time-Varying Copulas and Reducible Non-Linear Stochastic Differential," Economics Working Papers 09-02, Queen's Management School, Queen's University Belfast.

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    2. Jun Yu & Peter C. B. Phillips, 2001. "A Gaussian approach for continuous time models of the short-term interest rate," Econometrics Journal, Royal Economic Society, vol. 4(2), pages 1-3.
    3. Umberto Picchini & Andrea De Gaetano & Susanne Ditlevsen, 2010. "Stochastic Differential Mixed‐Effects Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(1), pages 67-90, March.
    4. Jun Yu & Zhenlin Yang & Xibin Zhang, 2002. "A Class of Nonlinear Stochastic Volatility Models and Its Implications on Pricing Currency Options," Monash Econometrics and Business Statistics Working Papers 17/02, Monash University, Department of Econometrics and Business Statistics.
    5. Lubrano, Michel, 2004. "Modélisation bayésienne non linéaire du taux d’intérêt de court terme américain : l’aide des outils non paramétriques," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(2), pages 465-499, Juin-Sept.
    6. Nina Munkholt Jakobsen & Michael Sørensen, 2015. "Efficient Estimation for Diffusions Sampled at High Frequency Over a Fixed Time Interval," CREATES Research Papers 2015-33, Department of Economics and Business Economics, Aarhus University.
    7. Kyoung-Kuk Kim & Sojung Kim, 2016. "Simulation of Tempered Stable Lévy Bridges and Its Applications," Operations Research, INFORMS, vol. 64(2), pages 495-509, April.
    8. S. Bordignon & D. Raggi, 2008. "Volatility, Jumps and Predictability of Returns: a Sequential Analysis," Working Papers 636, Dipartimento Scienze Economiche, Universita' di Bologna.
    9. Sun, Libo & Lee, Chihoon & Hoeting, Jennifer A., 2015. "A penalized simulated maximum likelihood approach in parameter estimation for stochastic differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 84(C), pages 54-67.
    10. A. Hurn & J. Jeisman & K. Lindsay, 2007. "Teaching an Old Dog New Tricks: Improved Estimation of the Parameters of Stochastic Differential Equations by Numerical Solution of the Fokker-Planck Equation," NCER Working Paper Series 9, National Centre for Econometric Research.
    11. Kalogeropoulos, Konstantinos & Roberts, Gareth O. & Dellaportas, Petros, 2010. "Inference for stochastic volatility models using time change transformations," LSE Research Online Documents on Economics 31421, London School of Economics and Political Science, LSE Library.
    12. Siem Jan Koopman & Rutger Lit & Thuy Minh Nguyen, 2012. "Fast Efficient Importance Sampling by State Space Methods," Tinbergen Institute Discussion Papers 12-008/4, Tinbergen Institute, revised 16 Oct 2014.
    13. Flávio B. Gonçalves & Gareth O. Roberts, 2014. "Exact Simulation Problems for Jump-Diffusions," Methodology and Computing in Applied Probability, Springer, vol. 16(4), pages 907-930, December.
    14. Ruijun Bu & Ludovic Giet & Kaddour Hadri & Michel Lubrano, 2009. "Modeling Multivariate Interest Rates using Time-Varying Copulas and Reducible Stochastic Differential Equations," Working Papers halshs-00408014, HAL.
    15. Hao Zhou, 2003. "Itô conditional moment generator and the estimation of short rate processes," Finance and Economics Discussion Series 2003-32, Board of Governors of the Federal Reserve System (U.S.).
    16. Giuliano De Rossi, 2010. "Maximum Likelihood Estimation of the Cox–Ingersoll–Ross Model Using Particle Filters," Computational Economics, Springer;Society for Computational Economics, vol. 36(1), pages 1-16, June.
    17. Paul Fearnhead & Omiros Papaspiliopoulos & Gareth O. Roberts, 2008. "Particle filters for partially observed diffusions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(4), pages 755-777, September.
    18. Pascal St-Amour, 2005. "Direct Preference Wealth in Aggregate Household Portfolios," FAME Research Paper Series rp136, International Center for Financial Asset Management and Engineering.
    19. Kalogeropoulos, Konstantinos & Dellaportas, Petros & Roberts, Gareth O., 2007. "Likelihood-based inference for correlated diffusions," MPRA Paper 5696, University Library of Munich, Germany.
    20. Ruijun Bu & Jie Cheng & Kaddour Hadri, 2014. "Reducible Diffusions with Time-Varying Transformations with Application to Short-Term Interest Rates," Economics Working Papers 14-01, Queen's Management School, Queen's University Belfast.
    21. Mengheng Li & Siem Jan (S.J.) Koopman, 2018. "Unobserved Components with Stochastic Volatility in U.S. Inflation: Estimation and Signal Extraction," Tinbergen Institute Discussion Papers 18-027/III, Tinbergen Institute.
    22. Aleksandar Mijatovic & Paul Schneider, 2009. "Empirical asset pricing with nonlinear risk premia," Papers 0911.0928, arXiv.org.
    23. Song, Xinyu & Wang, Yazhen, 2020. "GARCH quasi-likelihood ratios for SV model and the diffusion limit," Statistics & Probability Letters, Elsevier, vol. 165(C).
    24. Kalogeropoulos, Konstantinos, 2007. "Likelihood-based inference for a class of multivariate diffusions with unobserved paths," LSE Research Online Documents on Economics 31423, London School of Economics and Political Science, LSE Library.
    25. Dennis Kristensen & Young Jun Lee & Antonio Mele, 2023. "Closed-form approximations of moments and densities of continuous-time Markov models," Papers 2308.09009, arXiv.org.
    26. Richard Anton Braun & Huiyu Li & John Stachurski, 2009. "Computing Densities: A Conditional Monte Carlo Estimator," CARF F-Series CARF-F-181, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    27. Neil Shephard & Torben G. Andersen, 2008. "Stochastic Volatility: Origins and Overview," OFRC Working Papers Series 2008fe23, Oxford Financial Research Centre.
    28. Federico M. Bandi & Peter C.B. Phillips, 2005. "A Simple Approach to the Parametric Estimation of Potentially Nonstationary Diffusions," Cowles Foundation Discussion Papers 1522, Cowles Foundation for Research in Economics, Yale University.
    29. Choi, Hwan-sik & Jeong, Minsoo & Park, Joon Y., 2014. "An asymptotic analysis of likelihood-based diffusion model selection using high frequency data," Journal of Econometrics, Elsevier, vol. 178(P3), pages 539-557.
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    31. Bakshi, Gurdip & Ju, Nengjiu & Ou-Yang, Hui, 2006. "Estimation of continuous-time models with an application to equity volatility dynamics," Journal of Financial Economics, Elsevier, vol. 82(1), pages 227-249, October.
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    33. Choi, Hwan-sik, 2016. "Information theory for maximum likelihood estimation of diffusion models," Journal of Econometrics, Elsevier, vol. 191(1), pages 110-128.
    34. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
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    36. Pastorello, S. & Rossi, E., 2010. "Efficient importance sampling maximum likelihood estimation of stochastic differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2753-2762, November.
    37. A. Golightly & D. J. Wilkinson, 2005. "Bayesian Inference for Stochastic Kinetic Models Using a Diffusion Approximation," Biometrics, The International Biometric Society, vol. 61(3), pages 781-788, September.
    38. Peter C. B. Phillips & Jun Yu, 2009. "Simulation-Based Estimation of Contingent-Claims Prices," The Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3669-3705, September.
    39. Kleppe, Tore Selland & Yu, Jun & Skaug, Hans J., 2014. "Maximum likelihood estimation of partially observed diffusion models," Journal of Econometrics, Elsevier, vol. 180(1), pages 73-80.
    40. Ming‐Chi Chen & Chia‐Chien Chang & Shih‐Kuei Lin & So‐De Shyu, 2010. "Estimation of Housing Price Jump Risks and Their Impact on the Valuation of Mortgage Insurance Contracts," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 77(2), pages 399-422, June.
    41. Varughese, Melvin M., 2013. "Parameter estimation for multivariate diffusion systems," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 417-428.
    42. Zhao-Hua Lu & Sy-Miin Chow & Nilam Ram & Pamela M. Cole, 2019. "Zero-Inflated Regime-Switching Stochastic Differential Equation Models for Highly Unbalanced Multivariate, Multi-Subject Time-Series Data," Psychometrika, Springer;The Psychometric Society, vol. 84(2), pages 611-645, June.
    43. Lars Josef Hook & Erik Lindstrom, 2015. "Efficient Computation of the Quasi Likelihood function for Discretely Observed Diffusion Processes," Papers 1509.07751, arXiv.org.
    44. Beskos, Alexandros & Kalogeropoulos, Konstantinos & Pazos, Erik, 2013. "Advanced MCMC methods for sampling on diffusion pathspace," Stochastic Processes and their Applications, Elsevier, vol. 123(4), pages 1415-1453.
    45. Theodore Simos & Mike Tsionas, 2018. "Bayesian inference of the fractional Ornstein–Uhlenbeck process under a flow sampling scheme," Computational Statistics, Springer, vol. 33(4), pages 1687-1713, December.
    46. Pascal St-Amour, 2005. "Direct Preference for Wealth in Aggregate Household Portfolio," Cahiers de Recherches Economiques du Département d'économie 05.04, Université de Lausanne, Faculté des HEC, Département d’économie.
    47. Cheng, Ai-ru (Meg) & Gallant, A. Ronald & Ji, Chuanshu & Lee, Beom S., 2008. "A Gaussian approximation scheme for computation of option prices in stochastic volatility models," Journal of Econometrics, Elsevier, vol. 146(1), pages 44-58, September.
    48. C.S. Bos & S.J. Koopman & M. Ooms, 2007. "Long Memory Modelling of Inflation with Stochastic Variance and Structural Breaks," Tinbergen Institute Discussion Papers 07-099/4, Tinbergen Institute.
    49. Florent MCISAAC, 2017. "Testing Goodwin with a Stochastic Differential Approach – The United States (1948-2017)," Working Paper b9367a07-3c34-4bca-83a2-f, Agence française de développement.
    50. Golightly, A. & Wilkinson, D.J., 2008. "Bayesian inference for nonlinear multivariate diffusion models observed with error," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1674-1693, January.
    51. Somnath Chatterjee, 2005. "Application Of The Kalman Filter For Estimating Continuous Time Term Structure Models: The Case Of Uk And Germany," Working Papers 2005_2, Business School - Economics, University of Glasgow.
    52. Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Impact of jumps on returns and realised variances: econometric analysis of time-deformed Levy processes," Economics Papers 2003-W12, Economics Group, Nuffield College, University of Oxford.
    53. Mogens Bladt & Samuel Finch & Michael Sørensen, 2016. "Simulation of multivariate diffusion bridges," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(2), pages 343-369, March.
