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Xibin Zhang

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. Maxwell King & Xibin Zhang & Muhammad Akram, 2019. "Hypothesis Testing Based on a Vector of Statistics," Monash Econometrics and Business Statistics Working Papers 30/19, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Lena S. Bjerkander & Jonas Dovern & Hans Manner, 2024. "Testing with Vectors of Statistics: Revisiting Combined Hypothesis Tests with an Application to Specification Testing," CESifo Working Paper Series 11027, CESifo.

  2. Tingting Cheng & Jiti Gao & Xibin Zhang, 2015. "Bayesian Bandwidth Estimation In Nonparametric Time-Varying Coefficient Models," Monash Econometrics and Business Statistics Working Papers 3/15, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Lafourcade, Pierre & Gerali, Andrea & Brůha, Jan & Bursian, Dirk & Buss, Ginters & Corbo, Vesna & Haavio, Markus & Håkanson, Christina & Hlédik, Tibor & Kátay, Gábor & Kulikov, Dmitry & Lozej, Matija , 2016. "Labour market modelling in the light of the financial crisis," Occasional Paper Series 175, European Central Bank.
    2. Jan Bruha & Jiri Polansky, 2015. "Empirical Analysis of Labor Markets over Business Cycles: An International Comparison," Working Papers 2015/15, Czech National Bank.

  3. Tingting Cheng & Jiti Gao & Xibin Zhang, 2014. "Semiparametric Localized Bandwidth Selection for Kernel Density Estimation," Monash Econometrics and Business Statistics Working Papers 27/14, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Tingting Cheng & Jiti Gao & Oliver Linton, 2017. "Multi-step non- and semi-parametric predictive regressions for short and long horizon stock return prediction," Monash Econometrics and Business Statistics Working Papers 13/17, Monash University, Department of Econometrics and Business Statistics.
    2. Sreevani, & Murthy, C.A., 2016. "On bandwidth selection using minimal spanning tree for kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 102(C), pages 67-84.

  4. Xibin Zhang & Maxwell L. King, 2013. "Gaussian kernel GARCH models," Monash Econometrics and Business Statistics Working Papers 19/13, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Hu, Shuowen & Poskitt, D.S. & Zhang, Xibin, 2021. "Bayesian estimation for a semiparametric nonlinear volatility model," Economic Modelling, Elsevier, vol. 98(C), pages 361-370.
    2. Tingting Cheng & Jiti Gao & Xibin Zhang, 2014. "Semiparametric Localized Bandwidth Selection in Kernel Density Estimation," Monash Econometrics and Business Statistics Working Papers 14/14, Monash University, Department of Econometrics and Business Statistics.
    3. Haotian Chen & Xibin Zhang, 2014. "Bayesian Estimation for Partially Linear Models with an Application to Household Gasoline Consumption," Monash Econometrics and Business Statistics Working Papers 28/14, Monash University, Department of Econometrics and Business Statistics.
    4. Tingting Cheng & Jiti Gao & Xibin Zhang, 2016. "Nonparametric Localized Bandwidth Selection for Kernel Density Estimation," Monash Econometrics and Business Statistics Working Papers 7/16, Monash University, Department of Econometrics and Business Statistics.
    5. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2016. "Bayesian Bandwidth Selection for a Nonparametric Regression Model with Mixed Types of Regressors," Econometrics, MDPI, vol. 4(2), pages 1-27, April.
    6. Chen, Haotian & Smyth, Russell & Zhang, Xibin, 2017. "A Bayesian sampling approach to measuring the price responsiveness of gasoline demand using a constrained partially linear model," Energy Economics, Elsevier, vol. 67(C), pages 346-354.
    7. Tingting Cheng & Jiti Gao & Xibin Zhang, 2014. "Semiparametric Localized Bandwidth Selection for Kernel Density Estimation," Monash Econometrics and Business Statistics Working Papers 27/14, Monash University, Department of Econometrics and Business Statistics.

  5. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2013. "Bayesian bandwidth selection for a nonparametric regession model with mixed types of regressors," Monash Econometrics and Business Statistics Working Papers 13/13, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2016. "Bayesian Bandwidth Selection for a Nonparametric Regression Model with Mixed Types of Regressors," Econometrics, MDPI, vol. 4(2), pages 1-27, April.
    2. Xu, Bin & Lin, Boqiang, 2017. "Assessing CO2 emissions in China's iron and steel industry: A nonparametric additive regression approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 325-337.

  6. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2013. "A sampling algorithm for bandwidth estimation in a nonparametric regression model with a flexible error density," Monash Econometrics and Business Statistics Working Papers 20/13, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2016. "Bayesian Bandwidth Selection for a Nonparametric Regression Model with Mixed Types of Regressors," Econometrics, MDPI, vol. 4(2), pages 1-27, April.
    2. Guohua Feng & Chuan Wang & Xibin Zhang, 2019. "Estimation of inefficiency in stochastic frontier models: a Bayesian kernel approach," Journal of Productivity Analysis, Springer, vol. 51(1), pages 1-19, February.
    3. Tristan Senga Kiessé & Nabil Zougab & Célestin C. Kokonendji, 2016. "Bayesian estimation of bandwidth in semiparametric kernel estimation of unknown probability mass and regression functions of count data," Computational Statistics, Springer, vol. 31(1), pages 189-206, March.
    4. Philip T. Reiss & Jeff Goldsmith & Han Lin Shang & R. Todd Ogden, 2017. "Methods for Scalar-on-Function Regression," International Statistical Review, International Statistical Institute, vol. 85(2), pages 228-249, August.

  7. Song Li & Mervyn J. Silvapulle & Param Silvapulle & Xibin Zhang, 2012. "Bayesian Approaches to Non-parametric Estimation of Densities on the Unit Interval," Monash Econometrics and Business Statistics Working Papers 3/12, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Zougab, Nabil & Adjabi, Smail & Kokonendji, Célestin C., 2014. "Bayesian estimation of adaptive bandwidth matrices in multivariate kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 28-38.
    2. Song Li & Mervyn J. Silvapulle & Param Silvapulle & Xibin Zhang, 2015. "Bayesian Approaches to Nonparametric Estimation of Densities on the Unit Interval," Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 394-412, March.
    3. Bedouhene Kahina & Zougab Nabil, 2020. "A Bayesian procedure for bandwidth selection in circular kernel density estimation," Monte Carlo Methods and Applications, De Gruyter, vol. 26(1), pages 69-82, March.

  8. Xibin Zhang & Maxwell L. King, 2011. "Bayesian semiparametric GARCH models," Monash Econometrics and Business Statistics Working Papers 24/11, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Song Li & Mervyn J. Silvapulle & Param Silvapulle & Xibin Zhang, 2015. "Bayesian Approaches to Nonparametric Estimation of Densities on the Unit Interval," Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 394-412, March.
    2. Han Shang, 2014. "Bayesian bandwidth estimation for a semi-functional partial linear regression model with unknown error density," Computational Statistics, Springer, vol. 29(3), pages 829-848, June.
    3. Shang, Han Lin, 2013. "Bayesian bandwidth estimation for a nonparametric functional regression model with unknown error density," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 185-198.
    4. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2016. "Bayesian Bandwidth Selection for a Nonparametric Regression Model with Mixed Types of Regressors," Econometrics, MDPI, vol. 4(2), pages 1-27, April.
    5. Zhang, Xibin & King, Maxwell L. & Shang, Han Lin, 2014. "A sampling algorithm for bandwidth estimation in a nonparametric regression model with a flexible error density," Computational Statistics & Data Analysis, Elsevier, vol. 78(C), pages 218-234.
    6. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2011. "Bayesian estimation of bandwidths for a nonparametric regression model with a flexible error density," Monash Econometrics and Business Statistics Working Papers 10/11, Monash University, Department of Econometrics and Business Statistics.

  9. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2011. "Bayesian estimation of bandwidths for a nonparametric regression model with a flexible error density," Monash Econometrics and Business Statistics Working Papers 10/11, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Shang, Han Lin, 2013. "Bayesian bandwidth estimation for a nonparametric functional regression model with unknown error density," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 185-198.
    2. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2016. "Bayesian Bandwidth Selection for a Nonparametric Regression Model with Mixed Types of Regressors," Econometrics, MDPI, vol. 4(2), pages 1-27, April.

  10. Maxwell L. King & Xibin Zhang & Muhammad Akram, 2011. "A New Procedure For Multiple Testing Of Econometric Models," Monash Econometrics and Business Statistics Working Papers 7/11, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Jin Seo Cho & Halbert White, 2014. "Testing the Equality of Two Positive-Definite Matrices with Application to Information Matrix Testing," Working papers 2014rwp-67, Yonsei University, Yonsei Economics Research Institute.
    2. Julia Polak & Maxwell L. King & Xibin Zhang, 2014. "A Model Validation Procedure," Monash Econometrics and Business Statistics Working Papers 21/14, Monash University, Department of Econometrics and Business Statistics.

  11. Qing Liu & David Pitt & Xibin Zhang & Xueyuan Wu, 2010. "A Bayesian approach to parameter estimation for kernel density estimation via transformations," Monash Econometrics and Business Statistics Working Papers 18/10, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Catalina Bolance & Montserrat Guillen & David Pitt, 2014. "Non-parametric Models for Univariate Claim Severity Distributions - an approach using R," Working Papers 2014-01, Universitat de Barcelona, UB Riskcenter.
    2. Zougab, Nabil & Adjabi, Smail & Kokonendji, Célestin C., 2014. "Bayesian estimation of adaptive bandwidth matrices in multivariate kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 28-38.
    3. David Pitt & Montserrat Guillen & Catalina Bolancé, 2011. "Estimation of Parametric and Nonparametric Models for Univariate Claim Severity Distributions - an approach using R," Working Papers XREAP2011-06, Xarxa de Referència en Economia Aplicada (XREAP), revised Jun 2011.

  12. 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.

    Cited by:

    1. Y. Ziane & S. Adjabi & N. Zougab, 2015. "Adaptive Bayesian bandwidth selection in asymmetric kernel density estimation for nonnegative heavy-tailed data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(8), pages 1645-1658, August.
    2. 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.
    3. Zougab, Nabil & Adjabi, Smail & Kokonendji, Célestin C., 2014. "Bayesian estimation of adaptive bandwidth matrices in multivariate kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 28-38.
    4. Yasmina Ziane & Nabil Zougab & Smail Adjabi, 2018. "Birnbaum–Saunders power-exponential kernel density estimation and Bayes local bandwidth selection for nonnegative heavy tailed data," Computational Statistics, Springer, vol. 33(1), pages 299-318, March.
    5. Tristan Senga Kiessé & Nabil Zougab & Célestin C. Kokonendji, 2016. "Bayesian estimation of bandwidth in semiparametric kernel estimation of unknown probability mass and regression functions of count data," Computational Statistics, Springer, vol. 31(1), pages 189-206, March.
    6. Ziane Yasmina & Zougab Nabil & Adjabi Smail, 2021. "Body tail adaptive kernel density estimation for nonnegative heavy-tailed data," Monte Carlo Methods and Applications, De Gruyter, vol. 27(1), pages 57-69, March.

  13. Xibin Zhang & Robert D. Brooks & Maxwell L. King, 2007. "A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation," Monash Econometrics and Business Statistics Working Papers 11/07, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Anastasios Panagiotelis & Michael S. Smith & Peter J Danaher, 2013. "From Amazon to Apple: Modeling Online Retail Sales, Purchase Incidence and Visit Behavior," Monash Econometrics and Business Statistics Working Papers 5/13, Monash University, Department of Econometrics and Business Statistics.
    2. Cui, Zhenyu & Kirkby, J. Lars & Nguyen, Duy, 2021. "A data-driven framework for consistent financial valuation and risk measurement," European Journal of Operational Research, Elsevier, vol. 289(1), pages 381-398.
    3. Song Li & Mervyn J. Silvapulle & Param Silvapulle & Xibin Zhang, 2015. "Bayesian Approaches to Nonparametric Estimation of Densities on the Unit Interval," Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 394-412, March.
    4. Xixuan Han & Boyu Wei & Hailiang Yang, 2018. "Index Options And Volatility Derivatives In A Gaussian Random Field Risk-Neutral Density Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(04), pages 1-41, June.
    5. Oliver Morell & Dennis Otto & Roland Fried, 2013. "On robust cross-validation for nonparametric smoothing," Computational Statistics, Springer, vol. 28(4), pages 1617-1637, August.
    6. Rong Zhang & Brett A. Inder & Xibin Zhang, 2012. "Parameter estimation for a discrete-response model with double rules of sample selection: A Bayesian approach," Monash Econometrics and Business Statistics Working Papers 5/12, Monash University, Department of Econometrics and Business Statistics.
    7. Han Shang, 2014. "Bayesian bandwidth estimation for a semi-functional partial linear regression model with unknown error density," Computational Statistics, Springer, vol. 29(3), pages 829-848, June.
    8. Shang, Han Lin, 2013. "Bayesian bandwidth estimation for a nonparametric functional regression model with unknown error density," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 185-198.
    9. Zhang, Rong & Inder, Brett A. & Zhang, Xibin, 2015. "Bayesian estimation of a discrete response model with double rules of sample selection," Computational Statistics & Data Analysis, Elsevier, vol. 86(C), pages 81-96.
    10. Jan Koláček & Ivana Horová, 2017. "Bandwidth matrix selectors for kernel regression," Computational Statistics, Springer, vol. 32(3), pages 1027-1046, September.
    11. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2016. "Bayesian Bandwidth Selection for a Nonparametric Regression Model with Mixed Types of Regressors," Econometrics, MDPI, vol. 4(2), pages 1-27, April.
    12. Zhang, Xibin & King, Maxwell L. & Shang, Han Lin, 2014. "A sampling algorithm for bandwidth estimation in a nonparametric regression model with a flexible error density," Computational Statistics & Data Analysis, Elsevier, vol. 78(C), pages 218-234.
    13. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2011. "Bayesian estimation of bandwidths for a nonparametric regression model with a flexible error density," Monash Econometrics and Business Statistics Working Papers 10/11, Monash University, Department of Econometrics and Business Statistics.
    14. Guohua Feng & Chuan Wang & Xibin Zhang, 2019. "Estimation of inefficiency in stochastic frontier models: a Bayesian kernel approach," Journal of Productivity Analysis, Springer, vol. 51(1), pages 1-19, February.
    15. Tristan Senga Kiessé & Nabil Zougab & Célestin C. Kokonendji, 2016. "Bayesian estimation of bandwidth in semiparametric kernel estimation of unknown probability mass and regression functions of count data," Computational Statistics, Springer, vol. 31(1), pages 189-206, March.
    16. Filippone, Maurizio & Sanguinetti, Guido, 2011. "Approximate inference of the bandwidth in multivariate kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3104-3122, December.
    17. Dalderop, Jeroen, 2020. "Nonparametric filtering of conditional state-price densities," Journal of Econometrics, Elsevier, vol. 214(2), pages 295-325.
    18. Ana M. Monteiro & Antonio A. F. Santos, 2020. "Conditional risk-neutral density from option prices by local polynomial kernel smoothing with no-arbitrage constraints," Review of Derivatives Research, Springer, vol. 23(1), pages 41-61, April.
    19. Li, Yong & Zhang, Mingzhi & Zhang, Yonghui, 2022. "Sequential Bayesian bandwidth selection for multivariate kernel regression with applications," Economic Modelling, Elsevier, vol. 112(C).
    20. Feng, Guohua & Zhang, Xiaohui, 2014. "Returns to scale at large banks in the US: A random coefficient stochastic frontier approach," Journal of Banking & Finance, Elsevier, vol. 39(C), pages 135-145.
    21. Hart, Jeffrey D. & Choi, Taeryon & Yi, Seongbaek, 2016. "Frequentist nonparametric goodness-of-fit tests via marginal likelihood ratios," Computational Statistics & Data Analysis, Elsevier, vol. 96(C), pages 120-132.
    22. Rong Zhang & Brett A. Inder & Xibin Zhang, 2013. "Bayesian estimation of a discrete response model with double rules of sample selection," Monash Econometrics and Business Statistics Working Papers 24/13, Monash University, Department of Econometrics and Business Statistics.

