Political Science Research Paper Topics 2014 Toyota

Personal Details

First Name:Taisuke
Middle Name:
Last Name:Otsu
Suffix:
RePEc Short-ID:pot36
[This author has chosen not to make the email address public]
http://personal.lse.ac.uk/otsu/
Terminal Degree:2004 Economics Department; University of Wisconsin-Madison (from RePEc Genealogy)

Affiliation

Economics Department
London School of Economics (LSE)

London, United Kingdom
http://econ.lse.ac.uk/

: +44 (0)20 7955 7545
+44 (0)20 7831 1840
Houghton Street, London WC2A 2AE
RePEc:edi:edlseuk (more details at EDIRC)

Research output

Jump to: Working papersArticles

Working papers

  1. Taisuke Otsu & Chen Qiu, 2018. "Information theoretic approach to high dimensional multiplicative models: Stochastic discount factor and treatment effect," STICERD - Econometrics Paper Series 595, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  2. Karun Adusumilli & Taisuke Otsu & Yoon-Jae Whang, 2017. "Inference on distribution functions under measurement error," STICERD - Econometrics Paper Series 594, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  3. 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.
  4. Lorenzo Camponovo & Taisuke Otsu, 2017. "Relative error accurate statistic based on nonparametric likelihood," STICERD - Econometrics Paper Series 593, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  5. Yukitoshi Matsushita & Taisuke Otsu, 2017. "Likelihood inference on semiparametric models: Average derivative and treatment effect," STICERD - Econometrics Paper Series 592, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  6. Lorenzo Camponovo & Yukitoshi Matsushita & Taisuke Otsu, 2017. "Empirical likelihood for high frequency data," STICERD - Econometrics Paper Series 591, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  7. Yukitoshi Matsushita & Taisuke Otsu, 2016. "Likelihood inference on semiparametric models with generated regressors," STICERD - Econometrics Paper Series 587, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  8. Myung Hwan Seo & Taisuke Otsu, 2016. "Local M-estimation with discontinuous criterion for dependent and limited observations," STICERD - Econometrics Paper Series /589, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  9. Taisuke Otsu & Luke Taylor, 2016. "Specification testing for errors-in-variables models," STICERD - Econometrics Paper Series /2015/586, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  10. Taisuke Otsu & Yoshiyasu Rai, 2015. "Bootstrap inference of matching estimators for average treatment effects," STICERD - Econometrics Paper Series /2015/580, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  11. Taisuke Otsu & Martin Pesendorfer & Yuya Takahashi, 2015. "Pooling data across markets in dynamic Markov games," STICERD - Econometrics Paper Series /2015/582, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  12. Lorenzo Camponovo & Yukitoshi Matsushita & Taisuke Otsu, 2015. "Nonparametric likelihood for volatility under high frequency data," STICERD - Econometrics Paper Series /2015/581, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  13. Karun Adusumilli & Taisuke Otsu, 2015. "Nonparametric instrumental regression with errors in variables," STICERD - Econometrics Paper Series /2015/585, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  14. Adusumilli, Karun & Otsu, Taisuke, 2014. "Empirical likelihood for random sets," LSE Research Online Documents on Economics 58064, London School of Economics and Political Science, LSE Library.
  15. Taisuke Otsu & Myung Hwan Seo, 2014. "Asymptotics for maximum score method under general conditions," STICERD - Econometrics Paper Series 571, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  16. Taisuke Otsu & Luke Taylor, 2014. "Estimation of Nonseparable Models with Censored Dependent Variables and Endogenous Regressors," STICERD - Econometrics Paper Series 575, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  17. Kirill Evdokimov & Yuichi Kitamura & Taisuke Otsu, 2014. "Robust estimation of moment condition models with weakly dependent data," STICERD - Econometrics Paper Series 579, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  18. Otsu, Taisuke & Pesendorfer, Martin & Takahashi, Yuya, 2014. "Testing Equilibrium Multiplicity in Dynamic Games," CEPR Discussion Papers 10111, C.E.P.R. Discussion Papers.
  19. 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.
  20. Otsu, Taisuke & Xu, Ke-Li & Matsushita, Yukitoshi, 2013. "Estimation and inference of discontinuity in density," LSE Research Online Documents on Economics 85878, London School of Economics and Political Science, LSE Library.
  21. Otsu, Taisuke & Pesendorfer, Martin & Takahashi, Yuya, 2013. "Testing for Equilibrium Multiplicity in Dynamic Markov Games," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 423, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
  22. Taisuke Otsu, 2011. "Empirical Likelihood for Nonparametric Additive Models," Cowles Foundation Discussion Papers 1792, Cowles Foundation for Research in Economics, Yale University.
  23. Taisuke Otsu, 2011. "Moderate Deviations of Generalized Method of Moments and Empirical Likelihood Estimators," Cowles Foundation Discussion Papers 1785, Cowles Foundation for Research in Economics, Yale University.
  24. Ivan Canay & Taisuke Otsu, 2011. "Hodges-Lehmann Optimality for Testing Moment," Cowles Foundation Discussion Papers 1789, Cowles Foundation for Research in Economics, Yale University.
