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Alan Bester

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.

Articles

  1. Bester, C. Alan & Conley, Timothy G. & Hansen, Christian B., 2011. "Inference with dependent data using cluster covariance estimators," Journal of Econometrics, Elsevier, vol. 165(2), pages 137-151.

    Cited by:

    1. James G. MacKinnon & Matthew D. Webb, 2019. "Randomization Inference For Difference-in-differences With Few Treated Clusters," Working Paper 1355, Economics Department, Queen's University.
    2. Christina Gathmann & Björn Sass, 2012. "Taxing Childcare: Effects on Family Labor Supply and Children," CESifo Working Paper Series 3776, CESifo.
    3. Ferdinand Rauch & Stephan Maurer & Jörn-Steffen Pischke, 2018. "Of Mice and Merchants: Trade and Growth in the Iron Age," Economics Series Working Papers 854, University of Oxford, Department of Economics.
    4. Stephan E. Maurer & Andrei V. Potlogea, 2021. "Male‐biased Demand Shocks and Women's Labour Force Participation: Evidence from Large Oil Field Discoveries," Economica, London School of Economics and Political Science, vol. 88(349), pages 167-188, January.
    5. Wei, Yao & Anselmi, Laura & Munford, Luke & Sutton, Matt, 2023. "The impact of devolution on experienced health and well-being," Social Science & Medicine, Elsevier, vol. 333(C).
    6. Timothy G. Conley & Sílvia Gonçalves & Min Seong Kim & Benoit Perron, 2023. "Bootstrap inference under cross‐sectional dependence," Quantitative Economics, Econometric Society, vol. 14(2), pages 511-569, May.
    7. Natalia Bailey & Sean Holly & M. Hashem Pesaran, 2016. "A Two‐Stage Approach to Spatio‐Temporal Analysis with Strong and Weak Cross‐Sectional Dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 249-280, January.
    8. Chami, Goylette F. & Kontoleon, Andreas A. & Bulte, Erwin & Fenwick, Alan & Kabatereine, Narcis B. & Tukahebwa, Edridah M. & Dunne, David W., 2017. "Community-directed mass drug administration is undermined by status seeking in friendship networks and inadequate trust in health advice networks," Social Science & Medicine, Elsevier, vol. 183(C), pages 37-47.
    9. Michael Pollmann, 2020. "Causal Inference for Spatial Treatments," Papers 2011.00373, arXiv.org, revised Jan 2023.
    10. Hidalgo, Javier & Schafgans, Marcia, 2017. "Inference and testing breaks in large dynamic panels with strong cross sectional dependence," Journal of Econometrics, Elsevier, vol. 196(2), pages 259-274.
    11. Andrew Plantinga & Christopher Severen, 2017. "Land-Use Regulations, Property Values, and Rents: Decomposing the Effects of the California Coastal Act," Working Papers 17-33, Federal Reserve Bank of Philadelphia.
    12. Ulrich K. Müller & Mark W. Watson, 2021. "Spatial Correlation Robust Inference," Working Papers 2021-61, Princeton University. Economics Department..
    13. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2024. "Cluster-Robust Jackknife and Bootstrap Inference for Binary Response Models," Working Paper 1515, Economics Department, Queen's University.
    14. Margherita Comola & Marcel Fafchamps, 2009. "Testing Unilateral and Bilateral Link Formation," CSAE Working Paper Series 2009-13, Centre for the Study of African Economies, University of Oxford.
    15. Timothy Conley & Silvia Gonçalves & Christian Hansen, 2018. "Inference with Dependent Data in Accounting and Finance Applications," Journal of Accounting Research, Wiley Blackwell, vol. 56(4), pages 1139-1203, September.
    16. Katja Görlitz & Christina Gravert, 2018. "The effects of a high school curriculum reform on university enrollment and the choice of college major," Education Economics, Taylor & Francis Journals, vol. 26(3), pages 321-336, May.
    17. James G. MacKinnon, 2014. "Wild Cluster Bootstrap Confidence Intervals," Working Paper 1329, Economics Department, Queen's University.
    18. Stephan Heblich & Alex Trew, 2019. "Banking and Industrialization," Journal of the European Economic Association, European Economic Association, vol. 17(6), pages 1753-1796.
    19. Kojevnikov, Denis & Song, Kyungchul, 2023. "Some impossibility results for inference with cluster dependence with large clusters," Other publications TiSEM 80b8e4ed-54bc-4a34-883f-f, Tilburg University, School of Economics and Management.
    20. Zhang, Xianyang & Shao, Xiaofeng, 2013. "On a general class of long run variance estimators," Economics Letters, Elsevier, vol. 120(3), pages 437-441.
    21. Guido W. Imbens & Michal Kolesar, 2012. "Robust Standard Errors in Small Samples: Some Practical Advice," NBER Working Papers 18478, National Bureau of Economic Research, Inc.
    22. Cervellati, Matteo & Esposito, Elena & Sunde, Uwe & Valmori, Simona, 2017. "Malaria Risk and Civil Violence," Discussion Papers in Economics 36389, University of Munich, Department of Economics.
    23. Bruce E. Hansen & Seojeong Lee, 2019. "Asymptotic Theory for Clustered Samples," Papers 1902.01497, arXiv.org.
    24. Ferdinand Rauch & Guy Michaels, 2013. "Resetting the Urban Network: 117-2012," Economics Series Working Papers 684, University of Oxford, Department of Economics.
    25. Nathaniel Baum-Snow & Fernando Ferreira, 2014. "Causal Inference in Urban and Regional Economics," NBER Working Papers 20535, National Bureau of Economic Research, Inc.
    26. Bramoullé, Yann & Boucher, Vincent, 2020. "Binary Outcomes and Linear Interactions," CEPR Discussion Papers 15505, C.E.P.R. Discussion Papers.
    27. Samuel Bazzi & Martin Fiszbein & Mesay Gebresilasse, 2020. "Rugged Individualism and Collective (In)action During the COVID-19 Pandemic," Boston University - Department of Economics - The Institute for Economic Development Working Papers Series dp-351, Boston University - Department of Economics.
    28. Samuel Bazzi & Martin Fiszbein & Mesay Gebresilasse, 2018. "Frontier Culture: The Roots and Persistence of “Rugged Individualism†in the United States," Boston University - Department of Economics - The Institute for Economic Development Working Papers Series dp-302, Boston University - Department of Economics.
