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Citations for "Consistent Estimation with a Large Number of Weak Instruments"

by John C. Chao & Norman Rasmus Swanson

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  1. Anderson, T.W. & Kunitomo, Naoto & Matsushita, Yukitoshi, 2010. "On the asymptotic optimality of the LIML estimator with possibly many instruments," Journal of Econometrics, Elsevier, vol. 157(2), pages 191-204, August.
  2. Ribeiro, André L.P. & Hotta, Luiz K., 2013. "An analysis of contagion among Asian countries using the canonical model of contagion," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 62-69.
  3. George Kapetanios & Massimiliano Marcellino, 2006. "Factor-GMM Estimation with Large Sets of Possibly Weak Instruments," Working Papers 577, Queen Mary University of London, School of Economics and Finance.
  4. Cattaneo, Matias D. & Crump, Richard K. & Jansson, Michael, 2012. "Optimal inference for instrumental variables regression with non-Gaussian errors," Journal of Econometrics, Elsevier, vol. 167(1), pages 1-15.
  5. Frondel, Manuel & Vance, Colin, 2013. "Fuel Taxes versus Efficiency Standards – An Instrumental Variable Approach," Ruhr Economic Papers 445, Rheinisch-Westfälisches Institut für Wirtschaftsforschung (RWI), Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
  6. Antonio Ciccone & Giovanni Peri, 2003. "Skills’ Substitutability and Technological Progress: U.S. States 1950-1990," CESifo Working Paper Series 1024, CESifo Group Munich.
  7. Xu Cheng & Zhipeng Liao, 2012. "Select the Valid and Relevant Moments: A One-Step Procedure for GMM with Many Moments," PIER Working Paper Archive 12-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  8. Annamaria Conti & Jerry Thursby & Marie C. Thursby, 2013. "Patents as Signals for Startup Financing," NBER Working Papers 19191, National Bureau of Economic Research, Inc.
  9. John Chao & Norman Swanson, 2004. "Estimation and Testing Using Jackknife IV in Heteroskedastic Regressions With Many Weak Instruments," Departmental Working Papers 200420, Rutgers University, Department of Economics.
  10. Alessandro Gambini & Alberto Zazzaro, 2013. "Long-lasting bank relationships and growth of firms," Small Business Economics, Springer, vol. 40(4), pages 977-1007, May.
  11. Florens, Jean-Pierre & Van Bellegem, Sébastien, 2015. "Instrumental variable estimation in functional linear models," Journal of Econometrics, Elsevier, vol. 186(2), pages 465-476.
  12. Balan, David J. & Knack, Stephen, 2011. "The correlation between human capital and morality and its effect on economic performance : theory and evidence," Policy Research Working Paper Series 5720, The World Bank.
  13. Van Bellegem, Sébastien & Florens, Jean-Pierre, 2014. "Instrumental variable estimation in functional linear models," CORE Discussion Papers 2014056, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  14. Maurice J.G. Bun & Frank Windmeijer, 2011. "A Comparison of Bias Approximations for the 2SLS Estimator," Tinbergen Institute Discussion Papers 11-088/4, Tinbergen Institute.
  15. Antonio Ciccone & Giovanni Peri, 2005. "Long-Run Substitutability Between More and Less Educated Workers: Evidence from U.S. States, 1950-1990," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 652-663, November.
  16. Chao, John C. & Swanson, Norman R. & Hausman, Jerry A. & Newey, Whitney K. & Woutersen, Tiemen, 2012. "Asymptotic Distribution Of Jive In A Heteroskedastic Iv Regression With Many Instruments," Econometric Theory, Cambridge University Press, vol. 28(01), pages 42-86, February.
  17. repec:rwi:repape:0445 is not listed on IDEAS
  18. Forchini, Giovanni, 2010. "The Asymptotic Distribution Of The Liml Estimator In A Partially Identified Structural Equation," Econometric Theory, Cambridge University Press, vol. 26(03), pages 917-930, June.
  19. Hansen, Christian & Kozbur, Damian, 2014. "Instrumental variables estimation with many weak instruments using regularized JIVE," Journal of Econometrics, Elsevier, vol. 182(2), pages 290-308.
  20. Naoto Kunitomo, 2012. "An optimal modification of the LIML estimation for many instruments and persistent heteroscedasticity," Annals of the Institute of Statistical Mathematics, Springer, vol. 64(5), pages 881-910, October.
  21. Carrasco, Marine & Tchuente, Guy, 2015. "Regularized LIML for many instruments," Journal of Econometrics, Elsevier, vol. 186(2), pages 427-442.
  22. Poskitt, D.S. & Skeels, C.L., 2007. "Approximating the distribution of the two-stage least squares estimator when the concentration parameter is small," Journal of Econometrics, Elsevier, vol. 139(1), pages 217-236, July.
  23. Chao, John C. & Hausman, Jerry A. & Newey, Whitney K. & Swanson, Norman R. & Woutersen, Tiemen, 2014. "Testing overidentifying restrictions with many instruments and heteroskedasticity," Journal of Econometrics, Elsevier, vol. 178(P1), pages 15-21.
