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Yong Bao

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.

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Yong Bao & Melody Lo & Franklin G. Mixon, 2010. "General-interest versus specialty journals: Using intellectual influence of econometrics research to rank economics journals and articles," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 345-353.

    Mentioned in:

    1. General-interest versus specialty journals: Using intellectual influence of econometrics research to rank economics journals and articles (Journal of Applied Econometrics 2010) in ReplicationWiki ()

Working papers

  1. Yong Bao & Aman Ullah, 2021. "Analytical Finite Sample Econometrics-from A.L.Nagar to Now," Working Papers 202114, University of California at Riverside, Department of Economics, revised Oct 2021.

    Cited by:

    1. Yong Bao & Aman Ullah, 2021. "The Special Issue in Honor of Anirudh Lal Nagar: An Introduction," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 1-8, December.

  2. Aman Ullah & Yong Bao & Ru Zhang, 2014. "Moment Approximation for Unit Root Models with Nonnormal Errors," Working Papers 201401, University of California at Riverside, Department of Economics.

    Cited by:

    1. Yong Bao & Aman Ullah, 2021. "Analytical Finite Sample Econometrics: From A. L. Nagar to Now," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 17-37, December.

  3. Yong Bao & Aman Ullah & Yun Wang & Jun Yu, 2013. "Bias in the Mean Reversion Estimator in Continuous-Time Gaussian and Lévy Processes," Working Papers 02-2013, Singapore Management University, School of Economics.

    Cited by:

    1. Bao, Yong & Ullah, Aman & Wang, Yun & Yu, Jun, 2015. "Bias in the estimation of mean reversion in continuous-time Lévy processes," Economics Letters, Elsevier, vol. 134(C), pages 16-19.
    2. Iglesias, Emma M., 2014. "Testing of the mean reversion parameter in continuous time models," Economics Letters, Elsevier, vol. 122(2), pages 187-189.

Articles

  1. Yong Bao & Aman Ullah, 2021. "Analytical Finite Sample Econometrics: From A. L. Nagar to Now," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 17-37, December.
    See citations under working paper version above.
  2. Yong Bao, 2021. "Indirect Inference Estimation of a First-Order Dynamic Panel Data Model," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 79-98, December.

    Cited by:

    1. Yong Bao & Aman Ullah, 2021. "The Special Issue in Honor of Anirudh Lal Nagar: An Introduction," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 1-8, December.
    2. Chen, Weihao & Cizek, Pavel, 2023. "Bias-Corrected Instrumental Variable Estimation in Linear Dynamic Panel Data Models," Other publications TiSEM 9bf2c16c-522f-4223-8037-c, Tilburg University, School of Economics and Management.
    3. Chen, Weihao & Cizek, Pavel, 2023. "Bias-Corrected Instrumental Variable Estimation in Linear Dynamic Panel Data Models," Discussion Paper 2023-028, Tilburg University, Center for Economic Research.

  3. Yong Bao & Xiaotian Liu & Lihong Yang, 2020. "Indirect Inference Estimation of Spatial Autoregressions," Econometrics, MDPI, vol. 8(3), pages 1-26, September.

    Cited by:

    1. Rossi, Francesca & Robinson, Peter M., 2023. "Higher-order least squares inference for spatial autoregressions," Journal of Econometrics, Elsevier, vol. 232(1), pages 244-269.

  4. Yong Bao, 2018. "The asymptotic covariance matrix of the QMLE in ARMA models," Econometric Reviews, Taylor & Francis Journals, vol. 37(4), pages 309-324, April.

    Cited by:

    1. Eric Beutner & Alexander Heinemann & Stephan Smeekes, 2019. "A General Framework for Prediction in Time Series Models," Papers 1902.01622, arXiv.org.
    2. Norkutė, Milda & Westerlund, Joakim, 2019. "The factor analytical method for interactive effects dynamic panel models with moving average errors," Econometrics and Statistics, Elsevier, vol. 11(C), pages 83-104.

  5. Yong Bao & Aman Ullah & Yun Wang, 2017. "Distribution of the mean reversion estimator in the Ornstein–Uhlenbeck process," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 1039-1056, October.

    Cited by:

    1. Zi‐Yi Guo, 2021. "Out‐of‐sample performance of bias‐corrected estimators for diffusion processes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 243-268, March.
    2. Yong Bao & Xiaotian Liu & Aman Ullah, 2020. "On the Exact Statistical Distribution of Econometric Estimators and Test Statistics," Working Papers 202014, University of California at Riverside, Department of Economics, revised Jun 2020.
    3. Yiu Lim Lui & Weilin Xiao & Jun Yu, 2022. "The Grid Bootstrap for Continuous Time Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1390-1402, June.
    4. Emma M. Iglesias & Garry D. A. Phillips, 2020. "Further Results on Pseudo‐Maximum Likelihood Estimation and Testing in the Constant Elasticity of Variance Continuous Time Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(2), pages 357-364, March.
    5. Jianghao Chu & Tae-Hwy Lee & Aman Ullah & Haifeng Xu, 2020. "Exact Distribution of the F-statistic under Heteroskedasticity of Unknown Form for Improved Inference," Working Papers 202027, University of California at Riverside, Department of Economics.

  6. Melody Lo & Yong Bao, 2016. "Are Overall Journal Rankings a Good Mapping for Article Quality in Specialty Fields?," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 62-67, January.

    Cited by:

    1. Claude Diebolt & Michael Haupert, 2021. "The Role of Cliometrics in History and Economics," Working Papers 06-21, Association Française de Cliométrie (AFC).
    2. Johannes Koenig & David I. Stern & Richard S.J. Tol, 2022. "Confidence Intervals for Recursive Journal Impact Factors," Working Paper Series 0122, Department of Economics, University of Sussex Business School.
    3. Bornmann, Lutz & Butz, Alexander & Wohlrabe, Klaus, 2017. "What are the Top Five Journals in Economics? A New Meta–ranking," MPRA Paper 79176, University Library of Munich, Germany.
    4. Ham, John C. & Wright, Julian & Ye, Ziqiu, 2023. "Documenting and Explaining the Dramatic Rise of the New Society Journals in Economics," IZA Discussion Papers 16337, Institute of Labor Economics (IZA).

  7. Yong Bao, 2015. "Should We Demean the Data?," Annals of Economics and Finance, Society for AEF, vol. 16(1), pages 163-171, May.

    Cited by:

    1. Funjika, Patricia & Getachew, Yoseph Y., 2022. "Colonial origin, ethnicity and intergenerational mobility in Africa," World Development, Elsevier, vol. 153(C).

  8. Bao, Yong & Ullah, Aman & Wang, Yun & Yu, Jun, 2015. "Bias in the estimation of mean reversion in continuous-time Lévy processes," Economics Letters, Elsevier, vol. 134(C), pages 16-19.

    Cited by:

    1. Zi‐Yi Guo, 2021. "Out‐of‐sample performance of bias‐corrected estimators for diffusion processes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 243-268, March.
    2. Emma M. Iglesias & Garry D. A. Phillips, 2020. "Further Results on Pseudo‐Maximum Likelihood Estimation and Testing in the Constant Elasticity of Variance Continuous Time Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(2), pages 357-364, March.

  9. Bao, Yong & Hua, Ying, 2014. "On the Fisher information matrix of a vector ARMA process," Economics Letters, Elsevier, vol. 123(1), pages 14-16.

