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  • "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
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  • "Matching Theory and Evidence on Covid-19 using a Stochastic Network SIR Model", by M. Hashem Pesaran and Cynthia Fan Yang, forthcoming in Journal of Applied Econometrics, December 2021.

    Abstract: This paper develops an individual-based stochastic network SIR model for the empirical analysis of the Covid-19 pandemic. It derives moment conditions for the number of infected and active cases for single as well as multigroup epidemic models. These moment conditions are used to investigate the identification and estimation of the transmission rates. The paper then proposes a method that jointly estimates the transmission rate and the magnitude of under-reporting of infected cases. Empirical evidence on six European countries matches the simulated outcomes once the under-reporting of infected cases is addressed. It is estimated that the number of actual cases could be between 4 to 10 times higher than the reported numbers in October 2020 and declined to 2 to 3 times in April 2021. The calibrated models are used in the counterfactual analyses of the impact of social distancing and vaccination on the epidemic evolution, and the timing of early interventions in the UK and Germany.
    JEL Classifications: C13, C15, C31, D85, I18, J18
    Key Words: Covid-19, multigroup SIR model, basic and e¤ective reproduction numbers, transmission rates, vaccination, calibration and counterfactual analysis.
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  • "Arbitrage Pricing Theory, the Stochastic Discount Factor and Estimation of Risk Premia from Portfolios", by M. Hashem Pesaran and Ron P. Smith, forthcoming in Econometrics and Statistics, November 2021, CESifo Working Paper No. 9001

    Abstract: The arbitrage pricing theory (APT) attributes differences in expected returns to exposure to systematic risk factors. Two aspects of the APT are considered. Firstly, the factors in the statistical asset pricing model are related to a theoretically consistent set of factors defined by their conditional covariation with the stochastic discount factor (SDF) used to price securities within inter-temporal asset pricing models. It is shown that risk premia arise from non-zero correlation of observed factors with SDF and the pricing errors arise from the correlation of the errors in the statistical model with SDF. Secondly, the estimates of factor risk premia using portfolios are compared to those obtained using individual securities. It is shown that in the presence of pricing errors consistent estimation of risk premia requires a large number of not fully diversified portfolios. Also, in general, it is not possible to rank estimators using individual securities and portfolios in terms of their small sample bias.
    JEL Classifications: C38, G12
    Key Words: Arbitrage Pricing Theory, Stochastic Discount Factor, portfolios, factor strength, identification of risk premia, two-pass regressions, Fama-MacBeth.
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