Using the stochastic frontier analysis (SFA) model, we estimate total-factor energy efficiency (TFEE) scores for 47 regions across Japan during 1996–2008. We extend the cross-sectional SFA model proposed by Zhou et al. (Applied Energy, 2012) to panel data models and add environmental...

This paper considers a quasi-maximum likelihood estimation for a linear panel data model with time and individual fixed effects, where the disturbances have dynamic and spatial correlations which might be spatially stable or unstable. We first consider both separable and nonseparable...

This paper investigates the quasi-maximum likelihood (QML) estimation of spatial panel data models where spatial weights matrices can be time varying. We show that QML estimate is consistent and asymptotically normal. We also derive the asymptotic distribution of average impact coefficients...

The objectives of this paper are to study the impact of liberalisation on trade deficits and current accounts of developing countries. It is expected that trade liberalisation would promote economic growth from the supply side by leading to a more efficient use of resources, by encouraging...

This work refers to analyses of matching processes on occupational labour markets in Germany. Up to now, all studies in this field are based on the crucial assumption of separate occupational labour markets. I outlined some theoretical considerations that occupational markets are probably not...

An autoregressive fixed effects panel data equation in error-ridden endogenous and exogenous variables, with finite memory of disturbances, latent regressors and measurement errors is considered. Finite sample properties of GMM estimators are explored by Monte Carlo (MC) simulations. Two kinds...

The Generalized Method of Moments (GMM) is discussed for handling the joint occurrence of fixed effects and random measurement errors in an autoregressive panel data model. Finite memory of disturbances, latent regressors and measurement errors is assumed. Two specializations of GMM are...

GMM estimation of autoregressive panel data equations in error-ridden variables when the noise has memory, is considered. The impact of variation in the memory length in signal and noise spread and in the degree of individual heterogeneity are discussed with respect to finite sample bias, using...

We study the relationship between conditional quantiles of returns and the long-, medium- and short-term volatility in a portfolio of financial assets. We argue that the combination of quantile panel regression and wavelet decomposition of the volatility time series provides us with new insights...

In panel experiments, we randomly assign units to different interventions, measuring their outcomes, and repeating the procedure in several periods. Using the potential outcomes framework, we define finite population dynamic causal effects that capture the relative effectiveness of alternative...