  25. Yukitoshi Matsushita & Taisuke Otsu, 2011. "Second-order Refinement of Empirical Likelihood for Testing Overidentifying Restrictions," Cowles Foundation Discussion Papers 1791, Cowles Foundation for Research in Economics, Yale University, revised Jan 2012.
  26. Taisuke Otsu, 2011. "Large Deviations of Generalized Method of Moments and Empirical Likelihood Estimators," Cowles Foundation Discussion Papers 1783, Cowles Foundation for Research in Economics, Yale University.
  27. Shin Kanaya & Taisuke Otsu, 2011. "Large Deviations of Realized Volatility," Cowles Foundation Discussion Papers 1798, Cowles Foundation for Research in Economics, Yale University.
  28. Lorenzo Camponovo & Taisuke Otsu, 2011. "Breakdown Point Theory for Implied Probability Bootstrap," Cowles Foundation Discussion Papers 1793, Cowles Foundation for Research in Economics, Yale University.
  29. Francesco Bravo & Juan Carlos Escanciano & Taisuke Otsu, 2011. "A Simple Test for Identification in GMM under Conditional Moment Restrictions," Cowles Foundation Discussion Papers 1789, Cowles Foundation for Research in Economics, Yale University.
  30. Taisuke Otsu & Ke-Li Xu, 2011. "Empirical Likelihood for Regression Discontinuity Design," Cowles Foundation Discussion Papers 1799, Cowles Foundation for Research in Economics, Yale University.
    • Otsu, Taisuke & Xu, Ke-Li & Matsushita, Yukitoshi, 2015. "Empirical likelihood for regression discontinuity design," LSE Research Online Documents on Economics 58513, London School of Economics and Political Science, LSE Library.
    • Yukitoshi Matsushita & Taisuke Otsu & Ke-Li Xu, 2014. "Empirical Likelihood for Regression Discontinuity Design," STICERD - Econometrics Paper Series 573, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    • Otsu, Taisuke & Matsushita, Yukitoshi & Xu, Ke-Li, 2014. "Empirical likelihood for regression discontinuity design," LSE Research Online Documents on Economics 58065, London School of Economics and Political Science, LSE Library.
  31. Lorenzo Camponovo & Taisuke Otsu, 2011. "Robustness of Bootstrap in Instrumental Variable Regression," Cowles Foundation Discussion Papers 1796, Cowles Foundation for Research in Economics, Yale University.
    • Camponovo, Lorenzo & Otsu, Taisuke, 2015. "Robustness of bootstrap in instrumental variable regression," LSE Research Online Documents on Economics 60185, London School of Economics and Political Science, LSE Library.
    • Camponovo, Lorenzo & Otsu, Taisuke, 2014. "Robustness of bootstrap in instrumental variable regression," LSE Research Online Documents on Economics 58185, London School of Economics and Political Science, LSE Library.
    • Lorenzo Camponovo & Taisuke Otsu, 2014. "Robustness of bootstrap in instrumental variable regression," STICERD - Econometrics Paper Series 572, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  32. Lorenzo Camponovo & Taisuke Otsu, 2011. "On Bartlett Correctability of Empirical Likelihood in Generalized Power Divergence Family," Cowles Foundation Discussion Papers 1825, Cowles Foundation for Research in Economics, Yale University.
  33. Yuichi Kitamura & Taisuke Otsu & Kirill Evdokimov, 2009. "Robustness, Infinitesimal Neighborhoods, and Moment Restrictions," Cowles Foundation Discussion Papers 1720, Cowles Foundation for Research in Economics, Yale University.
  34. Vadim Marmer & Taisuke Otsu, 2009. "Optimal Comparison of Misspecified Moment Restriction Models under a Chosen Measure of Fit," Cowles Foundation Discussion Papers 1724, Cowles Foundation for Research in Economics, Yale University, revised Jul 2011.
  35. Joseph G. Altonji & Hidehiko Ichimura & Taisuke Otsu, 2008. "Estimating Derivatives in Nonseparable Models with Limited Dependent Variables," CIRJE F-Series CIRJE-F-574, CIRJE, Faculty of Economics, University of Tokyo.
    • Joseph G. Altonji & Hidehiko Ichimura & Taisuke Otsu, 2008. "Estimating Derivatives in Nonseparable Models with Limited Dependent Variables," Cowles Foundation Discussion Papers 1668R, Cowles Foundation for Research in Economics, Yale University, revised May 2011.
    • Joseph Altonji & Hidehiko Ichimura & Taisuke Otsu, 2008. "Estimating derivatives in nonseparable models with limited dependent variables," CeMMAP working papers CWP20/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Joseph G. Altonji & Hidehiko Ichimura & Taisuke Otsu, 2008. "Estimating Derivatives in Nonseparable Models with Limited Dependent Variables," NBER Working Papers 14161, National Bureau of Economic Research, Inc.
    • Joseph G. Altonji & Hidehiko Ichimura & Taisuke Otsu, 2008. "Estimating Derivatives in Nonseparable Models with Limited Dependent Variables," Cowles Foundation Discussion Papers 1668, Cowles Foundation for Research in Economics, Yale University.
  36. Taisuke Otsu & Myung Hwan Seo & Yoon-Jae Whang, 2008. "Testing for Non-Nested Conditional Moment Restrictions Using Unconditional Empirical Likelihood," Cowles Foundation Discussion Papers 1660, Cowles Foundation for Research in Economics, Yale University.
  37. Nikolay Gospodinov & Taisuke Otsu, 2008. "Local GMM Estimation of Time Series Models with Conditional Moment Restrictions," Working Papers 08010, Concordia University, Department of Economics.
  38. Taisuke Otsu & Yoon-Jae Whang, 2005. "Testing for Non-nested Conditional Moment Retrictions via Conditional Empirical Likelihood," Cowles Foundation Discussion Papers 1533, Cowles Foundation for Research in Economics, Yale University.

