I derive the unconditional transformed likelihood function and its derivatives for a fixed-effects panel data model with time lags, spatial lags, and spatial time lags that encompasses the pure time dynamic and pure space dynamic models as special cases. In addition, the model can accommodate...

We propose a novel estimator for the dynamic panel model, which solves the failure of strict exogeneity by calculating the bias in the first-order conditions as a function of the autoregressive parameter and solving the resulting equation. We show that this estimator performs well as compared...

The system GMM estimator for dynamic panel data models combines moment conditions for the model in first differences with moment conditions for the model in levels. It has been shown to improve on the GMM estimator in the first differenced model in terms of bias and root mean squared error....

This paper develops an instrumental variable (IV) estimator for consistent estimation of dynamic panel data models with a multifactor error structure when both N and T, the cross-sectional and time series dimensions respectively, are large. Our approach projects out the common factors from...

This paper evaluates the first-differenced maximum likelihood (FDML) and the continuously updating system generalized method of moments (CU-GMM) estimators of dynamic panel models when the data is close to non-stationary. This case is far from trivial, as a high degree of persistence is the norm...

We explore inference on regression coefficients in semiparametric multinomial response models. We consider cross-sectional, and both static and dynamic panel settings where we focus throughout on inference under sufficient conditions for point identification. The approach to identification uses...

In this paper, we use Monte Carlo methods to study the small sample properties of the classical maximum likelihood (ML) estimator in artificial samples generated by the New-Keynesian open economy DSGE model estimated by Adolfson et al. (2008) with Bayesian techniques. While asymptotic...

In this paper, we study identification and misspecification problems in standard closed and open-economy empirical New-Keynesian DSGE models used in monetary policy analysis. We find that problems with model misspecification still appear to be a first-order issue in monetary DSGE models, and...