    29. Pesaran, M. Hashem & Tosetti, Elisa, 2007. "Large Panels with Common Factors and Spatial Correlations," IZA Discussion Papers 3032, Institute of Labor Economics (IZA).
    30. Gupta, Abhimanyu & Hidalgo, Javier, 2022. "Nonparametric prediction with spatial data," LSE Research Online Documents on Economics 115292, London School of Economics and Political Science, LSE Library.
    31. Kim, Min Seong & Sun, Yixiao, 2013. "Heteroskedasticity and spatiotemporal dependence robust inference for linear panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 177(1), pages 85-108.
    32. Daniel Aaronson & Bhashkar Mazumder, 2009. "The impact of Rosenwald Schools on Black achievement," Working Paper Series WP-09-26, Federal Reserve Bank of Chicago.
    33. Michaels, Guy & Nigmatulina, Dzhamilya & Rauch, Ferdinand & Regan, Tanner & Baruah, Neeraj & Dahlstrand-Rudin, Amanda, 2017. "Planning ahead for better neighborhoods: long run evidence from Tanzania," LSE Research Online Documents on Economics 86570, London School of Economics and Political Science, LSE Library.
    34. Brewer Mike & Crossley Thomas F. & Joyce Robert, 2018. "Inference with Difference-in-Differences Revisited," Journal of Econometric Methods, De Gruyter, vol. 7(1), pages 1-16, January.
    35. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2023. "Leverage, influence, and the jackknife in clustered regression models: Reliable inference using summclust," Stata Journal, StataCorp LP, vol. 23(4), pages 942-982, December.
    36. Vincent BOUCHER & Ismael MOURIFIÉ, 2013. "My Friend Far Far Away: Asymptotic Properties of Pairwise Stable Networks," Working Papers tecipa-499, University of Toronto, Department of Economics.
    37. J. Hidalgo & M. Schafgans, 2020. "Inference without smoothing for large panels with cross-sectional and temporal dependence," Papers 2006.14409, arXiv.org.
    38. Stephan Maurer & Ferdinand Rauch, 2019. "Economic Geography Aspects of the Panama Canal," Working Paper Series of the Department of Economics, University of Konstanz 2019-02, Department of Economics, University of Konstanz.
    39. Matthew Gentzkow & Jesse M. Shapiro & Michael Sinkinson, 2011. "The Effect of Newspaper Entry and Exit on Electoral Politics," American Economic Review, American Economic Association, vol. 101(7), pages 2980-3018, December.
    40. Javier Hidalgo & Marcia M Schafgans, 2015. "Inference and Testing Breaks in Large Dynamic Panels with Strong Cross Sectional Dependence," STICERD - Econometrics Paper Series /2015/583, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    41. James G. MacKinnon & Matthew D. Webb & Morten Ø. Nielsen, 2017. "Bootstrap And Asymptotic Inference With Multiway Clustering," Working Paper 1386, Economics Department, Queen's University.
    42. Sun, Yu & Yan, Karen X., 2019. "Inference on Difference-in-Differences average treatment effects: A fixed-b approach," Journal of Econometrics, Elsevier, vol. 211(2), pages 560-588.
    43. Hagemann, Andreas, 2019. "Placebo inference on treatment effects when the number of clusters is small," Journal of Econometrics, Elsevier, vol. 213(1), pages 190-209.
    44. Matthew D. Webb, 2014. "Reworking Wild Bootstrap Based Inference For Clustered Errors," Working Paper 1315, Economics Department, Queen's University.
    45. Bruno Ferman, 2019. "Inference in Difference-in-Differences: How Much Should We Trust in Independent Clusters?," Papers 1909.01782, arXiv.org, revised Sep 2022.
    46. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2022. "Fast and Reliable Jackknife and Bootstrap Methods for Cluster-Robust Inference," Working Paper 1485, Economics Department, Queen's University.
    47. Wang, Wenjie & Zhang, Yichong, 2024. "Wild bootstrap inference for instrumental variables regressions with weak and few clusters," Journal of Econometrics, Elsevier, vol. 241(1).
    48. Görlitz, Katja & Gravert, Christina, 2015. "The Effects of Increasing the Standards of the High School Curriculum on School Dropout," IZA Discussion Papers 8766, Institute of Labor Economics (IZA).
    49. David Powell, 2016. "Synthetic Control Estimation Beyond Case Studies Does the Minimum Wage Reduce Employment?," Working Papers WR-1142, RAND Corporation.
    50. Edward L. Glaeser & Sari Pekkala Kerr & William R. Kerr, 2012. "Entrepreneurship and Urban Growth: An Empirical Assessment with Historical Mines," NBER Working Papers 18333, National Bureau of Economic Research, Inc.
    51. Michael P. Leung, 2020. "Dependence-Robust Inference Using Resampled Statistics," Papers 2002.02097, arXiv.org, revised Aug 2021.
    52. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2020. "Wild Bootstrap and Asymptotic Inference with Multiway Clustering," CREATES Research Papers 2020-06, Department of Economics and Business Economics, Aarhus University.
    53. Maurer, Stephan E., 2019. "Oil discoveries and education provision in the Postbellum South," Economics of Education Review, Elsevier, vol. 73(C).
    54. Antoine A. Djogbenou & James G. MacKinnon & Morten Ørregaard Nielsen, 2019. "Asymptotic Theory and Wild Bootstrap Inference with Clustered Errors," CREATES Research Papers 2019-05, Department of Economics and Business Economics, Aarhus University.
    55. James G. MacKinnon & Morten {O}rregaard Nielsen & Matthew D. Webb, 2022. "Cluster-Robust Inference: A Guide to Empirical Practice," Papers 2205.03285, arXiv.org.
    56. James G. MacKinnon & Matthew D. Webb, 2017. "Pitfalls When Estimating Treatment Effects Using Clustered Data," Working Paper 1387, Economics Department, Queen's University.
    57. David Roodman & James G. MacKinnon & Matthew D. Webb & Morten Ø. Nielsen, 2018. "Fast And Wild: Bootstrap Inference In Stata Using Boottest," Working Paper 1406, Economics Department, Queen's University.
    58. A. Colin Cameron & Douglas L. Miller, 2015. "A Practitioner’s Guide to Cluster-Robust Inference," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 317-372.
