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Ivana Komunjer

Citations

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

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Arnaud Costinot & Dave Donaldson & Ivana Komunjer, 2010. "What Goods Do Countries Trade? A Quantitative Exploration of Ricardo's Ideas," NBER Working Papers 16262, National Bureau of Economic Research, Inc.

    Mentioned in:

    1. Whither Ricardian comparative advantage?
      by jdingel in Trade Diversion on 2011-06-08 22:40:23

Working papers

  1. Nikolay Gospodinov & Ivana Komunjer & Serena Ng, 2014. "Minimum Distance Estimation of Dynamic Models with Errors-In-Variables," FRB Atlanta Working Paper 2014-11, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Meijer, Erik & Spierdijk, Laura & Wansbeek, Tom, 2017. "Consistent estimation of linear panel data models with measurement error," Journal of Econometrics, Elsevier, vol. 200(2), pages 169-180.
    2. Gospodinov, Nikolay & Komunjer, Ivana & Ng, Serena, 2017. "Simulated minimum distance estimation of dynamic models with errors-in-variables," Journal of Econometrics, Elsevier, vol. 200(2), pages 181-193.

  2. Julieta Caunedo & Riccardo DiCecio & Ivana Komunjer & Michael T. Owyang, 2013. "Asymmetry, Complementarities, and State Dependence in Federal Reserve Forecasts," Working Papers 2013-012, Federal Reserve Bank of St. Louis, revised 29 Dec 2017.

    Cited by:

    1. Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2015. "Central banks’ inflation forecasts under asymmetric loss: Evidence from four Latin-American countries," Economics Letters, Elsevier, vol. 129(C), pages 66-70.
    2. Tara Sinclair & Herman O. Stekler & Warren Carrow, 2012. "Evaluating a Vector of the Fed's Forecasts," Working Papers 2012-3, The George Washington University, Institute for International Economic Policy.
    3. Travis J. Berge & Andrew C. Chang & Nitish R. Sinha, 2019. "Evaluating the Conditionality of Judgmental Forecasts," Finance and Economics Discussion Series 2019-002, Board of Governors of the Federal Reserve System (U.S.).
    4. Mihaela SIMIONESCU, 2015. "The Evaluation of Global Accuracy of Romanian Inflation Rate Predictions Using Mahalanobis Distance," Management Dynamics in the Knowledge Economy, College of Management, National University of Political Studies and Public Administration, vol. 3(1), pages 133-149, March.
    5. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2021. "The Rationality of USDA Forecasts under Multivariate Asymmetric Loss," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1006-1033, May.
    6. Yoichi Tsuchiya, 2022. "Evaluating plant managers’ production plans over business cycles: asymmetric loss and rationality," SN Business & Economics, Springer, vol. 2(8), pages 1-29, August.
    7. Garratt, Anthony & Petrella, Ivan & Zhang, Yunyi, 2022. "Asymmetry and Interdependence when Evaluating U.S. Energy Information Administration Forecasts," MPRA Paper 115559, University Library of Munich, Germany.

  3. Pierre-Andre Chiappori & Ivana Komunjer & Dennis Kristensen, 2011. "Nonparametric Identification and Estimation of Transformation Models," CAM Working Papers 2011-01, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.

    Cited by:

    1. Senay Sokullu, 2012. "Nonparametric Estimation of Semiparametric Transformation Models," Bristol Economics Discussion Papers 12/625, School of Economics, University of Bristol, UK.
    2. Gouriéroux, Christian & Monfort, Alain & Zakoian, Jean-Michel, 2017. "Pseudo-Maximum Likelihood and Lie Groups of Linear Transformations," MPRA Paper 79623, University Library of Munich, Germany.
    3. Áureo de Paula & Imran Rasul & Pedro CL Souza, 2023. "Identifying network ties from panel data: Theory and an application to tax competition," CeMMAP working papers 21/23, Institute for Fiscal Studies.
    4. Kloodt, Nick, 2021. "Identification in a fully nonparametric transformation model with heteroscedasticity," Statistics & Probability Letters, Elsevier, vol. 170(C).
    5. Irene Botosaru & Chris Muris, 2017. "Binarization for panel models with fixed effects," CeMMAP working papers CWP31/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Botosaru, Irene & Muris, Chris & Pendakur, Krishna, 2023. "Identification of time-varying transformation models with fixed effects, with an application to unobserved heterogeneity in resource shares," Journal of Econometrics, Elsevier, vol. 232(2), pages 576-597.
    7. Effraimidis, Georgios, 2016. "Nonparametric Identification of a Time-Varying Frailty Model," DaCHE discussion papers 2016:6, University of Southern Denmark, Dache - Danish Centre for Health Economics.
    8. Hoderlein, Stefan & Su, Liangjun & White, Halbert & Yang, Thomas Tao, 2016. "Testing for monotonicity in unobservables under unconfoundedness," Journal of Econometrics, Elsevier, vol. 193(1), pages 183-202.
    9. Christoph Breunig & Stephan Martin, 2020. "Nonclassical Measurement Error in the Outcome Variable," Papers 2009.12665, arXiv.org, revised May 2021.
    10. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," LSE Research Online Documents on Economics 103830, London School of Economics and Political Science, LSE Library.
    11. Áureo de Paula & Imran Rasul & Pedro CL Souza, 2018. "Recovering social networks from panel data: identification, simulations and an application," CeMMAP working papers CWP17/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Ruixuan Liu, 2020. "A competing risks model with time‐varying heterogeneity and simultaneous failure," Quantitative Economics, Econometric Society, vol. 11(2), pages 535-577, May.
    13. Liyu Dou & Jakub Kastl & John Lazarev, 2020. "Quantifying Delay Externalities in Airline Networks," Working Papers 2020-65, Princeton University. Economics Department..
    14. Timo Kuosmanen & Sheng Dai, 2023. "Modeling economies of scope in joint production: Convex regression of input distance function," Papers 2311.11637, arXiv.org.
    15. Andrew Chesher & Adam Rosen & Konrad Smolinski, 2011. "An instrumental variable model of multiple discrete choice," CeMMAP working papers CWP39/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Arthur Lewbel & Xun Lu & Liangjun Su, 2012. "Specification Testing for Transformation Models with an Application to Generalized Accelerated Failure-time Models," Boston College Working Papers in Economics 817, Boston College Department of Economics, revised 01 May 2013.
    17. Bonev, Petyo, 2020. "Nonparametric identification in nonseparable duration models with unobserved heterogeneity," Economics Working Paper Series 2005, University of St. Gallen, School of Economics and Political Science.
    18. Joachim Freyberger, 2021. "Normalizations and misspecification in skill formation models," Papers 2104.00473, arXiv.org, revised Jul 2022.
    19. Senay Sokullu & Irene Botosaru & Chris Muris, 2022. "Time-Varying Linear Transformation Models with Fixed Effects and Endogeneity for Short Panels," Bristol Economics Discussion Papers 22/756, School of Economics, University of Bristol, UK.
    20. Shosei Sakaguchi, 2024. "Partial identification and inference in duration models with endogenous censoring," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 308-326, March.
    21. Breunig, Christoph, 2016. "Specification testing in nonparametric instrumental quantile regression," SFB 649 Discussion Papers 2016-032, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    22. Lin, Yingqian & Tu, Yundong, 2024. "Functional coefficient cointegration models with Box–Cox transformation," Economics Letters, Elsevier, vol. 234(C).
    23. Centorrino, Samuele & Parmeter, Christopher F., 2024. "Nonparametric estimation of stochastic frontier models with weak separability," Journal of Econometrics, Elsevier, vol. 238(2).
    24. Nick Kloodt & Natalie Neumeyer & Ingrid Keilegom, 2021. "Specification testing in semi-parametric transformation models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(4), pages 980-1003, December.
    25. Irene Botosaru & Chris Muris & Krishna Pendakur, 2020. "Intertemporal Collective Household Models: Identification in Short Panels with Unobserved Heterogeneity in Resource Shares," Department of Economics Working Papers 2020-09, McMaster University.
    26. Christoph Breunig, 2019. "Specification Testing in Nonparametric Instrumental Quantile Regression," Papers 1909.10129, arXiv.org.
    27. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," Journal of Econometrics, Elsevier, vol. 216(1), pages 175-191.
    28. Krief, Jerome M., 2017. "Direct instrumental nonparametric estimation of inverse regression functions," Journal of Econometrics, Elsevier, vol. 201(1), pages 95-107.
    29. Chalak, Karim, 2024. "Nonparametric Gini-Frisch bounds," Journal of Econometrics, Elsevier, vol. 238(1).
    30. Hubner, Stefan, 2023. "Identification of unobserved distribution factors and preferences in the collective household model," Journal of Econometrics, Elsevier, vol. 234(1), pages 301-326.

  4. Arnaud Costinot & Dave Donaldson & Ivana Komunjer, 2010. "What Goods Do Countries Trade? A Quantitative Exploration of Ricardo's Ideas," NBER Working Papers 16262, National Bureau of Economic Research, Inc.

    Cited by:

    1. Larch, Mario & Luckstead, Jeff & Yotov, Yoto, 2021. "Economic Sanctions and Agricultural Trade," School of Economics Working Paper Series 2021-16, LeBow College of Business, Drexel University.
    2. W. Steingress, 2015. "Specialization Patterns in International Trade," Working papers 542, Banque de France.
    3. Gabriel J. Felbermayr & Jasmin Katrin Gröschl & Benedikt Heid, 2020. "Quantifying the Supply and Demand Effects of Natural Disasters Using Monthly Trade Data," CESifo Working Paper Series 8798, CESifo.
    4. Elizaveta Archanskaia, 2013. "Proximity as a Source of Comparative Advantage," SciencePo Working papers Main hal-01070440, HAL.
    5. Ding Nan & Pomi Shahbaz & Shamsheer ul Haq & Muhammad Nadeem & Muhammad Imran, 2023. "The Economies’ Ability to Produce Diversified and Complex Goods to Meet the Global Competition: Role of Gross Value Chain, Institutional Quality, and Human Capital," Sustainability, MDPI, vol. 15(8), pages 1-17, April.
    6. Nan Li & Jie Cai & Ana Maria Santacreu, 2017. "Knowledge Diffusion and Trade across Countries and Sectors," 2017 Meeting Papers 692, Society for Economic Dynamics.
    7. French, Scott, 2016. "The composition of trade flows and the aggregate effects of trade barriers," Journal of International Economics, Elsevier, vol. 98(C), pages 114-137.
    8. de Sousa, J. & Mayer, T. & Zignago, S., 2011. "Market access in global and regional trade," Working papers 358, Banque de France.
    9. Vasilii Erokhin & Gao Tianming & Anna Ivolga, 2021. "Cross-Country Potentials and Advantages in Trade in Fish and Seafood Products in the RCEP Member States," Sustainability, MDPI, vol. 13(7), pages 1-40, March.
    10. Sandra Poncet & Felipe Starosta de Waldemar, 2014. "Product relatedness and firm exports in China," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01044982, HAL.
    11. Daniel M. Bernhofen, 2010. "The Empirics of General Equilibrium Trade Theory: What Have We Learned?," Discussion Papers 10/24, University of Nottingham, GEP.
    12. Céline CARRERE & Marco FUGAZZA & Marcelo OLARREAGA & Frédéric ROBERT-NICOUD, 2016. "On the heterogeneous effect of trade on unemployment," Working Papers P180, FERDI.
    13. Jerónimo Carballo & Ignacio Marra de Artiñano & Christian Volpe Martincus, 2021. "Information Frictions, Investment Promotion, and Multinational Production: Firm-Level Evidence," CESifo Working Paper Series 9043, CESifo.
    14. Gordeev, Roman, 2020. "Comparative advantages of Russian forest products on the global market," Forest Policy and Economics, Elsevier, vol. 119(C).
    15. Francois, Joseph & Bekkers, Eddy & Rojas-Romagosa, Hugo, 2016. "Melting Ice Caps and the Economic Impact of Opening the Northern Sea Route," CEPR Discussion Papers 11670, C.E.P.R. Discussion Papers.
    16. Schetter, Ulrich & Diodato, Dario & Protzer, Eric & Neffke, Frank & Hausmann, Ricardo, 2024. "From Products to Capabilities: Constructing a Genotypic Product Space," CEPR Discussion Papers 19369, C.E.P.R. Discussion Papers.
    17. Bahar, Dany & Rosenow, Samuel & Stein, Ernesto & Wagner, Rodrigo, 2019. "Export take-offs and acceleration: Unpacking cross-sector linkages in the evolution of comparative advantage," World Development, Elsevier, vol. 117(C), pages 48-60.
    18. Caron, Justin & Fally, Thibault, 2018. "Per Capita Income, Consumption Patterns, and CO2 Emissions," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt0n98j4z7, Department of Agricultural & Resource Economics, UC Berkeley.
    19. Lo, Chu-Ping & Yang, Chih-Hai, 2020. "Business Services,Trade,and Research Intensity," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 61(1), pages 38-59, June.
    20. Konstantin Kucheryavyy & Gary Lyn & Andrés Rodríguez-Clare, 2023. "Grounded by Gravity: A Well-Behaved Trade Model with Industry-Level Economies of Scale," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(2), pages 372-412, April.
    21. Julian di Giovanni & Andrei A. Levchenko, 2012. "The Risk Content of Exports: A Portfolio View of International Trade," NBER International Seminar on Macroeconomics, University of Chicago Press, vol. 8(1), pages 97-151.
    22. Sebastian Sotelo, 2020. "Domestic Trade Frictions and Agriculture," Journal of Political Economy, University of Chicago Press, vol. 128(7), pages 2690-2738.
    23. Heerman, Kari E. & Sheldon, Ian M., 2018. "Increased economic integration in the Asia-Pacific Region: What might be the potential impact on agricultural trade?," 2018 Annual Meeting, August 5-7, Washington, D.C. 274279, Agricultural and Applied Economics Association.
    24. Stephen J. Redding & David E. Weinstein, 2018. "Aggregating From Micro to Macro Patterns of Trade," Working Papers 18-10, Center for Economic Studies, U.S. Census Bureau.
    25. Egger, Peter H. & Nigai, Sergey, 2015. "Structural gravity with dummies only: Constrained ANOVA-type estimation of gravity models," Journal of International Economics, Elsevier, vol. 97(1), pages 86-99.
    26. Boehm, Johannes, 2015. "The impact of contract enforcement costs onoutsourcing and aggregate productivity," LSE Research Online Documents on Economics 64997, London School of Economics and Political Science, LSE Library.
    27. Rodrigo Adao & Arnaud Costinot & Dave Donaldson, 2017. "Nonparametric Counterfactual Predictions in Neoclassical Models of International Trade," American Economic Review, American Economic Association, vol. 107(3), pages 633-689, March.
    28. Cecilia Bellora & Jean-Marc Bourgeon, 2016. "Food trade, Biodiversity Effects and Price Volatility," Working Papers 2016-06, CEPII research center.
    29. Andrei A Levchenko & Jing Zhang, 2013. "The Global Labor Market Impact of Emerging Giants: A Quantitative Assessment," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 61(3), pages 479-519, August.
    30. Alcalá, Francisco, 2016. "Specialization across goods and export quality," Journal of International Economics, Elsevier, vol. 98(C), pages 216-232.
    31. Laurence Wicht, 2020. "A multi-sector analysis of Switzerland's gains from trade," Working Papers 2020-20, Swiss National Bank.
    32. Lionel Fontagné & Gianluca Santoni, 2021. "GVCs and the endogenous geography of RTAs," Post-Print halshs-03956355, HAL.
    33. Sam Kortum & John Romalis & Brent Neiman & Jonathan Eaton, 2010. "Trade and the Global Recession," 2010 Meeting Papers 1340, Society for Economic Dynamics.
    34. Larch, Mario & Tan, Shawn W. & Yotov, Yoto V., 2023. "A simple method to ex-ante quantify the unobservable effects of trade liberalization and trade protection," Journal of Comparative Economics, Elsevier, vol. 51(4), pages 1200-1213.
    35. Sampson, Thomas, 2023. "Technology gaps, trade and income," LSE Research Online Documents on Economics 117370, London School of Economics and Political Science, LSE Library.
    36. Cebreros Alfonso, 2018. "Labor Heterogeneity and the Pattern of Trade," Working Papers 2018-01, Banco de México.
    37. Flach, Lisandra & Heiland, Inga & Larch, Mario & Steininger, Marina & Teti, Feodora A., 2023. "Quantifying the partial and general equilibrium effects of sanctions on Russia," Open Access Publications from Kiel Institute for the World Economy 302103, Kiel Institute for the World Economy (IfW Kiel).
    38. Robert-Nicoud, Frédéric & Carrère, Céline & Grujovic, Anja, 2019. "Trade and frictional unemployment in the global economy," CEPR Discussion Papers 10692, C.E.P.R. Discussion Papers.
    39. Sakamoto, Tomoyuki & Managi, Shunsuke, 2016. "New evidence of environmental efficiency on the export performance," MPRA Paper 74850, University Library of Munich, Germany, revised 2016.
    40. Ulrich Schetter, 2019. "A Structural Ranking of Economic Complexity," Growth Lab Working Papers 148, Harvard's Growth Lab.
    41. Costas Arkolakis & Arnaud Costinot & Dave Donaldson & Andrés Rodríguez-Clare, 2019. "The Elusive Pro-Competitive Effects of Trade," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(1), pages 46-80.
    42. Pierre-Daniel Sarte & Fernando Parro & Esteban Rossi-Hansberg & Lorenzo Caliendo, 2014. "The Impact of Regional and Sectoral Productivity Changes on the U.S. Economy," 2014 Meeting Papers 426, Society for Economic Dynamics.
    43. Theresa M. Greaney & Kozo Kiyota, 2020. "The gravity model and trade in intermediate inputs," The World Economy, Wiley Blackwell, vol. 43(8), pages 2034-2049, August.
    44. William R. Kerr, 2013. "Heterogeneous Technology Diffusion and Ricardian Trade Patterns," Harvard Business School Working Papers 14-039, Harvard Business School.
    45. Scott French, 2017. "Comparative Advantage and Biased Gravity," Discussion Papers 2017-03, School of Economics, The University of New South Wales.
    46. Juyoung Cheong & Shino Takayama & Terence Yeo, 2013. "Preferential Trade Agreements and Welfare: General Equilibrium Analysis," Discussion Papers Series 482, School of Economics, University of Queensland, Australia.
    47. Joao Paulo Pessoa, 2016. "International competition and labor market adjustment," CEP Discussion Papers dp1411, Centre for Economic Performance, LSE.
    48. Liuchun Deng, 2016. "Specialization Dynamics, Convergence, and Idea Flows," SERIES 09-2016, Dipartimento di Economia e Finanza - Università degli Studi di Bari "Aldo Moro", revised Nov 2016.
    49. Benny Kleinman & Ernest Liu & Stephen J. Redding, 2021. "Dynamic Spatial General Equilibrium," Working Papers 2021-31, Princeton University. Economics Department..
    50. Redding, Stephen & Weinstein, David, 2019. "Aggregation and the Gravity Equation," CEPR Discussion Papers 13459, C.E.P.R. Discussion Papers.
    51. Markus Brueckner & Ngo Van Long & Joaquin Vespignani, 2020. "Non-gravity trade," CAMA Working Papers 2020-52, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    52. Dongin Kim & Sandro Steinbach, 2024. "The Linder hypothesis for foreign direct investment revisited," Review of International Economics, Wiley Blackwell, vol. 32(4), pages 1901-1928, September.
    53. Arnaud Costinot & Andrés Rodríguez-Clare, 2013. "Trade Theory with Numbers: Quantifying the Consequences of Globalization," NBER Working Papers 18896, National Bureau of Economic Research, Inc.
    54. Nelson Lind & Natalia Ramondo, 2022. "Global Innovation and Knowledge Diffusion," NBER Working Papers 29629, National Bureau of Economic Research, Inc.
    55. Rudik, Ivan & Lyn, Gary & Tan, Weiliang & Ortiz-Bobea, Ariel, 2021. "Heterogeneity and Market Adaptation to Climate Change in Dynamic-Spatial Equilibrium," ISU General Staff Papers 202106020700001127, Iowa State University, Department of Economics.
    56. Mario Larch & Yoto V. Yotov, 2016. "General Equilibrium Trade Policy Analysis with Structural Gravity," CESifo Working Paper Series 6020, CESifo.
    57. Gnidchenko, A., 2014. "Improving the Methods for Estimating the Structure and the Basis of Export Potential through Export Diversification," Journal of the New Economic Association, New Economic Association, vol. 21(1), pages 83-109.
    58. Eum, Jihyun & Sheldon, Ian & Thompson, Stanley, 2017. "Asymmetric Trade Costs: Agricultural Trade among Developing and Developed Countries," 2017: Globalization Adrift, December 3-5, 2017, Washington, D.C. 266814, International Agricultural Trade Research Consortium.
    59. Lionel Fontagné & Philippe Martin & Gianluca Orefice, 2017. "The International Elasticity Puzzle Is Worse Than You Think," Working Papers 2017-03, CEPII research center.
    60. Redding, Stephen J. & Weinstein, David E., 2024. "Accounting for trade patterns," Journal of International Economics, Elsevier, vol. 150(C).
    61. Konstantakopoulou, Ioanna & Tsionas, Mike G., 2019. "Measuring comparative advantages in the Euro Area," Economic Modelling, Elsevier, vol. 76(C), pages 260-269.
    62. Blank, Sven & Egger, Peter H. & Merlo, Valeria & Wamser, Georg, 2022. "A structural quantitative analysis of services trade de-liberalization," Journal of International Economics, Elsevier, vol. 137(C).
    63. Morrow, Peter M. & Trefler, Daniel, 2022. "How do endowments determine trade? quantifying the output mix, factor price, and skill-biased technology channels," Journal of International Economics, Elsevier, vol. 137(C).
    64. Costa, Francisco Junqueira Moreira da & Pessoa, João Paulo, 2019. "Winners and losers from China’s ascension in international trade: a structural approach," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 809, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    65. Papageorgiou, Chris & Perez-Sebastian, Fidel & Spatafora, Nikola, 2016. "Quality Upgrading and the Stages of Diversification," MPRA Paper 79400, University Library of Munich, Germany.
    66. Mayer, Thierry & Bas, Maria, 2015. "From Micro to Macro: Demand, Supply, and Heterogeneity in the Trade Elasticity," CEPR Discussion Papers 10637, C.E.P.R. Discussion Papers.
    67. Andrianarimanana, Mihasina Harinaivo & Yongjian, Pu & Rabezanahary Tanteliniaina, Mirindra Finaritra, 2023. "Assessment of the importance of climate, land, and soil on the global supply for agricultural products and global food security: Evidence from Madagascar," Food Policy, Elsevier, vol. 115(C).
    68. Benny Kleinman & Ernest Liu & Stephen J. Redding, 2024. "International Friends and Enemies," American Economic Journal: Macroeconomics, American Economic Association, vol. 16(4), pages 350-385, October.
    69. Dominick Bartelme & Ting Lan & Mr. Andrei A Levchenko, 2024. "Specialization, Market Access and Real Income," IMF Working Papers 2024/051, International Monetary Fund.
    70. Levchenko, Andrei A. & Zhang, Jing, 2016. "The evolution of comparative advantage: Measurement and welfare implications," Journal of Monetary Economics, Elsevier, vol. 78(C), pages 96-111.
    71. Carballo, Jerónimo & Graziano, Alejandro & Schaur, Georg & Volpe Martincus, Christian, 2023. "Import Processing and Trade Costs," IDB Publications (Working Papers) 12716, Inter-American Development Bank.
    72. Dubey, Ram Sewak & Kang, Minwook, 2020. "Industrial subsidy policy and the optimal level of specialization," Economic Modelling, Elsevier, vol. 91(C), pages 81-88.
    73. Keith Head & Thierry Mayer, 2013. "Gravity Equations: Workhorse, Toolkit, and Cookbook," SciencePo Working papers Main hal-00973067, HAL.
    74. French, Scott, 2017. "Revealed comparative advantage: What is it good for?," Journal of International Economics, Elsevier, vol. 106(C), pages 83-103.
    75. Binoy Goswami & Hiranya K. Nath, 2020. "India's Revealed Comparative Advantages in Merchandise Trade with Country Groups at Different Levels of Development," Working Papers 2001, Sam Houston State University, Department of Economics and International Business.
    76. Gianluca Orefice & Hillel Rapoport & Gianluca Santoni, 2021. "How Do Immigrants Promote Exports?," Working Papers 2021-06, CEPII research center.
    77. Orefice, Gianluca & Rapoport, Hillel & Santoni, Gianluca, 2022. "How Do Immigrants Promote Exports? Networks, Knowledge, Diversity," IZA Discussion Papers 15722, Institute of Labor Economics (IZA).
    78. Nath, Hiranya K. & Liu, Lirong & Tochkov, Kiril, 2015. "Comparative advantages in U.S. bilateral services trade with China and India," Journal of Asian Economics, Elsevier, vol. 38(C), pages 79-92.
    79. Elizaveta Archanskaia & Guillaume Daudin, 2012. "Heterogeneity and the Distance Puzzle," Working Papers DT/2012/09, DIAL (Développement, Institutions et Mondialisation).
    80. Federico Esposito, 2017. "Entrepreneurial Risk and Diversification through Trade," Working Papers w201714, Banco de Portugal, Economics and Research Department.
    81. Kebede, Hundanol A., 2024. "Gains from market integration: Welfare effects of new rural roads in Ethiopia," Journal of Development Economics, Elsevier, vol. 168(C).
    82. Olarreaga, Marcelo & Ugarte, Cristian, 2020. "Can export promotion reduce unemployment?," CEPR Discussion Papers 15049, C.E.P.R. Discussion Papers.
    83. Bombardini, Matilde & Gallipoli, Giovanni & Pupato, Germán, 2014. "Unobservable skill dispersion and comparative advantage," Journal of International Economics, Elsevier, vol. 92(2), pages 317-329.
    84. Cecilia Bellora & Jean-Marc Bourgeon, 2015. "Agricultural Trade, Biodiversity Effects and Food Price Volatility," CESifo Working Paper Series 5417, CESifo.
    85. Nelson Lind & Natalia Ramondo, 2018. "Trade with Correlation," NBER Working Papers 24380, National Bureau of Economic Research, Inc.
    86. Pablo D. Fajgelbaum & Amit K. Khandelwal, 2014. "Measuring the Unequal Gains from Trade," NBER Working Papers 20331, National Bureau of Economic Research, Inc.
    87. Rodrigo Adão & Costas Arkolakis & Sharat Ganapati, 2020. "Aggregate Implications of Firm Heterogeneity: A Nonparametric Analysis of Monopolistic Competition Trade Models," Working Papers 2020-161, Becker Friedman Institute for Research In Economics.
    88. Larch, Mario & Tan, Shawn & Yotov, Yoto, 2021. "A simple method to quantify the ex-ante effects of “deep” trade liberalization and “hard” trade protection," School of Economics Working Paper Series 2021-14, LeBow College of Business, Drexel University.
    89. Redding, Stephen J., 2016. "Goods trade, factor mobility and welfare," Journal of International Economics, Elsevier, vol. 101(C), pages 148-167.
    90. Fabien Candau & Charles Regnacq & Julie Schlick, 2022. "Climate Change, Comparative Advantage and the Water Capability to Produce Agricultural Goods," Working papers of Transitions Energétiques et Environnementales (TREE) hal-03671521, HAL.
    91. Stefano Bolatto & Massimo Sbracia, 2016. "Deconstructing the Gains from Trade: Selection of Industries vs Reallocation of Workers," Review of International Economics, Wiley Blackwell, vol. 24(2), pages 344-363, May.
    92. Mariano A. Somale, 2017. "Comparative Advantage in Innovation and Production," International Finance Discussion Papers 1206, Board of Governors of the Federal Reserve System (U.S.).
    93. Clémence Lenoir & Julien Martin & Isabelle Mejean, 2023. "Search Frictions in International Goods Markets," Journal of the European Economic Association, European Economic Association, vol. 21(1), pages 326-366.
    94. Rodolfo Metulini & Stefania Tamea & Francesco Laio & Massimo Riccaboni, 2016. "The Water Suitcase of Migrants: Assessing Virtual Water Fluxes Associated to Human Migration," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-13, April.
    95. Charlotte Janssens & Petr Havlík & Tamás Krisztin & Justin Baker & Stefan Frank & Tomoko Hasegawa & David Leclère & Sara Ohrel & Shaun Ragnauth & Erwin Schmid & Hugo Valin & Nicole Van Lipzig & Miet M, 2020. "Global hunger and climate change adaptation through international trade," Nature Climate Change, Nature, vol. 10(9), pages 829-835, September.
    96. Borchert, Ingo & Larch, Mario & Shikher, Serge & Yotov, Yoto, 2020. "Disaggregated Gravity: Benchmark Estimates and Stylized Facts from a New Database," School of Economics Working Paper Series 2020-8, LeBow College of Business, Drexel University.
    97. Benedikt Heid & Frank Stähler, 2024. "Disentangling Frictions Across the World: Markups Versus Trade Costs," CESifo Working Paper Series 11420, CESifo.
    98. Chang-Tai Hsieh & Ralph Ossa, 2011. "A Global View of Productivity Growth in China," NBER Working Papers 16778, National Bureau of Economic Research, Inc.
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  5. Komunjer, Ivana & Ragusa, Giuseppe, 2009. "Existence and Uniqueness of Semiparametric Projections," University of California at San Diego, Economics Working Paper Series qt0wg3j51c, Department of Economics, UC San Diego.