    54. Marcin Mider & Paul A. Jenkins & Murray Pollock & Gareth O. Roberts, 2022. "The Computational Cost of Blocking for Sampling Discretely Observed Diffusions," Methodology and Computing in Applied Probability, Springer, vol. 24(4), pages 3007-3027, December.
    55. Florent McIsaac, 2021. "Testing Goodwin with a stochastic differential approach—The United States (1948–2019)," Metroeconomica, Wiley Blackwell, vol. 72(4), pages 696-730, November.
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    57. Bin Zhu & Peter X.-K. Song & Jeremy M.G. Taylor, 2011. "Stochastic Functional Data Analysis: A Diffusion Model-Based Approach," Biometrics, The International Biometric Society, vol. 67(4), pages 1295-1304, December.
    58. Golightly, Andrew & Bradley, Emma & Lowe, Tom & Gillespie, Colin S., 2019. "Correlated pseudo-marginal schemes for time-discretised stochastic kinetic models," Computational Statistics & Data Analysis, Elsevier, vol. 136(C), pages 92-107.
    59. Giuseppina Albano & Michele La Rocca & Cira Perna, 2019. "Small sample properties of ML estimator in Vasicek and CIR models: a simulation experiment," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(1), pages 5-19, June.
    60. Michael S. Johannes & Nicholas G. Polson & Jonathan R. Stroud, 2009. "Optimal Filtering of Jump Diffusions: Extracting Latent States from Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 22(7), pages 2559-2599, July.
    61. Denitsa Stefanova, 2012. "Stock Market Asymmetries: A Copula Diffusion," Tinbergen Institute Discussion Papers 12-125/IV/DSF45, Tinbergen Institute.
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    65. Xiao Huang, 2011. "Quasi‐maximum likelihood estimation of discretely observed diffusions," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 241-256, July.
    66. Kevin W. Lu & Phillip J. Paine & Simon P. Preston & Andrew T. A. Wood, 2022. "Approximate maximum likelihood estimation for one‐dimensional diffusions observed on a fine grid," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(3), pages 1085-1114, September.
    67. Osnat Stramer & Jun Yan, 2007. "Asymptotics of an Efficient Monte Carlo Estimation for the Transition Density of Diffusion Processes," Methodology and Computing in Applied Probability, Springer, vol. 9(4), pages 483-496, December.
    68. Yijie Peng & Michael C. Fu & Jian-Qiang Hu, 2016. "Gradient-based simulated maximum likelihood estimation for stochastic volatility models using characteristic functions," Quantitative Finance, Taylor & Francis Journals, vol. 16(9), pages 1393-1411, September.
    69. Michael Sørensen, 2008. "Efficient estimation for ergodic diffusions sampled at high frequency," CREATES Research Papers 2007-46, Department of Economics and Business Economics, Aarhus University.
    70. Martin J. Lenardon & Anna Amirdjanova, 2006. "Interaction between stock indices via changepoint analysis," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 22(5‐6), pages 573-586, September.
    71. Stan Hurn & J.Jeisman & K.A. Lindsay, 2006. "Teaching an old dog new tricks: Improved estimation of the parameters of SDEs by numerical solution of the Fokker-Planck equation," Stan Hurn Discussion Papers 2006-01, School of Economics and Finance, Queensland University of Technology.
    72. Alexandra Chronopoulou & Samy Tindel, 2013. "On inference for fractional differential equations," Statistical Inference for Stochastic Processes, Springer, vol. 16(1), pages 29-61, April.
    73. Siem Jan Koopman & Charles S. Bos, 2002. "Time Series Models with a Common Stochastic Variance for Analysing Economic Time Series," Tinbergen Institute Discussion Papers 02-113/4, Tinbergen Institute.
    74. J. Jimenez & R. Biscay & T. Ozaki, 2005. "Inference Methods for Discretely Observed Continuous-Time Stochastic Volatility Models: A Commented Overview," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 12(2), pages 109-141, June.
    75. Bu Ruijun & Cheng Jie & Hadri Kaddour, 2017. "Specification analysis in regime-switching continuous-time diffusion models for market volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(1), pages 65-80, February.
    76. Beatris Adriana Escobedo-Trujillo & José Daniel López-Barrientos & Carmen Geraldi Higuera-Chan & Francisco Alejandro Alaffita-Hernández, 2023. "Robust Statistic Estimation in Constrained Optimal Control Problems of Pollution Accumulation (Part II: Markovian Switchings)," Mathematics, MDPI, vol. 11(4), pages 1-22, February.
    77. Eva María Ramos-Ábalos & Ramón Gutiérrez-Sánchez & Ahmed Nafidi, 2020. "Powers of the Stochastic Gompertz and Lognormal Diffusion Processes, Statistical Inference and Simulation," Mathematics, MDPI, vol. 8(4), pages 1-13, April.
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    80. James E. Griffin & Mark F.J. Steel, 2002. "Inference With Non-Gaussian Ornstein-Uhlenbeck Processes for Stochastic Volatility," Econometrics 0201002, University Library of Munich, Germany, revised 04 Apr 2003.
    81. Libo Sun & Chihoon Lee & Jennifer A. Hoeting, 2019. "A penalized simulated maximum likelihood method to estimate parameters for SDEs with measurement error," Computational Statistics, Springer, vol. 34(2), pages 847-863, June.
    82. Beatris Adriana Escobedo-Trujillo & José Daniel López-Barrientos & Carmen Geraldi Higuera-Chan & Francisco Alejandro Alaffita-Hernández, 2023. "Robust Statistic Estimation of Constrained Optimal Control Problems of Pollution Accumulation (Part I)," Mathematics, MDPI, vol. 11(4), pages 1-19, February.
    83. Michael Sørensen, 2008. "Parametric inference for discretely sampled stochastic differential equations," CREATES Research Papers 2008-18, Department of Economics and Business Economics, Aarhus University.
    84. Alcock, Jamie & Burrage, Kevin, 2004. "A genetic estimation algorithm for parameters of stochastic ordinary differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 255-275, September.
    85. Siddhartha Chib & Michael K Pitt & Neil Shephard, 2004. "Likelihood based inference for diffusion driven models," Economics Papers 2004-W20, Economics Group, Nuffield College, University of Oxford.
    86. Gutiérrez, R. & Gutiérrez-Sánchez, R. & Nafidi, A., 2009. "The trend of the total stock of the private car-petrol in Spain: Stochastic modelling using a new gamma diffusion process," Applied Energy, Elsevier, vol. 86(1), pages 18-24, January.
    87. Giuliano De Rossi, 2004. "Maximum likelihood estimation of the Cox-Ingersoll-Ross model using particle filters," Computing in Economics and Finance 2004 302, Society for Computational Economics.
    88. Xiaohu Wang & Peter C.B. Phillips & Jun Yu, 2011. "Bias in Estimating Multivariate and Univariate Diffusions," Cowles Foundation Discussion Papers 1778, Cowles Foundation for Research in Economics, Yale University.
    89. Giovanni Caggiano & Leone Leonida, "undated". "A note on the empirics of the neoclassical growth model," Working Papers 2006_2, Business School - Economics, University of Glasgow.
    90. Peavoy, Daniel & Franzke, Christian L.E. & Roberts, Gareth O., 2015. "Systematic physics constrained parameter estimation of stochastic differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 83(C), pages 182-199.
    91. Alejandra López-Pérez & Manuel Febrero-Bande & Wencesalo González-Manteiga, 2021. "Parametric Estimation of Diffusion Processes: A Review and Comparative Study," Mathematics, MDPI, vol. 9(8), pages 1-27, April.
    92. Amilcar A. Menichini, 2017. "On the value and determinants of the interest tax shields," Review of Quantitative Finance and Accounting, Springer, vol. 48(3), pages 725-748, April.
    93. Marcel Rindisbacher & Jérôme Detemple & René Garcia, 2004. "Asymptotic Properties of Monte Carlo Estimators of Diffusion Processes," Econometric Society 2004 North American Winter Meetings 483, Econometric Society.
    94. Niu Wei-Fang, 2013. "Maximum likelihood estimation of continuous time stochastic volatility models with partially observed GARCH," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 421-438, September.
    95. Stan Hurn & J.Jeisman & K.A. Lindsay, 2006. "Seeing the wood for the trees: A critical evaluation of methods to estimate the parameters of stochastic differential equations," Stan Hurn Discussion Papers 2006, School of Economics and Finance, Queensland University of Technology.
    96. Stan Hurn & J.Jeisman & K.A. Lindsay, 2006. "Seeing the Wood for the Trees: A Critical Evaluation of Methods to Estimate the Parameters of Stochastic Differential Equations. Working paper #2," NCER Working Paper Series 2, National Centre for Econometric Research.
    97. S. C. Kou & Benjamin P. Olding & Martin Lysy & Jun S. Liu, 2012. "A Multiresolution Method for Parameter Estimation of Diffusion Processes," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(500), pages 1558-1574, December.
    98. Giet, Ludovic & Lubrano, Michel, 2008. "A minimum Hellinger distance estimator for stochastic differential equations: An application to statistical inference for continuous time interest rate models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2945-2965, February.
    99. Höök, Lars Josef & Lindström, Erik, 2016. "Efficient computation of the quasi likelihood function for discretely observed diffusion processes," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 426-437.
    100. Fornari, Fabio & Mele, Antonio, 2006. "Approximating volatility diffusions with CEV-ARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 30(6), pages 931-966, June.
    101. Pitt, Michael K. & Silva, Ralph dos Santos & Giordani, Paolo & Kohn, Robert, 2012. "On some properties of Markov chain Monte Carlo simulation methods based on the particle filter," Journal of Econometrics, Elsevier, vol. 171(2), pages 134-151.
    102. Olesia Verchenko, 2011. "Testing option pricing models: complete and incomplete markets," Discussion Papers 38, Kyiv School of Economics.
    103. Kleppe, Tore Selland & Skaug, Hans Julius, 2012. "Fitting general stochastic volatility models using Laplace accelerated sequential importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3105-3119.
    104. Quentin Clairon & Adeline Samson, 2020. "Optimal control for estimation in partially observed elliptic and hypoelliptic linear stochastic differential equations," Statistical Inference for Stochastic Processes, Springer, vol. 23(1), pages 105-127, April.
    105. Ruijun Bu & Ludovic Giet & Kaddour Hadri & Michel Lubrano, 2009. "Modelling Multivariate Interest Rates using Time-Varying Copulas and Reducible Non-Linear Stochastic Differential," Economics Working Papers 09-02, Queen's Management School, Queen's University Belfast.