    59. Gupta, A, 2015. "Autoregressive Spatial Spectral Estimates," Economics Discussion Papers 23825, University of Essex, Department of Economics.
    60. Luna Bellani & Anselm Hager & Stephan E. Maurer, 2020. "The Long Shadow of Slavery: The Persistence of Slave Owners in Southern Law-making," Working Paper Series of the Department of Economics, University of Konstanz 2020-03, Department of Economics, University of Konstanz.
    61. Hidalgo, Javier & Schafgans, Marcia, 2021. "Inference without smoothing for large panels with cross-sectional and temporal dependence," LSE Research Online Documents on Economics 107426, London School of Economics and Political Science, LSE Library.
    62. Jung, Yeonha, 2020. "The long reach of cotton in the US South: Tenant farming, mechanization, and low-skill manufacturing," Journal of Development Economics, Elsevier, vol. 143(C).
    63. Matz Dahlberg & Karin Edmark & Heléne Lundqvist, 2011. "Ethnic Diversity and Preferences for Redistribution," Working Papers 2011/2, Institut d'Economia de Barcelona (IEB).
    64. Previtero, Alessandro, 2014. "Stock market returns and annuitization," Journal of Financial Economics, Elsevier, vol. 113(2), pages 202-214.
    65. Rho, Seunghwa & Vogelsang, Timothy J., 2021. "Inference in time series models using smoothed-clustered standard errors," Journal of Econometrics, Elsevier, vol. 224(1), pages 113-133.
    66. Frank Davenport, 2017. "Estimating standard errors in spatial panel models with time varying spatial correlation," Papers in Regional Science, Wiley Blackwell, vol. 96, pages 155-177, March.
    67. Ng Cheuk Fai, 2022. "Robust Inference in High Dimensional Linear Model with Cluster Dependence," Papers 2212.05554, arXiv.org.
    68. Sun, Yixiao, 2013. "Fixed-smoothing Asymptotics in a Two-step GMM Framework," University of California at San Diego, Economics Working Paper Series qt64x4z265, Department of Economics, UC San Diego.
    69. James G. MacKinnon & Matthew D. Webb, 2015. "Wild Bootstrap Inference For Wildly Different Cluster Sizes," Working Paper 1314, Economics Department, Queen's University.
    70. Sun, Yixiao, 2014. "Let’s fix it: Fixed-b asymptotics versus small-b asymptotics in heteroskedasticity and autocorrelation robust inference," Journal of Econometrics, Elsevier, vol. 178(P3), pages 659-677.
    71. Samuel Bazzi & Martin Fiszbein & Mesay Gebresilasse, 2020. "Frontier Culture: The Roots and Persistence of “Rugged Individualism” in the United States," Econometrica, Econometric Society, vol. 88(6), pages 2329-2368, November.
    72. Cory Koedel & Mark Ehlert & Michael Podgursky & Eric Parsons, 2012. "Teacher Preparation Programs and Teacher Quality: Are There Real Differences Across Programs?," Working Papers 1204, Department of Economics, University of Missouri, revised 13 Jul 2012.
    73. Hwang, Jungbin & Sun, Yixiao, 2018. "Should we go one step further? An accurate comparison of one-step and two-step procedures in a generalized method of moments framework," Journal of Econometrics, Elsevier, vol. 207(2), pages 381-405.
    74. Jingnan Zhang & Chengye Li & Junhui Wang, 2023. "A stochastic block Ising model for multi‐layer networks with inter‐layer dependence," Biometrics, The International Biometric Society, vol. 79(4), pages 3564-3573, December.
    75. Carl Müller-Crepon, 2022. "Local ethno-political polarization and election violence in majoritarian vs. proportional systems," Journal of Peace Research, Peace Research Institute Oslo, vol. 59(2), pages 242-258, March.
    76. Vogelsang, Timothy J., 2012. "Heteroskedasticity, autocorrelation, and spatial correlation robust inference in linear panel models with fixed-effects," Journal of Econometrics, Elsevier, vol. 166(2), pages 303-319.
    77. Bryan, Mark L. & Jenkins, Stephen P., 2013. "Regression Analysis of Country Effects Using Multilevel Data: A Cautionary Tale," IZA Discussion Papers 7583, Institute of Labor Economics (IZA).
    78. David Powell, 2017. "Inference with Correlated Clusters," Working Papers WR-1137-1, RAND Corporation.
    79. Dustan, Andrew & Ngo, Diana K.L., 2018. "Commuting to educational opportunity? School choice effects of mass transit expansion in Mexico City," Economics of Education Review, Elsevier, vol. 63(C), pages 116-133.
    80. Kelly, Morgan, 2020. "Understanding Persistence," CEPR Discussion Papers 15246, C.E.P.R. Discussion Papers.
    81. De Noni, Ivan & Orsi, Luigi & Belussi, Fiorenza, 2018. "The role of collaborative networks in supporting the innovation performances of lagging-behind European regions," Research Policy, Elsevier, vol. 47(1), pages 1-13.
    82. Ulrich K. Müller & Mark W. Watson, 2022. "Spatial Correlation Robust Inference," Econometrica, Econometric Society, vol. 90(6), pages 2901-2935, November.
    83. Kojevnikov, Denis & Song, Kyungchul, 2023. "Some impossibility results for inference with cluster dependence with large clusters," Journal of Econometrics, Elsevier, vol. 237(2).
    84. Hidalgo, Javier & Schafgans, Marcia, 2017. "Inference and testing breaks in large dynamic panels with strong cross sectional dependence," LSE Research Online Documents on Economics 68839, London School of Economics and Political Science, LSE Library.
    85. Thomas Barrios & Rebecca Diamond & Guido W. Imbens & Michal Kolesar, 2010. "Clustering, Spatial Correlations and Randomization Inference," NBER Working Papers 15760, National Bureau of Economic Research, Inc.
    86. Andreas Hagemann, 2020. "Inference with a single treated cluster," Papers 2010.04076, arXiv.org.
    87. Carolina Caetano & Gregorio Caetano & Hao Fe & Eric R. Nielsen, 2021. "A Dummy Test of Identification in Models with Bunching," Finance and Economics Discussion Series 2021-068, Board of Governors of the Federal Reserve System (U.S.).
    88. James G. MacKinnon & Morten {O}rregaard Nielsen & Matthew D. Webb, 2023. "Testing for the appropriate level of clustering in linear regression models," Papers 2301.04522, arXiv.org, revised Mar 2023.
