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Nikolay Gospodinov

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. Richard K. Crump & Nikolay Gospodinov, 2019. "Deconstructing the yield curve," Staff Reports 884, Federal Reserve Bank of New York.

    Cited by:

    1. Moench, Emanuel & Soofi-Siavash, Soroosh, 2022. "What moves treasury yields?," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1016-1043.

  2. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2017. "Too Good to Be True? Fallacies in Evaluating Risk Factor Models," FRB Atlanta Working Paper 2017-9, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2017. "Too Good to Be True? Fallacies in Evaluating Risk Factor Models," FRB Atlanta Working Paper 2017-9, Federal Reserve Bank of Atlanta.
    2. Svetlana Bryzgalova & Jiantao Huang & Christian Julliard, 2023. "Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models," Journal of Finance, American Finance Association, vol. 78(1), pages 487-557, February.
    3. Sentana, Enrique & Manresa, Elena & Penaranda, Francisco, 2017. "Empirical Evaluation of Overspecified Asset Pricing Models," CEPR Discussion Papers 12085, C.E.P.R. Discussion Papers.
    4. Raymond Kan & Cesare Robotti, 0. "Comment on: Pseudo-True SDFs in Conditional Asset Pricing Models," Journal of Financial Econometrics, Oxford University Press, vol. 18(4), pages 729-735.
    5. Lin, Qi, 2021. "The q5 model and its consistency with the intertemporal CAPM," Journal of Banking & Finance, Elsevier, vol. 127(C).
    6. Hansen, Erwin, 2022. "Economic evaluation of asset pricing models under predictability," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 50-66.
    7. Gospodinov, Nikolay & Robotti, Cesare, 2021. "Common pricing across asset classes: Empirical evidence revisited," Journal of Financial Economics, Elsevier, vol. 140(1), pages 292-324.
    8. Marie-Claude Beaulieu & Jean-Marie Dufour & Lynda Khalaf, 2020. "Arbitrage Pricing, Weak Beta, Strong Beta: Identification-Robust and Simultaneous Inference," CIRANO Working Papers 2020s-30, CIRANO.
    9. Jamali, Ibrahim & Yamani, Ehab & Smallwood, Aaron D., 2023. "An investment-based explanation of currency excess returns," Journal of International Money and Finance, Elsevier, vol. 133(C).
    10. Zhang, Xiang, 2020. "Leisure and long-run risks: An empirical evaluation on value premium puzzle," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).

  3. Nikolay Gospodinov, 2017. "Asset Co-movements: Features and Challenges," FRB Atlanta Working Paper 2017-11, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Tsionas, Mike G. & Philippas, Dionisis & Philippas, Nikolaos, 2022. "Multivariate stochastic volatility for herding detection: Evidence from the energy sector," Energy Economics, Elsevier, vol. 109(C).

  4. Nikolay Gospodinov & Esfandiar Maasoumi, 2017. "General Aggregation of Misspecified Asset Pricing Models," FRB Atlanta Working Paper 2017-10, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Bertille Antoine & Prosper Dovonon, 2020. "Robust Estimation with Exponentially Tilted Hellinger Distance," Discussion Papers dp20-02, Department of Economics, Simon Fraser University.
    2. L. Ponta & A. Carbone, 2019. "Quantifying horizon dependence of asset prices: a cluster entropy approach," Papers 1908.00257, arXiv.org, revised Apr 2020.
    3. Ponta, Linda & Carbone, Anna, 2018. "Information measure for financial time series: Quantifying short-term market heterogeneity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 132-144.
    4. Gospodinov, Nikolay & Maasoumi, Esfandiar, 2021. "Generalized aggregation of misspecified models: With an application to asset pricing," Journal of Econometrics, Elsevier, vol. 222(1), pages 451-467.

  5. Nikolay Gospodinov, 2016. "The role of commodity prices in forecasting U.S. core inflation," FRB Atlanta Working Paper 2016-5, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Anthony Garratt & Ivan Petrella, 2022. "Commodity prices and inflation risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 392-414, March.
    2. Gospodinov, Nikolay & Maasoumi, Esfandiar, 2021. "Generalized aggregation of misspecified models: With an application to asset pricing," Journal of Econometrics, Elsevier, vol. 222(1), pages 451-467.

  6. Nikolay Gospodinov & Bin Wei, 2016. "Forecasts of inflation and interest rates in no-arbitrage affine models," FRB Atlanta Working Paper 2016-3, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Abrahams, Michael & Adrian, Tobias & Crump, Richard K. & Moench, Emanuel & Yu, Rui, 2016. "Decomposing real and nominal yield curves," Journal of Monetary Economics, Elsevier, vol. 84(C), pages 182-200.
    2. Dbouk, Wassim & Jamali, Ibrahim, 2018. "Predicting daily oil prices: Linear and non-linear models," Research in International Business and Finance, Elsevier, vol. 46(C), pages 149-165.
    3. Nikolay Gospodinov, 2016. "The role of commodity prices in forecasting U.S. core inflation," FRB Atlanta Working Paper 2016-5, Federal Reserve Bank of Atlanta.

  7. Nikolay Gospodinov & Hai V. Nguyen, 2015. "Long-Term Health Effects of Vietnam War's Herbicide Exposure on the Vietnamese Population," Working Papers 150019, Canadian Centre for Health Economics.

    Cited by:

    1. Le, Duong Trung & Pham, Thanh Minh & Polachek, Solomon, 2022. "The long-term health impact of Agent Orange: Evidence from the Vietnam War," World Development, Elsevier, vol. 155(C).

  8. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2015. "Asymptotic variance approximations for invariant estimators in uncertain asset-pricing models," FRB Atlanta Working Paper 2015-9, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2017. "Too Good to Be True? Fallacies in Evaluating Risk Factor Models," FRB Atlanta Working Paper 2017-9, Federal Reserve Bank of Atlanta.
    2. Gospodinov, Nikolay & Robotti, Cesare, 2021. "Common pricing across asset classes: Empirical evidence revisited," Journal of Financial Economics, Elsevier, vol. 140(1), pages 292-324.

  9. Stanislav Anatolyev & Nikolay Gospodinov, 2015. "Multivariate return decomposition: theory and implications," FRB Atlanta Working Paper 2015-7, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Stanislav Anatolyev, 2021. "Directional news impact curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 94-107, January.
    2. Chen, Nan-Kuang & Chen, Shiu-Sheng & Chou, Yu-Hsi, 2013. "Further evidence on bear market predictability: The role of the external finance premium," MPRA Paper 49093, University Library of Munich, Germany.
    3. Nikolay Gospodinov, 2017. "Asset Co-movements: Features and Challenges," FRB Atlanta Working Paper 2017-11, Federal Reserve Bank of Atlanta.

  10. Nikolay Gospodinov & Ivana Komunjer & Serena Ng, 2014. "Minimum Distance Estimation of Dynamic Models with Errors-In-Variables," FRB Atlanta Working Paper 2014-11, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Meijer, Erik & Spierdijk, Laura & Wansbeek, Tom, 2017. "Consistent estimation of linear panel data models with measurement error," Journal of Econometrics, Elsevier, vol. 200(2), pages 169-180.
    2. Gospodinov, Nikolay & Komunjer, Ivana & Ng, Serena, 2017. "Simulated minimum distance estimation of dynamic models with errors-in-variables," Journal of Econometrics, Elsevier, vol. 200(2), pages 181-193.

  11. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2014. "Spurious Inference in Unidentified Asset-Pricing Models," FRB Atlanta Working Paper 2014-12, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2017. "Too Good to Be True? Fallacies in Evaluating Risk Factor Models," FRB Atlanta Working Paper 2017-9, Federal Reserve Bank of Atlanta.
    2. Frank Windmeijer, 2018. "Testing Over- and Underidentification in Linear Models, with Applications to Dynamic Panel Data and Asset-Pricing Models," Bristol Economics Discussion Papers 18/696, School of Economics, University of Bristol, UK.
    3. Stefano Giglio & Dacheng Xiu, 2017. "Inference on Risk Premia in the Presence of Omitted Factors," NBER Working Papers 23527, National Bureau of Economic Research, Inc.
    4. Stanislav Anatolyev & Anna Mikusheva, 2018. "Factor models with many assets: strong factors, weak factors, and the two-pass procedure," Papers 1807.04094, arXiv.org, revised Apr 2019.
    5. Craig Burnside, 2016. "Identification and Inference in Linear Stochastic Discount Factor Models with Excess Returns," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 295-330.
    6. Sentana, Enrique & Manresa, Elena & Penaranda, Francisco, 2017. "Empirical Evaluation of Overspecified Asset Pricing Models," CEPR Discussion Papers 12085, C.E.P.R. Discussion Papers.
    7. Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Ernst Schaumburg, 2020. "Characteristic-Sorted Portfolios: Estimation and Inference," The Review of Economics and Statistics, MIT Press, vol. 102(3), pages 531-551, July.
    8. Nikolay Gospodinov & Esfandiar Maasoumi, 2017. "General Aggregation of Misspecified Asset Pricing Models," FRB Atlanta Working Paper 2017-10, Federal Reserve Bank of Atlanta.
    9. Yinchu Zhu, 2019. "How well can we learn large factor models without assuming strong factors?," Papers 1910.10382, arXiv.org, revised Nov 2019.
    10. He, Zhongzhi (Lawrence) & Zhu, Jie & Zhu, Xiaoneng, 2015. "Dynamic factors and asset pricing: International and further U.S. evidence," Pacific-Basin Finance Journal, Elsevier, vol. 32(C), pages 21-39.
    11. Shang, Hua & Yuan, Ping & Huang, Lin, 2016. "Macroeconomic factors and the cross-section of commodity futures returns," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 316-332.

  12. Hirbod Assa & Nikolay Gospodinov, 2014. "Hedging and Pricing in Imperfect Markets under Non-Convexity," FRB Atlanta Working Paper 2014-13, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Nikolay Gospodinov, 2017. "Asset Co-movements: Features and Challenges," FRB Atlanta Working Paper 2017-11, Federal Reserve Bank of Atlanta.

  13. Nikolay Gospodinov & Ibrahim Jamali, 2014. "The Response of Stock Market Volatility to Futures-Based Measures of Monetary Policy Shocks," FRB Atlanta Working Paper 2014-14, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Fady Barsoum, 2013. "The Effects of Monetary Policy Shocks on a Panel of Stock Market Volatilities: A Factor-Augmented Bayesian VAR Approach," Working Paper Series of the Department of Economics, University of Konstanz 2013-15, Department of Economics, University of Konstanz.
    2. Kapp, Daniel & Kristiansen, Kristian, 2021. "Euro area equity risk premia and monetary policy: a longer-term perspective," Working Paper Series 2535, European Central Bank.
    3. Aakriti Mathur & Rajeswari Sengupta, 2019. "Analysing monetary policy statements of the Reserve Bank of India," IHEID Working Papers 08-2019, Economics Section, The Graduate Institute of International Studies.
    4. Chen, Wei & Xu, Huilin & Jia, Lifen & Gao, Ying, 2021. "Machine learning model for Bitcoin exchange rate prediction using economic and technology determinants," International Journal of Forecasting, Elsevier, vol. 37(1), pages 28-43.
    5. Picault, Matthieu & Raffestin, Louis, 2020. "The other side of forward guidance: Are central banks constrained by financial markets?," Finance Research Letters, Elsevier, vol. 36(C).
    6. Muhammad Ali Nasir & Muhammad Shahbaz & Trinh Thi Mai & Moade Shubita, 2021. "Development of Vietnamese stock market: Influence of domestic macroeconomic environment and regional markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1435-1458, January.
    7. Tosin B. Fateye & Oluwaseun D. Ajay & Cyril A. Ajay, 2021. "Modelling of Daily Price Volatility of South Africa Property Stock Market Using GARCH Analysis," AfRES 2021-013, African Real Estate Society (AfRES).
    8. Prabu A, Edwin & Bhattacharyya, Indranil & Ray, Partha, 2016. "Is the stock market impervious to monetary policy announcements: Evidence from emerging India," International Review of Economics & Finance, Elsevier, vol. 46(C), pages 166-179.
    9. Houssam Bouzgarrou & Tarek Chebbi, 2016. "The reaction of sovereign CDS spread volatilities to news announcements," Journal of Asset Management, Palgrave Macmillan, vol. 17(5), pages 347-360, September.
    10. Aliyu, Shehu Usman Rano, 2020. "What have we learnt from modelling stock returns in Nigeria: Higgledy-piggledy?," MPRA Paper 110382, University Library of Munich, Germany, revised 06 Jun 2021.
    11. Apergis, Nicholas & Chatziantoniou, Ioannis & Cooray, Arusha, 2020. "Monetary policy and commodity markets: Unconventional versus conventional impact and the role of economic uncertainty," International Review of Financial Analysis, Elsevier, vol. 71(C).
    12. Fang Fang & Weijia Dong & Xin Lv, 2016. "Asymmetric Reactions of China¡¯s Stock Market to Short-term Interest Rates," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(5), pages 260-270, May.
    13. Jiang, Yonghong & Ao, Zhiming & Mo, Bin, 2023. "The risk spillover between China’s economic policy uncertainty and commodity markets: Evidence from frequency spillover and quantile connectedness approaches," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
    14. Dridi, Ichrak & Boughrara, Adel, 2023. "Flexible inflation targeting and stock market volatility: Evidence from emerging market economies," Economic Modelling, Elsevier, vol. 126(C).
    15. Ahmed Al Samman & Mahmoud Moustafa Otaify, 2017. "How Does Volatility of Characteristics-sorted Portfolios Respond to Macroeconomic Volatility?," International Journal of Economics and Financial Issues, Econjournals, vol. 7(4), pages 300-315.
    16. Pradhan, Rudra P. & Hall, John H. & du Toit, Elda, 2021. "The lead–lag relationship between spot and futures prices: Empirical evidence from the Indian commodity market," Resources Policy, Elsevier, vol. 70(C).
    17. He, Feng & Ma, Feng & Wang, Ziwei & Yang, Bohan, 2021. "Asymmetric volatility spillover between oil-importing and oil-exporting countries' economic policy uncertainty and China's energy sector," International Review of Financial Analysis, Elsevier, vol. 75(C).
    18. Feng He & Libo Yin, 2021. "Shocks to the equity capital ratio of financial intermediaries and the predictability of stock return volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 945-962, September.
    19. Wen, Fenghua & Shui, Aojie & Cheng, Yuxiang & Gong, Xu, 2022. "Monetary policy uncertainty and stock returns in G7 and BRICS countries: A quantile-on-quantile approach," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 457-482.
    20. Julio Pindado & Ignacio Requejo & Juan C. Rivera, 2020. "Does money supply shape corporate capital structure? International evidence from a panel data analysis," The European Journal of Finance, Taylor & Francis Journals, vol. 26(6), pages 554-584, April.
    21. Lopomo Beteto Wegner, Danilo, 2015. "Government insurance, information, and asset prices," International Review of Economics & Finance, Elsevier, vol. 37(C), pages 165-183.

  14. Nikolay Gospodinov & Ibrahim Jamali, 2013. "Monetary policy surprises, positions of traders, and changes in commodity futures prices," FRB Atlanta Working Paper 2013-12, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Yao, Wei & Alexiou, Constantinos, 2022. "Exploring the transmission mechanism of speculative and inventory arbitrage activity to commodity price volatility. Novel evidence for the US economy," International Review of Financial Analysis, Elsevier, vol. 80(C).
    2. Triantafyllou, Athanasios & Dotsis, George, 2017. "Option-implied expectations in commodity markets and monetary policy," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 1-17.
    3. Shang, Hua & Yuan, Ping & Huang, Lin, 2016. "Macroeconomic factors and the cross-section of commodity futures returns," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 316-332.