    Cited by:

    1. Abdelhamid Ouakasse & Guy Mélard, 2017. "A New Recursive Estimation Method for Single Input Single Output Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 417-457, May.
    2. Maddalena Cavicchioli, 2020. "A note on the asymptotic and exact Fisher information matrices of a Markov switching VARMA process," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(1), pages 129-139, March.
    3. Cavicchioli, Maddalena, 2017. "Asymptotic Fisher information matrix of Markov switching VARMA models," Journal of Multivariate Analysis, Elsevier, vol. 157(C), pages 124-135.
    4. Maddalena Cavicchioli, 2021. "OLS Estimation of Markov switching VAR models: asymptotics and application to energy use," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(3), pages 431-449, September.

  10. Bao, Yong, 2013. "Finite-Sample Bias Of The Qmle In Spatial Autoregressive Models," Econometric Theory, Cambridge University Press, vol. 29(1), pages 68-88, February.

    Cited by:

    1. Yang, Zhenlin, 2015. "A general method for third-order bias and variance corrections on a nonlinear estimator," Journal of Econometrics, Elsevier, vol. 186(1), pages 178-200.
    2. Bao, Yong & Ullah, Aman & Wang, Yun & Yu, Jun, 2015. "Bias in the estimation of mean reversion in continuous-time Lévy processes," Economics Letters, Elsevier, vol. 134(C), pages 16-19.
    3. Christoph Strumann, 2019. "Hodges–Lehmann Estimation of Static Panel Models with Spatially Correlated Disturbances," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 141-168, January.
    4. Shew Fan Liu & Zhenlin Yang, 2015. "Asymptotic Distribution and Finite Sample Bias Correction of QML Estimators for Spatial Error Dependence Model," Econometrics, MDPI, vol. 3(2), pages 1-36, May.
    5. Robinson, Peter M. & Rossi, Francesca, 2015. "Refined Tests For Spatial Correlation," Econometric Theory, Cambridge University Press, vol. 31(6), pages 1249-1280, December.
    6. Yu, Dalei & Bai, Peng & Ding, Chang, 2015. "Adjusted quasi-maximum likelihood estimator for mixed regressive, spatial autoregressive model and its small sample bias," Computational Statistics & Data Analysis, Elsevier, vol. 87(C), pages 116-135.
    7. Yang, Zhenlin & Yu, Jihai & Liu, Shew Fan, 2016. "Bias correction and refined inferences for fixed effects spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 61(C), pages 52-72.
    8. Yong Bao & Aman Ullah & Yun Wang & Jun Yu, 2013. "Bias in the Mean Reversion Estimator in Continuous-Time Gaussian and Lévy Processes," Working Papers 02-2013, Singapore Management University, School of Economics.
    9. Maria Kyriacou & Peter C.B. Phillips & Francesca Rossi, 2019. "Continuously Updated Indirect Inference in Heteroskedastic Spatial Models," Working Papers 15/2019, University of Verona, Department of Economics.
    10. Grant Hillier & Federico Martellosio, 2013. "Properties of the maximum likelihood estimator in spatial autoregressive models," CeMMAP working papers 44/13, Institute for Fiscal Studies.
    11. Rossi, Francesca & Robinson, Peter M., 2023. "Higher-order least squares inference for spatial autoregressions," Journal of Econometrics, Elsevier, vol. 232(1), pages 244-269.
    12. Grant Hillier & Federico Martellosio, 2013. "Properties of the maximum likelihood estimator in spatial autoregressive models," CeMMAP working papers CWP44/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Yong Bao & Aman Ullah, 2021. "Analytical Finite Sample Econometrics: From A. L. Nagar to Now," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 17-37, December.
    14. Kyoo Il Kim, 2016. "Higher Order Bias Correcting Moment Equation for M-Estimation and Its Higher Order Efficiency," Econometrics, MDPI, vol. 4(4), pages 1-19, December.
    15. Federico Martellosio & Grant Hillier, 2019. "Adjusted QMLE for the spatial autoregressive parameter," Papers 1909.08141, arXiv.org.
    16. Liu, Shew Fan & Yang, Zhenlin, 2015. "Improved inferences for spatial regression models," Regional Science and Urban Economics, Elsevier, vol. 55(C), pages 55-67.
    17. Kripfganz, Sebastian, 2014. "Unconditional Transformed Likelihood Estimation of Time-Space Dynamic Panel Data Models," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100604, Verein für Socialpolitik / German Economic Association.
    18. Francesca Rossi & Peter M. Robinson, 2020. "Higher-Order Least Squares Inference for Spatial Autoregressions," Working Papers 04/2020, University of Verona, Department of Economics.
    19. Martellosio, Federico & Hillier, Grant, 2020. "Adjusted QMLE for the spatial autoregressive parameter," Journal of Econometrics, Elsevier, vol. 219(2), pages 488-506.

  11. Bao, Yong & Ullah, Aman & Zinde-Walsh, Victoria, 2013. "On existence of moment of mean reversion estimator in linear diffusion models," Economics Letters, Elsevier, vol. 120(2), pages 146-148.

    Cited by:

    1. Chen, Ye & Yu, Jun, 2015. "Optimal jackknife for unit root models," Statistics & Probability Letters, Elsevier, vol. 99(C), pages 135-142.

  12. Bao, Yong & Kan, Raymond, 2013. "On the moments of ratios of quadratic forms in normal random variables," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 229-245.

    Cited by:

    1. Li, Min & Liu, Min-Qian & Wang, Xiao-Lei & Zhou, Yong-Dao, 2020. "Prediction for computer experiments with both quantitative and qualitative factors," Statistics & Probability Letters, Elsevier, vol. 165(C).
    2. Yong Bao & Aman Ullah, 2021. "Analytical Finite Sample Econometrics: From A. L. Nagar to Now," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 17-37, December.

  13. Yong Bao, 2013. "On Sample Skewness and Kurtosis," Econometric Reviews, Taylor & Francis Journals, vol. 32(4), pages 415-448, December.

    Cited by:

    1. Willi Mutschler, 2015. "Higher-order statistics for DSGE models," CQE Working Papers 4315, Center for Quantitative Economics (CQE), University of Muenster.
    2. Willi Mutschler, 2014. "Identification of DSGE Models - the Effect of Higher-Order Approximation and Pruning," CQE Working Papers 3314, Center for Quantitative Economics (CQE), University of Muenster.
    3. Mutschler, Willi, 2015. "Note on Higher-Order Statistics for the Pruned-State-Space of nonlinear DSGE models," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113138, Verein für Socialpolitik / German Economic Association.
    4. Wei-Han Liu, 2014. "Optimal hedge ratio estimation and hedge effectiveness with multivariate skew distributions," Applied Economics, Taylor & Francis Journals, vol. 46(12), pages 1420-1435, April.
    5. Marián Vávra, 2020. "Assessing distributional properties of forecast errors for fan-chart modelling," Empirical Economics, Springer, vol. 59(6), pages 2841-2858, December.
    6. Liu, 2014. "Do futures prices exhibit maturity effect? A nonparametric revisit," Applied Economics, Taylor & Francis Journals, vol. 46(8), pages 813-825, March.
    7. M. Barkhagen & S. García & J. Gondzio & J. Kalcsics & J. Kroeske & S. Sabanis & A. Staal, 2023. "Optimising portfolio diversification and dimensionality," Journal of Global Optimization, Springer, vol. 85(1), pages 185-234, January.
    8. Matei Demetrescu & Robinson Kruse-Becher, 2021. "Is U.S. real output growth really non-normal? Testing distributional assumptions in time-varying location-scale models," CREATES Research Papers 2021-07, Department of Economics and Business Economics, Aarhus University.

