The stochastic frontier model used for continuous dependent variables is extended to accommodate output measured as a discrete ordinal outcome variable. Conditional on the inefficiency error, the assumptions of the ordered probit model are adopted for the log of output. Bayesian estimation utilizing a Gibbs sampler with data augmentation is applied to a convenient re-parameterisation of the mod...

Estimation of the dynamic error components model is considered using two alternative linear estimators that are designed to improve the properties of the standard firstdifferenced GMM estimator. Both estimators require restrictions on the initial conditions process. Asymptotic efficiency comparisons and Monte Carlo simulations for the simple AR(1) model demonstrate the dramatic improvement in p...

The consensus of the aid effectiveness literature is that foreign aid is effective at spurring economic growth in recipient countries. However, economic growth is heterogeneous in nature, driven by a number of different activities within an economy. This paper contributes to the literature by disaggregating the Gross Domestic Product of recipients in order to investigate the type of economic gr...

This paper argues that the Phillips curve–wage curve controversy cannot be settled within the conventional testing frameworks and suggests an alternative test, which builds on the model of Blanchard and Katz (1997). Using long macro data for the OECD countries, the evidence gives very strong support for the Phillips curve and indicates that wage behaviour is no different among the OECD countrie...

In panel stochastic frontier models, the Fixed Effects (FE) approach produces biased technical efficiency scores when time-invariant variables are important in the production process, and the Random Effects (RE) approach imposes distributional assumptions about the inefficiency. Moreover, technical efficiency scores obtained from these models are biased when the sample contains a large number o...

This paper discusses likelihood-based estimation of panel data models with individualspecific effects and both lagged dependent variable regressors and additional predetermined explanatory variables. The resulting new estimator, labeled as sub-system LIML (ssLIML), is asymptotically equivalent to standard panel GMM as N →∞ for fixed T , but tends to present smaller biases in finite samples as i...

This paper investigates the determinants of Spanish vertical intra-industry trade with a large sample of countries. We empirically test the comparative advantage explanation. To this aim, we build physical, human and technological capital stocks. On average, that is using OLS techniques, differences in endowments are a limitation for vertical intra-industry trade. Using quantile regressions tec...

Recent developments in nonlinear panel data analysis allow identifying and estimating general dynamic systems. In this review we describe some results and techniques for nonparametric identification and flexible estimation in the presence of time-invariant and time-varying latent variables. This opens the possibility to estimate nonlinear reduced forms in a large class of structural dynamic mod...

Multinational firms pay relatively high wages. Less is known about the wage structure within multinational and non-multinational firms. We examine the impact of acquisitions on wage dispersion in Sweden using a large matched employer-employee data set. Foreign acquisitions of Swedish firms increase wage dispersion by increasing wages for high-skilled workers. The positive impact is concentrated...

This paper considers the estimation of average autoregressive roots-near-unity in panels where the time-series have heterogenous local-to-unity parameters. The pooled estimator is shown to have a potentially severe bias and a robust median based procedure is proposed instead. This median estimator has a small asymptotic bias that can be eliminated almost completely by a bias correction procedur...