    Cited by:

    1. Giacomini, Raffaella & Ragusa, Giuseppe, 2014. "Theory-coherent forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 145-155.

  6. Komunjer, Ivana & Santos, Andres, 2009. "Semiparametric Estimation of Nonseparable Models: A Minimum Distance from Independence Approach," University of California at San Diego, Economics Working Paper Series qt32k957bp, Department of Economics, UC San Diego.

    Cited by:

    1. Florian Gunsilius, 2018. "Point-identification in multivariate nonseparable triangular models," Papers 1806.09680, arXiv.org.
    2. Poirier, Alexandre, 2017. "Efficient estimation in models with independence restrictions," Journal of Econometrics, Elsevier, vol. 196(1), pages 1-22.
    3. Torgovitsky, Alexander, 2017. "Minimum distance from independence estimation of nonseparable instrumental variables models," Journal of Econometrics, Elsevier, vol. 199(1), pages 35-48.
    4. Liangjun Su & Stefan Hoderlein & Halbert White, 2013. "Testing Monotonicity in Unobservables with Panel Data," Boston College Working Papers in Economics 892, Boston College Department of Economics, revised 01 Feb 2016.
    5. Junlong Feng & Sokbae Lee, 2023. "Individual Welfare Analysis: Random Quasilinear Utility, Independence, and Confidence Bounds," Papers 2304.01921, arXiv.org, revised Nov 2024.

  7. Komunjer, Ivana, 2008. "Global Identification In Nonlinear Semiparametric Models," University of California at San Diego, Economics Working Paper Series qt2r59d87f, Department of Economics, UC San Diego.

    Cited by:

    1. Chiappori, Pierre-Andre & Komunjer, Ivana, 2008. "Correct Specification and Identification of Nonparametric Transformation Models," University of California at San Diego, Economics Working Paper Series qt4v12m2rg, Department of Economics, UC San Diego.
    2. Komunjer, Ivana, 2009. "Global identification of the semiparametric Box-Cox model," Economics Letters, Elsevier, vol. 104(2), pages 53-56, August.

  8. Komunjer, Ivana & OWYANG, MICHAEL, 2007. "Multivariate Forecast Evaluation And Rationality Testing," University of California at San Diego, Economics Working Paper Series qt81w8m5sf, Department of Economics, UC San Diego.

    Cited by:

    1. Gloria Gonzalez‐Rivera & Yun Luo & Esther Ruiz, 2020. "Prediction regions for interval‐valued time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 373-390, June.
    2. Sinclair, Tara M. & Gamber, Edward N. & Stekler, Herman & Reid, Elizabeth, 2012. "Jointly evaluating the Federal Reserve’s forecasts of GDP growth and inflation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 309-314.
    3. Gloria Gonzalez-Rivera & Wei Lin, 2015. "Interval-valued Time Series Models: Estimation based on Order Statistics. Exploring the Agriculture Marketing Service Data," Working Papers 201505, University of California at Riverside, Department of Economics.
    4. Emmanuel C. Mamatzakis & Mike G. Tsionas, 2020. "Revealing forecaster's preferences: A Bayesian multivariate loss function approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 412-437, April.
    5. Tara Sinclair & Herman O. Stekler & Warren Carrow, 2012. "Evaluating a Vector of the Fed's Forecasts," Working Papers 2012-3, The George Washington University, Institute for International Economic Policy.
    6. Wei Lin & Gloria González‐Rivera, 2019. "Extreme returns and intensity of trading," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1121-1140, November.
    7. Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2017. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," ETA: Economic Theory and Applications 253725, Fondazione Eni Enrico Mattei (FEEM).
    8. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2011. "Forecast Evaluation in Call Centers: Combined Forecasts, Flexible Loss Functions and Economic Criteria," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1109, Universitá degli Studi di Milano.
    9. Michael P. Clements, 2022. "Forecaster Efficiency, Accuracy, and Disagreement: Evidence Using Individual‐Level Survey Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(2-3), pages 537-568, March.
    10. Jens J. Krüger, 2014. "A multivariate evaluation of German output growth and inflation forecasts," Economics Bulletin, AccessEcon, vol. 34(3), pages 1410-1418.
    11. Travis J. Berge & Andrew C. Chang & Nitish R. Sinha, 2019. "Evaluating the Conditionality of Judgmental Forecasts," Finance and Economics Discussion Series 2019-002, Board of Governors of the Federal Reserve System (U.S.).
    12. Hans Christian Müller-Dröge & Tara M. Sinclair & Herman O. Stekler, 2014. "Evaluating Forecasts Of A Vector Of Variables: A German Forecasting Competition," Working Papers 2014-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    13. Alp, Tansel & Demetrescu, Matei, 2010. "Joint forecasts of Dow Jones stocks under general multivariate loss function," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2360-2371, November.
    14. Andrew Martinez, 2017. "Testing for Differences in Path Forecast Accuracy: Forecast-Error Dynamics Matter," Working Papers (Old Series) 1717, Federal Reserve Bank of Cleveland.
    15. Travis J. Berge, 2017. "Understanding Survey Based Inflation Expectations," Finance and Economics Discussion Series 2017-046, Board of Governors of the Federal Reserve System (U.S.).
    16. Wang, Yiyao & Lee, Tae-Hwy, 2014. "Asymmetric loss in the Greenbook and the Survey of Professional Forecasters," International Journal of Forecasting, Elsevier, vol. 30(2), pages 235-245.
    17. Ouysse, Rachida, 2016. "Bayesian model averaging and principal component regression forecasts in a data rich environment," International Journal of Forecasting, Elsevier, vol. 32(3), pages 763-787.
    18. Mamatzakis, Emmanuel & Tsionas, Mike G., 2015. "How are market preferences shaped? The case of sovereign debt of stressed euro-area countries," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 106-116.
    19. Dovern, Jonas, 2015. "A multivariate analysis of forecast disagreement: Confronting models of disagreement with survey data," European Economic Review, Elsevier, vol. 80(C), pages 16-35.
    20. Fabiana Gomez & David Pacini, 2015. "Counting Biased Forecasters: An Application of Multiple Testing Techniques," Bristol Economics Discussion Papers 15/661, School of Economics, University of Bristol, UK.
    21. Fresoli, Diego & Ruiz, Esther & Pascual, Lorenzo, 2015. "Bootstrap multi-step forecasts of non-Gaussian VAR models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 834-848.
    22. Jingwei Pan, 0000. "Evaluating Correlation Forecasts Under Asymmetric Loss," Proceedings of Economics and Finance Conferences 11413234, International Institute of Social and Economic Sciences.
    23. Tae-Hwy Lee & Tao Wang, 2023. "Estimation and Testing of Forecast Rationality with Many Moments," Working Papers 202307, University of California at Riverside, Department of Economics.
    24. An, Zidong & Zheng, Xinye, 2023. "Diligent forecasters can make accurate predictions despite disagreeing with the consensus," Economic Modelling, Elsevier, vol. 125(C).
    25. González-Rivera, Gloria & Luo, Yun, 2019. "Prediction regions for interval-valued time series," DES - Working Papers. Statistics and Econometrics. WS 29054, Universidad Carlos III de Madrid. Departamento de Estadística.
    26. Michael Clements, 2016. "Are Macro-Forecasters Essentially The Same? An Analysis of Disagreement, Accuracy and Efficiency," ICMA Centre Discussion Papers in Finance icma-dp2016-08, Henley Business School, University of Reading.
    27. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2021. "The Rationality of USDA Forecasts under Multivariate Asymmetric Loss," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1006-1033, May.
    28. Boskabadi, Elahe, 2022. "Economic policy uncertainty and forecast bias in the survey of professional forecasters," MPRA Paper 115081, University Library of Munich, Germany.
    29. Christodoulakis, George, 2020. "Estimating the term structure of commodity market preferences," European Journal of Operational Research, Elsevier, vol. 282(3), pages 1146-1163.
    30. Gloria Gonzalez-Rivera & Wei Lin, 2014. "Interval-valued Time Series: Model Estimation based on Order Statistics," Working Papers 201429, University of California at Riverside, Department of Economics.
    31. Yoichi Tsuchiya, 2022. "Evaluating plant managers’ production plans over business cycles: asymmetric loss and rationality," SN Business & Economics, Springer, vol. 2(8), pages 1-29, August.
    32. Julieta Caunedo & Riccardo DiCecio & Ivana Komunjer & Michael T. Owyang, 2013. "Asymmetry, Complementarities, and State Dependence in Federal Reserve Forecasts," Working Papers 2013-012, Federal Reserve Bank of St. Louis, revised 29 Dec 2017.
    33. Garratt, Anthony & Petrella, Ivan & Zhang, Yunyi, 2022. "Asymmetry and Interdependence when Evaluating U.S. Energy Information Administration Forecasts," MPRA Paper 115559, University Library of Munich, Germany.
    34. Ulu, Yasemin, 2013. "Multivariate test for forecast rationality under asymmetric loss functions: Recent evidence from MMS survey of inflation–output forecasts," Economics Letters, Elsevier, vol. 119(2), pages 168-171.
    35. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
    36. Kexin Ding & Ani L. Katchova, 2024. "Testing the optimality of USDA's WASDE forecasts under unknown loss," Agribusiness, John Wiley & Sons, Ltd., vol. 40(4), pages 846-865, October.
    37. Olga Isengildina‐Massa & Berna Karali & Todd H. Kuethe & Ani L. Katchova, 2021. "Joint Evaluation of the System of USDA's Farm Income Forecasts," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(3), pages 1140-1160, September.
    38. Todd E. Clark & Michael W. McCracken, 2013. "Evaluating the accuracy of forecasts from vector autoregressions," Working Papers 2013-010, Federal Reserve Bank of St. Louis.

  9. Komunjer, Ivana & Vuong, Quang, 2006. "Efficientt Conditional Quantile Estimation: The Time Series Case," University of California at San Diego, Economics Working Paper Series qt78842570, Department of Economics, UC San Diego.

    Cited by:

    1. Habert white & Tae-Hwan Kim & Simone Manganelli, 2012. "VAR for VaR: Measuring Tail Dependence Using Multivariate Regression Quantiles," Working papers 2012rwp-45, Yonsei University, Yonsei Economics Research Institute.
    2. Otsu, Taisuke, 2008. "Conditional empirical likelihood estimation and inference for quantile regression models," Journal of Econometrics, Elsevier, vol. 142(1), pages 508-538, January.
    3. Marc Hallin & Catherine Vermandele & Bas J. M. Werker, 2008. "Semiparametrically efficient inference based on signs and ranks for median‐restricted models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(2), pages 389-412, April.
    4. Komunjer, Ivana & Vuong, Quang, 2010. "Efficient estimation in dynamic conditional quantile models," Journal of Econometrics, Elsevier, vol. 157(2), pages 272-285, August.
    5. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    6. White, Halbert & Kim, Tae-Hwan & Manganelli, Simone, 2010. "VAR for VaR: measuring systemic risk using multivariate regression quantiles," MPRA Paper 35372, University Library of Munich, Germany.
    7. Manganelli, Simone & White, Halbert & Kim, Tae-Hwan, 2008. "Modeling autoregressive conditional skewness and kurtosis with multi-quantile CAViaR," Working Paper Series 957, European Central Bank.

  10. Costinot, Arnaud & Komunjer, Ivana, 2006. "What Goods Do Countries Trade? New Ricardian Predictions," University of California at San Diego, Economics Working Paper Series qt86n316hw, Department of Economics, UC San Diego.

    Cited by:

    1. Costinot, Arnaud, 2007. "On the Origins of Comparative Advantage," University of California at San Diego, Economics Working Paper Series qt07g7g8h8, Department of Economics, UC San Diego.
    2. Antti SIMOLA & Jouko KINNUNEN & Hannu TÖRMÄ & Jukka KOLA, 2010. "Bioenergy Production in Finland and its Effects on Regional Growth and Employment," EcoMod2010 259600157, EcoMod.
    3. James E. Anderson & Yoto V. Yotov, 2010. "Specialization: Pro- and Anti-globalizing, 1990-2002," NBER Working Papers 16301, National Bureau of Economic Research, Inc.
    4. Arnaud Costinot, 2009. "An Elementary Theory of Comparative Advantage," NBER Working Papers 14645, National Bureau of Economic Research, Inc.
    5. Costas Arkolakis & Arnaud Costinot & Andrés Rodríguez-Clare, 2009. "New Trade Models, Same Old Gains?," NBER Working Papers 15628, National Bureau of Economic Research, Inc.
    6. Chen, Natalie & Novy, Dennis, 2008. "International Trade Integration: A Disaggregated Approach," CEPR Discussion Papers 7103, C.E.P.R. Discussion Papers.
    7. James E. Anderson, 2009. "Gravity, Productivity and the Pattern of Production and Trade," NBER Working Papers 14642, National Bureau of Economic Research, Inc.
    8. Morrow, Peter M., 2010. "Ricardian-Heckscher-Ohlin comparative advantage: Theory and evidence," Journal of International Economics, Elsevier, vol. 82(2), pages 137-151, November.
    9. Davin Chor, 2008. "Unpacking Sources of Comparative Advantage : A Quantitative Approach," Macroeconomics Working Papers 22071, East Asian Bureau of Economic Research.
    10. Amoroso, Nicolás & Chiquiar, Daniel & Ramos-Francia, Manuel, 2011. "Technology and endowments as determinants of comparative advantage: Evidence from Mexico," The North American Journal of Economics and Finance, Elsevier, vol. 22(2), pages 164-196, August.
    11. Sergei Koulayev, 2009. "Estimating demand in search markets: the case of online hotel bookings," Working Papers 09-16, Federal Reserve Bank of Boston.
    12. Christian Hepenstrick, 2010. "Per-capita incomes and the extensive margin of bilateral trade," IEW - Working Papers 519, Institute for Empirical Research in Economics - University of Zurich.
    13. Matilde Bombardini & Giovanni Gallipoli & German Pupato, 2012. "Skill Dispersion and Trade Flows," American Economic Review, American Economic Association, vol. 102(5), pages 2327-2348, August.
    14. Cheng‐Te Lee & Shang‐Fen Wu, 2023. "Technology advantage, terms of trade, and pattern of trade," International Journal of Economic Theory, The International Society for Economic Theory, vol. 19(1), pages 166-174, March.
    15. Shikher, Serge, 2011. "Capital, technology, and specialization in the neoclassical model," Journal of International Economics, Elsevier, vol. 83(2), pages 229-242, March.

  11. Ivana Komunjer, 2004. "Asymmetric Power Distribution: Theory and Applications to Risk Measurement," Econometric Society 2004 Latin American Meetings 44, Econometric Society.

