This article investigates the main sources of heterogeneity in regional efficiency. We estimate a translog stochastic frontier production function in the analysis of Spanish regions in the period 1964-1996, to attempt to measure and explain changes in technical efficiency. Our results confirm...

We analyze recent contributions to growth theory based on the model of expanding variety of Romer (1990). In the first part, we present different versions of the benchmark linear model with imperfect competition. These include the “labequipment” model, labor-for-intermediates” and...

This paper investigates the impact of regional sectoral diversity on regional employment growth in Italy over the period 1991-2001. Assuming that externalities may be stronger between industries selling similar products or sharing the same skills and technology (i.e. related industries), we...

This paper makes an attempt to estimate the impact of regional variety and trade linkages on regional economic growth by means of export and import data by Italian province (NUTS 3) and sector (3-digit) for the period 1995-2003. Our results show strong evidence of related variety contributing to...

This paper analyzes the effects of the evolution of knowledge base in the manufacturing sectors on regional productivity growth. Knowledge is viewed as a heterogeneous asset, and an evolutionary perspective is adopted. The results of the empirical estimations corroborate the hypothesis that...

In this paper we contribute to the longstanding discussion on the role of knowledge to economic growth in a spatial context. We observe that in adopting the European policy strategy towards a competitive knowledge economy, The Netherlands is – as most European countries - mainly oriented...

Let a class $\F$ of densities be given. We draw an i.i.d.\ sample from a density $f$ which may or may not be in $\F$. After every $n$, one must make a guess whether $f \in \F$ or not. A class is almost surely testable if there exists such a testing sequence such that for any $f$, we make...

For the standard kernel density estimate, it is known that one can tune the bandwidth such that the expected L1 error is within a constant factor of the optimal L1 error (obtained when one is allowed to choose the bandwidth with knowledge of the density). In this paper, we pose the same problem...

We continue the development of a method for the selection of a bandwidth or a number of design parameters in density estimation. We provide explicit non-asymptotic density-free inequalities that relate the $L_1$ error of the selected estimate with that of the best possible estimate, and study in...