  14. Bao, Yong, 2013. "Finite Sample Bias Of The Qmle In Spatial Autoregressive Models – Erratum," Econometric Theory, Cambridge University Press, vol. 29(1), pages 89-89, February.

    Cited by:

    1. Yang, Zhenlin, 2015. "A general method for third-order bias and variance corrections on a nonlinear estimator," Journal of Econometrics, Elsevier, vol. 186(1), pages 178-200.
    2. Bao, Yong & Ullah, Aman & Wang, Yun & Yu, Jun, 2015. "Bias in the estimation of mean reversion in continuous-time Lévy processes," Economics Letters, Elsevier, vol. 134(C), pages 16-19.
    3. Christoph Strumann, 2019. "Hodges–Lehmann Estimation of Static Panel Models with Spatially Correlated Disturbances," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 141-168, January.
    4. Shew Fan Liu & Zhenlin Yang, 2015. "Asymptotic Distribution and Finite Sample Bias Correction of QML Estimators for Spatial Error Dependence Model," Econometrics, MDPI, vol. 3(2), pages 1-36, May.
    5. Robinson, Peter M. & Rossi, Francesca, 2015. "Refined Tests For Spatial Correlation," Econometric Theory, Cambridge University Press, vol. 31(6), pages 1249-1280, December.
    6. Yu, Dalei & Bai, Peng & Ding, Chang, 2015. "Adjusted quasi-maximum likelihood estimator for mixed regressive, spatial autoregressive model and its small sample bias," Computational Statistics & Data Analysis, Elsevier, vol. 87(C), pages 116-135.
    7. Yang, Zhenlin & Yu, Jihai & Liu, Shew Fan, 2016. "Bias correction and refined inferences for fixed effects spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 61(C), pages 52-72.
    8. Yong Bao & Aman Ullah & Yun Wang & Jun Yu, 2013. "Bias in the Mean Reversion Estimator in Continuous-Time Gaussian and Lévy Processes," Working Papers 02-2013, Singapore Management University, School of Economics.
    9. Maria Kyriacou & Peter C.B. Phillips & Francesca Rossi, 2019. "Continuously Updated Indirect Inference in Heteroskedastic Spatial Models," Working Papers 15/2019, University of Verona, Department of Economics.
    10. Grant Hillier & Federico Martellosio, 2013. "Properties of the maximum likelihood estimator in spatial autoregressive models," CeMMAP working papers 44/13, Institute for Fiscal Studies.
    11. Rossi, Francesca & Robinson, Peter M., 2023. "Higher-order least squares inference for spatial autoregressions," Journal of Econometrics, Elsevier, vol. 232(1), pages 244-269.
    12. Grant Hillier & Federico Martellosio, 2013. "Properties of the maximum likelihood estimator in spatial autoregressive models," CeMMAP working papers CWP44/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Yong Bao & Aman Ullah, 2021. "Analytical Finite Sample Econometrics: From A. L. Nagar to Now," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 17-37, December.
    14. Kyoo Il Kim, 2016. "Higher Order Bias Correcting Moment Equation for M-Estimation and Its Higher Order Efficiency," Econometrics, MDPI, vol. 4(4), pages 1-19, December.
    15. Federico Martellosio & Grant Hillier, 2019. "Adjusted QMLE for the spatial autoregressive parameter," Papers 1909.08141, arXiv.org.
    16. Liu, Shew Fan & Yang, Zhenlin, 2015. "Improved inferences for spatial regression models," Regional Science and Urban Economics, Elsevier, vol. 55(C), pages 55-67.
    17. Kripfganz, Sebastian, 2014. "Unconditional Transformed Likelihood Estimation of Time-Space Dynamic Panel Data Models," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100604, Verein für Socialpolitik / German Economic Association.
    18. Francesca Rossi & Peter M. Robinson, 2020. "Higher-Order Least Squares Inference for Spatial Autoregressions," Working Papers 04/2020, University of Verona, Department of Economics.
    19. Martellosio, Federico & Hillier, Grant, 2020. "Adjusted QMLE for the spatial autoregressive parameter," Journal of Econometrics, Elsevier, vol. 219(2), pages 488-506.

  15. Yong Bao & Melody Lo & Franklin G. Mixon, 2010. "General-interest versus specialty journals: Using intellectual influence of econometrics research to rank economics journals and articles," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 345-353.

    Cited by:

    1. Klaus Wohlrabe, 2016. "Taking the Temperature: A Meta-Ranking of Economics Journals," CESifo Working Paper Series 5726, CESifo.
    2. Bornmann, Lutz & Butz, Alexander & Wohlrabe, Klaus, 2017. "What are the Top Five Journals in Economics? A New Meta–ranking," MPRA Paper 79176, University Library of Munich, Germany.
    3. Theodore Eisenberg & Martin T. Wells, 2014. "Ranking Law Journals And The Limits Of Journal Citation Reports," Economic Inquiry, Western Economic Association International, vol. 52(4), pages 1301-1314, October.
    4. Franklin G. Mixon, Jr. & Kamal P. Upadhyaya, 2021. "Scholarly Impact of Core Econometrics Journals: A Catalog and Citations-Based Ranking," International Econometric Review (IER), Econometric Research Association, vol. 13(4), pages 118-131, December.
    5. Hagendorf, Klaus, 2011. "Crowding out capitalism: A law of historical materialism," MPRA Paper 31745, University Library of Munich, Germany.
    6. L. Lambertini & G. Leitmann, 2011. "Market Power, Resource Extraction and Pollution: Some Paradoxes and a Unified View," Working Papers wp798, Dipartimento Scienze Economiche, Universita' di Bologna.
    7. Ham, John C. & Wright, Julian & Ye, Ziqiu, 2023. "Documenting and Explaining the Dramatic Rise of the New Society Journals in Economics," IZA Discussion Papers 16337, Institute of Labor Economics (IZA).
    8. Christopher Bruffaerts & Bram De Rock & Catherine Dehon, 2013. "The Research Efficiency of US Universities: a Nonparametric Frontier Modelling Approach," Working Papers ECARES ECARES 2013-31, ULB -- Universite Libre de Bruxelles.

  16. Yong Bao & Thomas Fullerton & Donald Lien, 2009. "Borderplex menu evidence for the law of one price: a convergence approach," Applied Economics Letters, Taylor & Francis Journals, vol. 16(17), pages 1717-1720.

    Cited by:

    1. Pei-Chien Lin & Ho-Chuan Huang, 2011. "Inequality convergence in a panel of states," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 9(2), pages 195-206, June.

  17. Yong Bao, 2009. "Estimation Risk-Adjusted Sharpe Ratio and Fund Performance Ranking under a General Return Distribution," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 152-173, Spring.