  24. Peter C. B. Phillips & Chirok Han, 2004. "GMM with Many Moment Conditions," Econometric Society 2004 Far Eastern Meetings 525, Econometric Society.
  25. repec:wyi:journl:002148 is not listed on IDEAS
  26. Ackerberg, Daniel & Devereux, Paul J., 2008. "Improved JIVE Estimators for Overidentified Linear Models with and without Heteroskedasticity," CEPR Discussion Papers 6926, C.E.P.R. Discussion Papers.
  27. Liu, Xiaodong & Lee, Lung-fei, 2010. "GMM estimation of social interaction models with centrality," Journal of Econometrics, Elsevier, vol. 159(1), pages 99-115, November.
  28. D.S. Poskitt & C.L. Skeels, 2005. "Small Concentration Asymptotics and Instrumental Variables Inference," Department of Economics - Working Papers Series 948, The University of Melbourne.
  29. Kazuhiko Hayakawa, 2006. "Efficient GMM Estimation of Dynamic Panel Data Models Where Large Heterogeneity May Be Present," Hi-Stat Discussion Paper Series d05-130, Institute of Economic Research, Hitotsubashi University.
  30. Dobbelaere, Sabien, 2004. "Ownership, firm size and rent sharing in Bulgaria," Labour Economics, Elsevier, vol. 11(2), pages 165-189, April.
  31. Caner, Mehmet, 2014. "Near exogeneity and weak identification in generalized empirical likelihood estimators: Many moment asymptotics," Journal of Econometrics, Elsevier, vol. 182(2), pages 247-268.
  32. Givens, David, 2013. "Defining governance matters: A factor analytic assessment of governance institutions," Journal of Comparative Economics, Elsevier, vol. 41(4), pages 1026-1053.
  33. Liu, Hong & Zhao, Zhong, 2014. "Parental job loss and children's health: Ten years after the massive layoff of the SOEs' workers in China," China Economic Review, Elsevier, vol. 31(C), pages 303-319.
  34. Andreas Pick, 2007. "Financial contagion and tests using instrumental variables," DNB Working Papers 139, Netherlands Central Bank, Research Department.
  35. repec:wyi:journl:002137 is not listed on IDEAS
  36. Kapetanios, George & Marcellino, Massimiliano, 2010. "Cross-sectional averaging and instrumental variable estimation with many weak instruments," Economics Letters, Elsevier, vol. 108(1), pages 36-39, July.
  37. Christian Hansen & Jerry Hausman & Whitney Newey, 2006. "Estimation with many instrumental variables," CeMMAP working papers CWP19/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  38. P.A. Bekker & F. Crudu, 2013. "Jackknife Instrumental Variable Estimation with Heteroskedasticity," Working Paper CRENoS 201313, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
  39. Bun, Maurice J.G. & Windmeijer, Frank, 2011. "A comparison of bias approximations for the two-stage least squares (2SLS) estimator," Economics Letters, Elsevier, vol. 113(1), pages 76-79, October.
  40. Phillips, Peter C.B., 2014. "Optimal estimation of cointegrated systems with irrelevant instruments," Journal of Econometrics, Elsevier, vol. 178(P2), pages 210-224.
  41. Brick, Ivan E. & Palia, Darius, 2007. "Evidence of jointness in the terms of relationship lending," Journal of Financial Intermediation, Elsevier, vol. 16(3), pages 452-476, July.
  42. James H. Stock & Motohiro Yogo, 2002. "Testing for Weak Instruments in Linear IV Regression," NBER Technical Working Papers 0284, National Bureau of Economic Research, Inc.
  43. Anatolyev, Stanislav & Gospodinov, Nikolay, 2011. "Specification Testing In Models With Many Instruments," Econometric Theory, Cambridge University Press, vol. 27(02), pages 427-441, April.
  44. Arel-Bundock, Vincent, 2013. "A solution to the weak instrument bias in 2SLS estimation: Indirect inference with stochastic approximation," Economics Letters, Elsevier, vol. 120(3), pages 495-498.
  45. Yoonseok Lee & Ryo Okui, 2009. "A Specification Test for Instrumental Variables Regression with Many Instruments," Cowles Foundation Discussion Papers 1741, Cowles Foundation for Research in Economics, Yale University.
  46. Martins, Luis F. & Gabriel, Vasco J., 2014. "Linear instrumental variables model averaging estimation," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 709-724.
  47. Sonia Laszlo, 2003. "Education, Labour Supply and Market Development in Rural Peru," Development and Comp Systems 0312005, EconWPA.
  48. J. Ginger Meng & Gang Hu & Jushan Bai, 2011. "Olive: A Simple Method For Estimating Betas When Factors Are Measured With Error," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 34(1), pages 27-60, 03.
