Elsevier

Journal of Urban Economics

Volume 66, Issue 3, November 2009, Pages 186-195
Journal of Urban Economics

Agglomeration and the export decisions of French firms

https://doi.org/10.1016/j.jue.2009.07.002Get rights and content

Abstract

This paper asks whether export spillovers influence the export behavior of French manufacturers. I use a database containing export flows by firm and importing country between 1986 and 1992. The decision to start exporting to a particular country is estimated using a logit model, controlling for the specific characteristics of firms, locations, countries and years. The export spillovers identified are industry- and/or destination-specific, and are computed at a very disaggregated geographical level. The results indicate that the pool of local exporters positively affects the decision to start exporting to a country. These effects are clearly destination-specific, and are larger for firms that export to remote markets.

Introduction

Increasing exports by domestic firms often appears to be one of the priorities of policy makers, in both developed and developing countries. For instance, in December 2004, the French Foreign Trade minister argued that “Exports are a national cause for which the government is mobilized”. He then announced a set of measures to be taken by the government in order to “consolidate the international presence of firms already exporting, and broaden the number of exporters (⋯)”.

From the economic point of view, such interventions are justified in the case of market failures. One potentially important failure in the case of exports is positive export-agglomeration economies, or export spillovers: proximity to other exporters can benefit local firms and help them to start exporting to a given market. While the effect of exporters on neighboring firms’ export performance is called export spillovers in the literature, the relationship captured in empirical work (including in the present paper) comprises more than just informal information-sharing between local firms.1 Duranton and Puga (2004) distinguish sharing, matching and learning mechanisms in the microeconomic foundations of agglomeration economies. Proximity to other exporters can indirectly affect a firm’s export behavior through the same mechanisms, via cost-sharing (transaction costs, and the cost of gathering information on export markets), or informal information transfers which lower the variable or fixed costs of exports.

Rosenthal and Strange (2004) distinguish the literature on the presence and scope of agglomeration economies from work specifically aimed at characterizing the source of urban increasing returns. The current paper appears in the first category: using individual export panel data by destination country and detailed data on the location of exporters, I evaluate the extent of export-agglomeration economies in French data.

Export spillovers have been analyzed in a number of recent papers. Aitken et al. (1997) find the probability that Mexican plants export in 1986 and 1989 to be positively linked to the presence of multinational firms in the same State, but uncorrelated with proximity to exporters in general. Greenaway et al. (2004) show that the presence of multinational firms in the UK positively influences the export decisions of domestic firms over the 1993–1996 period. Lovely et al. (2005) assume that exporting requires specialized knowledge of foreign markets, and that this type of information is more difficult to obtain when markets are less accessible. The degree of spatial concentration of exporters’ headquarters is compared to that of non-exporters in the US in 2000. Export destinations are classified by the difficulty of the trading environment (in particular, the instability of the political climate). The results show that the geographic concentration of exporter headquarter activity relative to the domestic sector increases with the share of an industry’s exports destined for countries with difficult trading environments. However, Barrios et al. (2003) find no evidence that Spanish firms between 1990 and 1998 benefitted from either the export activity of other firms or the activity of multinationals. Equally, Bernard and Jensen (2004) find no role for export-agglomeration economies in a panel of US manufacturing firms, either from local exporters or from export activity by other firms in the same industry.

While the evidence thus appears mixed, the empirical literature has almost uniquely looked at export spillovers across all destinations: the underlying assumption is that the presence of other exporters affects the cost of exporting, and thus the export decision, for all destination countries. In this context, one natural question regarding export spillovers is: what if export spillovers are in fact destination-specific? It appears reasonable to imagine that the relevant information that allows a firm to start exporting somewhere be destination-specific. When looking for foreign markets in which to sell its product, a manufacturer will want to learn about consumer preferences and the structure of distribution markets abroad, both of which are destination-specific. Any cost-sharing effect related to exporter agglomeration is also likely to refer specifically to one importing country.

In this paper, I investigate the presence of export spillovers, allowing these effects to be general, industry-specific, or industry- and destination-specific. I use a database provided by the French Customs, containing individual export flows by French manufacturers and destination countries between 1986 and 1992. The Customs data are matched to firm-level information, such as the address of the firm, sales, value-added and the number of employees. I estimate a discrete-choice model of the probability that a firm start to export to a country. Issues relating to the identification of agglomeration economies, such as omitted variables and endogeneity, are addressed by the use of firm–country fixed effects and the inclusion of an appropriate country demand variable. I identify potential export spillovers via time variation in the right-hand side local spillovers variable, measured as the number of other exporters located in the same area as the firm in question. Agglomeration is likely to have both positive and negative effects on export behavior, which latter come from increasing congestion in export infrastructure or greater competition regarding the exported good. Our estimations will thus capture the net effect of all of these impacts of exporter agglomeration on export behavior.

The paper is structured as follows. In Section 2, I describe the theoretical foundations of the logit model of the decision to start exporting. Section 3 describes the data sources and the variables that will be used in the estimations. I also emphasize a number of important aspects of the database, including the number of firms that start to export by country. In Section 4, I set out the identification strategy, and describe the results of the logit estimations, explaining how the preferred specification is determined. Last, Section 5 concludes.

Section snippets

The empirical model

Consider a firm i facing the decision whether to export to country j. If it does decide to export, the firm will make an annual profit of Πij. However, if the firm has not exported to j before, it incurs a sunk cost of fj to cover the cost of entering the market. Amongst firms that are observed to export to a given country in a given year, we will thus have both firms that are continuing exporters and firms which have just started to export to j; these correspond to firms that have already paid

Data

I now describe the three main data sources and explain how the variables are constructed. I then illustrate some salient features of exporters and markets, in particular the number of firms that start to export per destination country.

Firm-level estimation

I first discuss the main estimation issues regarding export spillovers, and then present the results.

Conclusions

This paper builds on existing empirical literature that has analyzed the broad question of export spillovers. I investigate the impact of proximity to other exporters on the export behavior of individual French manufacturers. This paper differs from the previous literature in two respects. First, export spillovers are identified via time variation within firm–country pairs, controlling for omitted variables and endogeneity, and spillovers are considered as either general, industry-specific, or

Acknowledgments

I thank Andrew Clark, Keith Head, Francis Kramarz, Megan MacGarvie, Jacques Melitz, and two anonymous referees for very helpful comments and suggestions. I also thank Philippe Lagarde for helping me to access the data. This paper was written while I was at CREST.

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