    Cited by:

    1. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
    2. Jin-Ray Lu & Chiang-Chang Hwang & Yi-Chun Chen & Chu-Ting Wen, 2013. "Including More Information Content to Enhance the Value at Risk Estimation for Real Estate Investment Trusts," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 4(3), pages 25-34, July.
    3. Li, Xiao-Ming & Rose, Lawrence C., 2009. "The tail risk of emerging stock markets," Emerging Markets Review, Elsevier, vol. 10(4), pages 242-256, December.
    4. Douch, Mohamed & Farooq, Omar & Bouaddi, Mohammed, 2015. "Stock price synchronicity and tails of return distribution," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 37(C), pages 1-11.
    5. Yu, Dalei & Bai, Peng & Ding, Chang, 2015. "Adjusted quasi-maximum likelihood estimator for mixed regressive, spatial autoregressive model and its small sample bias," Computational Statistics & Data Analysis, Elsevier, vol. 87(C), pages 116-135.
    6. Mendoza-Velázquez, Alfonso & Galvanovskis, Evalds, 2009. "Introducing the GED-Copula with an application to Financial Contagion in Latin America," MPRA Paper 46669, University Library of Munich, Germany, revised 01 Feb 2010.
    7. Victoria Zinde-Walsh & Dongming Zhu, 2007. "Properties And Estimation Of Asymmetric Exponential Power Distribution," Departmental Working Papers 2007-11, McGill University, Department of Economics.
    8. BOUADDI, Mohammed & ROMBOUTS, Jeroen V.K., 2007. "Mixed exponential power asymmetric conditional heteroskedasticity," LIDAM Discussion Papers CORE 2007097, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Matteo Bonato & Rangan Gupta & Chi Keung Marco Lau & Shixuan Wang, 2019. "Moments-Based Spillovers across Gold and Oil Markets," Working Papers 201966, University of Pretoria, Department of Economics.
    10. Demetrescu, Matei & Hacioglu Hoke, Sinem, 2018. "Predictive regressions under asymmetric loss: factor augmentation and model selection," Bank of England working papers 723, Bank of England.
    11. Huber, Peter & Oberhofer, Harald & Pfaffermayr, Michael, 2015. "Who Creates Jobs? Econometric Modeling and Evidence for Austrian Firm Level Data," Department of Economics Working Paper Series 205, WU Vienna University of Economics and Business.
    12. Bao, Te & Diks, Cees & Li, Hao, 2018. "A generalized CAPM model with asymmetric power distributed errors with an application to portfolio construction," Economic Modelling, Elsevier, vol. 68(C), pages 611-621.
    13. Tae-Hwan Kim & Dong Jin Lee & Paul Mizen, 2020. "Impulse Response Analysis in Conditional Quantile Models and an Application to Monetary Policy," Working papers 2020rwp-164, Yonsei University, Yonsei Economics Research Institute.
    14. J. Miguel Marin & Genaro Sucarrat, 2015. "Financial density selection," The European Journal of Finance, Taylor & Francis Journals, vol. 21(13-14), pages 1195-1213, November.
    15. Liu, Xiaochun, 2019. "On tail fatness of macroeconomic dynamics," Journal of Macroeconomics, Elsevier, vol. 62(C).
    16. Yi-Ting Chen, 2016. "Testing for Granger Causality in Moments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(2), pages 265-288, April.
    17. Komunjer, Ivana & Vuong, Quang, 2010. "Efficient estimation in dynamic conditional quantile models," Journal of Econometrics, Elsevier, vol. 157(2), pages 272-285, August.
    18. Mendoza, Alfonso. & Galvanovskis, Evalds., 2014. "La cópula GED bivariada. Una aplicación en entornos de crisis," El Trimestre Económico, Fondo de Cultura Económica, vol. 0(323), pages .721-746, julio-sep.
    19. Lafaye de Micheaux, Pierre & Ouimet, Frédéric, 2018. "A uniform L1 law of large numbers for functions of i.i.d. random variables that are translated by a consistent estimator," Statistics & Probability Letters, Elsevier, vol. 142(C), pages 109-117.
    20. Yong Bao & Aman Ullah, 2009. "Expectation of Quadratic Forms in Normal and Nonnormal Variables with Econometric Applications," Working Papers 200907, University of California at Riverside, Department of Economics, revised Jun 2009.
    21. Dong Jin Lee & Tae-Hwan Kim & Paul Mizen, 2020. "Impulse response analysis in conditional quantile models with an application to monetary policy," Discussion Papers 2020/08, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
    22. Vijverberg, Chu-Ping C. & Vijverberg, Wim P.M. & Taşpınar, Süleyman, 2016. "Linking Tukey’s legacy to financial risk measurement," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 595-615.
    23. León, Ángel & Ñíguez, Trino-Manuel, 2020. "Modeling asset returns under time-varying semi-nonparametric distributions," Journal of Banking & Finance, Elsevier, vol. 118(C).
    24. Fischer, Matthias, 2012. "A skew and leptokurtic distribution with polynomial tails and characterizing functions in closed form," FAU Discussion Papers in Economics 03/2012, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    25. Petrella, Ivan & Santoro, Emiliano & Simonsen, Lasse de la Porte, 2018. "Time-varying Price Flexibility and Inflation Dynamics," CEPR Discussion Papers 13027, C.E.P.R. Discussion Papers.
    26. Bera Anil K. & Galvao Antonio F. & Montes-Rojas Gabriel V. & Park Sung Y., 2016. "Asymmetric Laplace Regression: Maximum Likelihood, Maximum Entropy and Quantile Regression," Journal of Econometric Methods, De Gruyter, vol. 5(1), pages 79-101, January.
    27. Mahdi Teimouri & Saralees Nadarajah, 2022. "Maximum Likelihood Estimation for the Asymmetric Exponential Power Distribution," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 665-692, August.
    28. A. T. Soyinka & A. A. Olosunde, 2021. "Inferences from Asymmetric Multivariate Exponential Power Distribution," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 350-370, November.
    29. Lu Ou & Zhibiao Zhao, 2021. "Value‐at‐risk forecasting via dynamic asymmetric exponential power distributions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 291-300, March.
    30. Ruediger Bachmann & Kai Carstensen & Stefan Lautenbacher & Martin Schneider, 2021. "Uncertainty and Change: Survey Evidence of Firms's Subjective Beliefs," CESifo Working Paper Series 9394, CESifo.
    31. Mohammed Bouaddi & Khouzeima Moutanabbir, 2022. "Systematic extreme potential gain and loss spillover across countries," Risk Management, Palgrave Macmillan, vol. 24(4), pages 327-366, December.
    32. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    33. de Castro, Luciano & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2020. "Quantile selection in non-linear GMM quantile models," Economics Letters, Elsevier, vol. 195(C).
    34. Halvarsson, Daniel, 2019. "Asymmetric Double Pareto Distributions: Maximum Likelihood Estimation with Application to the Growth Rate Distribution of Firms," Ratio Working Papers 327, The Ratio Institute.
    35. Fabrizio Leisen & Luca Rossini & Cristiano Villa, 2020. "Loss-based approach to two-piece location-scale distributions with applications to dependent data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(2), pages 309-333, June.
    36. Kaiping Wang, 2014. "Modeling Stock Index Returns using Semi-Parametric Approach with Multiplicative Adjustment," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 65-75, December.
    37. Vijverberg, Wim P. & Hasebe, Takuya, 2015. "GTL Regression: A Linear Model with Skewed and Thick-Tailed Disturbances," IZA Discussion Papers 8898, Institute of Labor Economics (IZA).
    38. Zhu, Dongming & Galbraith, John W., 2011. "Modeling and forecasting expected shortfall with the generalized asymmetric Student-t and asymmetric exponential power distributions," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 765-778, September.
    39. Yong Bao, 2013. "On Sample Skewness and Kurtosis," Econometric Reviews, Taylor & Francis Journals, vol. 32(4), pages 415-448, December.

  12. Ivana Komunjer & Federico Echenique, 2004. "Testing Models with Multiple Equilibria by Quantile Methods," Econometric Society 2004 North American Summer Meetings 447, Econometric Society.

    Cited by:

    1. Timmermann, Allan & Wermers, Russ, 2014. "Runs on Money Market Funds," CEPR Discussion Papers 9906, C.E.P.R. Discussion Papers.
    2. Amir, Rabah & Lazzati, Natalia, 2011. "Network effects, market structure and industry performance," Journal of Economic Theory, Elsevier, vol. 146(6), pages 2389-2419.
    3. Taisuke Otsu & Yoshiyasu Rai, 2013. "On Testability Of Complementarity In Models With Multiple Equilibria," STICERD - Econometrics Paper Series 560, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    4. Vincent P. Crawford & Miguel A. Costa-Gomes & Nagore Iriberri, 2010. "Strategic Thinking," Levine's Working Paper Archive 661465000000001148, David K. Levine.
    5. Giovanni Cespa & Xavier Vives, 2011. "Expectations, Liquidity, and Short-term Trading," CESifo Working Paper Series 3390, CESifo.
    6. Yuichi Kitamura & Louise Laage, 2018. "Nonparametric Analysis of Finite Mixtures," Papers 1811.02727, arXiv.org.
    7. Natalia Lazzati & John K.-H. Quah & Koji Shirai, 2016. "A revealed preference theory of monotone choice and strategic complementarity," Discussion Paper Series 147, School of Economics, Kwansei Gakuin University, revised Oct 2016.
    8. Alberto Bisin & Andrea Moro & Giorgio Topa, 2011. "The Empirical Content of Models with Multiple Equilibria in Economies with Social Interactions," NBER Working Papers 17196, National Bureau of Economic Research, Inc.
    9. Vives, Xavier & Vravosinos, Orestis, 2024. "Strategic complementarity in games," Journal of Mathematical Economics, Elsevier, vol. 113(C).
    10. Giovanni Cespa & Xavier Vives, 2014. "The Beauty Contest and Short-Term Trading," CSEF Working Papers 383, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    11. Komunjer, Ivana, 2007. "Global Identification In Nonlinear Semiparametric Models," University of California at San Diego, Economics Working Paper Series qt8dk0n386, Department of Economics, UC San Diego.
    12. Lukasz Balbus & Pawel Dziewulski & Kevin Reffett & Lukasz Wozny, 2020. "Markov distributional equilibrium dynamics in games with complementarities and no aggregate risk," KAE Working Papers 2020-052, Warsaw School of Economics, Collegium of Economic Analysis.
    13. Ron N. Borkovsky & Paul B. Ellickson & Brett R. Gordon & Victor Aguirregabiria & Gardete Pedro, 2014. "Multiplicity of Equilibria and Information Structures in Empirical Games: Challenges and Prospects," Working Papers tecipa-510, University of Toronto, Department of Economics.
    14. Natalia Lazzati & John K.-H. Quah & Koji Shirai, 2018. "Nonparametric analysis of monotone choice," Discussion Paper Series 184, School of Economics, Kwansei Gakuin University.
    15. Miyauchi, Yuhei, 2016. "Structural estimation of pairwise stable networks with nonnegative externality," Journal of Econometrics, Elsevier, vol. 195(2), pages 224-235.
    16. Wermers, Russ, 2012. "Runs on money market mutual funds," CFR Working Papers 12-05, University of Cologne, Centre for Financial Research (CFR).
    17. Áureo de Paula, 2012. "Econometric analysis of games with multiple equilibria," CeMMAP working papers 29/12, Institute for Fiscal Studies.
    18. Camargo, Bráz Ministério de & Pastorino, Elena, 2012. "Career concerns: a human capital perspective," Textos para discussão 288, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).

  13. Allan Timmermann & Graham Elliott & Ivana Komunjer, 2004. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Econometric Society 2004 North American Summer Meetings 601, Econometric Society.

    Cited by:

    1. Clements, Michael P., 2008. "Explanations of the inconsistencies in survey respondents'forecasts," The Warwick Economics Research Paper Series (TWERPS) 870, University of Warwick, Department of Economics.
    2. Pesaran, M. Hashem & Weale, Martin, 2006. "Survey Expectations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 14, pages 715-776, Elsevier.
    3. Ivana Komunjer & Michael T. Owyang, 2012. "Multivariate Forecast Evaluation and Rationality Testing," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1066-1080, November.
    4. Stan Hurn & Jing Tian & Lina Xu, 2021. "Assessing the Informational Content of Official Australian Bureau of Meteorology Forecasts of Wind Speed," The Economic Record, The Economic Society of Australia, vol. 97(319), pages 525-547, December.
    5. Metodij Hadzi-Vaskov & Mr. Luca A Ricci & Alejandro M. Werner & Rene Zamarripa, 2021. "Authorities’ Fiscal Forecasts in Latin America: Are They Optimistic?," IMF Working Papers 2021/154, International Monetary Fund.
    6. Pratiti Chatterjee & Fabio Milani, 2020. "Perceived Uncertainty Shocks, Excess Optimism-Pessimism, and Learning in the Business Cycle," Working Papers 202101, University of California-Irvine, Department of Economics.
    7. Benjamin Born & Zeno Enders & Manuel Menkhoff & Gernot J. Müller & Knut Niemann, 2023. "Firm Expectations and News: Micro v Macro," ifo Working Paper Series 400, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    8. Reitz, Stefan & Rülke, Jan & Stadtmann, Georg, 2012. "Nonlinear Expectations in Speculative Markets," VfS Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62045, Verein für Socialpolitik / German Economic Association.
    9. Sinclair, Tara M. & Gamber, Edward N. & Stekler, Herman & Reid, Elizabeth, 2012. "Jointly evaluating the Federal Reserve’s forecasts of GDP growth and inflation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 309-314.
    10. Emmanuel C. Mamatzakis & Mike G. Tsionas, 2020. "Revealing forecaster's preferences: A Bayesian multivariate loss function approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 412-437, April.
    11. Carlos Capistrán-Carmona, 2005. "Bias in Federal Reserve Inflation Forecasts: Is the Federal Reserve Irrational or Just Cautious?," Computing in Economics and Finance 2005 127, Society for Computational Economics.
    12. Aretz, Kevin & Bartram, Söhnke M. & Pope, Peter F., 2011. "Asymmetric Loss Functions and the Rationality of Expected Stock Returns," MPRA Paper 47343, University Library of Munich, Germany.
    13. Atsushi Inoue & Lutz Kilian & Fatma Burcu Kiraz, 2009. "Do Actions Speak Louder Than Words? Household Expectations of Inflation Based on Micro Consumption Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(7), pages 1331-1363, October.
    14. Reitz, Stefan & Rülke, Jan-Christoph & Stadtmann, Georg, 2012. "Nonlinear expectations in speculative markets: Evidence from the ECB survey of professional forecasters," Discussion Papers 311, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    15. Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2015. "Central banks’ inflation forecasts under asymmetric loss: Evidence from four Latin-American countries," Economics Letters, Elsevier, vol. 129(C), pages 66-70.
    16. Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2019. "Forecasting Realized Oil-Price Volatility: The Role of Financial Stress and Asymmetric Loss," Working Papers 201903, University of Pretoria, Department of Economics.
    17. Timo Dimitriadis & Andrew J. Patton & Patrick W. Schmidt, 2019. "Testing Forecast Rationality for Measures of Central Tendency," Papers 1910.12545, arXiv.org, revised Jul 2024.
    18. Lutz Kilian & Simone Manganelli, 2008. "The Central Banker as a Risk Manager: Estimating the Federal Reserve's Preferences under Greenspan," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(6), pages 1103-1129, September.
    19. Christian Pierdzioch & Jan C Rülke & Georg Stadtmann, 2012. "Forecasting the Dollar/British Pound Exchange Rate: Asymmetric Loss and Forecast Rationality," Economics Bulletin, AccessEcon, vol. 32(3), pages 213-213.
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    137. James Ming Chen, 2018. "On Exactitude in Financial Regulation: Value-at-Risk, Expected Shortfall, and Expectiles," Risks, MDPI, vol. 6(2), pages 1-28, June.
    138. Laura Garcia-Jorcano & Lidia Sanchis-Marco, 2023. "Measuring Systemic Risk Using Multivariate Quantile-Located ES Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 1-72.
    139. Gonzalez-Rivera, Gloria & Lee, Tae-Hwy & Yoldas, Emre, 2007. "Optimality of the RiskMetrics VaR model," Finance Research Letters, Elsevier, vol. 4(3), pages 137-145, September.
    140. Jan G. De Gooijer, 2023. "Penalized Averaging of Quantile Forecasts from GARCH Models with Many Exogenous Predictors," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 407-424, June.
    141. De Gooijer Jan G. & Zerom Dawit, 2020. "Penalized Averaging of Parametric and Non-Parametric Quantile Forecasts," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-15, January.
    142. Giuseppe Storti & Chao Wang, 2023. "Modeling uncertainty in financial tail risk: A forecast combination and weighted quantile approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1648-1663, November.