  14. Param Silvapulle & Xibin Zhang, 2006. "Assessing Dependence Changes in the Asian Financial Market Returns Using Plots Based on Nonparametric Measures," Monash Econometrics and Business Statistics Working Papers 9/06, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Nguyen, Cuong C. & Bhatti, M. Ishaq, 2012. "Copula model dependency between oil prices and stock markets: Evidence from China and Vietnam," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(4), pages 758-773.

  15. Xibin Zhang & Maxwell L. King & Rob J. Hyndman, 2004. "Bandwidth Selection for Multivariate Kernel Density Estimation Using MCMC," Monash Econometrics and Business Statistics Working Papers 9/04, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Zhang, Xibin & King, Maxwell L., 2008. "Box-Cox stochastic volatility models with heavy-tails and correlated errors," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 549-566, June.
    2. Chauveau, Didier & Hoang, Vy Thuy Lynh, 2016. "Nonparametric mixture models with conditionally independent multivariate component densities," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 1-16.
    3. H. Poulos, 2010. "Spatially explicit mapping of hurricane risk in New England, USA using ArcGIS," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 54(3), pages 1015-1023, September.
    4. Kenneth L. Sørensen & Rune Vejlin, 2014. "Return To Experience And Initial Wage Level: Do Low Wage Workers Catch Up?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(6), pages 984-1006, September.

  16. Xibin Zhang & Maxwell L. King, 2004. "Box-Cox Stochastic Volatility Models with Heavy-Tails and Correlated Errors," Monash Econometrics and Business Statistics Working Papers 26/04, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Zhang, Xibin & King, Maxwell L. & Hyndman, Rob J., 2006. "A Bayesian approach to bandwidth selection for multivariate kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 50(11), pages 3009-3031, July.
    2. Kaeck, Andreas & Rodrigues, Paulo & Seeger, Norman J., 2017. "Equity index variance: Evidence from flexible parametric jump–diffusion models," Journal of Banking & Finance, Elsevier, vol. 83(C), pages 85-103.
    3. Zhang, Xibin & King, Maxwell L., 2008. "Box-Cox stochastic volatility models with heavy-tails and correlated errors," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 549-566, June.
    4. Gong, Xu & Wen, Fenghua & Xia, X.H. & Huang, Jianbai & Pan, Bin, 2017. "Investigating the risk-return trade-off for crude oil futures using high-frequency data," Applied Energy, Elsevier, vol. 196(C), pages 152-161.
    5. Harvey, A. & Chakravarty, T., 2008. "Beta-t-(E)GARCH," Cambridge Working Papers in Economics 0840, Faculty of Economics, University of Cambridge.
    6. Xibin Zhang & Maxwell L. King, 2011. "Bayesian semiparametric GARCH models," Monash Econometrics and Business Statistics Working Papers 24/11, Monash University, Department of Econometrics and Business Statistics.
    7. Xibin Zhang & Maxwell L. King, 2013. "Gaussian kernel GARCH models," Monash Econometrics and Business Statistics Working Papers 19/13, Monash University, Department of Econometrics and Business Statistics.
    8. Zhongxian Men & Adam W. Kolkiewicz & Tony S. Wirjanto, 2019. "Threshold Stochastic Conditional Duration Model for Financial Transaction Data," JRFM, MDPI, vol. 12(2), pages 1-21, May.
    9. María José Rodríguez & Esther Ruiz, 2012. "Revisiting Several Popular GARCH Models with Leverage Effect: Differences and Similarities," Journal of Financial Econometrics, Oxford University Press, vol. 10(4), pages 637-668, September.
    10. Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2021. "Multiscale Stochastic Volatility Model with Heavy Tails and Leverage Effects," JRFM, MDPI, vol. 14(5), pages 1-28, May.
    11. Georgios Tsiotas, 2009. "On the use of non-linear transformations in Stochastic Volatility models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(4), pages 555-583, November.
    12. Rodríguez, Mª José & Ruiz Ortega, Esther, 2009. "GARCH models with leverage effect : differences and similarities," DES - Working Papers. Statistics and Econometrics. WS ws090302, Universidad Carlos III de Madrid. Departamento de Estadística.
    13. Weigand, Roland, 2014. "Matrix Box-Cox Models for Multivariate Realized Volatility," University of Regensburg Working Papers in Business, Economics and Management Information Systems 478, University of Regensburg, Department of Economics.
    14. Tingguo Zheng & Tao Song, 2014. "A Realized Stochastic Volatility Model With Box-Cox Transformation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 593-605, October.
    15. Zhongxian Men & Adam W. Kolkiewicz & Tony S. Wirjanto, 2013. "Bayesian Inference of Asymmetric Stochastic Conditional Duration Models," Working Paper series 28_13, Rimini Centre for Economic Analysis.

  17. Y.K. Tse & Xibin Zhang, 2003. "A Monte Carlo Investigation of Some Tests for Stochastic Dominance," Monash Econometrics and Business Statistics Working Papers 7/03, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Linton, Oliver & Maasoumi, Esfandiar & Whang, Yoon-Jae, 2002. "Consistent testing for stochastic dominance: a subsampling approach," LSE Research Online Documents on Economics 24927, London School of Economics and Political Science, LSE Library.
    2. Guo, Xu & Wong, Wing-Keung & Zhu, Lixing, 2013. "Make Almost Stochastic Dominance really Almost," MPRA Paper 49745, University Library of Munich, Germany.
    3. Lean, H.H. & McAleer, M.J. & Wong, W.-K., 2013. "Risk-averse and Risk-seeking Investor Preferences for Oil Spot and Futures," Econometric Institute Research Papers EI 2013-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Daniel Sotelsek-Salem & Ismael Ahamdanech-Zarco & John Bishop, 2012. "Dominance testing for ‘pro-poor’ growth with an application to European growth," Empirical Economics, Springer, vol. 43(2), pages 723-739, October.
    5. Thomas C. Chiang & Hooi Hooi Lean & Wing-Keung Wong, 2008. "Do REITs Outperform Stocks and Fixed-Income Assets? New Evidence from Mean-Variance and Stochastic Dominance Approaches," JRFM, MDPI, vol. 1(1), pages 1-40, December.
    6. Marcus Asplund & Volker Nocke, 2003. "Firm Turnover in Imperfectly Competitive Markets," PIER Working Paper Archive 03-010, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    7. Hooi Hooi Lean & Michael McAleer & Wing-Keung Wong, 2010. "Investor Preferences for Oil Spot and Futures Based on Mean-Variance and Stochastic Dominance," Working Papers in Economics 10/22, University of Canterbury, Department of Economics and Finance.
    8. Abre-Rehmat Qurat-ul-Ann & Faisal Mehmood Mirza, 2021. "Multidimensional Energy Poverty in Pakistan: Empirical Evidence from Household Level Micro Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(1), pages 211-258, May.
    9. Maasoumi, Esfandiar & Heshmati, Almas, 2005. "Evaluating Dominance Ranking of PSID Incomes by Various Household Attributes," IZA Discussion Papers 1727, Institute of Labor Economics (IZA).
    10. Dahl, Bruce L. & Wilson, William W. & Nganje, William E., 2004. "Stochastic Dominance in Wheat Variety Development and Release Strategies," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(1), pages 1-18, April.
    11. Michael D. Grubb, 2009. "Selling to Overconfident Consumers," American Economic Review, American Economic Association, vol. 99(5), pages 1770-1807, December.
    12. Oliver Linton & Kyungchul Song & Yoon-Jae Whang, 2008. "Bootstrap Tests of Stochastic Dominance with AsymptoticSimilarity on the Boundary," STICERD - Econometrics Paper Series 527, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    13. Thi Hong Van Hoang & Hooi Hooi Lean & Wing-Keung Wong, 2013. "Is Gold Good for Portfolio Diversification? A Stochastic Dominance Analysis of the Paris Stock Exchange," Working Papers 05-13, Association Française de Cliométrie (AFC).
    14. Dominic Gasbarro & Wing-Keung Wong & J. Kenton Zumwalt, 2007. "Stochastic Dominance Analysis of iShares," The European Journal of Finance, Taylor & Francis Journals, vol. 13(1), pages 89-101.
    15. Wong, Wing-Keung & Phoon, Kok Fai & Lean, Hooi Hooi, 2008. "Stochastic dominance analysis of Asian hedge funds," Pacific-Basin Finance Journal, Elsevier, vol. 16(3), pages 204-223, June.
    16. David Maddison, 2005. "Are There Too Many Revivals on Broadway? A Stochastic Dominance Approach," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 29(4), pages 325-334, November.
    17. Lean, H.H. & McAleer, M.J. & Wong, W.-K., 2010. "Market Efficiency of Oil Spot and Futures: A Stochastic Dominance Approach," Econometric Institute Research Papers EI 2010-11, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    18. Lean, Hooi Hooi & Smyth, Russell & Wong, Wing-Keung, 2007. "Revisiting calendar anomalies in Asian stock markets using a stochastic dominance approach," Journal of Multinational Financial Management, Elsevier, vol. 17(2), pages 125-141, April.
    19. Heshmati, Almas & Rudolf, Robert, 2013. "Income vs. Consumption Inequality in South Korea: Evaluating Stochastic Dominance Rankings by Various Household Attributes," IZA Discussion Papers 7731, Institute of Labor Economics (IZA).
    20. Mishra, Vinod & Smyth, Russell, 2010. "An examination of the impact of India's performance in one-day cricket internationals on the Indian stock market," Pacific-Basin Finance Journal, Elsevier, vol. 18(3), pages 319-334, June.
    21. Hooi Lean & Kok Phoon & Wing-Keung Wong, 2013. "Stochastic dominance analysis of CTA funds," Review of Quantitative Finance and Accounting, Springer, vol. 40(1), pages 155-170, January.
    22. Duangkamon Chotikapanich & William E. Griffiths, 2006. "Bayesian Assessment of Lorenz and Stochastic Dominance in Income Distributions," Department of Economics - Working Papers Series 960, The University of Melbourne.

  18. Y.K. Tse & Xibin Zhang & Jun Yu, 2002. "Estimation of Hyperbolic Diffusion Using MCMC Method," Monash Econometrics and Business Statistics Working Papers 18/02, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Zhang, Xibin & King, Maxwell L., 2008. "Box-Cox stochastic volatility models with heavy-tails and correlated errors," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 549-566, June.
    2. Rob L. Hyndman & Xibin Zhang & Maxwell L. King,, 2004. "Bandwidth Selection for Multivariate Kernel Density Estimation Using MCMC," Econometric Society 2004 Australasian Meetings 120, Econometric Society.
    3. Peter C.B. Phillips & Jun Yu, 2007. "Maximum Likelihood and Gaussian Estimation of Continuous Time Models in Finance," Cowles Foundation Discussion Papers 1597, Cowles Foundation for Research in Economics, Yale University.
    4. Song Li & Mervyn J. Silvapulle & Param Silvapulle & Xibin Zhang, 2015. "Bayesian Approaches to Nonparametric Estimation of Densities on the Unit Interval," Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 394-412, March.
    5. Xibin Zhang & Robert D. Brooks & Maxwell L. King, 2007. "A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation," Monash Econometrics and Business Statistics Working Papers 11/07, Monash University, Department of Econometrics and Business Statistics.
    6. Han Shang, 2014. "Bayesian bandwidth estimation for a semi-functional partial linear regression model with unknown error density," Computational Statistics, Springer, vol. 29(3), pages 829-848, June.
    7. Denitsa Stefanova, 2012. "Stock Market Asymmetries: A Copula Diffusion," Tinbergen Institute Discussion Papers 12-125/IV/DSF45, Tinbergen Institute.
    8. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2016. "Bayesian Bandwidth Selection for a Nonparametric Regression Model with Mixed Types of Regressors," Econometrics, MDPI, vol. 4(2), pages 1-27, April.
    9. Zhang, Xibin & King, Maxwell L. & Shang, Han Lin, 2014. "A sampling algorithm for bandwidth estimation in a nonparametric regression model with a flexible error density," Computational Statistics & Data Analysis, Elsevier, vol. 78(C), pages 218-234.
    10. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2011. "Bayesian estimation of bandwidths for a nonparametric regression model with a flexible error density," Monash Econometrics and Business Statistics Working Papers 10/11, Monash University, Department of Econometrics and Business Statistics.
    11. Malmsten, Hans & Teräsvirta, Timo, 2004. "Stylized Facts of Financial Time Series and Three Popular Models of Volatility," SSE/EFI Working Paper Series in Economics and Finance 563, Stockholm School of Economics, revised 03 Sep 2004.