  15. Nikolay Gospodinov & Serena Ng, 2013. "Minimum distance estimation of possibly non-invertible moving average models," FRB Atlanta Working Paper 2013-11, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Alain Guay, 2020. "Identification of Structural Vector Autoregressions Through Higher Unconditional Moments," Working Papers 20-19, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    2. Jean-Jacques Forneron, 2019. "Detecting Identification Failure in Moment Condition Models," Papers 1907.13093, arXiv.org, revised Oct 2023.
    3. Guay, Alain, 2021. "Identification of structural vector autoregressions through higher unconditional moments," Journal of Econometrics, Elsevier, vol. 225(1), pages 27-46.
    4. João Henrique Gonçalves Mazzeu & Esther Ruiz & Helena Veiga, 2018. "Uncertainty And Density Forecasts Of Arma Models: Comparison Of Asymptotic, Bayesian, And Bootstrap Procedures," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 388-419, April.
    5. Lynda Khalaf & Beatriz Peraza López, 2020. "Simultaneous Indirect Inference, Impulse Responses and ARMA Models," Econometrics, MDPI, vol. 8(2), pages 1-26, April.
    6. Josef Arlt, 2023. "The problem of annual inflation rate indicator," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2772-2788, July.
    7. Jean-Jacques Forneron, 2019. "A Sieve-SMM Estimator for Dynamic Models," Papers 1902.01456, arXiv.org, revised Jan 2023.
    8. Jean‐Jacques Forneron, 2023. "A Sieve‐SMM Estimator for Dynamic Models," Econometrica, Econometric Society, vol. 91(3), pages 943-977, May.
    9. Nikolay Gospodinov & Ivana Komunjer & Serena Ng, 2014. "Minimum Distance Estimation of Dynamic Models with Errors-In-Variables," FRB Atlanta Working Paper 2014-11, Federal Reserve Bank of Atlanta.
    10. Alain Hecq & Daniel Velasquez-Gaviria, 2023. "Spectral identification and estimation of mixed causal-noncausal invertible-noninvertible models," Papers 2310.19543, arXiv.org.

  16. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2013. "Misspecification-robust inference in linear asset pricing models with irrelevant risk factors," FRB Atlanta Working Paper 2013-09, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2017. "Too Good to Be True? Fallacies in Evaluating Risk Factor Models," FRB Atlanta Working Paper 2017-9, Federal Reserve Bank of Atlanta.
    2. Zhang, Xiang & Liu, Yangyi & Wu, Kun & Maillet, Bertrand, 2021. "Tradable or nontradable factors—what does the Hansen–Jagannathan distance tell us?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 853-879.
    3. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2018. "Asymptotic variance approximations for invariant estimators in uncertain asset-pricing models," Econometric Reviews, Taylor & Francis Journals, vol. 37(7), pages 695-718, August.
    4. Tobias Adrian & Richard K. Crump & Emanuel Moench, 2011. "Regression-based estimation of dynamic asset pricing models," Staff Reports 493, Federal Reserve Bank of New York.
    5. Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2022. "Eigenvalue tests for the number of latent factors in short panels," Papers 2210.16042, arXiv.org.
    6. Shi, Qi, 2020. "A much robust and updated evidences of the alternative real-estate based asset pricing," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    7. Gagliardini, Patrick & Ossola, Elisa & Scaillet, Olivier, 2019. "Estimation of large dimensional conditional factor models in finance," Working Papers unige:125031, University of Geneva, Geneva School of Economics and Management.
    8. Stefano Giglio & Dacheng Xiu, 2017. "Inference on Risk Premia in the Presence of Omitted Factors," NBER Working Papers 23527, National Bureau of Economic Research, Inc.
    9. Svetlana Bryzgalova & Jiantao Huang & Christian Julliard, 2023. "Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models," Journal of Finance, American Finance Association, vol. 78(1), pages 487-557, February.
    10. Bertille Antoine & Prosper Dovonon, 2020. "Robust Estimation with Exponentially Tilted Hellinger Distance," Discussion Papers dp20-02, Department of Economics, Simon Fraser University.
    11. Beaulieu, Marie-Claude & Gagnon, Marie-Hélène & Khalaf, Lynda, 2016. "Less is more: Testing financial integration using identification-robust asset pricing models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 45(C), pages 171-190.
    12. Khalaf, Lynda & Schaller, Huntley, 2016. "Identification and inference in two-pass asset pricing models," Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 165-177.
    13. Peter Christoffersen & Mathieu Fournier & Kris Jacobs & Mehdi Karoui, 2015. "Option-Based Estimation of the Price of Co-Skewness and Co-Kurtosis Risk," CREATES Research Papers 2015-54, Department of Economics and Business Economics, Aarhus University.
    14. Aleksejs Krecetovs & Pasquale Della Corte, 2016. "Macro uncertainty and currency premia," 2016 Meeting Papers 624, Society for Economic Dynamics.
    15. Gregory Connor & Robert A. Korajczyk, 2019. "Semi-strong factors in asset returns," Economics Department Working Paper Series n294-19.pdf, Department of Economics, National University of Ireland - Maynooth.
    16. Patrick Gagliardini & Elisa Ossola & Olivier Scaillet, 2016. "A diagnostic criterion for approximate factor structure," Papers 1612.04990, arXiv.org, revised Aug 2017.
    17. Patrick Gagliardini & Diego Ronchetti, 2020. "Comparing Asset Pricing Models by the Conditional Hansen-Jagannathan Distance," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 333-394.
    18. Xyngis, Georgios, 2017. "Business-cycle variation in macroeconomic uncertainty and the cross-section of expected returns: Evidence for scale-dependent risks," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 43-65.
    19. Craig Burnside, 2016. "Identification and Inference in Linear Stochastic Discount Factor Models with Excess Returns," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 295-330.
    20. Momani, Mohammad Q.M., 2018. "Revisiting Pastor–Stambaugh liquidity factor," Economics Letters, Elsevier, vol. 163(C), pages 190-192.
    21. Toda, Alexis Akira & Walsh, Kieran James, 2016. "Fat Tails and Spurious Estimation of Consumption-Based Asset Pricing Models," MPRA Paper 78980, University Library of Munich, Germany.
    22. Raymond Kan & Cesare Robotti, 0. "Comment on: Pseudo-True SDFs in Conditional Asset Pricing Models," Journal of Financial Econometrics, Oxford University Press, vol. 18(4), pages 729-735.
    23. Frank Kleibergen & Zhaoguo Zhan, 2022. "Misspecification and Weak Identification in Asset Pricing," Papers 2206.13600, arXiv.org.
    24. Esfandiar Maasoumi & Almas Heshmati & Inhee Lee, 2021. "Green innovations and patenting renewable energy technologies," Empirical Economics, Springer, vol. 60(1), pages 513-538, January.
    25. Lin, Qi, 2021. "The q5 model and its consistency with the intertemporal CAPM," Journal of Banking & Finance, Elsevier, vol. 127(C).
    26. Joachim Freyberger & Andreas Neuhierl & Michael Weber & Michael Weber, 2018. "Dissecting Characteristics Nonparametrically," CESifo Working Paper Series 7187, CESifo.
    27. Lin, Xiaoji & Palazzo, Berardino & Yang, Fan, 2020. "The risks of old capital age: Asset pricing implications of technology adoption," Journal of Monetary Economics, Elsevier, vol. 115(C), pages 145-161.
    28. Frank Kleibergen & Zhaoguo Zhan, 2014. "Unexplained factors and their effects on second pass R-squared’s," UvA-Econometrics Working Papers 14-05, Universiteit van Amsterdam, Dept. of Econometrics.
    29. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2016. "On the properties of the constrained Hansen–Jagannathan distance," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 121-150.
    30. Bruzda, Joanna, 2019. "Complex analytic wavelets in the measurement of macroeconomic risks," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    31. Gospodinov, Nikolay & Robotti, Cesare, 2021. "Common pricing across asset classes: Empirical evidence revisited," Journal of Financial Economics, Elsevier, vol. 140(1), pages 292-324.
    32. Marie-Claude Beaulieu & Jean-Marie Dufour & Lynda Khalaf, 2020. "Arbitrage Pricing, Weak Beta, Strong Beta: Identification-Robust and Simultaneous Inference," CIRANO Working Papers 2020s-30, CIRANO.
    33. Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2023. "Latent Factor Analysis in Short Panels," Papers 2306.14004, arXiv.org.
    34. Kim, Jinyong & Kim, Kun Ho & Lee, Jeong Hwan, 2021. "Cross-sectional tests of asset pricing models with full-rank mimicking portfolios," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    35. Laurinaityte, Nora & Meinerding, Christoph & Schlag, Christian & Thimme, Julian, 2020. "GMM weighting matrices incross-sectional asset pricing tests," Discussion Papers 62/2020, Deutsche Bundesbank.
    36. Shang, Hua & Yuan, Ping & Huang, Lin, 2016. "Macroeconomic factors and the cross-section of commodity futures returns," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 316-332.
    37. Beaulieu, Marie-Claude & Dufour, Jean-Marie & Khalaf, Lynda & Melin, Olena, 2023. "Identification-robust beta pricing, spanning, mimicking portfolios, and the benchmark neutrality of catastrophe bonds," Journal of Econometrics, Elsevier, vol. 236(1).
    38. Barras, Laurent, 2019. "A large-scale approach for evaluating asset pricing models," Journal of Financial Economics, Elsevier, vol. 134(3), pages 549-569.
    39. Sun, Yang & Zhang, Xuan & Zhang, Zhekai, 2022. "The reduced-rank beta in linear stochastic discount factor models," International Review of Financial Analysis, Elsevier, vol. 84(C).
    40. Nikolay Gospodinov & Ibrahim Jamali, 2018. "Monetary policy uncertainty, positions of traders and changes in commodity futures prices," European Financial Management, European Financial Management Association, vol. 24(2), pages 239-260, March.
    41. Bretscher, Lorenzo & Hsu, Alex & Tamoni, Andrea, 2020. "Fiscal policy driven bond risk premia," Journal of Financial Economics, Elsevier, vol. 138(1), pages 53-73.
    42. Li, Huan, 2020. "Asset pricing with long-run durable expenditure risk," Finance Research Letters, Elsevier, vol. 32(C).
    43. Gospodinov, Nikolay & Maasoumi, Esfandiar, 2021. "Generalized aggregation of misspecified models: With an application to asset pricing," Journal of Econometrics, Elsevier, vol. 222(1), pages 451-467.

  17. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2012. "Robust inference in linear asset pricing models," FRB Atlanta Working Paper 2012-17, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2017. "Too Good to Be True? Fallacies in Evaluating Risk Factor Models," FRB Atlanta Working Paper 2017-9, Federal Reserve Bank of Atlanta.
    2. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2018. "Asymptotic variance approximations for invariant estimators in uncertain asset-pricing models," Econometric Reviews, Taylor & Francis Journals, vol. 37(7), pages 695-718, August.
    3. Tobias Adrian & Richard K. Crump & Emanuel Moench, 2011. "Regression-based estimation of dynamic asset pricing models," Staff Reports 493, Federal Reserve Bank of New York.
    4. Torben G. Andersen & Martin Thyrsgaard & Viktor Todorov, 2019. "Cross-Sectional Dispersion of Risk in Trading Time," NBER Working Papers 26329, National Bureau of Economic Research, Inc.
    5. Aleksejs Krecetovs & Pasquale Della Corte, 2016. "Macro uncertainty and currency premia," 2016 Meeting Papers 624, Society for Economic Dynamics.
    6. Gregory Connor & Robert A. Korajczyk, 2019. "Semi-strong factors in asset returns," Economics Department Working Paper Series n294-19.pdf, Department of Economics, National University of Ireland - Maynooth.
    7. Patrick Gagliardini & Elisa Ossola & Olivier Scaillet, 2016. "A diagnostic criterion for approximate factor structure," Papers 1612.04990, arXiv.org, revised Aug 2017.
    8. Xyngis, Georgios, 2017. "Business-cycle variation in macroeconomic uncertainty and the cross-section of expected returns: Evidence for scale-dependent risks," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 43-65.
    9. Craig Burnside, 2016. "Identification and Inference in Linear Stochastic Discount Factor Models with Excess Returns," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 295-330.
    10. Toda, Alexis Akira & Walsh, Kieran James, 2016. "Fat Tails and Spurious Estimation of Consumption-Based Asset Pricing Models," MPRA Paper 78980, University Library of Munich, Germany.
    11. Joachim Freyberger & Andreas Neuhierl & Michael Weber & Michael Weber, 2018. "Dissecting Characteristics Nonparametrically," CESifo Working Paper Series 7187, CESifo.
    12. Barras, Laurent, 2019. "A large-scale approach for evaluating asset pricing models," Journal of Financial Economics, Elsevier, vol. 134(3), pages 549-569.

  18. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2011. "Chi-squared tests for evaluation and comparison of asset pricing models," FRB Atlanta Working Paper 2011-08, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Zhang, Xiang & Liu, Yangyi & Wu, Kun & Maillet, Bertrand, 2021. "Tradable or nontradable factors—what does the Hansen–Jagannathan distance tell us?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 853-879.
    2. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2018. "Asymptotic variance approximations for invariant estimators in uncertain asset-pricing models," Econometric Reviews, Taylor & Francis Journals, vol. 37(7), pages 695-718, August.
    3. Ahmed, Shamim & Bu, Ziwen & Symeonidis, Lazaros & Tsvetanov, Daniel, 2023. "Which factor model? A systematic return covariation perspective," Journal of International Money and Finance, Elsevier, vol. 136(C).
    4. Stefano Giglio & Dacheng Xiu, 2017. "Inference on Risk Premia in the Presence of Omitted Factors," NBER Working Papers 23527, National Bureau of Economic Research, Inc.
    5. Beaulieu, Marie-Claude & Gagnon, Marie-Hélène & Khalaf, Lynda, 2016. "Less is more: Testing financial integration using identification-robust asset pricing models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 45(C), pages 171-190.
    6. Patrick Gagliardini & Diego Ronchetti, 2020. "Comparing Asset Pricing Models by the Conditional Hansen-Jagannathan Distance," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 333-394.
    7. Fletcher, Jonathan, 2018. "Bayesian tests of global factor models," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 279-289.
    8. Kim, Soohun & Skoulakis, Georgios, 2018. "Ex-post risk premia estimation and asset pricing tests using large cross sections: The regression-calibration approach," Journal of Econometrics, Elsevier, vol. 204(2), pages 159-188.
    9. J. Davies & Jonathan Fletcher & Andrew Marshall, 2015. "Testing index-based models in U.K. stock returns," Review of Quantitative Finance and Accounting, Springer, vol. 45(2), pages 337-362, August.
    10. Alastair R. Hall, 2015. "Econometricians Have Their Moments: GMM at 32," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 1-24, June.
    11. Raymond Kan & Cesare Robotti, 0. "Comment on: Pseudo-True SDFs in Conditional Asset Pricing Models," Journal of Financial Econometrics, Oxford University Press, vol. 18(4), pages 729-735.
    12. Francesco Bravo, 2022. "Misspecified semiparametric model selection with weakly dependent observations," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(4), pages 558-586, July.
    13. Borup, Daniel, 2019. "Asset pricing model uncertainty," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 166-189.
    14. Nikolay Gospodinov & Esfandiar Maasoumi, 2017. "General Aggregation of Misspecified Asset Pricing Models," FRB Atlanta Working Paper 2017-10, Federal Reserve Bank of Atlanta.
    15. Fletcher, Jonathan, 2019. "Model comparison tests of linear factor models in U.K. stock returns," Finance Research Letters, Elsevier, vol. 28(C), pages 281-291.
    16. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2016. "On the properties of the constrained Hansen–Jagannathan distance," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 121-150.
    17. Gospodinov, Nikolay & Robotti, Cesare, 2021. "Common pricing across asset classes: Empirical evidence revisited," Journal of Financial Economics, Elsevier, vol. 140(1), pages 292-324.
    18. Díaz Antonia & Puch Luis A., 2019. "Investment, technological progress and energy efficiency," The B.E. Journal of Macroeconomics, De Gruyter, vol. 19(2), pages 1-28, June.
    19. Kim, Jinyong & Kim, Kun Ho & Lee, Jeong Hwan, 2021. "Cross-sectional tests of asset pricing models with full-rank mimicking portfolios," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    20. Fletcher, Jonathan, 2014. "Benchmark models of expected returns in U.K. portfolio performance: An empirical investigation," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 30-46.
    21. Kwan, Yum K. & Leung, Charles Ka Yui & Dong, Jinyue, 2015. "Comparing consumption-based asset pricing models: The case of an Asian city," Journal of Housing Economics, Elsevier, vol. 28(C), pages 18-41.
    22. Prosper Donovon & Alastair R. Hall, 2015. "GMM and Indirect Inference: An appraisal of their connections and new results on their properties under second order identification," Economics Discussion Paper Series 1505, Economics, The University of Manchester.
    23. Ma, Xiuli & Zhang, Xindong & Liu, Weimin, 2021. "Further tests of asset pricing models: Liquidity risk matters," Economic Modelling, Elsevier, vol. 95(C), pages 255-273.
    24. Atsushi Inoue & Barbara Rossi, 2015. "Tests for the validity of portfolio or group choice in financial and panel regressions," Economics Working Papers 1523, Department of Economics and Business, Universitat Pompeu Fabra.
    25. Gospodinov, Nikolay & Maasoumi, Esfandiar, 2021. "Generalized aggregation of misspecified models: With an application to asset pricing," Journal of Econometrics, Elsevier, vol. 222(1), pages 451-467.

