Firm Size and Geographical Aggregation: An Empirical Appraisal in Industrial Location

This paper assesses empirically the importance of size discrimination and disaggregate data for deciding where to locate a start-up concern. We compare three econometric specifications using Catalan data: a multinomial logit with 4 and 41 alternatives (provinces and comarques, respectively) in which firm size is the main covariate; a conditional logit with 4 and 41 alternatives including attributes of the sites as well as size-site interactions; and a Poisson model on the comarques and the full spatial choice set (942 municipalities) with site-specific variables. Our results suggest that if these two issues are ignored, conclusions may be misleading. We provide evidence that large and small firms behave differently and conclude that Catalan firms tend to choose between comarques rather than between municipalities. Moreover, labour-intensive firms seem more likely to be located in the city of Barcelona. Keywords: Catalonia, industrial location, multinomial response model. JEL: C250, E30, R00, R12

Industrial location at a local level: some comments about the territorial level of the analysis

This paper contributes to the existing literature on industrial location by discussing some issues regarding the territorial levels that have been used in location analysis. We analyse which could be the advantages and disadvantages of performing locational analysis at a different local levels. We use data for new manufacturing firms located at municipality, county and travel to work areas level. We show that location determinants vary according to the territorial level used in the analysis, so we conclude that the level at which we perform the investigation should be carefully selected. Keywords: industrial location, cities, agglomeration economies, count data models.

Empirical studies in industrial location: an assessment of their methods and results

This paper surveys recent evidence on the determinants of (national and/or foreign) industrial location. We find that the basic analytical framework has remained essentially unaltered since the early contributions of the early 1980's while, in contrast, there have been significant advances in the quality of the data and, to a lesser extent, the econometric modelling. We also identify certain determinants (neoclassical and institutional factors) that tend to provide largely consistent results across the reviewed studies. In light of this evidence, we finally suggest future lines of research.

(Optimal) Spatial Aggregation in the Determinants of Industrial Location

Empirical studies on the determinants of industrial location typically use variables measured at the available administrative level (municipalities, counties, etc.). However, this amounts to assuming that the effects these determinants may have on the location process do not extent beyond the geographical limits of the selected site. We address the validity of this assumption by comparing results from standard count data models with those obtained by calculating the geographical scope of the spatially varying explanatory variables using a wide range of distances and alternative spatial autocorrelation measures. Our results reject the usual practice of using administrative records as covariates without making some kind of spatial correction. Keywords: industrial location, count data models, spatial statistics JEL classification: C25, C52, R11, R30

Industrial Location and Space: New Insights

This paper tries to resolve some of the main shortcomings in the empirical literature of location decisions for new plants, i.e. spatial effects and overdispersion. Spatial effects are omnipresent, being a source of overdispersion in the data as well as a factor shaping the functional relationship between the variables that explain a firm’s location decisions. Using Count Data models, empirical researchers have dealt with overdispersion and excess zeros by developments of the Poisson regression model. This study aims to take this a step further, by adopting Bayesian methods and models in order to tackle the excess of zeros, spatial and non-spatial overdispersion and spatial dependence simultaneously. Data for Catalonia is used and location determinants are analysed to that end. The results show that spatial effects are determinant. Additionally, overdispersion is descomposed into an unstructured iid effect and a spatially structured effect. Keywords: Bayesian Analysis, Spatial Models, Firm Location. JEL Classification: C11, C21, R30.

The Geographical Scope of Industrial Location Determinants: An Alternative Approach

This paper considers the estimation of the geographical scope of industrial location determinants. While previous studies impose strong assumptions on the weighting scheme of the spatial neighbour matrix, we propose a exible parametrisation that allows for di fferent (distance-based) de finitions of neighbourhood and di fferent weights to the neighbours. In particular, we estimate how far can reach indirect marginal e ffects and discuss how to report them. We also show that the use of smooth transition functions provides tools for policy analysis that are not available in the traditional threshold modelling. Keywords: count data models, industrial location, smooth transition functions, threshold models. JEL-Codes: C25, C52, R11, R30.