  15. Timmermann, Allan & Elliott, Graham & Komunjer, Ivana, 2003. "Estimating Loss Function Parameters," CEPR Discussion Papers 3821, C.E.P.R. Discussion Papers.

    Cited by:

    1. Martin Skitmore & Franco K. T. Cheung, 2007. "Explorations in specifying construction price forecast loss functions," Construction Management and Economics, Taylor & Francis Journals, vol. 25(5), pages 449-465.
    2. Graham Elliott & Ivana Komunjer & Allan Timmermann, 2008. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Journal of the European Economic Association, MIT Press, vol. 6(1), pages 122-157, March.
    3. Stan Hurn & Ralf Becker, 2006. "Testing for nonlinearity in mean in the presence of heteroskedasticity," Stan Hurn Discussion Papers 2006-02, School of Economics and Finance, Queensland University of Technology.
    4. Siliverstovs, Boriss & Engsted, Tom & Haldrup, Niels, 2002. "Long-Run Forecasting in Multicointegrated Systems," Finance Working Papers 02-14, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    5. Basu, Sudipta & Markov, Stanimir, 2004. "Loss function assumptions in rational expectations tests on financial analysts' earnings forecasts," Journal of Accounting and Economics, Elsevier, vol. 38(1), pages 171-203, December.
    6. Yang Yang & Tae-Hwy Lee, 2004. "Bagging Binary Predictors for Time Series," Econometric Society 2004 Far Eastern Meetings 512, Econometric Society.
    7. Lee, Tae-Hwy & Yang, Yang, 2006. "Bagging binary and quantile predictors for time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 465-497.
    8. Allan Timmermann & Andrew J. Patton, 2004. "Properties of Optimal Forecasts," Econometric Society 2004 North American Winter Meetings 234, Econometric Society.
    9. Adrian Pagan & Hashem Pesaran, 2007. "Econometric Analysis of Structural Systems with Permanent and Transitory Shocks. Working paper #7," NCER Working Paper Series 7, National Centre for Econometric Research.
    10. Pedro Henrique Melo Albuquerque & Yaohao Peng & João Pedro Fontoura da Silva, 2022. "Making the whole greater than the sum of its parts: A literature review of ensemble methods for financial time series forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1701-1724, December.
    11. Alexander, Marcus & Christakis, Nicholas A., 2008. "Bias and asymmetric loss in expert forecasts: A study of physician prognostic behavior with respect to patient survival," Journal of Health Economics, Elsevier, vol. 27(4), pages 1095-1108, July.

  16. Komunjer, Ivana, 2002. "Quasi-Maximum Likelihood Estimation for Conditional Quantiles," Working Papers 1139, California Institute of Technology, Division of the Humanities and Social Sciences.

    Cited by:

    1. Tae-Hwy Lee & Weiping Yang, 2014. "Granger-Causality in Quantiles between Financial Markets: Using Copula Approach," Working Papers 201406, University of California at Riverside, Department of Economics.
    2. Lee, Tae-Hwy & Ullah, Aman & Wang, He, 2018. "The second-order bias of quantile estimators," Economics Letters, Elsevier, vol. 173(C), pages 143-147.
    3. Tae-Hwy Lee & Weiping Yang, 2012. "Money–Income Granger-Causality in Quantiles," Advances in Econometrics, in: 30th Anniversary Edition, pages 385-409, Emerald Group Publishing Limited.
    4. Großmaß Lidan, 2014. "Liquidity and the Value at Risk," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 234(5), pages 572-602, October.
    5. Bernstein, David H. & Parmeter, Christopher F. & Tsionas, Mike G., 2023. "On the performance of the United States nuclear power sector: A Bayesian approach," Energy Economics, Elsevier, vol. 125(C).
    6. Catania, Leopoldo & Luati, Alessandra, 2023. "Semiparametric modeling of multiple quantiles," Journal of Econometrics, Elsevier, vol. 237(2).
    7. Taylor, James W., 2022. "Forecasting Value at Risk and expected shortfall using a model with a dynamic omega ratio," Journal of Banking & Finance, Elsevier, vol. 140(C).
    8. Habert white & Tae-Hwan Kim & Simone Manganelli, 2012. "VAR for VaR: Measuring Tail Dependence Using Multivariate Regression Quantiles," Working papers 2012rwp-45, Yonsei University, Yonsei Economics Research Institute.
    9. Oliver Linton & Dajing Shang & Yang Yan, 2012. "Efficient estimation of conditional risk measures in a semiparametric GARCH model," CeMMAP working papers CWP25/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Gabriel Montes-Rojas & Zacharias Psaradakis & Martín Sola, 2024. "On Regime Separation in Markov-Switching Quantile Regressions," Department of Economics Working Papers 2024_05, Universidad Torcuato Di Tella.
    11. Otsu, Taisuke, 2008. "Conditional empirical likelihood estimation and inference for quantile regression models," Journal of Econometrics, Elsevier, vol. 142(1), pages 508-538, January.
    12. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.
    13. Dong Jin Lee, 2009. "Testing Parameter Stability in Quantile Models: An Application to the U.S. Inflation Process," Working papers 2009-26, University of Connecticut, Department of Economics.
    14. Santos, Douglas G. & Candido, Osvaldo & Tófoli, Paula V., 2022. "Forecasting risk measures using intraday and overnight information," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    15. Marc Hallin & Catherine Vermandele & Bas J. M. Werker, 2008. "Semiparametrically efficient inference based on signs and ranks for median‐restricted models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(2), pages 389-412, April.
    16. Alhamzawi, Rahim & Yu, Keming, 2013. "Conjugate priors and variable selection for Bayesian quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 209-219.
    17. Akanksha Negi, 2020. "Doubly weighted M-estimation for nonrandom assignment and missing outcomes," Papers 2011.11485, arXiv.org.
    18. Tae-Hwy Lee & Aman Ullah & He Wang, 2024. "The second-order bias and mean squared error of quantile regression estimators," Indian Economic Review, Springer, vol. 59(1), pages 11-68, October.
    19. Bera, A. K. & Galvao Jr, A. F. & Montes-Rojas, G. & Park, S. Y., 2010. "Which quantile is the most informative? Maximum likelihood, maximum entropy and quantile regression," Working Papers 10/08, Department of Economics, City University London.
    20. Hartwig, Benny & Meinerding, Christoph & Schüler, Yves S., 2021. "Identifying indicators of systemic risk," Journal of International Economics, Elsevier, vol. 132(C).
    21. Tianshun Yan & Yanyong Zhao & Wentao Wang, 2020. "Likelihood-based estimation of a semiparametric time-dependent jump diffusion model of the short-term interest rate," Computational Statistics, Springer, vol. 35(2), pages 539-557, June.
    22. Christophe Boucher & Sessi Tokpavi, 2019. "Stocks and Bonds: Flight-to-Safety for Ever?," Post-Print hal-02067096, HAL.
    23. Ji, Yonggang & Lin, Nan & Zhang, Baoxue, 2012. "Model selection in binary and tobit quantile regression using the Gibbs sampler," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 827-839.
    24. Escanciano, Juan Carlos & Velasco, Carlos, 2010. "Specification tests of parametric dynamic conditional quantiles," Journal of Econometrics, Elsevier, vol. 159(1), pages 209-221, November.
    25. Christophe Boucher & Sessi Tokpavi, 2018. "Stocks and Bonds: Flight-to-Safety for Ever?," Working Papers hal-04141705, HAL.
    26. Alhamzawi, Rahim, 2016. "Bayesian model selection in ordinal quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 68-78.
    27. Susana Faria & Maria Conceição Portela, 2016. "Student Performance in Mathematics using PISA-2009 data for Portugal," Working Papers de Gestão (Management Working Papers) 01, Católica Porto Business School, Universidade Católica Portuguesa.
    28. Komunjer, Ivana & Vuong, Quang, 2010. "Efficient estimation in dynamic conditional quantile models," Journal of Econometrics, Elsevier, vol. 157(2), pages 272-285, August.
    29. Lieli, Robert P. & Stinchcombe, Maxwell B. & Grolmusz, Viola M., 2019. "Unrestricted and controlled identification of loss functions: Possibility and impossibility results," International Journal of Forecasting, Elsevier, vol. 35(3), pages 878-890.
    30. Ivana Komunjer, 2007. "Asymmetric power distribution: Theory and applications to risk measurement," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(5), pages 891-921.
    31. Zongwu Cai & Meng Shi & Yue Zhao & Wuqing Wu, 2020. "Testing Financial Hierarchy Based on A PDQ-CRE Model," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202011, University of Kansas, Department of Economics, revised Jul 2020.
    32. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207, April.
    33. Timo Dimitriadis & Julie Schnaitmann, 2019. "Forecast Encompassing Tests for the Expected Shortfall," Papers 1908.04569, arXiv.org, revised Aug 2020.
    34. Dong Jin Lee, 2020. "Optimal tests for parameter breaking process in conditional quantile models," The Japanese Economic Review, Springer, vol. 71(3), pages 479-510, July.
    35. Lijuan Huo & Tae-Hwan Kim & Yunmi Kim, 2013. "Testing for Autocorrelation in Quantile Regression Models," Working papers 2013rwp-54, Yonsei University, Yonsei Economics Research Institute.
    36. Yang Yang & Tae-Hwy Lee, 2004. "Bagging Binary Predictors for Time Series," Econometric Society 2004 Far Eastern Meetings 512, Econometric Society.
    37. Joan Jasiak & C. Gourieroux, 2006. "Dynamic Quantile Models," Working Papers 2006_4, York University, Department of Economics.
    38. Andrew J. Patton & Johanna F. Ziegel & Rui Chen, 2017. "Dynamic Semiparametric Models for Expected Shortfall (and Value-at-Risk)," Papers 1707.05108, arXiv.org.
    39. Sebastian Bayer & Timo Dimitriadis, 2022. "Regression-Based Expected Shortfall Backtesting [Backtesting Expected Shortfall]," Journal of Financial Econometrics, Oxford University Press, vol. 20(3), pages 437-471.
    40. Jungsik Noh & Sangyeol Lee, 2016. "Quantile Regression for Location-Scale Time Series Models with Conditional Heteroscedasticity," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(3), pages 700-720, September.
    41. Yunmi Kim & Lijuan Huo & Tae-Hwan Kim, 2020. "Dealing with Markov-Switching Parameters in Quantile Regression Models," Working papers 2020rwp-166, Yonsei University, Yonsei Economics Research Institute.
    42. De Rezende, Rafael B., 2015. "Risks in macroeconomic fundamentals and excess bond returns predictability," Working Paper Series 295, Sveriges Riksbank (Central Bank of Sweden).
    43. Gneiting, Tilmann, 2011. "Making and Evaluating Point Forecasts," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 746-762.
    44. Huang, Dashan & Yu, Baimin & Fabozzi, Frank J. & Fukushima, Masao, 2009. "CAViaR-based forecast for oil price risk," Energy Economics, Elsevier, vol. 31(4), pages 511-518, July.
    45. Fabian Krüger & Ingmar Nolte, 2011. "Disagreement, Uncertainty and the True Predictive Density," Working Paper Series of the Department of Economics, University of Konstanz 2011-43, Department of Economics, University of Konstanz.
    46. Sessi Tokpavi & Christophe Boucher, 2018. "Stocks and Bonds: Flight-to-Safety for Ever?," EconomiX Working Papers 2018-39, University of Paris Nanterre, EconomiX.
    47. Ying-Ying Lee, 2015. "Interpretation and Semiparametric Efficiency in Quantile Regression under Misspecification," Econometrics, MDPI, vol. 4(1), pages 1-14, December.
    48. White, Halbert & Kim, Tae-Hwan & Manganelli, Simone, 2010. "VAR for VaR: measuring systemic risk using multivariate regression quantiles," MPRA Paper 35372, University Library of Munich, Germany.
    49. Reiss Philip T. & Huang Lei, 2012. "Smoothness Selection for Penalized Quantile Regression Splines," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-27, May.
    50. Timo Dimitriadis & Tobias Fissler & Johanna Ziegel, 2020. "The Efficiency Gap," Papers 2010.14146, arXiv.org, revised Sep 2022.
    51. Christian Brownlees & Giuseppe Cavaliere & Alice Monti, 2018. "Evaluating The Accuracy Of Tail Risk Forecasts For Systemic Risk Measurement," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(02), pages 1-25, June.
    52. Bera Anil K. & Galvao Antonio F. & Montes-Rojas Gabriel V. & Park Sung Y., 2016. "Asymmetric Laplace Regression: Maximum Likelihood, Maximum Entropy and Quantile Regression," Journal of Econometric Methods, De Gruyter, vol. 5(1), pages 79-101, January.
    53. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207.
    54. Lee, Tae-Hwy & Yang, Yang, 2006. "Bagging binary and quantile predictors for time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 465-497.
    55. Tae-Hwy Lee & Aman Ullah & He Wang, 2023. "The Second-order Bias and Mean Squared Error of Quantile Regression Estimators," Working Papers 202313, University of California at Riverside, Department of Economics.
    56. El Ghouch, Anouar & Genton, Marc G., 2009. "Local Polynomial Quantile Regression With Parametric Features," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1416-1429.
    57. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    58. de Castro, Luciano & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2020. "Quantile selection in non-linear GMM quantile models," Economics Letters, Elsevier, vol. 195(C).
    59. Meligkotsidou, Loukia & Vrontos, Ioannis D. & Vrontos, Spyridon D., 2009. "Quantile regression analysis of hedge fund strategies," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 264-279, March.
    60. Timo Dimitriadis & Tobias Fissler & Johanna Ziegel, 2022. "Characterizing M-estimators," Papers 2208.08108, arXiv.org.
    61. Cai, Zongwu & Chen, Linna & Fang, Ying, 2018. "A semiparametric quantile panel data model with an application to estimating the growth effect of FDI," Journal of Econometrics, Elsevier, vol. 206(2), pages 531-553.
    62. Zongwu Cai & Ying Fang & Dingshi Tian, 2024. "CAViaR Model Selection Via Adaptive Lasso," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202403, University of Kansas, Department of Economics, revised Jan 2024.
    63. Xiaochun Meng & James W. Taylor & Souhaib Ben Taieb & Siran Li, 2020. "Scores for Multivariate Distributions and Level Sets," Papers 2002.09578, arXiv.org, revised Jun 2023.
    64. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
    65. Manganelli, Simone & White, Halbert & Kim, Tae-Hwan, 2008. "Modeling autoregressive conditional skewness and kurtosis with multi-quantile CAViaR," Working Paper Series 957, European Central Bank.
    66. Rahim Alhamzawi, 2016. "Bayesian Analysis of Composite Quantile Regression," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 8(2), pages 358-373, October.
    67. Dong Jin Lee & Jai Hyung Yoon, 2012. "The New Keynesian Phillips Curves in Multiple Quantiles and the Asymmetry of Monetary Policy," Working papers 2012-03, University of Connecticut, Department of Economics.
    68. Gonzalez-Rivera, Gloria & Lee, Tae-Hwy & Yoldas, Emre, 2007. "Optimality of the RiskMetrics VaR model," Finance Research Letters, Elsevier, vol. 4(3), pages 137-145, September.
    69. Alecos Papadopoulos, 2024. "Some notes on the asymmetry of the regression error," Journal of Productivity Analysis, Springer, vol. 61(1), pages 37-42, February.
    70. Haowen Bao & Zongwu Cai & Yuying Sun & Shouyang Wang, 2023. "Penalized Model Averaging for High Dimensional Quantile Regressions," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202302, University of Kansas, Department of Economics, revised Jan 2023.
    71. Marco Bee & Luca Trapin, 2018. "Estimating and Forecasting Conditional Risk Measures with Extreme Value Theory: A Review," Risks, MDPI, vol. 6(2), pages 1-16, April.