  19. Nikolay Gospodinov & Damba Lkhagvasuren, 2011. "A Moment-Matching Method for Approximating Vector Autoregressive Processes by Finite-State Markov Chains," Working Papers 11005, Concordia University, Department of Economics, revised 16 Dec 2011.

    Cited by:

    1. Xing Guo & Pablo Ottonello & Diego J. Perez, 2023. "Monetary Policy and Redistribution in Open Economies," Journal of Political Economy Macroeconomics, University of Chicago Press, vol. 1(1), pages 191-241.
    2. Ethan Struby & Michael F. Connolly, 2022. "Shadow Rate Models and Monetary Policy," Working Papers 2022-03, Carleton College, Department of Economics.
    3. Gianluca Benigno & Huigang Chen & Christopher Otrok & Alessandro Rebucci & Eric R. Young, 2011. "Optimal Capital Controls and Real Exchange Rate Policies: A Pecuniary Externality Perspective," Discussion Papers 1512, Centre for Macroeconomics (CFM), revised Feb 2015.
    4. Eva F. Janssens & Sean McCrary, 2023. "Finite-State Markov-Chain Approximations: A Hidden Markov Approach," Finance and Economics Discussion Series 2023-040, Board of Governors of the Federal Reserve System (U.S.).
    5. Rabitsch, Katrin & Stepanchuk, Serhiy & Tsyrennikov, Viktor, 2015. "International portfolios: A comparison of solution methods," Journal of International Economics, Elsevier, vol. 97(2), pages 404-422.
    6. Tanaka, Ken'ichiro & Toda, Alexis Akira, 2015. "Discretizing Distributions with Exact Moments: Error Estimate and Convergence Analysis," University of California at San Diego, Economics Working Paper Series qt7g23r5kh, Department of Economics, UC San Diego.
    7. Leland E. Farmer & Alexis Akira Toda, 2017. "Discretizing nonlinear, non‐Gaussian Markov processes with exact conditional moments," Quantitative Economics, Econometric Society, vol. 8(2), pages 651-683, July.
    8. Grey Gordon, 2020. "Efficient VAR Discretization," Working Paper 20-06, Federal Reserve Bank of Richmond.
    9. Lauren E. Cipriano & Thomas A. Weber, 2018. "Population-level intervention and information collection in dynamic healthcare policy," Health Care Management Science, Springer, vol. 21(4), pages 604-631, December.
    10. Jordan Roulleau-Pasdeloup, 2022. "Analyzing Linear DSGE models: the Method of Undetermined Markov States," Papers 2209.05081, arXiv.org, revised Feb 2023.
    11. Leland E. Farmer, 2021. "The discretization filter: A simple way to estimate nonlinear state space models," Quantitative Economics, Econometric Society, vol. 12(1), pages 41-76, January.

  20. Gospodinov, Nikolay & Lkhagvasuren, Damba, 2011. "A new method for approximating vector autoregressive processes by finite-state Markov chains," MPRA Paper 33827, University Library of Munich, Germany.

    Cited by:

    1. Douglas J. Miller & George Judge, 2015. "Information Recovery in a Dynamic Statistical Markov Model," Econometrics, MDPI, vol. 3(2), pages 1-12, March.

  21. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2010. "On the Hansen-Jagannathan distance with a no-arbitrage constraint," FRB Atlanta Working Paper 2010-04, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2013. "Chi-squared tests for evaluation and comparison of asset pricing models," Journal of Econometrics, Elsevier, vol. 173(1), pages 108-125.
    2. Hammami, Yacine & Lindahl, Anna, 2014. "An intertemporal capital asset pricing model with bank credit growth as a state variable," Journal of Banking & Finance, Elsevier, vol. 39(C), pages 14-28.
    3. J. Davies & Jonathan Fletcher & Andrew Marshall, 2015. "Testing index-based models in U.K. stock returns," Review of Quantitative Finance and Accounting, Springer, vol. 45(2), pages 337-362, August.
    4. Yuan Liao & Anna Simoni, 2019. "Bayesian inference for partially identified smooth convex models," Post-Print hal-03089881, HAL.
    5. Almeida, Caio & Garcia, René, 2012. "Assessing misspecified asset pricing models with empirical likelihood estimators," Journal of Econometrics, Elsevier, vol. 170(2), pages 519-537.
    6. Fletcher, Jonathan, 2014. "Benchmark models of expected returns in U.K. portfolio performance: An empirical investigation," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 30-46.
    7. Wickern, Tobias, 2011. "Confidence in prior knowledge: Calibration and impact on portfolio performance," Discussion Papers in Econometrics and Statistics 7/11, University of Cologne, Institute of Econometrics and Statistics.
    8. Yuan Liao & Anna Simoni, 2016. "Bayesian Inference for Partially Identified Convex Models: Is it Valid for Frequentist Inference?," Departmental Working Papers 201607, Rutgers University, Department of Economics.

  22. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2010. "Further results on the limiting distribution of GMM sample moment conditions," FRB Atlanta Working Paper 2010-11, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2013. "Chi-squared tests for evaluation and comparison of asset pricing models," Journal of Econometrics, Elsevier, vol. 173(1), pages 108-125.
    2. Khalaf, Lynda & Schaller, Huntley, 2016. "Identification and inference in two-pass asset pricing models," Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 165-177.
    3. Fletcher, Jonathan, 2014. "Benchmark models of expected returns in U.K. portfolio performance: An empirical investigation," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 30-46.

  23. GOSPODINOV, Nikolay & MAYNARD, Alex & PESAVENTO, Elena, 2009. "Sensitivity of Impulse Responses to Small Low Frequency Co-Movements : Reconciling the Evidence on the Effects of Technology Shocks," Cahiers de recherche 03-2009, Centre interuniversitaire de recherche en économie quantitative, CIREQ.

    Cited by:

    1. Michelle Alexopoulos & Jon Cohen, 2012. "The Effects of Computer Technologies on the Canadian Economy: Evidence from New Direct Measures," International Productivity Monitor, Centre for the Study of Living Standards, vol. 23, pages 17-32, Spring.
    2. Matthias Gubler & Matthias S. Hertweck, 2011. "Commodity Price Shocks and the Business Cycle: Structural Evidence for the U.S," Working Paper Series of the Department of Economics, University of Konstanz 2011-03, Department of Economics, University of Konstanz.
    3. Michelle Alexopoulos & Trevor Tombe, 2010. "Management Matters," Working Papers tecipa-406, University of Toronto, Department of Economics.
    4. Chevillon, Guillaume & Mavroeidis, Sophocles & Zhan, Zhaoguo, 2016. "Robust inference in structural VARs with long-run restrictions," ESSEC Working Papers WP1702, ESSEC Research Center, ESSEC Business School.
    5. Pierre Perron & Yohei Yamamoto, 2011. "Estimating and Testing Multiple Structural Changes in Linear Models Using Band Spectral Regressions," Boston University - Department of Economics - Working Papers Series WP2011-049, Boston University - Department of Economics.
    6. Lovcha, Yuliya & Pérez Laborda, Alejandro, 2016. "Frequency-Domain Estimation as an Alternative to Pre-Filtering External Cycles in Structural VAR Analysis," Working Papers 2072/290743, Universitat Rovira i Virgili, Department of Economics.
    7. Kilian, Lutz, 2011. "Structural Vector Autoregressions," CEPR Discussion Papers 8515, C.E.P.R. Discussion Papers.
    8. Nikolay Gospodinov & Damba Lkhagvasuren, 2014. "A Moment‐Matching Method For Approximating Vector Autoregressive Processes By Finite‐State Markov Chains," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 843-859, August.
    9. Michelle Alexopoulos & Jon Cohen, 2016. "The Medium Is the Measure: Technical Change and Employment, 1909—1949," The Review of Economics and Statistics, MIT Press, vol. 98(4), pages 792-810, October.
    10. Jinho Choi & Juan Carlos Escanciano & Junjie Guo, 2022. "Generalized band spectrum estimation with an application to the New Keynesian Phillips curve," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 1055-1078, August.
    11. Kurt Graden Lunsford, 2023. "Business Cycles and Low-Frequency Fluctuations in the US Unemployment Rate," Working Papers 23-19, Federal Reserve Bank of Cleveland.
    12. Chaudourne, Jeremy & Fève, Patrick & Guay, Alain, 2014. "Understanding the effect of technology shocks in SVARs with long-run restrictions," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 154-172.
    13. Nadav Ben Zeev, 2019. "Is There A Single Shock That Drives The Majority Of Business Cycle Fluctuations?," Working Papers 1906, Ben-Gurion University of the Negev, Department of Economics.
    14. Lieb, Lenard & Smeekes, Stephan, 2017. "Inference for Impulse Responses under Model Uncertainty," Research Memorandum 022, Maastricht University, Graduate School of Business and Economics (GSBE).
    15. Lovcha, Yuliya & Pérez Laborda, Àlex, 2016. "The Variance-Frequency Decomposition as an Instrument for VAR Identification: an Application to Technology Shocks," Working Papers 2072/261537, Universitat Rovira i Virgili, Department of Economics.
    16. Riccardo DiCecio & Michael T. Owyang, 2010. "Identifying technology shocks in the frequency domain," Working Papers 2010-025, Federal Reserve Bank of St. Louis.

  24. Nikolay Gospodinov & Ye Tao, 2009. "Bootstrap Unit Root Tests in Models with GARCH(1,1) Errors," Working Papers 09001, Concordia University, Department of Economics.

    Cited by:

    1. Nikolay Gospodinov & Ye Tao, 2011. "Bootstrap Unit Root Tests in Models with GARCH(1,1) Errors," Econometric Reviews, Taylor & Francis Journals, vol. 30(4), pages 379-405, August.
    2. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    3. Reboredo, Juan C., 2012. "Do food and oil prices co-move?," Energy Policy, Elsevier, vol. 49(C), pages 456-467.

  25. Nikolay Gospodinov & Masayuki Hirukawa, 2008. "Time Series Nonparametric Regression Using Asymmetric Kernels with an Application to Estimation of Scalar Diffusion Processes," CIRJE F-Series CIRJE-F-573, CIRJE, Faculty of Economics, University of Tokyo.

    Cited by:

    1. Taoufik Bouezmarni & Jeroen V.K. Rombouts, 2006. "Nonparametric Density Estimation for Positive Time Series," Cahiers de recherche 06-09, HEC Montréal, Institut d'économie appliquée.
    2. Hirukawa, Masayuki, 2010. "Nonparametric multiplicative bias correction for kernel-type density estimation on the unit interval," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 473-495, February.

  26. Stanislav Anatolyev & Nikolay Gospodinov, 2008. "Specification Testing in Models with Many Instruments," Working Papers w0124, New Economic School (NES).

    Cited by:

    1. Dennis Lim & Wenjie Wang & Yichong Zhang, 2022. "A Conditional Linear Combination Test with Many Weak Instruments," Papers 2207.11137, arXiv.org, revised Apr 2023.
    2. Dick, Christian D. & Schmeling, Maik & Schrimpf, Andreas, 2010. "Macro expectations, aggregate uncertainty, and expected term premia," ZEW Discussion Papers 10-064, ZEW - Leibniz Centre for European Economic Research.
    3. Norman R. Swanson & John C. Chao & Jerry A. Hausman & Whitney K. Newey & Tiemen Woutersen, 2011. "Testing Overidentifying Restrictions with Many Instruments and Heteroskedasticity," Departmental Working Papers 201118, Rutgers University, Department of Economics.
    4. Eric Gautier & Christiern Rose, 2022. "Fast, Robust Inference for Linear Instrumental Variables Models using Self-Normalized Moments," Papers 2211.02249, arXiv.org, revised Nov 2022.
    5. Hyunseok Jung & Xiaodong Liu, 2023. "Testing for Peer Effects without Specifying the Network Structure," Papers 2306.09806, arXiv.org, revised Mar 2024.
    6. Anatolyev, Stanislav & Sølvsten, Mikkel, 2023. "Testing many restrictions under heteroskedasticity," Journal of Econometrics, Elsevier, vol. 236(1).
    7. Crudu, Federico & Mellace, Giovanni & Sándor, Zsolt, 2021. "Inference In Instrumental Variable Models With Heteroskedasticity And Many Instruments," Econometric Theory, Cambridge University Press, vol. 37(2), pages 281-310, April.
    8. Wang, Wenjie, 2022. "Wild bootstrap test of overidentification with many instruments and heteroskedasticity," MPRA Paper 115168, University Library of Munich, Germany.
    9. Kohtaro Hitomi & Masamune Iwasawa & Yoshihiko Nishiyama, 2020. "Optimal Minimax Rates against Non-smooth Alternatives," KIER Working Papers 1051, Kyoto University, Institute of Economic Research.
    10. Zhenhong Huang & Chen Wang & Jianfeng Yao, 2023. "A specification test for the strength of instrumental variables," Papers 2302.14396, arXiv.org.
    11. Abutaliev, Albert & Anatolyev, Stanislav, 2013. "Asymptotic variance under many instruments: Numerical computations," Economics Letters, Elsevier, vol. 118(2), pages 272-274.
    12. Guy Tchuente, 2021. "A Note on the Topology of the First Stage of 2SLS with Many Instruments," Papers 2106.15003, arXiv.org.
    13. Johannes W. Ligtenberg, 2023. "Inference in IV models with clustered dependence, many instruments and weak identification," Papers 2306.08559, arXiv.org, revised Mar 2024.
    14. Kolesár, Michal, 2018. "Minimum distance approach to inference with many instruments," Journal of Econometrics, Elsevier, vol. 204(1), pages 86-100.
    15. Marine Carrasco & Guy Tchuente, 2016. "Regularization Based Anderson Rubin Tests for Many Instruments," Studies in Economics 1608, School of Economics, University of Kent.
    16. Lee, Yoonseok & Okui, Ryo, 2012. "Hahn–Hausman test as a specification test," Journal of Econometrics, Elsevier, vol. 167(1), pages 133-139.
    17. Michal Kolesár & Raj Chetty & John N. Friedman & Edward L. Glaeser & Guido W. Imbens, 2011. "Identification and Inference with Many Invalid Instruments," NBER Working Papers 17519, National Bureau of Economic Research, Inc.
    18. Max-Sebastian Dov`i, 2021. "Inference on the New Keynesian Phillips Curve with Very Many Instrumental Variables," Papers 2101.09543, arXiv.org, revised Mar 2021.
    19. Qingliang Fan & Zijian Guo & Ziwei Mei, 2022. "A Heteroskedasticity-Robust Overidentifying Restriction Test with High-Dimensional Covariates," Papers 2205.00171, arXiv.org, revised Mar 2023.
    20. Wang, Wenjie & Kaffo, Maximilien, 2016. "Bootstrap inference for instrumental variable models with many weak instruments," Journal of Econometrics, Elsevier, vol. 192(1), pages 231-268.
    21. Stanislav Anatolyev, 2012. "Instrumental variables estimation and inference in the presence of many exogenous regressors," Working Papers w0162, Center for Economic and Financial Research (CEFIR).
    22. Pierre Chaussé, 2011. "Generalized empirical likelihood for a continuum of moment conditions," Working Papers 1104, University of Waterloo, Department of Economics, revised Oct 2011.
    23. Wenjie Wang, 2012. "Bootstrapping Anderson-Rubin Statistic and J Statistic in Linear IV Models with Many Instruments," KIER Working Papers 810, Kyoto University, Institute of Economic Research.
    24. Kaffo, Maximilien & Wang, Wenjie, 2017. "On bootstrap validity for specification testing with many weak instruments," Economics Letters, Elsevier, vol. 157(C), pages 107-111.
    25. Díaz Antonia & Puch Luis A., 2019. "Investment, technological progress and energy efficiency," The B.E. Journal of Macroeconomics, De Gruyter, vol. 19(2), pages 1-28, June.
    26. Marine Carrasco & Mohamed Doukali, 2022. "Testing overidentifying restrictions with many instruments and heteroscedasticity using regularised jackknife IV [Specification testing in models with many instruments]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 71-97.
    27. Tom Boot & Johannes W. Ligtenberg, 2023. "Identification- and many instrument-robust inference via invariant moment conditions," Papers 2303.07822, arXiv.org, revised Sep 2023.
    28. Yoonseok Lee & Ryo Okui, 2009. "A Specification Test for Instrumental Variables Regression with Many Instruments," Cowles Foundation Discussion Papers 1741, Cowles Foundation for Research in Economics, Yale University.
    29. Anna Mikusheva & Liyang Sun, 2020. "Inference with Many Weak Instruments," Papers 2004.12445, arXiv.org, revised Oct 2021.
    30. Kohtaro Hitomi & Masamune Iwasawa & Yoshihiko Nishiyama, 2018. "Rate Optimal Specification Test When the Number of Instruments is Large," KIER Working Papers 986, Kyoto University, Institute of Economic Research.
    31. Travaglini, Guido, 2010. "Dynamic Econometric Testing of Climate Change and of its Causes," MPRA Paper 23600, University Library of Munich, Germany.
    32. Atsushi Inoue & Barbara Rossi, 2015. "Tests for the validity of portfolio or group choice in financial and panel regressions," Economics Working Papers 1523, Department of Economics and Business, Universitat Pompeu Fabra.
    33. Wang, Wenjie, 2020. "On Bootstrap Validity for the Test of Overidentifying Restrictions with Many Instruments and Heteroskedasticity," MPRA Paper 104858, University Library of Munich, Germany.
    34. Zhenhong Huang & Chen Wang & Jianfeng Yao, 2023. "Assessing the strength of many instruments with the first-stage F and Cragg-Donald statistics," Papers 2302.14423, arXiv.org.