  19. Jun Yu & Zhenlin Yang & Xibin Zhang, 2002. "A Class of Nonlinear Stochastic Volatility Models and Its Implications on Pricing Currency Options," Monash Econometrics and Business Statistics Working Papers 17/02, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Kaeck, Andreas & Rodrigues, Paulo & Seeger, Norman J., 2017. "Equity index variance: Evidence from flexible parametric jump–diffusion models," Journal of Banking & Finance, Elsevier, vol. 83(C), pages 85-103.
    2. Zhang, Xibin & King, Maxwell L., 2008. "Box-Cox stochastic volatility models with heavy-tails and correlated errors," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 549-566, June.
    3. Casas, Isabel & Lopes Moreira Da Veiga, María Helena, 2019. "Exploring option pricing and hedging via volatility asymmetry," DES - Working Papers. Statistics and Econometrics. WS 28234, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Jun Yu, 2010. "Simulation-based Estimation Methods for Financial Time Series Models," Working Papers 19-2010, Singapore Management University, School of Economics.
    5. Goodwin, Roger L, 2015. "Random Variables, Their Properties, and Deviational Ellipses: In Map Point and Excel, v 4.3," MPRA Paper 64863, University Library of Munich, Germany, revised 07 Jun 2015.
    6. Rachidi Kotchoni, 2012. "Applications of the Characteristic Function Based Continuum GMM in Finance," Post-Print hal-00867795, HAL.
    7. Mao, Xiuping & Czellar, Veronika & Ruiz, Esther & Veiga, Helena, 2020. "Asymmetric stochastic volatility models: Properties and particle filter-based simulated maximum likelihood estimation," Econometrics and Statistics, Elsevier, vol. 13(C), pages 84-105.
    8. Zhongxian Men & Adam W. Kolkiewicz & Tony S. Wirjanto, 2019. "Threshold Stochastic Conditional Duration Model for Financial Transaction Data," JRFM, MDPI, vol. 12(2), pages 1-21, May.
    9. Daniel PREVE & Anders ERIKSSON & Jun YU, 2009. "Forecasting Realized Volatility Using A Nonnegative Semiparametric Model," Working Papers 22-2009, Singapore Management University, School of Economics.
    10. Xiao, Wei-Lin & Zhang, Wei-Guo & Zhang, Xi-Li & Wang, Ying-Luo, 2010. "Pricing currency options in a fractional Brownian motion with jumps," Economic Modelling, Elsevier, vol. 27(5), pages 935-942, September.
    11. Carmen Broto & Esther Ruiz, 2004. "Estimation methods for stochastic volatility models: a survey," Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 613-649, December.
    12. Mao, Xiuping & Ruiz, Esther & Veiga, Helena, 2017. "Threshold stochastic volatility: Properties and forecasting," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1105-1123.
    13. Goodwin, Roger L, 2014. "Random Variables, Their Properties, and Deviational Ellipses: In Map Point and Excel, v 4.0," MPRA Paper 64391, University Library of Munich, Germany, revised 15 May 2015.
    14. Foschi, Paolo & Pascucci, Andrea, 2009. "Calibration of a path-dependent volatility model: Empirical tests," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2219-2235, April.
    15. Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2021. "Multiscale Stochastic Volatility Model with Heavy Tails and Leverage Effects," JRFM, MDPI, vol. 14(5), pages 1-28, May.
    16. Georgios Tsiotas, 2009. "On the use of non-linear transformations in Stochastic Volatility models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(4), pages 555-583, November.
    17. Mao, Xiuping & Ruiz Ortega, Esther & Lopes Moreira Da Veiga, María Helena, 2013. "One for all : nesting asymmetric stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS ws131110, Universidad Carlos III de Madrid. Departamento de Estadística.
    18. Kawakatsu, Hiroyuki, 2007. "Specification and estimation of discrete time quadratic stochastic volatility models," Journal of Empirical Finance, Elsevier, vol. 14(3), pages 424-442, June.
    19. Weigand, Roland, 2014. "Matrix Box-Cox Models for Multivariate Realized Volatility," University of Regensburg Working Papers in Business, Economics and Management Information Systems 478, University of Regensburg, Department of Economics.
    20. Ruiz Ortega, Esther & Veiga, Helena, 2006. "Modelling long-memory volatilities with leverage effect: ALMSV versus FIEGARCH," DES - Working Papers. Statistics and Econometrics. WS ws066016, Universidad Carlos III de Madrid. Departamento de Estadística.
    21. Tingguo Zheng & Tao Song, 2014. "A Realized Stochastic Volatility Model With Box-Cox Transformation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 593-605, October.
    22. Borovkova, Svetlana & Permana, Ferry J., 2009. "Implied volatility in oil markets," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2022-2039, April.
    23. Wang, Nianling & Lou, Zhusheng, 2023. "Sequential Bayesian analysis for semiparametric stochastic volatility model with applications," Economic Modelling, Elsevier, vol. 123(C).
    24. Didit Budi Nugroho & Takayuki Morimoto, 2019. "Incorporating Realized Quarticity into a Realized Stochastic Volatility Model," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 26(4), pages 495-528, December.
    25. Giannikis, D. & Vrontos, I.D. & Dellaportas, P., 2008. "Modelling nonlinearities and heavy tails via threshold normal mixture GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1549-1571, January.
    26. Georgios Tsiotas, 2020. "On the use of power transformations in CAViaR models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 296-312, March.

Articles

  1. Shang Han Lin & Zhang Xibin, 2022. "Bayesian bandwidth estimation for local linear fitting in nonparametric regression models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 26(1), pages 55-71, February.

    Cited by:

    1. Litimein, Ouahiba & Laksaci, Ali & Mechab, Boubaker & Bouzebda, Salim, 2023. "Local linear estimate of the functional expectile regression," Statistics & Probability Letters, Elsevier, vol. 192(C).

  2. Hu, Shuowen & Poskitt, D.S. & Zhang, Xibin, 2021. "Bayesian estimation for a semiparametric nonlinear volatility model," Economic Modelling, Elsevier, vol. 98(C), pages 361-370.

    Cited by:

    1. Bucci, Andrea & Palomba, Giulio & Rossi, Eduardo, 2023. "The role of uncertainty in forecasting volatility comovements across stock markets," Economic Modelling, Elsevier, vol. 125(C).
    2. Wang, Nianling & Lou, Zhusheng, 2023. "Sequential Bayesian analysis for semiparametric stochastic volatility model with applications," Economic Modelling, Elsevier, vol. 123(C).

  3. Liddle, Brantley & Smyth, Russell & Zhang, Xibin, 2020. "Time-varying income and price elasticities for energy demand: Evidence from a middle-income panel," Energy Economics, Elsevier, vol. 86(C).

    Cited by:

    1. Uddin, Md. Main & Mishra, Vinod & Smyth, Russell, 2020. "Income inequality and CO2 emissions in the G7, 1870–2014: Evidence from non-parametric modelling," Energy Economics, Elsevier, vol. 88(C).
    2. Sarkar, Biswajit & Seok, Hyesung & Jana, Tapas Kumar & Dey, Bikash Koli, 2023. "Is the system reliability profitable for retailing and consumer service of a dynamical system under cross-price elasticity of demand?," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    3. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2020. "The Environmental Kuznets Curve across Australian states and territories," Energy Economics, Elsevier, vol. 90(C).
    4. Gulasekaran Rajaguru & Safdar Ullah Khan, 2021. "Causality between Energy Consumption and Economic Growth in the Presence of Growth Volatility: Multi-Country Evidence," JRFM, MDPI, vol. 14(10), pages 1-26, October.
    5. Liddle, Brantley & Huntington, Hillard, 2020. "‘On the Road Again’: A 118 country panel analysis of gasoline and diesel demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 151-167.
    6. Lee, Chien-Chiang & Ho, Shan-Ju, 2022. "Impacts of export diversification on energy intensity, renewable energy, and waste energy in 121 countries: Do environmental regulations matter?," Renewable Energy, Elsevier, vol. 199(C), pages 1510-1522.
    7. Moghaddam, Mohsen Bakhshi & Lloyd-Ellis, Huw, 2022. "Heterogeneous effects of oil price fluctuations: Evidence from a nonparametric panel data model in Canada," Energy Economics, Elsevier, vol. 110(C).
    8. Gao, Jiti & Peng, Bin & Smyth, Russell, 2021. "On income and price elasticities for energy demand: A panel data study," Energy Economics, Elsevier, vol. 96(C).
    9. Yoosoon Chang & Yongok Choi & Chang Sik Kim & J. Isaac Miller & Joon Y. Park, 2024. "Common Trends and Country Specific Heterogeneities in Long-Run World Energy Consumption," CAMA Working Papers 2024-04, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    10. Awaworyi Churchill, Sefa & Baako, Kingsley Tetteh & Mintah, Kwabena & Zhang, Quanda, 2021. "Transport infrastructure and house prices in the long run," Transport Policy, Elsevier, vol. 112(C), pages 1-12.
    11. Brantley Liddle, 2022. "What Is the Temporal Path of the GDP Elasticity of Energy Consumption in OECD Countries? An Assessment of Previous Findings and New Evidence," Energies, MDPI, vol. 15(10), pages 1-12, May.
    12. Eleyan, Mohammed I.Abu & Çatık, Abdurrahman Nazif & Balcılar, Mehmet & Ballı, Esra, 2021. "Are long-run income and price elasticities of oil demand time-varying? New evidence from BRICS countries," Energy, Elsevier, vol. 229(C).
    13. Liddle, Brantley & Huntington, Hillard, 2021. "There’s Technology Improvement, but is there Economy-wide Energy Leapfrogging? A Country Panel Analysis," World Development, Elsevier, vol. 140(C).
    14. Wang, Shubin & Sun, Shaolong & Zhao, Erlong & Wang, Shouyang, 2021. "Urban and rural differences with regional assessment of household energy consumption in China," Energy, Elsevier, vol. 232(C).
    15. Ivanovski, Kris & Hailemariam, Abebe, 2022. "Time-varying geopolitical risk and oil prices," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 206-221.
    16. Gorus, Muhammed Sehid & Karagol, Erdal Tanas, 2022. "Reactions of energy intensity, energy efficiency, and activity indexes to income and energy price changes: The panel data evidence from OECD countries," Energy, Elsevier, vol. 254(PA).
    17. Salim Hamza Ringim & Abdulkareem Alhassan & Hasan Güngör & Festus Victor Bekun, 2022. "Economic Policy Uncertainty and Energy Prices: Empirical Evidence from Multivariate DCC-GARCH Models," Energies, MDPI, vol. 15(10), pages 1-18, May.
    18. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris, 2021. "R&D expenditure and energy consumption in OECD nations," Energy Economics, Elsevier, vol. 100(C).
    19. Susana Silva & Isabel Soares & Oscar Afonso, 2021. "Assessing the double dividend of a third-generation environmental tax reform with resource substitution," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(10), pages 15145-15156, October.
    20. Eshagh Mansourkiaee & Hussein Moghaddam, 2022. "Econometric Analysis of Residential Sector Gas Demand Elasticities in Gas Exporting Countries," Energy and Environment Research, Canadian Center of Science and Education, vol. 11(2), pages 1-1, December.
    21. Bhattacharya, Mita & Inekwe, John & Yan, Eric, 2021. "Dynamics of energy poverty: Evidence from nonparametric estimates across the ASEAN+6 region," Energy Economics, Elsevier, vol. 103(C).
    22. Zihan Zhang & Enping Li & Guowei Zhang, 2023. "How Efficient China’s Tiered Pricing Is for Household Electricity: Evidence from Survey Data," Sustainability, MDPI, vol. 15(2), pages 1-17, January.
    23. Wang, Banban & Wei, Jie & Tan, Xiujie & Su, Bin, 2021. "The sectorally heterogeneous and time-varying price elasticities of energy demand in China," Energy Economics, Elsevier, vol. 102(C).
    24. Liddle, Brantley & Huntington, Hillard, 2021. "How prices, income, and weather shape household electricity demand in high-income and middle-income countries," Energy Economics, Elsevier, vol. 95(C).
    25. Vahid Mohamad Taghvaee & Abbas Assari Arani & Susanne Soretz & Lotfali Agheli, 2023. "Diesel demand elasticities and sustainable development pillars of economy, environment and social (health): comparing two strategies of subsidy removal and energy efficiency," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(3), pages 2285-2315, March.

  4. Guohua Feng & Chuan Wang & Xibin Zhang, 2019. "Estimation of inefficiency in stochastic frontier models: a Bayesian kernel approach," Journal of Productivity Analysis, Springer, vol. 51(1), pages 1-19, February.

    Cited by:

    1. Mike G. Tsionas, 2019. "Robust Bayesian Inference in Stochastic Frontier Models," JRFM, MDPI, vol. 12(4), pages 1-9, December.
    2. Guohua Feng & Chuan Wang, 2021. "Determinants of profitability of community banks in the USA: a cost-frontier-based decomposition approach," Empirical Economics, Springer, vol. 60(6), pages 2969-2992, June.
    3. Li, Huijuan & Cai, Weihong & Li, Wenxiu, 2021. "Does global value chains participation improve skill premium? Mediating role of skill-biased technological change," Economic Modelling, Elsevier, vol. 99(C).

  5. Hailemariam, Abebe & Smyth, Russell & Zhang, Xibin, 2019. "Oil prices and economic policy uncertainty: Evidence from a nonparametric panel data model," Energy Economics, Elsevier, vol. 83(C), pages 40-51.

    Cited by:

    1. Salem, Leila Ben & Nouira, Ridha & Jeguirim, Khaled & Rault, Christophe, 2022. "The Determinants of Crude Oil Prices: Evidence from ARDL and Nonlinear ARDL Approaches," IZA Discussion Papers 15666, Institute of Labor Economics (IZA).
    2. Wen, Jun & Khalid, Samia & Mahmood, Hamid & Zakaria, Muhammad, 2021. "Symmetric and asymmetric impact of economic policy uncertainty on food prices in China: A new evidence," Resources Policy, Elsevier, vol. 74(C).
    3. Assaf, Ata & Charif, Husni & Mokni, Khaled, 2021. "Dynamic connectedness between uncertainty and energy markets: Do investor sentiments matter?," Resources Policy, Elsevier, vol. 72(C).
    4. Das, Debojyoti & Bhatia, Vaneet & Kumar, Surya Bhushan & Basu, Sankarshan, 2022. "Do precious metals hedge crude oil volatility jumps?," International Review of Financial Analysis, Elsevier, vol. 83(C).
    5. Uddin, Md. Main & Mishra, Vinod & Smyth, Russell, 2020. "Income inequality and CO2 emissions in the G7, 1870–2014: Evidence from non-parametric modelling," Energy Economics, Elsevier, vol. 88(C).
    6. Yingce Yang & Junjie Guo & Ruihong He, 2023. "The Asymmetric Impact of the Oil Price and Disaggregate Shocks on Economic Policy Uncertainty: Evidence From China," SAGE Open, , vol. 13(2), pages 21582440231, June.
    7. Li, Xiao-Lin & Li, Jingya & Wang, Jia & Si, Deng-Kui, 2021. "Trade policy uncertainty, political connection and government subsidy: Evidence from Chinese energy firms," Energy Economics, Elsevier, vol. 99(C).
    8. Claudiu Tiberiu Albulescu, 2020. "Coronavirus and oil price crash," Working Papers hal-02507184, HAL.
    9. Sheng, Xin & Gupta, Rangan & Ji, Qiang, 2020. "The impacts of structural oil shocks on macroeconomic uncertainty: Evidence from a large panel of 45 countries," Energy Economics, Elsevier, vol. 91(C).
    10. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2020. "The Environmental Kuznets Curve across Australian states and territories," Energy Economics, Elsevier, vol. 90(C).
    11. Xin Sheng & Rangan Gupta & Afees A. Salisu & Elie Bouri, 2021. "OPEC News and Exchange Rate Forecasting Using Dynamic Bayesian Learning," Working Papers 202101, University of Pretoria, Department of Economics.
    12. William Ginn, 2022. "Climate Disasters and the Macroeconomy: Does State-Dependence Matter? Evidence for the US," Economics of Disasters and Climate Change, Springer, vol. 6(1), pages 141-161, March.
    13. Scarcioffolo, Alexandre R. & Etienne, Xiaoli L., 2021. "Regime-switching energy price volatility: The role of economic policy uncertainty," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 336-356.
    14. Bonato, Matteo & Çepni, Oğuzhan & Gupta, Rangan & Pierdzioch, Christian, 2021. "Do oil-price shocks predict the realized variance of U.S. REITs?," Energy Economics, Elsevier, vol. 104(C).
    15. Anjan K. Saha & Vinod Mishra & Russell Smyth, 2021. "Financial development and top income shares in OECD countries," Southern Economic Journal, John Wiley & Sons, vol. 87(3), pages 952-978, January.
    16. Moghaddam, Mohsen Bakhshi & Lloyd-Ellis, Huw, 2022. "Heterogeneous effects of oil price fluctuations: Evidence from a nonparametric panel data model in Canada," Energy Economics, Elsevier, vol. 110(C).
    17. Tunc, Ahmet & Kocoglu, Mustafa & Aslan, Alper, 2022. "Time-varying characteristics of the simultaneous interactions between economic uncertainty, international oil prices and GDP: A novel approach for Germany," Resources Policy, Elsevier, vol. 77(C).
    18. Apergis, Nicholas & Hayat, Tasawar & Saeed, Tareq, 2021. "US partisan conflict uncertainty and oil prices," Energy Policy, Elsevier, vol. 150(C).
    19. Saban Nazlioglu & Rangan Gupta & Alper Gormus & Ugur Soytas, 2019. "Price and Volatility Linkages between International REITs and Oil Markets," Working Papers 201954, University of Pretoria, Department of Economics.
    20. Fasanya, Ismail O. & Adekoya, Oluwasegun B. & Adetokunbo, Abiodun M., 2021. "On the connection between oil and global foreign exchange markets: The role of economic policy uncertainty," Resources Policy, Elsevier, vol. 72(C).
    21. Gilles Dufrénot & William Ginn & Marc Pourroy, 2023. "ENSO Climate Patterns on Global Economic Conditions," Working Papers hal-04064759, HAL.
    22. Saiful Badli & Raja Masbar & Nazamuddin Nazamuddin & Muhammad Nasir & T. Zulham & Jumadil Saputra & Syahril Syahril & Helmi Noviar, 2020. "Investigating the Efficiency of Government Expenditure on Energy Consumption (Fuel) Subsidy Policy in Indonesia: An Application of Stochastic Frontier Model," International Journal of Energy Economics and Policy, Econjournals, vol. 10(4), pages 161-165.
    23. Hai-Jie Wang & Yong Geng & Xi-Qiang Xia & Quan-Jing Wang, 2021. "Impact of Economic Policy Uncertainty on Carbon Emissions: Evidence from 137 Multinational Countries," IJERPH, MDPI, vol. 19(1), pages 1-12, December.
    24. Xin Sheng & Rangan Gupta & Oguzhan Cepni, 2022. "Persistence of State-Level Uncertainty of the United States: The Role of Climate Risks," Working Papers 202208, University of Pretoria, Department of Economics.
    25. Awaworyi Churchill, Sefa & Baako, Kingsley Tetteh & Mintah, Kwabena & Zhang, Quanda, 2021. "Transport infrastructure and house prices in the long run," Transport Policy, Elsevier, vol. 112(C), pages 1-12.
    26. Demirer, Riza & Gupta, Rangan & Pierdzioch, Christian & Shahzad, Syed Jawad Hussain, 2020. "The predictive power of oil price shocks on realized volatility of oil: A note," Resources Policy, Elsevier, vol. 69(C).
    27. Yan Ding & Yue Liu & Pierre Failler, 2022. "The Impact of Uncertainties on Crude Oil Prices: Based on a Quantile-on-Quantile Method," Energies, MDPI, vol. 15(10), pages 1-35, May.
    28. Badeeb, Ramez Abubakr & Szulczyk, Kenneth R. & Lean, Hooi Hooi, 2021. "Asymmetries in the effect of oil rent shocks on economic growth: A sectoral analysis from the perspective of the oil curse," Resources Policy, Elsevier, vol. 74(C).
    29. Moghaddam, Mohsen Bakhshi, 2023. "The relationship between oil price changes and economic growth in Canadian provinces: Evidence from a quantile-on-quantile approach," Energy Economics, Elsevier, vol. 125(C).
    30. Borozan, Djula & Lolic Cipcic, Marina, 2022. "Asymmetric and nonlinear oil price pass-through to economic growth in Croatia: Do oil-related policy shocks matter?," Resources Policy, Elsevier, vol. 76(C).
    31. Nong, Huifu & Liu, Hongxiao, 2023. "Measuring the frequency and quantile connectedness between policy categories and global oil price," Resources Policy, Elsevier, vol. 83(C).
    32. Sun, Ting-Ting & Su, Chi-Wei & Mirza, Nawazish & Umar, Muhammad, 2021. "How does trade policy uncertainty affect agriculture commodity prices?," Pacific-Basin Finance Journal, Elsevier, vol. 66(C).
    33. Abebe Hailemariam & Tutsirai Sakutukwa & Ratbek Dzhumashev, 2021. "Long-term determinants of income inequality: evidence from panel data over 1870–2016," Empirical Economics, Springer, vol. 61(4), pages 1935-1958, October.
    34. Elie Bouri & Rangan Gupta & Clement Kweku Kyei & Sowmya Subramaniam, 2020. "High-Frequency Movements of the Term Structure of Interest Rates of the United States: The Role of Oil Market Uncertainty," Working Papers 202085, University of Pretoria, Department of Economics.
    35. Wang, Jiqian & He, Xiaofeng & Ma, Feng & Li, Pan, 2022. "Uncertainty and oil volatility: Evidence from shrinkage method," Resources Policy, Elsevier, vol. 75(C).
    36. Doğan, Buhari & Trabelsi, Nader & Tiwari, Aviral Kumar & Ghosh, Sudeshna, 2023. "Dynamic dependence and causality between crude oil, green bonds, commodities, geopolitical risks, and policy uncertainty," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 36-62.
    37. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2020. "Point and Density Forecasting of Macroeconomic and Financial Uncertainties of the United States," Working Papers 202058, University of Pretoria, Department of Economics.
    38. Sefa Awaworyi Churchill & Bin Peng & Russell Smyth & Quanda Zhang, 2022. "R&D intensity and income inequality in the G7: 1870–2016," Scottish Journal of Political Economy, Scottish Economic Society, vol. 69(3), pages 263-282, July.
    39. Liddle, Brantley & Smyth, Russell & Zhang, Xibin, 2020. "Time-varying income and price elasticities for energy demand: Evidence from a middle-income panel," Energy Economics, Elsevier, vol. 86(C).
    40. Elder, John & Payne, James E., 2023. "Racial and ethnic disparities in unemployment and oil price uncertainty," Energy Economics, Elsevier, vol. 119(C).
    41. Adediran, Idris A. & Yinusa, Olalekan D. & Lakhani, Kanwal Hammad, 2021. "Where lies the silver lining when uncertainty hang dark clouds over the global financial markets?," Resources Policy, Elsevier, vol. 70(C).
    42. Qichang Xie & Yingkun Yan & Xu Wang, 2023. "Assessing the role of foreign direct investment in environmental sustainability: a spatial semiparametric panel approach," Economic Change and Restructuring, Springer, vol. 56(2), pages 1263-1295, April.
    43. Syed Jawad Hussain Shahzad & Rangan Gupta & Riza Demirer & Christian Pierdzioch, 2022. "Oil shocks and directional predictability of macroeconomic uncertainties of developed economies: Evidence from high‐frequency data†," Scottish Journal of Political Economy, Scottish Economic Society, vol. 69(2), pages 169-185, May.
    44. Wang, Yilei & Cheng, Sheng & Cao, Yan, 2022. "How does economic policy uncertainty respond to the global oil price fluctuations? Evidence from BRICS countries," Resources Policy, Elsevier, vol. 79(C).
    45. Dutta, Anupam & Bouri, Elie & Saeed, Tareq, 2021. "News-based equity market uncertainty and crude oil volatility," Energy, Elsevier, vol. 222(C).
    46. Ivanovski, Kris & Hailemariam, Abebe, 2022. "Time-varying geopolitical risk and oil prices," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 206-221.
    47. Yang, Lu & Hamori, Shigeyuki, 2021. "Systemic risk and economic policy uncertainty: International evidence from the crude oil market," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 142-158.
    48. Jun, Xiao & Huang, Wenwei & Guo, Yiting & Cao, Yuqiang & Lu, Meiting, 2023. "Why does economic policy uncertainty increase firm-level pollutant emission?," Economic Modelling, Elsevier, vol. 129(C).
    49. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2021. "Point and density forecasting of macroeconomic and financial uncertainties of the USA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 700-707, July.
    50. Zhang, Feng & Huang, Yongming & Nan, Xiaoli, 2022. "The price volatility of natural resource commodity and global economic policy uncertainty: Evidence from US economy," Resources Policy, Elsevier, vol. 77(C).
    51. Lin, Boqiang & Bai, Rui, 2021. "Oil prices and economic policy uncertainty: Evidence from global, oil importers, and exporters’ perspective," Research in International Business and Finance, Elsevier, vol. 56(C).
    52. Rabeh Khalfaoui & Sakiru Adebola Solarin & Adel Al-Qadasi & Sami Ben Jabeur, 2022. "Dynamic causality interplay from COVID-19 pandemic to oil price, stock market, and economic policy uncertainty: evidence from oil-importing and oil-exporting countries," Post-Print hal-03797569, HAL.
    53. Bei Zhang & Xiaoqing Ai & Xingming Fang & Shi Chen, 2022. "The Transmission Mechanisms and Impacts of Oil Price Fluctuations: Evidence from DSGE Model," Energies, MDPI, vol. 15(16), pages 1-20, August.
    54. Zhang, Yue-Jun & Yan, Xing-Xing, 2020. "The impact of US economic policy uncertainty on WTI crude oil returns in different time and frequency domains," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 750-768.
    55. Ioannis Dokas & Georgios Oikonomou & Minas Panagiotidis & Eleftherios Spyromitros, 2023. "Macroeconomic and Uncertainty Shocks’ Effects on Energy Prices: A Comprehensive Literature Review," Energies, MDPI, vol. 16(3), pages 1-35, February.
    56. Qin, Meng & Su, Chi-Wei & Hao, Lin-Na & Tao, Ran, 2020. "The stability of U.S. economic policy: Does it really matter for oil price?," Energy, Elsevier, vol. 198(C).
    57. Salim Hamza Ringim & Abdulkareem Alhassan & Hasan Güngör & Festus Victor Bekun, 2022. "Economic Policy Uncertainty and Energy Prices: Empirical Evidence from Multivariate DCC-GARCH Models," Energies, MDPI, vol. 15(10), pages 1-18, May.
    58. Huang, Jianbai & Dong, Xuesong & Zhang, Hongwei & Liu, Jia & Gao, Wang, 2022. "Dynamic and frequency-domain spillover among within and cross-country policy uncertainty, crude oil and gold market: Evidence from US and China," Resources Policy, Elsevier, vol. 78(C).
    59. Huang, Yisu & Xu, Weiju & Huang, Dengshi & Zhao, Chenchen, 2023. "Chinese crude oil futures volatility and sustainability: An uncertainty indices perspective," Resources Policy, Elsevier, vol. 80(C).
    60. Nicholas Marinucci & Kris Ivanovski, 2023. "Does Inequality Affect Climate Change? A Regional and Sectoral Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 166(3), pages 705-729, April.
    61. Nakhli, Mohamed Sahbi & Shahbaz, Muhammad & Ben Jebli, Mehdi & Wang, Shizhen, 2022. "Nexus between economic policy uncertainty, renewable & non-renewable energy and carbon emissions: Contextual evidence in carbon neutrality dream of USA," Renewable Energy, Elsevier, vol. 185(C), pages 75-85.
    62. Szczygielski, Jan Jakub & Charteris, Ailie & Bwanya, Princess Rutendo & Brzeszczyński, Janusz, 2023. "Which COVID-19 information really impacts stock markets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
    63. Donadelli, Michael & Gufler, Ivan & Pellizzari, Paolo, 2020. "The macro and asset pricing implications of rising Italian uncertainty: Evidence from a novel news-based macroeconomic policy uncertainty index," Economics Letters, Elsevier, vol. 197(C).
    64. Ruixin Su & Jianguo Du & Fakhar Shahzad & Xingle Long, 2020. "Unveiling the Effect of Mean and Volatility Spillover between the United States Economic Policy Uncertainty and WTI Crude Oil Price," Sustainability, MDPI, vol. 12(16), pages 1-12, August.
    65. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris, 2021. "R&D expenditure and energy consumption in OECD nations," Energy Economics, Elsevier, vol. 100(C).
    66. Xiafei Li & Yu Wei & Xiaodan Chen & Feng Ma & Chao Liang & Wang Chen, 2022. "Which uncertainty is powerful to forecast crude oil market volatility? New evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4279-4297, October.
    67. Mokni, Khaled, 2021. "When, where, and how economic policy uncertainty predicts Bitcoin returns and volatility? A quantiles-based analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 65-73.
    68. Guo, Yangli & He, Feng & Liang, Chao & Ma, Feng, 2022. "Oil price volatility predictability: New evidence from a scaled PCA approach," Energy Economics, Elsevier, vol. 105(C).
    69. He, Huizi & Sun, Mei & Gao, Cuixia & Li, Xiuming, 2021. "Detecting lag linkage effect between economic policy uncertainty and crude oil price: A multi-scale perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    70. Rasool Dehghanzadeh Shahabad & Mehmet Balcilar, 2022. "Modelling the Dynamic Interaction between Economic Policy Uncertainty and Commodity Prices in India: The Dynamic Autoregressive Distributed Lag Approach," Mathematics, MDPI, vol. 10(10), pages 1-21, May.
    71. Wei, Wei & Hu, Haiqing & Chang, Chun-Ping, 2022. "Why the same degree of economic policy uncertainty can produce different outcomes in energy efficiency? New evidence from China," Structural Change and Economic Dynamics, Elsevier, vol. 60(C), pages 467-481.
    72. Liu, Xiaoqin & Wojewodzki, Michal & Cai, Yifei & Sharma, Satish, 2023. "The dynamic relationships between carbon prices and policy uncertainties," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    73. Riza Demirer & Rangan Gupta & Christian Pierdzioch & Syed Jawad Hussain Shahzad, 2021. "A note on oil price shocks and the forecastability of gold realized volatility," Applied Economics Letters, Taylor & Francis Journals, vol. 28(21), pages 1889-1897, December.
    74. Kuamvi Sodji, 2023. "Estimating the link between trade uncertainty, pandemic uncertainty and food price stability in Togo: New evidence for an asymmetric analysis," Review of Development Economics, Wiley Blackwell, vol. 27(2), pages 1113-1134, May.
    75. Bhattacharya, Mita & Inekwe, John & Yan, Eric, 2021. "Dynamics of energy poverty: Evidence from nonparametric estimates across the ASEAN+6 region," Energy Economics, Elsevier, vol. 103(C).
    76. Hang Su & Yong Geng & Xi-Qiang Xia & Quan-Jing Wang, 2022. "Economic Policy Uncertainty, Social Development, Political Regimes and Environmental Quality," IJERPH, MDPI, vol. 19(4), pages 1-15, February.
    77. Jiang, Lan & Jiang, Hua, 2023. "Analysis of predictions considering mineral prices, residential energy, and environmental risk: Evidence from the USA in COP 26 perspective," Resources Policy, Elsevier, vol. 82(C).
    78. Ghazouani, Tarek, 2022. "Dynamic impact of globalization on renewable energy consumption: Non-parametric modelling evidence," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    79. Yao, Yao & Ivanovski, Kris & Inekwe, John & Smyth, Russell, 2020. "Human capital and CO2 emissions in the long run," Energy Economics, Elsevier, vol. 91(C).
    80. Su, Chi-Wei & Huang, Shi-Wen & Qin, Meng & Umar, Muhammad, 2021. "Does crude oil price stimulate economic policy uncertainty in BRICS?," Pacific-Basin Finance Journal, Elsevier, vol. 66(C).
    81. Oscar Claveria, 2021. "Disagreement on expectations: firms versus consumers," SN Business & Economics, Springer, vol. 1(12), pages 1-23, December.
    82. Dogan, Ergun & Zhang, Xibin, 2023. "A nonparametric panel data model for examining the contribution of tourism to economic growth," Economic Modelling, Elsevier, vol. 128(C).
    83. Sheng Cheng & Wei Liu & Qisheng Jiang & Yan Cao, 2023. "Multi–Scale Risk Connectedness Between Economic Policy Uncertainty of China and Global Oil Prices in Time–Frequency Domains," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1593-1616, April.
    84. Yicong Lin & Mingxuan Song, 2023. "Robust bootstrap inference for linear time-varying coefficient models: Some Monte Carlo evidence," Tinbergen Institute Discussion Papers 23-049/III, Tinbergen Institute.
    85. Lin, Boqiang & Xu, Bin, 2020. "Effective ways to reduce CO2 emissions from China's heavy industry? Evidence from semiparametric regression models," Energy Economics, Elsevier, vol. 92(C).
    86. Ivanovski, Kris & Hailemariam, Abebe, 2021. "Forecasting the dynamic relationship between crude oil and stock prices since the 19th century," Journal of Commodity Markets, Elsevier, vol. 24(C).