  17. Komunjer, Ivana, 2001. "Consistent Estimation for Aggregated GARCH," University of California at San Diego, Economics Working Paper Series qt1fp2v3q7, Department of Economics, UC San Diego.

    Cited by:

    1. Jondeau, Eric, 2015. "The dynamics of squared returns under contemporaneous aggregation of GARCH models," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 80-93.
    2. Gibson, Heather D. & Hall, Stephen G. & Tavlas, George S., 2017. "A suggestion for constructing a large time-varying conditional covariance matrix," Economics Letters, Elsevier, vol. 156(C), pages 110-113.
    3. Eric Jondeau, 2008. "Contemporaneous Aggregation of GARCH Models and Evaluation of the Aggregation Bias," Swiss Finance Institute Research Paper Series 08-06, Swiss Finance Institute.

Articles

  1. Komunjer, Ivana & Zhu, Yinchu, 2020. "Likelihood ratio testing in linear state space models: An application to dynamic stochastic general equilibrium models," Journal of Econometrics, Elsevier, vol. 218(2), pages 561-586.

    Cited by:

    1. Andrzej Kocięcki & Marcin Kolasa, 2022. "A solution to the global identification problem in DSGE models," Working Papers 2022-01, Faculty of Economic Sciences, University of Warsaw.

  2. Julieta Caunedo & Riccardo Dicecio & Ivana Komunjer & Michael T. Owyang, 2020. "Asymmetry, Complementarities, and State Dependence in Federal Reserve Forecasts," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(1), pages 205-228, February.
    See citations under working paper version above.
  3. Gospodinov, Nikolay & Komunjer, Ivana & Ng, Serena, 2017. "Simulated minimum distance estimation of dynamic models with errors-in-variables," Journal of Econometrics, Elsevier, vol. 200(2), pages 181-193.

    Cited by:

    1. Bao, Yong & Yu, Xuewen, 2023. "Indirect inference estimation of dynamic panel data models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1027-1053.
    2. Yong Bao & Xiaotian Liu & Lihong Yang, 2020. "Indirect Inference Estimation of Spatial Autoregressions," Econometrics, MDPI, vol. 8(3), pages 1-26, September.
    3. Czellar, Veronika & Frazier, David T. & Renault, Eric, 2022. "Approximate maximum likelihood for complex structural models," Journal of Econometrics, Elsevier, vol. 231(2), pages 432-456.
    4. Sönksen, Jantje & Grammig, Joachim, 2021. "Empirical asset pricing with multi-period disaster risk: A simulation-based approach," Journal of Econometrics, Elsevier, vol. 222(1), pages 805-832.
    5. Veronika Czellar & David T. Frazier & Eric Renault, 2020. "Approximate Maximum Likelihood for Complex Structural Models," Papers 2006.10245, arXiv.org.
    6. Worapree Maneesoonthorn & David T. Frazier & Gael M. Martin, 2024. "Probabilistic Predictions of Option Prices Using Multiple Sources of Data," Papers 2412.00658, arXiv.org.
    7. Czellar, Veronika & Frazier, David T. & Renault, Eric, 2021. "Approximate Maximum Likelihood for Complex Structural Models," The Warwick Economics Research Paper Series (TWERPS) 1337, University of Warwick, Department of Economics.
    8. Yong Bao, 2021. "Indirect Inference Estimation of a First-Order Dynamic Panel Data Model," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 79-98, December.
    9. Jean-Jacques Forneron, 2019. "A Sieve-SMM Estimator for Dynamic Models," Papers 1902.01456, arXiv.org, revised Jan 2023.
    10. Shuowen Chen, 2022. "Indirect Inference for Nonlinear Panel Models with Fixed Effects," Papers 2203.10683, arXiv.org, revised Apr 2022.

  4. Komunjer, Ivana & Ragusa, Giuseppe, 2016. "Existence And Characterization Of Conditional Density Projections," Econometric Theory, Cambridge University Press, vol. 32(4), pages 947-987, August.

    Cited by:

    1. Qiu, Chen & Otsu, Taisuke, 2022. "Information theoretic approach to high dimensional multiplicative models: stochastic discount factor and treatment effect," LSE Research Online Documents on Economics 110494, London School of Economics and Political Science, LSE Library.
    2. Tae-Hwy Lee & Millie Yi Mao & Aman Ullah, 2020. "Maximum Entropy Analysis of Consumption-based Capital Asset Pricing Model and Volatility," Working Papers 202015, University of California at Riverside, Department of Economics.
    3. Andreas Tryphonides, 2018. "Tilting Approximate Models," Papers 1805.10869, arXiv.org, revised Mar 2024.
    4. Timothy Christensen & Benjamin Connault, 2019. "Counterfactual Sensitivity and Robustness," Papers 1904.00989, arXiv.org, revised May 2022.
    5. Chen Qiu & Taisuke Otsu, 2022. "Information theoretic approach to high‐dimensional multiplicative models: Stochastic discount factor and treatment effect," Quantitative Economics, Econometric Society, vol. 13(1), pages 63-94, January.
    6. Christis Katsouris, 2023. "Optimal Estimation Methodologies for Panel Data Regression Models," Papers 2311.03471, arXiv.org, revised Nov 2023.
    7. Naoya Sueishi, 2022. "A Misuse of Specification Tests," Papers 2211.11915, arXiv.org.
    8. Tryphonides, Andreas, 2017. "Conditional moment restrictions and the role of density information in estimated structural models," SFB 649 Discussion Papers 2017-016, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    9. Timothy Christensen & Benjamin Connault, 2023. "Counterfactual Sensitivity and Robustness," Econometrica, Econometric Society, vol. 91(1), pages 263-298, January.

  5. Chiappori, Pierre-André & Komunjer, Ivana & Kristensen, Dennis, 2015. "Nonparametric identification and estimation of transformation models," Journal of Econometrics, Elsevier, vol. 188(1), pages 22-39.
    See citations under working paper version above.
  6. Komunjer, Ivana & Ng, Serena, 2014. "Measurement Errors In Dynamic Models," Econometric Theory, Cambridge University Press, vol. 30(1), pages 150-175, February.

    Cited by:

    1. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2016. "Modeling and Forecasting (Un)Reliable Realized Covariances for More Reliable Financial Decisions," CREATES Research Papers 2016-10, Department of Economics and Business Economics, Aarhus University.
    2. Daniel Kaufmann, 2017. "Is Deflation Costly After All? The Perils of Erroneous Historical Classifications," IRENE Working Papers 17-09, IRENE Institute of Economic Research.
    3. Thomas von Brasch & Diana-Cristina Iancu & Terje Skjerpen, 2017. "Productivity dispersion and measurement errors," Discussion Papers 869, Statistics Norway, Research Department.
    4. Edith Kitzmantel, 2016. "EU-Fiskalregeln - Anker oder Mühlstein der europäischen Wirtschaftspolitik?," Wirtschaft und Gesellschaft - WuG, Kammer für Arbeiter und Angestellte für Wien, Abteilung Wirtschaftswissenschaft und Statistik, vol. 42(3), pages 431-450.
    5. Nikolay Gospodinov & Ivana Komunjer & Serena Ng, 2014. "Minimum Distance Estimation of Dynamic Models with Errors-In-Variables," FRB Atlanta Working Paper 2014-11, Federal Reserve Bank of Atlanta.
    6. Alicia N. Rambaldi & Ryan R. J. McAllister & Cameron S. Fletcher, 2015. "Decoupling land values in residential property prices: smoothing methods for hedonic imputed price indices," Discussion Papers Series 549, School of Economics, University of Queensland, Australia.
    7. Gospodinov, Nikolay & Komunjer, Ivana & Ng, Serena, 2017. "Simulated minimum distance estimation of dynamic models with errors-in-variables," Journal of Econometrics, Elsevier, vol. 200(2), pages 181-193.
    8. Hilbert, Martin, 2016. "The bad news is that the digital access divide is here to stay: Domestically installed bandwidths among 172 countries for 1986–2014," Telecommunications Policy, Elsevier, vol. 40(6), pages 567-581.
    9. Jiahe Lin & George Michailidis, 2019. "Regularized Estimation of High-dimensional Factor-Augmented Vector Autoregressive (FAVAR) Models," Papers 1912.04146, arXiv.org, revised May 2020.

  7. Pierre-André Chiappori & Olivier Donni & Ivana Komunjer, 2012. "Learning from a Piece of Pie," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(1), pages 162-195.

    Cited by:

    1. Le Breton, Michel & Van Der Straeten, Karine, 2012. "Alliances Electorales entre Deux Tours de Scrutin : Le Point de Vue de la Théorie des Jeux Coopératifs et une Application aux Elections Régionales de Mars 2010," TSE Working Papers 12-295, Toulouse School of Economics (TSE).
    2. Jean-paul Chavas & Martina Menon & Federico Perali, 2014. "The Sharing Rule: Where Is It?," Working Papers 27/2014, University of Verona, Department of Economics.
    3. Donni, Olivier & Molina, José Alberto, 2018. "Household Collective Models: Three Decades of Theoretical Contributions and Empirical Evidence," IZA Discussion Papers 11915, Institute of Labor Economics (IZA).
    4. Jean-Paul Chavas & Eleonora Matteazzi & Martina Menon & Federico Perali, 2021. "Bargaining in the Family," CHILD Working Papers Series 88 JEL Classification: D1, Centre for Household, Income, Labour and Demographic Economics (CHILD) - CCA.
    5. Bo E. Honoré & Áureo de Paula, 2016. "A new model for interdependent durations with an application to joint retirement," CeMMAP working papers 07/16, Institute for Fiscal Studies.
    6. Bo E. Honoré & Áureo de Paula, 2013. "Interdependent durations in joint retirement," CeMMAP working papers 05/13, Institute for Fiscal Studies.
    7. Cherchye, Laurens & Demuynck, Thomas & De Rock, Bram, 2013. "The empirical content of Cournot competition," Journal of Economic Theory, Elsevier, vol. 148(4), pages 1552-1581.
    8. Oliveira, Fernando S., 2023. "The emergence of social inequality: A Co-Evolutionary analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 215(C), pages 192-206.
    9. Nishimura, Hiroki, 2021. "Revealed preferences of individual players in sequential games," Journal of Mathematical Economics, Elsevier, vol. 96(C).
    10. Laurens CHERCHYE & Thomas DEMUYNCK & Bram DE ROCK, 2011. "Nash bargained consumption decisions: a revealed preference analysis," Working Papers of Department of Economics, Leuven ces11.07, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    11. , P. & ,, 2014. "On the consistency of data with bargaining theories," Theoretical Economics, Econometric Society, vol. 9(1), January.
    12. Jean-Paul Chavas & Eleonora Matteazzi & Martina Menon & Federico Perali, 2022. "(In)Efficient Bargaining in the Family," Working Papers 2, SITES.
    13. Hubner, Stefan, 2016. "Topics in nonparametric identification and estimation," Other publications TiSEM 08fce56b-3193-46e0-871b-0, Tilburg University, School of Economics and Management.
    14. David Boto-García & Petr Mariel, 2024. "How well do couples know their partners’ preferences? Experimental evidence from joint recreation," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 41(3), pages 657-686, October.
    15. Hubner, Stefan, 2023. "Identification of unobserved distribution factors and preferences in the collective household model," Journal of Econometrics, Elsevier, vol. 234(1), pages 301-326.

  8. Komunjer, Ivana, 2012. "Global Identification In Nonlinear Models With Moment Restrictions," Econometric Theory, Cambridge University Press, vol. 28(4), pages 719-729, August.