  27. Nikolay Gospodinov & Masayuki Hirukawa, 2008. "Nonparametric Estimation of Scalar Diffusion Processes of Interest Rates Using Asymmetric Kernels," Working Papers 08011, Concordia University, Department of Economics, revised Dec 2008.

    Cited by:

    1. Debopam Bhattacharya & Shin Kanaya & Margaret Stevens, 2014. "Are University Admissions Academically Fair?," CREATES Research Papers 2014-06, Department of Economics and Business Economics, Aarhus University.

  28. Nikolay Gospodinov & Taisuke Otsu, 2008. "Local GMM Estimation of Time Series Models with Conditional Moment Restrictions," Working Papers 08010, Concordia University, Department of Economics.

    Cited by:

    1. Valerio Scalone, 2018. "Estimating Non-Linear DSGEs with the Approximate Bayesian Computation: an application to the Zero Lower Bound," Working papers 688, Banque de France.
    2. Patrick Gagliardini & Diego Ronchetti, 2020. "Comparing Asset Pricing Models by the Conditional Hansen-Jagannathan Distance," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 333-394.
    3. Raymond Kan & Cesare Robotti, 0. "Comment on: Pseudo-True SDFs in Conditional Asset Pricing Models," Journal of Financial Econometrics, Oxford University Press, vol. 18(4), pages 729-735.
    4. Chambers, Marcus J., 2013. "Jackknife estimation of stationary autoregressive models," Journal of Econometrics, Elsevier, vol. 172(1), pages 142-157.
    5. Crudu, Federico & Sándor, Zsolt, 2011. "On the finite-sample properties of conditional empirical likelihood estimators," MPRA Paper 34116, University Library of Munich, Germany.
    6. Zhentao Shi & Huanhuan Zheng, 2018. "Structural estimation of behavioral heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(5), pages 690-707, August.

  29. Stanislav Anatolyev & Nikolay Gospodinov, 2007. "Modeling Financial Return Dynamics by Decomposition," Working Papers w0095, New Economic School (NES).

    Cited by:

    1. Haibin Xie & Yuying Sun & Pengying Fan, 2023. "Return direction forecasting: a conditional autoregressive shape model with beta density," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-16, December.
    2. Thomakos, Dimitrios D. & Wang, Tao, 2010. "'Optimal' probabilistic and directional predictions of financial returns," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 102-119, January.
    3. Stanislav Anatolyev & Natalia Kryzhanovskaya, 2009. "Directional Prediction of Returns under Asymmetric Loss: Direct and Indirect Approaches," Working Papers w0136, Center for Economic and Financial Research (CEFIR).

  30. Nikolay Gospodinov, 2006. "A New Look at the Forward Premium Puzzle," Working Papers 08009, Concordia University, Department of Economics, revised Dec 2008.

    Cited by:

    1. Frankel, Jeffrey & Poonawala, Jumana, 2009. "The Forward Market in Emerging Currencies: Less Biased Than in Major Currencies," Working Paper Series rwp09-023, Harvard University, John F. Kennedy School of Government.
    2. Gourieroux, Christian & Jasiak, Joann, 2010. "Inference for Noisy Long Run Component Process," MPRA Paper 98987, University Library of Munich, Germany.
    3. Bai, Shuming & Mollick, Andre Varella, 2010. "Currency crisis and the forward discount bias: Evidence from emerging economies under breaks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(5), pages 556-574, December.
    4. Raj Aggarwal & Brian M. Lucey & Fergal A. O'Connor, 2014. "Rationality in Precious Metals Forward Markets: Evidence of Behavioural Deviations in the Gold Markets," The Institute for International Integration Studies Discussion Paper Series iiisdp462, IIIS.
    5. Yin-Wong Cheung & Wenhao Wang, 2020. "Uncovered Interest Rate Parity Redux: Non- Uniform Effects," GRU Working Paper Series GRU_2020_004, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    6. Aziz Chouikh & Abdelwahed Trabelsi, 2014. "Modeling Risk Premia in Forward Foreign Exchange Rates as Unobserved Components: The Model Identification Problem," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 5(3), pages 119-135, July.
    7. Carmen Gloria Silva, 2010. "Forward premium puzzle and term structure of interest rates: the case of New Zealand," Working Papers Central Bank of Chile 570, Central Bank of Chile.
    8. Jamali, Ibrahim & Yamani, Ehab, 2019. "Out-of-sample exchange rate predictability in emerging markets: Fundamentals versus technical analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 241-263.
    9. Shang, Hua, 2013. "Inference in asset pricing models with a low-variance factor," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 1046-1060.
    10. Shehadeh, Ali A. & Li, Youwei & Vigne, Samuel A. & Almaharmeh, Mohammad I. & Wang, Yizhi, 2021. "The existence and severity of the forward premium puzzle during tranquil and turbulent periods: Developed versus developing country currencies," International Review of Financial Analysis, Elsevier, vol. 78(C).
    11. Stanislav Anatolyev & Nikolay Gospodinov, 2012. "Asymptotics of near unit roots (in Russian)," Quantile, Quantile, issue 10, pages 57-71, December.
    12. Stanislav Anatolyev & Nikolay Gospodinov & Ibrahim Jamali & Xiaochun Liu, 2015. "Foreign exchange predictability during the financial crisis: implications for carry trade profitability," FRB Atlanta Working Paper 2015-6, Federal Reserve Bank of Atlanta.
    13. Matei Demetrescu & Christoph Roling & Anna Titova, 2021. "Reevaluating the prudence of economic forecasts in the EU: The role of instrument persistence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 151-161, January.
    14. Christian Gourieroux & Joann Jasiak, 2022. "Long Run Risk in Stationary Structural Vector Autoregressive Models," Papers 2202.09473, arXiv.org.
    15. Shehadeh, Ali & Li, Youwei & Moore, Michael, 2016. "The Forward Premium Bias, Carry Trade Return and the Risks of Volatility and Liquidity," MPRA Paper 71709, University Library of Munich, Germany.
    16. Phillips, Peter C.B. & Lee, Ji Hyung, 2013. "Predictive regression under various degrees of persistence and robust long-horizon regression," Journal of Econometrics, Elsevier, vol. 177(2), pages 250-264.
    17. Norman C. Miller, 2014. "Exchange Rate Economics," Books, Edward Elgar Publishing, number 14981.
    18. Anatolyev, Stanislav & Gospodinov, Nikolay & Jamali, Ibrahim & Liu, Xiaochun, 2017. "Foreign exchange predictability and the carry trade: A decomposition approach," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 199-211.

  31. Nikolay Gospodinov, 2001. "Asymptotic Confidence Intervals for Impulse Responses of Near-Integrated Processes: An Application to Purchasing Power Parity," Computing in Economics and Finance 2001 136, Society for Computational Economics.

    Cited by:

    1. Rossi, Barbara, 2005. "Confidence Intervals for Half-Life Deviations From Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 432-442, October.
    2. Sofiane H. Sekioua, 2004. "Real interest parity (RIP) over the 20th century: New evidence based on confidence intervals for the dominant root and half-lives of shocks," Money Macro and Finance (MMF) Research Group Conference 2004 91, Money Macro and Finance Research Group.

  32. Nikolay Gospodinov, 1999. "Median Unbiased Forecasts for Highly Persistent Autoregressive Processes," Computing in Economics and Finance 1999 533, Society for Computational Economics.

    Cited by:

    1. Mihaela Simionescu, 2014. "Forecast Intervals for Inflation Rate and Unemployment Rate in Romania," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 10(5), pages 39-51, October.
    2. Athanasia Gavala & Nikolay Gospodinov & Deming Jiang, 2006. "Forecasting volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(6), pages 381-400.
    3. Zi‐Yi Guo, 2021. "Out‐of‐sample performance of bias‐corrected estimators for diffusion processes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 243-268, March.
    4. Simionescu, Mihaela, 2014. "New Strategies to Improve the Accuracy of Predictions based on Monte Carlo and Bootstrap Simulations: An Application to Bulgarian and Romanian Inflation || Nuevas estrategias para mejorar la exactitud," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 18(1), pages 112-129, December.
    5. Mihaela Simionescu, 2015. "A New Technique based on Simulations for Improving the Inflation Rate Forecasts in Romania," Working Papers of Institute for Economic Forecasting 150206, Institute for Economic Forecasting.
    6. Kim, Hyeongwoo & Durmaz, Nazif, 2012. "Bias correction and out-of-sample forecast accuracy," International Journal of Forecasting, Elsevier, vol. 28(3), pages 575-586.
    7. Kruse, Robinson & Kaufmann, Hendrik & Wegener, Christoph, 2018. "Bias-corrected estimation for speculative bubbles in stock prices," Economic Modelling, Elsevier, vol. 73(C), pages 354-364.
    8. Müller, Ulrich K. & Wang, Yulong, 2019. "Nearly weighted risk minimal unbiased estimation," Journal of Econometrics, Elsevier, vol. 209(1), pages 18-34.
    9. Clements, Michael P. & Kim, Jae H., 2007. "Bootstrap prediction intervals for autoregressive time series," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3580-3594, April.
    10. João Henrique Gonçalves Mazzeu & Esther Ruiz & Helena Veiga, 2018. "Uncertainty And Density Forecasts Of Arma Models: Comparison Of Asymptotic, Bayesian, And Bootstrap Procedures," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 388-419, April.
    11. Simionescu, Mihaela, 2017. "Prediction intervals for inflation and unemployment rate in Romania. A Bayesian approach," GLO Discussion Paper Series 82, Global Labor Organization (GLO).
    12. Medel, Carlos & Pincheira, Pablo, 2015. "The Out-of-sample Performance of an Exact Median-Unbiased Estimator for the Near-Unity AR(1) Model," MPRA Paper 62552, University Library of Munich, Germany.
    13. Fallahi, Firouz & Voia, Marcel-Cristian, 2015. "Convergence and persistence in per capita energy use among OECD countries: Revisited using confidence intervals," Energy Economics, Elsevier, vol. 52(PA), pages 246-253.
    14. Fallahi, Firouz & Karimi, Mohammad & Voia, Marcel-Cristian, 2016. "Persistence in world energy consumption: Evidence from subsampling confidence intervals," Energy Economics, Elsevier, vol. 57(C), pages 175-183.
    15. Fallahi, Firouz, 2017. "Stochastic convergence in per capita energy use in world," Energy Economics, Elsevier, vol. 65(C), pages 228-239.
    16. Beutner, Eric & Heinemann, Alexander & Smeekes, Stephan, 2017. "A Justification of Conditional Confidence Intervals," Research Memorandum 023, Maastricht University, Graduate School of Business and Economics (GSBE).
    17. Stanislav Anatolyev & Nikolay Gospodinov, 2012. "Asymptotics of near unit roots (in Russian)," Quantile, Quantile, issue 10, pages 57-71, December.
    18. Gonçalves Mazzeu, Joao Henrique & Ruiz Ortega, Esther & Veiga, Helena, 2015. "Model uncertainty and the forecast accuracy of ARMA models: A survey," DES - Working Papers. Statistics and Econometrics. WS ws1508, Universidad Carlos III de Madrid. Departamento de Estadística.

Articles

  1. Richard K. Crump & Nikolay Gospodinov, 2022. "On the Factor Structure of Bond Returns," Econometrica, Econometric Society, vol. 90(1), pages 295-314, January.

    Cited by:

    1. Moench, Emanuel & Soofi-Siavash, Soroosh, 2022. "What moves treasury yields?," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1016-1043.
    2. Pablo Guerrón-Quintana & Alexey Khazanov & Molin Zhong, 2023. "Financial and Macroeconomic Data Through the Lens of a Nonlinear Dynamic Factor Model," Finance and Economics Discussion Series 2023-027, Board of Governors of the Federal Reserve System (U.S.).
    3. Dennis Schroers, 2024. "Robust Functional Data Analysis for Stochastic Evolution Equations in Infinite Dimensions," Papers 2401.16286, arXiv.org.

  2. Gospodinov, Nikolay & Maasoumi, Esfandiar, 2021. "Generalized aggregation of misspecified models: With an application to asset pricing," Journal of Econometrics, Elsevier, vol. 222(1), pages 451-467.

    Cited by:

    1. Richard K. Crump & Nikolay Gospodinov & Hunter Wieman, 2023. "Sparse Trend Estimation," Staff Reports 1049, Federal Reserve Bank of New York.

  3. Gospodinov, Nikolay & Robotti, Cesare, 2021. "Common pricing across asset classes: Empirical evidence revisited," Journal of Financial Economics, Elsevier, vol. 140(1), pages 292-324.

    Cited by:

    1. Lin, Qi, 2022. "Understanding idiosyncratic momentum in the Chinese stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    2. Svetlana Bryzgalova & Jiantao Huang & Christian Julliard, 2023. "Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models," Journal of Finance, American Finance Association, vol. 78(1), pages 487-557, February.
    3. Lee, Kiryoung, 2022. "Which uncertainty measures matter for the cross-section of corporate bond returns? Evidence from the U.S. during 1973–2020," Finance Research Letters, Elsevier, vol. 48(C).
    4. Dickerson, Alexander & Mueller, Philippe & Robotti, Cesare, 2023. "Priced risk in corporate bonds," Journal of Financial Economics, Elsevier, vol. 150(2).
    5. Jamali, Ibrahim & Yamani, Ehab & Smallwood, Aaron D., 2023. "An investment-based explanation of currency excess returns," Journal of International Money and Finance, Elsevier, vol. 133(C).
    6. Rob Kim Marjerison & Chungil Chae & Shitong Li, 2021. "Investor Activity in Chinese Financial Institutions: A Precursor to Economic Sustainability," Sustainability, MDPI, vol. 13(21), pages 1-17, November.
    7. Lioui, Abraham & Tarelli, Andrea, 2022. "Chasing the ESG factor," Journal of Banking & Finance, Elsevier, vol. 139(C).

  4. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2019. "Too good to be true? Fallacies in evaluating risk factor models," Journal of Financial Economics, Elsevier, vol. 132(2), pages 451-471.
    See citations under working paper version above.
  5. Stanislav Anatolyev & Nikolay Gospodinov, 2019. "Multivariate Return Decomposition: Theory and Implications," Econometric Reviews, Taylor & Francis Journals, vol. 38(5), pages 487-508, May.
    See citations under working paper version above.
  6. Nikolay Gospodinov & Ibrahim Jamali, 2018. "Monetary policy uncertainty, positions of traders and changes in commodity futures prices," European Financial Management, European Financial Management Association, vol. 24(2), pages 239-260, March.