  10. Fleissig, Adrian R. & Gallant, A. Ronald & Seater, John J., 2000. "Separability, Aggregation, And Euler Equation Estimation," Macroeconomic Dynamics, Cambridge University Press, vol. 4(4), pages 547-572, December.

    Cited by:

    1. Michal Pakos, "undated". "Measuring Intratemporal and Intertemporal Substitutions When Both Income and Substitution Effects Are Present: The Role of Consumer Durables," GSIA Working Papers 2007-E29, Carnegie Mellon University, Tepper School of Business.

  11. A. Ronald Gallant & Chien-Te Hsu & George Tauchen, 1999. "Using Daily Range Data To Calibrate Volatility Diffusions And Extract The Forward Integrated Variance," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 617-631, November.
    See citations under working paper version above.
  12. Ronald Gallant, A. & Tauchen, George, 1999. "The relative efficiency of method of moments estimators1," Journal of Econometrics, Elsevier, vol. 92(1), pages 149-172, September.

    Cited by:

    1. Chumacero Rómulo A., 2001. "Estimating ARMA Models Efficiently," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 5(2), pages 1-14, July.
    2. Paola Zerilli, 2007. "Option Pricing and Spikes in Volatility: Theoretical and Empirical Analysis," Discussion Papers 07/08, Department of Economics, University of York.
    3. Ravi Bansal & Hao Zhou, 2002. "Term Structure of Interest Rates with Regime Shifts," Journal of Finance, American Finance Association, vol. 57(5), pages 1997-2043, October.
    4. Ravi Bansal & George Tauchen & Hao Zhou, 2004. "Regime Shifts, Risk Premiums in the Term Structure, and the Business Cycle," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 396-409, October.
    5. Gallant, A. Ronald & Tauchen, George, 2002. "Simulated Score Methods and Indirect Inference for Continuous-time Models," Working Papers 02-09, Duke University, Department of Economics.
    6. Veiga, Helena, 2006. "Are feedback factors important in modelling financial data?," DES - Working Papers. Statistics and Econometrics. WS ws060101, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Ángel León & Javier Mencía & Enrique Sentana, 2007. "Parametric properties of semi-nonparametric distributions, with applications to option valuation," Working Papers 0707, Banco de España.
    8. Meddahi, N., 2001. "An Eigenfunction Approach for Volatility Modeling," Cahiers de recherche 2001-29, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    9. León, Angel & Moreno, Manuel, 2017. "One-sided performance measures under Gram-Charlier distributions," Journal of Banking & Finance, Elsevier, vol. 74(C), pages 38-50.
    10. Dante Jara, 2004. "Un Modelo Estadístico Flexible para la Estructura Intertemporal de Tasas en Chile," Econometrics 0412010, University Library of Munich, Germany.
    11. Christian Bontemps & Nour Meddahi, 2002. "Testing Normality: A GMM Approach," CIRANO Working Papers 2002s-63, CIRANO.
    12. Coppejans, Mark & Gallant, A. Ronald, 2000. "Cross Validated SNP Density Estimates," Working Papers 00-10, Duke University, Department of Economics.
    13. Javier Mencía & Enrique Sentana, 2018. "Volatility-Related Exchange Traded Assets: An Econometric Investigation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(4), pages 599-614, October.
    14. Ortelli, Claudio & Trojani, Fabio, 2005. "Robust efficient method of moments," Journal of Econometrics, Elsevier, vol. 128(1), pages 69-97, September.
    15. Otranto, Edoardo & Calzolari, Giorgio & Di Iorio, Francesca, 2005. "Indirect estimation of Markov switching models with endogenous switching," MPRA Paper 22983, University Library of Munich, Germany, revised 2005.
    16. Karen K. Lewis & Edith X. Liu, 2022. "How Can Asset Prices Value Exchange Rate Wedges?," Finance and Economics Discussion Series 2022-075, Board of Governors of the Federal Reserve System (U.S.).
    17. Gabriele Fiorentini & Enrique Sentana, 2020. "Discrete Mixtures of Normals Pseudo Maximum Likelihood Estimators of Structural Vector Autoregressions," Working Papers wp2020_2023, CEMFI.
    18. Di Iorio, Francesca & Calzolari, Giorgio, 2006. "Discontinuities in indirect estimation: An application to EAR models," Computational Statistics & Data Analysis, Elsevier, vol. 50(8), pages 2124-2136, April.
    19. Michael Creel, 2008. "Estimation of Dynamic Latent Variable Models Using Simulated Nonparametric Moments," UFAE and IAE Working Papers 725.08, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 02 Jun 2008.
    20. Garcia, René & Renault, Eric & Veredas, David, 2011. "Estimation of stable distributions by indirect inference," Journal of Econometrics, Elsevier, vol. 161(2), pages 325-337, April.
    21. Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2022. "PML vs minimum χ 2 : the comeback," Working Papers wp2022_2210, CEMFI.