Articles

  1. Karun Adusumilli & Taisuke Otsu, 2017. "Empirical Likelihood for Random Sets," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1064-1075, July.
    • Adusumilli, Karun & Otsu, Taisuke, 2014. "Empirical likelihood for random sets," LSE Research Online Documents on Economics 58064, London School of Economics and Political Science, LSE Library.
    • Karun Adusumilli & Taisuke Otsu, 2014. "Empirical Likelihood for Random Sets," STICERD - Econometrics Paper Series 574, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  2. Taisuke Otsu & Martin Pesendorfer & Yuya Takahashi, 2016. "Pooling data across markets in dynamic Markov games," Quantitative Economics, Econometric Society, vol. 7(2), pages 523-559, July.
    • Taisuke Otsu & Martin Pesendorfer & Yuya Takahashi, 2015. "Pooling data across markets in dynamic Markov games," STICERD - Econometrics Paper Series /2015/582, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    • Otsu, Taisuke & Pesendorfer, Martin & Takahashi, Yuya, 2016. "Pooling data across markets in dynamic Markov games," LSE Research Online Documents on Economics 66182, London School of Economics and Political Science, LSE Library.
  3. Otsu, Taisuke & Xu, Ke-Li & Matsushita, Yukitoshi, 2015. "Empirical likelihood for regression discontinuity design," Journal of Econometrics, Elsevier, vol. 186(1), pages 94-112.
    • Taisuke Otsu & Ke-Li Xu, 2011. "Empirical Likelihood for Regression Discontinuity Design," Cowles Foundation Discussion Papers 1799, Cowles Foundation for Research in Economics, Yale University.
    • Otsu, Taisuke & Xu, Ke-Li & Matsushita, Yukitoshi, 2015. "Empirical likelihood for regression discontinuity design," LSE Research Online Documents on Economics 58513, London School of Economics and Political Science, LSE Library.
    • Yukitoshi Matsushita & Taisuke Otsu & Ke-Li Xu, 2014. "Empirical Likelihood for Regression Discontinuity Design," STICERD - Econometrics Paper Series 573, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    • Otsu, Taisuke & Matsushita, Yukitoshi & Xu, Ke-Li, 2014. "Empirical likelihood for regression discontinuity design," LSE Research Online Documents on Economics 58065, London School of Economics and Political Science, LSE Library.
  4. Lorenzo Camponovo & Taisuke Otsu, 2015. "Robustness of Bootstrap in Instrumental Variable Regression," Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 352-393, March.
    • Camponovo, Lorenzo & Otsu, Taisuke, 2015. "Robustness of bootstrap in instrumental variable regression," LSE Research Online Documents on Economics 60185, London School of Economics and Political Science, LSE Library.
    • Lorenzo Camponovo & Taisuke Otsu, 2011. "Robustness of Bootstrap in Instrumental Variable Regression," Cowles Foundation Discussion Papers 1796, Cowles Foundation for Research in Economics, Yale University.
    • Camponovo, Lorenzo & Otsu, Taisuke, 2014. "Robustness of bootstrap in instrumental variable regression," LSE Research Online Documents on Economics 58185, London School of Economics and Political Science, LSE Library.
    • Lorenzo Camponovo & Taisuke Otsu, 2014. "Robustness of bootstrap in instrumental variable regression," STICERD - Econometrics Paper Series 572, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  5. Camponovo, Lorenzo & Otsu, Taisuke, 2014. "On Bartlett correctability of empirical likelihood in generalized power divergence family," Statistics & Probability Letters, Elsevier, vol. 86(C), pages 38-43.
    • Camponovo, Lorenzo & Otsu, Taisuke, 2014. "On Bartlett correctability of empirical likelihood in generalized power divergence family," LSE Research Online Documents on Economics 55597, London School of Economics and Political Science, LSE Library.
    • Lorenzo Camponovo & Taisuke Otsu, 2011. "On Bartlett Correctability of Empirical Likelihood in Generalized Power Divergence Family," Cowles Foundation Discussion Papers 1825, Cowles Foundation for Research in Economics, Yale University.
  6. Rai, Yoshiyasu & Otsu, Taisuke, 2013. "On testability of complementarity in models with multiple equilibria," Economics Letters, Elsevier, vol. 120(1), pages 79-82.
  7. Yuichi Kitamura & Taisuke Otsu & Kirill Evdokimov, 2013. "Robustness, Infinitesimal Neighborhoods, and Moment Restrictions," Econometrica, Econometric Society, vol. 81(3), pages 1185-1201, May.
  8. Taisuke Otsu & Ke-Li Xu & Yukitoshi Matsushita, 2013. "Estimation and Inference of Discontinuity in Density," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(4), pages 507-524, October.
  9. Matsushita, Yukitoshi & Otsu, Taisuke, 2013. "Second-Order Refinement Of Empirical Likelihood For Testing Overidentifying Restrictions," Econometric Theory, Cambridge University Press, vol. 29(02), pages 324-353, April.
  10. Joseph G. Altonji & Hidehiko Ichimura & Taisuke Otsu, 2012. "Estimating Derivatives in Nonseparable Models With Limited Dependent Variables," Econometrica, Econometric Society, vol. 80(4), pages 1701-1719, July.
