"Short T Dynamic Panel Data Models with Individual, Time and Interactive Effects", by Kazuhiko Hayakawa, M. Hashem Pesaran and L. Vanessa Smith, forthcoming in Journal of Applied Econometrics, February 2023.

Abstract: This paper proposes a transformed quasi maximum likelihood (TQML) estimator for short T dynamic fixed effects panel data models allowing for interactive effects through a multi-factor error structure. The proposed estimator is robust to the heterogeneity of the initial values and common unobserved effects, whilst at the same time allowing for standard fixed and time effects. It is applicable to both stationary and unit root cases. The order condition for identification of the number of interactive effects is established, and conditions are derived under which the parameters are locally idented. It is shown that global identification in the presence of the lagged dependent variable cannot be guaranteed. The TQML estimator is proven to be consistent and asymptotically normally distributed. A sequential multiple testing likelihood ratio procedure is also proposed for estimation of the number of factors which is shown to be consistent. Finite sample results obtained from Monte Carlo simulations show that the proposed procedure for determining the number of factors performs very well and the TQML estimator has small bias and RMSE, and correct empirical size in most settings. The practical use of the TQML approach is demonstrated by means of two empirical illustrations from the literature on cross county crime rates and cross country growth regressions.
JEL Classifications: C12, C13, C23.
Key Words: short T dynamic panels, unobserved common factors, quasi maximum likelihood, interactive effects, multiple testing, sequential likelihood ratio tests, crime rate, growth regressions.
Full Text: http://www.econ.cam.ac.uk/people-files/emeritus/mhp1/fp23/HPS_paper_Short_T_Dynamic_FE_Panels_with_interactive_effects_March_2023 _SSRN-id3268434.pdf
SSRN Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3268434

"Identification and Estimation of Categorical Random Coeficient Models", by Zhan Gao and M. Hashem Pesaran, forthcoming in Empirical Economics, a Special Issue in Honor of Peter Schmidt, February 2023, Cambridge Working Papers in Economics, CWPE2228

Abstract: This paper proposes a linear categorical random coefficient model, in which the random coefficients follow parametric categorical distributions. The distributional parameters are identified based on a linear recurrence structure of moments of the random coefficients. A Generalized Method of Moments estimation procedure is proposed also employed by Peter Schmidt and his coauthors to address heterogeneity in time effects in panel data models. Using Monte Carlo simulations, we find that moments of the random coefficients can be estimated reasonably accurately, but large samples are required for estimation of the parameters of the underlying categorical distribution. The utility of the proposed estimator is illustrated by estimating the distribution of returns to education in the U.S. by gender and educational levels. We find that rising heterogeneity between educational groups is mainly due to the increasing returns to education for those with postsecondary education, whereas within group heterogeneity has been rising mostly in the case of individuals with high school or less education.
JEL Classifications: C01, C21, C13, C46, J30
Key Words: Random coefficient models, categorical distribution, return to education
Full Text: https://www.econ.cam.ac.uk/research-files/repec/cam/pdf/cwpe2228.pdf

"Testing for Alpha in Linear Factor Pricing Models with a Large Number of Securities", by M. Hashem Pesarann and Takashi Yamagata, forthcoming in Journal of Financial Econometrics, January 2023