  13. Barnett, William A. & Gallant, A. Ronald & Hinich, Melvin J. & Jungeilges, Jochen A. & Kaplan, Daniel T. & Jensen, Mark J., 1997. "A single-blind controlled competition among tests for nonlinearity and chaos," Journal of Econometrics, Elsevier, vol. 82(1), pages 157-192.
    See citations under working paper version above.
  14. Gallant, A. Ronald & Hsieh, David & Tauchen, George, 1997. "Estimation of stochastic volatility models with diagnostics," Journal of Econometrics, Elsevier, vol. 81(1), pages 159-192, November.
    See citations under working paper version above.
  15. Gallant, A. Ronald & Tauchen, George, 1997. "Estimation Of Continuous-Time Models For Stock Returns And Interest Rates," Macroeconomic Dynamics, Cambridge University Press, vol. 1(1), pages 135-168, January.
    See citations under working paper version above.
  16. Fenton, Victor M & Gallant, A Ronald, 1996. "Convergence Rates of SNP Density Estimators," Econometrica, Econometric Society, vol. 64(3), pages 719-727, May.

    Cited by:

    1. Gallant, A. Ronald & Hsieh, David & Tauchen, George, 1995. "Estimation of Stochastic Volatility Models with Diagnostics," Working Papers 95-36, Duke University, Department of Economics.
    2. Dennis Kristensen, 2009. "Semiparametric modelling and estimation (in Russian)," Quantile, Quantile, issue 7, pages 53-83, September.
    3. Dias, Ronaldo & Garcia, Nancy L., 2007. "Consistent estimator for basis selection based on a proxy of the Kullback-Leibler distance," Journal of Econometrics, Elsevier, vol. 141(1), pages 167-178, November.
    4. Ignacio Mauleon & Javier Perote, 2000. "Testing densities with financial data: an empirical comparison of the Edgeworth-Sargan density to the Student's t," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 225-239.
    5. Mauleon, Ignacio, 2003. "Financial densities in emerging markets: an application of the multivariate ES density," Emerging Markets Review, Elsevier, vol. 4(2), pages 197-223, June.
    6. Pieter J. Van Der Sluis, 1998. "Computationally attractive stability tests for the efficient method of moments," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages 203-227.
    7. Pedro Gozalo & Oliver Linton, 1994. "Local Nonlinear Least Squares Estimation: Using Parametric Information Nonparametrically," Cowles Foundation Discussion Papers 1075, Cowles Foundation for Research in Economics, Yale University.
    8. Neha Gupta, 2015. "Government Intervention in Grain Markets in India: Rethinking the Procurement Policy," Working Papers id:7810, eSocialSciences.
    9. Ming Liu & Harold H. Zhang, "undated". "Specification Tests in the Efficient Method of Moments Framework with Application to the Stochastic Volatility Models," Computing in Economics and Finance 1997 93, Society for Computational Economics.
    10. Liesenfeld, Roman & Breitung, Jörg, 1998. "Simulation based methods of moments in empirical finance," Tübinger Diskussionsbeiträge 136, University of Tübingen, School of Business and Economics.
    11. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
    12. Kevin Hasker & Robin Sickles, 2010. "eBay in the Economic Literature: Analysis of an Auction Marketplace," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 37(1), pages 3-42, August.
    13. Fenton, Victor M. & Gallant, A. Ronald, 1996. "Qualitative and asymptotic performance of SNP density estimators," Journal of Econometrics, Elsevier, vol. 74(1), pages 77-118, September.
    14. Gozalo, Pedro & Linton, Oliver, 2000. "Local nonlinear least squares: Using parametric information in nonparametric regression," Journal of Econometrics, Elsevier, vol. 99(1), pages 63-106, November.
    15. Foster, Joshua, 2022. "Semi-nonparametric estimation of secret reserve prices in auctions," Economics Letters, Elsevier, vol. 220(C).
    16. Coppejans, Mark, 2004. "On Kolmogorov's representation of functions of several variables by functions of one variable," Journal of Econometrics, Elsevier, vol. 123(1), pages 1-31, November.
    17. Ignacio Mauleon, 2006. "Modelling multivariate moments in European Stock Markets," The European Journal of Finance, Taylor & Francis Journals, vol. 12(3), pages 241-263.
    18. Andersen, Torben G. & Chung, Hyung-Jin & Sorensen, Bent E., 1999. "Efficient method of moments estimation of a stochastic volatility model: A Monte Carlo study," Journal of Econometrics, Elsevier, vol. 91(1), pages 61-87, July.
    19. Brendstrup, Bjarne & Paarsch, Harry J., 2006. "Identification and estimation in sequential, asymmetric, English auctions," Journal of Econometrics, Elsevier, vol. 134(1), pages 69-94, September.
    20. Antic, J. & Laffont, C.M. & Chafaï, D. & Concordet, D., 2009. "Comparison of nonparametric methods in nonlinear mixed effects models," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 642-656, January.
    21. Teruko Takada, 2001. "Nonparametric density estimation: A comparative study," Economics Bulletin, AccessEcon, vol. 3(16), pages 1-10.

  17. Gallant, A. Ronald & Tauchen, George, 1996. "Which Moments to Match?," Econometric Theory, Cambridge University Press, vol. 12(4), pages 657-681, October.
    See citations under working paper version above.
  18. Fenton, Victor M & Gallant, A Ronald, 1996. "Erratum [Convergence Rates of SNP Density Estimators]," Econometrica, Econometric Society, vol. 64(6), pages 1493-1493, November.

    Cited by:

    1. Gallant, A. Ronald & Hsieh, David & Tauchen, George, 1995. "Estimation of Stochastic Volatility Models with Diagnostics," Working Papers 95-36, Duke University, Department of Economics.
    2. Dias, Ronaldo & Garcia, Nancy L., 2007. "Consistent estimator for basis selection based on a proxy of the Kullback-Leibler distance," Journal of Econometrics, Elsevier, vol. 141(1), pages 167-178, November.
    3. Mauleon, Ignacio, 2003. "Financial densities in emerging markets: an application of the multivariate ES density," Emerging Markets Review, Elsevier, vol. 4(2), pages 197-223, June.
    4. Pieter J. Van Der Sluis, 1998. "Computationally attractive stability tests for the efficient method of moments," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages 203-227.
    5. Neha Gupta, 2015. "Government Intervention in Grain Markets in India: Rethinking the Procurement Policy," Working Papers id:7810, eSocialSciences.
    6. Liesenfeld, Roman & Breitung, Jörg, 1998. "Simulation based methods of moments in empirical finance," Tübinger Diskussionsbeiträge 136, University of Tübingen, School of Business and Economics.
    7. Fenton, Victor M. & Gallant, A. Ronald, 1996. "Qualitative and asymptotic performance of SNP density estimators," Journal of Econometrics, Elsevier, vol. 74(1), pages 77-118, September.
    8. Foster, Joshua, 2022. "Semi-nonparametric estimation of secret reserve prices in auctions," Economics Letters, Elsevier, vol. 220(C).
    9. Coppejans, Mark, 2004. "On Kolmogorov's representation of functions of several variables by functions of one variable," Journal of Econometrics, Elsevier, vol. 123(1), pages 1-31, November.
    10. Ignacio Mauleon, 2006. "Modelling multivariate moments in European Stock Markets," The European Journal of Finance, Taylor & Francis Journals, vol. 12(3), pages 241-263.
    11. Andersen, Torben G. & Chung, Hyung-Jin & Sorensen, Bent E., 1999. "Efficient method of moments estimation of a stochastic volatility model: A Monte Carlo study," Journal of Econometrics, Elsevier, vol. 91(1), pages 61-87, July.
    12. Brendstrup, Bjarne & Paarsch, Harry J., 2006. "Identification and estimation in sequential, asymmetric, English auctions," Journal of Econometrics, Elsevier, vol. 134(1), pages 69-94, September.
    13. Antic, J. & Laffont, C.M. & Chafaï, D. & Concordet, D., 2009. "Comparison of nonparametric methods in nonlinear mixed effects models," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 642-656, January.