  6. Awaworyi Churchill, Sefa & Inekwe, John & Smyth, Russell & Zhang, Xibin, 2019. "R&D intensity and carbon emissions in the G7: 1870–2014," Energy Economics, Elsevier, vol. 80(C), pages 30-37.

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    2. Uddin, Md. Main & Mishra, Vinod & Smyth, Russell, 2020. "Income inequality and CO2 emissions in the G7, 1870–2014: Evidence from non-parametric modelling," Energy Economics, Elsevier, vol. 88(C).
    3. Chris Belmert Milindi & Roula Inglesi-Lotz, 2021. "Impact of technological progress on carbon emissions in different country income groups," Working Papers 202123, University of Pretoria, Department of Economics.
    4. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2020. "The Environmental Kuznets Curve across Australian states and territories," Energy Economics, Elsevier, vol. 90(C).
    5. Ehigiamusoe, Kizito Uyi & Lean, Hooi Hooi & Smyth, Russell, 2020. "The moderating role of energy consumption in the carbon emissions-income nexus in middle-income countries," Applied Energy, Elsevier, vol. 261(C).
    6. Khan, Syed Abdul Rehman & Zia-Ul-Haq, Hafiz Muhammad & Ponce, Pablo & Janjua, Laeeq, 2023. "Re-investigating the impact of non-renewable and renewable energy on environmental quality: A roadmap towards sustainable development," Resources Policy, Elsevier, vol. 81(C).
    7. Shu, Haicheng & Wang, Yu & Umar, Muhammad & Zhong, Yifan, 2023. "Dynamics of renewable energy research, investment in EnvoTech and environmental quality in the context of G7 countries," Energy Economics, Elsevier, vol. 120(C).
    8. Acheampong, Alex O. & Dzator, Janet & Dzator, Michael & Salim, Ruhul, 2022. "Unveiling the effect of transport infrastructure and technological innovation on economic growth, energy consumption and CO2 emissions," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    9. Pablo Ponce & Cristiana Oliveira & Viviana Álvarez & María de la Cruz del Río-Rama, 2020. "The Liberalization of the Internal Energy Market in the European Union: Evidence of Its Influence on Reducing Environmental Pollution," Energies, MDPI, vol. 13(22), pages 1-17, November.
    10. Shahbaz, Muhammad & Nasir, Muhammad Ali & Hille, Erik & Mahalik, Mantu Kumar, 2020. "UK's net-zero carbon emissions target: Investigating the potential role of economic growth, financial development, and R&D expenditures based on historical data (1870–2017)," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    11. Huang, Junbing & Xiang, Shiqi & Wang, Yajun & Chen, Xiang, 2021. "Energy-saving R&D and carbon intensity in China," Energy Economics, Elsevier, vol. 98(C).
    12. Su, Chi-Wei & Pang, Li-Dong & Tao, Ran & Shao, Xuefeng & Umar, Muhammad, 2022. "Renewable energy and technological innovation: Which one is the winner in promoting net-zero emissions?," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    13. Adedoyin, Festus Fatai & Alola, Andrew Adewale & Bekun, Festus Victor, 2021. "The alternative energy utilization and common regional trade outlook in EU-27: Evidence from common correlated effects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    14. Payab, Ahmad Haseeb & Kautish, Pradeep & Sharma, Rajesh & Siddiqui, Aaliyah & Mehta, Atul & Siddiqui, Mujahid, 2023. "Does human capital complement sustainable development goals? Evidence from leading carbon emitter countries," Utilities Policy, Elsevier, vol. 81(C).
    15. Xin, Daleng & Ahmad, Manzoor & Lei, Hong & Khattak, Shoukat Iqbal, 2021. "Do innovation in environmental-related technologies asymmetrically affect carbon dioxide emissions in the United States?," Technology in Society, Elsevier, vol. 67(C).
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    17. Dong, Kangyin & Jiang, Qingzhe & Shahbaz, Muhammad & Zhao, Jun, 2021. "Does low-carbon energy transition mitigate energy poverty? The case of natural gas for China," Energy Economics, Elsevier, vol. 99(C).
    18. Lee, Chien-Chiang & Chang, Yu-Fang & Wang, En-Ze, 2022. "Crossing the rivers by feeling the stones: The effect of China's green credit policy on manufacturing firms' carbon emission intensity," Energy Economics, Elsevier, vol. 116(C).
    19. Amin, Nabila & Shabbir, Muhammad Salman & Song, Huaming & Farrukh, Muhammad Umar & Iqbal, Shahid & Abbass, Kashif, 2023. "A step towards environmental mitigation: Do green technological innovation and institutional quality make a difference?," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    20. Moghaddam, Mohsen Bakhshi & Lloyd-Ellis, Huw, 2022. "Heterogeneous effects of oil price fluctuations: Evidence from a nonparametric panel data model in Canada," Energy Economics, Elsevier, vol. 110(C).
    21. Herzer, Dierk, 2022. "The impact on domestic CO2 emissions of domestic government-funded clean energy R&D and of spillovers from foreign government-funded clean energy R&D," Energy Policy, Elsevier, vol. 168(C).
    22. Chishti, Muhammad Zubair & Sinha, Avik, 2021. "Do the shocks in technological and financial innovation influence the environmental quality? Evidence from BRICS economies," MPRA Paper 110943, University Library of Munich, Germany, revised Nov 2021.
    23. Chen, Yang & Cheng, Liang & Lee, Chien-Chiang & Wang, Chang-song, 2021. "The impact of regional banks on environmental pollution: Evidence from China's city commercial banks," Energy Economics, Elsevier, vol. 102(C).
    24. Awaworyi Churchill, Sefa & Baako, Kingsley Tetteh & Mintah, Kwabena & Zhang, Quanda, 2021. "Transport infrastructure and house prices in the long run," Transport Policy, Elsevier, vol. 112(C), pages 1-12.
    25. Chishti, Muhammad Zubair & Patel, Ritesh, 2023. "Breaking the climate deadlock: Leveraging the effects of natural resources on climate technologies to achieve COP26 targets," Resources Policy, Elsevier, vol. 82(C).
    26. Mounir Dahmani, 2024. "Environmental quality and sustainability: exploring the role of environmental taxes, environment-related technologies, and R&D expenditure," Post-Print hal-04374168, HAL.
    27. Sudharshan Reddy Paramati & Md Samsul Alam & Shawkat Hammoudeh & Khalid Hafeez, 2021. "Long‐run relationship between R&D investment and environmental sustainability: Evidence from the European Union member countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5775-5792, October.
    28. Li, Junhui & Li, Guowei, 2023. "What drives resource sustainability in Asia? Discovering the moderating role of financial development and industrialization," Resources Policy, Elsevier, vol. 85(PA).
    29. Khan, Zeeshan & Ali, Muhsin & Jinyu, Liu & Shahbaz, Muhammad & Siqun, Yang, 2020. "Consumption-based carbon emissions and trade nexus: Evidence from nine oil exporting countries," Energy Economics, Elsevier, vol. 89(C).
    30. Razzaq, Asif & Ajaz, Tahseen & Li, Jing Claire & Irfan, Muhammad & Suksatan, Wanich, 2021. "Investigating the asymmetric linkages between infrastructure development, green innovation, and consumption-based material footprint: Novel empirical estimations from highly resource-consuming economi," Resources Policy, Elsevier, vol. 74(C).
    31. Shabir, Maria & Pazienza, Pasquale & De Lucia, Caterina, 2023. "Energy innovation and ecological footprint: Evidence from OECD countries during 1990–2018," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    32. Li, Guangqin & Zhang, Xi, 2023. "Does GVC embedding reduce carbon emissions? Empirical evidence from 218 Chinese cities," Structural Change and Economic Dynamics, Elsevier, vol. 66(C), pages 253-263.
    33. Li, Xin & Li, Zheng & Su, Chi-Wei & Umar, Muhammad & Shao, Xuefeng, 2022. "Exploring the asymmetric impact of economic policy uncertainty on China's carbon emissions trading market price: Do different types of uncertainty matter?," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    34. Sefa Awaworyi Churchill & Bin Peng & Russell Smyth & Quanda Zhang, 2022. "R&D intensity and income inequality in the G7: 1870–2016," Scottish Journal of Political Economy, Scottish Economic Society, vol. 69(3), pages 263-282, July.
    35. Liddle, Brantley & Smyth, Russell & Zhang, Xibin, 2020. "Time-varying income and price elasticities for energy demand: Evidence from a middle-income panel," Energy Economics, Elsevier, vol. 86(C).
    36. Yan, Yu & Huang, Junbing, 2022. "The role of population agglomeration played in China's carbon intensity: A city-level analysis," Energy Economics, Elsevier, vol. 114(C).
    37. Opoku, Eric Evans Osei & Dogah, Kingsley E. & Aluko, Olufemi Adewale, 2022. "The contribution of human development towards environmental sustainability," Energy Economics, Elsevier, vol. 106(C).
    38. Yang Chen & Chien-Chiang Lee & Ming Chen, 2022. "Ecological footprint, human capital, and urbanization," Energy & Environment, , vol. 33(3), pages 487-510, May.
    39. Maghyereh, Aktham & Abdoh, Hussein, 2021. "The effect of structural oil shocks on bank systemic risk in the GCC countries," Energy Economics, Elsevier, vol. 103(C).
    40. Chen, Huanyu & Yi, Jizheng & Chen, Aibin & Peng, Duanxiang & Yang, Jieqiong, 2023. "Green technology innovation and CO2 emission in China: Evidence from a spatial-temporal analysis and a nonlinear spatial durbin model," Energy Policy, Elsevier, vol. 172(C).
    41. Yongwang Zhang & Lin Song, 2020. "Defining the Optimal Implementation Space of Environmental Regulation in China’s Export Trade," Sustainability, MDPI, vol. 12(20), pages 1-19, October.
    42. Yao, Yao & Ivanovski, Kris & Inekwe, John & Smyth, Russell, 2019. "Human capital and energy consumption: Evidence from OECD countries," Energy Economics, Elsevier, vol. 84(C).
    43. Hossain, Ashrafee & Masum, Abdullah-Al & Saadi, Samir & Benkraiem, Ramzi, 2023. "Generalist CEO and carbon emissions," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 68-86.
    44. Muhammad Wasif Zafar & Muhammad Mansoor Saleem & Mehmet Akif Destek & Abdullah Emre Caglar, 2022. "The dynamic linkage between remittances, export diversification, education, renewable energy consumption, economic growth, and CO2 emissions in top remittance‐receiving countries," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(1), pages 165-175, February.
    45. Sinha, Avik & Sengupta, Tuhin & Saha, Tanaya, 2020. "Technology policy and environmental quality at crossroads: Designing SDG policies for select Asia Pacific countries," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    46. Haiqian Ke & Shangze Dai & Haichao Yu, 2022. "Effect of green innovation efficiency on ecological footprint in 283 Chinese Cities from 2008 to 2018," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(2), pages 2841-2860, February.
    47. Jun, Xiao & Huang, Wenwei & Guo, Yiting & Cao, Yuqiang & Lu, Meiting, 2023. "Why does economic policy uncertainty increase firm-level pollutant emission?," Economic Modelling, Elsevier, vol. 129(C).
    48. Zhu Weimin & Muhammad Zubair Chishti & Abdul Rehman & Manzoor Ahmad, 2022. "A pathway toward future sustainability: Assessing the influence of innovation shocks on CO2 emissions in developing economies," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(4), pages 4786-4809, April.
    49. Zhu, Zhishuang & Liao, Hua & Liu, Li, 2021. "The role of public energy R&D in energy conservation and transition: Experiences from IEA countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    50. Xiaosan, Zhang & Qingquan, Jiang & Shoukat Iqbal, Khattak & Manzoor, Ahmad & Zia Ur, Rahman, 2021. "Achieving sustainability and energy efficiency goals: Assessing the impact of hydroelectric and renewable electricity generation on carbon dioxide emission in China," Energy Policy, Elsevier, vol. 155(C).
    51. Yu, Jian & Shi, Xunpeng & Guo, Dongmei & Yang, Longjian, 2021. "Economic policy uncertainty (EPU) and firm carbon emissions: Evidence using a China provincial EPU index," Energy Economics, Elsevier, vol. 94(C).
    52. Buccella, Domenico & Fanti, Luciano & Gori, Luca, 2020. "To abate, or not to abate? A strategic approach on green production in Cournot and Bertrand duopolies," GLO Discussion Paper Series 636, Global Labor Organization (GLO).
    53. Wang, Xiong & Yang, Wanping & Ren, Xiaohang & Lu, Zudi, 2023. "Can financial inclusion affect energy poverty in China? Evidence from a spatial econometric analysis," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 255-269.
    54. Bai, Jiancheng & Han, Zhiyong & Rizvi, Syed Kumail Abbas & Naqvi, Bushra, 2023. "Green trade or green technology? The way forward for G-7 economies to achieve COP 26 targets while making competing policy choices," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    55. Zameer, Hashim & Yasmeen, Humaira & Zafar, Muhammad Wasif & Waheed, Abdul & Sinha, Avik, 2020. "Analyzing the association between Innovation, Economic Growth, and Environment: Divulging the Importance of FDI and Trade Openness in India," MPRA Paper 101323, University Library of Munich, Germany, revised 2020.
    56. Yu, Zhang & Khan, Syed Abdul Rehman & Ponce, Pablo & Lopes de Sousa Jabbour, Ana Beatriz & Chiappetta Jabbour, Charbel Jose, 2022. "Factors affecting carbon emissions in emerging economies in the context of a green recovery: Implications for sustainable development goals," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    57. Appiah, Michael & Li, Mingxing & Sehrish, Saba & Abaji, Emad Eddin, 2023. "Investigating the connections between innovation, natural resource extraction, and environmental pollution in OECD nations; examining the role of capital formation," Resources Policy, Elsevier, vol. 81(C).
    58. Saptorshee Kanto Chakraborty & Massimiliano Mazzanti, 2020. "Carbon taxes and trade spillovers within Europe," SEEDS Working Papers 0420, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Apr 2020.
    59. Sami Fethi & Elif Senyucel, 2021. "The role of tourism development on CO2 emission reduction in an extended version of the environmental Kuznets curve: evidence from top 50 tourist destination countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(2), pages 1499-1524, February.
    60. Zhao, Jun & Jiang, Qingzhe & Dong, Xiucheng & Dong, Kangyin, 2021. "Assessing energy poverty and its effect on CO2 emissions: The case of China," Energy Economics, Elsevier, vol. 97(C).
    61. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris, 2021. "R&D expenditure and energy consumption in OECD nations," Energy Economics, Elsevier, vol. 100(C).
    62. Wan, Guanghua & Wang, Chen & Wang, Jinxian & Zhang, Xun, 2022. "The income inequality-CO2 emissions nexus: Transmission mechanisms," Ecological Economics, Elsevier, vol. 195(C).
    63. Liu, Jun & Liu, Liang & Qian, Yu & Song, Shunfeng, 2022. "The effect of artificial intelligence on carbon intensity: Evidence from China's industrial sector," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    64. Yu, Jian & Liu, Peng & Fu, Dahai & Shi, Xunpeng, 2023. "How do power shortages affect CO2 emission intensity? Firm-level evidence from China," Energy, Elsevier, vol. 282(C).
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    66. Sinha, Avik & Sengupta, Tuhin & Alvarado, Rafael, 2020. "Interplay between Technological Innovation and Environmental Quality: Formulating the SDG Policies for Next 11 Economies," MPRA Paper 104247, University Library of Munich, Germany, revised 2020.
    67. Shahzadi, Irum & Yaseen, Muhammad Rizwan & Iqbal Khan, Muhammad Tariq & Amjad Makhdum, Muhammad Sohail & Ali, Qamar, 2022. "The nexus between research and development, renewable energy and environmental quality: Evidence from developed and developing countries," Renewable Energy, Elsevier, vol. 190(C), pages 1089-1099.
    68. Sun, Yunpeng & Guan, Weimin & Razzaq, Asif & Shahzad, Mohsin & Binh An, Nguyen, 2022. "Transition towards ecological sustainability through fiscal decentralization, renewable energy and green investment in OECD countries," Renewable Energy, Elsevier, vol. 190(C), pages 385-395.
    69. Bhattacharya, Mita & Inekwe, John & Yan, Eric, 2021. "Dynamics of energy poverty: Evidence from nonparametric estimates across the ASEAN+6 region," Energy Economics, Elsevier, vol. 103(C).
    70. Zhong, Zhiqi & Chen, Yongqiang & Fu, Meiyan & Li, Minzhen & Yang, Kaishuo & Zeng, Lingping & Liang, Jing & Ma, Rupeng & Xie, Quan, 2023. "Role of CO2 geological storage in China's pledge to carbon peak by 2030 and carbon neutrality by 2060," Energy, Elsevier, vol. 272(C).
    71. Khan, Zeeshan & Malik, Muhammad Yousaf & Latif, Kashmala & Jiao, Zhilun, 2020. "Heterogeneous effect of eco-innovation and human capital on renewable & non-renewable energy consumption: Disaggregate analysis for G-7 countries," Energy, Elsevier, vol. 209(C).
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    73. Khezri, Mohsen & Heshmati, Almas & Khodaei, Mehdi, 2022. "Environmental implications of economic complexity and its role in determining how renewable energies affect CO2 emissions," Applied Energy, Elsevier, vol. 306(PB).
    74. Mehmet Akif, Destek & Muhammad, Shahbaz & Ilyas, Okumus & Shawkat, Hammoudeh & Avik, Sinha, 2020. "The relationship between economic growth and carbon emissions in G-7 countries: evidence from time-varying parameters with a long history," MPRA Paper 100514, University Library of Munich, Germany, revised Apr 2020.
    75. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2023. "Human capital and energy consumption: Six centuries of evidence from the United Kingdom," Energy Economics, Elsevier, vol. 117(C).
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  7. Tingting Cheng & Jiti Gao & Xibin Zhang, 2019. "Bayesian Bandwidth Estimation in Nonparametric Time-Varying Coefficient Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(1), pages 1-12, January.
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  8. Silvapulle, Param & Smyth, Russell & Zhang, Xibin & Fenech, Jean-Pierre, 2017. "Nonparametric panel data model for crude oil and stock market prices in net oil importing countries," Energy Economics, Elsevier, vol. 67(C), pages 255-267.