    Cited by:

    1. Yao, Wei & Alexiou, Constantinos, 2022. "Exploring the transmission mechanism of speculative and inventory arbitrage activity to commodity price volatility. Novel evidence for the US economy," International Review of Financial Analysis, Elsevier, vol. 80(C).
    2. Abid, Ilyes & Goutte, Stéphane & Guesmi, Khaled & Jamali, Ibrahim, 2019. "Transmission of shocks and contagion from U.S. to MENA equity markets: The role of oil and gas markets," Energy Policy, Elsevier, vol. 134(C).
    3. Zhuo Huang & Fang Liang & Chen Tong, 2021. "The predictive power of macroeconomic uncertainty for commodity futures volatility," International Review of Finance, International Review of Finance Ltd., vol. 21(3), pages 989-1012, September.
    4. Hardik A. Marfatia & Rangan Gupta & Stephen M. Miller, 2020. "125 Years of Time-Varying Effects of Fiscal Policy on Financial Markets," Working papers 2020-12, University of Connecticut, Department of Economics.
    5. Lee, Kiryoung, 2022. "Which uncertainty measures matter for the cross-section of corporate bond returns? Evidence from the U.S. during 1973–2020," Finance Research Letters, Elsevier, vol. 48(C).
    6. Marfatia, Hardik A. & Gupta, Rangan & Cakan, Esin, 2021. "Dynamic impact of the U.S. monetary policy on oil market returns and volatility," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 159-169.
    7. Vasilios Plakandaras & Rangan Gupta & Mehmet Balcilar & Qiang Ji, 2021. "Evolving United States Stock Market Volatility: The Role of Conventional and Unconventional Monetary Policies," Working Papers 202113, University of Pretoria, Department of Economics.
    8. Aslam, Faheem & Zil-e-huma, & Bibi, Rashida & Ferreira, Paulo, 2022. "Cross-correlations between economic policy uncertainty and precious and industrial metals: A multifractal cross-correlation analysis," Resources Policy, Elsevier, vol. 75(C).
    9. Christian Koziol & Tilo Treuter, 2019. "How do speculators in agricultural commodity markets impact production decisions and commodity prices? A theoretical analysis," European Financial Management, European Financial Management Association, vol. 25(3), pages 718-743, June.
    10. Tarek Chebbi, 2021. "The response of precious metal futures markets to unconventional monetary surprises in the presence of uncertainty," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1897-1916, April.
    11. Shimeng Shi, 2022. "Bitcoin futures risk premia," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2190-2217, December.
    12. Shixuan Wang & Rangan Gupta & Matteo Bonato & Oguzhan Cepni, 2022. "The Effects of Conventional and Unconventional Monetary Policy Shocks on US REITs Moments: Evidence from VARs with Functional Shocks," Working Papers 202219, University of Pretoria, Department of Economics.
    13. Sun Young Kim & Kyung Yoon Kwon, 2021. "Does economic uncertainty matter in international commodity futures markets?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 849-869, January.
    14. Jahantigh , Forough & Rahmi Ghasemabadi , Mohammad & Jalali , Omolbanin, 2018. "The Impact of Monetary Policy Shock on the Price of Storable Goods: A Case Study of Food," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 13(4), pages 471-490, October.
    15. Marfatia, Hardik A. & Gupta, Rangan & Miller, Stephen, 2020. "125 ​Years of time-varying effects of fiscal policy on financial markets," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 303-320.
    16. Bin Xu & Boqiang Lin, 2021. "Large fluctuations of China's commodity prices: Main sources and heterogeneous effects," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2074-2089, April.

  7. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2018. "Asymptotic variance approximations for invariant estimators in uncertain asset-pricing models," Econometric Reviews, Taylor & Francis Journals, vol. 37(7), pages 695-718, August.
    See citations under working paper version above.
  8. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2017. "Spurious Inference in Reduced‐Rank Asset‐Pricing Models," Econometrica, Econometric Society, vol. 85, pages 1613-1628, September.

    Cited by:

    1. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2017. "Too Good to Be True? Fallacies in Evaluating Risk Factor Models," FRB Atlanta Working Paper 2017-9, Federal Reserve Bank of Atlanta.
    2. Zhang, Xiang & Liu, Yangyi & Wu, Kun & Maillet, Bertrand, 2021. "Tradable or nontradable factors—what does the Hansen–Jagannathan distance tell us?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 853-879.
    3. Frank Windmeijer, 2018. "Testing Over- and Underidentification in Linear Models, with Applications to Dynamic Panel Data and Asset-Pricing Models," Bristol Economics Discussion Papers 18/696, School of Economics, University of Bristol, UK.
    4. Stanislav Anatolyev & Anna Mikusheva, 2018. "Factor models with many assets: strong factors, weak factors, and the two-pass procedure," Papers 1807.04094, arXiv.org, revised Apr 2019.
    5. Sentana, Enrique & Manresa, Elena & Penaranda, Francisco, 2017. "Empirical Evaluation of Overspecified Asset Pricing Models," CEPR Discussion Papers 12085, C.E.P.R. Discussion Papers.
    6. Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Ernst Schaumburg, 2020. "Characteristic-Sorted Portfolios: Estimation and Inference," The Review of Economics and Statistics, MIT Press, vol. 102(3), pages 531-551, July.
    7. Lingwei Kong, 2023. "Weak (Proxy) Factors Robust Hansen-Jagannathan Distance For Linear Asset Pricing Models," Papers 2307.14499, arXiv.org.
    8. Borup, Daniel, 2019. "Asset pricing model uncertainty," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 166-189.
    9. Gospodinov, Nikolay & Robotti, Cesare, 2021. "Common pricing across asset classes: Empirical evidence revisited," Journal of Financial Economics, Elsevier, vol. 140(1), pages 292-324.
    10. Yinchu Zhu, 2019. "How well can we learn large factor models without assuming strong factors?," Papers 1910.10382, arXiv.org, revised Nov 2019.
    11. Lioui, Abraham & Tarelli, Andrea, 2020. "Factor Investing for the Long Run," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    12. Sun, Yang & Zhang, Xuan & Zhang, Zhekai, 2022. "The reduced-rank beta in linear stochastic discount factor models," International Review of Financial Analysis, Elsevier, vol. 84(C).
    13. Bretscher, Lorenzo & Hsu, Alex & Tamoni, Andrea, 2020. "Fiscal policy driven bond risk premia," Journal of Financial Economics, Elsevier, vol. 138(1), pages 53-73.
    14. Gospodinov, Nikolay & Maasoumi, Esfandiar, 2021. "Generalized aggregation of misspecified models: With an application to asset pricing," Journal of Econometrics, Elsevier, vol. 222(1), pages 451-467.

  9. Gospodinov, Nikolay & Komunjer, Ivana & Ng, Serena, 2017. "Simulated minimum distance estimation of dynamic models with errors-in-variables," Journal of Econometrics, Elsevier, vol. 200(2), pages 181-193.

    Cited by:

    1. Yong Bao & Xiaotian Liu & Lihong Yang, 2020. "Indirect Inference Estimation of Spatial Autoregressions," Econometrics, MDPI, vol. 8(3), pages 1-26, September.
    2. Sönksen, Jantje & Grammig, Joachim, 2021. "Empirical asset pricing with multi-period disaster risk: A simulation-based approach," Journal of Econometrics, Elsevier, vol. 222(1), pages 805-832.
    3. Jean-Jacques Forneron, 2019. "A Sieve-SMM Estimator for Dynamic Models," Papers 1902.01456, arXiv.org, revised Jan 2023.
    4. Shuowen Chen, 2022. "Indirect Inference for Nonlinear Panel Models with Fixed Effects," Papers 2203.10683, arXiv.org, revised Apr 2022.
    5. Bao, Yong & Yu, Xuewen, 2023. "Indirect inference estimation of dynamic panel data models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1027-1053.
    6. Czellar, Veronika & Frazier, David T. & Renault, Eric, 2022. "Approximate maximum likelihood for complex structural models," Journal of Econometrics, Elsevier, vol. 231(2), pages 432-456.
    7. Veronika Czellar & David T. Frazier & Eric Renault, 2020. "Approximate Maximum Likelihood for Complex Structural Models," Papers 2006.10245, arXiv.org.
    8. Czellar, Veronika & Frazier, David T. & Renault, Eric, 2021. "Approximate Maximum Likelihood for Complex Structural Models," The Warwick Economics Research Paper Series (TWERPS) 1337, University of Warwick, Department of Economics.
    9. Yong Bao, 2021. "Indirect Inference Estimation of a First-Order Dynamic Panel Data Model," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 79-98, December.

  10. Anatolyev, Stanislav & Gospodinov, Nikolay & Jamali, Ibrahim & Liu, Xiaochun, 2017. "Foreign exchange predictability and the carry trade: A decomposition approach," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 199-211.

    Cited by:

    1. Stanislav Anatolyev, 2021. "Directional news impact curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 94-107, January.
    2. Maake, Tebogo & Bonga-Bonga, Lumengo, 2019. "The relationship between carry trade and asset markets in South Africa," MPRA Paper 96667, University Library of Munich, Germany.
    3. Jamali, Ibrahim & Yamani, Ehab, 2019. "Out-of-sample exchange rate predictability in emerging markets: Fundamentals versus technical analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 241-263.
    4. Qian Zhang & Kuo-Jui Wu & Ming-Lang Tseng, 2019. "Exploring Carry Trade and Exchange Rate toward Sustainable Financial Resources: An application of the Artificial Intelligence UKF Method," Sustainability, MDPI, vol. 11(12), pages 1-26, June.
    5. Fu, Hsuan & Luger, Richard, 2022. "Multiple testing of the forward rate unbiasedness hypothesis across currencies," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 232-245.

  11. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2016. "On the properties of the constrained Hansen–Jagannathan distance," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 121-150.

    Cited by:

    1. Caio Almeida & René Garcia, 2017. "Economic Implications of Nonlinear Pricing Kernels," Management Science, INFORMS, vol. 63(10), pages 3361-3380, October.
    2. Raymond Kan & Cesare Robotti, 0. "Comment on: Pseudo-True SDFs in Conditional Asset Pricing Models," Journal of Financial Econometrics, Oxford University Press, vol. 18(4), pages 729-735.
    3. Caio Almeida & Kym Ardison & René Garcia & Jose Vicente, 2017. "Nonparametric Tail Risk, Stock Returns, and the Macroeconomy," Journal of Financial Econometrics, Oxford University Press, vol. 15(3), pages 333-376.
    4. Gospodinov, Nikolay & Maasoumi, Esfandiar, 2021. "Generalized aggregation of misspecified models: With an application to asset pricing," Journal of Econometrics, Elsevier, vol. 222(1), pages 451-467.

  12. Nikolay Gospodinov & Serena Ng, 2015. "Minimum Distance Estimation of Possibly Noninvertible Moving Average Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 403-417, July.
    See citations under working paper version above.
  13. Gospodinov, Nikolay & Jamali, Ibrahim, 2015. "The response of stock market volatility to futures-based measures of monetary policy shocks," International Review of Economics & Finance, Elsevier, vol. 37(C), pages 42-54.
    See citations under working paper version above.
  14. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2014. "Misspecification-Robust Inference in Linear Asset-Pricing Models with Irrelevant Risk Factors," The Review of Financial Studies, Society for Financial Studies, vol. 27(7), pages 2139-2170.
    See citations under working paper version above.
  15. Nikolay Gospodinov & Damba Lkhagvasuren, 2014. "A Moment‐Matching Method For Approximating Vector Autoregressive Processes By Finite‐State Markov Chains," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 843-859, August.
    See citations under working paper version above.
  16. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2013. "Chi-squared tests for evaluation and comparison of asset pricing models," Journal of Econometrics, Elsevier, vol. 173(1), pages 108-125.
    See citations under working paper version above.
  17. Nikolay Gospodinov & Serena Ng, 2013. "Commodity Prices, Convenience Yields, and Inflation," The Review of Economics and Statistics, MIT Press, vol. 95(1), pages 206-219, March.

    Cited by:

    1. O'Rourke, Kevin & Ellison, Martin & Lee, Sang Seok, 2020. "The Ends of 27 Big Depressions," CEPR Discussion Papers 15061, C.E.P.R. Discussion Papers.
    2. Nikolay Gospodinov & Ibrahim Jamali, 2013. "Monetary policy surprises, positions of traders, and changes in commodity futures prices," FRB Atlanta Working Paper 2013-12, Federal Reserve Bank of Atlanta.
    3. Wang, Yudong & Liu, Li & Wu, Chongfeng, 2020. "Forecasting commodity prices out-of-sample: Can technical indicators help?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 666-683.
    4. Bakas, Dimitrios & Triantafyllou, Athanasios, 2018. "The impact of uncertainty shocks on the volatility of commodity prices," Journal of International Money and Finance, Elsevier, vol. 87(C), pages 96-111.
    5. Kyungbo Park & Hangook Kim & Jeonghwa Cha, 2023. "An Exploratory Study on the Development of a Crisis Index: Focusing on South Korea’s Petroleum Industry," Energies, MDPI, vol. 16(14), pages 1-24, July.
    6. Sévi, Benoît, 2015. "Explaining the convenience yield in the WTI crude oil market using realized volatility and jumps," Economic Modelling, Elsevier, vol. 44(C), pages 243-251.
    7. Baruník, Jozef & Bevilacqua, Mattia & Tunaru, Radu, 2022. "Asymmetric network connectedness of fears," LSE Research Online Documents on Economics 108199, London School of Economics and Political Science, LSE Library.
    8. West, Kenneth D. & Wong, Ka-Fu, 2014. "A factor model for co-movements of commodity prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 289-309.
    9. Abid, Ilyes & Goutte, Stéphane & Guesmi, Khaled & Jamali, Ibrahim, 2019. "Transmission of shocks and contagion from U.S. to MENA equity markets: The role of oil and gas markets," Energy Policy, Elsevier, vol. 134(C).
    10. Mehmet Balcilar & Nico Katzke & Rangan Gupta, 2015. "Do Precious Metal Prices Help in Forecasting South African Inflation?," Working Papers 03/2015, Stellenbosch University, Department of Economics.
    11. Yu-chin Chen & Stephen J. Turnovsky & Eric Zivot, 2011. "Forecasting Inflation using Commodity Price Aggregates," Working Papers UWEC-2011-14, University of Washington, Department of Economics.
    12. Shiu-Sheng Chen, 2016. "Commodity prices and related equity prices," Canadian Journal of Economics, Canadian Economics Association, vol. 49(3), pages 949-967, August.
    13. Wen, Chufu & Zhu, Haoyang & Dai, Zhifeng, 2023. "Forecasting commodity prices returns: The role of partial least squares approach," Energy Economics, Elsevier, vol. 125(C).
    14. Bonnier, Jean-Baptiste, 2021. "Speculation and informational efficiency in commodity futures markets," Journal of International Money and Finance, Elsevier, vol. 117(C).
    15. Simona Delle Chiaie & Laurent Ferrara & Domenico Giannone, 2022. "Common factors of commodity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 461-476, April.
    16. Yang Liu & Liyan Han & Libo Yin, 2018. "Does news uncertainty matter for commodity futures markets? Heterogeneity in energy and non‐energy sectors," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(10), pages 1246-1261, October.
    17. Julien Chevallier & Benoît Sévi, 2013. "A Fear Index to Predict Oil Futures Returns," Working Papers 2013.62, Fondazione Eni Enrico Mattei.
    18. Ron Alquist & Gregory Bauer & Antonio Diez de los Rios, 2014. "What Does the Convenience Yield Curve Tell Us about the Crude Oil Market?," Staff Working Papers 14-42, Bank of Canada.
    19. Karol Szafranek, 2015. "Financialisation of the commodity markets. Conclusions from the VARX DCC GARCH," NBP Working Papers 213, Narodowy Bank Polski.
    20. Ron Alquist & Olivier Coibion, 2014. "Commodity Price Co-Movement and Global Economic Activity," Staff Working Papers 14-32, Bank of Canada.
    21. Fernandez, Viviana, 2020. "The predictive power of convenience yields," Resources Policy, Elsevier, vol. 65(C).
    22. GONÇALVES, Sílvia & PERRON, Benoit, 2018. "Bootstrapping factor models with cross sectional dependence," Cahiers de recherche 2018-07, Universite de Montreal, Departement de sciences economiques.
    23. Pierre L. Siklos, 2018. "The Macroeconomic Response to Real and Financial Factors, Commodity Prices, and Monetary Policy: International Evidence," Working Papers wp35, South East Asian Central Banks (SEACEN) Research and Training Centre.
    24. Massimo Guidolin & Manuela Pedio, 2020. "Distilling Large Information Sets to Forecast Commodity Returns: Automatic Variable Selection or HiddenMarkov Models?," BAFFI CAREFIN Working Papers 20140, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    25. Zhang, Yongmin & Ding, Shusheng & Scheffel, Eric M., 2019. "A key determinant of commodity price Co-movement: The role of daily market liquidity," Economic Modelling, Elsevier, vol. 81(C), pages 170-180.
    26. Byrne, Joseph P. & Ibrahim, Boulis Maher & Sakemoto, Ryuta, 2019. "Carry trades and commodity risk factors," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 121-129.
    27. Yin, Libo & Han, Liyan, 2015. "Co-movements in commodity prices: Global, sectoral and commodity-specific factors," Economics Letters, Elsevier, vol. 126(C), pages 96-100.
    28. Silvia Gonçalves & Benoit Perron, 2012. "Bootstrapping factor-augmented regression models," CIRANO Working Papers 2012s-12, CIRANO.
    29. Thomas Conlon & Brian M. Lucey & Gazi Salah Uddin, 2018. "Is gold a hedge against inflation? A wavelet time-scale perspective," Review of Quantitative Finance and Accounting, Springer, vol. 51(2), pages 317-345, August.
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    35. Jamali, Ibrahim & Yamani, Ehab, 2019. "Out-of-sample exchange rate predictability in emerging markets: Fundamentals versus technical analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 241-263.
    36. Derek Bunn & Julien Chevallier & Yannick Le Pen & Benoît Sévi, 2017. "Fundamental and Financial Influences on the Co-movement of Oil and Gas prices," Post-Print hal-01619890, HAL.
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    40. Apergis, Nicholas & Chatziantoniou, Ioannis & Cooray, Arusha, 2020. "Monetary policy and commodity markets: Unconventional versus conventional impact and the role of economic uncertainty," International Review of Financial Analysis, Elsevier, vol. 71(C).
    41. Massimo Guidolin & Manuela Pedio, 2022. "Switching Coefficients or Automatic Variable Selection: An Application in Forecasting Commodity Returns," Forecasting, MDPI, vol. 4(1), pages 1-32, February.
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    43. Dagher, Leila & Jamali, Ibrahim & badra, nasser, 2018. "The Predictive Power of Oil and Commodity Prices for Equity Markets," MPRA Paper 116055, University Library of Munich, Germany.
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    46. Yannick Le Pen & Benoît Sévi, 2013. "Futures Trading and the Excess Comovement of Commodity Prices," AMSE Working Papers 1301, Aix-Marseille School of Economics, France, revised Jan 2013.
    47. Dbouk, Wassim & Jamali, Ibrahim, 2018. "Predicting daily oil prices: Linear and non-linear models," Research in International Business and Finance, Elsevier, vol. 46(C), pages 149-165.
    48. Gutierrez, Luciano, 2011. "Looking for Rational Bubbles in Agricultural Commodity Markets," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 120377, European Association of Agricultural Economists.
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    50. Shang, Hua & Yuan, Ping & Huang, Lin, 2016. "Macroeconomic factors and the cross-section of commodity futures returns," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 316-332.
    51. Martin Feldkircher & Pierre L. Siklos, 2018. "Global inflation dynamics and inflation expectations," CAMA Working Papers 2018-60, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    52. Mr. Ron Alquist & Mr. Olivier Coibion, 2013. "The Comovement in Commodity Prices: Sources and Implications," IMF Working Papers 2013/140, International Monetary Fund.
    53. Kucher, Oleg & Kurov, Alexander, 2014. "Business cycle, storage, and energy prices," Review of Financial Economics, Elsevier, vol. 23(4), pages 217-226.
    54. Jed Armstrong & Günes Kamber & Özer Karagedikli, 2016. "Developing a labour utilisation composite index for New Zealand," Reserve Bank of New Zealand Analytical Notes series AN2016/04, Reserve Bank of New Zealand.
    55. Daskalaki, Charoula & Kostakis, Alexandros & Skiadopoulos, George, 2014. "Are there common factors in individual commodity futures returns?," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 346-363.
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    59. Takuji Fueki & Jouchi Nakajima & Shinsuke Ohyama & Yoichiro Tamanyu, 2021. "Identifying oil price shocks and their consequences: The role of expectations in the crude oil market," International Finance, Wiley Blackwell, vol. 24(1), pages 53-76, April.
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  18. Gospodinov, Nikolay & Hirukawa, Masayuki, 2012. "Nonparametric estimation of scalar diffusion models of interest rates using asymmetric kernels," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 595-609.

    Cited by:

    1. Ouimet, Frédéric & Tolosana-Delgado, Raimon, 2022. "Asymptotic properties of Dirichlet kernel density estimators," Journal of Multivariate Analysis, Elsevier, vol. 187(C).
    2. Debopam Bhattacharya & Shin Kanaya & Margaret Stevens, 2014. "Are University Admissions Academically Fair?," CREATES Research Papers 2014-06, Department of Economics and Business Economics, Aarhus University.
    3. Masayuki Hirukawa & Mari Sakudo, 2016. "Testing Symmetry of Unknown Densities via Smoothing with the Generalized Gamma Kernels," Econometrics, MDPI, vol. 4(2), pages 1-27, June.
    4. Masayuki Hirukawa & Mari Sakudo, 2015. "Family of the generalised gamma kernels: a generator of asymmetric kernels for nonnegative data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 27(1), pages 41-63, March.
    5. Funke, Benedikt & Hirukawa, Masayuki, 2019. "Nonparametric estimation and testing on discontinuity of positive supported densities: a kernel truncation approach," Econometrics and Statistics, Elsevier, vol. 9(C), pages 156-170.
    6. Funke, Benedikt & Hirukawa, Masayuki, 2021. "Bias correction for local linear regression estimation using asymmetric kernels via the skewing method," Econometrics and Statistics, Elsevier, vol. 20(C), pages 109-130.
    7. Ye, Xu-Guo & Lin, Jin-Guan & Zhao, Yan-Yong & Hao, Hong-Xia, 2015. "Two-step estimation of the volatility functions in diffusion models with empirical applications," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 135-159.

  19. Gospodinov, Nikolay & Jamali, Ibrahim, 2012. "The effects of Federal funds rate surprises on S&P 500 volatility and volatility risk premium," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 497-510.

    Cited by:

    1. Gagan Deep Sharma & Mandeep Mahendru & Mrinalini Srivastava, 2019. "Can Central Banking Policies Make a Difference in Financial Market Performance in Emerging Economies? The Case of India," Economies, MDPI, vol. 7(2), pages 1-19, May.
    2. Fady Barsoum, 2013. "The Effects of Monetary Policy Shocks on a Panel of Stock Market Volatilities: A Factor-Augmented Bayesian VAR Approach," Working Paper Series of the Department of Economics, University of Konstanz 2013-15, Department of Economics, University of Konstanz.
    3. Nkwoma John Inekwe, 2016. "Financial uncertainty, risk aversion and monetary policy," Empirical Economics, Springer, vol. 51(3), pages 939-961, November.
    4. López, Raquel, 2015. "Do stylized facts of equity-based volatility indices apply to fixed-income volatility indices? Evidence from the US Treasury market," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 292-303.
    5. Caporale, Guglielmo Maria & Kyriacou, Kyriacos & Spagnolo, Nicola, 2023. "Aggregate insider trading and stock market volatility in the UK," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 89(C).
    6. Albulena Basha & Wendong Zhang & Chad Hart, 2021. "The impacts of interest rate changes on US Midwest farmland values," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 81(5), pages 746-766, February.
    7. Matthew W. Clance & Riza Demirer & Rangan Gupta & Clement Kweku Kyei, 2020. "Predicting Firm-Level Volatility in the United States: The Role of Monetary Policy Uncertainty," Working Papers 202007, University of Pretoria, Department of Economics.
    8. Georgios Chortareas & Menelaos Karanasos & Emmanouil Noikokyris, 2019. "Quantitative Easing And The Uk Stock Market: Does The Bank Of England Information Dissemination Strategy Matter?," Economic Inquiry, Western Economic Association International, vol. 57(1), pages 569-583, January.
    9. Vasilios Plakandaras & Rangan Gupta & Mehmet Balcilar & Qiang Ji, 2021. "Evolving United States Stock Market Volatility: The Role of Conventional and Unconventional Monetary Policies," Working Papers 202113, University of Pretoria, Department of Economics.
    10. Thampanya, Natthinee & Wu, Junjie & Nasir, Muhammad Ali & Liu, Jia, 2020. "Fundamental and behavioural determinants of stock return volatility in ASEAN-5 countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
    11. Gu, Chen & Kurov, Alexander & Stan, Raluca, 2023. "Monetary policy and uncertainty resolution in commodity markets," Finance Research Letters, Elsevier, vol. 55(PA).
    12. Dimitrios I. Vortelinos, 2015. "The Effect of Macro News on Volatility and Jumps," Annals of Economics and Finance, Society for AEF, vol. 16(2), pages 425-447, November.
    13. Onan, Mustafa & Salih, Aslihan & Yasar, Burze, 2014. "Impact of macroeconomic announcements on implied volatility slope of SPX options and VIX," Finance Research Letters, Elsevier, vol. 11(4), pages 454-462.
    14. Vortelinos, Dimitrios I. & Koulakiotis, Athanasios & Tsagkanos, Athanasios, 2017. "Intraday analysis of macroeconomic news surprises and asymmetries in mini-futures markets," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 150-168.
    15. Vortelinos, Dimitrios I., 2015. "Out-of-sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini-futures markets," Review of Financial Economics, Elsevier, vol. 27(C), pages 58-67.
    16. Dimitrios I. Vortelinos, 2015. "Out‐of‐sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini‐futures markets," Review of Financial Economics, John Wiley & Sons, vol. 27(1), pages 58-67, November.
    17. Reinhold Heinlein & Gabriele M. Lepori, 2022. "Do financial markets respond to macroeconomic surprises? Evidence from the UK," Empirical Economics, Springer, vol. 62(5), pages 2329-2371, May.
    18. Roy Trivedi, Smita, 2018. "Exchange rate volatility: Trader's beliefs and the role of news," MPRA Paper 89330, University Library of Munich, Germany.
    19. Shixuan Wang & Rangan Gupta & Matteo Bonato & Oguzhan Cepni, 2022. "The Effects of Conventional and Unconventional Monetary Policy Shocks on US REITs Moments: Evidence from VARs with Functional Shocks," Working Papers 202219, University of Pretoria, Department of Economics.
    20. Nkwoma, Inekwe John, 2017. "Futures-Based Measures Of Monetary Policy And Jump Risk," Macroeconomic Dynamics, Cambridge University Press, vol. 21(2), pages 384-405, March.
    21. Fernandez-Perez, Adrian & Frijns, Bart & Tourani-Rad, Alireza, 2017. "When no news is good news – The decrease in investor fear after the FOMC announcement," Journal of Empirical Finance, Elsevier, vol. 41(C), pages 187-199.
    22. Tang, Yong & Luo, Yong & Xiong, Jie & Zhao, Fei & Zhang, Yi-Cheng, 2013. "Impact of monetary policy changes on the Chinese monetary and stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4435-4449.
    23. Gu, Chen & Chen, Denghui & Stan, Raluca, 2022. "Resolution of financial market uncertainty around the release of unemployment rate announcements," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 586-596.

  20. Nikolay Gospodinov & Raymond Kan & Cesare Robotti, 2012. "Further Results on the Limiting Distribution of GMM Sample Moment Conditions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(4), pages 494-504, May.
    See citations under working paper version above.
  21. Gospodinov, Nikolay & Otsu, Taisuke, 2012. "Local GMM estimation of time series models with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 170(2), pages 476-490.
    See citations under working paper version above.
  22. Nikolay Gospodinov & Ibrahim Jamali, 2011. "Risk premiums and predictive ability of BAX futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(6), pages 534-561, June.

    Cited by:

    1. Abid, Ilyes & Goutte, Stéphane & Guesmi, Khaled & Jamali, Ibrahim, 2019. "Transmission of shocks and contagion from U.S. to MENA equity markets: The role of oil and gas markets," Energy Policy, Elsevier, vol. 134(C).
    2. Bou-Hamad, Imad & Jamali, Ibrahim, 2020. "Forecasting financial time-series using data mining models: A simulation study," Research in International Business and Finance, Elsevier, vol. 51(C).
    3. Jamali, Ibrahim & Yamani, Ehab, 2019. "Out-of-sample exchange rate predictability in emerging markets: Fundamentals versus technical analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 241-263.
    4. Floros, Christos & Kizys, Renatas & Pierdzioch, Christian, 2013. "Financial crises, the decoupling–recoupling hypothesis, and the risk premium on the Greek stock index futures market," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 166-173.
    5. Dbouk, Wassim & Jamali, Ibrahim, 2018. "Predicting daily oil prices: Linear and non-linear models," Research in International Business and Finance, Elsevier, vol. 46(C), pages 149-165.
    6. Shang, Hua & Yuan, Ping & Huang, Lin, 2016. "Macroeconomic factors and the cross-section of commodity futures returns," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 316-332.

  23. Gospodinov, Nikolay & Maynard, Alex & Pesavento, Elena, 2011. "Sensitivity of Impulse Responses to Small Low-Frequency Comovements: Reconciling the Evidence on the Effects of Technology Shocks," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(4), pages 455-467.
    See citations under working paper version above.
  24. Anatolyev, Stanislav & Gospodinov, Nikolay, 2011. "Specification Testing In Models With Many Instruments," Econometric Theory, Cambridge University Press, vol. 27(2), pages 427-441, April.
    See citations under working paper version above.
  25. Nikolay Gospodinov & Ye Tao, 2011. "Bootstrap Unit Root Tests in Models with GARCH(1,1) Errors," Econometric Reviews, Taylor & Francis Journals, vol. 30(4), pages 379-405, August.
    See citations under working paper version above.
  26. Gospodinov, Nikolay, 2010. "Inference in Nearly Nonstationary SVAR Models With Long-Run Identifying Restrictions," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 1-12.