    89. Andreas Hagemann, 2017. "Cluster-Robust Bootstrap Inference in Quantile Regression Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 446-456, January.
    90. Jungbin Hwang, 2017. "Simple and Trustworthy Cluster-Robust GMM Inference," Working papers 2017-19, University of Connecticut, Department of Economics, revised Aug 2020.
    91. Wang, Wenjie, 2021. "Wild Bootstrap for Instrumental Variables Regression with Weak Instruments and Few Clusters," MPRA Paper 106227, University Library of Munich, Germany.
    92. Zhang, Xianyang, 2016. "Fixed-smoothing asymptotics in the generalized empirical likelihood estimation framework," Journal of Econometrics, Elsevier, vol. 193(1), pages 123-146.
    93. Ivan A. Canay & Andres Santos & Azeem M. Shaikh, 2018. "The wild bootstrap with a "small" number of "large" clusters," CeMMAP working papers CWP27/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    94. James G. MacKinnon, 2019. "How cluster-robust inference is changing applied econometrics," Working Paper 1413, Economics Department, Queen's University.
    95. Nick Obradovich, 2017. "Climate change may speed democratic turnover," Climatic Change, Springer, vol. 140(2), pages 135-147, January.
    96. Andreas Hagemann, 2019. "Permutation inference with a finite number of heterogeneous clusters," Papers 1907.01049, arXiv.org, revised Feb 2023.
    97. Denis Kojevnikov & Kyungchul Song, 2021. "Some Impossibility Results for Inference With Cluster Dependence with Large Clusters," Papers 2109.03971, arXiv.org, revised Jun 2023.
    98. Nafisa Halim & Kathryn Yount & Solveig Cunningham & Rohini Pande, 2016. "Women’s Political Empowerment and Investments in Primary Schooling in India," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 125(3), pages 813-851, February.
    99. Hwang, Jungbin, 2021. "Simple and trustworthy cluster-robust GMM inference," Journal of Econometrics, Elsevier, vol. 222(2), pages 993-1023.
    100. Hoyt Bleakley & Jeffrey Lin, 2011. "Portage and path dependence," Working Papers 11-38, Federal Reserve Bank of Philadelphia.
    101. Michael P. Leung, 2023. "Network Cluster‐Robust Inference," Econometrica, Econometric Society, vol. 91(2), pages 641-667, March.
    102. Anna Gloria Billé & Roberto Benedetti & Paolo Postiglione, 2017. "A two-step approach to account for unobserved spatial heterogeneity," Spatial Economic Analysis, Taylor & Francis Journals, vol. 12(4), pages 452-471, October.
    103. Wenjie Wang & Yichong Zhang, 2021. "Wild Bootstrap for Instrumental Variables Regressions with Weak and Few Clusters," Papers 2108.13707, arXiv.org, revised Jan 2024.
    104. Aman Ullah & Tao Wang & Weixin Yao, 2022. "Nonlinear Modal Regression for Dependent Data with Application for Predicting COVID-19," Working Papers 202207, University of California at Riverside, Department of Economics.
    105. Joanne Haddad, 2022. "Settlers and Norms," Working Papers ECARES 2022-02, ULB -- Universite Libre de Bruxelles.
    106. Hidalgo, Javier & Schafgans, Marcia M. A., 2017. "Inference without smoothing for large panels with cross-sectional and temporal dependence," LSE Research Online Documents on Economics 87748, London School of Economics and Political Science, LSE Library.
    107. Moscone, F. & Tosetti, Elisa, 2015. "Robust estimation under error cross section dependence," Economics Letters, Elsevier, vol. 133(C), pages 100-104.
    108. James G. MacKinnon & Matthew D. Webb, 2020. "When and How to Deal with Clustered Errors in Regression Models," Working Paper 1421, Economics Department, Queen's University.
    109. Javier Hidalgo & Marcia M Schafgans, 2017. "Inference Without Smoothing for Large Panels with Cross- Sectional and Temporal Dependence," STICERD - Econometrics Paper Series 597, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    110. Moscone, Francesco & Tosetti, Elisa, 2012. "HAC estimation in spatial panels," Economics Letters, Elsevier, vol. 117(1), pages 60-65.
    111. Hidalgo, Javier & Schafgans, Marcia, 2021. "Inference without smoothing for large panels with cross-sectional and temporal dependence," Journal of Econometrics, Elsevier, vol. 223(1), pages 125-160.
    112. Daniel L. Chen, 2015. "Can markets stimulate rights? On the alienability of legal claims," RAND Journal of Economics, RAND Corporation, vol. 46(1), pages 23-65, March.
    113. Hendricks, Nathan P. & Smith, Aaron D., 2012. "Comparing the Bias of Dynamic Panel Estimators in Multilevel Panels: Individual versus Grouped Data," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124548, Agricultural and Applied Economics Association.
    114. Antoine A. Djogbenou & James G. MacKinnon & Morten Ø. Nielsen, 2017. "Validity Of Wild Bootstrap Inference With Clustered Errors," Working Paper 1383, Economics Department, Queen's University.
    115. Jan David Bakker & Stephan Maurer & Jörn-Steffen Pischke & Ferdinand Rauch, 2021. "Of Mice and Merchants: Connectedness and the Location of Economic Activity in the Iron Age," The Review of Economics and Statistics, MIT Press, vol. 103(4), pages 652-665, October.
    116. Ulrich K. Muller & Mark W. Watson, 2021. "Spatial Correlation Robust Inference," Papers 2102.09353, arXiv.org.
    117. Yong Cai, 2021. "A Modified Randomization Test for the Level of Clustering," Papers 2105.01008, arXiv.org, revised Jan 2022.
    118. Andreas Hagemann, 2023. "Inference on quantile processes with a finite number of clusters," Papers 2301.04687, arXiv.org, revised Jun 2023.
    119. Laurent Davezies & Xavier D'Haultfoeuille & Yannick Guyonvarch, 2018. "Asymptotic results under multiway clustering," Papers 1807.07925, arXiv.org, revised Aug 2018.
    120. Pakel, Cavit, 2019. "Bias reduction in nonlinear and dynamic panels in the presence of cross-section dependence," Journal of Econometrics, Elsevier, vol. 213(2), pages 459-492.
    121. Martin Fiszbein, 2017. "Agricultural Diversity, Structural Change and Long-run Development: Evidence from the U.S," NBER Working Papers 23183, National Bureau of Economic Research, Inc.