The determinants of industrial location in Spain, 1856-1929

Durant el segle XIX, l'economia espanyola va transitar per les primeres etapes de la industrialització. Aquest procés es va donar en paral·lel a la integració del mercat domèstic de béns i factors, en un moment en què les reformes liberals i la construcció de la xarxa ferroviària, entre d'altres, van generar una important caiguda en els costos detransport. Al mateix temps que es donava aquesta progressiva integració del mercat domèstic espanyol, es van produir canvis significatius en la pauta de localització industrial. D'una banda, hi hagué un augment considerable de la concentració espacial de la indústria des de mitjans de segle XIX i fins a la Guerra Civil, i d¿altra, un increment de l'especialització regional. Ara bé, quines van ser les forces que van generar aquests canvis? Des d¿un punt de vista teòric, el model de Heckscher-Ohlin suggereix que la distribució a l'espai de l¿activitat econòmica ve determinada per l'avantatge comparativa dels territoris en funció de la dotació relativa de factors. Al seu torn, els models de Nova Geografia Econòmica (NEG) mostren l'existència d'una relació en forma de campana entre el procés d'integració econòmica i el grau de concentració geogràfica de l'activitat industrial. Aquest article examina empíricament els determinants de la localització industrial a Espanya entre 1856 i 1929, mitjançant l'estimació d¿un model que combina els elements de tipus Heckscher-Ohlin i els factors apuntats des de la NEG, amb l'objectiu de contrastar la força relativa dels arguments vinculats a aquestes dues interpretacions a l'hora de modular la localització de la indústria a Espanya. L'anàlisi dels resultats obtinguts mostra que tant la dotació de factors com els mecanismes de tipus NEG van ser elements determinants que expliquen la distribució geogràfica de la indústria des del segle XIX, tot i que la seva força relativa va anar variant amb el temps.

The determinants of industrial location in Spain, 1856-1929

Durant el segle XIX, l'economia espanyola va transitar per les primeres etapes de la industrialització. Aquest procés es va donar en paral·lel a la integració del mercat domèstic de béns i factors, en un moment en què les reformes liberals i la construcció de la xarxa ferroviària, entre d'altres, van generar una important caiguda en els costos detransport. Al mateix temps que es donava aquesta progressiva integració del mercat domèstic espanyol, es van produir canvis significatius en la pauta de localització industrial. D'una banda, hi hagué un augment considerable de la concentració espacial de la indústria des de mitjans de segle XIX i fins a la Guerra Civil, i d¿altra, un increment de l'especialització regional. Ara bé, quines van ser les forces que van generar aquests canvis? Des d¿un punt de vista teòric, el model de Heckscher-Ohlin suggereix que la distribució a l'espai de l¿activitat econòmica ve determinada per l'avantatge comparativa dels territoris en funció de la dotació relativa de factors. Al seu torn, els models de Nova Geografia Econòmica (NEG) mostren l'existència d'una relació en forma de campana entre el procés d'integració econòmica i el grau de concentració geogràfica de l'activitat industrial. Aquest article examina empíricament els determinants de la localització industrial a Espanya entre 1856 i 1929, mitjançant l'estimació d¿un model que combina els elements de tipus Heckscher-Ohlin i els factors apuntats des de la NEG, amb l'objectiu de contrastar la força relativa dels arguments vinculats a aquestes dues interpretacions a l'hora de modular la localització de la indústria a Espanya. L'anàlisi dels resultats obtinguts mostra que tant la dotació de factors com els mecanismes de tipus NEG van ser elements determinants que expliquen la distribució geogràfica de la indústria des del segle XIX, tot i que la seva força relativa va anar variant amb el temps.

Geoadditive models for regional count data: an application to industrial location

We propose a geoadditive negative binomial model (Geo-NB-GAM) for regional count data that allows us to address simultaneously some important methodological issues, such as spatial clustering, nonlinearities, and overdispersion. This model is applied to the study of location determinants of inward greenfield investments that occurred during 2003–2007 in 249 European regions. After presenting the data set and showing the presence of overdispersion and spatial clustering, we review the theoretical framework that motivates the choice of the location determinants included in the empirical model, and we highlight some reasons why the relationship between some of the covariates and the dependent variable might be nonlinear. The subsequent section first describes the solutions proposed by previous literature to tackle spatial clustering, nonlinearities, and overdispersion, and then presents the Geo-NB-GAM. The empirical analysis shows the good performance of Geo-NB-GAM. Notably, the inclusion of a geoadditive component (a smooth spatial trend surface) permits us to control for spatial unobserved heterogeneity that induces spatial clustering. Allowing for nonlinearities reveals, in keeping with theoretical predictions, that the positive effect of agglomeration economies fades as the density of economic activities reaches some threshold value. However, no matter how dense the economic activity becomes, our results suggest that congestion costs never overcome positive agglomeration externalities.

Industrial location and sectoral linkages: the case of the Brazilian automotive industry

The aim of this article is to analyse the spatial distribution of the automotive industry in Brazil in terms of its various economic categories between 1995 and 2011, and to shed light on its sectoral linkages through inter-regional input-output matrices. By calculating the coefficient of localization (QLij) for that period, it was found that the third wave of investments, which began in the second half of the 1990s, actually caused a slight spatial deconcentration of this sector in the national economy. The coefficient of geographic association (CAik)calculated for different years revealed a slight reduction, while maintaining a high level of concentration, which suggests that vehicle production is closely integrated with other economic activities. This integration was corroborated particularly in terms of input purchases (backward linkages) in all of the analysed regions.