    Cited by:

    1. P. A. Nazarov & Kazakova, Maria, 2014. "Theoretical Basis of Prediction of Main Budget Parameters of Country," Published Papers r90221, Russian Presidential Academy of National Economy and Public Administration.
    2. Fève, Patrick & Guay, Alain, 2009. "Identification of Technology Shocks in Structural VARs," TSE Working Papers 09-028, Toulouse School of Economics (TSE).
    3. Chevillon, Guillaume & Mavroeidis, Sophocles & Zhan, Zhaoguo, 2016. "Robust inference in structural VARs with long-run restrictions," ESSEC Working Papers WP1702, ESSEC Research Center, ESSEC Business School.
    4. Velinov, Anton, 2016. "On the importance of testing structural identification schemes and the potential consequences of incorrectly identified models," VfS Annual Conference 2016 (Augsburg): Demographic Change 145581, Verein für Socialpolitik / German Economic Association.
    5. Tom Holden, 2010. "Products, patents and productivity persistence: A DSGE model of endogenous growth," Economics Series Working Papers 512, University of Oxford, Department of Economics.
    6. Christopher J. Gust & Robert J. Vigfusson, 2009. "The power of long-run structural VARs," International Finance Discussion Papers 978, Board of Governors of the Federal Reserve System (U.S.).
    7. Helmut Lütkepohl & Anna Staszewska-Bystrova & Peter Winker, 2017. "Estimation of Structural Impulse Responses: Short-Run versus Long-Run Identifying Restrictions," Discussion Papers of DIW Berlin 1642, DIW Berlin, German Institute for Economic Research.
    8. Andrei Polbin & Sergey Drobyshevsky, 2014. "Developing a Dynamic Stochastic Model of General Equilibrium for the Russian Economy," Research Paper Series, Gaidar Institute for Economic Policy, issue 166P, pages 156-156.
    9. Patrick Fève & Alain Guay, 2009. "The Response of Hours to a Technology Shock: A Two-Step Structural VAR Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(5), pages 987-1013, August.
    10. Gospodinov, Nikolay & Maynard, Alex & Pesavento, Elena, 2011. "Sensitivity of Impulse Responses to Small Low-Frequency Comovements: Reconciling the Evidence on the Effects of Technology Shocks," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(4), pages 455-467.
    11. Sevgi Coskun, 2020. "Technology Shocks and Non-stationary Hours in Emerging Countries and DSVAR," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 14(2), pages 129-163, May.
    12. Kilian, Lutz, 2011. "Structural Vector Autoregressions," CEPR Discussion Papers 8515, C.E.P.R. Discussion Papers.
    13. P. A. Nazarov & Kazakova, Maria, 2014. "Development of Prediction Model of Basic Budget Parameters in Russian Federation," Published Papers r90220, Russian Presidential Academy of National Economy and Public Administration.
    14. Stanislav Anatolyev & Nikolay Gospodinov, 2012. "Asymptotics of near unit roots (in Russian)," Quantile, Quantile, issue 10, pages 57-71, December.
    15. Chaudourne, Jeremy & Fève, Patrick & Guay, Alain, 2014. "Understanding the effect of technology shocks in SVARs with long-run restrictions," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 154-172.
    16. Markku Lanne & Henri Nyberg, 2015. "Nonlinear dynamic interrelationships between real activity and stock returns," CREATES Research Papers 2015-36, Department of Economics and Business Economics, Aarhus University.
    17. Velinov, Anton & Chen, Wenjuan, 2015. "Do stock prices reflect their fundamentals? New evidence in the aftermath of the financial crisis," Journal of Economics and Business, Elsevier, vol. 80(C), pages 1-20.
    18. Lieb, Lenard & Smeekes, Stephan, 2017. "Inference for Impulse Responses under Model Uncertainty," Research Memorandum 022, Maastricht University, Graduate School of Business and Economics (GSBE).
    19. P. A. Nazarov & Kazakova, Maria, 2014. "Methodological Principles of Prediction of Tax Revenues of Budgetary System," Published Papers r90219, Russian Presidential Academy of National Economy and Public Administration.
    20. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    21. Nguyen, Trang & Chaiechi, Taha & Eagle, Lynne & Low, David, 2020. "Dynamic impacts of SME stock market development and innovation on macroeconomic indicators: A Post-Keynesian approach," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 327-347.

  27. Anatolyev, Stanislav & Gospodinov, Nikolay, 2010. "Modeling Financial Return Dynamics via Decomposition," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(2), pages 232-245.

    Cited by:

    1. Stanislav Anatolyev, 2021. "Directional news impact curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 94-107, January.
    2. Lee Tae-Hwy & Wang He & Xi Zhou & Zhang Ru, 2023. "Density Forecast of Financial Returns Using Decomposition and Maximum Entropy," Journal of Econometric Methods, De Gruyter, vol. 12(1), pages 57-83, January.
    3. Nyberg, Henri & Pönkä, Harri, 2016. "International sign predictability of stock returns: The role of the United States," Economic Modelling, Elsevier, vol. 58(C), pages 323-338.
    4. Nyberg, Henri, 2011. "Forecasting the direction of the US stock market with dynamic binary probit models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 561-578.
    5. Hadhri, Sinda & Ftiti, Zied, 2017. "Stock return predictability in emerging markets: Does the choice of predictors and models matter across countries?," Research in International Business and Finance, Elsevier, vol. 42(C), pages 39-60.
    6. Harri Pönkä, 2017. "Predicting the direction of US stock markets using industry returns," Empirical Economics, Springer, vol. 52(4), pages 1451-1480, June.
    7. James W. Taylor & Keming Yu, 2016. "Using auto-regressive logit models to forecast the exceedance probability for financial risk management," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(4), pages 1069-1092, October.
    8. Liu, Xiaochun, 2015. "Modeling time-varying skewness via decomposition for out-of-sample forecast," International Journal of Forecasting, Elsevier, vol. 31(2), pages 296-311.
    9. Bernardina Algieri & Arturo Leccadito, 2020. "CARL and His POT: Measuring Risks in Commodity Markets," Risks, MDPI, vol. 8(1), pages 1-15, March.
    10. Straetmans, S.T.M. & Candelon, B. & Ahmed, J., 2012. "Predicting and capitalizing on stock market bears in the U.S," Research Memorandum 019, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    11. Lei, Heng & Xue, Minggao & Liu, Huiling, 2022. "Probability distribution forecasting of carbon allowance prices: A hybrid model considering multiple influencing factors," Energy Economics, Elsevier, vol. 113(C).
    12. Stanislav Anatolyev & Nikolay Gospodinov, 2015. "Multivariate return decomposition: theory and implications," FRB Atlanta Working Paper 2015-7, Federal Reserve Bank of Atlanta.
    13. de Resende, Charlene C. & Pereira, Adriano C.M. & Cardoso, Rodrigo T.N. & de Magalhães, A.R. Bosco, 2017. "Investigating market efficiency through a forecasting model based on differential equations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 199-212.
    14. Chen, Nan-Kuang & Chen, Shiu-Sheng & Chou, Yu-Hsi, 2013. "Further evidence on bear market predictability: The role of the external finance premium," MPRA Paper 49093, University Library of Munich, Germany.
    15. Stanislav Anatolyev & Jozef Barunik, 2017. "Forecasting dynamic return distributions based on ordered binary choice," Papers 1711.05681, arXiv.org, revised Jan 2019.
    16. Andreea Röthig & Andreas Röthig & Carl Chiarella, 2015. "On Candlestick-based Trading Rules Profitability Analysis via Parametric Bootstraps and Multivariate Pair-Copula based Models," Research Paper Series 362, Quantitative Finance Research Centre, University of Technology, Sydney.
    17. Liu, Xiaochun, 2017. "Can macroeconomic dynamics explain the time variation of risk–return trade-offs in the U.S. financial market?," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 275-293.
    18. Bury, Thomas, 2014. "Predicting trend reversals using market instantaneous state," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 404(C), pages 79-91.
    19. Hambuckers, J. & Ulm, M., 2023. "On the role of interest rate differentials in the dynamic asymmetry of exchange rates," Economic Modelling, Elsevier, vol. 129(C).
    20. Frazier, David T. & Liu, Xiaochun, 2016. "A new approach to risk-return trade-off dynamics via decomposition," Journal of Economic Dynamics and Control, Elsevier, vol. 62(C), pages 43-55.
    21. Liu, Jingzhen, 2019. "Impacts of lagged returns on the risk-return relationship of Chinese aggregate stock market: Evidence from different data frequencies," Research in International Business and Finance, Elsevier, vol. 48(C), pages 243-257.
    22. Algieri, Bernardina & Leccadito, Arturo, 2019. "Ask CARL: Forecasting tail probabilities for energy commodities," Energy Economics, Elsevier, vol. 84(C).
    23. Gu, Wentao & Peng, Yiqing, 2019. "Forecasting the market return direction based on a time-varying probability density model," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    24. Stanislav Anatolyev & Nikolay Gospodinov & Ibrahim Jamali & Xiaochun Liu, 2015. "Foreign exchange predictability during the financial crisis: implications for carry trade profitability," FRB Atlanta Working Paper 2015-6, Federal Reserve Bank of Atlanta.
    25. Liu, Jiadong & Papailias, Fotis & Quinn, Barry, 2021. "Direction-of-change forecasting in commodity futures markets," International Review of Financial Analysis, Elsevier, vol. 74(C).
    26. Liu, Xiaochun, 2017. "Unfolded risk-return trade-offs and links to Macroeconomic Dynamics," Journal of Banking & Finance, Elsevier, vol. 82(C), pages 1-19.
    27. Thomas Bury, 2013. "Predicting trend reversals using market instantaneous state," Papers 1310.8169, arXiv.org, revised Mar 2014.
    28. Stanislav Anatolyev & Natalia Kryzhanovskaya, 2009. "Directional Prediction of Returns under Asymmetric Loss: Direct and Indirect Approaches," Working Papers w0136, Center for Economic and Financial Research (CEFIR).
    29. Ginker, Tim & Lieberman, Offer, 2017. "Robustness of binary choice models to conditional heteroscedasticity," Economics Letters, Elsevier, vol. 150(C), pages 130-134.
    30. Nikolay Gospodinov, 2017. "Asset Co-movements: Features and Challenges," FRB Atlanta Working Paper 2017-11, Federal Reserve Bank of Atlanta.
    31. Riza Erdugan & Nada Kulendran & Riccardo Natoli, 2019. "Incorporating financial market volatility to improve forecasts of directional changes in Australian share market returns," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(4), pages 417-445, December.
    32. Nyberg, Henri, 2013. "Predicting bear and bull stock markets with dynamic binary time series models," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3351-3363.
    33. Anatolyev, Stanislav & Gospodinov, Nikolay & Jamali, Ibrahim & Liu, Xiaochun, 2017. "Foreign exchange predictability and the carry trade: A decomposition approach," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 199-211.
    34. Luis H. R. Alvarez E. & Paavo Salminen, 2017. "Timing in the presence of directional predictability: optimal stopping of skew Brownian motion," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 86(2), pages 377-400, October.
    35. Stanislav Anatolyev, 2013. "Objects of nonstructural time series modeling (in Russian)," Quantile, Quantile, issue 11, pages 1-12, December.
    36. Nyberg, Henri, 2011. "Forecasting the direction of the US stock market with dynamic binary probit models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 561-578, April.
    37. Liu, Xiaochun & Luger, Richard, 2015. "Unfolded GARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 186-217.
    38. Yang, Minxian, 2019. "The risk return relationship: Evidence from index returns and realised variances," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.

  28. Gospodinov, Nikolay & Irvine, Ian, 2009. "Tobacco taxes and regressivity," Journal of Health Economics, Elsevier, vol. 28(2), pages 375-384, March.

    Cited by:

    1. Donald S. Kenkel & Maximilian D. Schmeiser & Carly J. Urban, 2014. "Is Smoking Inferior? Evidence from Variation in the Earned Income Tax Credit," NBER Working Papers 20097, National Bureau of Economic Research, Inc.
    2. Ciccarelli, Carlo & De Fraja, Gianni & Vuri, Daniela, 2021. "Effects of passive smoking on prenatal and infant development: Lessons from the past," Economics & Human Biology, Elsevier, vol. 42(C).
    3. Pearl Bader & David Boisclair & Roberta Ferrence, 2011. "Effects of Tobacco Taxation and Pricing on Smoking Behavior in High Risk Populations: A Knowledge Synthesis," IJERPH, MDPI, vol. 8(11), pages 1-22, October.
    4. Davide Dragone & Francesco Manaresi & Luca Savorelli, 2016. "Obesity and Smoking: can we Kill Two Birds with one Tax?," Health Economics, John Wiley & Sons, Ltd., vol. 25(11), pages 1464-1482, November.
    5. Ian Irvine, 2008. "Smoking Intensity, Compensatory Behavior and Tobacco Tax Policy," Working Papers 200818, Geary Institute, University College Dublin.
    6. Qin, Ping. & Chen, Peilin. & Zhang, Xiao-Bing. & Xie, Lunyu., 2020. "Coal taxation reform in China and its distributional effects on residential consumers," Energy Policy, Elsevier, vol. 139(C).
    7. Jin, Hyun Joung & Cho, Sung Min, 2021. "Effects of cigarette price increase on fresh food expenditures of low-income South Korean households that spend relatively more on cigarettes," Health Policy, Elsevier, vol. 125(1), pages 75-82.
    8. Richard Bird & Michael Smart & Jorge Martinez-Vazquez, 2016. "Taxing Consumption in Canada: Rates, Revenues, and Redistribution," International Center for Public Policy Working Paper Series, at AYSPS, GSU paper1605, International Center for Public Policy, Andrew Young School of Policy Studies, Georgia State University.
    9. Martin Gonzalez-Rozada, 2019. "Increasing Cigarette Taxes is Unfair to the Poor? Evidence from Argentina," Department of Economics Working Papers 2019_01, Universidad Torcuato Di Tella.
    10. Anindya Sen, 2017. "Smokes, Smugglers and Lost Tax Revenues: How Governments Should Respond," C.D. Howe Institute Commentary, C.D. Howe Institute, issue 471, February.
    11. Sen Anindya & Ariizumi Hideki & Driambe Daciana, 2010. "Do Changes In Cigarette Taxes Impact Youth Smoking? Evidence from Canadian Provinces," Forum for Health Economics & Policy, De Gruyter, vol. 13(2), pages 1-25, August.
    12. Davide, Dragone & Francesco, Manaresi & Luca, Savorelli, 2013. "Obesity and smoking: can we catch two birds with one tax?," SIRE Discussion Papers 2013-31, Scottish Institute for Research in Economics (SIRE).
    13. Colombo, Luca & Galmarini, Umberto, 2023. "Taxation and anti-smoking campaigns: Complementary policies in tobacco control," Journal of Policy Modeling, Elsevier, vol. 45(1), pages 31-57.
    14. Raul A. Ponce-Rodriguez & Charles R. Hankla & Jorge Martinez-Vazquez & Eunice Heredia-Ortiz, 2016. "Frozen In Time: Rethinking the Poltical Economy of Decentralization: How Elections and Parties Shape the Provision of Local Public Goods," International Center for Public Policy Working Paper Series, at AYSPS, GSU paper1604, International Center for Public Policy, Andrew Young School of Policy Studies, Georgia State University.

  29. Nikolay Gospodinov, 2009. "A New Look at the Forward Premium Puzzle," Journal of Financial Econometrics, Oxford University Press, vol. 7(3), pages 312-338, Summer.
    See citations under working paper version above.
  30. Gospodinov, Nikolay, 2008. "Asymptotic and bootstrap tests for linearity in a TAR-GARCH(1,1) model with a unit root," Journal of Econometrics, Elsevier, vol. 146(1), pages 146-161, September.

    Cited by:

    1. Narayan, Paresh Kumar & Liu, Ruipeng & Westerlund, Joakim, 2016. "A GARCH model for testing market efficiency," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 41(C), pages 121-138.
    2. Ghassan, Hassan Belkacem & AlHajhoj, Hassan Rafdan, 2016. "Long run dynamic volatilities between OPEC and non-OPEC crude oil prices," Applied Energy, Elsevier, vol. 169(C), pages 384-394.
    3. Nikolay Gospodinov & Ye Tao, 2011. "Bootstrap Unit Root Tests in Models with GARCH(1,1) Errors," Econometric Reviews, Taylor & Francis Journals, vol. 30(4), pages 379-405, August.
    4. Jesús Gonzalo & Jean-Yves Pitarakis, 2013. "Estimation and inference in threshold type regime switching models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 8, pages 189-205, Edward Elgar Publishing.
    5. Hassan Ghassan & Prashanta Banerjee, 2015. "A threshold cointegration analysis of asymmetric adjustment of OPEC and non-OPEC monthly crude oil prices," Empirical Economics, Springer, vol. 49(1), pages 305-323, August.
    6. Bernard Njindan Iyke, 2019. "A Test Of The Efficiency Of The Foreign Exchange Market In Indonesia," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 0(12th BMEB), pages 1-26, January.

  31. Athanasia Gavala & Nikolay Gospodinov & Deming Jiang, 2006. "Forecasting volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(6), pages 381-400.

