The objective of this paper is to analyze why firms in some industries locate in specialized economic environments (localization economies) while those in other industries prefer large city locations (urbanization economies). To this end, we examine the location decisions of new manufacturing firms in Spain at the city level and for narrowly defined industries (three-digit level). First, we estimate firm location models to obtain estimates that reflect the importance of localization and urbanization economies in each industry. In a second step, we regress these estimates on industry characteristics that are related to the potential importance of three agglomeration theories, namely, labor market pooling, input sharing and knowledge spillovers. Localization effects are low and urbanization effects are high in knowledge-intensive industries, suggesting that firms (partly) locate in large cities to reap the benefits of inter-industry knowledge spillovers. We also find that localization effects are high in industries that employ workers whose skills are more industry-specific, suggesting that industries (partly) locate in specialized economic environments to share a common pool of specialized workers.

Jofre-Monseny, J. (IEB); Marín-López, R. (IEB); Viladecans-Marsal, E. (IEB)

XREAP2012-08.pdf

The 51st ERSA Conference held in Barcelona in 2011 was one of the largest ever. Here, by examining the characteristics of the conference, this paper identifies the main trends in Regional Science at a moment in which the discipline is renewing its efforts to provide responses in a complex, globalised world in which cities and regions are acquiring greater and greater importance. This paper follows in the tradition of a long list of studies that have examined the nature of the field of Regional Science and draws on a broad array of sources of information: the delegates’ demographic details, the conference program itself, a satisfaction survey conducted among delegates, a quality survey addressed to those chairing the sessions and, finally, a bibliometric database including each author signing a paper presented at the conference. With this information we describe the ERSA delegates: their relative youthfulness; the areas in which women are taking on a more important role; the countries and regions of the world that have the most dominant profile in Regional Science today; the thematic areas that are being driven by professionals as opposed to academics; the relevance of regional economic growth and innovation as trending topics in the field; the growing frequency of co-authorship and, consequently, of scientific collaboration; and, finally, and perhaps most importantly, the continuous enhancement of the quality of the work being undertaken in the discipline. Indeed, following on from this description, the results of the regression analysis conducted show that for ERSA delegates what matters most is quality, and this must be the direction that future conferences should move toward. Ultimately, therefore, ERSA conferences are comprehensive, all-embracing occasions, representing an ideal opportunity for regional scientists to present their work to each other and to network.

Royuela, V. (AQR-IREA)

XREAP2012-12.pdf

The goal of this paper is twofold: first, we aim to assess the role played by inventors’ cross-regional mobility and networks of collaboration in fostering knowledge diffusion across regions and subsequent innovation. Second, we intend to evaluate the feasibility of using mobility and networks information to build cross-regional interaction matrices to be used within the spatial econometrics toolbox. To do so, we depart from a knowledge production function where regional innovation intensity is a function not only of the own regional innovation inputs but also external accessible R&D gained through interregional interactions. Differently from much of the previous literature, cross-section gravity models of mobility and networks are estimated to use the fitted values to build our ‘spatial’ weights matrices, which characterize the intensity of knowledge interactions across a panel of 269 regions covering most European countries over 6 years.

Miguelez, E. (AQR-IREA, XREAP); Moreno, R. (AQR-IREA, XREAP)

XREAP2012-14.pdf

Scarcities of environmental services are no longer merely a remote hypothesis. Consequently, analysis of their inequalities between nations becomes of paramount importance for the achievement of sustainability in terms either of international policy, or of Universalist ethical principles of equity. This paper aims, on the one hand, at revising methodological aspects of the inequality measurement of certain environmental data and, on the other, at extending the scarce empirical evidence relating to the international distribution of Ecological Footprint (EF), by using a longer EF time series. Most of the techniques currently important in the literature are revised and then tested on EF data with interesting results. We look in depth at Lorenz dominance analyses and consider the underlying properties of different inequality indices. Those indices which fit best with environmental inequality measurements are CV2 and GE(2) because of their neutrality property, however a trade-off may occur when subgroup decompositions are performed. A weighting factor decomposition method is proposed in order to isolate weighting factor changes in inequality growth rates. Finally, the only non-ambiguous way of decomposing inequality by source is the natural decomposition of CV2, which additionally allows the interpretation of marginal term contributions. Empirically, this paper contributes to the environmental inequality measurement of EF: this inequality has been quite stable and its change over time is due to per capita vector changes rather than population changes. Almost the entirety of the EF inequality is explainable by differences in the means between the countries of the World Bank group. This finding suggests that international environmental agreements should be attempted on a regional basis in an attempt to achieve greater consensus between the parties involved. Additionally, source decomposition warns of the dangers of confining CO2 emissions reduction to crop-based energies because of the implications for basic needs satisfaction.

