A model for network panel data is discussed, based on the assumption that the observed data are discrete observations of a continuous-time Markov process on the space of all directed graphs on a given node set, in which changes in tie variables are independent conditional on the current graph. The model for tie changes is parametric and designed for applications to social network analysis, wher...

In this paper a pairwise comparison estimation procedure is proposed for the regression coefficients in a censored transformation model. The main advantage of the new estimator is that it can accommodate covariate dependent censoring without the requirement of smoothing parameters, trimming procedures, or stringent tail behavior restrictions. We also modify the pairwise estimator for other vari...

For small group sizes, the multilevel iterative generalised least squares (IGLS) estimator is biased and inconsistent where the random effects are correlated with the fixed predictors. Consistent estimates of the parameters of endogenous variables may be obtained using instrumental variables or conditioning on group level effects. In this paper we review various approaches to ensure consistency...

Credible Research Designs for Minimum Wage Studies We assess alternative research designs for minimum wage studies. States in the U.S. with larger minimum wage increases differ from others in business cycle severity, increased inequality and polarization, political economy, and regional distribution. The resulting timevarying heterogeneity biases the canonical two-way fixed effects estimator. W...

This paper presents an extension to the fixed-effect Logit for panel-data discrete-choice models, where the error component structure is multiplicative (individual effects multiplied by time effects). In linear models with such an error-component structure as investigated by Ahn, Lee and Schmidt (2001), usual fixed-effect estimators are generally inconsistent. We propose a conditional Logit est...

A model for network panel data is discussed, based on the assumption that the observed data are discrete observations of a continuoustime Markov process on the space of all directed graphs on a given node set, in which changes in tie variables are independent conditional on the current graph. The model for tie changes is parametric and designed for applications to social network analysis, where...

This paper employs recently developed techniques for testing hypotheses in cointegrated panels to test the strong version of purchasing power parity for a panel of post Bretton Woods data. We compare results using fully modiŽ ed and dynamic OLS approaches , and strongly reject the hypothesis . We also introduce a new between-dimensio n dynamic OLS estimator and Ž nd that the between-dimensio n ...

This paper uses panel data from African countries and a dynamic panel estimator to investigate the effects of corruption on economic growth and income distribution. I find that corruption decreases economic growthdirectly and indirectly through decreased investment in physical capital. A unit increase in corruption reduces the growth rates of GDP and per capita income by between 0.75 and 0.9 pe...

In this paper we consider the problem of estimating nonparametric panel data models with fixed effects. We introduce an iterative nonparametric kernel estimator. We also extend the estimation method to the case of a semiparametric partially linear fixed effects model. To determine whether a parametric, semiparametric or nonparametric model is appropriate, we propose test statistics to test betw...

Methods of remotely measuring burn severity are needed to evaluate the ecological and environmental impacts of large, remote wildland fires. The challenges that were associated with the Landsat program highlight the need to evaluate alternative sensors for characterising post-fire effects. We compared statistical correlations between 55 Composite Burn Index field plots and spectral indices from...