  2. Bester, C. Alan & Hansen, Christian, 2009. "Identification of Marginal Effects in a Nonparametric Correlated Random Effects Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 235-250.

    Cited by:

    1. Brantly Callaway & Tong Li, 2019. "Quantile treatment effects in difference in differences models with panel data," Quantitative Economics, Econometric Society, vol. 10(4), pages 1579-1618, November.
    2. Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur, 2016. "Inference in High-Dimensional Panel Models With an Application to Gun Control," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 590-605, October.
    3. 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.
    4. Victor Chernozhukov & Ivan Fernandez-Val & Stefan Hoderlein & Hajo Holzmann & Whitney K. Newey, 2013. "Nonparametric identification in panels using quantiles," CeMMAP working papers 66/13, Institute for Fiscal Studies.
    5. 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.
    6. Cavit Pakel & Martin Weidner, 2023. "Bounds on Average Effects in Discrete Choice Panel Data Models," Papers 2309.09299, arXiv.org, revised May 2024.
    7. Khan, Shakeeb & Ponomareva, Maria & Tamer, Elie, 2016. "Identification of panel data models with endogenous censoring," Journal of Econometrics, Elsevier, vol. 194(1), pages 57-75.
    8. Ghanem, Dalia & Hirshleifer, Sarojini & Ortiz-Becerra, Karen, 2019. "Testing Attrition Bias in Field Experiments," 2019 Annual Meeting, July 21-23, Atlanta, Georgia 291215, Agricultural and Applied Economics Association.
    9. Ghanem, Dalia, 2017. "Testing identifying assumptions in nonseparable panel data models," Journal of Econometrics, Elsevier, vol. 197(2), pages 202-217.
    10. Čížek, Pavel & Lei, Jinghua, 2018. "Identification and estimation of nonseparable single-index models in panel data with correlated random effects," Journal of Econometrics, Elsevier, vol. 203(1), pages 113-128.
    11. Hoderlein, Stefan & White, Halbert, 2012. "Nonparametric identification in nonseparable panel data models with generalized fixed effects," Journal of Econometrics, Elsevier, vol. 168(2), pages 300-314.
    12. Stefan Hoderlein & Yuya Sasaki, 2011. "On the role of time in nonseparable panel data models," CeMMAP working papers CWP15/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Gregory Connor & Oliver Linton & Matthias Hagmann, 2007. "Efficient Estimation of a Semiparametric Characteristic-Based Factor Model of Security Returns," FMG Discussion Papers dp599, Financial Markets Group.
    14. Dalia Ghanem & Pedro H. C. Sant'Anna & Kaspar Wuthrich, 2022. "Selection and parallel trends," Papers 2203.09001, arXiv.org, revised Mar 2024.
    15. Chen, Songnian & Wang, Xi, 2018. "Semiparametric estimation of panel data models without monotonicity or separability," Journal of Econometrics, Elsevier, vol. 206(2), pages 515-530.
    16. Bester, C. Alan & Hansen, Christian B., 2016. "Grouped effects estimators in fixed effects models," Journal of Econometrics, Elsevier, vol. 190(1), pages 197-208.
    17. Juan Rodriguez-Poo & Alexandra Soberón, 2015. "Differencing techniques in semi-parametric panel data varying coefficient models with fixed effects: a Monte Carlo study," Computational Statistics, Springer, vol. 30(3), pages 885-906, September.
    18. Louise Laage, 2020. "A Correlated Random Coefficient Panel Model with Time-Varying Endogeneity," Papers 2003.09367, arXiv.org, revised Nov 2022.
    19. Chen, Mingli, 2016. "Estimation of Nonlinear Panel Models with Multiple Unobserved Effects," The Warwick Economics Research Paper Series (TWERPS) 1120, University of Warwick, Department of Economics.
    20. Bryan S. Graham & James Powell, 2008. "Identification and Estimation of 'Irregular' Correlated Random Coefficient Models," NBER Working Papers 14469, National Bureau of Economic Research, Inc.
    21. Lu, Xun & White, Habert, 2015. "Testing For Treatment Dependence Of Effects Of A Continuous Treatment," Econometric Theory, Cambridge University Press, vol. 31(5), pages 1016-1053, October.
    22. Evgeniy M. Ozhegov & Daria Teterina, 2018. "The Ensemble Method For Censored Demand Prediction," HSE Working papers WP BRP 200/EC/2018, National Research University Higher School of Economics.
    23. Laura Liu & Alexandre Poirier & Ji-Liang Shiu, 2021. "Identification and Estimation of Partial Effects in Nonlinear Semiparametric Panel Models," Papers 2105.12891, arXiv.org, revised Jul 2024.
    24. Sarojini Hirshleifer & Dalia Ghanem & Karen Ortiz-Becerra, 2019. "Testing for Attrition Bias in Field Experiments," Working Papers 201919, University of California at Riverside, Department of Economics, revised Aug 2019.
    25. Lu, Xun & White, Halbert, 2014. "Testing for separability in structural equations," Journal of Econometrics, Elsevier, vol. 182(1), pages 14-26.
    26. Sadikoglu, Serhan, 2019. "Essays in econometric theory," Other publications TiSEM 99d83644-f9dc-49e3-a4e1-5, Tilburg University, School of Economics and Management.
    27. Amaresh K Tiwari, 2021. "A Control Function Approach to Estimate Panel Data Binary Response Model," Papers 2102.12927, arXiv.org, revised Sep 2021.
    28. Irene Botosaru & Chris Muris, 2022. "Identification of time-varying counterfactual parameters in nonlinear panel models," Papers 2212.09193, arXiv.org, revised Nov 2023.

