Networks and the Dynamics of Firms' Export Portfolio: Evidence for Mexico

Abstract

In this paper we use network-analysis tools to identify communities in the web of exporters' destinations. Next we use our network-based community measure as predictor of additional countries chosen by firms expanding their export destination portfolio. We defend that our network-based community measure is superior to extended gravity measures. This superiority stems from the fact that community is a revealed measure, is country-specific and can be calculated at the industry level. Using data on Mexican new exporters over the period 2003-2009, we show that the probability of choosing a new export destination multiplies almost by three if it belongs to the same community of any of the firm's previous destinations. The introduction of the network-based community variable improves the accuracy of the model up to 20% relative to a model that only includes gravity and extended gravity variables. We also show that industry-specific communities and general communities play similar roles in determining the dynamics of Mexican exporters' country portfolio. JEL Code: F1

Previous experience, experimentation and export survival: Evidence from firm‐product‐destination level data

“…This paper is related to previous studies on trade duration at the product‐country level (Besedeš & Prusa, 2006a, 2006b), firm level (Kostevc & Zajc Kejzar, 2020), firm‐product level (Görg et al, 2012), firm‐country level (Esteve‐Pérez et al, 2013), firm‐product‐country level (Cadot et al, 2013) and to studies on the dynamics of firms’ export portfolio (Amador & Opromolla, 2013; De Lucio et al, 2016; Freund & Pierola, 2010). Yet, the previous papers on portfolio dynamics have focussed on switching patterns of export products and destinations without explicitly examining trade duration.…”

The Dynamic Evolution of Overseas Market Network of Chinese Enterprises: Agglomeration or Dispersion

“…On this basis, this article further extends the dimension to the perspective of "community" to test whether the evolution of corporate overseas market network connection has the characteristics of concentration within the community. is article draws on the identification strategies of Lucio [21] and Wei et al [18] and uses Chinese customs data at the beginning of the sample (2000) to identify and classify different countries in the export network.…”

“…After testing the benchmark model, this article further introduces the community relationship between overseas markets into the benchmark model and analyzes and discusses the influence of the community relationship on the dynamic evolution of the corporate overseas market network. Before estimating the econometric equation ( 7), this article draws on Lucio et al [21] and Wei et al [18], using Chinese customs data to identify and classify the social relationships of the export destinations of enterprises. In the end, this article divides the world's 196 economies into 45 communities.…”

“…Based on the benchmark model, this article draws on Lucio et al [21] and Wei et al [18] to divide the overseas tradelinked communities of corporate export networks and divides 196 economies around the world into 45 communities. It also examines the enterprise's decision making on the location of the export market within the community and outside the community.…”