  49. John C. Chao & Norman Rasmus Swanson, 2004. "Consistent Estimation with a Large Number of Weak Instruments," Yale School of Management Working Papers ysm374, Yale School of Management.
  50. Guay, Alain & Guerre, Emmanuel & Lazarová, Štěpána, 2013. "Robust adaptive rate-optimal testing for the white noise hypothesis," Journal of Econometrics, Elsevier, vol. 176(2), pages 134-145.
  51. Channing Arndt & Sam Jones & Finn Tarp, 2009. "Aid and Growth: Have We Come Full Circle?," Working Paper Series WIDER Discussion Paper 20, World Institute for Development Economic Research (UNU-WIDER).
  52. Wenjie Wang, 2012. "Bootstrapping Anderson-Rubin Statistic and J Statistic in Linear IV Models with Many Instruments," KIER Working Papers 810, Kyoto University, Institute of Economic Research.
  53. Caner, Mehmet & Yıldız, Neşe, 2012. "CUE with many weak instruments and nearly singular design," Journal of Econometrics, Elsevier, vol. 170(2), pages 422-441.
  54. D. S. Poskitt & C. L. Skeels, 2004. "Approximating the Distribution of the Instrumental Variables Estimator when the Concentration Parameter is Small," Monash Econometrics and Business Statistics Working Papers 19/04, Monash University, Department of Econometrics and Business Statistics.
  55. Lee, Lung-fei & Yu, Jihai, 2014. "Efficient GMM estimation of spatial dynamic panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 180(2), pages 174-197.
  56. Menzel, Konrad, 2014. "Consistent estimation with many moment inequalities," Journal of Econometrics, Elsevier, vol. 182(2), pages 329-350.
  57. Stanislav Anatolyev, 2007. "Inference about predictive ability when there are many predictors," Working Papers w0096, Center for Economic and Financial Research (CEFIR).
  58. Zongwu Cai & Ying Fang, 2013. "Reducing the Asymptotic Bias of Weak Instruments Estimation Using Independently Repeated Cross-sectional Information," Papers 2013-10-14, Working Paper.
  59. Mehmet Caner, 2005. "Near Exogeneity and Weak Identification in Generalized Empirical Likelihood Estimators: Fixed and Many Moment Asymptotics," Econometrics 0509018, EconWPA.
  60. Whitney Newey & Frank Windmeijer, 2005. "GMM with many weak moment conditions," CeMMAP working papers CWP18/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  61. Cizek, P., 2009. "Generalized Methods of Trimmed Moments," Discussion Paper 2009-25, Tilburg University, Center for Economic Research.
  62. Guggenberger, Patrik & Ramalho, Joaquim J.S. & Smith, Richard J., 2012. "GEL statistics under weak identification," Journal of Econometrics, Elsevier, vol. 170(2), pages 331-349.
  63. Maurice J.G. Bun & Frank Windmeijer, 2011. "A Comparison of Bias Approximations for the 2SLS Estimator," Tinbergen Institute Discussion Papers 11-088/4, Tinbergen Institute.
  64. Liu, Xiaodong, 2012. "On the consistency of the LIML estimator of a spatial autoregressive model with many instruments," Economics Letters, Elsevier, vol. 116(3), pages 472-475.
  65. Eriksen, Michael D., 2010. "Homeownership subsidies and the marriage decisions of low-income households," Regional Science and Urban Economics, Elsevier, vol. 40(6), pages 490-497, November.
  66. Cai, Zongwu & Fang, Ying & Su, Jia, 2012. "Reducing asymptotic bias of weak instrumental estimation using independently repeated cross-sectional information," Statistics & Probability Letters, Elsevier, vol. 82(1), pages 180-185.
  67. Mehmet Caner, 2005. "Higher Order Expansions in GMM with Nearly Weak and Many Nearly Weak Instruments," Working Papers 209, University of Pittsburgh, Department of Economics, revised Jan 2005.
  68. Phillips, Peter C.B., 2003. "Vision And Influence In Econometrics: John Denis Sargan," Econometric Theory, Cambridge University Press, vol. 19(03), pages 495-511, June.
  69. John C. Chao & Norman R. Swanson, 2003. "Asymptotic Normality of Single-Equation Estimators for the Case with a Large Number of Weak Instruments," Departmental Working Papers 200312, Rutgers University, Department of Economics.
  70. Guggenberger, Patrik & Smith, Richard J., 2008. "Generalized empirical likelihood tests in time series models with potential identification failure," Journal of Econometrics, Elsevier, vol. 142(1), pages 134-161, January.
  71. Doko Tchatoka, Firmin Sabro & Dufour, Jean-Marie, 2008. "Instrument endogeneity and identification-robust tests: some analytical results," MPRA Paper 29613, University Library of Munich, Germany.
  72. Michal Kolesár & Raj Chetty & John N. Friedman & Edward L. Glaeser & Guido W. Imbens, 2011. "Identification and Inference with Many Invalid Instruments," NBER Working Papers 17519, National Bureau of Economic Research, Inc.
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.