    • Joseph G. Altonji & Hidehiko Ichimura & Taisuke Otsu, 2008. "Estimating Derivatives in Nonseparable Models with Limited Dependent Variables," Cowles Foundation Discussion Papers 1668R, Cowles Foundation for Research in Economics, Yale University, revised May 2011.
    • Joseph Altonji & Hidehiko Ichimura & Taisuke Otsu, 2008. "Estimating derivatives in nonseparable models with limited dependent variables," CeMMAP working papers CWP20/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Joseph G. Altonji & Hidehiko Ichimura & Taisuke Otsu, 2008. "Estimating Derivatives in Nonseparable Models with Limited Dependent Variables," NBER Working Papers 14161, National Bureau of Economic Research, Inc.
    • Joseph G. Altonji & Hidehiko Ichimura & Taisuke Otsu, 2008. "Estimating Derivatives in Nonseparable Models with Limited Dependent Variables," CIRJE F-Series CIRJE-F-574, CIRJE, Faculty of Economics, University of Tokyo.
    • Joseph G. Altonji & Hidehiko Ichimura & Taisuke Otsu, 2008. "Estimating Derivatives in Nonseparable Models with Limited Dependent Variables," Cowles Foundation Discussion Papers 1668, Cowles Foundation for Research in Economics, Yale University.
  11. Kanaya, Shin & Otsu, Taisuke, 2012. "Large deviations of realized volatility," Stochastic Processes and their Applications, Elsevier, vol. 122(2), pages 546-581.
  12. Canay, Ivan A. & Otsu, Taisuke, 2012. "Hodges–Lehmann optimality for testing moment conditions," Journal of Econometrics, Elsevier, vol. 171(1), pages 45-53.
  13. Lorenzo Camponovo & Taisuke Otsu, 2012. "Breakdown point theory for implied probability bootstrap," Econometrics Journal, Royal Economic Society, vol. 15(1), pages 32-55, February.
  14. Marmer, Vadim & Otsu, Taisuke, 2012. "Optimal comparison of misspecified moment restriction models under a chosen measure of fit," Journal of Econometrics, Elsevier, vol. 170(2), pages 538-550.
    • Marmer, Vadim & Otsu, Taisuke, 2008. "Optimal Comparison of Misspecified Moment Restriction Models under a Chosen Measure of Fit," Microeconomics.ca working papers vadim_marmer-2008-13, Vancouver School of Economics, revised 25 Jul 2011.
    • Vadim Marmer & Taisuke Otsu, 2009. "Optimal Comparison of Misspecified Moment Restriction Models under a Chosen Measure of Fit," Cowles Foundation Discussion Papers 1724, Cowles Foundation for Research in Economics, Yale University, revised Jul 2011.
  15. Otsu, Taisuke & Seo, Myung Hwan & Whang, Yoon-Jae, 2012. "Testing for non-nested conditional moment restrictions using unconditional empirical likelihood," Journal of Econometrics, Elsevier, vol. 167(2), pages 370-382.
  16. Gospodinov, Nikolay & Otsu, Taisuke, 2012. "Local GMM estimation of time series models with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 170(2), pages 476-490.
  17. Otsu, Taisuke & Whang, Yoon-Jae, 2011. "Testing For Nonnested Conditional Moment Restrictions Via Conditional Empirical Likelihood," Econometric Theory, Cambridge University Press, vol. 27(01), pages 114-153, February.
  18. Otsu, Taisuke, 2011. "Empirical Likelihood Estimation Of Conditional Moment Restriction Models With Unknown Functions," Econometric Theory, Cambridge University Press, vol. 27(01), pages 8-46, February.
  19. Taisuke Otsu, 2011. "Large deviations of generalized method of moments and empirical likelihood estimators," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 321-329, July.
  20. Otsu, Taisuke, 2011. "Moderate deviations of generalized method of moments and empirical likelihood estimators," Journal of Multivariate Analysis, Elsevier, vol. 102(8), pages 1203-1216, September.
  21. Otsu, Taisuke, 2010. "On Bahadur efficiency of empirical likelihood," Journal of Econometrics, Elsevier, vol. 157(2), pages 248-256, August.
  22. Taisuke Otsu, 2009. "RESET for quantile regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(2), pages 381-391, August.
  23. Taisuke Otsu, 2009. "Generalized Neyman–Pearson optimality of empirical likelihood for testing parameter hypotheses," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(4), pages 773-787, December.
  24. Otsu, Taisuke, 2008. "Large deviation asymptotics for statistical treatment rules," Economics Letters, Elsevier, vol. 101(1), pages 53-56, October.
  25. Otsu, Taisuke, 2008. "Conditional empirical likelihood estimation and inference for quantile regression models," Journal of Econometrics, Elsevier, vol. 142(1), pages 508-538, January.
  26. Otsu, Taisuke, 2007. "Penalized empirical likelihood estimation of semiparametric models," Journal of Multivariate Analysis, Elsevier, vol. 98(10), pages 1923-1954, November.
  27. Otsu, Taisuke, 2006. "MATRIX ALGEBRA, by Karim M. Abadir and Jan R. Magnus, Cambridge University Press, 2005," Econometric Theory, Cambridge University Press, vol. 22(05), pages 968-972, October.
  28. Otsu, Taisuke, 2006. "Generalized Empirical Likelihood Inference For Nonlinear And Time Series Models Under Weak Identification," Econometric Theory, Cambridge University Press, vol. 22(03), pages 513-527, June.
  29. Taisuke Otsu, 2004. "Effect of small-sample adjustments for Cox test under non-nested linear regression models," Economics Bulletin, AccessEcon, vol. 3(28), pages 1-4.