  3. Bester, C. Alan & Hansen, Christian, 2009. "A Penalty Function Approach to Bias Reduction in Nonlinear Panel Models with Fixed Effects," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 131-148.

    Cited by:

    1. Geert Dhaene & Koen Jochmans, 2011. "Profile-score Adjustements for Nonlinearfixed-effect Models," SciencePo Working papers Main hal-01073733, HAL.
    2. Jesus M. Carro & Alejandra Traferri, 2014. "State Dependence And Heterogeneity In Health Using A Bias‐Corrected Fixed‐Effects Estimator," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(2), pages 181-207, March.
    3. Lamarche, Carlos & Parker, Thomas, 2023. "Wild bootstrap inference for penalized quantile regression for longitudinal data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1799-1826.
    4. Ivan Fernandez-Val & Martin Weidner, 2018. "Fixed effect estimation of large T panel data models," CeMMAP working papers CWP22/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Manuel Arellano & Stéphane Bonhomme, 2009. "Robust Priors in Nonlinear Panel Data Models," Econometrica, Econometric Society, vol. 77(2), pages 489-536, March.
    6. Geert Dhaene & Koen Jochmans, 2015. "Split-panel jackknife estimation of fixed-effect models," Post-Print hal-03392997, HAL.
    7. Vasilis Sarafidis & Tom Wansbeek, 2020. "Celebrating 40 Years of Panel Data Analysis: Past, Present and Future," Monash Econometrics and Business Statistics Working Papers 6/20, Monash University, Department of Econometrics and Business Statistics.
    8. Dhaene, Geert & Sun, Yutao, 2021. "Second-order corrected likelihood for nonlinear panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 220(2), pages 227-252.
    9. Kunz, Johannes S. & Staub, Kevin E. & Winkelmann, Rainer, 2017. "Estimating Fixed Effects: Perfect Prediction and Bias in Binary Response Panel Models, with an Application to the Hospital Readmissions Reduction Program," IZA Discussion Papers 11182, Institute of Labor Economics (IZA).
    10. Lee, Yoonseok & Phillips, Peter C.B., 2015. "Model selection in the presence of incidental parameters," Journal of Econometrics, Elsevier, vol. 188(2), pages 474-489.
    11. F. Bartolucci & R. Bellio & A. Salvan & N. Sartori, 2016. "Modified Profile Likelihood for Fixed-Effects Panel Data Models," Econometric Reviews, Taylor & Francis Journals, vol. 35(7), pages 1271-1289, August.
    12. Čížek, Pavel & Lei, Jinghua, 2018. "Identification and estimation of nonseparable single-index models in panel data with correlated random effects," Journal of Econometrics, Elsevier, vol. 203(1), pages 113-128.
    13. Laura Hospido, 2007. "Modelling Heterogeneity and Dynamics in the Volatility of Individual Wages," Working Papers wp2007_0717, CEMFI.
    14. Sun, Yixiao & Kim, Min Seong, 2009. "k-step Bootstrap Bias Correction for Fixed Effects Estimators in Nonlinear Panel Models," University of California at San Diego, Economics Working Paper Series qt9gn6n5mr, Department of Economics, UC San Diego.
    15. Patrick GAGLIARDINI & Christian GOURIEROUX, 2010. "Efficiency in Large Dynamic Panel Models with Common Factor," Working Papers 2010-05, Center for Research in Economics and Statistics.
    16. Francesco Bartolucci & Francesco Valentini & Claudia Pigini, 2023. "Recursive Computation of the Conditional Probability Function of the Quadratic Exponential Model for Binary Panel Data," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 529-557, February.
    17. Amrei Stammann, 2023. "Debiased Fixed Effects Estimation of Binary Logit Models with Three-Dimensional Panel Data," Papers 2311.04073, arXiv.org.
    18. William Greene, 2014. "Models for ordered choices," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 15, pages 333-362, Edward Elgar Publishing.
    19. Geert Dhaene & Koen Jochmans, 2016. "Likelihood Inference in an Autoregression with Fixed Effects," Post-Print hal-03391995, HAL.
    20. Johannes S. Kunz & Kevin E. Staub & Rainer Winkelmann, 2021. "Predicting Individual Effects in Fixed Effects Panel Probit Models," SoDa Laboratories Working Paper Series 2021-05, Monash University, SoDa Laboratories.
    21. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    22. Yongsung Chang & Sunoong Hwang, 2011. "Asymmetric Phase Shifts in the U.S. Industrial Production Cycles," RCER Working Papers 564, University of Rochester - Center for Economic Research (RCER).
    23. Alexander Chudik & M. Hashem Pesaran & Jui‐Chung Yang, 2018. "Half‐panel jackknife fixed‐effects estimation of linear panels with weakly exogenous regressors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(6), pages 816-836, September.