    Cited by:

    1. Áureo de Paula & Imran Rasul & Pedro CL Souza, 2023. "Identifying network ties from panel data: Theory and an application to tax competition," CeMMAP working papers 21/23, Institute for Fiscal Studies.
    2. Fabio A. Miessi Sanches & Daniel Silva Junior, Sorawoot Srisuma, 2015. "Minimum Distance Estimation of Search Costs using Price Distribution," Working Papers, Department of Economics 2015_31, University of São Paulo (FEA-USP).
    3. Áureo de Paula & Imran Rasul & Pedro CL Souza, 2018. "Recovering social networks from panel data: identification, simulations and an application," CeMMAP working papers CWP17/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Mutschler, Willi, 2014. "Identification of DSGE Models - A Comparison of Methods and the Effect of Second Order Approximation," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100598, Verein für Socialpolitik / German Economic Association.
    5. Nail Kashaev, 2022. "Estimation of Parametric Binary Outcome Models with Degenerate Pure Choice-Based Data with Application to COVID-19-Positive Tests from British Columbia," University of Western Ontario, Departmental Research Report Series 20225, University of Western Ontario, Department of Economics.
    6. Zhentao Shi & Huanhuan Zheng, 2018. "Structural estimation of behavioral heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(5), pages 690-707, August.
    7. Komarova, Tatiana & Sanches, Fábio Adriano & Silva Junior, Daniel & Srisuma, Sorawoot, 2018. "Joint analysis of the discount factor and payoff parameters in dynamic discrete choice games," LSE Research Online Documents on Economics 86858, London School of Economics and Political Science, LSE Library.
    8. Arthur Lewbel, 2018. "The Identification Zoo - Meanings of Identification in Econometrics," Boston College Working Papers in Economics 957, Boston College Department of Economics, revised 14 Dec 2019.
    9. Iaria, Alessandro & ,, 2020. "Identification and Estimation of Demand for Bundles," CEPR Discussion Papers 14363, C.E.P.R. Discussion Papers.
    10. Timo Dimitriadis & Tobias Fissler & Johanna Ziegel, 2020. "The Efficiency Gap," Papers 2010.14146, arXiv.org, revised Sep 2022.
    11. Timo Dimitriadis & Tobias Fissler & Johanna Ziegel, 2022. "Characterizing M-estimators," Papers 2208.08108, arXiv.org.
    12. Forneron, Jean-Jacques, 2024. "Detecting identification failure in moment condition models," Journal of Econometrics, Elsevier, vol. 238(1).

  9. Ivana Komunjer & Michael T. Owyang, 2012. "Multivariate Forecast Evaluation and Rationality Testing," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1066-1080, November.
    See citations under working paper version above.
  10. Arnaud Costinot & Dave Donaldson & Ivana Komunjer, 2012. "What Goods Do Countries Trade? A Quantitative Exploration of Ricardo's Ideas," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(2), pages 581-608.
    See citations under working paper version above.
  11. Ivana Komunjer & Serena Ng, 2011. "Dynamic Identification of Dynamic Stochastic General Equilibrium Models," Econometrica, Econometric Society, vol. 79(6), pages 1995-2032, November.

    Cited by:

    1. Ho, Paul, 2024. "Estimating the effects of demographics on interest rates: A robust Bayesian perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 158(C).
    2. Ríos-Rull, José-Víctor & Schorfheide, Frank & Fuentes-Albero, Cristina & Kryshko, Maxym & Santaeulàlia-Llopis, Raül, 2012. "Methods versus substance: Measuring the effects of technology shocks," Journal of Monetary Economics, Elsevier, vol. 59(8), pages 826-846.
    3. Jean-Bernard Chatelain & Kirsten Ralf, 2019. "Publish and Perish: Creative Destruction and Macroeconomic Theory," PSE Working Papers halshs-01720655, HAL.
    4. Inoue, Atsushi & Kuo, Chun-Hung & Rossi, Barbara, 2020. "Identifying the sources of model misspecification," Journal of Monetary Economics, Elsevier, vol. 110(C), pages 1-18.
    5. Jean-Bernard Chatelain & Kirsten Ralf, 2014. "Stability and Identification with Optimal Macroprudential Policy Rules," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00978145, HAL.
    6. Andrzej Kocięcki & Marcin Kolasa, 2022. "A solution to the global identification problem in DSGE models," Working Papers 2022-01, Faculty of Economic Sciences, University of Warsaw.
    7. Chatelain, Jean-Bernard & Ralf, Kirsten, 2017. "Can we Identify the Fed's Preferences?," MPRA Paper 76831, University Library of Munich, Germany.
    8. Massimo Franchi & Paolo Paruolo, 2015. "Minimality of State Space Solutions of DSGE Models and Existence Conditions for Their VAR Representation," Computational Economics, Springer;Society for Computational Economics, vol. 46(4), pages 613-626, December.
    9. Meradj Morteza Pouraghdam, 2016. "Three essays on the role of frictions in the economy [Trois essais sur le rôle du désaccord en économie]," SciencePo Working papers Main tel-03498781, HAL.
    10. Peter A. Zadrozny, 2022. "Linear Identification of Linear Rational-Expectations Models by Exogenous Variables Reconciles Lucas and Sims," CESifo Working Paper Series 10078, CESifo.
    11. Peter A. Zadrozny, 2016. "Extended Yule-Walker Identification of Varma Models with Single- or Mixed-Frequency Data," CESifo Working Paper Series 5884, CESifo.
    12. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    13. Paul Beaudry & Fabrice Collard & Patrick Feve & Alain Guay & Franck Portier, 2022. "Dynamic Identification in VARs," Working Papers 22-08, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    14. Kyle Jurado, 2016. "Advance Information and Distorted Beliefs in Macroeconomic and Financial Fluctuations," 2016 Meeting Papers 154, Society for Economic Dynamics.
    15. Jesús Fernández-Villaverde & Pablo A. Guerrón-Quintana, 2020. "Estimating DSGE Models: Recent Advances and Future Challenges," NBER Working Papers 27715, National Bureau of Economic Research, Inc.
    16. Meenagh, David & Minford, Patrick & Wickens, Michael & Xu, Yongdeng, 2018. "Testing DSGE Models by indirect inference: a survey of recent findings," Cardiff Economics Working Papers E2018/14, Cardiff University, Cardiff Business School, Economics Section.
    17. Olkhov, Victor, 2019. "New Essentials of Economic Theory," MPRA Paper 95065, University Library of Munich, Germany.
    18. Benchimol, Jonathan & Bounader, Lahcen, 2018. "Optimal monetary policy under bounded rationality," Bank of Finland Research Discussion Papers 9/2018, Bank of Finland.
    19. Majid Al-Sadoon & Piotr Zwiernik, 2019. "The identification problem for linear rational expectations models," Economics Working Papers 1669, Department of Economics and Business, Universitat Pompeu Fabra.
    20. Dave, Chetan & Malik, Samreen, 2017. "A tale of fat tails," European Economic Review, Elsevier, vol. 100(C), pages 293-317.
    21. Enrique Martínez García, 2020. "A Matter of Perspective: Mapping Linear Rational Expectations Models into Finite-Order VAR Form," Globalization Institute Working Papers 389, Federal Reserve Bank of Dallas.
    22. D.S. Poskitt & Wenying Yao, 2012. "VAR Modeling and Business Cycle Analysis: A Taxonomy of Errors," Monash Econometrics and Business Statistics Working Papers 11/12, Monash University, Department of Econometrics and Business Statistics.
    23. Yunus Aksoy & Henrique S. Basso & Ron P. Smith & Tobias Grasl, 2019. "Demographic Structure and Macroeconomic Trends," American Economic Journal: Macroeconomics, American Economic Association, vol. 11(1), pages 193-222, January.
    24. Olkhov, Victor, 2019. "New Essentials of Economic Theory I. Assumptions, Economic Space and Variables," MPRA Paper 93085, University Library of Munich, Germany.
    25. Anderson, Brian D.O. & Deistler, Manfred & Felsenstein, Elisabeth & Koelbl, Lukas, 2016. "The structure of multivariate AR and ARMA systems: Regular and singular systems; the single and the mixed frequency case," Journal of Econometrics, Elsevier, vol. 192(2), pages 366-373.
    26. Adolfson, Malin & Laséen, Stefan & Lindé, Jesper & Ratto, Marco, 2018. "Identification Versus Misspecification in New Keynesian Monetary Policy Models," Working Paper Series 362, Sveriges Riksbank (Central Bank of Sweden).
    27. Adjemian, Stéphane & Bastani, Houtan & Juillard, Michel & Karamé, Fréderic & Mihoubi, Ferhat & Mutschler, Willi & Pfeifer, Johannes & Ratto, Marco & Rion, Normann & Villemot, Sébastien, 2022. "Dynare: Reference Manual Version 5," Dynare Working Papers 72, CEPREMAP, revised Mar 2023.
      • Stéphane Adjemian & Houtan Bastani & Michel Juillard & Frédéric Karamé & Ferhat Mihoubi & Willi Mutschler & Johannes Pfeifer & Marco Ratto & Sébastien Villemot & Normann Rion, 2023. "Dynare: Reference Manual Version 5," PSE Working Papers hal-04219920, HAL.
      • Stéphane Adjemian & Houtan Bastani & Michel Juillard & Frédéric Karamé & Ferhat Mihoubi & Willi Mutschler & Johannes Pfeifer & Marco Ratto & Sébastien Villemot & Normann Rion, 2023. "Dynare: Reference Manual Version 5," Working Papers hal-04219920, HAL.
    28. Komunjer, Ivana & Zhu, Yinchu, 2020. "Likelihood ratio testing in linear state space models: An application to dynamic stochastic general equilibrium models," Journal of Econometrics, Elsevier, vol. 218(2), pages 561-586.
    29. Pedro Chaim & Márcio Poletti Laurini, 2022. "Data Cloning Estimation and Identification of a Medium-Scale DSGE Model," Stats, MDPI, vol. 6(1), pages 1-13, December.
    30. Elmar Mertens & James M. Nason, 2020. "Inflation and professional forecast dynamics: An evaluation of stickiness, persistence, and volatility," Quantitative Economics, Econometric Society, vol. 11(4), pages 1485-1520, November.
    31. Yao, Wenying & Kam, Timothy & Vahid, Farshid, 2014. "VAR(MA), what is it good for? more bad news for reduced-form estimation and inference," Working Papers 2014-14, University of Tasmania, Tasmanian School of Business and Economics.
    32. Nathan Bedock & Dalibor Stevanovic, 2012. "An Empirical Study of Credit Shock Transmission in a Small Open Economy," CIRANO Working Papers 2012s-16, CIRANO.
    33. Andrew Binning & Junior Maih, 2016. "Implementing the zero lower bound in an estimated regime-switching DSGE model," Working Paper 2016/3, Norges Bank.
    34. Andrew Binning & Junior Maih, 2015. "Sigma Point Filters For Dynamic Nonlinear Regime Switching Models," Working Papers No 4/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    35. Reicher, Christopher Phillip, 2013. "A note on the identification of dynamic economic models with generalized shock processes," Kiel Working Papers 1821, Kiel Institute for the World Economy (IfW Kiel).
    36. Tenreyro, Silvana & Broadbent, Ben & Di Pace, Federico & Drechsel, Thomas & Harrison, Richard, 2019. "The Brexit Vote, Productivity Growth and Macroeconomic Adjustments in the United Kingdom," CEPR Discussion Papers 13993, C.E.P.R. Discussion Papers.
    37. Deistler, Manfred & Wagner, Martin, 2017. "Cointegration in singular ARMA models," Economics Letters, Elsevier, vol. 155(C), pages 39-42.
    38. Mutschler, Willi, 2014. "Identification of DSGE Models - A Comparison of Methods and the Effect of Second Order Approximation," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100598, Verein für Socialpolitik / German Economic Association.
    39. Daniel O. Beltran & David Draper, 2018. "Estimating dynamic macroeconomic models: how informative are the data?," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(2), pages 501-520, February.
    40. Xiaoshan Chen & Tatiana Kirsanova & Campbell Leith, 2013. "How Optimal is US Monetary Policy?," Working Papers 2013_08, Business School - Economics, University of Glasgow.
    41. William Bednar & Nick Pretnar, 2019. "Home Production with Time to Consume," 2019 Meeting Papers 328, Society for Economic Dynamics.
    42. K. Lawler & T. Vlasova & A. Moscardini, 2019. "Using System Dynamics in Macroeconomics," Вестник Киевского национального университета имени Тараса Шевченко. Экономика., Socionet;Киевский национальный университет имени Тараса Шевченко, vol. 3(204), pages 34-40.
    43. Prosper Dovonon & Alastair Hall, 2018. "The Asymptotic Properties of GMM and Indirect Inference under Second-order Identification," CIRANO Working Papers 2018s-37, CIRANO.
    44. Olkhov, Victor, 2019. "Methods of Economic Theory: Variables, Transactions and Expectations as Functions of Risks," MPRA Paper 95628, University Library of Munich, Germany.
    45. Härtl, Tilmann, 2022. "Identifying Proxy VARs with Restrictions on the Forecast Error Variance," VfS Annual Conference 2022 (Basel): Big Data in Economics 264071, Verein für Socialpolitik / German Economic Association.
    46. Haberis, Alex & Sokol, Andrej, 2014. "A procedure for combining zero and sign restrictions in aVAR-identification scheme," LSE Research Online Documents on Economics 58077, London School of Economics and Political Science, LSE Library.
    47. Enrique Martínez García & Mark A. Wynne, 2014. "Assessing Bayesian model comparison in small samples," Globalization Institute Working Papers 189, Federal Reserve Bank of Dallas.
    48. Angelini, Giovanni, 2020. "Bootstrap lag selection in DSGE models with expectations correction," Econometrics and Statistics, Elsevier, vol. 14(C), pages 38-48.
    49. Luca Fanelli & Marco M. Sorge, 2015. "Indeterminacy, Misspecification and Forecastability: Good Luck in Bad Policy?," CSEF Working Papers 402, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    50. Raffaella Giacomini, 2013. "The relationship between DSGE and VAR models," CeMMAP working papers CWP21/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    51. Mutschler, Willi, 2015. "Identification of DSGE models—The effect of higher-order approximation and pruning," Journal of Economic Dynamics and Control, Elsevier, vol. 56(C), pages 34-54.
    52. S. Boragan Aruoba & Francis X. Diebold & Jeremy J. Nalewaik & Frank Schorfheide & Dongho Song, 2013. "Improving GDP measurement: a measurement-error perspective," Working Papers 13-16, Federal Reserve Bank of Philadelphia.
    53. Juan Carlos Parra-Alvarez & Olaf Posch & Mu-Chun Wang, 2020. "Estimation of heterogeneous agent models: A likelihood approach," CREATES Research Papers 2020-05, Department of Economics and Business Economics, Aarhus University.
    54. Willi Mutschler, 2015. "Higher-order statistics for DSGE models," CQE Working Papers 4315, Center for Quantitative Economics (CQE), University of Muenster.
    55. Nikolay Gospodinov & Serena Ng, 2015. "Minimum Distance Estimation of Possibly Noninvertible Moving Average Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 403-417, July.
    56. Marie-Christine Duker & David S. Matteson & Ruey S. Tsay & Ines Wilms, 2024. "Vector AutoRegressive Moving Average Models: A Review," Papers 2406.19702, arXiv.org.
    57. Le, Vo Phuong Mai & Minford, Patrick & Wickens, Michael, 2013. "A Monte Carlo procedure for checking identification in DSGE models," Cardiff Economics Working Papers E2013/4, Cardiff University, Cardiff Business School, Economics Section.
    58. Andreas Tryphonides, 2017. "Set Identified Dynamic Economies and Robustness to Misspecification," Papers 1712.03675, arXiv.org, revised Jan 2018.
    59. Jan P. A. M. Jacobs & Samad Sarferaz & Jan-Egbert Sturm & Simon van Norden, 2018. "Can GDP measurement be further improved? Data revision and reconciliation," Papers 1808.04970, arXiv.org.
    60. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
    61. Hsiao, Cody Yu-Ling & Jin, Tao & Kwok, Simon & Wang, Xi & Zheng, Xin, 2023. "Entrepreneurial risk shocks and financial acceleration asymmetry in a two-country DSGE model," China Economic Review, Elsevier, vol. 81(C).
    62. Zhongjun Qu & Denis Tkachenko, 2023. "Using arbitrary precision arithmetic to sharpen identification analysis for DSGE models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 644-667, June.
    63. Daniel Rees & David Lancaster & Richard Finlay, 2014. "A State-space Approach to Australian GDP Measurement," RBA Research Discussion Papers rdp2014-12, Reserve Bank of Australia.
    64. Saccal, Alessandro, 2020. "A note on minimality in Dynare," MPRA Paper 103656, University Library of Munich, Germany.
    65. Giovanni Angelini & Giuseppe Cavaliere & Luca Fanelli, 2022. "Bootstrap inference and diagnostics in state space models: With applications to dynamic macro models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 3-22, January.
    66. Giovanni Angelini & Paolo Gorgi, 2018. "DSGE Models with Observation-Driven Time-Varying parameters," Tinbergen Institute Discussion Papers 18-030/III, Tinbergen Institute.
    67. Dey, Jaya & Tsai, Yi-Chan, 2017. "Explaining the durable goods co-movement puzzle: A Bayesian approach," Journal of Macroeconomics, Elsevier, vol. 52(C), pages 75-99.
    68. Bernd Funovits, 2014. "Implications of Stochastic Singularity in Linear Multivariate Rational Expectations Models," Vienna Economics Papers vie1405, University of Vienna, Department of Economics.
    69. Pedro Brinca & Nikolay Iskrev & Francesca Loria, 2022. "On Identification Issues in Business Cycle Accounting Models," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 55-138, Emerald Group Publishing Limited.
    70. Angelini, Giovanni & Gorgi, Paolo, 2018. "DSGE Models with observation-driven time-varying volatility," Economics Letters, Elsevier, vol. 171(C), pages 169-171.
    71. Callum Jones & Mariano Kulish & Juan Pablo Nicolini, 2022. "Priors and the Slope of the Phillips Curve," Working Papers 165, Red Nacional de Investigadores en Economía (RedNIE).
    72. Yasuo Hirose & Hirokuni Iiboshi & Mototsugu Shintani & Kozo Ueda, 2024. "Estimating a Behavioral New Keynesian Model with the Zero Lower Bound," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 56(8), pages 2185-2197, December.
    73. Prosper Dovonon & Alastair R. Hall, 2017. "The Asymptotic Properties of GMM and Indirect Inference Under Second-Order Identification," Economics Discussion Paper Series 1705, Economics, The University of Manchester.
    74. Den Haan, Wouter & Drechsel, Thomas, 2018. "Agnostic Structural Disturbances (ASDs): Detecting and Reducing Misspecification in Empirical Macroeconomic Models," CEPR Discussion Papers 13145, C.E.P.R. Discussion Papers.
    75. Adjemian, Stéphane & Juillard, Michel & Karamé, Fréderic & Mutschler, Willi & Pfeifer, Johannes & Ratto, Marco & Rion, Normann & Villemot, Sébastien, 2024. "Dynare: Reference Manual, Version 6," Dynare Working Papers 80, CEPREMAP, revised Sep 2024.
    76. Majid M. Al-Sadoon, 2020. "Regularized Solutions to Linear Rational Expectations Models," Papers 2009.05875, arXiv.org, revised Oct 2020.
    77. Dovonon, Prosper & Hall, Alastair R., 2018. "The asymptotic properties of GMM and indirect inference under second-order identification," Journal of Econometrics, Elsevier, vol. 205(1), pages 76-111.
    78. Anna Mikusheva, 2014. "Estimation of dynamic stochastic general equilibrium models (in Russian)," Quantile, Quantile, issue 12, pages 1-21, February.
    79. Franchi, Massimo, 2018. "Testing for cointegration in I(1) state space systems via a finite order approximation," Economics Letters, Elsevier, vol. 165(C), pages 73-76.
    80. Filippo Ferroni & Stefano Grassi & Miguel A. León-Ledesma, 2017. "Selecting Primal Innovations in DSGE models," Working Paper Series WP-2017-20, Federal Reserve Bank of Chicago.
    81. Tatiana Kirsanova & Celsa Machado & Ana Paula Ribeiro, 2020. "Tight and Loose, and Red and Blue: A 'Dance' of Macro Policies in the US," Working Papers 2020_14, Business School - Economics, University of Glasgow.
    82. Filippo Ferroni & Stefano Grassi & Miguel A. Leon-Ledesma, 2015. "Fundamental shock selection in DSGE models," Studies in Economics 1508, School of Economics, University of Kent.
    83. Xiaoshan Chen & Eric M. Leeper & Campbell B. Leith, 2020. "Strategic Interactions in U.S. Monetary and Fiscal Policies," NBER Working Papers 27540, National Bureau of Economic Research, Inc.
    84. Juan Carlos Parra‐Alvarez & Olaf Posch & Mu‐Chun Wang, 2023. "Estimation of Heterogeneous Agent Models: A Likelihood Approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(2), pages 304-330, April.
    85. Victor Olkhov, 2019. "Financial Variables, Market Transactions, and Expectations as Functions of Risk," IJFS, MDPI, vol. 7(4), pages 1-27, November.
    86. Alessandro SACCAL, 2021. "A Note On Gensys’ Minimality," Theoretical and Practical Research in the Economic Fields, ASERS Publishing, vol. 12(1), pages 57-60.
    87. McAdam, Peter & Warne, Anders, 2018. "Euro area real-time density forecasting with financial or labor market frictions," Working Paper Series 2140, European Central Bank.
    88. Paul Ho, 2019. "Global Robust Bayesian Analysis in Large Models," 2019 Meeting Papers 390, Society for Economic Dynamics.
    89. Sergey Ivashchenko & Willi Mutschler, 2019. "The effect of observables, functional specifications, model features and shocks on identification in linearized DSGE models," CQE Working Papers 8319, Center for Quantitative Economics (CQE), University of Muenster.
    90. Guglielminetti, Elisa & Pouraghdam, Meradj, 2018. "Time-varying job creation and macroeconomic shocks," Labour Economics, Elsevier, vol. 50(C), pages 156-179.
    91. Funovits, Bernd, 2017. "The full set of solutions of linear rational expectations models," Economics Letters, Elsevier, vol. 161(C), pages 47-51.
    92. Juan Carlos Parra-Alvarez & Olaf Posch & Mu-Chun Wang, 2017. "Identification and estimation of heterogeneous agent models: A likelihood approach," CREATES Research Papers 2017-35, Department of Economics and Business Economics, Aarhus University.
    93. Emanuele Bacchiocchi & Toru Kitagawa, 2022. "Locally- but not Globally-identified SVARs," Working Papers wp1171, Dipartimento Scienze Economiche, Universita' di Bologna.
    94. Majid M. Al-Sadoon, 2020. "The Spectral Approach to Linear Rational Expectations Models," Papers 2007.13804, arXiv.org, revised Aug 2024.
    95. Claire A. Reicher, 2016. "A Note on the Identification of Dynamic Economic Models with Generalized Shock Processes," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(3), pages 412-423, June.
    96. Krogh, Tord S., 2015. "Macro frictions and theoretical identification of the New Keynesian Phillips curve," Journal of Macroeconomics, Elsevier, vol. 43(C), pages 191-204.
    97. Raffaella Giacomini, 2013. "The relationship between DSGE and VAR models," CeMMAP working papers 21/13, Institute for Fiscal Studies.
    98. Massimo Franchi, 2013. "Comment on: Ravenna, F., 2007. Vector autoregressions and reduced form representations of DSGE models. Journal of Monetary Economics 54, 2048-2064," DSS Empirical Economics and Econometrics Working Papers Series 2013/2, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
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    101. Deák, Szabolcs & Levine, Paul & Pham, Son T., 2024. "Simple mandates, monetary rules, and trend-inflation," Macroeconomic Dynamics, Cambridge University Press, vol. 28(4), pages 757-790, June.
    102. Fanelli, Luca & Sorge, Marco M., 2017. "Indeterminate forecast accuracy under indeterminacy," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 57-70.
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  12. Komunjer, Ivana & Vuong, Quang, 2010. "Efficient estimation in dynamic conditional quantile models," Journal of Econometrics, Elsevier, vol. 157(2), pages 272-285, August.