    Cited by:

    1. Michael Pinelis & David Ruppert, 2020. "Machine Learning Portfolio Allocation," Papers 2003.00656, arXiv.org, revised Nov 2021.
    2. Schuster, Martin & Auer, Benjamin R., 2012. "A note on empirical Sharpe ratio dynamics," Economics Letters, Elsevier, vol. 116(1), pages 124-128.
    3. Homm, Ulrich & Pigorsch, Christian, 2012. "Beyond the Sharpe ratio: An application of the Aumann–Serrano index to performance measurement," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2274-2284.
    4. Fischer, Thomas & Lundtofte , Frederik, 2018. "Unequal Returns: Using the Atkinson Index to Measure Financial Risk," Working Papers 2018:25, Lund University, Department of Economics.
    5. Ken Johnston & John Hatem & Elton Scott, 2013. "A note on the evaluation of long-run investment decisions using the sharpe ratio," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 37(1), pages 150-157, January.
    6. Vedolin, Andrea, 2012. "Uncertainty and leveraged Lucas Trees: the cross section of equilibrium volatility risk premia," LSE Research Online Documents on Economics 43091, London School of Economics and Political Science, LSE Library.
    7. Taylor, Mark & Filippou, Ilias & Rapach, David & Zhou, Guofu, 2020. "Exchange Rate Prediction with Machine Learning and a Smart Carry Trade Portfolio," CEPR Discussion Papers 15305, C.E.P.R. Discussion Papers.
    8. Lipton, Amy F. & Kish, Richard J., 2010. "Robust performance measures for high yield bond funds," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(3), pages 332-340, August.

  18. Yong Bao & Shatakshee Dhongde, 2009. "Testing Convergence in Income Distribution," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(2), pages 295-302, April.

    Cited by:

    1. Shatakshee Dhongde & Xing Miao, 2013. "Cross-Country Convergence in Income Inequality," Working Papers 290, ECINEQ, Society for the Study of Economic Inequality.
    2. Pei-Chien Lin & Ho-Chuan Huang, 2011. "Inequality convergence in a panel of states," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 9(2), pages 195-206, June.
    3. Chambers, Dustin & Dhongde, Shatakshee, 2016. "Convergence in income distributions: Evidence from a panel of countries," Economic Modelling, Elsevier, vol. 59(C), pages 262-270.
    4. Bao, Yong & Yu, Xuewen, 2023. "Indirect inference estimation of dynamic panel data models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1027-1053.
    5. Huang, Ho-Chuan (River) & Liu, Wei-Han & Yeh, Chih-Chuan, 2012. "Convergence in price levels across US cities," Economics Letters, Elsevier, vol. 114(3), pages 245-248.
    6. Christina Christou & Juncal Cunado & Rangan Gupta, 2016. "Price Convergence Patterns across U.S. States," Working Papers 201629, University of Pretoria, Department of Economics.
    7. Dustin Chambers & Shatakshee Dhongde, 2017. "Are countries becoming equally unequal?," Empirical Economics, Springer, vol. 53(4), pages 1323-1348, December.
    8. Dustin Chambers & Susan Hamer, 2012. "Culture And Growth: Some Empirical Evidence," Bulletin of Economic Research, Wiley Blackwell, vol. 64(4), pages 549-564, October.

  19. Yong Bao & Aman Ullah, 2009. "On skewness and kurtosis of econometric estimators," Econometrics Journal, Royal Economic Society, vol. 12(2), pages 232-247, July.

    Cited by:

    1. Xiaohu Wang & Peter C.B. Phillips & Jun Yu, 2011. "Bias in Estimating Multivariate and Univariate Diffusions," Cowles Foundation Discussion Papers 1778, Cowles Foundation for Research in Economics, Yale University.
    2. Yong Bao & Aman Ullah, 2021. "Analytical Finite Sample Econometrics: From A. L. Nagar to Now," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 17-37, December.

  20. Bao, Yong, 2009. "Finite-Sample Moments Of The Coefficient Of Variation," Econometric Theory, Cambridge University Press, vol. 25(1), pages 291-297, February.

    Cited by:

    1. Dennis D. Boos & Jason A. Osborne, 2015. "Assessing Variability of Complex Descriptive Statistics in Monte Carlo Studies Using Resampling Methods," International Statistical Review, International Statistical Institute, vol. 83(2), pages 228-238, August.

  21. Bao, Yong & Ullah, Aman, 2007. "The second-order bias and mean squared error of estimators in time-series models," Journal of Econometrics, Elsevier, vol. 140(2), pages 650-669, October.

    Cited by:

    1. Lee, Tae-Hwy & Ullah, Aman & Wang, He, 2018. "The second-order bias of quantile estimators," Economics Letters, Elsevier, vol. 173(C), pages 143-147.
    2. Yang, Zhenlin, 2015. "A general method for third-order bias and variance corrections on a nonlinear estimator," Journal of Econometrics, Elsevier, vol. 186(1), pages 178-200.
    3. DHAENE, Geert & JOCHMANS, Koen, 2010. "Split-panel jackknife estimation of fixed-effect models," LIDAM Discussion Papers CORE 2010003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Koen Jochmans, 2022. "Bias in instrumental-variable estimators of fixed-effect models for count data," Post-Print hal-03699836, HAL.
    5. Liang Jiang & Xiaohu Wang & Jun Yu, 2014. "On Bias in the Estimation of Structural Break Points," Working Papers 22-2014, Singapore Management University, School of Economics.
    6. Shew Fan Liu & Zhenlin Yang, 2015. "Asymptotic Distribution and Finite Sample Bias Correction of QML Estimators for Spatial Error Dependence Model," Econometrics, MDPI, vol. 3(2), pages 1-36, May.
    7. Yong Li & Xiaobin Liu & Jun Yu & Tao Zeng, 2018. "A New Wald Test for Hypothesis Testing Based on MCMC outputs," Papers 1801.00973, arXiv.org.
    8. Kilian, Lutz & Inoue, Atsushi & Guerron-Quintana, Pablo A., 2014. "Impulse Response Matching Estimators for DSGE Models," CEPR Discussion Papers 10298, C.E.P.R. Discussion Papers.
    9. Kruse, Yves Robinson & Kaufmann, Hendrik, 2015. "Bias-corrected estimation in mildly explosive autoregressions," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112897, Verein für Socialpolitik / German Economic Association.
    10. Kruse, Robinson & Kaufmann, Hendrik & Wegener, Christoph, 2018. "Bias-corrected estimation for speculative bubbles in stock prices," Economic Modelling, Elsevier, vol. 73(C), pages 354-364.
    11. Kiviet, Jan F. & Phillips, Garry D.A., 2014. "Improved variance estimation of maximum likelihood estimators in stable first-order dynamic regression models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 424-448.
    12. Liu-Evans, Gareth, 2014. "A note on approximating moments of least squares estimators," MPRA Paper 57543, University Library of Munich, Germany.
    13. Jun Yu, 2009. "Bias in the Estimation of the Mean Reversion Parameter in Continuous Time Models," Microeconomics Working Papers 23045, East Asian Bureau of Economic Research.
    14. Atukorala, Ranjani & Sriananthakumar, Sivagowry, 2015. "A comparison of the accuracy of asymptotic approximations in the dynamic regression model using Kullback-Leibler information," Economic Modelling, Elsevier, vol. 45(C), pages 169-174.
    15. Jean-Jacques Forneron & Serena Ng, 2015. "The ABC of Simulation Estimation with Auxiliary Statistics," Papers 1501.01265, arXiv.org, revised Oct 2017.
    16. Bao Yong & Zhang Ru, 2013. "Estimation Bias and Feasible Conditional Forecasts from the First-Order Moving Average Model," Journal of Time Series Econometrics, De Gruyter, vol. 6(1), pages 63-80, July.
    17. Demos Antonis & Kyriakopoulou Dimitra, 2019. "Finite-Sample Theory and Bias Correction of Maximum Likelihood Estimators in the EGARCH Model," Journal of Time Series Econometrics, De Gruyter, vol. 11(1), pages 1-20, January.
    18. Tom Engsted & Thomas Q. Pedersen, 2011. "Bias-correction in vector autoregressive models: A simulation study," CREATES Research Papers 2011-18, Department of Economics and Business Economics, Aarhus University.
    19. Liu-Evans Gareth D. & Phillips Garry D. A., 2012. "Bootstrap, Jackknife and COLS: Bias and Mean Squared Error in Estimation of Autoregressive Models," Journal of Time Series Econometrics, De Gruyter, vol. 4(2), pages 1-35, November.
    20. Kiviet, J.F. & Phillips, G.D.A., 1999. "Higher-Order Asymptotic Expansions of the Least-Squares Estimation Bias in First-Order Dynamic Regression Models," Discussion Papers 9903, University of Exeter, Department of Economics.
    21. Stelios Arvanitis & Antonis Demos, 2015. "A class of indirect inference estimators: higher‐order asymptotics and approximate bias correction," Econometrics Journal, Royal Economic Society, vol. 18(2), pages 200-241, June.
    22. Iglesias Emma M, 2009. "Finite Sample Theory of QMLEs in ARCH Models with an Exogenous Variable in the Conditional Variance Equation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(2), pages 1-30, May.
    23. Atsushi Inoue & Lutz Kilian, 2016. "Joint Confidence Sets for Structural Impulse Responses," CESifo Working Paper Series 5746, CESifo.
    24. Christian Brownlees & Vladislav Morozov, 2022. "Unit Averaging for Heterogeneous Panels," Papers 2210.14205, arXiv.org, revised Nov 2022.
    25. Yong Bao & Aman Ullah & Yun Wang & Jun Yu, 2013. "Bias in the Mean Reversion Estimator in Continuous-Time Gaussian and Lévy Processes," Working Papers 02-2013, Singapore Management University, School of Economics.
    26. Arvanitis Stelios & Demos Antonis, 2018. "On the Validity of Edgeworth Expansions and Moment Approximations for Three Indirect Inference Estimators," Journal of Econometric Methods, De Gruyter, vol. 7(1), pages 1-38, January.
    27. Yong Bao, 2015. "Should We Demean the Data?," Annals of Economics and Finance, Society for AEF, vol. 16(1), pages 163-171, May.
    28. Yong Bao & Aman Ullah, 2021. "Analytical Finite Sample Econometrics: From A. L. Nagar to Now," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 17-37, December.
    29. Kyoo Il Kim, 2016. "Higher Order Bias Correcting Moment Equation for M-Estimation and Its Higher Order Efficiency," Econometrics, MDPI, vol. 4(4), pages 1-19, December.
    30. Aman Ullah & Yong Bao & Ru Zhang, 2014. "Moment Approximation for Unit Root Models with Nonnormal Errors," Working Papers 201401, University of California at Riverside, Department of Economics.
    31. Tae-Hwy Lee & Aman Ullah & He Wang, 2018. "The Second-order Asymptotic Properties of Asymmetric Least Squares Estimation," Working Papers 201910, University of California at Riverside, Department of Economics.
    32. Bartolucci, Francesco & Pigini, Claudia & Valentini, Francesco, 2021. "Conditional inference and bias reduction for partial effects estimation of fixed-effects logit models," MPRA Paper 110031, University Library of Munich, Germany.
    33. Dennis Kristensen & Bernard Salanié, 2010. "Higher Order Improvements for Approximate Estimators," CAM Working Papers 2010-04, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    34. Anna Mikusheva & Mikkel S{o}lvsten, 2023. "Linear Regression with Weak Exogeneity," Papers 2308.08958, arXiv.org, revised Jan 2024.
    35. Ruby Chiu‐Hsing Weng & D. Stephen Coad, 2021. "Bias approximations for likelihood‐based estimators," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(4), pages 1474-1497, December.
    36. Chambers, Marcus J., 2013. "Jackknife estimation of stationary autoregressive models," Journal of Econometrics, Elsevier, vol. 172(1), pages 142-157.
    37. Kun Duan & Tapas Mishra & Mamata Parhi & Simon Wolfe, 2019. "How Effective are Policy Interventions in a Spatially-Embedded International Real Estate Market?," The Journal of Real Estate Finance and Economics, Springer, vol. 58(4), pages 596-637, May.
    38. Hendrik Kaufmannz & Robinson Kruse, 2013. "Bias-corrected estimation in potentially mildly explosive autoregressive models," CREATES Research Papers 2013-10, Department of Economics and Business Economics, Aarhus University.
    39. Liu-Evans, Gareth, 2010. "An alternative approach to approximating the moments of least squares estimators," MPRA Paper 26550, University Library of Munich, Germany.
    40. Phillips, Garry D.A. & Liu-Evans, Gareth, 2016. "Approximating and reducing bias in 2SLS estimation of dynamic simultaneous equation models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 734-762.
    41. Gonçalves Mazzeu, Joao Henrique & Ruiz Ortega, Esther & Veiga, Helena, 2015. "Model uncertainty and the forecast accuracy of ARMA models: A survey," DES - Working Papers. Statistics and Econometrics. WS ws1508, Universidad Carlos III de Madrid. Departamento de Estadística.
    42. Tae-Hwy Lee & Aman Ullah & He Wang, 2023. "The Second-order Bias and Mean Squared Error of Quantile Regression Estimators," Working Papers 202313, University of California at Riverside, Department of Economics.

  22. Bao, Yong, 2007. "The Approximate Moments Of The Least Squares Estimator For The Stationary Autoregressive Model Under A General Error Distribution," Econometric Theory, Cambridge University Press, vol. 23(5), pages 1013-1021, October.

    Cited by:

    1. Kilian, Lutz & Inoue, Atsushi & Guerron-Quintana, Pablo A., 2014. "Impulse Response Matching Estimators for DSGE Models," CEPR Discussion Papers 10298, C.E.P.R. Discussion Papers.
    2. Kruse, Robinson & Kaufmann, Hendrik & Wegener, Christoph, 2018. "Bias-corrected estimation for speculative bubbles in stock prices," Economic Modelling, Elsevier, vol. 73(C), pages 354-364.
    3. Kiviet, Jan F. & Phillips, Garry D.A., 2014. "Improved variance estimation of maximum likelihood estimators in stable first-order dynamic regression models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 424-448.
    4. Liu-Evans, Gareth, 2014. "A note on approximating moments of least squares estimators," MPRA Paper 57543, University Library of Munich, Germany.
    5. Jun Yu, 2009. "Bias in the Estimation of the Mean Reversion Parameter in Continuous Time Models," Microeconomics Working Papers 23045, East Asian Bureau of Economic Research.
    6. Yong Bao & Aman Ullah, 2009. "Expectation of Quadratic Forms in Normal and Nonnormal Variables with Econometric Applications," Working Papers 200907, University of California at Riverside, Department of Economics, revised Jun 2009.
    7. Benjamin Chiquoine & Erik Hjalmarsson, 2008. "Jackknifing stock return predictions," International Finance Discussion Papers 932, Board of Governors of the Federal Reserve System (U.S.).
    8. Liu-Evans Gareth D. & Phillips Garry D. A., 2012. "Bootstrap, Jackknife and COLS: Bias and Mean Squared Error in Estimation of Autoregressive Models," Journal of Time Series Econometrics, De Gruyter, vol. 4(2), pages 1-35, November.
    9. Kiviet, J.F. & Phillips, G.D.A., 1999. "Higher-Order Asymptotic Expansions of the Least-Squares Estimation Bias in First-Order Dynamic Regression Models," Discussion Papers 9903, University of Exeter, Department of Economics.
    10. Atsushi Inoue & Lutz Kilian, 2016. "Joint Confidence Sets for Structural Impulse Responses," CESifo Working Paper Series 5746, CESifo.
    11. Herv√ Le Bihan & Julien Matheron, 2012. "Price Stickiness and Sectoral Inflation Persistence: Additional Evidence," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(7), pages 1427-1442, October.
    12. Aman Ullah & Yong Bao & Ru Zhang, 2014. "Moment Approximation for Unit Root Models with Nonnormal Errors," Working Papers 201401, University of California at Riverside, Department of Economics.
    13. Gareth Liu-Evans, 2021. "Improving the Estimation and Predictions of Small Time Series Models," Working Papers 202106, University of Liverpool, Department of Economics.
    14. Chambers, Marcus J., 2013. "Jackknife estimation of stationary autoregressive models," Journal of Econometrics, Elsevier, vol. 172(1), pages 142-157.
    15. Liu-Evans, Gareth, 2010. "An alternative approach to approximating the moments of least squares estimators," MPRA Paper 26550, University Library of Munich, Germany.

  23. Tae-Hwy Lee & Yong Bao & Burak Saltoğlu, 2007. "Comparing density forecast models Previous versions of this paper have been circulated with the title, 'A Test for Density Forecast Comparison with Applications to Risk Management' since October 2003;," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(3), pages 203-225.

    Cited by:

    1. Francesco Ravazzolo & Shaun P. Vahey, 2010. "Forecast densities for economic aggregates from disaggregate ensembles," Working Paper 2010/02, Norges Bank.
    2. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2010. "Out-of-sample comparison of copula specifications in multivariate density forecasts," Post-Print hal-00732675, HAL.
    3. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    4. John M. Maheu & Thomas H. McCurdy, 2009. "Do High-Frequency Measures of Volatility Improve Forecasts of Return Distributions?," Working Paper series 19_09, Rimini Centre for Economic Analysis.
    5. Garratt, Anthony & Mitchell, James & Vahey, Shaun, 2013. "Measuring Output Gap Nowcast Uncertainty," EMF Research Papers 01, Economic Modelling and Forecasting Group.
    6. Anthony Garratt & James Mitchell & Shaun P. Vahey, 2009. "Measuring Output Gap Uncertainty," Birkbeck Working Papers in Economics and Finance 0909, Birkbeck, Department of Economics, Mathematics & Statistics.
    7. Francesco Ravazzolo & Shaun P Vahey, 2010. "Measuring Core Inflation in Australia with Disaggregate Ensembles," RBA Annual Conference Volume (Discontinued), in: Renée Fry & Callum Jones & Christopher Kent (ed.),Inflation in an Era of Relative Price Shocks, Reserve Bank of Australia.
    8. Dijk, D. van & Diks, C.G.H. & Panchenko, V., 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," CeNDEF Working Papers 08-03, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    9. Del Brio, Esther B. & Ñíguez, Trino-Manuel & Perote, Javier, 2011. "Multivariate semi-nonparametric distributions with dynamic conditional correlations," International Journal of Forecasting, Elsevier, vol. 27(2), pages 347-364.
    10. Cheng, Xixin & Li, W.K. & Yu, Philip L.H. & Zhou, Xuan & Wang, Chao & Lo, P.H., 2011. "Modeling threshold conditional heteroscedasticity with regime-dependent skewness and kurtosis," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2590-2604, September.
    11. Li, Yushu & Andersson, Jonas, 2014. "A Likelihood Ratio and Markov Chain Based Method to Evaluate Density Forecasting," Discussion Papers 2014/12, Norwegian School of Economics, Department of Business and Management Science.
    12. Hua, Jian & Manzan, Sebastiano, 2013. "Forecasting the return distribution using high-frequency volatility measures," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4381-4403.
    13. Lee, Tae-Hwy & Long, Xiangdong, 2009. "Copula-based multivariate GARCH model with uncorrelated dependent errors," Journal of Econometrics, Elsevier, vol. 150(2), pages 207-218, June.
    14. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Post-Print hal-00834423, HAL.
    15. Rompolis, Leonidas S., 2010. "Retrieving risk neutral densities from European option prices based on the principle of maximum entropy," Journal of Empirical Finance, Elsevier, vol. 17(5), pages 918-937, December.
    16. Gloria González-Rivera & Tae-Hwy Lee, 2007. "Nonlinear Time Series in Financial Forecasting," Working Papers 200803, University of California at Riverside, Department of Economics, revised Feb 2008.
    17. Kyungchul Song, 2009. "Testing Predictive Ability and Power Robustification," PIER Working Paper Archive 09-035, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

  24. Bao, Yong, 2007. "Finite-Sample Properties Of Forecasts From The Stationary First-Order Autoregressive Model Under A General Error Distribution," Econometric Theory, Cambridge University Press, vol. 23(4), pages 767-773, August.

    Cited by:

    1. Pesaran, M. Hashem & Pick, Andreas & Timmermann, Allan, 2011. "Variable selection, estimation and inference for multi-period forecasting problems," Journal of Econometrics, Elsevier, vol. 164(1), pages 173-187, September.
    2. Bao Yong & Zhang Ru, 2013. "Estimation Bias and Feasible Conditional Forecasts from the First-Order Moving Average Model," Journal of Time Series Econometrics, De Gruyter, vol. 6(1), pages 63-80, July.
    3. Hännikäinen, Jari, 2014. "Multi-step forecasting in the presence of breaks," MPRA Paper 55816, University Library of Munich, Germany.
    4. João Henrique Gonçalves Mazzeu & Esther Ruiz & Helena Veiga, 2018. "Uncertainty And Density Forecasts Of Arma Models: Comparison Of Asymptotic, Bayesian, And Bootstrap Procedures," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 388-419, April.

  25. Bao, Yong & Ullah, Aman, 2007. "Finite sample properties of maximum likelihood estimator in spatial models," Journal of Econometrics, Elsevier, vol. 137(2), pages 396-413, April.

