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Robert de jong

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.

Working papers

  1. Tiemen Woutersen & Robert M. de Jong, 2004. "Dynamic time series binary choice," Econometric Society 2004 North American Summer Meetings 365, Econometric Society.

    Cited by:

    1. Don Harding & Adrian Pagan, 2009. "An Econometric Analysis of Some Models for Constructed Binary Time Series," NCER Working Paper Series 39, National Centre for Econometric Research, revised 02 Jul 2009.
    2. Seo, Myung Hwan & Linton, Oliver, 2007. "A smoothed least squares estimator for threshold regression models," Journal of Econometrics, Elsevier, vol. 141(2), pages 704-735, December.
    3. Hahn, Jinyong & Kuersteiner, Guido, 2010. "Stationarity and mixing properties of the dynamic Tobit model," Economics Letters, Elsevier, vol. 107(2), pages 105-111, May.
    4. António R. Antunes & Diana Bonfim & Nuno Monteiro & Paulo M.M. Rodrigues, 2016. "Forecasting banking crises with dynamic panel probit models," Working Papers w201613, Banco de Portugal, Economics and Research Department.
    5. Christiansen, Charlotte & Eriksen, Jonas N. & Møller, Stig V., 2019. "Negative house price co-movements and US recessions," Regional Science and Urban Economics, Elsevier, vol. 77(C), pages 382-394.
    6. Lei, J., 2013. "Smoothed Spatial Maximum Score Estimation of Spatial Autoregressive Binary Choice Panel Models," Other publications TiSEM d63bf400-7ff2-4a1c-8067-1, Tilburg University, School of Economics and Management.
    7. Christophe Schalck & Meryem Yankol-Schalck, 2021. "Predicting French SME failures: new evidence from machine learning techniques," Applied Economics, Taylor & Francis Journals, vol. 53(51), pages 5948-5963, November.
    8. Geert Dhaene & Koen Jochmans, 2015. "Split-panel jackknife estimation of fixed-effect models," Post-Print hal-03392997, HAL.
    9. Siddhartha Chib & Michael J. Dueker, 2004. "Non-Markovian regime switching with endogenous states and time-varying state strengths," Working Papers 2004-030, Federal Reserve Bank of St. Louis.
    10. Frazier, David T. & Liu, Xiaochun, 2016. "A new approach to risk-return trade-off dynamics via decomposition," Journal of Economic Dynamics and Control, Elsevier, vol. 62(C), pages 43-55.
    11. Brown, David P. & Eckert, Andrew & Lin, James, 2018. "Information and Transparency in Wholesale Electricity Markets: Evidence from Alberta," Working Papers 2018-2, University of Alberta, Department of Economics.
    12. George Monokroussos, 2009. "A Classical MCMC Approach to the Estimation of Limited Dependent Variable Models of Time Series," Discussion Papers 09-07, University at Albany, SUNY, Department of Economics.
    13. Le-Yu Chen & Sokbae Lee, 2016. "Best Subset Binary Prediction," Papers 1610.02738, arXiv.org, revised May 2018.
    14. Nyberg, Henri & Pönkä, Harri, 2016. "International sign predictability of stock returns: The role of the United States," Economic Modelling, Elsevier, vol. 58(C), pages 323-338.
    15. Moysiadis, Theodoros & Fokianos, Konstantinos, 2014. "On binary and categorical time series models with feedback," Journal of Multivariate Analysis, Elsevier, vol. 131(C), pages 209-228.
    16. Pönkä, Harri & Stenborg, Markku, 2018. "Forecasting the state of the Finnish business cycle," MPRA Paper 91226, University Library of Munich, Germany.
    17. Nissilä, Wilma, 2020. "Probit based time series models in recession forecasting – A survey with an empirical illustration for Finland," BoF Economics Review 7/2020, Bank of Finland.
    18. Benjamin Williams, 2018. "Identification of a Nonseparable Model under Endogeneity using Binary Proxies for Unobserved Heterogeneity," Working Papers 2018-003, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    19. Moreira, Afonso M. & Martins, Luis F., 2020. "A new mechanism for anticipating price exuberance," International Review of Economics & Finance, Elsevier, vol. 65(C), pages 199-221.
    20. Park, Byeong U. & Simar, Léopold & Zelenyuk, Valentin, 2017. "Nonparametric estimation of dynamic discrete choice models for time series data," Computational Statistics & Data Analysis, Elsevier, vol. 108(C), pages 97-120.
    21. Harri Ponka, 2017. "The Role of Credit in Predicting US Recessions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(5), pages 469-482, August.
    22. Stanislav Anatolyev & Nikolay Gospodinov, 2007. "Modeling Financial Return Dynamics by Decomposition," Working Papers w0095, New Economic School (NES).
    23. Taisuke Otsu & Myung Hwan Seo, 2014. "Asymptotics for maximum score method under general conditions," STICERD - Econometrics Paper Series 571, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    24. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    25. Taylor, James W., 2017. "Probabilistic forecasting of wind power ramp events using autoregressive logit models," European Journal of Operational Research, Elsevier, vol. 259(2), pages 703-712.
    26. Jean-Yves Gnabo & Luiz de Mello & Diego Moccero, 2008. "Interdependencies between Monetary Policy and Foreign Exchange Intervention under Inflation Targeting: The Case of Brazil and the Czech Republic," WIDER Working Paper Series RP2008-95, World Institute for Development Economic Research (UNU-WIDER).
    27. Schumann, Martin & Severini, Thomas A. & Tripathi, Gautam, 2023. "The role of score and information bias in panel data likelihoods," Journal of Econometrics, Elsevier, vol. 235(2), pages 1215-1238.
    28. Truquet, Lionel, 2023. "Strong mixing properties of discrete-valued time series with exogenous covariates," Stochastic Processes and their Applications, Elsevier, vol. 160(C), pages 294-317.
    29. James W. Taylor & Keming Yu, 2016. "Using auto-regressive logit models to forecast the exceedance probability for financial risk management," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(4), pages 1069-1092, October.
    30. Anatolyev Stanislav, 2009. "Multi-Market Direction-of-Change Modeling Using Dependence Ratios," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(1), pages 1-24, March.
    31. Freitag, L., 2014. "Procyclicality and path dependence of sovereign credit ratings: The example of Europe," Research Memorandum 020, Maastricht University, Graduate School of Business and Economics (GSBE).
    32. Igor Kheifets & Carlos Velasco, 2012. "Model Adequacy Checks for Discrete Choice Dynamic Models," Working Papers w0170, New Economic School (NES).
    33. Michel, Jon & de Jong, Robert M., 2018. "Mixing properties of the dynamic Tobit model with mixing errors," Economics Letters, Elsevier, vol. 162(C), pages 112-115.
    34. Fokianos, Konstantinos & Moysiadis, Theodoros, 2017. "Binary time series models driven by a latent process," Econometrics and Statistics, Elsevier, vol. 2(C), pages 117-130.
    35. Yang Lu, 2020. "A simple parameter‐driven binary time series model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 187-199, March.
    36. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.
    37. Lei, J., 2013. "Smoothed Spatial Maximum Score Estimation of Spatial Autoregressive Binary Choice Panel Models," Discussion Paper 2013-061, Tilburg University, Center for Economic Research.
    38. Dardanoni, Valentino & Li Donni, Paolo, 2012. "Incentive and selection effects of Medigap insurance on inpatient care," Journal of Health Economics, Elsevier, vol. 31(3), pages 457-470.
    39. Woutersen, Tiemen & Hausman, Jerry A., 2019. "Increasing the power of specification tests," Journal of Econometrics, Elsevier, vol. 211(1), pages 166-175.
    40. Francis Bismans & Reynald Majetti, 2013. "Forecasting recessions using financial variables: the French case," Empirical Economics, Springer, vol. 44(2), pages 419-433, April.
    41. Gnabo, Jean-Yves & Laurent, Sébastien & Lecourt, Christelle, 2009. "Does transparency in central bank intervention policy bring noise to the FX market?: The case of the Bank of Japan," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(1), pages 94-111, February.
    42. Manner, Hans & Türk, Dennis & Eichler, Michael, 2016. "Modeling and forecasting multivariate electricity price spikes," Energy Economics, Elsevier, vol. 60(C), pages 255-265.
    43. Sadikoglu, Serhan, 2019. "Essays in econometric theory," Other publications TiSEM 99d83644-f9dc-49e3-a4e1-5, Tilburg University, School of Economics and Management.
    44. Park, Byeong U. & Simar, Leopold & Zelenyuk, Valentin, 2013. "Non-Parametric Approach to Dynamic Time Series Discrete Choice Models," LIDAM Discussion Papers ISBA 2013052, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    45. Leung, Michael P., 2019. "A weak law for moments of pairwise stable networks," Journal of Econometrics, Elsevier, vol. 210(2), pages 310-326.
    46. Fokianos, Konstantinos & Truquet, Lionel, 2019. "On categorical time series models with covariates," Stochastic Processes and their Applications, Elsevier, vol. 129(9), pages 3446-3462.
    47. Brause, Alexander, 2008. "Foreign exchange interventions in emerging market countries: New lessons from Argentina," W.E.P. - Würzburg Economic Papers 79, University of Würzburg, Department of Economics.
    48. Chen, Songnian & Zhang, Hanghui, 2015. "Binary quantile regression with local polynomial smoothing," Journal of Econometrics, Elsevier, vol. 189(1), pages 24-40.
    49. Liu, Xiaochun & Luger, Richard, 2015. "Unfolded GARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 186-217.

  2. Robert de Jong, 2004. "Nonlinear estimators with integrated regressors but without exogeneity," Econometric Society 2004 North American Winter Meetings 324, Econometric Society.

    Cited by:

    1. Ioannis Kasparis & Peter C.B. Phillips & Tassos Magdalinos, 2012. "Non-linearity Induced Weak Instrumentation," University of Cyprus Working Papers in Economics 02-2012, University of Cyprus Department of Economics.
    2. Hong, Seung Hyun & Wagner, Martin, 2011. "Cointegrating Polynomial Regressions," Economics Series 264, Institute for Advanced Studies.
    3. Seung Hyun Hong & Peter C. B. Phillips, 2005. "Testing Linearity in Cointegrating Relations with an Application to Purchasing Power Parity," Cowles Foundation Discussion Papers 1541, Cowles Foundation for Research in Economics, Yale University.
    4. Jesús Gonzalo & Jean‐Yves Pitarakis, 2006. "Threshold Effects in Cointegrating Relationships," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 813-833, December.
    5. Shi, Xiaoxia & Phillips, Peter C.B., 2012. "Nonlinear Cointegrating Regression Under Weak Identification," Econometric Theory, Cambridge University Press, vol. 28(3), pages 509-547, June.

  3. de Jong, R.M. & Davidson, J., 1996. "Consistency of Kernel Estimators of Heteroscedastic and Autocorrelated Covariance Matrices," Discussion Paper 1996-52, Tilburg University, Center for Economic Research.

    Cited by:

    1. Oliver Linton & Michael Vogt, 2012. "Nonparametric estimation of a periodic sequence in the presence of a smooth trend," CeMMAP working papers 23/12, Institute for Fiscal Studies.
    2. David I. Harvey & Stephen J. Leybourne & Yang Zu, 2024. "Tests for equal forecast accuracy under heteroskedasticity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 850-869, August.
    3. Paulo Parente & Richard J. Smith, 2019. "Quasi-maximum likelihood and the kernel block bootstrap for nonlinear dynamic models," CeMMAP working papers CWP60/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Kourogenis, Nikolaos & Pittis, Nikitas, 2010. "Unbounded heteroscedasticity in first-order autoregressive models and the Eicker-White asymptotic variance estimator," Economics Letters, Elsevier, vol. 106(2), pages 84-86, February.
    5. Luciano de Castro & Antonio F. Galvao & David M. Kaplan & Xin Liu, 2017. "Smoothed GMM for quantile models," Papers 1707.03436, arXiv.org, revised Feb 2018.
    6. Calhoun, Gray, 2014. "Out-Of-Sample Comparisons of Overfit Models," Staff General Research Papers Archive 32462, Iowa State University, Department of Economics.
    7. Casini, Alessandro, 2023. "Theory of evolutionary spectra for heteroskedasticity and autocorrelation robust inference in possibly misspecified and nonstationary models," Journal of Econometrics, Elsevier, vol. 235(2), pages 372-392.
    8. Michael Vogt & Oliver Linton, 2018. "Multiscale clustering of nonparametric regression curves," CeMMAP working papers CWP08/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Goncalves, Silvia & de Jong, Robert, 2003. "Consistency of the stationary bootstrap under weak moment conditions," Economics Letters, Elsevier, vol. 81(2), pages 273-278, November.
    10. Lea Wegner & Martin Wendler, 2024. "Robust change-point detection for functional time series based on U-statistics and dependent wild bootstrap," Statistical Papers, Springer, vol. 65(7), pages 4767-4810, September.
    11. Jason Allen & Allan Gregory & Katsumi Shimotsu, 2008. "Empirical Likelihood Block Bootstrapping," Staff Working Papers 08-18, Bank of Canada.
    12. Davidson, James, 2020. "A new consistency proof for HAC variance estimators," Economics Letters, Elsevier, vol. 186(C).
    13. Katsumi Shimotsu, 2006. "Simple (but Effective) Tests Of Long Memory Versus Structural Breaks," Working Paper 1101, Economics Department, Queen's University.
    14. Linton, Oliver, 2004. "Nonparametric inference for unbalanced time series data," LSE Research Online Documents on Economics 2116, London School of Economics and Political Science, LSE Library.
    15. Hill, Jonathan B. & Aguilar, Mike, 2013. "Moment condition tests for heavy tailed time series," Journal of Econometrics, Elsevier, vol. 172(2), pages 255-274.
    16. Giuseppe Cavaliere, 2002. "Bounded integrated processes and unit root tests," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(1), pages 41-69, February.
    17. Liu, Xiaobin & Li, Yong & Yu, Jun & Zeng, Tao, 2022. "Posterior-based Wald-type statistics for hypothesis testing," Journal of Econometrics, Elsevier, vol. 230(1), pages 83-113.
    18. Pelagatti, Matteo M. & Sen, Pranab K., 2013. "Rank tests for short memory stationarity," Journal of Econometrics, Elsevier, vol. 172(1), pages 90-105.
    19. Ghysels, Eric & Hill, Jonathan B. & Motegi, Kaiji, 2013. "Testing for Granger Causality with Mixed Frequency Data," CEPR Discussion Papers 9655, C.E.P.R. Discussion Papers.
    20. Cho, Cheol-Keun & Amsler, Christine & Schmidt, Peter, 2015. "A test of the null of integer integration against the alternative of fractional integration," Journal of Econometrics, Elsevier, vol. 187(1), pages 217-237.
    21. Lu, Ye & Park, Joon Y., 2019. "Estimation of longrun variance of continuous time stochastic process using discrete sample," Journal of Econometrics, Elsevier, vol. 210(2), pages 236-267.
    22. Jonathan B. Hill & Artyom Shneyerov, 2009. "Are There Common Values in BC Timber Sales? A Tail-Index Nonparametric Test," Working Papers 09003, Concordia University, Department of Economics.
    23. Francisco Peñaranda & Enrique Sentana, 2015. "A Unifying Approach to the Empirical Evaluation of Asset Pricing Models," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 412-435, May.
    24. Yoon-Jae Whang & Oliver Linton, 1997. "The Asymptotic Distribution of Nonparametric Estimates of the Lyapunov Exponent for Stochastic Time Series," Cowles Foundation Discussion Papers 1130R, Cowles Foundation for Research in Economics, Yale University.
    25. Alessandro Casini & Pierre Perron, 2021. "Prewhitened Long-Run Variance Estimation Robust to Nonstationarity," Papers 2103.02235, arXiv.org, revised Aug 2024.
    26. Casini, Alessandro, 2024. "The fixed-b limiting distribution and the ERP of HAR tests under nonstationarity," Journal of Econometrics, Elsevier, vol. 238(2).
    27. Xiao, Zhijie & Lima, Luiz Renato Regis de Oliveira, 2006. "Testing covariance stationarity," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 632, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    28. Sun, Yixiao & Phillips, Peter C.B. & Jin, Sainan, 2011. "Power Maximization And Size Control In Heteroskedasticity And Autocorrelation Robust Tests With Exponentiated Kernels," Econometric Theory, Cambridge University Press, vol. 27(6), pages 1320-1368, December.
    29. Nawaz, Nasreen, 2017. "Robust Inference by Sub-sampling," MPRA Paper 116721, University Library of Munich, Germany, revised 08 Jun 2019.
    30. Tony Lancaster, 2006. "A note on bootstraps and robustness," CeMMAP working papers CWP04/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    31. Amsler Christine & Schmidt Peter, 2012. "A Comparison of the Robustness of Several Tests of Short Memory to Autocorrelated Errors," Journal of Econometric Methods, De Gruyter, vol. 1(1), pages 56-66, August.
    32. Yannick Hoga, 2022. "Quantifying the data-dredging bias in structural break tests," Statistical Papers, Springer, vol. 63(1), pages 143-155, February.
    33. Michael Jansson & Marcelo J. Moreira, 2006. "Optimal Inference in Regression Models with Nearly Integrated Regressors," Econometrica, Econometric Society, vol. 74(3), pages 681-714, May.
    34. Boonsoo Koo & Myung Hwan Seo, 2013. "Structural-break models under mis-specification: implications for forecasting," Monash Econometrics and Business Statistics Working Papers 11/13, Monash University, Department of Econometrics and Business Statistics.
    35. Yixiao Sun & Peter C.B. Phillips, 2008. "Optimal Bandwidth Choice for Interval Estimation in GMM Regression," Cowles Foundation Discussion Papers 1661, Cowles Foundation for Research in Economics, Yale University.
    36. de Jong, Robert M., 2002. "Nonlinear minimization estimators in the presence of cointegrating relations," Journal of Econometrics, Elsevier, vol. 110(2), pages 241-259, October.
    37. J. Isaac Miller, 2010. "Cointegrating regressions with messy regressors and an application to mixed‐frequency series," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 255-277, July.
    38. Li, Jia & Liao, Zhipeng, 2020. "Uniform nonparametric inference for time series," Journal of Econometrics, Elsevier, vol. 219(1), pages 38-51.
    39. Enrique Sentana & Francisco Penaranda, 2004. "Spanning Tests in Return and Stochastic Discount Factor Mean-Variance Frontiers: A Unifying Approach," FMG Discussion Papers dp497, Financial Markets Group.
    40. Michael Vogt & Oliver Linton, 2014. "Nonparametric estimation of a periodic sequence in the presence of a smooth trend," Biometrika, Biometrika Trust, vol. 101(1), pages 121-140.
    41. Hill, Jonathan B. & Shneyerov, Artyom, 2013. "Are there common values in first-price auctions? A tail-index nonparametric test," Journal of Econometrics, Elsevier, vol. 174(2), pages 144-164.
    42. Giraitis, Liudas & Kokoszka, Piotr & Leipus, Remigijus & Teyssiere, Gilles, 2003. "Rescaled variance and related tests for long memory in volatility and levels," Journal of Econometrics, Elsevier, vol. 112(2), pages 265-294, February.
    43. Osadolor Ebhuoma & Michael Gebreslasie, 2016. "Remote Sensing-Driven Climatic/Environmental Variables for Modelling Malaria Transmission in Sub-Saharan Africa," IJERPH, MDPI, vol. 13(6), pages 1-29, June.
    44. Federico Belotti & Alessandro Casini & Leopoldo Catania & Stefano Grassi & Pierre Perron, 2021. "Simultaneous Bandwidths Determination for DK-HAC Estimators and Long-Run Variance Estimation in Nonparametric Settings," Papers 2103.00060, arXiv.org.
    45. Kourogenis, Nikolaos & Pittis, Nikitas & Samartzis, Panagiotis, 2024. "Unbounded heteroscedasticity in autoregressive models," The Journal of Economic Asymmetries, Elsevier, vol. 29(C).
    46. Hirukawa, Masayuki, 2023. "Robust Covariance Matrix Estimation in Time Series: A Review," Econometrics and Statistics, Elsevier, vol. 27(C), pages 36-61.
    47. Schnurr, Alexander & Fischer, Svenja, 2022. "Generalized ordinal patterns allowing for ties and their applications in hydrology," Computational Statistics & Data Analysis, Elsevier, vol. 171(C).
    48. Christis Hassapis, 2003. "Financial variables and real activity in Canada," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 36(2), pages 421-442, May.
    49. Dehling, Herold & Fried, Roland & Sharipov, Olimjon Sh. & Vogel, Daniel & Wornowizki, Max, 2013. "Estimation of the variance of partial sums of dependent processes," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 141-147.
    50. J. Isaac Miller, 2010. "A Nonlinear IV Likelihood-Based Rank Test for Multivariate Time Series and Long Panels," Working Papers 1001, Department of Economics, University of Missouri.
    51. Tobias Fissler & Yannick Hoga, 2021. "Backtesting Systemic Risk Forecasts using Multi-Objective Elicitability," Papers 2104.10673, arXiv.org, revised Feb 2022.
    52. Smeekes, S. & Urbain, J.R.Y.J., 2014. "A multivariate invariance principle for modified wild bootstrap methods with an application to unit root testing," Research Memorandum 008, Maastricht University, Graduate School of Business and Economics (GSBE).
    53. Luke Hartigan, 2016. "Alternative HAC Covariance Matrix Estimators with Improved Finite Sample Properties," Discussion Papers 2016-06, School of Economics, The University of New South Wales.
    54. Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Antoine Djogbenou & Sílvia Gonçalves & Benoit Perron, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 481-502, May.
    55. Li, Yong & Yu, Jun & Zeng, Tao, 2020. "Deviance information criterion for latent variable models and misspecified models," Journal of Econometrics, Elsevier, vol. 216(2), pages 450-493.
    56. Robert M. deJong, 2000. "Nonlinear Minimization Estimators in the Presence of Cointegrating Relations," Econometric Society World Congress 2000 Contributed Papers 1651, Econometric Society.
    57. Cheol-Keun Cho & Timothy J. Vogelsang, 2016. "Fixed- b Inference for Testing Structural Change in a Time Series Regression," Econometrics, MDPI, vol. 5(1), pages 1-26, December.
    58. J. Isaac Miller, 2007. "Cointegrating Regressions with Messy Regressors: Missingness, Mixed Frequency, and Measurement Error," Working Papers 0722, Department of Economics, University of Missouri, revised 15 Apr 2009.
    59. Luciano de Castro & Antonio F. Galvao & David M. Kaplan, 2017. "Smoothed instrumental variables quantile regression, with estimation of quantile Euler equations," Working Papers 1710, Department of Economics, University of Missouri, revised 28 Feb 2018.
    60. Wied, Dominik & Dehling, Herold & van Kampen, Maarten & Vogel, Daniel, 2014. "A fluctuation test for constant Spearman’s rho with nuisance-free limit distribution," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 723-736.
    61. Muller, Ulrich K., 2007. "A theory of robust long-run variance estimation," Journal of Econometrics, Elsevier, vol. 141(2), pages 1331-1352, December.
    62. Jean-michel Sahut & Medhi Mili & Frédéric Teulon, 2012. "What is the linkage between real growth in the Euro area and global financial market conditions?," Economics Bulletin, AccessEcon, vol. 32(3), pages 2464-2480.
    63. Francq, Christian & Zakoïan, Jean-Michel, 2007. "HAC estimation and strong linearity testing in weak ARMA models," Journal of Multivariate Analysis, Elsevier, vol. 98(1), pages 114-144, January.
    64. Dominik Wied & Matthias Arnold & Nicolai Bissantz & Daniel Ziggel, 2012. "A new fluctuation test for constant variances with applications to finance," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(8), pages 1111-1127, November.
    65. Kelejian, Harry H. & Prucha, Ingmar R., 2007. "HAC estimation in a spatial framework," Journal of Econometrics, Elsevier, vol. 140(1), pages 131-154, September.
    66. Peter C.B. Phillips & Yixiao Sun & Sainan Jin, 2005. "Improved HAR Inference," Cowles Foundation Discussion Papers 1513, Cowles Foundation for Research in Economics, Yale University.
    67. Yasutomo Murasawa, 2009. "Do coincident indicators have one-factor structure?," Empirical Economics, Springer, vol. 36(2), pages 339-365, May.
    68. Gilbert, Paul D. & Meijer, Erik, 2005. "Time Series Factor Analysis with an Application to Measuring Money," Research Report 05F10, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    69. Yun Feng & Xin Li, 2021. "Does cross-shareholding lead to China's stock returns comovement? Evidence from a GMM-based spatial AR model," Empirical Economics, Springer, vol. 61(6), pages 3213-3237, December.
    70. Matthias Arnold & Sebastian Stahlberg & Dominik Wied, 2013. "Modeling different kinds of spatial dependence in stock returns," Empirical Economics, Springer, vol. 44(2), pages 761-774, April.
    71. Oliver Linton, 2004. "Nonparametric inference for unbalance time series data," CeMMAP working papers 06/04, Institute for Fiscal Studies.
    72. Massimiliano Marcellino & Barbara Rossi, 2008. "Model Selection for Nested and Overlapping Nonlinear, Dynamic and Possibly Mis‐specified Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 867-893, December.

Articles

  1. Sakarya, Neslihan & de Jong, Robert M., 2020. "A Property Of The Hodrick–Prescott Filter And Its Application," Econometric Theory, Cambridge University Press, vol. 36(5), pages 840-870, October.

    Cited by:

    1. Peter C. B. Phillips & Zhentao Shi, 2021. "Boosting: Why You Can Use The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 521-570, May.
    2. Nadav Ben Zeev, 2019. "Asymmetric Business Cycles In Emerging Market Economies," Working Papers 1909, Ben-Gurion University of the Negev, Department of Economics.
    3. Ziwei Mei & Zhentao Shi & Peter C. B. Phillips, 2022. "The boosted HP filter is more general than you might think," Cowles Foundation Discussion Papers 2348, Cowles Foundation for Research in Economics, Yale University.
    4. Peter C. B. Phillips & Sainan Jin, 2021. "Business Cycles, Trend Elimination, And The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 469-520, May.
    5. Germaschewski, Yin & Horvath, Jaroslav & Rubini, Loris, 2021. "Property rights, expropriations, and business cycles in China," Journal of Economic Dynamics and Control, Elsevier, vol. 125(C).
    6. Germaschewski, Yin & Wang, Shu-Ling, 2022. "Fiscal stabilization in high-debt economies without monetary independence," Journal of Macroeconomics, Elsevier, vol. 72(C).
    7. Neslihan Sakarya & Robert M. de Jong, 2022. "The spectral analysis of the Hodrick–Prescott filter," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(3), pages 479-489, May.
    8. Ye Lu & Adrian Pagan, 2023. "To Boost or Not to Boost? That is the Question," Working Papers 2023-05, University of Sydney, School of Economics.
    9. Hiroshi Yamada, 2023. "Quantile regression version of Hodrick–Prescott filter," Empirical Economics, Springer, vol. 64(4), pages 1631-1645, April.
    10. Yin Germaschewski, 2023. "House price volatility in China: Demand versus supply," Economic Inquiry, Western Economic Association International, vol. 61(1), pages 199-220, January.
    11. Hiroshi Yamada & Ruoyi Bao, 2022. "$$\ell _{1}$$ ℓ 1 Common Trend Filtering," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1005-1025, March.

  2. Michel, Jon & de Jong, Robert M., 2018. "Mixing properties of the dynamic Tobit model with mixing errors," Economics Letters, Elsevier, vol. 162(C), pages 112-115.

    Cited by:

    1. Michel, Jon & de Jong, Robert M., 2019. "A model for level induced conditional heteroskedasticity," Statistics & Probability Letters, Elsevier, vol. 145(C), pages 293-300.
    2. Bykhovskaya, Anna & Duffy, James A., 2024. "The local to unity dynamic Tobit model," Journal of Econometrics, Elsevier, vol. 241(2).
    3. Anna Bykhovskaya & James A. Duffy, 2022. "The Local to Unity Dynamic Tobit Model," Papers 2210.02599, arXiv.org, revised May 2024.

  3. Zhang Jing & de Jong Robert & Haurin Donald, 2016. "Are US real house prices stationary? New evidence from univariate and panel data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(1), pages 1-18, February.