    Cited by:

    1. Herwartz, Helmut & Golosnoy, Vasyl, 2007. "Semiparametric Approaches to the Prediction of Conditional Correlation Matrices in Finance," Economics Working Papers 2007-23, Christian-Albrechts-University of Kiel, Department of Economics.
    2. Georgios Chortareas & Menelaos Karanasos & Emmanouil Noikokyris, 2019. "Quantitative Easing And The Uk Stock Market: Does The Bank Of England Information Dissemination Strategy Matter?," Economic Inquiry, Western Economic Association International, vol. 57(1), pages 569-583, January.
    3. Nikita Medvedev & Zhiguang Wang, 2022. "Multistep forecast of the implied volatility surface using deep learning," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(4), pages 645-667, April.
    4. Ashish Kumar, 2015. "Impact of Currency Futures on Volatility in Exchange Rate," Paradigm, , vol. 19(1), pages 95-108, June.
    5. Le, Van & Zurbruegg, Ralf, 2010. "The role of trading volume in volatility forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(5), pages 533-555, December.
    6. Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "High-Frequency and Model-Free Volatility Estimators," Working Papers 2009-13, Faculty of Economic Sciences, University of Warsaw.
    7. Constandina Koki & Loukia Meligkotsidou & Ioannis Vrontos, 2020. "Forecasting under model uncertainty: Non‐homogeneous hidden Markov models with Pòlya‐Gamma data augmentation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 580-598, July.
    8. Emmanuel Afuecheta & Idika E. Okorie & Saralees Nadarajah & Geraldine E. Nzeribe, 2024. "Forecasting Value at Risk and Expected Shortfall of Foreign Exchange Rate Volatility of Major African Currencies via GARCH and Dynamic Conditional Correlation Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 271-304, January.
    9. Kelvin Mutum, 2020. "Volatility Forecast Incorporating Investors’ Sentiment and its Application in Options Trading Strategies: A Behavioural Finance Approach at Nifty 50 Index," Vision, , vol. 24(2), pages 217-227, June.
    10. Gospodinov, Nikolay & Jamali, Ibrahim, 2012. "The effects of Federal funds rate surprises on S&P 500 volatility and volatility risk premium," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 497-510.
    11. Weiguo Zhang & Xue Gong & Chao Wang & Xin Ye, 2021. "Predicting stock market volatility based on textual sentiment: A nonlinear analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1479-1500, December.
    12. Jian Zhou & Zhixin Kang, 2011. "A Comparison of Alternative Forecast Models of REIT Volatility," The Journal of Real Estate Finance and Economics, Springer, vol. 42(3), pages 275-294, April.
    13. Yoon, Sun-Joong, 2017. "Time-varying risk aversion and return predictability," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 327-339.
    14. Min Liu & Wei‐Chong Choo & Chi‐Chuan Lee & Chien‐Chiang Lee, 2023. "Trading volume and realized volatility forecasting: Evidence from the China stock market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 76-100, January.
    15. Ariful Hoque & Chandrasekhar Krishnamurti, 2012. "Modeling moneyness volatility in measuring exchange rate volatility," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 8(4), pages 365-380, September.
    16. Balli, Hatice Ozer & Tsui, Wai Hong Kan & Balli, Faruk, 2019. "Modelling the volatility of international visitor arrivals to New Zealand," Journal of Air Transport Management, Elsevier, vol. 75(C), pages 204-214.

  32. Nikolay Gospodinov, 2005. "Testing For Threshold Nonlinearity in Short-Term Interest Rates," Journal of Financial Econometrics, Oxford University Press, vol. 3(3), pages 344-371.

    Cited by:

    1. Wolfgang Lemke & Theofanis Archontakis, 2008. "Bond pricing when the short-term interest rate follows a threshold process," Quantitative Finance, Taylor & Francis Journals, vol. 8(8), pages 811-822.
    2. Peter Sephton & Janelle Mann, 2013. "Threshold Cointegration: Model Selection with an Application," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 56(2), pages 54-77.
    3. Chen, Cathy W.S. & Gerlach, Richard H. & Tai, Amanda P.J., 2008. "Testing for nonlinearity in mean and volatility for heteroskedastic models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 489-499.
    4. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    5. Misiorek Adam & Trueck Stefan & Weron Rafal, 2006. "Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-36, September.
    6. Chew Lian Chua & Sandy Suardi & Sarantis Tsiaplias, 2011. "Predicting Short-Term Interest Rates: Does Bayesian Model Averaging Provide Forecast Improvement?," Melbourne Institute Working Paper Series wp2011n01, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    7. Sephton, Peter & Mann, Janelle, 2018. "Gold and crude oil prices after the great moderation," Energy Economics, Elsevier, vol. 71(C), pages 273-281.
    8. Gospodinov, Nikolay, 2008. "Asymptotic and bootstrap tests for linearity in a TAR-GARCH(1,1) model with a unit root," Journal of Econometrics, Elsevier, vol. 146(1), pages 146-161, September.
    9. Cathy W. S. Chen & Richard H. Gerlach & Ann M. H. Lin, 2010. "Falling and explosive, dormant, and rising markets via multiple‐regime financial time series models," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 26(1), pages 28-49, January.
    10. Jesús Gonzalo & Jean-Yves Pitarakis, 2013. "Estimation and inference in threshold type regime switching models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 8, pages 189-205, Edward Elgar Publishing.
    11. Leonidov, Andrei & Trainin, Vladimir & Zaitsev, Alexander & Zaitsev, Sergey, 2007. "Market mill dependence pattern in the stock market: Modeling of predictability and asymmetry via multi-component conditional distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 386(1), pages 240-252.
    12. Sephton, Peter S., 2019. "El Niño, La Niña, and a cup of Joe," Energy Economics, Elsevier, vol. 84(C).
    13. Christopoulos, Dimitris & McAdam, Peter & Tzavalis, Elias, 2018. "Dealing with endogeneity in threshold models using copulas: an illustration to the foreign trade multiplier," Working Paper Series 2136, European Central Bank.
    14. Ahmad Yamin & Donayre Luiggi, 2016. "Outliers and persistence in threshold autoregressive processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(1), pages 37-56, February.

  33. Nikolay Gospodinov & Ian Irvine, 2005. "A `long march' perspective on tobacco use in Canada," Canadian Journal of Economics, Canadian Economics Association, vol. 38(2), pages 366-393, May.

    Cited by:

    1. Laibson, David I., 1997. "Golden Eggs and Hyperbolic Discounting," Scholarly Articles 4481499, Harvard University Department of Economics.
    2. Anindya Sen, 2009. "Estimating the impacts of household behavior on youth smoking: evidence from Ontario, Canada," Review of Economics of the Household, Springer, vol. 7(2), pages 189-218, June.
    3. Auld M. Christopher & Zarrabi Mahmood, 2015. "Long-Term Effects of Tobacco Prices Faced by Adolescents," Forum for Health Economics & Policy, De Gruyter, vol. 18(1), pages 1-24, January.
    4. Gospodinov, Nikolay & Irvine, Ian, 2009. "Tobacco taxes and regressivity," Journal of Health Economics, Elsevier, vol. 28(2), pages 375-384, March.
    5. Latif, Ehsan, 2014. "The impact of recession on drinking and smoking behaviours in Canada," Economic Modelling, Elsevier, vol. 42(C), pages 43-56.

  34. Gospodinov Nikolay & Irvine Ian J., 2004. "Global Health Warnings on Tobacco Packaging: Evidence from the Canadian Experiment," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 4(1), pages 1-23, November.

    Cited by:

    1. Christopher Carpenter & Hai V. Nguyen, 2020. "Intended and Unintended Effects of Banning Menthol Cigarettes," NBER Working Papers 26811, National Bureau of Economic Research, Inc.
    2. Helen G. Levy & Edward C. Norton & Jeffrey A. Smith, 2018. "Tobacco Regulation and Cost-Benefit Analysis: How Should We Value Foregone Consumer Surplus?," American Journal of Health Economics, MIT Press, vol. 4(1), pages 1-25, Winter.
    3. Nikolay Gospodinov & Ian Irvine, 2005. "A ‘long march’ perspective on tobacco use in Canada," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 38(2), pages 366-393, May.
    4. Noar, Seth M. & Francis, Diane B. & Bridges, Christy & Sontag, Jennah M. & Ribisl, Kurt M. & Brewer, Noel T., 2016. "The impact of strengthening cigarette pack warnings: Systematic review of longitudinal observational studies," Social Science & Medicine, Elsevier, vol. 164(C), pages 118-129.
    5. Sunday Azagba & Mesbah Sharaf, 2011. "Cigarette Taxes and Smoking Participation: Evidence from Recent Tax Increases in Canada," IJERPH, MDPI, vol. 8(5), pages 1-18, May.
    6. Gospodinov, Nikolay & Irvine, Ian, 2009. "Tobacco taxes and regressivity," Journal of Health Economics, Elsevier, vol. 28(2), pages 375-384, March.
    7. Trinidad Beleche & Nellie Lew & Rosemarie L. Summers & J. Laron Kirby, 2018. "Are Graphic Warning Labels Stopping Millions of Smokers? A Comment on Huang, Chaloupka, and Fong," Econ Journal Watch, Econ Journal Watch, vol. 15(2), pages 129–157-1, May.

  35. Nikolay Gospodinov, 2004. "Asymptotic confidence intervals for impulse responses of near-integrated processes," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 505-527, December.

    Cited by:

    1. Ulrich K. Müller & Andriy Norets, 2016. "Coverage Inducing Priors in Nonstandard Inference Problems," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(515), pages 1233-1241, July.
    2. Rossi, Barbara & Pesavento, Elena, 2003. "Small Sample Confidence Intervals for Multivariate Impulse Response Functions at Long Horizons," Working Papers 03-19, Duke University, Department of Economics.
    3. Barbara Rossi, 2013. "Exchange rate predictability," Economics Working Papers 1369, Department of Economics and Business, Universitat Pompeu Fabra.
    4. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.
    5. Kilian, Lutz & Kim, Yun Jung, 2009. "Do Local Projections Solve the Bias Problem in Impulse Response Inference?," CEPR Discussion Papers 7266, C.E.P.R. Discussion Papers.
    6. Helmut Luetkepohl, 2011. "Vector Autoregressive Models," Economics Working Papers ECO2011/30, European University Institute.
    7. José Luis Montiel Olea & Mikkel Plagborg‐Møller, 2021. "Local Projection Inference Is Simpler and More Robust Than You Think," Econometrica, Econometric Society, vol. 89(4), pages 1789-1823, July.
    8. Atsushi Inoue & Lutz Kilian, 2019. "The Uniform Validity of Impulse Response Inference in Autoregressions," Working Papers 1908, Federal Reserve Bank of Dallas.
    9. De-Chih Liu, 2023. "Unemployment persistence with an evolutionary perspective: job creation or destruction (or both)?," Evolutionary and Institutional Economics Review, Springer, vol. 20(1), pages 83-109, April.
    10. Zeynel Abidin Ozdemir & Emre Aksoy, 2015. "Are real exchanges rate series really persistent?: evidence from three commonwealth of independent states countries," Applied Economics, Taylor & Francis Journals, vol. 47(40), pages 4299-4309, August.
    11. Kim, Jae H. & Silvapulle, Param & Hyndman, Rob J., 2007. "Half-life estimation based on the bias-corrected bootstrap: A highest density region approach," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3418-3432, April.
    12. Sofiane H. Sekioua, 2004. "Real interest parity (RIP) over the 20th century: New evidence based on confidence intervals for the dominant root and half-lives of shocks," Money Macro and Finance (MMF) Research Group Conference 2004 91, Money Macro and Finance Research Group.
    13. Liyu Dou & Ulrich K. Müller, 2021. "Generalized Local‐to‐Unity Models," Econometrica, Econometric Society, vol. 89(4), pages 1825-1854, July.
    14. Stanislav Anatolyev & Nikolay Gospodinov, 2012. "Asymptotics of near unit roots (in Russian)," Quantile, Quantile, issue 10, pages 57-71, December.
    15. Diego Romero-Avila & Carlos Usabiaga, 2007. "Unit root tests and persistence of unemployment: Spain vs. the United States," Applied Economics Letters, Taylor & Francis Journals, vol. 14(6), pages 457-461.
    16. Diego Romero‐Ávila & Carlos Usabiaga, 2007. "Unit Root Tests, Persistence, and the Unemployment Rate of the U.S. States," Southern Economic Journal, John Wiley & Sons, vol. 73(3), pages 698-716, January.
    17. Elena Pesavento, Barbara Rossi, 2006. "Impulse Response Confidence Intervals for Persistent Data: What Have We Learned?," Economics Working Papers ECO2006/19, European University Institute.
    18. Christian Gourieroux & Joann Jasiak, 2022. "Long Run Risk in Stationary Structural Vector Autoregressive Models," Papers 2202.09473, arXiv.org.
    19. Amilcar Velez, 2023. "The Local Projection Residual Bootstrap for AR(1) Models," Papers 2309.01889, arXiv.org, revised Feb 2024.
    20. Jayasuriya, Sisira & Kim, Jae H. & Kumar, Parmod, 2007. "International and Internal Market Integration in Indian agriculture: A study of the Indian Rice Market," 106th Seminar, October 25-27, 2007, Montpellier, France 7935, European Association of Agricultural Economists.
    21. Carlos Usabiaga & Diego Romero-Ávila, 2012. "New Disaggregate Evidence on Spanish Inflation Persistence," EcoMod2012 3800, EcoMod.
    22. Kim, Jae H. & Ji, Philip Inyeob, 2011. "Mean-reversion in international real interest rates," Economic Modelling, Elsevier, vol. 28(4), pages 1959-1966, July.
    23. Ozdemir, Zeynel Abidin & Gokmenoglu, Korhan & Ekinci, Cagdas, 2013. "Persistence in crude oil spot and futures prices," Energy, Elsevier, vol. 59(C), pages 29-37.
    24. G. K. Randolph Tan, 2006. "Robust Inference for Measures of Persistence in Singapore Sectoral Property Price Indexes," Journal of Property Research, Taylor & Francis Journals, vol. 23(4), pages 305-321, October.
    25. Mohsen Bahmani-Oskooee & Omid Ranjbar, 2016. "Quantile unit root test and PPP: evidence from 23 OECD countries," Applied Economics, Taylor & Francis Journals, vol. 48(31), pages 2899-2911, July.
    26. Diego Romero-Ávila & Carlos Usabiaga, 2012. "Disaggregate evidence on Spanish inflation persistence," Applied Economics, Taylor & Francis Journals, vol. 44(23), pages 3029-3046, August.
    27. Sekioua, Sofiane H., 2008. "Real interest parity (RIP) over the 20th century: New evidence based on confidence intervals for the largest root and the half-life," Journal of International Money and Finance, Elsevier, vol. 27(1), pages 76-101, February.
    28. Lieb, Lenard & Smeekes, Stephan, 2017. "Inference for Impulse Responses under Model Uncertainty," Research Memorandum 022, Maastricht University, Graduate School of Business and Economics (GSBE).
    29. Zeynel Abidin Ozdemir & Cagdas Ekinci & Korhan Gokmenoglu, 2015. "International Evidence On Real Interest Rate Persistence," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 60(04), pages 1-14.

  36. Gospodinov, Nikolay, 2002. "Bootstrap-Based Inference in Models with a Nearly Noninvertible Moving Average Component," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 254-268, April.

    Cited by:

    1. Lynda Khalaf & Beatriz Peraza López, 2020. "Simultaneous Indirect Inference, Impulse Responses and ARMA Models," Econometrics, MDPI, vol. 8(2), pages 1-26, April.
    2. Nikolay Gospodinov & Serena Ng, 2013. "Minimum distance estimation of possibly non-invertible moving average models," FRB Atlanta Working Paper 2013-11, Federal Reserve Bank of Atlanta.
    3. James Morley & Irina B. Panovska & Tara M. Sinclair, 2014. "Testing Stationarity for Unobserved Components Models," Discussion Papers 2012-41B, School of Economics, The University of New South Wales.
    4. Kim, Chang-Jin & Kim, Jaeho, 2013. "The `Pile-up Problem' in Trend-Cycle Decomposition of Real GDP: Classical and Bayesian Perspectives," MPRA Paper 51118, University Library of Munich, Germany.
    5. Mihaela Simionescu & Irina Dragan, 2016. "The Evaluation Of Quarterly Forecast Intervals For Inflation Rate In Romania," Economic Review: Journal of Economics and Business, University of Tuzla, Faculty of Economics, vol. 14(1), pages 80-89, May.
    6. Stanislav Anatolyev & Nikolay Gospodinov, 2012. "Asymptotics of near unit roots (in Russian)," Quantile, Quantile, issue 10, pages 57-71, December.
    7. James Morley & Irina B. Panovska & Tara M. Sinclair, 2013. "Testing Stationarity for Unobserved Components Models," Discussion Papers 2012-41A, School of Economics, The University of New South Wales.

  37. Gospodinov, Nikolay, 2002. "Median unbiased forecasts for highly persistent autoregressive processes," Journal of Econometrics, Elsevier, vol. 111(1), pages 85-101, November.
    See citations under working paper version above.

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