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  • "Uncertainty and Economic Activity: A Multi-Country Perspective", by Ambrogio Cesa-Bianchi, M. Hashem Pesaran and Alessandro Rebucci, forthcoming in The Review of Financial Studies, June 2019

    Abstract: This paper develops an asset pricing model with heterogeneous exposure to a persistent world growth factor to identify global growth and financial shocks in a multi-country panel VAR model for the analysis of the relationship between volatility and the business cycle. The econometric estimates yield three sets of empirical results regarding (i) the importance of global growth for the interpretation of the correlation between volatility and growth over the business cycle and the possible presence of omitted variable bias in single-country VARs studies, (ii) the extent to which output shocks drive volatility, and (iii) the transmission of volatility shocks to output growth.
    JEL Classifications: E44, F44, G15
    Key Words: Uncertainty, Business Cycle, Global Shocks, Multi-Country Asset Pricing Model, Panel VAR, Identification, Realized Volatility, Impulse Responses.
    Full Text: http://www.econ.cam.ac.uk/people-files/emeritus/mhp1/fp19/CPR_FinalManuscript.pdf
    Supplement: http://www.econ.cam.ac.uk/people-files/emeritus/mhp1/fp19/CPR_Supplement.pdf
    Data: http://www.econ.cam.ac.uk/people-files/emeritus/mhp1/fp19/REPLICATIONFILES-Submittedon19-08-2019.zip
     

  • "Exponent of Cross-sectional Dependence for Residuals", by Natalia Bailey, George Kapetanios and M. Hashem Pesaran, forthcoming in Sankhya B. The Indian Journal of Statistics, April 2019

    Abstract: In this paper we focus on estimating the degree of cross-sectional dependence in the error terms of a classical panel data regression model. For this purpose we propose an estimator of the exponent of cross-sectional dependence denoted by α, which is based on the number of non-zero pair-wise cross correlations of these errors. We prove that our estimator, ã, is consistent and derive the rate at which ã, approaches its true value. We evaluate the finite sample properties of the proposed estimator by use of a Monte Carlo simulation study. The numerical results are encouraging and supportive of the theoretical findings. Finally, we undertake an empirical investigation of α for the errors of the CAPM model and its Fama-French extensions using 10-year rolling samples from S&P 500 securities over the period Sept 1989 - May 2018.
    JEL Classifications: C21, C32
    Key Words: Pair-wise correlations, Cross-sectional dependence, Cross-sectional averages, Weak and strong factor models. CAPM and Fama-French Factors.
    Full Text: http://www.econ.cam.ac.uk/people-files/emeritus/mhp1/fp19/BKP_res_paper_4_Apr_2019.pdf