  19. Fenton, Victor M. & Gallant, A. Ronald, 1996. "Qualitative and asymptotic performance of SNP density estimators," Journal of Econometrics, Elsevier, vol. 74(1), pages 77-118, September.
    See citations under working paper version above.
  20. Barnett, William A. & Ronald Gallant, A. & Hinich, Melvin J. & Jungeilges, Jochen A. & Kaplan, Daniel T. & Jensen, Mark J., 1995. "Robustness of nonlinearity and chaos tests to measurement error, inference method, and sample size," Journal of Economic Behavior & Organization, Elsevier, vol. 27(2), pages 301-320, July.

    Cited by:

    1. William Barnett & Apostolos Serletis & Demitre Serletis, 2012. "Nonlinear and Complex Dynamics in Economics," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201238, University of Kansas, Department of Economics, revised Sep 2012.
    2. Barnett, William A. & Chauvet, Marcelle & Tierney, Heather L. R., 2008. "Measurement Error in Monetary Aggregates: A Markov Switching Factor Approach," MPRA Paper 10179, University Library of Munich, Germany.
    3. Christophe C. Gouel, 2012. "Agricultural price instability: a survey of competing explanations and remedies," Post-Print hal-01001218, HAL.
    4. William Barnett & Apostolos Serletis, 2012. "Martingales, Nonlinearity, And Chaos," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201225, University of Kansas, Department of Economics, revised Sep 2012.
    5. Caraiani, Petre, 2012. "Is the Romanian Business Cycle Characterized by Chaos?," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 142-151, September.
    6. William A. Barnett & Melvin J. Hinich & Piyu Yue, 2011. "The Exact Theoretical Rational Expectations Monetary Aggregate," World Scientific Book Chapters, in: Financial Aggregation And Index Number Theory, chapter 2, pages 53-84, World Scientific Publishing Co. Pte. Ltd..
    7. William A. Barnett, 1996. "A Perspective on the Current State of Macroeconomic Theory," Macroeconomics 9602003, University Library of Munich, Germany.
    8. Saadi, Samir & Rahman, Abdul, 2008. "Evidence of non-stationary bias in scaling by square root of time: Implications for Value-at-Risk," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(3), pages 272-289, July.
    9. Kyrtsou, Catherine & Serletis, Apostolos, 2006. "Univariate tests for nonlinear structure," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 154-168, March.
    10. Serletis, Apostolos & He, Mingyu & Chowdhury, M.M. Islam, 2023. "Chaos in long-maturity real rates," Economics Letters, Elsevier, vol. 225(C).
    11. Rahman, Abdul & Saadi, Samir, 2008. "Random walk and breaking trend in financial series: An econometric critique of unit root tests," Review of Financial Economics, Elsevier, vol. 17(3), pages 204-212, August.
    12. Shintani, Mototsugu, 2008. "A dynamic factor approach to nonlinear stability analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 32(9), pages 2788-2808, September.
    13. Elena Olmedo & Ricardo Gimeno & Lorenzo Escot & Ruth Mateos, 2007. "Convergencia y Estabilidad de los Tipos de Cambio Europeos: Una Aplicación de Exponentes de Lyapunov," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 44(129), pages 91-108.
    14. Barnett, William A. & Gallant, A. Ronald & Hinich, Melvin J. & Jungeilges, Jochen A. & Kaplan, Daniel T. & Jensen, Mark J., 1997. "A single-blind controlled competition among tests for nonlinearity and chaos," Journal of Econometrics, Elsevier, vol. 82(1), pages 157-192.
    15. Oliver Linton & Mototsugu Shintani, 2001. "Is There Chaos in the World Economy? A Nonparametric Test Using Consistent Standard Errors," FMG Discussion Papers dp383, Financial Markets Group.
    16. Serletis, Apostolos & Shintani, Mototsugu, 2006. "Chaotic monetary dynamics with confidence," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 228-252, March.
    17. Shintani, Mototsugu & Linton, Oliver, 2002. "Nonparametric neural network estimation of Lyapunov exponents and a direct test for chaos," LSE Research Online Documents on Economics 2093, London School of Economics and Political Science, LSE Library.
    18. Caraiani, Petre, 2014. "What drives the nonlinearity of time series: A frequency perspective," Economics Letters, Elsevier, vol. 125(1), pages 40-42.
    19. Barry E. Jones & Travis D. Nesmith, 2006. "Linear cointegration of nonlinear time series with an application to interest rate dynamics," Finance and Economics Discussion Series 2007-03, Board of Governors of the Federal Reserve System (U.S.).
    20. Marisa Faggini, 2011. "Chaotic Time Series Analysis in Economics: Balance and Perspectives," Working papers 25, Former Department of Economics and Public Finance "G. Prato", University of Torino.
    21. William A. Barnett & Hajar Aghababa, 2016. "Dynamic Structure of the Spot Price of Crude Oil: Does Time Aggregation Matter?," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201602, University of Kansas, Department of Economics, revised Aug 2016.
    22. Olmedo, Elena, 2011. "Is there chaos in the Spanish labour market?," Chaos, Solitons & Fractals, Elsevier, vol. 44(12), pages 1045-1053.
    23. Petre Caraiani, 2012. "Evidence of Multifractality from Emerging European Stock Markets," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-9, July.
    24. Ioannis Andreadis & Athanasios D. Fragkou & Theodoros E. Karakasidis & Apostolos Serletis, 2023. "Nonlinear dynamics in Divisia monetary aggregates: an application of recurrence quantification analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-17, December.
    25. Serletis, Apostolos & Uritskaya, Olga Y., 2007. "Detecting signatures of stochastic self-organization in US money and velocity measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(1), pages 281-291.
    26. William A. Barnett & Barry E. Jones & Milka Kirova & Travis Nesmith & Meenakshi Pasupathy, 2004. "The Nonlinear Skeletons in the Closet," Econometrics 0405003, University Library of Munich, Germany.
    27. Olmedo, Elena & Mateos, Ruth, 2015. "Quantitative characterization of chaordic tourist destination," Tourism Management, Elsevier, vol. 47(C), pages 115-126.

  21. Bansal, Ravi & Gallant, A. Ronald & Hussey, Robert & Tauchen, George, 1995. "Nonparametric estimation of structural models for high-frequency currency market data," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 251-287.

