Theoretical models of growth and trade suggest that patterns of international specialization are dynamic and evolve endogenously over time. Initial comparative advantages are either reinforced or gradually unwound with the passage of time. This paper puts forward an empirical framework for...

Specific functional forms are often used in economic models of distributions; goodness-of-fit measures are used to assess whether a functional form is appropriate in the light of real-world data. Standard approaches use a distance criterion based on the EDF, an aggregation of differences in...

We examine whether the information contained in social media (Twitter & Facebook) and web search queries (Google) influences financial markets. Using a multivariate system and focussing on Eurozone’s peripheral countries, the GIIPS (Greece, Ireland, Italy, Portugal and Spain), we show that...

Benford's Law is used to test for data irregularities. While novel, there are two weaknesses in the current methodology. First, test values used in practice are too conservative and the test values of this paper are more powerful and hold for fairly small samples. Second, testing requires...

Averaging methods are routinely used in order to limit biases resulting from the mismeasurement of permanent incomes. The Solon/Zimmerman estimator regresses a single-year measurement of the child's resources on a T-period average of the parents' income while the Behrman/Taubman estimator...

The techniques of simple random sampling are seldom appropriate in the empirical analysis of income distributions. Various types of weighting schemes are usually required either from the point of view of welfare-economic considerations (the mapping of household/family distributions into...

We introduce an alternative version of the Fama-French three-factor model of stock returns together with a new estimation methodology. We assume that the factor betas in the model are smooth nonlinear functions of observed security characteristics. We develop an estimation procedure that...

We propose an easy to use derivative based two-step estimation procedure for semi-parametric index models. In the first step various functionals involving the derivatives of the unknown function are estimated using nonparametric kernel estimators. The functionals used provide moment conditions...

Efficient semiparametric and parametric estimates are developed for a spatial autoregressive model, containing nonstochastic explanatory variables and innovations suspected to be non-normal. The main stress is on the case of distribution of unknown, nonparametric, form, where series...