    Cited by:

    1. Giorgio Canarella & Luis Gil-Alana & Rangan Gupta & Stephen M Miller, 2021. "Persistence and cyclical dynamics of US and UK house prices: Evidence from over 150 years of data," Urban Studies, Urban Studies Journal Limited, vol. 58(1), pages 53-72, January.
    2. David Gray, 2021. "A simple measure of beta-convergence revisited," Urban Studies, Urban Studies Journal Limited, vol. 58(12), pages 2569-2583, September.
    3. Marina Khismatullina & Michael Vogt, 2022. "Multiscale Comparison of Nonparametric Trend Curves," Papers 2209.10841, arXiv.org.

  4. Robert M. de Jong & Neslihan Sakarya, 2016. "The Econometrics of the Hodrick-Prescott Filter," The Review of Economics and Statistics, MIT Press, vol. 98(2), pages 310-317, May.

    Cited by:

    1. Courage Mlambo, 2022. "Non-Renewable Resources and Sustainable Resource Extraction: An Empirical Test of the Hotelling Rule’s Significance to Gold Extraction in South Africa," Sustainability, MDPI, vol. 14(17), pages 1-17, August.
    2. Francesco Giancaterini & Alain Hecq & Claudio Morana, 2022. "Is climate change time reversible?," Papers 2205.07579, arXiv.org, revised Nov 2022.
    3. Xie, Pinjie & Shu, Yalin & Sun, Feihu & Pan, Xianyou, 2024. "Enhancing the accuracy of China's electricity consumption forecasting through economic cycle division: An MSAR-OPLS scenario analysis," Energy, Elsevier, vol. 293(C).
    4. Joseph G. Haubrich, 2020. "How Cyclical Is Bank Capital?," Journal of Financial Services Research, Springer;Western Finance Association, vol. 58(1), pages 27-38, August.
    5. Faria, Gonçalo & Verona, Fabio, 2020. "The yield curve and the stock market: Mind the long run," Journal of Financial Markets, Elsevier, vol. 50(C).
    6. Dan Armeanu & Georgiana Camelia Crețan & Leonard Lache & Mihaela Mitroi, 2015. "Estimating Potential GDP for the Romanian Economy and Assessing the Sustainability of Economic Growth: A Multivariate Filter Approach," Sustainability, MDPI, vol. 7(3), pages 1-21, March.
    7. Hall, Viv B & Thomson, Peter, 2022. "A boosted HP filter for business cycle analysis: evidence from New Zealand’s small open economy," Working Paper Series 21184, Victoria University of Wellington, School of Economics and Finance.
    8. Ziwei Mei & Zhentao Shi & Peter C. B. Phillips, 2022. "The boosted HP filter is more general than you might think," Cowles Foundation Discussion Papers 2348, Cowles Foundation for Research in Economics, Yale University.
    9. Małgorzata Iwanicz-Drozdowska & Paola Bongini & Paweł Smaga & Bartosz Witkowski, 2019. "The role of banks in CESEE countries: exploring non-standard determinants of economic growth," Post-Communist Economies, Taylor & Francis Journals, vol. 31(3), pages 349-382, May.
    10. Sokbae Lee & Yuan Liao & Myung Hwan Seo & Youngki Shin, 2020. "Sparse HP Filter: Finding Kinks in the COVID-19 Contact Rate," Department of Economics Working Papers 2020-06, McMaster University.
    11. Sabaj, Ernil, 2018. "Cyclical Behavior of Fiscal Policy in the Western Balkans," MPRA Paper 84279, University Library of Munich, Germany.
    12. Yang, Jinyu & Dong, Dayong & Liang, Chao, 2024. "Climate policy uncertainty and the U.S. economic cycle," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    13. Hall, Viv B & Thomson, Peter, 2020. "Does Hamilton’s OLS regression provide a “better alternative” to the Hodrick-Prescott filter? A New Zealand Business Cycle Perspective," Working Paper Series 21070, Victoria University of Wellington, School of Economics and Finance.
    14. Alain Hecq & Elisa Voisin, 2019. "Predicting crashes in oil prices during the COVID-19 pandemic with mixed causal-noncausal models," Papers 1911.10916, arXiv.org, revised May 2022.
    15. Sergio Destefanis & Matteo Fragetta & Emanuel Gasteiger, 2024. "Does one size fit all in the Euro Area? Some counterfactual evidence," Empirical Economics, Springer, vol. 67(4), pages 1615-1647, October.
    16. Maranzano, Paolo & Pelagatti, Matteo, 2024. "A Hodrick-Prescott filter with automatically selected jumps," FEEM Working Papers 344134, Fondazione Eni Enrico Mattei (FEEM).
    17. Tang, Ying & Li, Zhiyong & Chen, Jing & Deng, Chao, 2021. "Liquidity creation cyclicality, capital regulation and interbank credit: Evidence from Chinese commercial banks," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    18. Neslihan Sakarya & Robert M. de Jong, 2022. "The spectral analysis of the Hodrick–Prescott filter," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(3), pages 479-489, May.
    19. Ben Amar, Amine & Goutte, Stéphane & Isleimeyyeh, Mohammad, 2022. "Asymmetric cyclical connectedness on the commodity markets: Further insights from bull and bear markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 386-400.
    20. Nghiem, Son & Tran, Bach & Afoakwah, Clifford & Byrnes, Joshua & Scuffham, Paul, 2021. "Wealthy, healthy and green: Are we there yet?," World Development, Elsevier, vol. 147(C).
    21. Ye Lu & Adrian Pagan, 2023. "To Boost or Not to Boost? That is the Question," Working Papers 2023-05, University of Sydney, School of Economics.
    22. Patricia Aranda-Cuéllar & José María López-Morales & María Jesús Such-Devesa, 2021. "Winter tourism dependence: A cyclical and cointegration analysis. Case study for the Alps," Tourism Economics, , vol. 27(7), pages 1540-1560, November.
    23. Haitham A. Al-Zoubi, 2024. "An affine model for short rates when monetary policy is path dependent," Review of Derivatives Research, Springer, vol. 27(2), pages 151-201, July.
    24. Carnazza, Giovanni & Liberati, Paolo & Sacchi, Agnese, 2020. "The cyclically-adjusted primary balance: A novel approach for the euro area," Journal of Policy Modeling, Elsevier, vol. 42(5), pages 1123-1145.
    25. Schüler, Yves S., 2018. "On the cyclical properties of Hamilton's regression filter," Discussion Papers 03/2018, Deutsche Bundesbank.
    26. Egon Smeral, 2019. "Seasonal forecasting performance considering varying income elasticities in tourism demand," Tourism Economics, , vol. 25(3), pages 355-374, May.
    27. Jylhä, Petri & Lof, Matthijs, 2022. "Mind the Basel gap," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    28. Niţoi, Mihai & Pochea, Maria Miruna, 2016. "Testing financial markets convergence in Central and Eastern Europe: A non-linear single factor model," Economic Systems, Elsevier, vol. 40(2), pages 323-334.
    29. Cassetta, Ernesto & Nava, Consuelo R. & Zoia, Maria Grazia, 2022. "EU electricity market integration and cross-country convergence in residential and industrial end-user prices," Energy Policy, Elsevier, vol. 165(C).
    30. Hiroshi Yamada, 2023. "Quantile regression version of Hodrick–Prescott filter," Empirical Economics, Springer, vol. 64(4), pages 1631-1645, April.
    31. Dorel Dusmanescu & Jean Andrei & Gheorghe H. Popescu & Elvira Nica & Mirela Panait, 2016. "Heuristic Methodology for Estimating the Liquid Biofuel Potential of a Region," Energies, MDPI, vol. 9(9), pages 1-19, August.
    32. Melina Dritsaki & Chaido Dritsaki, 2022. "Comparison of HP Filter and the Hamilton’s Regression," Mathematics, MDPI, vol. 10(8), pages 1-18, April.
    33. Cassetta, Ernesto & Nava, Consuelo R. & Zoia, Maria Grazia, 2022. "A three-step procedure to investigate the convergence of electricity and natural gas prices in the European Union," Energy Economics, Elsevier, vol. 105(C).
    34. Al-Zoubi, Haitham A., 2019. "Bond and option prices with permanent shocks," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 272-290.
    35. AMENDOLA, Adalgiso & DI SERIO, Mario & FRAGETTA, Matteo, 2018. "The Government Spending Multiplier at the Zero Lower Bound: Evidence from the Euro Area," CELPE Discussion Papers 153, CELPE - CEnter for Labor and Political Economics, University of Salerno, Italy.
    36. Alain Hecq & Sean Telg & Lenard Lieb, 2017. "Do Seasonal Adjustments Induce Noncausal Dynamics in Inflation Rates?," Econometrics, MDPI, vol. 5(4), pages 1-22, October.
    37. Yener Coskun & Nicholas Apergis & Esra Alp Coskun, 2022. "Nonlinear responses of consumption to wealth, income, and interest rate shocks," Empirical Economics, Springer, vol. 63(3), pages 1293-1335, September.
    38. Kanayo Ogujiuba & Terfa W Abraham & Nancy Stiegler, 2016. "Does Seasonality and Stochastic Cycles Affect Output Growth in Nigeria? Lessons for Development Planning," Journal of Economics and Behavioral Studies, AMH International, vol. 8(3), pages 48-53.
    39. Lolić, Ivana & Matošec, Marina & Sorić, Petar, 2024. "DIY google trends indicators in social sciences: A methodological note," Technology in Society, Elsevier, vol. 77(C).
    40. Hiroshi Yamada & Ruoyi Bao, 2022. "$$\ell _{1}$$ ℓ 1 Common Trend Filtering," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1005-1025, March.
    41. Carneiro,Francisco Galrao & Garrido,Leonardo, 2015. "New evidence on the cyclicality of fiscal policy," Policy Research Working Paper Series 7293, The World Bank.
    42. Wolf, Elias & Mokinski, Frieder & Schüler, Yves, 2020. "On adjusting the one-sided Hodrick-Prescott filter," Discussion Papers 11/2020, Deutsche Bundesbank.

  5. Yu, Jihai & de Jong, Robert & Lee, Lung-fei, 2012. "Estimation for spatial dynamic panel data with fixed effects: The case of spatial cointegration," Journal of Econometrics, Elsevier, vol. 167(1), pages 16-37.

    Cited by:

    1. Baltagi, Badi H. & Fingleton, Bernard & Pirotte, Alain, 2019. "A time-space dynamic panel data model with spatial moving average errors," Regional Science and Urban Economics, Elsevier, vol. 76(C), pages 13-31.
    2. Ciccarelli, Carlo & Elhorst, J.Paul, 2018. "A dynamic spatial econometric diffusion model with common factors: The rise and spread of cigarette consumption in Italy," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 131-142.
    3. Lee, Lung-fei & Yu, Jihai, 2015. "Estimation of fixed effects panel regression models with separable and nonseparable space–time filters," Journal of Econometrics, Elsevier, vol. 184(1), pages 174-192.
    4. Anna Gloria Billé & Marco Rogna, 2022. "The effect of weather conditions on fertilizer applications: A spatial dynamic panel data analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(1), pages 3-36, January.
    5. Michele Aquaro & Natalia Bailey & M. Hashem Pesaran, 2019. "Estimation and inference for spatial models with heterogeneous coefficients: an application to U.S. house prices," CESifo Working Paper Series 7542, CESifo.
    6. Luo, Guowang & Wu, Mixia & Pang, Zhen, 2022. "Estimation of spatial autoregressive models with covariate measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    7. LeSage, James P. & Chih, Yao-Yu & Vance, Colin, 2019. "Markov Chain Monte Carlo estimation of spatial dynamic panel models for large samples," Computational Statistics & Data Analysis, Elsevier, vol. 138(C), pages 107-125.
    8. Reuvers, Hanno & Wijler, Etienne, 2024. "Sparse generalized Yule–Walker estimation for large spatio-temporal autoregressions with an application to NO2 satellite data," Journal of Econometrics, Elsevier, vol. 239(1).
    9. Jin, Fei & Lee, Lung-fei & Yu, Jihai, 2020. "First difference estimation of spatial dynamic panel data models with fixed effects," Economics Letters, Elsevier, vol. 189(C).
    10. Xianghong Zhou & Weiwei Chen, 2021. "The Impact of Informatization on the Relationship between the Tourism Industry and Regional Economic Development," Sustainability, MDPI, vol. 13(16), pages 1-23, August.
    11. Salvatore Costantino & Maria Francesca Cracolici & J. Paul Elhorst, 2023. "A spatial origin‐destination approach for the analysis of local tourism demand in Italy," Papers in Regional Science, Wiley Blackwell, vol. 102(2), pages 393-419, April.
    12. Vicente Rios & Lisa Gianmoena, 2021. "On the link between temperature and regional COVID‐19 severity: Evidence from Italy," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(S1), pages 109-137, November.
    13. Herrera Gómez, Marcos, 2017. "Fundamentos de Econometría Espacial Aplicada [Fundamentals of Applied Spatial Econometrics]," MPRA Paper 80871, University Library of Munich, Germany.
    14. Júlia Gallego Ziero Uhr & André Luis Squarize Chagas, Daniel de Abreu Pereira Uhr, Renan Porn Peres, 2017. "A study on environmental infractions for Brazilian municipalities: a spatial dynamic panel approach," Working Papers, Department of Economics 2017_13, University of São Paulo (FEA-USP).
    15. Nicolas Debarsy & Cyrille Dossougoin & Cem Ertur & Jean-Yves Gnabo, 2018. "Measuring sovereign risk spillovers and assessing the role of transmission channels: A spatial econometrics approach," Post-Print hal-01744629, HAL.
    16. Triki, Mohamed Bilel, 2019. "The Italian wage curve revisited: A local and spatial cointegration," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 55, pages 73-90.
    17. Francesc Amat & Pablo Beramendi & Miriam Hortas-Rico & Vicente Rios, 2020. "How inequality shapes political participation: The role of spatial patterns of political competition," Working Papers. Collection B: Regional and sectoral economics 2002, Universidade de Vigo, GEN - Governance and Economics research Network.
    18. J. Wesley Burnett & Xueting Zhao, 2014. "Forecasting U.S. State-Level Carbon Dioxide Emissions," The Review of Regional Studies, Southern Regional Science Association, vol. 44(3), pages 223-240, Winter.
    19. Gao, Zhaoxing & Ma, Yingying & Wang, Hansheng & Yao, Qiwei, 2019. "Banded spatio-temporal autoregressions," Journal of Econometrics, Elsevier, vol. 208(1), pages 211-230.
    20. Fei Jin & Lung-fei Lee, 2013. "Generalized Spatial Two Stage Least Squares Estimation of Spatial Autoregressive Models with Autoregressive Disturbances in the Presence of Endogenous Regressors and Many Instruments," Econometrics, MDPI, vol. 1(1), pages 1-44, May.
    21. Xiaoyi Han & Lung-Fei Lee, 2016. "Bayesian Analysis of Spatial Panel Autoregressive Models With Time-Varying Endogenous Spatial Weight Matrices, Common Factors, and Random Coefficients," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 642-660, October.
    22. Lung-fei Lee & Jihai Yu, 2012. "QML Estimation of Spatial Dynamic Panel Data Models with Time Varying Spatial Weights Matrices," Spatial Economic Analysis, Taylor & Francis Journals, vol. 7(1), pages 31-74, March.
    23. Hanen Ragoubi & Zouheir Mighri, 2021. "Spillover effects of trade openness on CO2 emissions in middle‐income countries: A spatial panel data approach," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(3), pages 835-877, June.
    24. Guido M. Kuersteiner & Ingmar R. Prucha, 2015. "Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity," CESifo Working Paper Series 5445, CESifo.
    25. Zhu, Chen & Lee, Chien-Chiang, 2022. "The effects of low-carbon pilot policy on technological innovation: Evidence from prefecture-level data in China," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    26. Lee, Lung-fei & Yu, Jihai, 2014. "Efficient GMM estimation of spatial dynamic panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 180(2), pages 174-197.
    27. Qu, Xi & Lee, Lung-fei & Yu, Jihai, 2017. "QML estimation of spatial dynamic panel data models with endogenous time varying spatial weights matrices," Journal of Econometrics, Elsevier, vol. 197(2), pages 173-201.
    28. Dou, Baojun & Parrella, Maria Lucia & Yao, Qiwei, 2016. "Generalized Yule–Walker estimation for spatio-temporal models with unknown diagonal coefficients," Journal of Econometrics, Elsevier, vol. 194(2), pages 369-382.
    29. Michael McCullough & Joshua Berning & Jason L. Hanson, 2019. "Learning By Brewing: Homebrewing Legalization And The Brewing Industry," Contemporary Economic Policy, Western Economic Association International, vol. 37(1), pages 25-39, January.
    30. Sun, Yiguo & Malikov, Emir, 2017. "Estimation and Inference in Functional-Coefficient Spatial Autoregressive Panel Data Models with Fixed Effects," MPRA Paper 83671, University Library of Munich, Germany.
    31. Federica Cappelli & Caterina Conigliani & Valeria Costantini & Keti Lelo & Anil Markandya & Elena Paglialunga & Giorgia Sforna, 2020. "Do spatial interactions fuel the climate-conflict vicious cycle? The case of the African continent," Journal of Spatial Econometrics, Springer, vol. 1(1), pages 1-52, December.
    32. The Nguyen Huynh, 2022. "Dynamic spatial effects of determinants of foreign direct investment: A case of the southern key economic region of Vietnam," Australian Economic Papers, Wiley Blackwell, vol. 61(3), pages 436-454, September.
    33. Taşpınar, Süleyman & Doğan, Osman & Bera, Anil K., 2017. "GMM gradient tests for spatial dynamic panel data models," Regional Science and Urban Economics, Elsevier, vol. 65(C), pages 65-88.
    34. Yang, Zhenlin & Yu, Jihai & Liu, Shew Fan, 2016. "Bias correction and refined inferences for fixed effects spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 61(C), pages 52-72.
    35. Mengqi Zhang & Boping Tian, 2023. "Estimation of the Non-Parametric Spatial Dynamic Panel Data Model with Fixed Effects," Mathematics, MDPI, vol. 11(13), pages 1-23, June.
    36. Elhorst, J. Paul & Madre, Jean-Loup & Pirotte, Alain, 2020. "Car traffic, habit persistence, cross-sectional dependence, and spatial heterogeneity: New insights using French departmental data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 614-632.
    37. Sahar Amidi & Ali Fagheh Majidi & Bakhtiar Javaheri, 2020. "Growth spillover: a spatial dynamic panel data and spatial cross section data approaches in selected Asian countries," Future Business Journal, Springer, vol. 6(1), pages 1-14, December.
    38. Mengqi Zhang & Boping Tian, 2023. "Profile Maximum Likelihood Estimation of Single-Index Spatial Dynamic Panel Data Model," Mathematics, MDPI, vol. 11(13), pages 1-16, July.
    39. Debarsy, Nicolas & Yang, Zhenlin, 2018. "Editorial for the special issue entitled: New advances in spatial econometrics: Interactions matter," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 1-5.
    40. Yang, Kai & Lee, Lung-fei, 2021. "Estimation of dynamic panel spatial vector autoregression: Stability and spatial multivariate cointegration," Journal of Econometrics, Elsevier, vol. 221(2), pages 337-367.
    41. Song, Ge & Ren, Gaofeng, 2022. "Spatial response of cultivated land use efficiency to the maize structural adjustment policy in the "Sickle Bend" region of China: An empirical study from the cold area of northeast," Land Use Policy, Elsevier, vol. 123(C).
    42. Dou, Baojun & Parrella, Maria Lucia & Yao, Qiwei, 2016. "Generalized Yule–Walker estimation for spatio-temporal models with unknown diagonal coefficients," LSE Research Online Documents on Economics 67151, London School of Economics and Political Science, LSE Library.
    43. Niu, Honglei & Lekse, William, 2018. "Carbon emission effect of urbanization at regional level: Empirical evidence from China," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 12, pages 1-31.
    44. James Wesley Burnett & Xueting Zhao, 2017. "Spatially Explicit Prediction of Wholesale Electricity Prices," International Regional Science Review, , vol. 40(2), pages 99-140, March.
    45. Rios, Vicente & Gianmoena, Lisa, 2018. "Convergence in CO2 emissions: A spatial economic analysis with cross-country interactions," Energy Economics, Elsevier, vol. 75(C), pages 222-238.
    46. Naoto Jinji & Xingyuan Zhang, 2015. "International Knowledge Flows and Productivity: Intra- vs. Inter-Industry Spillovers," International Economic Journal, Taylor & Francis Journals, vol. 29(3), pages 451-474, September.
    47. Yongfu Huang & M. G. Quibria, 2013. "Green Growth: Theory and Evidence," WIDER Working Paper Series wp-2013-056, World Institute for Development Economic Research (UNU-WIDER).
    48. Lung‐fei Lee & Jihai Yu, 2012. "Spatial Panels: Random Components Versus Fixed Effects," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(4), pages 1369-1412, November.
    49. Taspinar, Suleyman & Dogan, Osman & Bera, Anil K., 2017. "GMM Gradient Tests for Spatial Dynamic Panel Data Models," MPRA Paper 82830, University Library of Munich, Germany.
    50. Kuersteiner, Guido M. & Prucha, Ingmar R., 2013. "Limit theory for panel data models with cross sectional dependence and sequential exogeneity," Journal of Econometrics, Elsevier, vol. 174(2), pages 107-126.
    51. Xueting Zhao & J. Burnett, 2014. "Forecasting province-level $${\text {CO}}_{2}$$ CO 2 emissions in China," Letters in Spatial and Resource Sciences, Springer, vol. 7(3), pages 171-183, October.
    52. Burridge, Peter & Iacone, Fabrizio & Lazarová, Štěpána, 2015. "Spatial effects in a common trend model of US city-level CPI," Regional Science and Urban Economics, Elsevier, vol. 54(C), pages 87-98.
    53. Hanno Reuvers & Etienne Wijler, 2021. "Sparse Generalized Yule-Walker Estimation for Large Spatio-temporal Autoregressions with an Application to NO2 Satellite Data," Papers 2108.02864, arXiv.org, revised Dec 2021.
    54. Ma, Yingying & Guo, Shaojun & Wang, Hansheng, 2023. "Sparse spatio-temporal autoregressions by profiling and bagging," Journal of Econometrics, Elsevier, vol. 232(1), pages 132-147.

  6. de Jong, Robert M. & Woutersen, Tiemen, 2011. "Dynamic Time Series Binary Choice," Econometric Theory, Cambridge University Press, vol. 27(4), pages 673-702, August.
    See citations under working paper version above.
  7. de Jong, Robert & Hu, Ling, 2011. "A note on nonlinear models with integrated regressors and convergence order results," Economics Letters, Elsevier, vol. 111(1), pages 23-25, April.

    Cited by:

    1. Li, Haiqi & Zheng, Chaowen & Guo, Yu, 2016. "Estimation and test for quantile nonlinear cointegrating regression," Economics Letters, Elsevier, vol. 148(C), pages 27-32.
    2. Zhou, Weilun & Gao, Jiti & Harris, David & Kew, Hsein, 2024. "Semi-parametric single-index predictive regression models with cointegrated regressors," Journal of Econometrics, Elsevier, vol. 238(1).

  8. Basu, Deepankar & de Jong, Robert, 2009. "A note on binary choice duration models," Economics Letters, Elsevier, vol. 102(1), pages 17-18, January.

    Cited by:

    1. Hafner, Christian & Preminger, Arie, 2014. "A note on the Tobit model in the presence of a duration variable," LIDAM Discussion Papers ISBA 2014010, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  9. Yu, Jihai & de Jong, Robert & Lee, Lung-fei, 2008. "Quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects when both n and T are large," Journal of Econometrics, Elsevier, vol. 146(1), pages 118-134, September.

    Cited by:

    1. Olivier Parent & James P. Lesage, 2010. "A Spatial Dynamic Panel Model with Random Effects Applied to Commuting Times," University of Cincinnati, Economics Working Papers Series 2010-01, University of Cincinnati, Department of Economics.
    2. Junyue Wu & Yasumasa Matsuda, 2021. "A threshold extension of spatial dynamic panel model with fixed effects," Journal of Spatial Econometrics, Springer, vol. 2(1), pages 1-30, December.
    3. Baltagi, Badi H. & Fingleton, Bernard & Pirotte, Alain, 2019. "A time-space dynamic panel data model with spatial moving average errors," Regional Science and Urban Economics, Elsevier, vol. 76(C), pages 13-31.
    4. Corinne Autant-Bernard, 2011. "Spatial econometrics of innovation : Recent contributions and research perspectives," Working Papers 1120, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    5. Cizek, P. & Jacobs, J. & Ligthart, J.E. & Vrijburg, H., 2015. "GMM Estimation of Fixed Effects Dynamic Panel Data Models with Spatial Lag and Spatial Errors (Revised version of CentER DP 2011-134)," Discussion Paper 2015-003, Tilburg University, Center for Economic Research.
    6. Frank M. Fossen & Ronny Freier & Thorsten Martin, 2014. "Race to the Debt Trap?: Spatial Econometric Evidence on Debt in German Municipalities," Discussion Papers of DIW Berlin 1358, DIW Berlin, German Institute for Economic Research.
    7. Edo, Samson & Osadolor, Nneka Esther & Dading, Isuwa Festus, 2020. "Growing external debt and declining export: The concurrent impediments in economic growth of Sub-Saharan African countries," International Economics, Elsevier, vol. 161(C), pages 173-187.
    8. Kuhn, Michael & Ochsen, Carsten, 2009. "Demographic and geographic determinants of regional physician supply," Thuenen-Series of Applied Economic Theory 105, University of Rostock, Institute of Economics.
    9. Salima Bouayad-Agha & Nadine Turpin & Lionel Védrine, 2010. "Fostering the potential endogenous development of European regions: a spatial dynamic panel data analysis of the Cohesion Policy on regional convergence over the period 1980-2005," TEPP Working Paper 2010-17, TEPP.
    10. Andrew Ojede & Bebonchu Atems & Steven Yamarik, 2018. "The Direct and Indirect (Spillover) Effects of Productive Government Spending on State Economic Growth," Growth and Change, Wiley Blackwell, vol. 49(1), pages 122-141, March.
    11. Liqian Cai & Arnab Bhattacharjee & Roger Calantone & Taps Maiti, 2019. "Variable Selection with Spatially Autoregressive Errors: A Generalized Moments LASSO Estimator," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 146-200, September.
    12. Iris Wanzenböck & Philipp Piribauer, 2018. "R&D networks and regional knowledge production in Europe: Evidence from a space‐time model," Papers in Regional Science, Wiley Blackwell, vol. 97(S1), pages 1-24, March.
    13. Natalia Bailey & Sean Holly & M. Hashem Pesaran, 2016. "A Two‐Stage Approach to Spatio‐Temporal Analysis with Strong and Weak Cross‐Sectional Dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 249-280, January.
    14. Ciccarelli, Carlo & Elhorst, J.Paul, 2018. "A dynamic spatial econometric diffusion model with common factors: The rise and spread of cigarette consumption in Italy," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 131-142.
    15. Hagen, Tobias & Mohl, Philipp, 2009. "Econometric evaluation of EU Cohesion Policy: a survey," ZEW Discussion Papers 09-052, ZEW - Leibniz Centre for European Economic Research.
    16. Christopher L. Foote, 2007. "Space and time in macroeconomic panel data: young workers and state-level unemployment revisited," Working Papers 07-10, Federal Reserve Bank of Boston.
    17. Lee, Lung-fei & Yu, Jihai, 2015. "Estimation of fixed effects panel regression models with separable and nonseparable space–time filters," Journal of Econometrics, Elsevier, vol. 184(1), pages 174-192.
    18. Hidalgo, Javier & Schafgans, Marcia, 2017. "Inference and testing breaks in large dynamic panels with strong cross sectional dependence," Journal of Econometrics, Elsevier, vol. 196(2), pages 259-274.
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  10. de Jong, Robert M. & Amsler, Christine & Schmidt, Peter, 2007. "A robust version of the KPSS test based on indicators," Journal of Econometrics, Elsevier, vol. 137(2), pages 311-333, April.