Abstract: This paper considers tests of alpha in linear factor pricing models when the number of securities, N, is much larger than the time dimension, T, of the individual return series. We focus on class of tests that are based on Student t tests of individual securities which have a number of advantages over the existing standardised Wald type tests, and propose a test procedure that allows for non-Gaussianity and general forms of weakly cross correlated errors. It does not require estimation of an invertible error covariance matrix, it is much faster to implement, and is valid even if N is much larger than T. We also show that the proposed test can account for some limited degree of pricing errors allowed under Ross’s Arbitrage Pricing Theory condition. Monte Carlo evidence shows that the proposed test performs remarkably well even when T = 60 and N = 5,000. The test is applied to monthly returns on securities in the S&P 500 at the end of each month in real time, using rolling windows of size 60. Statistically significant evidence against Sharpe-Lintner CAPM, Fama-French three and five factor models are found mainly during the period of Great Recession (2007M12-2009M06).
JEL Classifications: C12, C15, C23, G11, G12
Key Words: CAPM, Arbitrage Asset Pricing, Testing for alpha, Weak and spatial error cross-sectional dependence, S&P 500 securities.
Full Text: https://www.econ.cam.ac.uk/people-files/emeritus/mhp1/fp23/PY_LFPM_SW55_Nov_28_2022 Main_and_Supplement.pdf
Supplementary Data: https://www.econ.cam.ac.uk/people-files/emeritus/mhp1/fp23/supplementary_data_files.zip
Replication Files Table 1: https://www.econ.cam.ac.uk/people-files/emeritus/mhp1/fp23/Empirical_Results_Replication_Code_and_Data_for_Table 1.zip
Replication Files Tables 2-7: https://www.econ.cam.ac.uk/people-files/emeritus/mhp1/fp23/MC_Replication_Code_for_Tables_2_to_7.zip
Replication Files Table 8: https://www.econ.cam.ac.uk/people-files/emeritus/mhp1/fp23/Empirical_Results_Replication_Code_and_Data_for_Table 8.zip

"Social Distancing, Vaccination and Evolution of COVID-19 Transmission Rates in Europe", by Alexander Chudik, M. Hashem Pesaran and Alessandro Rebucci, forthcoming in IMF Economic Review, June 2022, Cambridge Working Papers in Economics CWPE2230, CESifo Working Paper No. 9754.

Abstract: This paper provides estimates of COVID-19 transmission rates and explains their evolution for selected European countries since the start of the pandemic taking account of changes in voluntary and government mandated social distancing, incentives to comply, vaccination and the emergence of new variants. Evidence based on panel data modeling indicates that the diversity of outcomes that we document may have resulted from the non-linear interaction of mandated and voluntary social distancing and the economic incentives that governments provided to support isolation. The importance of these factors declined over time, with vaccine uptake driving heterogeneity in country experiences in 2021. Our approach also allows us to identify the basic reproduction number, R₀, which is precisely estimated around 5, which is much larger than the values in the range of 2:4 - 3:9 assumed in the extant literature.
JEL Classifications: D0, F60, C4, I120, E7
Key Words: COVID-19, multiplication factor, under-reporting, social distancing, SIR model, stochastic network models, reproduction number, pandemics, vaccine.
Full Text: https://www.econ.cam.ac.uk/people-files/emeritus/mhp1/fp22/CPR_revision_JUNE26_2022.pdf
CWPE: https://www.econ.cam.ac.uk/research-files/repec/cam/pdf/cwpe2230.pdf
CESifo: https://www.cesifo.org/en/publikationen/2022/working-paper/social-distancing-vaccination-and-evolution-covid-19-transmission

"A Spatiotemporal Equilibrium Model of Migration and Housing Interlinkages, by Wukuang Cun and M. Hashem Pesaran, forthcoming in Journal of Housing Economics, April 2022, Cambridge Working Papers in Economics, CWPE2225

Abstract: This paper develops and solves a spatiotemporal equilibrium model in which regional wages and house prices are jointly determined with location-to-location migration flows. The agent’s optimal location choice and the resultant migration process are shown to be Markovian, with the transition probabilities across all location pairs given as non-linear functions of wage and housing cost differentials, endogenously responding to migration flows. The model can be used for the analysis of spatial distribution of population, income, and house prices, as well as for spatiotemporal impulse response analysis. The model is estimated on a panel of 48 mainland U.S. states and the District of Columbia using the training sample (1976-1999), and shown to fit the data well over the evaluation sample (2000-2014). The estimated model is then used to analyze the size and speed of spatial spill-over effects by computing spatiotemporal impulse responses of positive productivity and land-supply shocks to California, Texas, and Florida. Our simulation results show that states with a lower level of land-use regulation can benefit more from positive state-specific productivity shocks; and positive land-supply shocks are much more effective in states, such as California, that are subject to more stringent land-use regulations.
JEL Classifications: E00, R23, R31
Key Words: location choice, joint determination of migration flows and house prices, spatiotemporal impulse response analysis, land-use deregulation, population allocation, productivity and land supply shocks, California, Texas and Florida
Full Text: https://doi.org/10.1016/j.jhe.2022.101839