    Cited by:

    1. Yang, Zhenlin, 2015. "A general method for third-order bias and variance corrections on a nonlinear estimator," Journal of Econometrics, Elsevier, vol. 186(1), pages 178-200.
    2. Christoph Strumann, 2019. "Hodges–Lehmann Estimation of Static Panel Models with Spatially Correlated Disturbances," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 141-168, January.
    3. Yu, Dalei & Ding, Chang & He, Na & Wang, Ruiwu & Zhou, Xiaohua & Shi, Lei, 2019. "Robust estimation and confidence interval in meta-regression models," Computational Statistics & Data Analysis, Elsevier, vol. 129(C), pages 93-118.
    4. Shew Fan Liu & Zhenlin Yang, 2015. "Asymptotic Distribution and Finite Sample Bias Correction of QML Estimators for Spatial Error Dependence Model," Econometrics, MDPI, vol. 3(2), pages 1-36, May.
    5. Mustafa Koroglu & Yiguo Sun, 2016. "Functional-Coefficient Spatial Durbin Models with Nonparametric Spatial Weights: An Application to Economic Growth," Econometrics, MDPI, vol. 4(1), pages 1-16, February.
    6. Robinson, Peter & Rossi, Francesca, 2015. "Refinements in maximum likelihood inference on spatial autocorrelation in panel data," LSE Research Online Documents on Economics 61432, London School of Economics and Political Science, LSE Library.
    7. Robinson, Peter M. & Rossi, Francesca, 2015. "Refined Tests For Spatial Correlation," Econometric Theory, Cambridge University Press, vol. 31(6), pages 1249-1280, December.
    8. David M. Drukker & Peter Egger & Ingmar R. Prucha, 2013. "On Two-Step Estimation of a Spatial Autoregressive Model with Autoregressive Disturbances and Endogenous Regressors," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 686-733, August.
    9. Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
    10. Badi H. Baltagi & Long Liu, 2015. "Testing for Spacial Lag and Spatial Error Dependence in a Fixed Effects Panel Data Model Using Double Length Artificial Regressions," Center for Policy Research Working Papers 183, Center for Policy Research, Maxwell School, Syracuse University.
    11. Joris Pinkse & Margaret E. Slade, 2010. "The Future Of Spatial Econometrics," Journal of Regional Science, Wiley Blackwell, vol. 50(1), pages 103-117, February.
    12. Leopoldo Catania & Anna Gloria Bill'e, 2016. "Dynamic Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances," Papers 1602.02542, arXiv.org, revised Jan 2023.
    13. Yu, Dalei & Bai, Peng & Ding, Chang, 2015. "Adjusted quasi-maximum likelihood estimator for mixed regressive, spatial autoregressive model and its small sample bias," Computational Statistics & Data Analysis, Elsevier, vol. 87(C), pages 116-135.
    14. Demos Antonis & Kyriakopoulou Dimitra, 2019. "Finite-Sample Theory and Bias Correction of Maximum Likelihood Estimators in the EGARCH Model," Journal of Time Series Econometrics, De Gruyter, vol. 11(1), pages 1-20, January.
    15. Paul Rilstone, 2021. "Higher-Order Stochastic Expansions and Approximate Moments for Non-linear Models with Heterogeneous Observations," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 99-120, December.
    16. Stelios Arvanitis & Antonis Demos, 2015. "A class of indirect inference estimators: higher‐order asymptotics and approximate bias correction," Econometrics Journal, Royal Economic Society, vol. 18(2), pages 200-241, June.
    17. Yang, Zhenlin & Yu, Jihai & Liu, Shew Fan, 2016. "Bias correction and refined inferences for fixed effects spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 61(C), pages 52-72.
    18. Maria Kyriacou & Peter C.B. Phillips & Francesca Rossi, 2019. "Continuously Updated Indirect Inference in Heteroskedastic Spatial Models," Working Papers 15/2019, University of Verona, Department of Economics.
    19. Grant Hillier & Federico Martellosio, 2013. "Properties of the maximum likelihood estimator in spatial autoregressive models," CeMMAP working papers 44/13, Institute for Fiscal Studies.
    20. Rossi, Francesca & Robinson, Peter M., 2023. "Higher-order least squares inference for spatial autoregressions," Journal of Econometrics, Elsevier, vol. 232(1), pages 244-269.
    21. Anna Gloria Billé & Samantha Leorato, 2017. "Quasi-ML estimation, Marginal Effects and Asymptotics for Spatial Autoregressive Nonlinear Models," BEMPS - Bozen Economics & Management Paper Series BEMPS44, Faculty of Economics and Management at the Free University of Bozen.
    22. Grant Hillier & Federico Martellosio, 2013. "Properties of the maximum likelihood estimator in spatial autoregressive models," CeMMAP working papers CWP44/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    23. Yong Bao & Aman Ullah, 2021. "Analytical Finite Sample Econometrics: From A. L. Nagar to Now," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 17-37, December.
    24. Kyoo Il Kim, 2016. "Higher Order Bias Correcting Moment Equation for M-Estimation and Its Higher Order Efficiency," Econometrics, MDPI, vol. 4(4), pages 1-19, December.
    25. Kazuhiko Kakamu & Hajime Wago, 2008. "Small-sample Properties of Panel Spatial Autoregressive Models: Comparison of the Bayesian and Maximum Likelihood MethodsAn earlier version of this paper was presented at the 2007 Fall meeting of Japa," Spatial Economic Analysis, Taylor & Francis Journals, vol. 3(3), pages 305-319.
    26. Anna Gloria Billé & Leopoldo Catania, 2018. "Dynamic Spatial Autoregressive Models with Time-varying Spatial Weighting Matrices," BEMPS - Bozen Economics & Management Paper Series BEMPS55, Faculty of Economics and Management at the Free University of Bozen.
    27. Jesús Mur & Fernando López & Ana Angulo, 2009. "Testing the hypothesis of stability in spatial econometric models," Papers in Regional Science, Wiley Blackwell, vol. 88(2), pages 409-444, June.
    28. Federico Martellosio & Grant Hillier, 2019. "Adjusted QMLE for the spatial autoregressive parameter," Papers 1909.08141, arXiv.org.
    29. Liu, Shew Fan & Yang, Zhenlin, 2015. "Improved inferences for spatial regression models," Regional Science and Urban Economics, Elsevier, vol. 55(C), pages 55-67.
    30. Francesca Rossi & Peter M. Robinson, 2020. "Higher-Order Least Squares Inference for Spatial Autoregressions," Working Papers 04/2020, University of Verona, Department of Economics.
    31. Giuseppe Arbia, 2011. "A Lustrum of SEA: Recent Research Trends Following the Creation of the Spatial Econometrics Association (2007--2011)," Spatial Economic Analysis, Taylor & Francis Journals, vol. 6(4), pages 377-395, July.
    32. J. Paul Elhorst, 2022. "The dynamic general nesting spatial econometric model for spatial panels with common factors: Further raising the bar," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 42(3), pages 249-267, December.
    33. Martellosio, Federico & Hillier, Grant, 2020. "Adjusted QMLE for the spatial autoregressive parameter," Journal of Econometrics, Elsevier, vol. 219(2), pages 488-506.
    34. Bo Pieter Johannes Andree & Francisco Blasques & Eric Koomen, 2017. "Smooth Transition Spatial Autoregressive Models," Tinbergen Institute Discussion Papers 17-050/III, Tinbergen Institute.

  26. Tae-Hwy Lee & Yong Bao & Burak Saltoglu, 2006. "Evaluating predictive performance of value-at-risk models in emerging markets: a reality check," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(2), pages 101-128.