    Cited by:

    1. Giorgio Valente & Mr. Gene L. Leon & Lucio Sarno, 2006. "Nonlinearity in Deviations From Uncovered Interest Parity: An Explanation of the Forward Bias Puzzle," IMF Working Papers 2006/136, International Monetary Fund.
    2. Arvanitis Stelios & Demos Antonis, 2018. "On the Validity of Edgeworth Expansions and Moment Approximations for Three Indirect Inference Estimators," Journal of Econometric Methods, De Gruyter, vol. 7(1), pages 1-38, January.
    3. Peter Fuleky & Eric Zivot, 2010. "Indirect Inference Based on the Score," Working Papers UWEC-2010-08, University of Washington, Department of Economics.
    4. Thomas D. Tallarini & Harold H. Zhang, 2005. "External habit and the cyclicality of expected stock returns," Finance and Economics Discussion Series 2005-27, Board of Governors of the Federal Reserve System (U.S.).
    5. Gallant, A. Ronald & Hsieh, David & Tauchen, George, 1995. "Estimation of Stochastic Volatility Models with Diagnostics," Working Papers 95-36, Duke University, Department of Economics.
    6. Albert Marcet & David A. Marshall, 1994. "Solving nonlinear rational expectations models by parameterized expectations: Convergence to stationary solutions," Economics Working Papers 76, Department of Economics and Business, Universitat Pompeu Fabra.
    7. Bhar, Ramprasad & Kim, Suk-Joong & Pham, Toan M., 2004. "Exchange rate volatility and its impact on the transaction costs of covered interest rate parity," Japan and the World Economy, Elsevier, vol. 16(4), pages 503-525, December.
    8. Steve Ambler & Ali Dib & Nooman Rebei, 2003. "Nominal Rigidities and Exchange Rate Pass-Through in a Structural Model of a Small Open Economy," Staff Working Papers 03-29, Bank of Canada.
    9. Narayan, Paresh Kumar & Sharma, Susan Sunila & Phan, Dinh Hoang Bach & Liu, Guangqiang, 2020. "Predicting exchange rate returns," Emerging Markets Review, Elsevier, vol. 42(C).
    10. Liu, Ming & Zhang, Harold H., 1998. "Overparameterization in the seminonparametric density estimation," Economics Letters, Elsevier, vol. 60(1), pages 11-18, July.
    11. Eduardo Rossi & Paolo Santucci de Magistris, 2018. "Indirect inference with time series observed with error," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(6), pages 874-897, September.
    12. Sarno, Lucio & Schneider, Paul & Wagner, Christian, 2010. "Properties of Foreign Exchange Risk Premia," MPRA Paper 21302, University Library of Munich, Germany.
    13. Ravi Bansal & George Tauchen & Hao Zhou, 2004. "Regime Shifts, Risk Premiums in the Term Structure, and the Business Cycle," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 396-409, October.
    14. Hollifield, B. & Yaron, A., 1999. "The Foreign Exchange Risk Premium: Real and Nominal Factors," GSIA Working Papers 1999-17, Carnegie Mellon University, Tepper School of Business.
    15. Ming Liu & Harold H. Zhang, "undated". "Specification Tests in the Efficient Method of Moments Framework with Application to the Stochastic Volatility Models," Computing in Economics and Finance 1997 93, Society for Computational Economics.
    16. Per Bjarte Solibakke, 2003. "Validity of discrete-time stochastic volatility models in non-synchronous equity markets," The European Journal of Finance, Taylor & Francis Journals, vol. 9(5), pages 420-448.
    17. Jean-Marie Dufour & Pascale Valery, 2000. "Monte Carlo Test Applied to Models Estimated by Indirect Inference," Econometric Society World Congress 2000 Contributed Papers 1667, Econometric Society.
    18. Pieter J. van der Sluis, 1998. "Structural Stability Tests with Unknown Breakpoint for the Efficient Method of Moments with Application to Stochastic Volatility Models," Tinbergen Institute Discussion Papers 98-055/4, Tinbergen Institute.
    19. Liesenfeld, Roman & Breitung, Jörg, 1998. "Simulation based methods of moments in empirical finance," Tübinger Diskussionsbeiträge 136, University of Tübingen, School of Business and Economics.
    20. Gallant, A. Ronald & Tauchen, George, 2002. "Simulated Score Methods and Indirect Inference for Continuous-time Models," Working Papers 02-09, Duke University, Department of Economics.
    21. Tauchen, George, 1997. "The Objective Function of Simulation Estimators Near the Boundary of the Unstable Region of the Parameter Space," Working Papers 97-14, Duke University, Department of Economics.
    22. Michaelides, Alexander & Ng, Serena, 2000. "Estimating the rational expectations model of speculative storage: A Monte Carlo comparison of three simulation estimators," Journal of Econometrics, Elsevier, vol. 96(2), pages 231-266, June.
    23. Wagner, Christian, 2012. "Risk-premia, carry-trade dynamics, and economic value of currency speculation," Journal of International Money and Finance, Elsevier, vol. 31(5), pages 1195-1219.
    24. Perignon, Christophe & Smith, Daniel R., 2007. "Yield-factor volatility models," Journal of Banking & Finance, Elsevier, vol. 31(10), pages 3125-3144, October.
    25. Andersen, Torben G. & Lund, Jesper, 1997. "Estimating continuous-time stochastic volatility models of the short-term interest rate," Journal of Econometrics, Elsevier, vol. 77(2), pages 343-377, April.
    26. Sarno, Lucio & Schneider, Paul & Wagner, Christian, 2011. "Properties of Foreign Exchange Risk Premiums," CEPR Discussion Papers 8503, C.E.P.R. Discussion Papers.
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    28. Hao Zhou, 2000. "A study of the finite sample properties of EMM, GMM, QMLE, and MLE for a square-root interest rate diffusion model," Finance and Economics Discussion Series 2000-45, Board of Governors of the Federal Reserve System (U.S.).
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    1. Gao, Jiti & Tong, Howell & Wolff, Rodney, 2002. "Model Specification Tests in Nonparametric Stochastic Regression Models," Journal of Multivariate Analysis, Elsevier, vol. 83(2), pages 324-359, November.
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    12. Yingzhuo Yu & Cesar Escalante & Xiaohui Deng & Jack Houston & Lewell Gunter, 2011. "Analysing scale and scope specialization efficiencies of US agricultural and nonagricultural banks using the Fourier flexible functional form," Applied Financial Economics, Taylor & Francis Journals, vol. 21(15), pages 1103-1116.
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    2. GianCarlo Moschini, 2000. "Flexible Multistage Demand System Based on Indirect Separability, A," Center for Agricultural and Rural Development (CARD) Publications 00-wp265, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    3. Rodríguez, Francisco & Shelton, Cameron A., 2013. "Cleaning up the kitchen sink: Specification tests and average derivative estimators for growth econometrics," Journal of Macroeconomics, Elsevier, vol. 38(PB), pages 260-273.
    4. David C. Wheelock & Paul W. Wilson, 2007. "Non-parametric, unconditional quantile estimation for efficiency analysis with an application to Federal Reserve check processing operations," Working Papers 2005-027, Federal Reserve Bank of St. Louis.
    5. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    6. Shaikh, Sabina L., 1998. "A Whale Of A Good Time: Exploring Flexibility In The Recreation Demand Model," 1998 Annual meeting, August 2-5, Salt Lake City, UT 20826, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. Driscoll, Paul J., 1994. "When Flexible Forms Are Asked To Flex Too Much," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 19(1), pages 1-14, July.
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    9. Yingzhuo Yu & Cesar Escalante & Xiaohui Deng & Jack Houston & Lewell Gunter, 2011. "Analysing scale and scope specialization efficiencies of US agricultural and nonagricultural banks using the Fourier flexible functional form," Applied Financial Economics, Taylor & Francis Journals, vol. 21(15), pages 1103-1116.
    10. Adrian R. Fleissig, 2016. "Changing Trends in U.S. Alcohol Demand," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 44(3), pages 263-276, September.
    11. Jonathan K. Yoder & Adrienne M. Ohler & Hayley H. Chouinard, 2012. "What floats your boat? Preference revelation from lotteries over complex goods," Working Papers 2012-4, School of Economic Sciences, Washington State University.
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    14. Altunbas, Y. & Gardener, E. P. M. & Molyneux, P. & Moore, B., 2001. "Efficiency in European banking," European Economic Review, Elsevier, vol. 45(10), pages 1931-1955, December.
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    29. Fleissig, Adrian R. & Kastens, Terry & Terrell, Dek, 1997. "Semi-nonparametric estimates of substitution elasticities," Economics Letters, Elsevier, vol. 54(3), pages 209-215, July.
    30. Souza, João Carlos F. & Souza, Geraldo S., 1995. "A Monte Carlo Study on the Fit of a Cost Function by a Fourier Flexible Functional Form," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 15(2), November.
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    32. Dashti, Imad, 2003. "Inference from concave stochastic frontiers and the covariance of firm efficiency measures across firms," Energy Economics, Elsevier, vol. 25(6), pages 585-601, November.
    33. Tai‐Hsin Huang & Mei‐Hui Wang, 2003. "Estimation of Technical and Allocative Inefficiency Using Fourier Flexible Cost Frontiers for Taiwan's Banking Industry," Manchester School, University of Manchester, vol. 71(3), pages 341-362, June.
    34. David C. Wheelock & Paul W. Wilson, 2012. "Do Large Banks Have Lower Costs? New Estimates of Returns to Scale for U.S. Banks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(1), pages 171-199, February.
    35. Guohua Feng & Apostolos Serletis, 2009. "Efficiency and productivity of the US banking industry, 1998-2005: evidence from the Fourier cost function satisfying global regularity conditions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 105-138.
    36. Lee, Chi-Chuan & Huang, Tai-Hsin, 2017. "Cost efficiency and technological gap in Western European banks: A stochastic metafrontier analysis," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 161-178.
    37. Hilmer, Christiana E. & Holt, Matthew T., 2000. "A Comparison Of Resampling Techniques When Parameters Are On A Boundary: The Bootstrap, Subsample Bootstrap, And Subsample Jackknife," 2000 Annual meeting, July 30-August 2, Tampa, FL 21810, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    38. Tai-hsin Huang & Mei-hui Wang, 2004. "Comparisons of Economic Inefficiency Between Output and Input Measures of Technical Inefficiency Using the Fourier Flexible Cost Function," Journal of Productivity Analysis, Springer, vol. 22(1), pages 123-142, July.

