We study identification in a binary choice panel data model with a single predetermined binary covariate (i.e., a … parameter θ, whereas the distribution of unit-specific heterogeneity, as well as the feedback process that maps lagged … numerically, suggesting that meaningful learning about θ may be possible even in short panels with feedback. As a …

We study identification in a binary choice panel data model with a single predetermined binary covariate (i.e., a … parameter θ, whereas the distribution of unit-specific heterogeneity, as well as the feedback process that maps lagged outcomes … learning about θ is possible even in short panels with feedback. …

Many panel data methods, while allowing for general dependence between covariates and time-invariant agent …-specific heterogeneity, place strong a priori restrictions on feedback: how past outcomes, covariates, and heterogeneity map into future … covariate levels. Ruling out feedback entirely, as often occurs in practice, is unattractive in many dynamic economic settings …

This paper studies identification in a binary choice panel data model with choice probabilities depending on a lagged …

We develop a simulated ML method for short-panel estimation of one or more dynamic linear equations, where the …

In this paper we study the least sqares (LS) estimator in a linear panel regression model with interactive fixed …

In this paper we study the least squares (LS) estimator in a linear panel regression model with unknown number of …

a vector ARMA model for panel data, with dependent variables observed ordinally and find that current perceptions …

heterogeneity or unobserved state variables and panel data models with fixed effects. Recent developments in measurement error …

effects panel data analyses, the joint distribution of observed and unobserved agent-level characteristics is left …