    Cited by:

    1. Joseph Ross, 2021. "Stationarity Statistics on Rolling Windows," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 655-691, February.
    2. Jiang, Bibo & Lu, Ye & Park, Joon Y., 2018. "Testing for Stationarity at High Frequency," Working Papers 2018-09, University of Sydney, School of Economics.
    3. Busetti, F. & Harvey, A., 2008. "When is a copula constant? A test for changing relationships," Cambridge Working Papers in Economics 0841, Faculty of Economics, University of Cambridge.
    4. Simões, Oscar R. & Marçal, Emerson Fernandes, 2012. "Agregação temporal e não-linearidade afetam os testes da paridade do poder de compra: Evidência a partir de dados brasileiros," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 66(3), October.
    5. Ahmed, Muhammad Ashfaq & Nawaz, Nasreen, 2023. "A Sufficient Statistical Test for Dynamic Stability," MPRA Paper 116684, University Library of Munich, Germany.
    6. Aviral Kumar Tiwari & Aruna Kumar Dash & Subhendu Dutta, 2015. "Testing the mean reversion in prices of agricultural commodities in India," Economics Bulletin, AccessEcon, vol. 35(3), pages 1928-1940.
    7. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.
    8. Pelagatti, Matteo M. & Sen, Pranab K., 2013. "Rank tests for short memory stationarity," Journal of Econometrics, Elsevier, vol. 172(1), pages 90-105.
    9. Matteo Pelagatti & Bruno Bosco & Lucia Parisio & Fabio Baldi, 2007. "A Robust Multivariate Long Run Analysis of European Electricity Prices," Working Papers 2007.103, Fondazione Eni Enrico Mattei.
    10. Cho, Cheol-Keun & Amsler, Christine & Schmidt, Peter, 2015. "A test of the null of integer integration against the alternative of fractional integration," Journal of Econometrics, Elsevier, vol. 187(1), pages 217-237.
    11. Lujia Bai & Weichi Wu, 2021. "Detecting long-range dependence for time-varying linear models," Papers 2110.08089, arXiv.org, revised Mar 2023.
    12. Victor F. Moutinho & António C. Moreira & João Paulo C. Bento, 2018. "Strategic decisions on bilateral bidding behavior: evidence from a wholesale electricity market," Empirical Economics, Springer, vol. 54(3), pages 1353-1387, May.
    13. Busettti, F. & Harvey, A., 2007. "Tests of time-invariance," Cambridge Working Papers in Economics 0657, Faculty of Economics, University of Cambridge.
    14. Qin, Ruibing & Tian, Zheng & Jin, Hao & Zhang, Xiaowei, 2010. "Strong convergence rate of robust estimator of change point," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(10), pages 2026-2032.
    15. Claudiu Tiberiu Albulescu, 2022. "Health Care Expenditure in the European Union Countries: New Insights about the Convergence Process," IJERPH, MDPI, vol. 19(4), pages 1-16, February.
    16. Horváth, Lajos & Kokoszka, Piotr & Rice, Gregory, 2014. "Testing stationarity of functional time series," Journal of Econometrics, Elsevier, vol. 179(1), pages 66-82.
    17. Arun Narayanasamy & Humnath Panta & Rohit Agarwal, 2023. "Relations among Bitcoin Futures, Bitcoin Spot, Investor Attention, and Sentiment," JRFM, MDPI, vol. 16(11), pages 1-24, November.
    18. Fabio Busetti & Andrew Harvey, 2010. "Tests of strict stationarity based on quantile indicators," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(6), pages 435-450, November.
    19. James E Payne & Junsoo Lee, 2024. "Global perspective on the permanent or transitory nature of shocks to tourist arrivals: Evidence from new unit root tests with structural breaks and factors," Tourism Economics, , vol. 30(1), pages 67-103, February.
    20. Xiao, Zhijie, 2012. "Robust inference in nonstationary time series models," Journal of Econometrics, Elsevier, vol. 169(2), pages 211-223.

  11. Basu Deepankar & de Jong Robert M, 2007. "Dynamic Multinomial Ordered Choice with an Application to the Estimation of Monetary Policy Rules," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 11(4), pages 1-35, December.

    Cited by:

    1. Igor Kheifets & Carlos Velasco, 2013. "New Goodness-of-fit Diagnostics for Conditional Discrete Response Models," Cowles Foundation Discussion Papers 1924, Cowles Foundation for Research in Economics, Yale University.
    2. David Dale & Andrei Sirchenko, 2018. "Estimation of Nested and Zero-Inflated Ordered Probit Models," HSE Working papers WP BRP 193/EC/2018, National Research University Higher School of Economics.
    3. Igor Kheifets & Carlos Velasco, 2012. "Model Adequacy Checks for Discrete Choice Dynamic Models," Working Papers w0170, New Economic School (NES).

  12. Youngsoo Bae & Robert M. de Jong, 2007. "Money demand function estimation by nonlinear cointegration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(4), pages 767-793.

    Cited by:

    1. Stephen M. Miller & Luis F. Martins & Rangan Gupta, 2014. "A Time-Varying Approach of the US Welfare Cost of Inflation," Working papers 2014-11, University of Connecticut, Department of Economics.
    2. Deepankar Basu, 2009. "The Paradox of Thrift and Crowding-In of Private Investment in a Simple IS-LM Model," UMASS Amherst Economics Working Papers 2009-14, University of Massachusetts Amherst, Department of Economics.
    3. Alfredo Martín-Oliver, 2018. "Bank Competition with Financing and Savings Substitutes," Journal of Financial Services Research, Springer;Western Finance Association, vol. 54(2), pages 207-241, October.
    4. Emel Siklar & Ilyas Siklar, 2021. "Is There a Change in the Money Demand Stability in Turkey? A Nonlinear Approach," International Journal of Economics and Financial Research, Academic Research Publishing Group, vol. 7(2), pages 28-42, 06-2021.
    5. doğru, bülent, 2013. "Dynamic Analysis of Money Demand Function: Case of Turkey," MPRA Paper 48402, University Library of Munich, Germany.
    6. Javier Gómez Biscarri & Javier Hualde, 2014. "A Residual-Based ADF Test for Stationary Cointegration in I (2) Settings," Working Papers 779, Barcelona School of Economics.
    7. Shahbaz, Muhammad & Shahzad, Syed Jawad Hussain & Alam, Shaista & Apergis, Nicholas, 2018. "Globalisation, Economic Growth and Energy Consumption in the BRICS Region: The Importance of Asymmetries," MPRA Paper 86979, University Library of Munich, Germany, revised 16 May 2018.
    8. Tsuruga, Takayuki & Wake, Shota, 2019. "Money-financed fiscal stimulus: The effects of implementation lag," Journal of Economic Dynamics and Control, Elsevier, vol. 104(C), pages 132-151.
    9. Kristensen, Dennis & Rahbek, Anders, 2010. "Likelihood-based inference for cointegration with nonlinear error-correction," Journal of Econometrics, Elsevier, vol. 158(1), pages 78-94, September.
    10. Daniel Ordonez Callamand & Luis Fernando Melo-Velandia & Daniel Parra-Amado, 2018. "Una exploración reciente a la demanda por dinero en Colombia bajo un enfoque no lineal," Revista de Economía del Rosario, Universidad del Rosario, vol. 21(1), pages 5-37, June.
    11. Chen, Yao & Ward, Felix, 2019. "When do fixed exchange rates work? Evidence from the Gold Standard," Journal of International Economics, Elsevier, vol. 116(C), pages 158-172.
    12. Rostom,Ahmed Mohamed Tawfick, 2016. "Money demand in the Arab Republic of Egypt : a vector equilibrium correction model," Policy Research Working Paper Series 7679, The World Bank.
    13. Kim, Chang Sik & Kim, In-Moo, 2012. "Partial parametric estimation for nonstationary nonlinear regressions," Journal of Econometrics, Elsevier, vol. 167(2), pages 448-457.
    14. Inagaki, Kazuyuki, 2009. "Estimating the interest rate semi-elasticity of the demand for money in low interest rate environments," Economic Modelling, Elsevier, vol. 26(1), pages 147-154, January.
    15. Karsten Schweikert, 2020. "Oracle Efficient Estimation of Structural Breaks in Cointegrating Regressions," Papers 2001.07949, arXiv.org, revised Apr 2021.
    16. Karsten Schweikert, 2022. "Oracle Efficient Estimation of Structural Breaks in Cointegrating Regressions," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(1), pages 83-104, January.
    17. Hu, Zhishui & Phillips, Peter C.B. & Wang, Qiying, 2021. "Nonlinear Cointegrating Power Function Regression With Endogeneity," Econometric Theory, Cambridge University Press, vol. 37(6), pages 1173-1213, December.
    18. Barnett, William A. & Ghosh, Taniya & Adil, Masudul Hasan, 2022. "Is money demand really unstable? Evidence from Divisia monetary aggregates," Economic Analysis and Policy, Elsevier, vol. 74(C), pages 606-622.
    19. Choi, Chi-Young & Hu, Ling & Ogaki, Masao, 2008. "Robust estimation for structural spurious regressions and a Hausman-type cointegration test," Journal of Econometrics, Elsevier, vol. 142(1), pages 327-351, January.
    20. Nakashima, Kiyotaka, 2008. "An Extremely Low Interest Rate Policy and the Shape of the Japanese Money Demand Function: A Nonlinear Cointegration Approach," MPRA Paper 70689, University Library of Munich, Germany.
    21. Nakashima, Kiyotaka & Saito, Makoto, 2012. "On the comparison of alternative specifications for money demand: The case of extremely low interest rate regimes in Japan," Journal of the Japanese and International Economies, Elsevier, vol. 26(3), pages 454-471.
    22. Anthony N. Rezitis, 2019. "Investigating price transmission in the Finnish dairy sector: an asymmetric NARDL approach," Empirical Economics, Springer, vol. 57(3), pages 861-900, September.
    23. Choudhry, Taufiq & Hassan, Syed S., 2015. "Exchange rate volatility and UK imports from developing countries: The effect of the global financial crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 89-101.
    24. Muhammad Ahad & Zaheer Anwer, 2021. "Asymmetric impact of oil price on trade balance in BRICS countries: Multiplier dynamic analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2177-2197, April.
    25. Matteo Mogliani & Giovanni Urga, 2018. "On the Instability of Long‐Run Money Demand and the Welfare Cost of Inflation in the United States," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(7), pages 1645-1660, October.
    26. Ward, Felix & Chen, Yao, 2016. "Rigid relations: External adjustment under the Gold Standard (1880-1913)," VfS Annual Conference 2016 (Augsburg): Demographic Change 145930, Verein für Socialpolitik / German Economic Association.
    27. Chan, Nigel & Wang, Qiying, 2015. "Nonlinear regressions with nonstationary time series," Journal of Econometrics, Elsevier, vol. 185(1), pages 182-195.
    28. Zhou, Weilun & Gao, Jiti & Harris, David & Kew, Hsein, 2024. "Semi-parametric single-index predictive regression models with cointegrated regressors," Journal of Econometrics, Elsevier, vol. 238(1).
    29. Mouyad Alsamara & Zouhair Mrabet, 2019. "Asymmetric impacts of foreign exchange rate on the demand for money in Turkey: new evidence from nonlinear ARDL," International Economics and Economic Policy, Springer, vol. 16(2), pages 335-356, April.
    30. YABE, Ryota & 矢部, 竜太, 2014. "Empirical Likelihood Confidence Intervals for Nonparametric Nonlinear Nonstationary Regression Models," Discussion Papers 2014-20, Graduate School of Economics, Hitotsubashi University.

  13. de Jong, Robert & Wang, Chien-Ho, 2005. "Further Results On The Asymptotics For Nonlinear Transformations Of Integrated Time Series," Econometric Theory, Cambridge University Press, vol. 21(2), pages 413-430, April.

    Cited by:

    1. Yoon, Gawon, 2005. "Long-memory property of nonlinear transformations of break processes," Economics Letters, Elsevier, vol. 87(3), pages 373-377, June.
    2. Rickard Sandberg, 2017. "Sample Moments and Weak Convergence to Multivariate Stochastic Power Integrals," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(6), pages 1000-1009, November.
    3. Matei Demetrescu & Christoph Hanck & Adina I. Tarcolea, 2014. "Iv-Based Cointegration Testing In Dependent Panels With Time-Varying Variance," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(5), pages 393-406, August.
    4. J. Isaac Miller, 2010. "A Nonlinear IV Likelihood-Based Rank Test for Multivariate Time Series and Long Panels," Working Papers 1001, Department of Economics, University of Missouri.
    5. Demetrescu Matei, 2009. "Panel Unit Root Testing with Nonlinear Instruments for Infinite-Order Autoregressive Processes," Journal of Time Series Econometrics, De Gruyter, vol. 1(2), pages 1-30, December.
    6. Matei Demetrescu & Christoph Hanck, 2013. "Nonlinear IV panel unit root testing under structural breaks in the error variance," Statistical Papers, Springer, vol. 54(4), pages 1043-1066, November.
    7. Kasparis, Ioannis, 2010. "The Bierens test for certain nonstationary models," Journal of Econometrics, Elsevier, vol. 158(2), pages 221-230, October.
    8. Burak Alparslan Eroğlu & J. Isaac Miller & Taner Yiğit, 2022. "Time-varying cointegration and the Kalman filter," Econometric Reviews, Taylor & Francis Journals, vol. 41(1), pages 1-21, January.
    9. Qiying Wang & Peter C.B. Phillips, 2011. "Specification Testing for Nonlinear Cointegrating Regression," Cowles Foundation Discussion Papers 1779, Cowles Foundation for Research in Economics, Yale University, revised Feb 2011.
    10. Berenguer Rico, Vanessa, 2011. "Summability of stochastic processes: a generalization of integration and co-integration valid for non-linear processes," UC3M Working papers. Economics we1115, Universidad Carlos III de Madrid. Departamento de Economía.
    11. Berenguer-Rico, Vanessa & Gonzalo, Jesús, 2014. "Summability of stochastic processes—A generalization of integration for non-linear processes," Journal of Econometrics, Elsevier, vol. 178(P2), pages 331-341.
    12. Phillips, Peter C.B., 2009. "Local Limit Theory And Spurious Nonparametric Regression," Econometric Theory, Cambridge University Press, vol. 25(6), pages 1466-1497, December.
    13. Lee, Jungick & de Jong, Robert M., 2008. "Exponential functionals of integrated processes," Economics Letters, Elsevier, vol. 100(2), pages 181-184, August.