    Cited by:

    1. Lavergne, Pascal & Patilea, Valentin, 2013. "Smooth minimum distance estimation and testing with conditional estimating equations: Uniform in bandwidth theory," Journal of Econometrics, Elsevier, vol. 177(1), pages 47-59.
    2. Jungmo Yoon & Antonio F. Galvao, 2020. "Cluster robust covariance matrix estimation in panel quantile regression with individual fixed effects," Quantitative Economics, Econometric Society, vol. 11(2), pages 579-608, May.
    3. Tae-Hwan Kim & Dong Jin Lee & Paul Mizen, 2020. "Impulse Response Analysis in Conditional Quantile Models and an Application to Monetary Policy," Working papers 2020rwp-164, Yonsei University, Yonsei Economics Research Institute.
    4. Dong Jin Lee, 2020. "Optimal tests for parameter breaking process in conditional quantile models," The Japanese Economic Review, Springer, vol. 71(3), pages 479-510, July.
    5. De Rezende, Rafael B., 2015. "Risks in macroeconomic fundamentals and excess bond returns predictability," Working Paper Series 295, Sveriges Riksbank (Central Bank of Sweden).
    6. Dong Jin Lee & Tae-Hwan Kim & Paul Mizen, 2020. "Impulse response analysis in conditional quantile models with an application to monetary policy," Discussion Papers 2020/08, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
    7. Antonio Galvao & Kengo Kato & Gabriel Montes-Rojas & Jose Olmo, 2014. "Testing linearity against threshold effects: uniform inference in quantile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(2), pages 413-439, April.
    8. White, Halbert & Kim, Tae-Hwan & Manganelli, Simone, 2010. "VAR for VaR: measuring systemic risk using multivariate regression quantiles," MPRA Paper 35372, University Library of Munich, Germany.
    9. Timo Dimitriadis & Tobias Fissler & Johanna Ziegel, 2020. "The Efficiency Gap," Papers 2010.14146, arXiv.org, revised Sep 2022.
    10. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.

  13. Komunjer, Ivana & Vuong, Quang, 2010. "Semiparametric Efficiency Bound In Time-Series Models For Conditional Quantiles," Econometric Theory, Cambridge University Press, vol. 26(2), pages 383-405, April.

    Cited by:

    1. J. C. Escanciano & S. C. Goh, 2019. "Quantile-Regression Inference With Adaptive Control of Size," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(527), pages 1382-1393, July.
    2. Komunjer, Ivana & Ragusa, Giuseppe, 2009. "Existence and Uniqueness of Semiparametric Projections," University of California at San Diego, Economics Working Paper Series qt0wg3j51c, Department of Economics, UC San Diego.
    3. Ahnaf Rafi, 2023. "Efficient Semiparametric Estimation of Average Treatment Effects Under Covariate Adaptive Randomization," Papers 2305.08340, arXiv.org.
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    1. Clements, Michael P., 2008. "Explanations of the inconsistencies in survey respondents'forecasts," The Warwick Economics Research Paper Series (TWERPS) 870, University of Warwick, Department of Economics.
    2. Ivana Komunjer & Michael T. Owyang, 2012. "Multivariate Forecast Evaluation and Rationality Testing," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1066-1080, November.
    3. Stan Hurn & Jing Tian & Lina Xu, 2021. "Assessing the Informational Content of Official Australian Bureau of Meteorology Forecasts of Wind Speed," The Economic Record, The Economic Society of Australia, vol. 97(319), pages 525-547, December.
    4. Capistrán, Carlos & López-Moctezuma, Gabriel, 2014. "Forecast revisions of Mexican inflation and GDP growth," International Journal of Forecasting, Elsevier, vol. 30(2), pages 177-191.
    5. Michael Frenkel & Jin-Kyu Jung & Jan-Christoph Rülke, 2017. "Rationalizing the Bias in Central Banks' Interest Rate Projections," WHU Working Paper Series - Economics Group 17-03, WHU - Otto Beisheim School of Management.
    6. Lee, Tae-Hwy & Ullah, Aman & Wang, He, 2018. "The second-order bias of quantile estimators," Economics Letters, Elsevier, vol. 173(C), pages 143-147.
    7. Kilian, Lutz & Alquist, Ron, 2007. "What Do We Learn from the Price of Crude Oil Futures?," CEPR Discussion Papers 6548, C.E.P.R. Discussion Papers.
    8. Wieland, Volker & Wolters, Maik, 2013. "Forecasting and Policy Making," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 239-325, Elsevier.
    9. Emmanuel C. Mamatzakis & Mike G. Tsionas, 2020. "Revealing forecaster's preferences: A Bayesian multivariate loss function approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 412-437, April.
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    14. Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2015. "Central banks’ inflation forecasts under asymmetric loss: Evidence from four Latin-American countries," Economics Letters, Elsevier, vol. 129(C), pages 66-70.
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  19. Komunjer, Ivana, 2005. "Quasi-maximum likelihood estimation for conditional quantiles," Journal of Econometrics, Elsevier, vol. 128(1), pages 137-164, September.
    See citations under working paper version above.
  20. Giacomini, Raffaella & Komunjer, Ivana, 2005. "Evaluation and Combination of Conditional Quantile Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 416-431, October.
    See citations under working paper version above.

Chapters

  1. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.

    Cited by:

    1. Oh, Dong Hwan & Patton, Andrew J., 2024. "Better the devil you know: Improved forecasts from imperfect models," Journal of Econometrics, Elsevier, vol. 242(1).
    2. Kraus, Daniel & Czado, Claudia, 2017. "D-vine copula based quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 110(C), pages 1-18.
    3. Bayer, Sebastian, 2018. "Combining Value-at-Risk forecasts using penalized quantile regressions," Econometrics and Statistics, Elsevier, vol. 8(C), pages 56-77.
    4. Andrew J. Patton & Johanna F. Ziegel & Rui Chen, 2017. "Dynamic Semiparametric Models for Expected Shortfall (and Value-at-Risk)," Papers 1707.05108, arXiv.org.
    5. Bruzda, Joanna, 2019. "Quantile smoothing in supply chain and logistics forecasting," International Journal of Production Economics, Elsevier, vol. 208(C), pages 122-139.

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