Teixidó-Figueras, J. (GRIT, XREAP); Duro, J. A. (GRIT, XREAP)

XREAP2012-15.pdf

This article studies how product introduction decisions relate to profitability and uncertainty in the context of multi-product firms and product differentiation. These two features, common to many modern industries, have not received much attention in the literature as compared to the classical problem of firm entry, even if the determinants of firm and product entry are quite different. The theoretical predictions about the sign of the impact of uncertainty on product entry are not conclusive. Therefore, an econometric model relating firms’ product introduction decisions with profitability and profit uncertainty is proposed. Firm’s estimated profits are obtained from a structural model of product demand and supply, and uncertainty is proxied by profits’ variance. The empirical analysis is carried out using data on the Spanish car industry for the period 1990-2000. The results show a positive relationship between product introduction and profitability, and a negative one with respect to profit variability. Interestingly, the degree of uncertainty appears to be a driving force of entry stronger than profitability, suggesting that the product proliferation process in the Spanish car market may have been mainly a consequence of lower uncertainty rather than the result of having a more profitable market

Varela-Irimia, X-L. (GRIT, XREAP)

XREAP2012-16.pdf

Recently, White (2007) analysed the international inequalities in Ecological Footprints per capita (EF hereafter) based on a two-factor decomposition of an index from the Atkinson family (Atkinson (1970)). Specifically, this paper evaluated the separate role of environment intensity (EF/GDP) and average income as explanatory factors for these global inequalities. However, in addition to other comments on their appeal, this decomposition suffers from the serious limitation of the omission of the role exerted by probable factorial correlation (York et al. (2005)). This paper proposes, by way of an alternative, a decomposition of a conceptually similar index like Theil’s (Theil, 1967) which, in effect, permits clear decomposition in terms of the role of both factors plus an inter-factor correlation, in line with Duro and Padilla (2006). This decomposition might, in turn, be extended to group inequality components (Shorrocks, 1980), an analysis that cannot be conducted in the case of the Atkinson indices. The proposed methodology is implemented empirically with the aim of analysing the international inequalities in EF per capita for the 1980-2007 period and, amongst other results, we find that, indeed, the interactive component explains, to a significant extent, the apparent pattern of stability observed in overall international inequalities.

Duro, J. A. (GRIT, XREAP); Teixidó-Figueras, J. (GRIT, XREAP)

XREAP2012-17.pdf

In this paper we explore the sectoral and aggregate implications of some endogeneization rules (i.e. on value-added and final demand) which have been common in the Leontief model and have been recently proposed in the Ghosh model. We detect that these rules may give rise in both models to some allegedly pathological behavior in the sense that sectoral or aggregate output, very often, may not follow the logical and economically expected direct relationship with some underlying endogenous variables—namely, output and value-added in the Ghosh model and output and consumption in the Leontief model. Because of the common mathematical structure, whatever is or seems to be pathological in the Ghosh model also has a symmetric counterpart in the Leontief model. These would not be good news for the inner consistency of these linear models. To avoid such possible inconsistencies, we propose new and simple endogeneization rules that have a sound economic interpretation.

Manresa, A. (CREB); Sancho, F.

XREAP2012-18.pdf

A method to estimate an extreme quantile that requires no distributional assumptions is presented. The approach is based on transformed kernel estimation of the cumulative distribution function (cdf). The proposed method consists of a double transformation kernel estimation. We derive optimal bandwidth selection methods that have a direct expression for the smoothing parameter. The bandwidth can accommodate to the given quantile level. The procedure is useful for large data sets and improves quantile estimation compared to other methods in heavy tailed distributions. Implementation is straightforward and R programs are available.

Alemany, R. (RFA-IREA); Bolancé, C. (RFA-IREA); Guillén, M. (RFA-IREA)

XREAP2012-19.pdf