  14. de Jong, Robert M., 2004. "Addendum To “Asymptotics For Nonlinear Transformations Of Integrated Time Series”," Econometric Theory, Cambridge University Press, vol. 20(3), pages 627-635, June.

    Cited by:

    1. Qiying Wang & Peter C.B. Phillips, 2006. "Asymptotic Theory for Local Time Density Estimation and Nonparametric Cointegrating Regression," Cowles Foundation Discussion Papers 1594, Cowles Foundation for Research in Economics, Yale University.
    2. Heinen, Florian, 2011. "A note on testing for purchasing power parity," Hannover Economic Papers (HEP) dp-471, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    3. Kasparis, Ioannis, 2010. "The Bierens test for certain nonstationary models," Journal of Econometrics, Elsevier, vol. 158(2), pages 221-230, October.
    4. Phillips, Peter C.B., 2009. "Local Limit Theory And Spurious Nonparametric Regression," Econometric Theory, Cambridge University Press, vol. 25(6), pages 1466-1497, December.
    5. Lee, Jungick & de Jong, Robert M., 2008. "Exponential functionals of integrated processes," Economics Letters, Elsevier, vol. 100(2), pages 181-184, August.

  15. Goncalves, Silvia & de Jong, Robert, 2003. "Consistency of the stationary bootstrap under weak moment conditions," Economics Letters, Elsevier, vol. 81(2), pages 273-278, November.

    Cited by:

    1. A. Amendola & V. Candila, 2016. "Evaluation of volatility predictions in a VaR framework," Quantitative Finance, Taylor & Francis Journals, vol. 16(5), pages 695-709, May.
    2. Prayut Jain & Shashi Jain, 2019. "Can Machine Learning-Based Portfolios Outperform Traditional Risk-Based Portfolios? The Need to Account for Covariance Misspecification," Risks, MDPI, vol. 7(3), pages 1-27, July.
    3. Vikranth Lokeshwar Dhandapani & Shashi Jain, 2023. "Data-driven Approach for Static Hedging of Exchange Traded Options," Papers 2302.00728, arXiv.org, revised Jan 2024.
    4. Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
    5. Li, Jia & Patton, Andrew J., 2018. "Asymptotic inference about predictive accuracy using high frequency data," Journal of Econometrics, Elsevier, vol. 203(2), pages 223-240.
    6. Zacharias Psaradakis & Márian Vávra, 2018. "Bootstrap-Assisted Tests of Symmetry for Dependent Data," Birkbeck Working Papers in Economics and Finance 1806, Birkbeck, Department of Economics, Mathematics & Statistics.
    7. M. Chudý & S. Karmakar & W. B. Wu, 2020. "Long-term prediction intervals of economic time series," Empirical Economics, Springer, vol. 58(1), pages 191-222, January.
    8. Dominik Wied, 2017. "A nonparametric test for a constant correlation matrix," Econometric Reviews, Taylor & Francis Journals, vol. 36(10), pages 1157-1172, November.
    9. Dehling, Herold & Sharipov, Olimjon Sh. & Wendler, Martin, 2015. "Bootstrap for dependent Hilbert space-valued random variables with application to von Mises statistics," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 200-215.
    10. Calhoun, Gray, 2014. "Block Bootstrap Consistency Under Weak Assumptions," Staff General Research Papers Archive 34313, Iowa State University, Department of Economics.
    11. Hwang, Eunju & Shin, Dong Wan, 2012. "Strong consistency of the stationary bootstrap under ψ-weak dependence," Statistics & Probability Letters, Elsevier, vol. 82(3), pages 488-495.
    12. Fleming, Jeff & Kirby, Chris & Ostdiek, Barbara, 2006. "Bootstrap tests of multiple inequality restrictions on variance ratios," Economics Letters, Elsevier, vol. 91(3), pages 343-348, June.
    13. Hwang, Eunju & Shin, Dong Wan, 2013. "Stationary bootstrapping realized volatility," Statistics & Probability Letters, Elsevier, vol. 83(9), pages 2045-2051.

  16. de Jong, Robert M., 2003. "Logarithmic spurious regressions," Economics Letters, Elsevier, vol. 81(1), pages 13-21, October.

    Cited by:

    1. Imad A. Moosa, 2017. "Blaming suicide on NASA and divorce on margarine: the hazard of using cointegration to derive inference on spurious correlation," Applied Economics, Taylor & Francis Journals, vol. 49(15), pages 1483-1490, March.
    2. Esther Stroe-Kunold & Joachim Werner, 2009. "A drunk and her dog: a spurious relation? Cointegration tests as instruments to detect spurious correlations between integrated time series," Quality & Quantity: International Journal of Methodology, Springer, vol. 43(6), pages 913-940, November.
    3. Daniel Ventosa-Santaulària & Carlos Vladimir Rodríguez-Caballero, 2013. "Polynomial Regressions and Nonsense Inference," CREATES Research Papers 2013-40, Department of Economics and Business Economics, Aarhus University.
    4. Hosoya, Yuzo & Terasaka, Takahiro, 2009. "Inference on transformed stationary time series," Journal of Econometrics, Elsevier, vol. 151(2), pages 129-139, August.

  17. de Jong, Robert M., 2002. "Nonlinear minimization estimators in the presence of cointegrating relations," Journal of Econometrics, Elsevier, vol. 110(2), pages 241-259, October.

    Cited by:

    1. Dennis Kristensen & Anders Rahbek, 2010. "Testing and Inference in Nonlinear Cointegrating Vector Error Correction Models," CREATES Research Papers 2010-68, Department of Economics and Business Economics, Aarhus University.
    2. Kristensen, Dennis & Rahbek, Anders, 2010. "Likelihood-based inference for cointegration with nonlinear error-correction," Journal of Econometrics, Elsevier, vol. 158(1), pages 78-94, September.
    3. Novella Maugeri, 2014. "Some Pitfalls in Smooth Transition Models Estimation: A Monte Carlo Study," Computational Economics, Springer;Society for Computational Economics, vol. 44(3), pages 339-378, October.
    4. Seo Byeongseon, 2011. "Nonparametric Testing for Linearity in Cointegrated Error-Correction Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(2), pages 1-28, March.
    5. Nedeljkovic, Milan, 2008. "Testing for Smooth Transition Nonlinearity in Adjustments of Cointegrating Systems," Economic Research Papers 269887, University of Warwick - Department of Economics.
    6. Nedeljkovic, Milan, 2008. "Testing for Smooth Transition Nonlinearity in Adjustments of Cointegrating Systems," The Warwick Economics Research Paper Series (TWERPS) 876, University of Warwick, Department of Economics.
    7. Dennis Kristensen & Anders Rahbek, 2007. "Likelihood-Based Inference in Nonlinear Error-Correction Models," CREATES Research Papers 2007-38, Department of Economics and Business Economics, Aarhus University.
    8. 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.).
    9. Zhou, Weilun & Gao, Jiti & Harris, David & Kew, Hsein, 2024. "Semi-parametric single-index predictive regression models with cointegrated regressors," Journal of Econometrics, Elsevier, vol. 238(1).

  18. de Jong, Robert M. & Schmidt, Peter, 2002. "Spurious logarithms and the KPSS statistic," Economics Letters, Elsevier, vol. 76(3), pages 383-391, August.

    Cited by:

    1. Heinen, Florian, 2011. "A note on testing for purchasing power parity," Hannover Economic Papers (HEP) dp-471, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

  19. de Jong, Robert M., 2002. "A note on "Convergence rates and asymptotic normality for series estimators": uniform convergence rates," Journal of Econometrics, Elsevier, vol. 111(1), pages 1-9, November.

    Cited by:

    1. Dimitriou, Dimitrios & Simos, Theodore, 2011. "The relationship between stock returns and volatility in the seventeen largest international stock markets: A semi-parametric approach," MPRA Paper 37528, University Library of Munich, Germany.
    2. Jungyoon Lee & Peter M Robinson, 2013. "Series Estimation under Cross-sectional Dependence," STICERD - Econometrics Paper Series 570, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    3. Xiaohong Chen & Timothy Christensen, 2013. "Optimal Uniform Convergence Rates for Sieve Nonparametric Instrumental Variables Regression," Papers 1311.0412, arXiv.org.
    4. Cattaneo, Matias D. & Farrell, Max H., 2013. "Optimal convergence rates, Bahadur representation, and asymptotic normality of partitioning estimators," Journal of Econometrics, Elsevier, vol. 174(2), pages 127-143.
    5. Lee, Jungyoon & Robinson, Peter M., 2013. "Series estimation under cross-sectional dependence," LSE Research Online Documents on Economics 58188, London School of Economics and Political Science, LSE Library.
    6. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    7. Xiaohong Chen & Timothy M. Christensen, 2014. "Optimal Uniform Convergence Rates and Asymptotic Normality for Series Estimators under Weak Dependence and Weak Conditions," Cowles Foundation Discussion Papers 1976, Cowles Foundation for Research in Economics, Yale University.
    8. Xiaohong Chen & Timothy M. Christensen, 2013. "Optimal uniform convergence rates for sieve nonparametric instrumental variables regression," CeMMAP working papers 56/13, Institute for Fiscal Studies.
    9. Lee, Jungyoon & Robinson, Peter M., 2016. "Series estimation under cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 190(1), pages 1-17.
    10. Li, Qi & Yang, Jian & Hsiao, Cheng & Chang, Young-Jae, 2005. "The relationship between stock returns and volatility in international stock markets," Journal of Empirical Finance, Elsevier, vol. 12(5), pages 650-665, December.
    11. Xiaohong Chen, 2011. "Penalized Sieve Estimation and Inference of Semi-Nonparametric Dynamic Models: A Selective Review," Cowles Foundation Discussion Papers 1804, Cowles Foundation for Research in Economics, Yale University.
    12. 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.
    13. Xiaohong Chen & Timothy M. Christensen, 2014. "Optimal uniform convergence rates and asymptotic normality for series estimators under weak dependence and weak conditions," CeMMAP working papers 46/14, Institute for Fiscal Studies.
    14. Raffaello Seri & Samuele Centorrino & Michele Bernasconi, 2019. "Nonparametric Estimation and Inference in Economic and Psychological Experiments," Papers 1904.11156, arXiv.org, revised Dec 2019.
    15. Neumeyer, Natalie, 2005. "A note on uniform consistency of monotone function estimators," Technical Reports 2005,35, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

  20. James Davidson & Robert M. De Jong, 2002. "Consistency of kernel variance estimators for sums of semiparametric linear processes," Econometrics Journal, Royal Economic Society, vol. 5(1), pages 160-175, June.

    Cited by:

    1. Davidson, James, 2020. "A new consistency proof for HAC variance estimators," Economics Letters, Elsevier, vol. 186(C).
    2. Hirukawa, Masayuki, 2023. "Robust Covariance Matrix Estimation in Time Series: A Review," Econometrics and Statistics, Elsevier, vol. 27(C), pages 36-61.
    3. Yasutomo Murasawa, 2009. "Do coincident indicators have one-factor structure?," Empirical Economics, Springer, vol. 36(2), pages 339-365, May.
    4. Margherita Gerolimetto & Isabella Procidano, 2008. "A test for fractional cointegration using the sieve bootstrap," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 17(3), pages 373-391, July.

  21. de Jong, Robert & Han, Chirok, 2002. "THE PROPERTIES OF Lp-GMM ESTIMATORS," Econometric Theory, Cambridge University Press, vol. 18(2), pages 491-504, April.

    Cited by:

    1. Pierre Chausse & Dinghai Xu, 2012. "GMM Estimation of a Stochastic Volatility Model with Realized Volatility: A Monte Carlo Study," Working Papers 1203, University of Waterloo, Department of Economics, revised May 2012.
    2. Han, Chirok, 2008. "Detecting invalid instruments using L1-GMM," Economics Letters, Elsevier, vol. 101(3), pages 285-287, December.

  22. de Jong, Robert M., 2001. "Convergence of averages of scaled functions of I(1) linear processes," Economics Letters, Elsevier, vol. 71(1), pages 27-33, April.

    Cited by:

    1. Gadea, Maria-Dolores & Montanes, Antonio & Reyes, Marcelo, 2004. "The European Union currencies and the US dollar: from post-Bretton-Woods to the Euro," Journal of International Money and Finance, Elsevier, vol. 23(7-8), pages 1109-1136.

  23. de Jong, Robert M., 2001. "Nonlinear estimation using estimated cointegrating relations," Journal of Econometrics, Elsevier, vol. 101(1), pages 109-122, March.

    Cited by:

    1. Burton Hollifield & Robert A. Miller & patrik Sandas, "undated". "An Empirical Analysis of Limit Order Markets," Rodney L. White Center for Financial Research Working Papers 29-99, Wharton School Rodney L. White Center for Financial Research.
    2. Stephen M. Miller & Luis F. Martins & Rangan Gupta, 2014. "A Time-Varying Approach of the US Welfare Cost of Inflation," Working papers 2014-11, University of Connecticut, Department of Economics.
    3. Jaebeom Kim & Masao Ogaki & Minseok Yang, 2007. "Structural Error Correction Models: A System Method for Linear Rational Expectations Models and an Application to an Exchange Rate Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(8), pages 2057-2075, December.
    4. Bayer, Christian, 2006. "Investment dynamics with fixed capital adjustment cost and capital market imperfections," Journal of Monetary Economics, Elsevier, vol. 53(8), pages 1909-1947, November.
    5. Dennis Kristensen & Anders Rahbek, 2010. "Testing and Inference in Nonlinear Cointegrating Vector Error Correction Models," CREATES Research Papers 2010-68, Department of Economics and Business Economics, Aarhus University.
    6. Kristensen, Dennis & Rahbek, Anders, 2010. "Likelihood-based inference for cointegration with nonlinear error-correction," Journal of Econometrics, Elsevier, vol. 158(1), pages 78-94, September.
    7. Aguero, Jorge M., 2004. "Asymmetric Price Adjustments And Behavior Under Risk: Evidence From Peruvian Agricultural Markets," 2004 Annual meeting, August 1-4, Denver, CO 20394, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    8. de Jong, Robert M., 2002. "Nonlinear minimization estimators in the presence of cointegrating relations," Journal of Econometrics, Elsevier, vol. 110(2), pages 241-259, October.
    9. Novella Maugeri, 2014. "Some Pitfalls in Smooth Transition Models Estimation: A Monte Carlo Study," Computational Economics, Springer;Society for Computational Economics, vol. 44(3), pages 339-378, October.
    10. Seo, Myung Hwan, 2007. "Estimation of nonlinear error correction models," LSE Research Online Documents on Economics 6802, London School of Economics and Political Science, LSE Library.
    11. Robert M. deJong, 2000. "Nonlinear Minimization Estimators in the Presence of Cointegrating Relations," Econometric Society World Congress 2000 Contributed Papers 1651, Econometric Society.
    12. Christis Katsouris, 2023. "Estimating Conditional Value-at-Risk with Nonstationary Quantile Predictive Regression Models," Papers 2311.08218, arXiv.org, revised Apr 2024.
    13. Myung Hwan Seo, 2007. "Estimation of Nonlinear Error CorrectionModels," STICERD - Econometrics Paper Series 517, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    14. Jaebeom Kim & Masao Ogaki & Minseok Yang, 2003. "Structural Error Correction Models: Instrumental Variables Methods and an application to an exchange rate model," RCER Working Papers 502, University of Rochester - Center for Economic Research (RCER).