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    1. Cheema, Muhammad A. & Scrimgeour, Frank, 2019. "Oil prices and stock market anomalies," Energy Economics, Elsevier, vol. 83(C), pages 578-587.
    2. Uddin, Md. Main & Mishra, Vinod & Smyth, Russell, 2020. "Income inequality and CO2 emissions in the G7, 1870–2014: Evidence from non-parametric modelling," Energy Economics, Elsevier, vol. 88(C).
    3. Jihoon Lee & Hong Chong Cho, 2021. "Impact of Structural Oil Price Shock Factors on the Gasoline Market and Macroeconomy in South Korea," Sustainability, MDPI, vol. 13(4), pages 1-23, February.
    4. Awaworyi Churchill, Sefa & Inekwe, John & Smyth, Russell & Zhang, Xibin, 2019. "R&D intensity and carbon emissions in the G7: 1870–2014," Energy Economics, Elsevier, vol. 80(C), pages 30-37.
    5. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2020. "The Environmental Kuznets Curve across Australian states and territories," Energy Economics, Elsevier, vol. 90(C).
    6. Pandey, Dharen Kumar & Lucey, Brian M. & Kumar, Satish, 2023. "Border disputes, conflicts, war, and financial markets research: A systematic review," Research in International Business and Finance, Elsevier, vol. 65(C).
    7. Mo, Xuan & Su, Zhi & Yin, Libo, 2019. "Can the skewness of oil returns affect stock returns? Evidence from China’s A-Share markets," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    8. Chowdhury, Kushal Banik & Garg, Bhavesh, 2023. "Fresh evidence on the oil-stock interactions under heterogeneous market conditions," Finance Research Letters, Elsevier, vol. 54(C).
    9. Selahattin Güriş & Sevcan Çağlayan, 2023. "Co2 Emisyonlarını Etkileyen Faktörlerin Zamanla Değişen Katsayılı Parametrik Olmayan Panel Veri Modelleri ile Analizi," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(39), pages 76-88, December.
    10. Fei Liu & Jiti Gao & Yanrong Yang, 2019. "Nonparametric Estimation in Panel Data Models with Heterogeneity and Time Varyingness," Monash Econometrics and Business Statistics Working Papers 24/19, Monash University, Department of Econometrics and Business Statistics.
    11. Zhang, Hao & Cai, Guixin & Yang, Dongxiao, 2020. "The impact of oil price shocks on clean energy stocks: Fresh evidence from multi-scale perspective," Energy, Elsevier, vol. 196(C).
    12. Westerlund, Joakim & Sharma, Susan Sunila, 2019. "Panel evidence on the ability of oil returns to predict stock returns in the G7 area," Energy Economics, Elsevier, vol. 77(C), pages 3-12.
    13. Anjan K. Saha & Vinod Mishra & Russell Smyth, 2021. "Financial development and top income shares in OECD countries," Southern Economic Journal, John Wiley & Sons, vol. 87(3), pages 952-978, January.
    14. Moghaddam, Mohsen Bakhshi & Lloyd-Ellis, Huw, 2022. "Heterogeneous effects of oil price fluctuations: Evidence from a nonparametric panel data model in Canada," Energy Economics, Elsevier, vol. 110(C).
    15. Satish Kumar & Rabeh Khalfaoui & Aviral Kumar Tiwari, 2021. "Does geopolitical risk improve the directional predictability from oil to stock returns? Evidence from oil-exporting and oil-importing countries," Post-Print hal-03797578, HAL.
    16. Zhang, Guofu & Liu, Wei, 2018. "Analysis of the international propagation of contagion between oil and stock markets," Energy, Elsevier, vol. 165(PA), pages 469-486.
    17. Lin, Hang & Zhang, Zhengjun, 2022. "Extreme co-movements between infectious disease events and crude oil futures prices: From extreme value analysis perspective," Energy Economics, Elsevier, vol. 110(C).
    18. Mensi, Walid & Hammoudeh, Shawkat & Vinh Vo, Xuan & Hoon Kang, Sang, 2021. "Volatility spillovers between oil and equity markets and portfolio risk implications in the US and vulnerable EU countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
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    21. Joo, Young C. & Park, Sung Y., 2021. "The impact of oil price volatility on stock markets: Evidences from oil-importing countries," Energy Economics, Elsevier, vol. 101(C).
    22. Jianxu Liu & Quanrui Song & Yang Qi & Sanzidur Rahman & Songsak Sriboonchitta, 2020. "Measurement of Systemic Risk in Global Financial Markets and Its Application in Forecasting Trading Decisions," Sustainability, MDPI, vol. 12(10), pages 1-15, May.
    23. Xuan, Liang & Jiti, Gao & xiaodong, Gong, 2021. "Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients," MPRA Paper 108497, University Library of Munich, Germany, revised 30 May 2021.
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    25. Chen, Zhihong & Xia, Huizhu, 2020. "Trend instrumental variable regression with an application to the US New Keynesian Phillips Curve," Economic Modelling, Elsevier, vol. 93(C), pages 595-604.
    26. Abebe Hailemariam & Tutsirai Sakutukwa & Ratbek Dzhumashev, 2021. "Long-term determinants of income inequality: evidence from panel data over 1870–2016," Empirical Economics, Springer, vol. 61(4), pages 1935-1958, October.
    27. Sudhi SHARMA & Miklesh YADAV, 2020. "Analyzing the robustness of ARIMA and neural networks as a predictive model of crude oil prices," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(2(623), S), pages 289-300, Summer.
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    31. Sefa Awaworyi Churchill & Bin Peng & Russell Smyth & Quanda Zhang, 2022. "R&D intensity and income inequality in the G7: 1870–2016," Scottish Journal of Political Economy, Scottish Economic Society, vol. 69(3), pages 263-282, July.
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    33. Afees A. Salisu & Rangan Gupta & Riza Demirer, 2022. "Oil Price Uncertainty Shocks and Global Equity Markets: Evidence from a GVAR Model," JRFM, MDPI, vol. 15(8), pages 1-26, August.
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    36. Okorie, David Iheke & Lin, Boqiang, 2020. "Crude oil price and cryptocurrencies: Evidence of volatility connectedness and hedging strategy," Energy Economics, Elsevier, vol. 87(C).
    37. Qichang Xie & Yingkun Yan & Xu Wang, 2023. "Assessing the role of foreign direct investment in environmental sustainability: a spatial semiparametric panel approach," Economic Change and Restructuring, Springer, vol. 56(2), pages 1263-1295, April.
    38. Yunus, Nafeesa, 2020. "Time-varying linkages among gold, stocks, bonds and real estate," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 165-185.
    39. Muhammad Ali, Khalid M. Iraqi, Abdul Waheed Khan, 2019. "Impact of Oil Prices on Stock Market Performance: Evidence from Top Oil Importing Countries," Journal of Finance and Economics Research, Geist Science, Iqra University, Faculty of Business Administration, vol. 4(2), pages 1-14, October.
    40. Fei Liu & Jiti Gao & Yanrong Yang, 2020. "Time-Varying Panel Data Models with an Additive Factor Structure," Monash Econometrics and Business Statistics Working Papers 42/20, Monash University, Department of Econometrics and Business Statistics.
    41. Aviral Kumar Tiwari & Samia Nasreen & Subhan Ullah & Muhammad Shahbaz, 2021. "Analysing spillover between returns and volatility series of oil across major stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2458-2490, April.
    42. Ivanovski, Kris & Hailemariam, Abebe, 2022. "Time-varying geopolitical risk and oil prices," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 206-221.
    43. Ren, Xiaohang & Tong, Ziwei & Sun, Xianming & Yan, Cheng, 2022. "Dynamic impacts of energy consumption on economic growth in China: Evidence from a non-parametric panel data model," Energy Economics, Elsevier, vol. 107(C).
    44. Hadhri, Sinda, 2021. "The nexus, downside risk and asset allocation between oil and Islamic stock markets: A cross-country analysis," Energy Economics, Elsevier, vol. 101(C).
    45. Daniel J. Tulloch & Ivan Diaz-Rainey & I. M. Premachandra, 2020. "Modelling Sector-Level Asset Prices," JRFM, MDPI, vol. 13(6), pages 1-32, June.
    46. Gorus, Muhammed Sehid & Karagol, Erdal Tanas, 2022. "Reactions of energy intensity, energy efficiency, and activity indexes to income and energy price changes: The panel data evidence from OECD countries," Energy, Elsevier, vol. 254(PA).
    47. Sun, Xianming & Xiao, Shiyi & Ren, Xiaohang & Xu, Bing, 2023. "Time-varying impact of information and communication technology on carbon emissions," Energy Economics, Elsevier, vol. 118(C).
    48. Babak Fazelabdolabadi, 2019. "Uncertainty and energy-sector equity returns in Iran: a Bayesian and quasi-Monte Carlo time-varying analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-20, December.
    49. Wu, Xi & Wang, Yudong, 2021. "How does corporate investment react to oil prices changes? Evidence from China," Energy Economics, Elsevier, vol. 97(C).
    50. Zolfaghari, Mehdi & Ghoddusi, Hamed & Faghihian, Fatemeh, 2020. "Volatility spillovers for energy prices: A diagonal BEKK approach," Energy Economics, Elsevier, vol. 92(C).
    51. Hassan, Kamrul & Hoque, Ariful & Gasbarro, Dominic, 2019. "Separating BRIC using Islamic stocks and crude oil: dynamic conditional correlation and volatility spillover analysis," Energy Economics, Elsevier, vol. 80(C), pages 950-969.
    52. David Iheke Okorie & Boqiang Lin, 2022. "Crude oil market and Nigerian stocks: An asymmetric information spillover approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4002-4017, October.
    53. Basel Maraqa & Murad Bein, 2020. "Dynamic Interrelationship and Volatility Spillover among Sustainability Stock Markets, Major European Conventional Indices, and International Crude Oil," Sustainability, MDPI, vol. 12(9), pages 1-14, May.
    54. Ghaemi Asl, Mahdi & Adekoya, Oluwasegun Babatunde & Rashidi, Muhammad Mahdi & Ghasemi Doudkanlou, Mohammad & Dolatabadi, Ali, 2022. "Forecast of Bayesian-based dynamic connectedness between oil market and Islamic stock indices of Islamic oil-exporting countries: Application of the cascade-forward backpropagation network," Resources Policy, Elsevier, vol. 77(C).
    55. Nicholas Marinucci & Kris Ivanovski, 2023. "Does Inequality Affect Climate Change? A Regional and Sectoral Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 166(3), pages 705-729, April.
    56. Saptorshee Kanto Chakraborty & Massimiliano Mazzanti, 2020. "Carbon taxes and trade spillovers within Europe," SEEDS Working Papers 0420, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Apr 2020.
    57. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris, 2021. "R&D expenditure and energy consumption in OECD nations," Energy Economics, Elsevier, vol. 100(C).
    58. Yonghong Jiang & Jinqi Mu & He Nie & Lanxin Wu, 2022. "Time‐frequency analysis of risk spillovers from oil to BRICS stock markets: A long‐memory Copula‐CoVaR‐MODWT method," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3386-3404, July.
    59. Hassan, Kamrul & Hoque, Ariful & Wali, Muammer & Gasbarro, Dominic, 2020. "Islamic stocks, conventional stocks, and crude oil: Directional volatility spillover analysis in BRICS," Energy Economics, Elsevier, vol. 92(C).
    60. Elkhan Richard Sadik-Zada & Wilhelm Loewenstein, 2020. "Drivers of CO 2 -Emissions in Fossil Fuel Abundant Settings: (Pooled) Mean Group and Nonparametric Panel Analyses," Energies, MDPI, vol. 13(15), pages 1-24, August.
    61. Xuan Liang & Jiti Gao & Xiaodong Gong, 2019. "Time-Varying Coefficient Spatial Autoregressive Panel Data Model with Fixed Effects," Monash Econometrics and Business Statistics Working Papers 26/19, Monash University, Department of Econometrics and Business Statistics.
    62. Rasool Dehghanzadeh Shahabad & Mehmet Balcilar, 2022. "Modelling the Dynamic Interaction between Economic Policy Uncertainty and Commodity Prices in India: The Dynamic Autoregressive Distributed Lag Approach," Mathematics, MDPI, vol. 10(10), pages 1-21, May.
    63. Tian, Maoxi & Alshater, Muneer M. & Yoon, Seong-Min, 2022. "Dynamic risk spillovers from oil to stock markets: Fresh evidence from GARCH copula quantile regression-based CoVaR model," Energy Economics, Elsevier, vol. 115(C).
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    65. Chinnadurai Kathiravan & Murugesan Selvam & Balasundram Maniam & Leo Paul Dana & Manivannan Babu, 2023. "The Effects of Crude Oil Price Surprises on National Income: Evidence from India," Energies, MDPI, vol. 16(3), pages 1-16, January.
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  9. Chen, Haotian & Smyth, Russell & Zhang, Xibin, 2017. "A Bayesian sampling approach to measuring the price responsiveness of gasoline demand using a constrained partially linear model," Energy Economics, Elsevier, vol. 67(C), pages 346-354.