Citations

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

Working papers

  1. Yukitoshi Matsushita & Taisuke Otsu, 2016. "Likelihood inference on semiparametric models with generated regressors," STICERD - Econometrics Paper Series 587, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Yukitoshi Matsushita & Taisuke Otsu, 2017. "Likelihood inference on semiparametric models: Average derivative and treatment effect," STICERD - Econometrics Paper Series 592, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  2. Taisuke Otsu & Yoshiyasu Rai, 2015. "Bootstrap inference of matching estimators for average treatment effects," STICERD - Econometrics Paper Series /2015/580, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Huber, Martin & Camponovo, Lorenzo & Bodory, Hugo & Lechner, Michael, 2016. "A wild bootstrap algorithm for propensity score matching estimators," FSES Working Papers 470, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    2. Bodory, Hugo & Huber, Martin & Camponovo, Lorenzo & Lechner, Michael, 2016. "The finite sample performance of inference methods for propensity score matching and weighting estimators," FSES Working Papers 466, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
      • Bodory, Hugo & Camponovo, Lorenzo & Huber, Martin & Lechner, Michael, 2016. "The Finite Sample Performance of Inference Methods for Propensity Score Matching and Weighting Estimators," IZA Discussion Papers 9706, Institute for the Study of Labor (IZA).
      • Bodory, Hugo & Camponovo, Lorenzo & Huber, Martin & Lechner, Michael, 2016. "The finite sample performance of inference methods for propensity score matching and weighting estimators," Economics Working Paper Series 1604, University of St. Gallen, School of Economics and Political Science.
  3. Taisuke Otsu & Martin Pesendorfer & Yuya Takahashi, 2015. "Pooling data across markets in dynamic Markov games," STICERD - Econometrics Paper Series /2015/582, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Ruli Xiao, 2016. "Nonparametric Identification of Dynamic Games with Multiple Equilibria and Unobserved Heterogeneity," Caepr Working Papers 2016-002 Classification-C, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.
  4. Karun Adusumilli & Taisuke Otsu, 2015. "Nonparametric instrumental regression with errors in variables," STICERD - Econometrics Paper Series /2015/585, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Qiying Wang & Peter C.B. Phillips & Ioannis Kasparis, 2017. "Latent Variable Nonparametric Cointegrating Regression," Cowles Foundation Discussion Papers 3011, Cowles Foundation for Research in Economics, Yale University.
    2. Babii, Andrii, 2017. "Honest confidence sets in nonparametric IV regression and other ill-posed models," TSE Working Papers 17-803, Toulouse School of Economics (TSE).
  5. Adusumilli, Karun & Otsu, Taisuke, 2014. "Empirical likelihood for random sets," LSE Research Online Documents on Economics 58064, London School of Economics and Political Science, LSE Library.

    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.
      • Manganelli, Simone & White, Halbert & Kim, Tae-Hwan, 2015. "VAR for VaR: measuring tail dependence using multivariate regression quantiles," Working Paper Series 1814, European Central Bank.
      • White, Halbert & Kim, Tae-Hwan & Manganelli, Simone, 2015. "VAR for VaR: Measuring tail dependence using multivariate regression quantiles," Journal of Econometrics, Elsevier, vol. 187(1), pages 169-188.
    2. Yoon-Jae Whang, 2003. "Smoothed Empirical Likelihood Methods for Quantile Regression Models," Econometrics 0310005, EconWPA.
      • Yoon-Jae Whang, 2004. "Smoothed Empirical Likelihood Methods for Quantile Regression Models," Cowles Foundation Discussion Papers 1453, Cowles Foundation for Research in Economics, Yale University.
      • Whang, Yoon-Jae, 2006. "Smoothed Empirical Likelihood Methods For Quantile Regression Models," Econometric Theory, Cambridge University Press, vol. 22(02), pages 173-205, April.
    3. 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.
    4. Philip Kostov, 2013. "Empirical likelihood estimation of the spatial quantile regression," Journal of Geographical Systems, Springer, vol. 15(1), pages 51-69, January.
    5. 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.
  6. Kirill Evdokimov & Yuichi Kitamura & Taisuke Otsu, 2014. "Robust estimation of moment condition models with weakly dependent data," STICERD - Econometrics Paper Series 579, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Márcio Poletti Laurini & Luiz Koodi Hotta, 2016. "Generalized moment estimation of stochastic differential equations," Computational Statistics, Springer, vol. 31(3), pages 1169-1202, September.
  7. Otsu, Taisuke & Xu, Ke-Li & Matsushita, Yukitoshi, 2013. "Estimation and inference of discontinuity in density," LSE Research Online Documents on Economics 85878, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Ulrich Matter & Michaela Slotwinski, 2016. "Precise Control over Legislative Vote Outcomes: A Forensic Approach to Political Economics," CESifo Working Paper Series 6007, CESifo Group Munich.
    2. Jales, Hugo & Ma, Jun & Yu, Zhengfei, 2017. "Optimal bandwidth selection for local linear estimation of discontinuity in density," Economics Letters, Elsevier, vol. 153(C), pages 23-27.
    3. Schmidheiny, Kurt & Slotwinski, Michaela, 2015. "Behavioral Responses to Local Tax Rates: Quasi-Experimental Evidence from a Foreigners' Tax Scheme in Switzerland," CEPR Discussion Papers 10833, C.E.P.R. Discussion Papers.
    4. Eggers, Andrew C. & Freier, Ronny & Grembi, Veronica & Nannicini, Tommaso, 2015. "Regression Discontinuity Designs Based on Population Thresholds: Pitfalls and Solutions," IZA Discussion Papers 9553, Institute for the Study of Labor (IZA).
    5. Joshua D. Angrist & Victor Lavy & Jetson Leder-Luis & Adi Shany, 2017. "Maimonides Rule Redux," NBER Working Papers 23486, National Bureau of Economic Research, Inc.
    6. Xu, Ke-Li, 2017. "Regression discontinuity with categorical outcomes," Journal of Econometrics, Elsevier, vol. 201(1), pages 1-18.
    7. Jin-young Choi & Myoung-jae Lee, 2017. "Regression discontinuity: review with extensions," Statistical Papers, Springer, vol. 58(4), pages 1217-1246, December.
    8. Susan Athey & Guido W. Imbens, 2017. "The State of Applied Econometrics: Causality and Policy Evaluation," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 3-32, Spring.
  8. Otsu, Taisuke & Pesendorfer, Martin & Takahashi, Yuya, 2013. "Testing for Equilibrium Multiplicity in Dynamic Markov Games," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 423, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.