Regional Integration and Industrial Location in a Landlocked Spatial Economy

Regional integration proposals often require agreements between countries that differ in geographic size, resource endowments, transportation assets, technologies, and product quality. In this asymmetric setting, questions arise about the potential for mutual gains and the distribution of benefits among industries and workers in each country. This paper examines how regional integration between a small landlocked country and a large neighboring country--with a unique port facility that both nations must use to export goods--affects the wage and location decisions of firms, the allocation of labor, the welfare of each country's workers and firms, and aggregate measures of economic welfare in each country and the region. A simulated spatial labor market model is used to explore the economic effects of various stages of regional integration. Beginning with autarky as a benchmark case, we consider two forms of regional integration: partial mobility (mobile labor with geographically restricted firms); and full mobility (mobile labor and firms) with convergence of production technologies and product quality.

Chapter 3 Industrial Location in Cambodia: Industrial Policies and Economic Statistics

Cambodia has experienced high economic growth in the last decade. Because most of its industries were destroyed during the Pol Pot regime and civil war, in the last 20 years the country has been working hard to liberalize its economy to attract foreign investors With its efforts to join the regional and international community and with changes in the international trade environment, Cambodia started to grow its economy in the late 1990s. Now, in the early 21st century, the Cambodian economy seems to be prepared to take off. We can observe a kind of industrial agglomeration occurring, even though still at a small scale. In this paper, first, I will review the history of Cambodia’s economic development since the late 1980s. Second, I will examine the economic policies, laws, rules, and other environmental factors which have influenced industrial development and industrial location in Cambodia. Third, I will introduce industrial location in the late 2000s. Lastly, I will introduce some statistical data for the future analysis of industrial location in Cambodia.

Chapter 6 Economic integration and changes in industrial location in Vietnam

Vietnam has been praised for its achievements in economic growth and success in poverty reduction over the last two decades. The incidence of poverty reportedly fell from 58.1% in 1993 to 19.5% in 2004 (VASS [2006, 13]). The country is also considered to have only a moderate level of aggregate economic inequality by international comparisons. As of the early 2000s, Vietnam’s consumption-based Gini coefficient is found to be comparable to that of other countries with similar levels of per capita GDP. The Gini index did increase between 1993 and 2004, but rather slowly, from 0.34 to 0.37 (VASS [2006, 13]). Yet, as the country moves on with its market oriented reforms, the question of inequality has been highlighted in policy and academic discourses. In particular, it is pointed out that socio-economic inequalities between regions (or provinces) are significant and have been widening behind aggregate figures (NCSSH [2001], Mekong Economics [2005], VASS [2006]). Between 1993 and 2004, while real per capita expenditure increased in all regions, it grew fastest in those regions with the highest per capita expenditures and vice versa, resulting in greater regional disparities (VASS [2006, 37]). A major contributing factor to such regional inequalities is the uneven distribution of industry within the country. According to the Statistical Yearbook of Vietnam, of the country's gross industrial output in 2007, over 50% belongs to the South East region, close to 25% to the Red River Delta, and about 10% to the Mekong River Delta. All remaining regions share some 10% of the country's gross industrial output. At a quick glance, the South East increased its share of the total industrial gross output in the 1990s, while the Red River Delta started to gain ground in more recent years. How can the government deal with regional disparities is a valid question. In order to offer an answer, it is necessary in the first place to grasp the trend of disparities as well as its background. To that end, this paper is a preparatory endeavor. Regional disparities in industrial activities can essentially be seen as a result of the location decisions of enterprises. While the General Statistics Office (GSO) of Vietnam has conducted one enterprise census (followed by annual enterprise surveys) and two stages of establishment censuses since 2000, sectorally and geographically disaggregated data are not readily available. Therefore, for the moment, we will draw on earlier studies of industrial location and the determinants of enterprises’ location decisions in Vietnam. The remainder of this paper is structured as follows. The following two sections deal with the country context. Section 2 will outline some major developments in Vietnam’s international economic relations that may affect sub-national location of industry. According to the theory of spatial economics, economic integration is seen as a major driver of changes in industrial location, both between and within countries (Nishikimi [2008]). Section 3, on the other hand, will consider some possible factors affecting geographic distribution of industry in the domestic sphere. In Section 4, existing literature on industrial and firm location will be examined, and Section 5 will briefly summarize the findings and suggest some areas for future research.