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    1. Mehzabin Tuli, Farzana & Mitra, Suman & Crews, Mariah B., 2021. "Factors influencing the usage of shared E-scooters in Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 164-185.
    2. Xu, Lei & Chen, Jingrui & Qu, Fang & Wang, Jue & Lu, Yi, 2022. "Queuing to refuel before price rise in China: How do gasoline price changes affect consumer responses and behaviours?," Energy, Elsevier, vol. 253(C).
    3. Gimenez-Nadal, José Ignacio & Molina, José Alberto, 2019. "Green Commuting and Gasoline Taxes in the United States," IZA Discussion Papers 12377, Institute of Labor Economics (IZA).

  10. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2016. "Bayesian Bandwidth Selection for a Nonparametric Regression Model with Mixed Types of Regressors," Econometrics, MDPI, vol. 4(2), pages 1-27, April.
    See citations under working paper version above.
  11. Song Li & Mervyn J. Silvapulle & Param Silvapulle & Xibin Zhang, 2015. "Bayesian Approaches to Nonparametric Estimation of Densities on the Unit Interval," Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 394-412, March.
    See citations under working paper version above.
  12. Li, Han & O’Hare, Colin & Zhang, Xibin, 2015. "A semiparametric panel approach to mortality modeling," Insurance: Mathematics and Economics, Elsevier, vol. 61(C), pages 264-270.

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    1. Blake, David & Cairns, Andrew J.G., 2021. "Longevity risk and capital markets: The 2019-20 update," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 395-439.
    2. Li, Han & O’Hare, Colin, 2017. "Semi-parametric extensions of the Cairns–Blake–Dowd model: A one-dimensional kernel smoothing approach," Insurance: Mathematics and Economics, Elsevier, vol. 77(C), pages 166-176.
    3. Tsai, Cary Chi-Liang & Cheng, Echo Sihan, 2021. "Incorporating statistical clustering methods into mortality models to improve forecasting performances," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 42-62.
    4. Li, Han & Hyndman, Rob J., 2021. "Assessing mortality inequality in the U.S.: What can be said about the future?," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 152-162.
    5. Lydia Dutton & Athanasios A. Pantelous & Malgorzata Seklecka, 2020. "The impact of economic growth in mortality modelling for selected OECD countries," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 533-550, April.
    6. Hong Li & Yang Lu, 2016. "Coherent Forecasting Of Mortality Rates: A Sparse Vector-Autoregression Approach," Post-Print halshs-02418954, HAL.
    7. Cupido, Kyran & Jevtić, Petar & Paez, Antonio, 2020. "Spatial patterns of mortality in the United States: A spatial filtering approach," Insurance: Mathematics and Economics, Elsevier, vol. 95(C), pages 28-38.
    8. He, Lingyu & Huang, Fei & Shi, Jianjie & Yang, Yanrong, 2021. "Mortality forecasting using factor models: Time-varying or time-invariant factor loadings?," Insurance: Mathematics and Economics, Elsevier, vol. 98(C), pages 14-34.
    9. Ka Kin Lam & Bo Wang, 2021. "Robust Non-Parametric Mortality and Fertility Modelling and Forecasting: Gaussian Process Regression Approaches," Forecasting, MDPI, vol. 3(1), pages 1-21, March.

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    1. Zeng-Hua Lu & Alec Zuo, 2017. "Child disability, welfare payments, marital status and mothers’ labor supply: Evidence from Australia," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1339769-133, January.
    2. Dawood Ashraf & Mohsin Khawaja & M. Ishaq Bhatti, 2022. "Raising capital amid economic policy uncertainty: an empirical investigation," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-32, December.
    3. Wojtyś, Małgorzata & Marra, Giampiero & Radice, Rosalba, 2018. "Copula based generalized additive models for location, scale and shape with non-random sample selection," Computational Statistics & Data Analysis, Elsevier, vol. 127(C), pages 1-14.

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    See citations under working paper version above.
  15. Hu, Shuowen & Poskitt, D.S. & Zhang, Xibin, 2012. "Bayesian adaptive bandwidth kernel density estimation of irregular multivariate distributions," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 732-740.
    See citations under working paper version above.
  16. Liu, Qing & Pitt, David & Zhang, Xibin & Wu, Xueyuan, 2011. "A Bayesian Approach to Parameter Estimation for Kernel Density Estimation via Transformations," Annals of Actuarial Science, Cambridge University Press, vol. 5(2), pages 181-193, September.
    See citations under working paper version above.
  17. Jonathan Dark & Xibin Zhang & Nan Qu, 2010. "Influence diagnostics for multivariate GARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 278-291, July.

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    1. Fukang Zhu & Lei Shi & Shuangzhe Liu, 2015. "Influence diagnostics in log-linear integer-valued GARCH models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(3), pages 311-335, July.

  18. Zhang, Xibin & Brooks, Robert D. & King, Maxwell L., 2009. "A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation," Journal of Econometrics, Elsevier, vol. 153(1), pages 21-32, November.
    See citations under working paper version above.
  19. Lean, Hooi-Hooi & Wong, Wing-Keung & Zhang, Xibin, 2008. "The sizes and powers of some stochastic dominance tests: A Monte Carlo study for correlated and heteroskedastic distributions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(1), pages 30-48.

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    1. Kai-Yin Woo & Chulin Mai & Michael McAleer & Wing-Keung Wong, 2020. "Review on Efficiency and Anomalies in Stock Markets," Economies, MDPI, vol. 8(1), pages 1-51, March.
    2. Hoang, Thi-Hong-Van & Wong, Wing-Keung & Zhu, Zhenzhen, 2015. "Is gold different for risk-averse and risk-seeking investors? An empirical analysis of the Shanghai Gold Exchange," Economic Modelling, Elsevier, vol. 50(C), pages 200-211.
    3. Lam, Kin & Lean, Hooi Hooi & Wong, Wing-Keung, 2016. "Stochastic Dominance and Investors’ Behavior towards Risk: The Hong Kong Stocks and Futures Markets," MPRA Paper 74386, University Library of Munich, Germany.
    4. Raymond H. Chan & Ephraim Clark & Xu Guo & Wing-Keung Wong, 2020. "New development on the third-order stochastic dominance for risk-averse and risk-seeking investors with application in risk management," Risk Management, Palgrave Macmillan, vol. 22(2), pages 108-132, June.
    5. Zhuo Qiao & Wing-Keung Wong, 2015. "Which is a better investment choice in the Hong Kong residential property market: a big or small property?," Applied Economics, Taylor & Francis Journals, vol. 47(16), pages 1670-1685, April.
    6. Alkhazali, Osamah M. & Zoubi, Taisier A., 2020. "Gold and portfolio diversification: A stochastic dominance analysis of the Dow Jones Islamic indices," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    7. Blomvall, Jörgen & Hagenbjörk, Johan, 2022. "Reducing transaction costs for interest rate risk hedging with stochastic programming," European Journal of Operational Research, Elsevier, vol. 302(3), pages 1282-1293.
    8. Zhidong Bai & Hua Li & Michael McAleer & Wing-Keung Wong, 2015. "Stochastic dominance statistics for risk averters and risk seekers: an analysis of stock preferences for USA and China," Quantitative Finance, Taylor & Francis Journals, vol. 15(5), pages 889-900, May.
    9. Abdelbari El Khamlichi & Thi Hong Van Hoang & Wing‐keung Wong, 2016. "Is Gold Different for Islamic and Conventional Portfolios? A Sectorial Analysis," Post-Print hal-02964594, HAL.
    10. Kim-Hung Pho & Tuan-Kiet Tran & Thi Diem-Chinh Ho & Wing-Keung Wong, 2019. "Optimal Solution Techniques in Decision Sciences A Review," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(1), pages 114-161, March.
    11. Thi Hong Van Hoang & Hooi Hooi Lean & Wing-Keung Wong, 2013. "Is Gold Good for Portfolio Diversification? A Stochastic Dominance Analysis of the Paris Stock Exchange," Working Papers 05-13, Association Française de Cliométrie (AFC).
    12. Valenzuela, Maria Rebecca & Wong, Wing-Keung & Zhen, Zhu Zhen, 2017. "Income and Consumption Inequality in the Philippines: A Stochastic Dominance Analysis of Household Unit Records," ADBI Working Papers 662, Asian Development Bank Institute.
    13. Sheung-Chi Chow & Ma. Rebecca Valenzuela & Wing-Keung Wong, 2016. "New Tests for Richness and Poorness:A Stochastic Dominance Analysis of Income Distributions in Hong Kong," Monash Economics Working Papers 25-16, Monash University, Department of Economics.
    14. Lean, Hooi Hooi & McAleer, Michael & Wong, Wing-Keung, 2010. "Market efficiency of oil spot and futures: A mean-variance and stochastic dominance approach," Energy Economics, Elsevier, vol. 32(5), pages 979-986, September.
    15. Wing-Keung Wong & Hooi Hooi Lean & Michael McAleer & Feng-Tse Tsai, 2018. "Why Are Warrant Markets Sustained in Taiwan but Not in China?," Sustainability, MDPI, vol. 10(10), pages 1-17, October.
    16. Al-Khazali, Osamah & Mirzaei, Ali, 2017. "Stock market anomalies, market efficiency and the adaptive market hypothesis: Evidence from Islamic stock indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 190-208.
    17. Bouri, Elie & Gupta, Rangan & Wong, Wing-Keung & Zhu, Zhenzhen, 2018. "Is wine a good choice for investment?," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 171-183.
    18. Hoang, Thi-Hong-Van & Zhu, Zhenzhen & El Khamlichi, Abdelbari & Wong, Wing-Keung, 2019. "Does the Shari’ah screening impact the gold-stock nexus? A sectorial analysis," Resources Policy, Elsevier, vol. 61(C), pages 617-626.
    19. Lean, H.H. & McAleer, M.J. & Wong, W.-K., 2010. "Market Efficiency of Oil Spot and Futures: A Stochastic Dominance Approach," Econometric Institute Research Papers EI 2010-11, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. Ng, Pin & Wong, Wing-Keung & Xiao, Zhijie, 2017. "Stochastic dominance via quantile regression with applications to investigate arbitrage opportunity and market efficiency," European Journal of Operational Research, Elsevier, vol. 261(2), pages 666-678.
    21. Qiao, Zhuo & Wong, Wing-Keung & Fung, Joseph K.W., 2013. "Stochastic dominance relationships between stock and stock index futures markets: International evidence," Economic Modelling, Elsevier, vol. 33(C), pages 552-559.
    22. Nguyen Huu Hau & Tran Trung Tinh & Hoa Anh Tuong & Wing-Keung Wong, 2020. "Review of Matrix Theory with Applications in Education and Decision Sciences," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(1), pages 28-69, March.
    23. Kim-Hung Pho & Thi Diem-Chinh Ho & Tuan-Kiet Tran & Wing-Keung Wong, 2019. "Moment Generating Function, Expectation And Variance Of Ubiquitous Distributions With Applications In Decision Sciences: A Review," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(2), pages 65-150, June.
    24. Hooi Lean & Kok Phoon & Wing-Keung Wong, 2013. "Stochastic dominance analysis of CTA funds," Review of Quantitative Finance and Accounting, Springer, vol. 40(1), pages 155-170, January.
    25. Al-Khazali, Osamah & Lean, Hooi Hooi & Samet, Anis, 2014. "Do Islamic stock indexes outperform conventional stock indexes? A stochastic dominance approach," Pacific-Basin Finance Journal, Elsevier, vol. 28(C), pages 29-46.
    26. Wang, Ming-Hui & Ke, Mei-Chu & Liang Liao, Tung & Chiang, Yi-Chein & Hsu, Chuan-Hao, 2020. "Alternative estimation method of earnings growth rate for PEGR strategy," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    27. Al-Khazali, Osamah, 2014. "Revisiting fast profit investor sentiment and stock returns during Ramadan," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 158-170.

  20. Zhang, Xibin & King, Maxwell L., 2008. "Box-Cox stochastic volatility models with heavy-tails and correlated errors," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 549-566, June.
    See citations under working paper version above.
  21. Robert Brooks & Xibin Zhang & Emawtee Bissoondoyal Bheenick, 2007. "Country risk and the estimation of asset return distributions," Quantitative Finance, Taylor & Francis Journals, vol. 7(3), pages 261-265.

    Cited by:

    1. Chien‐Chiang Lee & Chi‐Chuan Lee & Donald Lien, 2019. "Do country risk and financial uncertainty matter for energy commodity futures?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(3), pages 366-383, March.

  22. Yu, Jun & Yang, Zhenlin & Zhang, Xibin, 2006. "A class of nonlinear stochastic volatility models and its implications for pricing currency options," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2218-2231, December.
    See citations under working paper version above.
  23. Zhang, Xibin & King, Maxwell L. & Hyndman, Rob J., 2006. "A Bayesian approach to bandwidth selection for multivariate kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 50(11), pages 3009-3031, July.

