We study the identification and estimation of panel dynamic simultaneous equations models. We show that the presence of time-persistent individual-specific effects does not lead to changes in the identification conditions of traditional Cowles Commission dynamic simultaneous equations models....

Though ordinary least square (OLS) estimates are super-consistent with cointegrated variables, their finite-T bias can be large in the presence of endogenous feedback. Fully modified OLS (FMOLS) are parsimonious tools to measure the cointegrating [long-run] slope between integrated variables in...

We study semi-parametric estimation and inference in cointegrated panels with endogenous feedback, allowing for general time-series and cross-section dependence and heterogeneity.Central to this literature are the fully-modified OLS of Phillips and Hansen (1990) that use a spectral...

In this paper, we study the asymptotic distributions for least-squares (OLS), fully modified (FM), and dynamic OLS (DOLS) estimators in cointegrated regression models in panel data. We show that the OLS, FM, and DOLS estimators are all asymptotically normally distributed. However, the asymptotic...

We study estimation and inference in panel data regression models when the regressors of interest are macro shocks, which speaks to a large empirical literature that targets impulse responses via local projections. Our results hold under general dynamics and are uniformly valid over the degree...

This is the first paper in a series of two that synthesizes, compares, and extends methods for causal inference with longitudinal panel data in a structural equation modeling (SEM) framework. Starting with a cross-lagged approach, this paper builds a general cross-lagged panel model (GCLM) with...

Lancaster (2002) proposes an estimator for the dynamic panel data model with homoskedastic errors and zero initial conditions. In this paper, we show this estimator is invariant to orthogonal transformations, but is inefficient because it ignores additional information available in the data. The...

This paper primarily reviews the panel stochastic frontier (SF) model in which the composite error term εit has four components, i.e. εit=τi−ηi+vit−uit, where ηi and uit are the persistent and transient inefficiency components, τi is the random firm effect and vit is the random noise....

The identification of information problems in different markets is challenging issue in the economic literature. In this paper, we study the identification of moral hazard from adverse selection and learning within the context of a multi-period dynamic model. We extend the model of Abbring et...