  24. Robert M. De Jong & James Davidson, 2000. "Consistency of Kernel Estimators of Heteroscedastic and Autocorrelated Covariance Matrices," Econometrica, Econometric Society, vol. 68(2), pages 407-424, March.
    See citations under working paper version above.
  25. de Jong, Robert M., 2000. "A Strong Consistency Proof For Heteroskedasticity And Autocorrelation Consistent Covariance Matrix Estimators," Econometric Theory, Cambridge University Press, vol. 16(2), pages 262-268, April.

    Cited by:

    1. Davidson, James, 2020. "A new consistency proof for HAC variance estimators," Economics Letters, Elsevier, vol. 186(C).
    2. Giuseppe Cavaliere & A. M. Robert Taylor, 2006. "Testing for a change in persistence in the presence of non-stationary volatility," Discussion Papers 06/04, University of Nottingham, Granger Centre for Time Series Econometrics.
    3. Chung-Ming Kuan & Yu-Wei Hsieh, 2006. "Improved HAC Covariance Matrix Estimation Based on Forecast Errors," IEAS Working Paper : academic research 06-A008, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    4. Giuseppe Cavaliere, 2002. "Bounded integrated processes and unit root tests," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(1), pages 41-69, February.
    5. Cavaliere, Giuseppe & Taylor, A.M. Robert, 2005. "Stationarity Tests Under Time-Varying Second Moments," Econometric Theory, Cambridge University Press, vol. 21(6), pages 1112-1129, December.
    6. Corradi, Valentina & Swanson, Norman R., 2002. "A consistent test for nonlinear out of sample predictive accuracy," Journal of Econometrics, Elsevier, vol. 110(2), pages 353-381, October.
    7. de Jong, Robert M., 2002. "Nonlinear minimization estimators in the presence of cointegrating relations," Journal of Econometrics, Elsevier, vol. 110(2), pages 241-259, October.
    8. Brendan K. Beare, 2008. "Unit Root Testing with Unstable Volatility," Economics Papers 2008-W06, Economics Group, Nuffield College, University of Oxford.
    9. Li, Jia & Liao, Zhipeng, 2020. "Uniform nonparametric inference for time series," Journal of Econometrics, Elsevier, vol. 219(1), pages 38-51.
    10. Hao Jin & Si Zhang & Jinsuo Zhang, 2017. "Spurious regression due to neglected of non-stationary volatility," Computational Statistics, Springer, vol. 32(3), pages 1065-1081, September.
    11. Chen, Xiaohong & Liao, Zhipeng, 2015. "Sieve semiparametric two-step GMM under weak dependence," Journal of Econometrics, Elsevier, vol. 189(1), pages 163-186.
    12. Altissimo, F. & Corradi, V., 2000. "Strong Rules for Detecting the Number of Breaks in a Time Series," Discussion Papers 0011, University of Exeter, Department of Economics.
    13. Luke Hartigan, 2016. "Alternative HAC Covariance Matrix Estimators with Improved Finite Sample Properties," Discussion Papers 2016-06, School of Economics, The University of New South Wales.
    14. Zacharias Psaradakis & Marián Vávra, 2015. "A Quantile-based Test for Symmetry of Weakly Dependent Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(4), pages 587-598, July.

  26. de Jong, Robert M. & Davidson, James, 2000. "The Functional Central Limit Theorem And Weak Convergence To Stochastic Integrals I," Econometric Theory, Cambridge University Press, vol. 16(5), pages 621-642, October.

    Cited by:

    1. Baillie, Richard T. & Kapetanios, George, 2007. "Testing for Neglected Nonlinearity in Long-Memory Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 447-461, October.
    2. Sun, Yixiao & Kaplan, David M., 2011. "A New Asymptotic Theory for Vector Autoregressive Long-run Variance Estimation and Autocorrelation Robust Testing," University of California at San Diego, Economics Working Paper Series qt8cx0t4gc, Department of Economics, UC San Diego.
    3. George Kapetanios & M. Hashem Pesaran & Takashi Yamagata, 2006. "Panels with Nonstationary Multifactor Error Structures," Working Papers 569, Queen Mary University of London, School of Economics and Finance.
    4. James Davidson & Andrea Monticini, 2007. "Tests for Cointegration with Structural Breaks Based on Subsamples," Discussion Papers 0704, University of Exeter, Department of Economics.
    5. B. Nielsen, 2009. "Test for cointegration rank in general vector autoregressions," Economics Papers 2009-W10, Economics Group, Nuffield College, University of Oxford.
    6. Clark, Todd E. & McCracken, Michael W., 2015. "Nested forecast model comparisons: A new approach to testing equal accuracy," Journal of Econometrics, Elsevier, vol. 186(1), pages 160-177.
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    41. Marc K. Chan & Simon S. Kwok, 2022. "The PCDID Approach: Difference-in-Differences When Trends Are Potentially Unparallel and Stochastic," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1216-1233, June.
    42. Jonathan Hill, 2012. "Dependence and stochastic limit theory (in Russian)," Quantile, Quantile, issue 10, pages 1-31, December.
    43. Kuswanto, Heri & Sibbertsen, Philipp, 2009. "Testing for Long Memory Against ESTAR Nonlinearities," Hannover Economic Papers (HEP) dp-427, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    44. Sibbertsen, Philipp, 2001. "Long-memory versus structural breaks: An overview," Technical Reports 2001,28, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    45. Bai, ChongEn & Li, Qi & Ouyang, Min, 2014. "Property taxes and home prices: A tale of two cities," Journal of Econometrics, Elsevier, vol. 180(1), pages 1-15.
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    47. Davidson James E. H. & Peel David A & Byers J. David, 2006. "Support for Governments and Leaders: Fractional Cointegration Analysis of Poll Evidence from the UK, 1960-2004," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(1), pages 1-23, March.
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    Cited by:

    1. Francesco Audrino & Peter Bühlmann, 2007. "Splines for Financial Volatility," University of St. Gallen Department of Economics working paper series 2007 2007-11, Department of Economics, University of St. Gallen.

  28. Robert M. De Jong, 1998. "Weak Laws of Large Numbers for Dependent Random Variables," Annals of Economics and Statistics, GENES, issue 51, pages 209-225.

    Cited by:

    1. Luciano de Castro & Antonio F. Galvao & David M. Kaplan & Xin Liu, 2017. "Smoothed GMM for quantile models," Papers 1707.03436, arXiv.org, revised Feb 2018.
    2. Kanaya, Shin, 2016. "Convergence rates of sums of α-mixing triangular arrays : with an application to non-parametric drift function estimation of continuous-time processes," Discussion Paper Series 646, Institute of Economic Research, Hitotsubashi University.
    3. Christian Gourieroux & Joann Jasiak, 2022. "Long Run Risk in Stationary Structural Vector Autoregressive Models," Papers 2202.09473, arXiv.org.
    4. Luciano de Castro & Antonio F. Galvao & David M. Kaplan, 2017. "Smoothed instrumental variables quantile regression, with estimation of quantile Euler equations," Working Papers 1710, Department of Economics, University of Missouri, revised 28 Feb 2018.
    5. Joann Jasiak & Aryan Manafi Neyazi, 2023. "GCov-Based Portmanteau Test," Papers 2312.05373, arXiv.org.

  29. James Davidson & Robert de Jong, 1997. "Strong laws of large numbers for dependent heterogeneous processes: a synthesis of recent and new results," Econometric Reviews, Taylor & Francis Journals, vol. 16(3), pages 251-279.

    Cited by:

    1. Kanaya, Shin, 2016. "Convergence rates of sums of α-mixing triangular arrays : with an application to non-parametric drift function estimation of continuous-time processes," Discussion Paper Series 646, Institute of Economic Research, Hitotsubashi University.
    2. Benedikt M. Pötscher & Ingmar R. Prucha, 1999. "Basic Elements of Asymptotic Theory," Electronic Working Papers 99-001, University of Maryland, Department of Economics.
    3. J. Isaac Miller, 2010. "Cointegrating regressions with messy regressors and an application to mixed‐frequency series," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 255-277, July.
    4. Cizek, P., 2004. "Asymptotics of Least Trimmed Squares Regression," Other publications TiSEM dab5d551-aca6-40bf-b92e-c, Tilburg University, School of Economics and Management.
    5. Giovanni Cerulli, 2012. "Are R&D Subsidies Provided Optimally? Evidence from a Simulated Agency-Firm Stochastic Dynamic Game," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(1), pages 1-7.
    6. Yves Atchade, 2005. "An Adaptive Version for the Metropolis Adjusted Langevin Algorithm with a Truncated Drift," RePAd Working Paper Series LRSP-WP1, Département des sciences administratives, UQO.
    7. Yves F. Atchadé, 2006. "An Adaptive Version for the Metropolis Adjusted Langevin Algorithm with a Truncated Drift," Methodology and Computing in Applied Probability, Springer, vol. 8(2), pages 235-254, June.
    8. J. Isaac Miller, 2007. "Cointegrating Regressions with Messy Regressors: Missingness, Mixed Frequency, and Measurement Error," Working Papers 0722, Department of Economics, University of Missouri, revised 15 Apr 2009.

  30. de Jong, Robert M., 1997. "Central Limit Theorems for Dependent Heterogeneous Random Variables," Econometric Theory, Cambridge University Press, vol. 13(3), pages 353-367, June.

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    1. Seo, Myung Hwan & Linton, Oliver, 2007. "A smoothed least squares estimator for threshold regression models," Journal of Econometrics, Elsevier, vol. 141(2), pages 704-735, December.
    2. George Kapetanios & M. Hashem Pesaran & Takashi Yamagata, 2006. "Panels with Nonstationary Multifactor Error Structures," Working Papers 569, Queen Mary University of London, School of Economics and Finance.
    3. Donald W. K. Andrews & Xu Cheng, 2011. "Maximum Likelihood Estimation and Uniform Inference with Sporadic Identification Failure," Cowles Foundation Discussion Papers 1824R, Cowles Foundation for Research in Economics, Yale University, revised Oct 2012.
    4. Manuel Lukas & Eric Hillebrand, 2014. "Bagging Weak Predictors," CREATES Research Papers 2014-01, Department of Economics and Business Economics, Aarhus University.
    5. Mengya Liu & Fukan Zhu & Ke Zhu, 2020. "Multi-frequency-band tests for white noise under heteroskedasticity," Papers 2004.09161, arXiv.org.
    6. Calhoun, Gray, 2014. "Out-Of-Sample Comparisons of Overfit Models," Staff General Research Papers Archive 32462, Iowa State University, Department of Economics.
    7. Todd E. Clark & Michael W. McCracken, 2009. "In-sample tests of predictive ability: a new approach," Research Working Paper RWP 09-10, Federal Reserve Bank of Kansas City.
    8. Donald W.K. Andrews, 2017. "Identification-Robust Subvector Inference," Cowles Foundation Discussion Papers 2105, Cowles Foundation for Research in Economics, Yale University, revised Sep 2017.
    9. Yuri Kifer, 2013. "A Nonconventional Invariance Principle for Random Fields," Journal of Theoretical Probability, Springer, vol. 26(2), pages 489-513, June.
    10. Davidson, James, 2020. "A new consistency proof for HAC variance estimators," Economics Letters, Elsevier, vol. 186(C).
    11. Robert F. Engle & Aaron D. Smith, 1999. "Stochastic Permanent Breaks," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 553-574, November.
    12. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.
    13. Qiu, Jin & Ma, Qing & Wu, Lang, 2019. "A moving blocks empirical likelihood method for panel linear fixed effects models with serial correlations and cross-sectional dependences," Economic Modelling, Elsevier, vol. 83(C), pages 394-405.
    14. Robert M. de Jong & Tiemen Woutersen, 2007. "Dynamic time series binary choice," Economics Working Paper Archive 538, The Johns Hopkins University,Department of Economics.
    15. Andrews, Donald W.K. & Guggenberger, Patrik, 2017. "Asymptotic Size Of Kleibergen’S Lm And Conditional Lr Tests For Moment Condition Models," Econometric Theory, Cambridge University Press, vol. 33(5), pages 1046-1080, October.
    16. J. Isaac Miller, 2010. "Cointegrating regressions with messy regressors and an application to mixed‐frequency series," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 255-277, July.
    17. Davidson, James, 2002. "Establishing conditions for the functional central limit theorem in nonlinear and semiparametric time series processes," Journal of Econometrics, Elsevier, vol. 106(2), pages 243-269, February.
    18. Andreou, Elena & Ghysels, Eric, 2006. "Monitoring disruptions in financial markets," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 77-124.
    19. Shin S. Ikeda, 2013. "A Note on the Mixingale Limit Theorem by McLeish (1977)," GRIPS Discussion Papers 13-11, National Graduate Institute for Policy Studies.
    20. Fawcett, Nicholas & Kapetanios, George & Mitchell, James & Price, Simon, 2014. "Generalised density forecast combinations," Bank of England working papers 492, Bank of England.
    21. Adamek, Robert & Smeekes, Stephan & Wilms, Ines, 2023. "Lasso inference for high-dimensional time series," Journal of Econometrics, Elsevier, vol. 235(2), pages 1114-1143.
    22. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Post-Print hal-00834423, HAL.
    23. Blasques, F. & Francq, Christian & Laurent, Sébastien, 2023. "Quasi score-driven models," Journal of Econometrics, Elsevier, vol. 234(1), pages 251-275.
    24. Verena Monschang & Mark Trede & Bernd Wilfling, 2023. "Multi-horizon uniform superior predictive ability revisited: A size-exploiting and consistent test," CQE Working Papers 10623, Center for Quantitative Economics (CQE), University of Muenster.
    25. J. Isaac Miller, 2010. "A Nonlinear IV Likelihood-Based Rank Test for Multivariate Time Series and Long Panels," Working Papers 1001, Department of Economics, University of Missouri.
    26. Jonathan Hill, 2012. "Dependence and stochastic limit theory (in Russian)," Quantile, Quantile, issue 10, pages 1-31, December.
    27. Mynbayev, Kairat & Darkenbayeva, Gulsim, 2019. "Analyzing variance in central limit theorems," MPRA Paper 101685, University Library of Munich, Germany.
    28. 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.
    29. Burak Alparslan Eroğlu & J. Isaac Miller & Taner Yiğit, 2022. "Time-varying cointegration and the Kalman filter," Econometric Reviews, Taylor & Francis Journals, vol. 41(1), pages 1-21, January.
    30. Gençay, Ramazan & Signori, Daniele, 2015. "Multi-scale tests for serial correlation," Journal of Econometrics, Elsevier, vol. 184(1), pages 62-80.
    31. Roy, Archi & Soni, Anchal & Deb, Soudeep, 2023. "A wavelet-based methodology to compare the impact of pandemic versus Russia–Ukraine conflict on crude oil sector and its interconnectedness with other energy and non-energy markets," Energy Economics, Elsevier, vol. 124(C).
    32. Mikihito Nishi, 2024. "Estimating Time-Varying Parameters of Various Smoothness in Linear Models via Kernel Regression," Papers 2406.14046, arXiv.org, revised Oct 2024.
    33. Calhoun, Gray, 2014. "Block Bootstrap Consistency Under Weak Assumptions," Staff General Research Papers Archive 34313, Iowa State University, Department of Economics.
    34. Li, Yong & Yu, Jun & Zeng, Tao, 2020. "Deviance information criterion for latent variable models and misspecified models," Journal of Econometrics, Elsevier, vol. 216(2), pages 450-493.
    35. Manuel Landajo & María José Presno, 2010. "Stationarity testing under nonlinear models. Some asymptotic results," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(5), pages 392-405, September.
    36. Fuqi Chen & Sévérien Nkurunziza, 2016. "A class of Stein-rules in multivariate regression model with structural changes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(1), pages 83-102, March.
    37. George Kapetanios & Zacharias Psaradakis, 2016. "Semiparametric Sieve-Type Generalized Least Squares Inference," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 951-985, June.
    38. Qiu, Jin & Lin, Zhengyan, 2006. "The variance of partial sums of strong near-epoch dependent variables," Statistics & Probability Letters, Elsevier, vol. 76(17), pages 1845-1854, November.
    39. Jean-Jacques Forneron, 2019. "A Sieve-SMM Estimator for Dynamic Models," Papers 1902.01456, arXiv.org, revised Jan 2023.
    40. 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.
    41. Jonathan B. Hill, 2005. "On Tail Index Estimation for Dependent, Heterogenous Data," Econometrics 0505005, University Library of Munich, Germany, revised 24 Mar 2006.

