This study used panel data models with spatial error correlation to analyze private tree planting in the US South from 1955 to 2003. Controlling for statewide, fixed effects allows us to disentangle the effect of spatial interaction from that of state heterogeneity and omitted variables. The results show that there is significant spatial interdependence among the southern states in private tree...

The commitment to public health insurance for children has increased in recent years, leading to two potentially contradictory concerns for public policy: that expanded availability of public insurance may lead families to decline private insurance for their children and that the additional public coverage may not reach many children without insurance. We use data from the 1987-1993 Surveys of ...

Research and development-based growth models aim to explain the role of technological progress in the growth process. The role of knowledge production and intertemporal spillover effects are investigated using a panel data set covering 49 US states over the period 1994-2004. The aim is to estimate knowledge flows in the context of a space-time dynamic suggested by the knowledge production funct...

We consider consistent estimation of partially linear panel data models with fixed effects. We propose profile-likelihood-based estimators for both the parametric and nonparametric components in the models and establish convergence rates and asymptotic normality for both estimators.

A panel data regression model with heteroskedastic as well as spatially correlated disturbancesis considered, and a joint LM test for homoskedasticity and no spatial correlation is derived. In addition, a conditional LM test for no spatial correlation given heteroskedasticity, as well as a conditional LM test for homoskedasticity given spatial correlation, are also derived. These LM tests are c...

We demonstrate that fixedand random-effects models for pooled cross-sectional and time series data, and latent growth curve models for panel data are special cases of a more general model. We compare the estimates obtained from each type of model for a data set consisting of homicide rates and a vector of explanatory variables for 400 US counties over a 15-year period. Most, but not all, estima...

This paper establishes asymptotic properties of quasi-maximum likelihood estimators for SAR panel data models with fixed effects and SAR disturbances. A direct approach is to estimate all the parameters including the fixed effects. Because of the incidental parameter problem, some parameter estimatorsmay be inconsistent or their distributions are not properly centered. We propose an alternative...

The conventional heteroskedasticity-robust (HR) variance matrix estimator for cross-sectional regression (with or without a degrees-of-freedom adjustment), applied to the fixed-effects estimator for panel data with serially uncorrelated errors, is inconsistent if the number of time periods T is fixed (and greater than 2) as the number of entities n increases. We provide a bias-adjusted HR estim...

Recent years have seen countries introducing reform of their utility industries with a view to promoting private ownership and competition. This paper studies the effect of the sequencing of privatisation, competition and regulation reforms in electricity generation using data from 25 developing countries for the period 1985 to 2001. A fixed effects panel data model is used. The study finds tha...

This paper introduces a dynamic panel data model in which the intercepts and the coefficients on the lagged endogenous variables are specific to the cross section units, while the coefficients on the exogenous variables are assumed to be normally distributed across the cross section. Thus the model includes mixture of fixed coefficients and random coefficients, which I call the “MFR” model. The...