    24. Schumann, Martin & Severini, Thomas A. & Tripathi, Gautam, 2021. "Integrated likelihood based inference for nonlinear panel data models with unobserved effects," Journal of Econometrics, Elsevier, vol. 223(1), pages 73-95.
    25. Xiaokun Wang & Kara M. Kockelman, 2009. "Baysian Inference For Ordered Response Data With A Dynamic Spatial‐Ordered Probit Model," Journal of Regional Science, Wiley Blackwell, vol. 49(5), pages 877-913, December.
    26. Albarrán, Pedro, 2015. "Estimation of Dynamic Nonlinear Random Effects Models with Unbalanced Panels," UC3M Working papers. Economics we1503, Universidad Carlos III de Madrid. Departamento de Economía.
    27. Yoshitsugu Kitazawa, 2017. "DFEL-RTN, a set of TSP programs for root-N consistent estimations of dynamic fixed effects logit models," Discussion Papers 81, Kyushu Sangyo University, Faculty of Economics.
    28. Laura Hospido, 2011. "Estimating non-linear models with multiple fixed effects:a computational note," Working Papers 1114, Banco de España.
    29. Francesco Bartolucci & Claudia Pigini & Francesco Valentini, 2023. "Conditional inference and bias reduction for partial effects estimation of fixed-effects logit models," Empirical Economics, Springer, vol. 64(5), pages 2257-2290, May.
    30. Galvao, Antonio F. & Gu, Jiaying & Volgushev, Stanislav, 2020. "On the unbiased asymptotic normality of quantile regression with fixed effects," Journal of Econometrics, Elsevier, vol. 218(1), pages 178-215.
    31. Galvao Jr., Antonio F., 2011. "Quantile regression for dynamic panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 164(1), pages 142-157, September.
    32. Bester, C. Alan & Hansen, Christian B., 2016. "Grouped effects estimators in fixed effects models," Journal of Econometrics, Elsevier, vol. 190(1), pages 197-208.
    33. Johannes S. Kunz & Kevin E. Staub & Rainer Winkelmann, 2019. "Predicting fixed effects in panel probit models," Monash Economics Working Papers 10-19, Monash University, Department of Economics.
    34. Maurice J.G. Bun & Martin A. Carree & Artūras Juodis, 2017. "On Maximum Likelihood Estimation of Dynamic Panel Data Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(4), pages 463-494, August.
    35. Galvao Jr, A. F. & Montes-Rojas, G., 2009. "Instrumental variables quantile regression for panel data with measurement errors," Working Papers 09/06, Department of Economics, City University London.
    36. Guangjie Li, 2015. "Consistency in Estimation and Model Selection of Dynamic Panel Data Models with Fixed Effects," Econometrics, MDPI, vol. 3(3), pages 1-31, July.
    37. Vladimir Filimonov & Guilherme Demos & Didier Sornette, 2016. "Modified Profile Likelihood Inference and Interval Forecast of the Burst of Financial Bubbles," Swiss Finance Institute Research Paper Series 16-12, Swiss Finance Institute.
    38. Traferri, Alejandra, 2009. "Correcting the bias in the estimation of a dynamic ordered probit with fixed effects of self-assessed health status," UC3M Working papers. Economics we094021, Universidad Carlos III de Madrid. Departamento de Economía.
    39. Trushin, Eshref & Ugur, Mehmet, 2018. "Ecosystem complexity, firm learning and survival: UK evidence on intra-industry age and size diversity as exit hazards," Greenwich Papers in Political Economy 19095, University of Greenwich, Greenwich Political Economy Research Centre.
    40. Lee, Yoonseok, 2012. "Bias in dynamic panel models under time series misspecification," Journal of Econometrics, Elsevier, vol. 169(1), pages 54-60.
    41. Buchmueller, Thomas C. & Cheng, Terence C. & Pham, Ngoc T.A. & Staub, Kevin E., 2021. "The effect of income-based mandates on the demand for private hospital insurance and its dynamics," Journal of Health Economics, Elsevier, vol. 75(C).
    42. Nini, Greg & Smith, David C. & Sufi, Amir, 2009. "Creditor control rights and firm investment policy," Journal of Financial Economics, Elsevier, vol. 92(3), pages 400-420, June.
    43. Yoshitsugu Kitazawa, 2013. "Exploration of dynamic fixed effects logit models from a traditional angle," Discussion Papers 60, Kyushu Sangyo University, Faculty of Economics.
    44. Pakel, Cavit, 2019. "Bias reduction in nonlinear and dynamic panels in the presence of cross-section dependence," Journal of Econometrics, Elsevier, vol. 213(2), pages 459-492.
    45. Amaresh Tiwari & Franz Palm, 2011. "Nonlinear Panel Data Models with Expected a Posteriori Values of Correlated Random Effects," CREPP Working Papers 1113, Centre de Recherche en Economie Publique et de la Population (CREPP) (Research Center on Public and Population Economics) HEC-Management School, University of Liège.

  4. Lori L. Leachman & Guillermo Rosas & Peter Lange & Alan Bester, 2007. "The Political Economy Of Budget Deficits," Economics and Politics, Wiley Blackwell, vol. 19(3), pages 369-420, November.