  31. de Jong, Robert M., 1996. "A strong law of large numbers for triangular mixingale arrays," Statistics & Probability Letters, Elsevier, vol. 27(1), pages 1-9, March.

    Cited by:

    1. Kanaya, Shin, 2016. "Convergence rates of sums of α-mixing triangular arrays : with an application to non-parametric drift function estimation of continuous-time processes," Discussion Paper Series 646, Institute of Economic Research, Hitotsubashi University.

  32. de Jong, Robert M., 1996. "The Bierens test under data dependence," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 1-32.

    Cited by:

    1. Jonathan B. Hill, 2004. "Consistent LM-Tests for Linearity Against Compound Smooth Transition Alternatives," Econometric Society 2004 North American Summer Meetings 42, Econometric Society.
    2. Horowitz, Joel L. & Spokoiny, Vladimir G., 1999. "An Adaptive, Rate-Optimal Test of a Parametric Model Against a Nonparametric Alternative," Working Papers 99-02, University of Iowa, Department of Economics.
    3. Cheng Hsiao & Qi Li & Jeff Racine, 2006. "A Consistent Model Specification Test with Mixed Discrete and Continuous Data," IEPR Working Papers 06.47, Institute of Economic Policy Research (IEPR).
    4. Krikamol Muandet & Wittawat Jitkrittum & Jonas Kubler, 2020. "Kernel Conditional Moment Test via Maximum Moment Restriction," Papers 2002.09225, arXiv.org, revised Jun 2020.
    5. Clark, Todd E. & West, Kenneth D., 2006. "Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 155-186.
    6. Domínguez, Manuel A., 1997. "Consistent specification testing of quantile regression models," DES - Working Papers. Statistics and Econometrics. WS 6211, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. 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.
    8. Hill, Jonathan B. & Aguilar, Mike, 2013. "Moment condition tests for heavy tailed time series," Journal of Econometrics, Elsevier, vol. 172(2), pages 255-274.
    9. Juan Carlos Escanciano & Carlos Velasco, 2006. "Testing the Martingale Difference Hypothesis Using Integrated Regression Functions," Faculty Working Papers 06/06, School of Economics and Business Administration, University of Navarra.
    10. Wasel Shadat, 2011. "On the Nonparametric Tests of Univariate GARCH Regression Models," Economics Discussion Paper Series 1115, Economics, The University of Manchester.
    11. Kevin Sheppard & Andrew J. Patton, 2008. "Evaluating Volatility and Correlation Forecasts," Economics Series Working Papers 2008fe22, University of Oxford, Department of Economics.
    12. Jonathan B. Hill, 2004. "Consistent Model Specification Tests Against Smooth Transition Alternatives," Econometrics 0402004, University Library of Munich, Germany, revised 05 Aug 2005.
    13. Masamune Iwasawa, 2015. "A Joint Specification Test for Response Probabilities in Unordered Multinomial Choice Models," Econometrics, MDPI, vol. 3(3), pages 1-31, September.
    14. Corradi, Valentina & Swanson, Norman R., 2002. "A consistent test for nonlinear out of sample predictive accuracy," Journal of Econometrics, Elsevier, vol. 110(2), pages 353-381, October.
    15. Kuan Chung-Ming & Lee Wei-Ming, 2004. "A New Test of the Martingale Difference Hypothesis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(4), pages 1-26, December.
    16. Norman R. Swanson & Valentina Corradi & Andres Fernandez, 2011. "Information in the Revision Process of Real-Time Datasets," Departmental Working Papers 201107, Rutgers University, Department of Economics.
    17. Ignacio N. Lobato, 2000. "A Consistent Test for the Martingale Difference Assumption," Econometric Society World Congress 2000 Contributed Papers 0278, Econometric Society.
    18. Park, Joon Y. & Whang, Yoon-Jae, 2004. "A Test of the Martingale Hypothesis," Working Papers 2004-11, Rice University, Department of Economics.
    19. Jungyoon Lee & Peter C.B. Phillips & Francesca Rossi, 2020. "Consistent Misspecification Testing in Spatial Autoregressive Models," Cowles Foundation Discussion Papers 2256, Cowles Foundation for Research in Economics, Yale University.
    20. O‐Chia Chuang & Xiaojun Song & Abderrahim Taamouti, 2022. "Testing for Asymmetric Comovements," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(5), pages 1153-1180, October.
    21. Kourogenis, Nikolaos & Pittis, Nikitas & Samartzis, Panagiotis, 2024. "Unbounded heteroscedasticity in autoregressive models," The Journal of Economic Asymmetries, Elsevier, vol. 29(C).
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    1. Seo, Myung Hwan & Linton, Oliver, 2007. "A smoothed least squares estimator for threshold regression models," Journal of Econometrics, Elsevier, vol. 141(2), pages 704-735, December.
    2. Lei, J., 2013. "Smoothed Spatial Maximum Score Estimation of Spatial Autoregressive Binary Choice Panel Models," Other publications TiSEM d63bf400-7ff2-4a1c-8067-1, Tilburg University, School of Economics and Management.
    3. Danilova, Albina & Julliard, Christian, 2015. "Information asymmetries, volatility, liquidity and the Tobin Tax," LSE Research Online Documents on Economics 119016, London School of Economics and Political Science, LSE Library.
    4. Kanaya, Shin, 2016. "Convergence rates of sums of α-mixing triangular arrays : with an application to non-parametric drift function estimation of continuous-time processes," Discussion Paper Series 646, Institute of Economic Research, Hitotsubashi University.
    5. Robert F. Engle & Aaron D. Smith, 1999. "Stochastic Permanent Breaks," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 553-574, November.
    6. de Jong, Robert M., 1996. "A strong law of large numbers for triangular mixingale arrays," Statistics & Probability Letters, Elsevier, vol. 27(1), pages 1-9, March.
    7. Wu, Rongning & Cao, Jiguo, 2011. "Blockwise empirical likelihood for time series of counts," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 661-673, March.
    8. Pavel Yaskov, 2018. "LLN for Quadratic Forms of Long Memory Time Series and Its Applications in Random Matrix Theory," Journal of Theoretical Probability, Springer, vol. 31(4), pages 2032-2055, December.
    9. de Jong, Robert M., 1998. "Uniform laws of large numbers and stochastic Lipschitz-continuity," Journal of Econometrics, Elsevier, vol. 86(2), pages 243-268, June.
    10. Lei, J., 2013. "Smoothed Spatial Maximum Score Estimation of Spatial Autoregressive Binary Choice Panel Models," Discussion Paper 2013-061, Tilburg University, Center for Economic Research.
    11. Peter Farkas & Laszlo Matyas, 2015. "Testing for Unit Roots in Panel Data with Boundary Crossing Counts," CEU Working Papers 2015_5, Department of Economics, Central European University, revised 03 Nov 2015.

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    1. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Nonparametric Tests for Treatment Effect Heterogeneity," NBER Technical Working Papers 0324, National Bureau of Economic Research, Inc.
    2. Andreou, Elena & Kasparis, Ioannis & Phillips, Peter C. B., 2013. "Nonparametric Predictive Regression," CEPR Discussion Papers 9570, C.E.P.R. Discussion Papers.
    3. Koenker, Roger & Machado, Jose A. F., 1999. "GMM inference when the number of moment conditions is large," Journal of Econometrics, Elsevier, vol. 93(2), pages 327-344, December.
    4. Stanislav Anatolyev, 2009. "Inference in Regression Models with Many Regressors," Working Papers w0125, New Economic School (NES).
    5. Karun Adusumilli & Taisuke Otsu, 2017. "Empirical Likelihood for Random Sets," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1064-1075, July.
    6. Abhimanyu Gupta & Myung Hwan Seo, 2019. "Robust Inference on Infinite and Growing Dimensional Time Series Regression," Papers 1911.08637, arXiv.org, revised Apr 2023.
    7. Domínguez, Manuel A., 1997. "Consistent specification testing of quantile regression models," DES - Working Papers. Statistics and Econometrics. WS 6211, Universidad Carlos III de Madrid. Departamento de Estadística.
    8. Ellison, Glenn & Ellison, Sara Fisher, 2000. "A simple framework for nonparametric specification testing," Journal of Econometrics, Elsevier, vol. 96(1), pages 1-23, May.
    9. Donald, Stephen G. & Imbens, Guido W. & Newey, Whitney K., 2003. "Empirical likelihood estimation and consistent tests with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 117(1), pages 55-93, November.
    10. Tue Gørgens & Allan Würtz, 2009. "Testing a parametric function against a nonparametric alternative in IV and GMM settings," CREATES Research Papers 2009-54, Department of Economics and Business Economics, Aarhus University.
    11. Otsu, Taisuke & Matsushita, Yukitoshi & Xu, Ke-Li, 2014. "Empirical likelihood for regression discontinuity design," LSE Research Online Documents on Economics 58065, London School of Economics and Political Science, LSE Library.
    12. Ignacio N. Lobato, 2000. "A Consistent Test for the Martingale Difference Assumption," Econometric Society World Congress 2000 Contributed Papers 0278, Econometric Society.
    13. Hill Jonathan B., 2013. "Stochastically weighted average conditional moment tests of functional form," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(2), pages 121-139, April.
    14. Amengual, Dante & Carrasco, Marine & Sentana, Enrique, 2020. "Testing distributional assumptions using a continuum of moments," Journal of Econometrics, Elsevier, vol. 218(2), pages 655-689.
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    16. Demian Pouzo, 2014. "Bootstrap Consistency for Quadratic Forms of Sample Averages with Increasing Dimension," Papers 1411.2701, arXiv.org, revised Aug 2015.
    17. Parente, Paulo M.D.C. & Smith, Richard J., 2017. "Tests of additional conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 200(1), pages 1-16.
    18. Ait-Sahalia, Yacine & Bickel, Peter J. & Stoker, Thomas M., 2001. "Goodness-of-fit tests for kernel regression with an application to option implied volatilities," Journal of Econometrics, Elsevier, vol. 105(2), pages 363-412, December.
    19. Gupta, A, 2015. "Nonparametric specification testing via the trinity of tests," Economics Discussion Papers 23824, University of Essex, Department of Economics.
    20. Paulo Parente & Richard Smith, 2012. "Exogeneity in semiparametric moment condition models," CeMMAP working papers 30/12, Institute for Fiscal Studies.
    21. Domínguez, Manuel A. & Lavergne, Pascal, 1998. "Asymptotic and bootstrap specification tests of nonlinear in variable econometric models," DES - Working Papers. Statistics and Econometrics. WS 4674, Universidad Carlos III de Madrid. Departamento de Estadística.
    22. Abhimanyu Gupta & Xi Qu, 2021. "Consistent specification testing under spatial dependence," Papers 2101.10255, arXiv.org, revised Aug 2022.

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