    Cited by:

    1. Y. Ziane & S. Adjabi & N. Zougab, 2015. "Adaptive Bayesian bandwidth selection in asymmetric kernel density estimation for nonnegative heavy-tailed data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(8), pages 1645-1658, August.
    2. Seok Young Hong & Oliver Linton, 2016. "Asymptotic properties of a Nadaraya-Watson type estimator for regression functions of in?finite order," CeMMAP working papers CWP53/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Catalina Bolance & Montserrat Guillen & David Pitt, 2014. "Non-parametric Models for Univariate Claim Severity Distributions - an approach using R," Working Papers 2014-01, Universitat de Barcelona, UB Riskcenter.
    4. Maxwell L. King & Xibin Zhang & Muhammad Akram, 2011. "A New Procedure For Multiple Testing Of Econometric Models," Monash Econometrics and Business Statistics Working Papers 7/11, Monash University, Department of Econometrics and Business Statistics.
    5. Zhang, Xibin & King, Maxwell L., 2008. "Box-Cox stochastic volatility models with heavy-tails and correlated errors," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 549-566, June.
    6. Hong, Seok Young & Linton, Oliver, 2020. "Nonparametric estimation of infinite order regression and its application to the risk-return tradeoff," Journal of Econometrics, Elsevier, vol. 219(2), pages 389-424.
    7. Hu, Shuowen & Poskitt, D.S. & Zhang, Xibin, 2021. "Bayesian estimation for a semiparametric nonlinear volatility model," Economic Modelling, Elsevier, vol. 98(C), pages 361-370.
    8. Hu, Guoqing & You, Fengqi, 2023. "An AI framework integrating physics-informed neural network with predictive control for energy-efficient food production in the built environment," Applied Energy, Elsevier, vol. 348(C).
    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. Anastasios Panagiotelis & Michael S. Smith & Peter J Danaher, 2013. "From Amazon to Apple: Modeling Online Retail Sales, Purchase Incidence and Visit Behavior," Monash Econometrics and Business Statistics Working Papers 5/13, Monash University, Department of Econometrics and Business Statistics.
    11. Zougab, Nabil & Adjabi, Smail & Kokonendji, Célestin C., 2014. "Bayesian estimation of adaptive bandwidth matrices in multivariate kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 28-38.
    12. H. Poulos, 2010. "Spatially explicit mapping of hurricane risk in New England, USA using ArcGIS," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 54(3), pages 1015-1023, September.
    13. Xijian Hu & Yaori Lu & Huiguo Zhang & Haijun Jiang & Qingdong Shi, 2021. "Selection of the Bandwidth Matrix in Spatial Varying Coefficient Models to Detect Anisotropic Regression Relationships," Mathematics, MDPI, vol. 9(18), pages 1-14, September.
    14. Kenneth L. Sørensen & Rune Vejlin, 2014. "Return To Experience And Initial Wage Level: Do Low Wage Workers Catch Up?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(6), pages 984-1006, September.
    15. Xibin Zhang & Maxwell L. King, 2011. "Bayesian semiparametric GARCH models," Monash Econometrics and Business Statistics Working Papers 24/11, Monash University, Department of Econometrics and Business Statistics.
    16. Song Li & Mervyn J. Silvapulle & Param Silvapulle & Xibin Zhang, 2015. "Bayesian Approaches to Nonparametric Estimation of Densities on the Unit Interval," Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 394-412, March.
    17. Xibin Zhang & Robert D. Brooks & Maxwell L. King, 2007. "A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation," Monash Econometrics and Business Statistics Working Papers 11/07, Monash University, Department of Econometrics and Business Statistics.
    18. Bagkavos, Dimitrios & Patil, Prakash N. & Wood, Andrew T.A., 2023. "Nonparametric goodness-of-fit testing for a continuous multivariate parametric model," Journal of Multivariate Analysis, Elsevier, vol. 196(C).
    19. David Pitt & Montserrat Guillén, 2010. "An introduction to parametric and non-parametric models for bivariate positive insurance claim severity distributions," Working Papers XREAP2010-03, Xarxa de Referència en Economia Aplicada (XREAP), revised Mar 2010.
    20. David Pitt & Montserrat Guillen & Catalina Bolancé, 2011. "Estimation of Parametric and Nonparametric Models for Univariate Claim Severity Distributions - an approach using R," Working Papers XREAP2011-06, Xarxa de Referència en Economia Aplicada (XREAP), revised Jun 2011.
    21. Madeleine Cule & Richard Samworth & Michael Stewart, 2010. "Maximum likelihood estimation of a multi‐dimensional log‐concave density," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(5), pages 545-607, November.
    22. Xibin Zhang & Maxwell L. King, 2013. "Gaussian kernel GARCH models," Monash Econometrics and Business Statistics Working Papers 19/13, Monash University, Department of Econometrics and Business Statistics.
    23. Rong Zhang & Brett A. Inder & Xibin Zhang, 2012. "Parameter estimation for a discrete-response model with double rules of sample selection: A Bayesian approach," Monash Econometrics and Business Statistics Working Papers 5/12, Monash University, Department of Econometrics and Business Statistics.
    24. Yasmina Ziane & Nabil Zougab & Smail Adjabi, 2018. "Birnbaum–Saunders power-exponential kernel density estimation and Bayes local bandwidth selection for nonnegative heavy tailed data," Computational Statistics, Springer, vol. 33(1), pages 299-318, March.
    25. Elena Di Bernardino & Didier Rullière, 2015. "Estimation of multivariate critical layers: Applications to rainfall data," Post-Print hal-00940089, HAL.
    26. Groß, Marcus & Rendtel, Ulrich & Schmid, Timo & Schmon, Sebastian & Tzavidis, Nikos, 2015. "Estimating the density of ethnic minorities and aged people in Berlin: Multivariate kernel density estimation applied to sensitive geo-referenced administrative data protected via measurement error," Discussion Papers 2015/7, Free University Berlin, School of Business & Economics.
    27. Mukhopadhyay, Subhadeep & Ghosh, Anil K., 2011. "Bayesian multiscale smoothing in supervised and semi-supervised kernel discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2344-2353, July.
    28. Perrin, G. & Soize, C. & Ouhbi, N., 2018. "Data-driven kernel representations for sampling with an unknown block dependence structure under correlation constraints," Computational Statistics & Data Analysis, Elsevier, vol. 119(C), pages 139-154.
    29. Seok Young Hong & Oliver Linton, 2016. "Asymptotic properties of a Nadaraya-Watson type estimator for regression functions of in finite order," CeMMAP working papers 53/16, Institute for Fiscal Studies.
    30. Tingting Cheng & Jiti Gao & Xibin Zhang, 2016. "Nonparametric Localized Bandwidth Selection for Kernel Density Estimation," Monash Econometrics and Business Statistics Working Papers 7/16, Monash University, Department of Econometrics and Business Statistics.
    31. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2016. "Bayesian Bandwidth Selection for a Nonparametric Regression Model with Mixed Types of Regressors," Econometrics, MDPI, vol. 4(2), pages 1-27, April.
    32. MacDonald, A. & Scarrott, C.J. & Lee, D. & Darlow, B. & Reale, M. & Russell, G., 2011. "A flexible extreme value mixture model," Computational Statistics & Data Analysis, Elsevier, vol. 55(6), pages 2137-2157, June.
    33. Langrené, Nicolas & Warin, Xavier, 2021. "Fast multivariate empirical cumulative distribution function with connection to kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 162(C).
    34. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2011. "Bayesian estimation of bandwidths for a nonparametric regression model with a flexible error density," Monash Econometrics and Business Statistics Working Papers 10/11, Monash University, Department of Econometrics and Business Statistics.
    35. Maxwell King & Xibin Zhang & Muhammad Akram, 2019. "Hypothesis Testing Based on a Vector of Statistics," Monash Econometrics and Business Statistics Working Papers 30/19, Monash University, Department of Econometrics and Business Statistics.
    36. Jha, Amit Prakash & Mahajan, Aarushi & Singh, Sanjay Kumar & Kumar, Piyush, 2022. "Renewable energy proliferation for sustainable development: Role of cross-border electricity trade," Renewable Energy, Elsevier, vol. 201(P1), pages 1189-1199.
    37. Guohua Feng & Chuan Wang & Xibin Zhang, 2019. "Estimation of inefficiency in stochastic frontier models: a Bayesian kernel approach," Journal of Productivity Analysis, Springer, vol. 51(1), pages 1-19, February.
    38. Julia Polak & Maxwell L. King & Xibin Zhang, 2014. "A Model Validation Procedure," Monash Econometrics and Business Statistics Working Papers 21/14, Monash University, Department of Econometrics and Business Statistics.
    39. Filippone, Maurizio & Sanguinetti, Guido, 2011. "Approximate inference of the bandwidth in multivariate kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3104-3122, December.
    40. C J Scarrott & A MacDonald, 2010. "Extreme-value-model-based risk assessment for nuclear reactors," Journal of Risk and Reliability, , vol. 224(4), pages 239-252, December.
    41. Mathieu Langlard & Fabrice Lamadie & Sophie Charton & Johan Debayle, 2021. "Bayesian Inference of a Parametric Random Spheroid from its Orthogonal Projections," Methodology and Computing in Applied Probability, Springer, vol. 23(2), pages 549-567, June.
    42. Sreevani, & Murthy, C.A., 2016. "On bandwidth selection using minimal spanning tree for kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 102(C), pages 67-84.
    43. Matthew D. Baird, 2014. "Cross Validation Bandwidth Selection for Derivatives of Multidimensional Densities," Working Papers WR-1060, RAND Corporation.
    44. Groß, Marcus & Rendtel, Ulrich, 2015. "Kernel density estimation for heaped data," Discussion Papers 2015/27, Free University Berlin, School of Business & Economics.
    45. Marcus Groß & Ulrich Rendtel & Timo Schmid & Sebastian Schmon & Nikos Tzavidis, 2017. "Estimating the density of ethnic minorities and aged people in Berlin: multivariate kernel density estimation applied to sensitive georeferenced administrative data protected via measurement error," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(1), pages 161-183, January.
    46. Tingting Cheng & Jiti Gao & Xibin Zhang, 2014. "Semiparametric Localized Bandwidth Selection for Kernel Density Estimation," Monash Econometrics and Business Statistics Working Papers 27/14, Monash University, Department of Econometrics and Business Statistics.
    47. Hart, Jeffrey D. & Choi, Taeryon & Yi, Seongbaek, 2016. "Frequentist nonparametric goodness-of-fit tests via marginal likelihood ratios," Computational Statistics & Data Analysis, Elsevier, vol. 96(C), pages 120-132.

  24. Xibin Zhang & Maxwell L. King, 2005. "Influence Diagnostics in Generalized Autoregressive Conditional Heteroscedasticity Processes," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 118-129, January.

    Cited by:

    1. Amélie Charles & Olivier Darné, 2012. "Volatility Persistence in Crude Oil Markets," Working Papers hal-00719387, HAL.
    2. F. Javier Trivez & Beatriz Catalan, 2009. "Detecting level shifts in ARMA-GARCH (1,1) Models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(6), pages 679-697.
    3. Charles, Amélie & Darné, Olivier, 2014. "Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 188-199.
    4. Ané, Thierry & Ureche-Rangau, Loredana & Gambet, Jean-Benoît & Bouverot, Julien, 2008. "Robust outlier detection for Asia-Pacific stock index returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(4), pages 326-343, October.
    5. Fukang Zhu & Lei Shi & Shuangzhe Liu, 2015. "Influence diagnostics in log-linear integer-valued GARCH models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(3), pages 311-335, July.
    6. Behmiri, Niaz Bashiri & Manera, Matteo, 2015. "The Role of Outliers and Oil Price Shocks on Volatility of Metal Prices," Energy: Resources and Markets 208768, Fondazione Eni Enrico Mattei (FEEM).
    7. Grané, Aurea & Veiga, Helena, 2010. "Wavelet-based detection of outliers in financial time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2580-2593, November.
    8. Fukang Zhu & Shuangzhe Liu & Lei Shi, 2016. "Local influence analysis for Poisson autoregression with an application to stock transaction data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(1), pages 4-25, February.
    9. Chikashi Tsuji, 2016. "Does the fear gauge predict downside risk more accurately than econometric models? Evidence from the US stock market," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1220711-122, December.
    10. Lei Shi & Md. Mostafizur Rahman & Wen Gan & Jianhua Zhao, 2015. "Stepwise local influence in generalized autoregressive conditional heteroskedasticity models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(2), pages 428-444, February.
    11. Jonathan Dark & Xibin Zhang & Nan Qu, 2010. "Influence diagnostics for multivariate GARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 278-291, July.
    12. Xiaowen Dai & Libin Jin & Anqi Shi & Lei Shi, 2016. "Outlier detection and accommodation in general spatial models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(3), pages 453-475, August.
    13. Loredana Ureche-Rangau & Franck Speeg, 2011. "A simple method for variance shift detection at unknown time points," Economics Bulletin, AccessEcon, vol. 31(3), pages 2204-2218.

  25. Y. K. Tse & K. W. Ng & Xibin Zhang, 2004. "A small‐sample overlapping variance‐ratio test," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(1), pages 127-135, January.

    Cited by:

    1. Amélie Charles & Olivier Darné, 2009. "Variance‐Ratio Tests Of Random Walk: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 23(3), pages 503-527, July.
    2. Amelie Charles & Olivier Darne, 2009. "Testing for Random Walk Behavior in Euro Exchange Rates," Economie Internationale, CEPII research center, issue 119, pages 25-45.
    3. Azad, A.S.M. Sohel, 2009. "Random walk and efficiency tests in the Asia-Pacific foreign exchange markets: Evidence from the post-Asian currency crisis data," Research in International Business and Finance, Elsevier, vol. 23(3), pages 322-338, September.

  26. Xibin Zhang, 2004. "Assessment of Local Influence in GARCH Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(2), pages 301-313, March.

    Cited by:

    1. Carnero, María Ángeles & Peña, Daniel & Ruiz Ortega, Esther, 2004. "Spurious and hidden volatility," DES - Working Papers. Statistics and Econometrics. WS ws042007, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Grossi, Luigi & Laurini, Fabrizio, 2009. "A robust forward weighted Lagrange multiplier test for conditional heteroscedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2251-2263, April.
    3. Grané, Aurea & Veiga, Helena, 2010. "Outliers in Garch models and the estimation of risk measures," DES - Working Papers. Statistics and Econometrics. WS ws100502, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Fukang Zhu & Lei Shi & Shuangzhe Liu, 2015. "Influence diagnostics in log-linear integer-valued GARCH models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(3), pages 311-335, July.
    5. Xibin Zhang & Maxwell L. King, 2002. "Influence Diagnostics in GARCH Processes," Monash Econometrics and Business Statistics Working Papers 19/02, Monash University, Department of Econometrics and Business Statistics.
    6. Grané, Aurea & Veiga, Helena, 2010. "Wavelet-based detection of outliers in financial time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2580-2593, November.
    7. Lei Shi & Md. Mostafizur Rahman & Wen Gan & Jianhua Zhao, 2015. "Stepwise local influence in generalized autoregressive conditional heteroskedasticity models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(2), pages 428-444, February.
    8. L. Grossi & G. Morelli, 2006. "Robust volatility forecasts and model selection in financial time series," Economics Department Working Papers 2006-SE02, Department of Economics, Parma University (Italy).
    9. Jonathan Dark & Xibin Zhang & Nan Qu, 2010. "Influence diagnostics for multivariate GARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 278-291, July.

  27. Y. K. Tse & X. B. Zhang, 2002. "The Variance Ratio Test with Stable Paretian Errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 23(1), pages 117-126, January.

    Cited by:

    1. Donald J. Brown & Rustam Ibragimov, 2005. "Sign Tests for Dependent Observations and Bounds for Path-Dependent Options," Cowles Foundation Discussion Papers 1518, Cowles Foundation for Research in Economics, Yale University.
    2. Donald Brown & Rustam Ibragimov, 2005. "Sign Tests for Dependent Observations and Bounds for Path-Dependent Options," Yale School of Management Working Papers amz2581, Yale School of Management, revised 01 Jul 2005.

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