    Cited by:

    1. Hansen, Stephen & McMahon, Michael & Velasco Rivera, Carlos, 2014. "Preferences or private assessments on a monetary policy committee?," Journal of Monetary Economics, Elsevier, vol. 67(C), pages 16-32.
  9. Taisuke Otsu, 2011. "Moderate Deviations of Generalized Method of Moments and Empirical Likelihood Estimators," Cowles Foundation Discussion Papers 1785, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Seojeong Lee, 2015. "A Consistent Variance Estimator for 2SLS When Instruments Identify Different LATEs," Discussion Papers 2015-01, School of Economics, The University of New South Wales.
    2. Jiang, Hui & Wang, Shaochen, 2017. "Moderate deviation principles for classical likelihood ratio tests of high-dimensional normal distributions," Journal of Multivariate Analysis, Elsevier, vol. 156(C), pages 57-69.
    3. Seojeong Lee, 2013. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for Generalized Method of Moments Estimators," Discussion Papers 2013-09, School of Economics, The University of New South Wales.
  10. Yukitoshi Matsushita & Taisuke Otsu, 2011. "Second-order Refinement of Empirical Likelihood for Testing Overidentifying Restrictions," Cowles Foundation Discussion Papers 1791, Cowles Foundation for Research in Economics, Yale University, revised Jan 2012.

    Cited by:

    1. Parente, Paulo M.D.C. & Smith, Richard J., 2017. "Tests of additional conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 200(1), pages 1-16.
  11. Taisuke Otsu, 2011. "Large Deviations of Generalized Method of Moments and Empirical Likelihood Estimators," Cowles Foundation Discussion Papers 1783, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Jiang, Hui & Wang, Shaochen, 2017. "Moderate deviation principles for classical likelihood ratio tests of high-dimensional normal distributions," Journal of Multivariate Analysis, Elsevier, vol. 156(C), pages 57-69.
  12. Shin Kanaya & Taisuke Otsu, 2011. "Large Deviations of Realized Volatility," Cowles Foundation Discussion Papers 1798, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Hacène Djellout & Hui Jiang, 2017. "Large Deviations Of The Threshold Estimator Of Integrated (Co-)Volatility Vector In The Presence Of Jumps," Post-Print hal-01147189, HAL.
    2. Djellout, Hacène & Samoura, Yacouba, 2014. "Large and moderate deviations of realized covolatility," Statistics & Probability Letters, Elsevier, vol. 86(C), pages 30-37.
    3. Hacène Djellout & Arnaud Guillin & Yacouba Samoura, 2017. "Large Deviations Of The Realized (Co-)Volatility Vector," Post-Print hal-01082903, HAL.
  13. Lorenzo Camponovo & Taisuke Otsu, 2011. "Breakdown Point Theory for Implied Probability Bootstrap," Cowles Foundation Discussion Papers 1793, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Lorenzo Camponovo & Taisuke Otsu, 2015. "Robustness of Bootstrap in Instrumental Variable Regression," Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 352-393, March.
      • Camponovo, Lorenzo & Otsu, Taisuke, 2015. "Robustness of bootstrap in instrumental variable regression," LSE Research Online Documents on Economics 60185, London School of Economics and Political Science, LSE Library.
      • Lorenzo Camponovo & Taisuke Otsu, 2011. "Robustness of Bootstrap in Instrumental Variable Regression," Cowles Foundation Discussion Papers 1796, Cowles Foundation for Research in Economics, Yale University.
      • Camponovo, Lorenzo & Otsu, Taisuke, 2014. "Robustness of bootstrap in instrumental variable regression," LSE Research Online Documents on Economics 58185, London School of Economics and Political Science, LSE Library.
      • Lorenzo Camponovo & Taisuke Otsu, 2014. "Robustness of bootstrap in instrumental variable regression," STICERD - Econometrics Paper Series 572, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    2. Marc G. Genton & Peter Hall, 2016. "A tilting approach to ranking influence," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(1), pages 77-97, January.
    3. Ferrari, Davide & Zheng, Chao, 2016. "Reliable inference for complex models by discriminative composite likelihood estimation," Journal of Multivariate Analysis, Elsevier, vol. 144(C), pages 68-80.
  14. Francesco Bravo & Juan Carlos Escanciano & Taisuke Otsu, 2011. "A Simple Test for Identification in GMM under Conditional Moment Restrictions," Cowles Foundation Discussion Papers 1789, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Xiaohong Chen & David Jacho-Chávez & Oliver Linton, 2012. "Averaging of moment condition estimators," CeMMAP working papers CWP26/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  15. Taisuke Otsu & Ke-Li Xu, 2011. "Empirical Likelihood for Regression Discontinuity Design," Cowles Foundation Discussion Papers 1799, Cowles Foundation for Research in Economics, Yale University.
    • Otsu, Taisuke & Xu, Ke-Li & Matsushita, Yukitoshi, 2015. "Empirical likelihood for regression discontinuity design," LSE Research Online Documents on Economics 58513, London School of Economics and Political Science, LSE Library.
    • Yukitoshi Matsushita & Taisuke Otsu & Ke-Li Xu, 2014. "Empirical Likelihood for Regression Discontinuity Design," STICERD - Econometrics Paper Series 573, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    • Otsu, Taisuke & Matsushita, Yukitoshi & Xu, Ke-Li, 2014. "Empirical likelihood for regression discontinuity design," LSE Research Online Documents on Economics 58065, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Donna Feir & Thomas Lemieux & Vadim Marmer, 2016. "Weak Identification in Fuzzy Regression Discontinuity Designs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 185-196, April.
    2. Xu, Ke-Li, 2017. "Regression discontinuity with categorical outcomes," Journal of Econometrics, Elsevier, vol. 201(1), pages 1-18.
    3. Jin-young Choi & Myoung-jae Lee, 2017. "Regression discontinuity: review with extensions," Statistical Papers, Springer, vol. 58(4), pages 1217-1246, December.
  16. Lorenzo Camponovo & Taisuke Otsu, 2011. "On Bartlett Correctability of Empirical Likelihood in Generalized Power Divergence Family," Cowles Foundation Discussion Papers 1825, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Kun Chen & Ngai Hang Chan & Chun Yip Yau, 2016. "Bartlett Correction of Empirical Likelihood for Non-Gaussian Short-Memory Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(5), pages 624-649, September.
    2. Roberto Baragona & Francesco Battaglia & Domenico Cucina, 2017. "Empirical likelihood ratio in penalty form and the convex hull problem," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(4), pages 507-529, November.
    3. Nicola Lunardon & Gianfranco Adimari, 2016. "Second-order Accurate Confidence Regions Based on Members of the Generalized Power Divergence Family," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(1), pages 213-227, March.
  17. Yuichi Kitamura & Taisuke Otsu & Kirill Evdokimov, 2009. "Robustness, Infinitesimal Neighborhoods, and Moment Restrictions," Cowles Foundation Discussion Papers 1720, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Seojeong Lee, 2014. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for GEL Estimators," Discussion Papers 2014-02, School of Economics, The University of New South Wales.
    2. Pierre Chausse & George Luta, 2017. "Casual Inference using Generalized Empirical Likelihood Methods," Working Papers 1707, University of Waterloo, Department of Economics, revised Dec 2017.
    3. Lorenzo Camponovo & Taisuke Otsu, 2015. "Robustness of Bootstrap in Instrumental Variable Regression," Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 352-393, March.
      • Camponovo, Lorenzo & Otsu, Taisuke, 2015. "Robustness of bootstrap in instrumental variable regression," LSE Research Online Documents on Economics 60185, London School of Economics and Political Science, LSE Library.
      • Lorenzo Camponovo & Taisuke Otsu, 2011. "Robustness of Bootstrap in Instrumental Variable Regression," Cowles Foundation Discussion Papers 1796, Cowles Foundation for Research in Economics, Yale University.
      • Camponovo, Lorenzo & Otsu, Taisuke, 2014. "Robustness of bootstrap in instrumental variable regression," LSE Research Online Documents on Economics 58185, London School of Economics and Political Science, LSE Library.
      • Lorenzo Camponovo & Taisuke Otsu, 2014. "Robustness of bootstrap in instrumental variable regression," STICERD - Econometrics Paper Series 572, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    4. Komunjer, Ivana & Ragusa, Giuseppe, 2016. "Existence And Characterization Of Conditional Density Projections," Econometric Theory, Cambridge University Press, vol. 32(04), pages 947-987, August.
    5. Hill, Jonathan B., 2015. "Robust Generalized Empirical Likelihood for heavy tailed autoregressions with conditionally heteroscedastic errors," Journal of Multivariate Analysis, Elsevier, vol. 135(C), pages 131-152.
    6. Leal, Laura Simonsen & Almeida, Caio, 2017. "An SDF Approach to Hedge Funds' Tail Risk:Evidence from Brazilian Funds," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 37(1), May.
    7. Magnus, Jan R. & Vasnev, Andrey L., 2015. "Interpretation and use of sensitivity in econometrics, illustrated with forecast combinations," International Journal of Forecasting, Elsevier, vol. 31(3), pages 769-781.
    8. Márcio Poletti Laurini & Luiz Koodi Hotta, 2016. "Generalized moment estimation of stochastic differential equations," Computational Statistics, Springer, vol. 31(3), pages 1169-1202, September.
    9. René Garcia & Caio Almeida & Kym Ardison & Jose Vicente, 2016. "Nonparametric Tail Risk, Stock Returns and the Macroeconomy," CIRANO Working Papers 2016s-20, CIRANO.
      • Caio Almeida & Kym Ardison & René Garcia & Jose Vicente, 2017. "

One of the good things about academic associations is that they often invite students to participate in meaningful discussions about professional matters.