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    1. Tullio Gregori, 1998. "A Bayesian approach to analyze regional elasticities," ERSA conference papers ersa98p226, European Regional Science Association.

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    2. Zhou, Yang & Ma, Rong & Su, Yun & Wu, Libo, 2019. "Too big to change: How heterogeneous firms respond to time-of-use electricity price," China Economic Review, Elsevier, vol. 58(C).
    3. J. G. Hirschberg, 2000. "Modelling time of day substitution using the second moments of demand," Applied Economics, Taylor & Francis Journals, vol. 32(8), pages 979-986.
    4. Brown, David P. & Sappington, David E.M., 2018. "On the role of maximum demand charges in the presence of distributed generation resources," Energy Economics, Elsevier, vol. 69(C), pages 237-249.
    5. Torriti, Jacopo & Hassan, Mohamed G. & Leach, Matthew, 2010. "Demand response experience in Europe: Policies, programmes and implementation," Energy, Elsevier, vol. 35(4), pages 1575-1583.
    6. Sueyoshi, Toshiyuki, 1999. "Tariff structure of Japanese electric power companies: An empirical analysis using DEA," European Journal of Operational Research, Elsevier, vol. 118(2), pages 350-374, October.

  33. Elbadawi, Ibrahim & Gallant, A Ronald & Souza, Geraldo, 1983. "An Elasticity Can Be Estimated Consistently without A Priori Knowledge of Functional Form," Econometrica, Econometric Society, vol. 51(6), pages 1731-1751, November.

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    1. Allen N. Berger & John H. Leusner & John J. Mingo, 1994. "The efficiency of bank branches," Finance and Economics Discussion Series 94-26, Board of Governors of the Federal Reserve System (U.S.).
    2. Wahl, Thomas I. & Hayes, Dermot J., 1989. "A Dynamic, Globally Flexible Model Of U.S. Meat Demand," 1989 Annual Meeting, July 30-August 2, Baton Rouge, Louisiana 270672, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Wolfgang Hardle & Oliver Linton, 1994. "Applied Nonparametric Methods," Cowles Foundation Discussion Papers 1069, Cowles Foundation for Research in Economics, Yale University.
    4. Fleissig, Adrian & Swofford, James L., 1996. "A dynamic asymptotically ideal model of money demand," Journal of Monetary Economics, Elsevier, vol. 37(2-3), pages 371-380, April.
    5. Kesavan, Thulasiram, 1988. "Monte Carlo experiments of market demand theory," ISU General Staff Papers 198801010800009854, Iowa State University, Department of Economics.
    6. Shaikh, Sabina L., 1998. "A Whale Of A Good Time: Exploring Flexibility In The Recreation Demand Model," 1998 Annual meeting, August 2-5, Salt Lake City, UT 20826, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. Chen, Heng Z. & Randall, Alan, 1997. "Semi-nonparametric estimation of binary response models with an application to natural resource valuation," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 323-340.
    8. Arthur Lewbel, 2001. "Demand Systems with and without Errors," American Economic Review, American Economic Association, vol. 91(3), pages 611-618, June.
    9. Das, M., 2003. "Identification and sequential estimation of panel data models with insufficient exclusion restrictions," Journal of Econometrics, Elsevier, vol. 114(2), pages 297-328, June.
    10. LaFrance, Jeffrey T & Pope, Rulon D., 2007. "Homogeneity and Supply," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt9kw967kf, Department of Agricultural & Resource Economics, UC Berkeley.
    11. Altunbas, Y. & Gardener, E. P. M. & Molyneux, P. & Moore, B., 2001. "Efficiency in European banking," European Economic Review, Elsevier, vol. 45(10), pages 1931-1955, December.
    12. Stoker, Thomas M., 1996. "Smoothing bias in the measurement of marginal effects," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 49-84.
    13. Toshinobu Matsuda, 2006. "A trigonometric flexible consumer demand system," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 39(1), pages 145-162, February.
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    3. Bianchi, Carlo & Calzolari, Giorgio, 1983. "Standard errors of forecasts in dynamic simulation of nonlinear econometric models: some empirical results," MPRA Paper 22657, University Library of Munich, Germany, revised 1983.
    4. Jeon, Jong-Pyeong, 1989. "The impacts of policy alternatives and foreign demand fluctuations on the US rice market," ISU General Staff Papers 1989010108000010204, Iowa State University, Department of Economics.
    5. Patrick Fève & François Langot, 1995. "La méthode des moments généralisés et ses extensions : théorie et applications en macro-économie," Économie et Prévision, Programme National Persée, vol. 119(3), pages 139-170.
    6. Le, Huong Nguyen Quynh & Nguyen, Thai Vu Hong & Schinckus, Christophe, 2021. "Bank efficiency, market structure and strategic interaction: Evidence from Vietnam," Research in International Business and Finance, Elsevier, vol. 56(C).
    7. Georgios Bitros & Epaminondas Panas, 2005. "Another look at the inflation-productivity trade-off," Macroeconomics 0506001, University Library of Munich, Germany.
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    9. Calzolari, Giorgio, 2012. "Econometric notes," MPRA Paper 36765, University Library of Munich, Germany.
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    30. Amemiya, Takeshi, 1983. "Non-linear regression models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 1, chapter 6, pages 333-389, Elsevier.
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    34. Koo, Won W. & Lehman, James R., 1984. "Effects of Government Programs on Corn, Soybeans, and Wheat Production in the U.S," Agricultural Economics Reports 23141, North Dakota State University, Department of Agribusiness and Applied Economics.
    35. Wahl, Thomas Iver, 1989. "Modeling dynamic adjustment in Japanese livestock markets under trade liberalization," ISU General Staff Papers 1989010108000010093, Iowa State University, Department of Economics.

  40. Gallant, A. Ronald, 1975. "Seemingly unrelated nonlinear regressions," Journal of Econometrics, Elsevier, vol. 3(1), pages 35-50, February.

