Regional determinants of firm entry in a developing country

Abstract

Abstract. We analyse the determinants of firm entry in developing countries using Argentina as an illustrative case. Our main finding is that although most of the regional determinants used in previous studies analysing developed countries are also relevant here, there is a need for additional explanatory variables that proxy for the specificities of developing economies (e.g., poverty, informal economy and idle capacity). We also find evidence of a core-periphery pattern in the spatial structure of entry that seems to be mostly driven by differences in agglomeration economies. Since regional policies aiming to attract new firms are largely based on evidence from developed countries, our results raise doubts about the usefulness of such policies when applied to developing economies. JEL classification: R12, R30, C33

Sectoral and regional determinants of firm dynamics in developing countries: Evidence for low-, medium- and high-tech manufacturing in Argentina

“…This means that after each crisis, a great number of firms enter the growing markets but many of them exit in the following years; consequently, the "revolving door" phenomenon may be more intense than is typically observed in developed countries. 6 In addition, after an economic crisis, existing firms that exploit their idle capacity may have greater aggregate effects on the satisfaction of demand for new goods than new firms (Calá, Manjón-Antolín and Arauzo-Carod, 2016).…”

“…Long-term unemployed individuals may not have the ability, financial resources and/or social capital needed to start a new business (Fritsch and Falck, 2007). However, changes in the conditions that determine profitability (exchange rate, tariffs, credit access or tax policy) and the lack of continuity in industrial policies may reduce the effect of past (dynamic) localization economies on current entry and exit (Calá, Manjón-Antolín and Arauzo-Carod, 2016).…”

“…Remarkably, studies on the regional and sectoral determinants of firm entry and exit are limited to developed countries, while much less research has focused on developing countries even though these countries are expected to become key players in the world economy, since it is widely assumed that they will noticeably increase their share of output over the next decades (Wilson and Purushothaman, 2006). More precisely, studies on developing countries either focus on industry (Lay, 2003;Wang, 2006;Günalp and Cilasun, 2006;Ozturk and Kilic, 2012) or on regional determinants (Naudé and others, 2008;Santarelli and Tran, 2012;Manjón-Antolín, 2015 and2016). Thus, this would appear to be the first attempt to quantify regional determinants of firm entry and exit in different manufacturing industries of a developing country.…”

Uncovering Norway’s regional disparities with respect to natural riches

“…In that sense we use per capita GDP as a tool to understand the trends in regional inequalities of economic activity, whereas the use of population density does not only reflect economic activity from a broad income accumulation viewpoint, but also digs into the roots of income generation tied to agglomeration economies as well as urbanization. While early evidence from Reynolds et al (1994) underlines the power of population density to represent the level of economic activity that stimulates firm formation, more recent evidence from Naude et al (2008) and Cala et al (2014) validates that population density can form agglomeration economies that clearly exemplify the high level of economic activity. Furthermore, early discussions of Carlino, Mills (1987) confirm that population and employment densities represent a true indicator of growth for the US case.…”

Regional determinants of the small and medium size manufacturing firm entry in a developing country: evidence from Turkey

“…An expansion in regional market demand for various goods and service are considered as one of the fundamental influences encouraging self-employment (Reynolds, 1994;Reynolds et al, 1994). Consumer demand is usually proxied by population, income and (un)employment measures and these variables are usually defined as levels or growth rates in econometric models (Calá et al, 2016). The composition of the labor force (in terms of age, gender, skills, education and etc.)…”