"Common Correlated Effects Estimation of Heterogeneous Dynamic Panel Quantile Regression Models", by Matthew Harding, Carlos Lamarche and M. Hashem Pesaran, forthcoming in Journal of Applied Econometrics, December 2019

Abstract: This paper proposes a quantile regression estimator for a heterogeneous panel model with lagged dependent variables and interactive effects. The paper adopts the Common Correlated Effects (CCE) approach proposed by Pesaran (2006) and Chudik and Pesaran (2015) and demonstrates that the extension to the estimation of dynamic quantile regression models is feasible under similar conditions to the ones used in the literature. The new quantile regression estimator is shown to be consistent and its asymptotic distribution is derived. Monte Carlo studies are carried out to study the small sample behavior of the proposed approach. The evidence shows that the estimator can significantly improve on the performance of existing estimators as long as the time series dimension of the panel is large. We present an application to the evaluation of Time-of-Use pricing using a large randomized control trial.
JEL Classifications: C21, C31, C33, D12, L94
Key Words: Common Correlated Effects; Dynamic Panel; Quantile Regression; Smart Meter; Randomized Experiment.
Full Text: http://www.econ.cam.ac.uk/people-files/emeritus/mhp1/fp20/qmg40-rev21.pdf
Appendix: http://www.econ.cam.ac.uk/people-files/emeritus/mhp1/fp20/qmg40-rev21-online-appendix.pdf
 

"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
 

"Econometric Analysis of Production Networks with Dominant Units", by M. Hashem Pesarann and Cynthia Fan Yang, forthcoming in Journal of Econometrics, March 2019

Abstract: This paper introduces the notions of strongly and weakly dominant units for networks, and shows that pervasiveness of shocks to a network is measured by the degree of dominance of its most pervasive unit; shown to be equivalent to the inverse of the shape parameter of the power law fi…tted to the network outdegrees. New cross- section and panel extremum estimators of the degree of dominance in networks are proposed, and their asymptotic properties investigated. The small sample properties of the proposed estimators are examined by Monte Carlo experiments, and their use is illustrated by an empirical application to US input-output tables.
JEL Classifications: C12, C13, C23, C67, E32
Key Words: Aggregate fluctuations, strongly and weakly dominant units, spatial models, outdegrees, degree of pervasiveness, power law, input-output tables, US economy.
Full Text: http://www.econ.cam.ac.uk/emeritus/mhp1/fp19/PY_Production_network_March_10_2019.pdf
Supplement: http://www.econ.cam.ac.uk/emeritus/mhp1/wp17/Online-supplement-PY-Production-network-4-August-2017.pdf
Readme: http://www.econ.cam.ac.uk/emeritus/mhp1/wp17/Readme-PY-Production-network-4-August-2017.pdf
Data: http://www.econ.cam.ac.uk/emeritus/mhp1/wp17/Data-PY-Production-network-4-August-2017.zip
Codes: http://www.econ.cam.ac.uk/emeritus/mhp1/wp17/Codes-PY-Production-network-4-August-2017.zip