    Cited by:

    1. Sofiane Aboura, 2014. "When the U.S. Stock Market Becomes Extreme?," Risks, MDPI, vol. 2(2), pages 1-15, May.
    2. Andriosopoulos, Kostas & Doumpos, Michael & Papapostolou, Nikos C. & Pouliasis, Panos K., 2013. "Portfolio optimization and index tracking for the shipping stock and freight markets using evolutionary algorithms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 52(C), pages 16-34.
    3. Tchamyou, Vanessa & Asongu, Simplice, 2017. "Conditional Market Timing in the Mutual Fund Industry," MPRA Paper 82633, University Library of Munich, Germany.
    4. Christina Ziegler, 2009. "Testing Predicitive Ability of Business Cycle Indicators for the Euro Area," ifo Working Paper Series 69, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    5. Dimitrakopoulos, Dimitris N. & Kavussanos, Manolis G. & Spyrou, Spyros I., 2010. "Value at risk models for volatile emerging markets equity portfolios," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(4), pages 515-526, November.
    6. Szubzda Filip & Chlebus Marcin, 2019. "Comparison of Block Maxima and Peaks Over Threshold Value-at-Risk models for market risk in various economic conditions," Central European Economic Journal, Sciendo, vol. 6(53), pages 70-85, January.
    7. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    8. Nomikos, Nikos K. & Pouliasis, Panos K., 2011. "Forecasting petroleum futures markets volatility: The role of regimes and market conditions," Energy Economics, Elsevier, vol. 33(2), pages 321-337, March.
    9. Shuowen Hu & D.S. Poskitt & Xibin Zhang, 2010. "Bayesian Adaptive Bandwidth Kernel Density Estimation of Irregular Multivariate Distributions," Monash Econometrics and Business Statistics Working Papers 21/10, Monash University, Department of Econometrics and Business Statistics.
    10. Yu, Tiffany Hui-Kuang & Wang, David Han-Min & Wu, Kuo-Lun, 2015. "Reexamining the red herring effect on healthcare expenditures," Journal of Business Research, Elsevier, vol. 68(4), pages 783-787.
    11. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 649-677.
    12. Nikkin L. Beronilla & Dennis S. Mapa, 2008. "Range-based models in estimating value-at-risk (VaR)," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 45(2), pages 87-99, December.
    13. Giot, Pierre & Laurent, Sebastien, 2004. "Modelling daily Value-at-Risk using realized volatility and ARCH type models," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 379-398, June.
    14. Ñíguez, Trino-Manuel & Perote, Javier, 2017. "Moments expansion densities for quantifying financial risk," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 53-69.
    15. Wang, Jying-Nan & Du, Jiangze & Hsu, Yuan-Teng, 2018. "Measuring long-term tail risk: Evaluating the performance of the square-root-of-time rule," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 120-138.
    16. Gonzalo Cortazar & Alejandro Bernales & Diether Beuermann, 2005. "Methodology and Implementation of Value-at-Risk Measures in Emerging Fixed-Income Markets with Infrequent Trading," Finance 0512030, University Library of Munich, Germany.
    17. Bei, Shuhua & Yang, Aijun & Pei, Haotian & Si, Xiaoli, 2023. "Price Risk Analysis using GARCH Family Models: Evidence from Shanghai Crude Oil Futures Market," Economic Modelling, Elsevier, vol. 125(C).
    18. Ledoit, Olivier & Santa-Clara, Pedro & Wolf, Michael, 1999. "Flexible Multivariate GARCH Modeling With an Application to International Stock Markets," University of California at Los Angeles, Anderson Graduate School of Management qt93s6p8gb, Anderson Graduate School of Management, UCLA.
    19. Chrétien, Stéphane & Coggins, Frank, 2010. "Performance and conservatism of monthly FHS VaR: An international investigation," International Review of Financial Analysis, Elsevier, vol. 19(5), pages 323-333, December.
    20. Mateusz Buczyński & Marcin Chlebus, 2019. "Old-fashioned parametric models are still the best. A comparison of Value-at-Risk approaches in several volatility states," Working Papers 2019-12, Faculty of Economic Sciences, University of Warsaw.
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  27. Bao, Yong & Ullah, Aman, 2006. "Moments of the estimated Sharpe ratio when the observations are not IID," Finance Research Letters, Elsevier, vol. 3(1), pages 49-56, March.

    Cited by:

    1. Schuster, Martin & Auer, Benjamin R., 2012. "A note on empirical Sharpe ratio dynamics," Economics Letters, Elsevier, vol. 116(1), pages 124-128.
    2. Carbajal-De-Nova, Carolina & Venegas-Martínez, Francisco, 2019. "On the paradigm shift of asset pricing models, before and after the global financial crisis: a literature review," Panorama Económico, Escuela Superior de Economía, Instituto Politécnico Nacional, vol. 15(29), pages 7-38, Primer se.
    3. Ken Johnston & John Hatem & Elton Scott, 2013. "A note on the evaluation of long-run investment decisions using the sharpe ratio," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 37(1), pages 150-157, January.
    4. Mahesh K.C & Arnab Kumar Laha, 2021. "A Robust Sharpe Ratio," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 444-465, November.
    5. John Douglas (J.D.) Opdyke, 2007. "Comparing Sharpe ratios: So where are the p-values?," Journal of Asset Management, Palgrave Macmillan, vol. 8(5), pages 308-336, December.
    6. Gonzales, Rolando, 2009. "Análisis de Portafolio con Ratios de Sharpe Remuestrados Mediante Bootstrapping [Portfolio analysis with Sharpe ratios resampled by bootstrapping]," MPRA Paper 28402, University Library of Munich, Germany.

  28. Bao, Yong & Ullah, Aman, 2004. "Bias of a Value-at-Risk estimator," Finance Research Letters, Elsevier, vol. 1(4), pages 241-249, December.

    Cited by:

    1. Carl Lonnbark, 2010. "A corrected Value-at-Risk predictor," Applied Economics Letters, Taylor & Francis Journals, vol. 17(12), pages 1193-1196.
    2. Christophe Boucher & Jon Danielsson & Patrick Kouontchou & Bertrand Maillet, 2014. "Risk models-at-risk," Post-Print hal-02312332, HAL.
    3. Radu Tunaru, 2015. "Model Risk in Financial Markets:From Financial Engineering to Risk Management," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 9524, January.
    4. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    5. Christian Gouriéroux & Jean-Michel Zakoian, 2012. "Estimation Adjusted VaR," Working Papers 2012-16, Center for Research in Economics and Statistics.
    6. Claußen, Arndt & Rösch, Daniel & Schmelzle, Martin, 2019. "Hedging parameter risk," Journal of Banking & Finance, Elsevier, vol. 100(C), pages 111-121.

  29. Yong Bao & Jang‐Ting Guo, 2004. "Reexamination of Economic Growth, Tax Policy, and Distributive Politics," Review of Development Economics, Wiley Blackwell, vol. 8(3), pages 474-482, August.

    Cited by:

    1. Christophe Ehrhart, 2009. "The effects of inequality on growth: a survey of the theoretical and empirical literature," Working Papers 107, ECINEQ, Society for the Study of Economic Inequality.
    2. Peter J. Stauvermann & Ronald R. Kumar, 2018. "Adult Learning, Economic Growth and the Distribution of Income," Economies, MDPI, vol. 6(1), pages 1-12, February.

Chapters

  1. Yong Bao & Aman Ullah & Ru Zhang, 2014. "Moment Approximation for Least-Squares Estimator in First-Order Regression Models with Unit Root and Nonnormal Errors," Advances in Econometrics, in: Essays in Honor of Peter C. B. Phillips, volume 14, pages 65-92, Emerald Group Publishing Limited.

    Cited by:

    1. Yong Bao & Aman Ullah, 2021. "Analytical Finite Sample Econometrics: From A. L. Nagar to Now," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 17-37, December.

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