Such was the case at last month's Citadel Symposium on Southern Politics in Charleston, SC. Several undergraduates in political science courses at Florida Southern College and the College of Charleston presented papers about the South.

In this post, I will try to summarize what we learned from some of these presenters.

David Ahnen (College of Charleston): "The Prospects of Hispanic Mobilization in the South"

Ahnen posited that Hispanics certainly have the ability to transform the politics of the South. However, based on data from the American National Elections Study, he reported that the Hispanic electorate has not been swept off its collective feet by either political party and shows signs of political moderation.

I come to this conclusion for five key reasons: (1) the early success of Republicans with the Hispanic vote debunks the fallacy that Republicans are incapable of carrying the majority of Hispanics; (2) the stances that Hispanics take on issues align most accurately with self-identified Independents; (3) Hispanics' loose party association with the Democrats is arguably due to Republican's stance on immigration and proclamation as to make English as the primary language in the United States; (4) Hispanics remain very moderate in terms of ideology; and (5) the 2012 election results do not provide conclusive results as to imminent identification under either political party.

Katherine Curley (College of Charleston): "Southern Women, Social Identity and Political Involvement in the American South"

Curley's preliminary review of data from the 2011 Pew Research Center for the people and the press suggested that women in the South, in general, report less knowledge of politics than men; and it is not merely southern gender roles that prescribe this behavior.

Instead, I would now suppose that the women living in the South, whether they identify as southerners or not, are less likely to come in contact with political information and most likely have few political avenues available in which they pursue political knowledge, activism or leadership.

Branden Davis, Saga Moss Lundstrom and Madison Nickell (all Florida Southern College): "Education's Impact on the South's Economic Development"

Davis/Lundstrom/Nickell (shown in this photo during their presentation) set out to determine whether education spending was related to education outcomes and median income in the South.

They report that, based on U.S. Census Bureau data, they could find no identifiable relationship among these variables.

The reality of the situation is that while X dollars may be spent per pupil a year you cannot assume that all of the money is being used for educational purposes ... Therefore, we have concluded that our research does not support the idea that looking at the raw numbers of how much a state spends on education can reflect how well educated the state is... The current way of reviewing data to be able to determine how much a state spends in relation to the level of education they have is inconsistent and not applicable to the way educational spending is set up today.

Matthew Geras (Florida Southern College): "The Effects of the 17th Amendment on Voter Responsiveness"

Geras attempted to determine how adoption of the 17th Amendment (1913) -- mandating the direct, popular election of U.S. Senators -- affected turnout, with particular attention to differences between the South and non-South. He found this task very difficult, due to a combination of other political factors at play during the period of study and insufficient, inconsistent electoral data. He concluded that "there is no clear or indisputable evidence that it had much effect at all on voter turnout in the United States." He voiced common complaints among historical scholars: (1) the available historical election data that is readily available makes it very difficult to draw definitive conclusions about national turnout during that time period; and (2) additional research would have to be done on a state-by-state basis to get a handle on the issue of voter suppression and lower turnout in the South.

Jake Benoit and Carter Payne (both Florida Southern College): "A Conservative Storm: The Impacts of Hurricanes Katrina and Rita on Voting Patterns in Louisiana"

Payne and Benoit originally speculated that, given the large pre-storm and pro-Democratic African-American population of the city and the decrease in the population of New Orleans as a result of the hurricanes, there would have been a decrease in Democratic voters and an increase in Republican voters in Orleans Parish, as well as the other impacted parishes in Louisiana. However, some surprises emerged from their review of voter registration data obtained from the Louisiana Secretary of State:

No clear conclusions on the political impacts of Hurricanes Katrina and Rita can be drawn from our data. If anything, the political impacts of Hurricanes Katrina and Rita were a slight acceleration of a process which was already occurring... A decrease in Democrats, mostly in White Democrats, is clearly the current trend in Louisiana... This shift could have been slightly accelerated by the natural disasters of 2005, but little evidence exists to support such a claim.

Commentary

The work of these undergraduate students contributed substantively to our understanding of southern politics. Interestingly, too, they encountered the same kinds of frustrations and limitations faced by all of us in this area of inquiry. Sometimes we try to demonstrate something worthwhile about politics in this part of the country, only to discover that the data are insufficient to reach a clear conclusion. Their performance reflects well on them; and it is a testament to their professors. The Citadel Symposium also deserves a "thank you" for always involving student scholars in this program.

AUTHOR NOTE: This column is part of a series of posts about southern politics. These posts derive from the 2014 Citadel Symposium on Southern Politics, a gathering of regional specialists in historic Charleston, SC. This symposium has been held every-other-year since 1978; and it has become a "main event" for serious South-watchers from around the country. A hundred specialists -- representing scholars from about 50 academic institutions -- participated in the most recent conference, March 6-7, 2014. In this series, I will attempt to incorporate pertinent aspects of the presented papers and some of my own comments into various themes.

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