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    1. Krebs, Tom & Krishna, Pravin & Maloney, William F., 2013. "Income Mobility and Welfare," Working Papers 13-02, University of Mannheim, Department of Economics.
    2. Warjiyo, Perry & Huffman, Wallace E., 1995. "Dynamic Input Demand Functions and Resource Adjustment for U.S. Agriculture: State Evidence," ISU General Staff Papers 199512190800001277, Iowa State University, Department of Economics.
    3. Aslanidis, Nektarios, 2007. "Business Cycle Regimes in CEECs Production: A Threshold SURE Approach," Working Papers 2072/5318, Universitat Rovira i Virgili, Department of Economics.
    4. Paul Cashin, 1991. "A Model Of The Disaggregated Demand For Meat In Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 35(3), pages 263-283, December.
    5. Gary King, 1989. "A Seemingly Unrelated Poisson Regression Model," Sociological Methods & Research, , vol. 17(3), pages 235-255, February.
    6. Willem Thorbecke, 2018. "The Effect of the Fed's Large‐Scale Asset Purchases on Inflationary Expectations," Southern Economic Journal, John Wiley & Sons, vol. 85(2), pages 407-423, October.
    7. Pope, Rulon D. & Just, Richard E., 1977. "On The Competitive Firm Under Production Uncertainty," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 21(2), pages 1-8, August.
    8. Anastasios Xepapadeas & Hassini Habib, 1995. "An almost ideal demand system with autoregressive disturbances for dairy products in Greece," Applied Economics Letters, Taylor & Francis Journals, vol. 2(6), pages 169-173.
    9. Cui, Hengjian & Hu, Tao, 2011. "On nonlinear regression estimator with denoised variables," Computational Statistics & Data Analysis, Elsevier, vol. 55(2), pages 1137-1149, February.
    10. David C. Ling & Andy Naranjo, 1999. "The Integration of Commercial Real Estate Markets and Stock Markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 27(3), pages 483-515, September.
    11. von Auer, Ludwig & Weinand, Sebastian, 2022. "A nonlinear generalization of the country-product-dummy method," Discussion Papers 45/2022, Deutsche Bundesbank.
    12. Barbara McKiernan, 1997. "Uncertainty and the arbitrage pricing theory," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 25(3), pages 307-311, September.
    13. Wai Choi & Anindya Sen & Adam White, 2011. "Response of industrial customers to hourly pricing in Ontario’s deregulated electricity market," Journal of Regulatory Economics, Springer, vol. 40(3), pages 303-323, December.
    14. Jean C. H. Loo, 1988. "Common Stock Returns, Expected Inflation, And The Rational Expectations Hypothesis," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 11(2), pages 165-172, June.
    15. David Besanko & Sachin Gupta & Dipak Jain, 1998. "Logit Demand Estimation Under Competitive Pricing Behavior: An Equilibrium Framework," Management Science, INFORMS, vol. 44(11-Part-1), pages 1533-1547, November.
    16. Capps, Oral, Jr., 1983. "Alternative Estimation Methods Of Nonlinear Demand Systems," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 8(1), pages 1-14, July.
    17. Alvarez, Sergio & Solis, Daniel & Hwang, Joonghyun, 2017. "An Economic Analysis of Shellfish Harvests Regulations for Food Safety," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252721, Southern Agricultural Economics Association.
    18. Xu, Qinfeng & You, Jinhong & Zhou, Bin, 2008. "Seemingly unrelated nonparametric models with positive correlation and constrained error variances," Economics Letters, Elsevier, vol. 99(2), pages 223-227, May.
    19. Naranjo, Andy & Protopapadakis, Aris, 1997. "Financial market integration tests: an investigation using US equity markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 7(2), pages 93-135, July.
    20. Mohammed Abdellaoui & Han Bleichrodt & Olivier l'Haridon & Corina Paraschiv, 2013. "Is There One Unifying Concept of Utility?An Experimental Comparison of Utility Under Risk and Utility Over Time," Management Science, INFORMS, vol. 59(9), pages 2153-2169, September.
    21. Francesco Fallucchi & Marc Kaufmann, 2021. "Narrow Bracketing in Work Choices," Papers 2101.04529, arXiv.org, revised Feb 2021.
    22. Azeez, A.A. & Yonezawa, Yasuhiro, 2006. "Macroeconomic factors and the empirical content of the Arbitrage Pricing Theory in the Japanese stock market," Japan and the World Economy, Elsevier, vol. 18(4), pages 568-591, December.
    23. Yuquan Chen & Xiaohua Yu, 2022. "Estimating market power for the Chinese fluid milk market with imported products," Agribusiness, John Wiley & Sons, Ltd., vol. 38(2), pages 386-401, April.
    24. Vasavada, Uptal & Fu, T.T., 1986. "The Role of Anticipated and Unanticipated Prices in Explaining Agricultural Supply Response," 1986 Annual Meeting, July 27-30, Reno, Nevada 278401, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    25. Marcela Munizaga & Sergio Jara-Díaz & Paulina Greeven & Chandra Bhat, 2008. "Econometric Calibration of the Joint Time Assignment--Mode Choice Model," Transportation Science, INFORMS, vol. 42(2), pages 208-219, May.
    26. Ana M. Bianco & Paula M. Spano, 2019. "Robust inference for nonlinear regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 369-398, June.
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    33. Amemiya, Takeshi, 1983. "Non-linear regression models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 1, chapter 6, pages 333-389, Elsevier.
    34. Zellner, Arnold & Ando, Tomohiro, 2010. "A direct Monte Carlo approach for Bayesian analysis of the seemingly unrelated regression model," Journal of Econometrics, Elsevier, vol. 159(1), pages 33-45, November.
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    37. Feng, Guohua & Serletis, Apostolos, 2008. "Productivity trends in U.S. manufacturing: Evidence from the NQ and AIM cost functions," Journal of Econometrics, Elsevier, vol. 142(1), pages 281-311, January.
    38. Korolev, Ivan, 2021. "Identification and estimation of the SEIRD epidemic model for COVID-19," Journal of Econometrics, Elsevier, vol. 220(1), pages 63-85.
    39. Cordeiro, Gauss M. & Vasconcellos, Klaus L. P., 1997. "Bias correction for a class of multivariate nonlinear regression models," Statistics & Probability Letters, Elsevier, vol. 35(2), pages 155-164, September.
    40. Julie Bertrand & Emmanuelle Comets & Marylore Chenel & France Mentré, 2012. "Some Alternatives to Asymptotic Tests for the Analysis of Pharmacogenetic Data Using Nonlinear Mixed Effects Models," Biometrics, The International Biometric Society, vol. 68(1), pages 146-155, March.
    41. Wagner, Martin & Grabarczyk, Peter & Hong, Seung Hyun, 2020. "Fully modified OLS estimation and inference for seemingly unrelated cointegrating polynomial regressions and the environmental Kuznets curve for carbon dioxide emissions," Journal of Econometrics, Elsevier, vol. 214(1), pages 216-255.
    42. Ana Rodríguez-Álvarez & Ignacio Rosal & José Baños-Pino, 2007. "The cost of strikes in the Spanish mining sector: modelling an undesirable input with a distance function," Journal of Productivity Analysis, Springer, vol. 27(1), pages 73-83, February.
    43. Bruno Feunou & Jean-Sébastien Fontaine, 2014. "Bond Risk Premia and Gaussian Term Structure Models," Staff Working Papers 14-13, Bank of Canada.
    44. Willem THORBECKE, 2019. "Oil Prices and the U.S. Economy: Evidence from the Stock Market," Discussion papers 19003, Research Institute of Economy, Trade and Industry (RIETI).
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Books

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    Cited by:

    1. Phaneuf, Daniel J. & Kling, Catherine L. & Herriges, Joseph A., 2000. "Estimation and Welfare Calculations in a Generalized Corner Solution Model with an Application to Recreation Demand," Staff General Research Papers Archive 1355, Iowa State University, Department of Economics.
    2. Harry H. Kelejian & Ingmar R. Prucha, 1997. "Estimation of Spatial Regression Models with Autoregressive Errors by Two-Stage Least Squares Procedures: A Serious Problem," International Regional Science Review, , vol. 20(1-2), pages 103-111, April.
    3. H. Kelejian, Harry & Prucha, Ingmar R., 2001. "On the asymptotic distribution of the Moran I test statistic with applications," Journal of Econometrics, Elsevier, vol. 104(2), pages 219-257, September.
    4. Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
    5. Jenish, Nazgul & Prucha, Ingmar R., 2009. "Central limit theorems and uniform laws of large numbers for arrays of random fields," Journal of Econometrics, Elsevier, vol. 150(1), pages 86-98, May.
    6. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    7. Chunrong Ai & Meixia Meng, 2011. "A locally linear estimation of regression discontinuity," Frontiers of Economics in China, Springer;Higher Education Press, vol. 6(4), pages 495-506, December.
    8. Chen, Ming-Hui & Ibrahim, Joseph G. & Sinha, Debajyoti, 2004. "A new joint model for longitudinal and survival data with a cure fraction," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 18-34, October.
    9. Benedikt M. Pötscher & Ingmar R. Prucha, 1999. "Basic Elements of Asymptotic Theory," Electronic Working Papers 99-001, University of Maryland, Department of Economics.
    10. Sun, Xiaoqian & He, Zhuoqiong & Kabrick, John, 2008. "Bayesian spatial prediction of the site index in the study of the Missouri Ozark Forest Ecosystem Project," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3749-3764, March.
    11. Escribano, Alvaro & Pfann, Gerard A., 1998. "Non-linear error correction, asymmetric adjustment and cointegration," Economic Modelling, Elsevier, vol. 15(2), pages 197-216, April.
    12. Jenish, Nazgul & Prucha, Ingmar R., 2012. "On spatial processes and asymptotic inference under near-epoch dependence," Journal of Econometrics, Elsevier, vol. 170(1), pages 178-190.

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