    Cited by:

    1. Attiya Y. Javid & Umaima Arif & Asma Arif, 2011. "Economic, Political and Institutional Determinants of Budget Deficits Volatility in Selected Asian Countries," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 50(4), pages 649-662.
    2. Agnello, Luca & Sousa, Ricardo M., 2009. "The determinants of public deficit volatility," Working Paper Series 1042, European Central Bank.
    3. Cicatiello, Lorenzo & De Simone, Elina & Gaeta, Giuseppe Lucio, 2016. "Political determinants of fiscal transparency: a panel data empirical investigation," MPRA Paper 72609, University Library of Munich, Germany.
    4. Luca Agnello & Ricardo M. Sousa, 2013. "Political, Institutional, and Economic Factors Underlying Deficit Volatility," Review of International Economics, Wiley Blackwell, vol. 21(4), pages 719-732, September.
    5. Tevdovski, Dragan & Jolakoski, Petar & Stojkoski, Viktor, 2021. "Determinants of budget deficits: Focus on the effects from the COVID-19 crisis," MPRA Paper 108056, University Library of Munich, Germany.
    6. Asma Arif & Mujahid Hussain, 2018. "Economic, Political and Institutional Determinants of Budget Deficits Volatility: A Panel Data Analysis," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(3), pages 98-114.
    7. Luca Agnello & Ricardo M. Sousa, 2014. "The Determinants of the Volatility of Fiscal Policy Discretion," Fiscal Studies, Institute for Fiscal Studies, vol. 35, pages 91-115, March.
    8. Dragan Tevdovski & Petar Jolakoski & Viktor Stojkoski, 2022. "Determinants Of Budget Deficits: The Effects Of The Covid-19 Crisis," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 67(232), pages 105-126, January –.
    9. Ringa Raudla, 2010. "Governing budgetary commons: what can we learn from Elinor Ostrom?," European Journal of Law and Economics, Springer, vol. 30(3), pages 201-221, December.
    10. Berggren, Niclas & Bjørnskov, Christian, 2018. "Regulation and Government Debt," Working Paper Series 1239, Research Institute of Industrial Economics.
    11. Hyungon Kim & Chang Kwon, 2015. "The Effects of Fiscal Consolidation and Welfare Composition of Spending on Electoral Outcomes: Evidence from US Gubernatorial Elections between 1978 and 2006," New Political Economy, Taylor & Francis Journals, vol. 20(2), pages 228-253, April.
    12. Garnov & A. & Zvyagin & L. & Sviridova & O., 2019. "System Data Analysis: Innovative Technologies, Methods and Techniques," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(Special 1), pages 26-39.
    13. Kapitsinis, Nikolaos & Metaxas, Theodore, 2011. "Economic crisis and the role of state policies in current globalized economy. The case of Greece," MPRA Paper 43650, University Library of Munich, Germany.

  5. Lori Leachman & Alan Bester & Guillermo Rosas & Peter Lange, 2005. "Multicointegration and Sustainability of Fiscal Practices," Economic Inquiry, Western Economic Association International, vol. 43(2), pages 454-466, April.

    Cited by:

    1. Hualde, Javier, 2014. "Estimation of long-run parameters in unbalanced cointegration," Journal of Econometrics, Elsevier, vol. 178(2), pages 761-778.
    2. Triches, Divanildo & Sleimann Bertussi, Luis Antônio, 2017. "Multicointegração e sustentabilidade da política fiscal no Brasil com regime de quebras estruturais (1997-2015)," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 71(3), September.
    3. Kia, Amir, 2008. "Fiscal sustainability in emerging countries: Evidence from Iran and Turkey," Journal of Policy Modeling, Elsevier, vol. 30(6), pages 957-972.
    4. Javier Gómez Biscarri & Javier Hualde, 2014. "A Residual-Based ADF Test for Stationary Cointegration in I (2) Settings," Working Papers 779, Barcelona School of Economics.
    5. Ayla Ogus & Niloufer Sohrabji, 2008. "On the optimality and sustainability of Turkey’s current account," Empirical Economics, Springer, vol. 35(3), pages 543-568, November.
    6. Hui, Hon Chung, 2013. "Fiscal sustainability in Malaysia: a re-examination," MPRA Paper 80018, University Library of Munich, Germany.
    7. Chen, Shyh-Wei & Wu, An-Chi, 2018. "Is there a bubble component in government debt? New international evidence," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 467-486.
    8. Regina Escario & Mar�a Dolores Gadea & Marcela Sabat�, 2009. "Government Solvency or just Pseudo-Sustainability? a Long-Run Multicointegration Approach for Spain," Documentos de Trabajo dt2009-07, Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza.
    9. Chen, Shyh-Wei, 2014. "Testing for fiscal sustainability: New evidence from the G-7 and some European countries," Economic Modelling, Elsevier, vol. 37(C), pages 1-15.
    10. Gerrit B. Koester & Christoph Priesmeier, 2013. "Does Wagner´s Law Ruin the Sustainability of German Public Finances?," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, vol. 69(3), pages 256-288, September.
    11. Gabriella Deborah Legrenzi & Costas Milas, 2010. "Spend-and-Tax Adjustments and the Sustainability of the Government's Intertemporal Budget Constraint," CESifo Working Paper Series 2926, CESifo.
    12. Cysne, Rubens Penha & Campos, Eduardo Lima, 2019. "Sustainability of the Brazilian public pebt an analysis using multicointegration," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 805, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    13. Campos, Eduardo Lima & Cysne, Rubens Penha, 2019. "Sustainability of Brazilian public debt: analysis of a possible structural break in the recent period," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 806, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    14. Demiralp, Berna & Gantt, Bonnie B. & Selover, David D., 2011. "Modeling unemployment as an inventory: A multicointegration approach," Journal of Macroeconomics, Elsevier, vol. 33(4), pages 724-737.
    15. Escario, Regina & Gadea, María Dolores & Sabaté, Marcela, 2012. "Multicointegration, seigniorage and fiscal sustainability. Spain 1857–2000," Journal of Policy Modeling, Elsevier, vol. 34(2), pages 270-283.

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