C2 - Single Equation Models; Single Variables
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Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects
Modeling and estimating persistent discrete data can be challenging. In this paper, we use an autoregressive panel probit model where the autocorrelation in the discrete variable is driven by the autocorrelation in the latent variable. In such a non-linear model, the autocorrelation in an unobserved variable results in an intractable likelihood containing high-dimensional integrals. -
Disentangling the Factors Driving Housing Resales
We use a recently developed model and loan-level microdata to decompose movements in housing resales since 2015. We find that fundamental factors, namely housing affordability and full-time employment, have had offsetting effects on resales over our study period.