Business environment, economic agglomeration and job creation around the world

ABSTRACT

This article looks at how economic agglomeration and the business environment affect job creation. The results suggest that economic agglomeration is strongly linked to job growth. Modern telecommunications, access to export markets, concentration of economic activity in large cities and capacity agglomeration, in particular, are important. In contrast, many areas of the business environment, including corruption, macroeconomic stability and infrastructure are not robustly linked to job growth. The main exception to this is that areas of the business environment directly related to labour markets are more consistently linked to job growth than other areas of the business environment.

KEYWORDS:

• Job creation
• business environment
• agglomeration
• firms

JEL CLASSIFICATION:

• J20
• J50
• L50
• O10

Acknowledgement

We are grateful to comments and discussions of Martin Rama.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 See World Bank (2012b) for comprehensive surveys on job creation.

2 Policy can affect agglomeration in several ways. For example, governments can offer location-based subsidies to shift regional agglomeration (Kline and Moretti 2013). We discuss this in more detail in Conclusions section.

3 For example, it takes about 5 days and costs about $456 to transport a standard export container to port and fulfil all customs, administrative and port requirements in Singapore. In comparison, it takes about 71 days and costs about $8450 to do the same in Tajikistan (World Bank 2012a).

4 This might not be as true in developed countries, where small, specialized firms can achieve their technological and innovation potential. In developing countries, where innovation mostly occurs in large firms and where external specialized research institutes and universities cannot be relied on, this is less likely to be the case.

5 See http:\\www.enterprisesurveys.org for a more complete description of the data.

6 In most cases, the initial sample frame is based on lists from government agencies. The quality and coverage of these lists, however, can vary significantly. As a result, they are often supplemented with other information. In Kenya, for example, lists from Kenya National Bureau of Statistics, the Kenya Association of Manufacturers, the Kenya National Chamber of Commerce, the Kenya Private Sector Alliance and from the Federation of Kenya Employers were combined (World Bank 2007a). Moreover, in some countries including Botswana, no lists were available. The sample frame was, therefore, constructed through block enumeration (World Bank 2006).

7 These are Africa, East Asia and Pacific, Europe and Central Asia, Mideast and North Africa, and South Asia.

8 The size dummies are for firms with between 10 and 20 employees, 21 to 60 employees and more than 60 employees.

9 See Aterido et al. (2011); Dollar, Hallward-Driemeier, and Mengistae (2005); Fisman and Svensson (2007); Harrison, Lin, and Xu (2014) and Svensson (2003).

10 Only about 16% of firms are large (i.e. have more than 100 workers) and only about 10% are foreign-owned.

11 This could be because retail firms are more affected by crime. Retail firms sell goods that can be easily resold and are probably more affected by theft by customers than manufacturing firms.

12 Dropping all observations with imputed values simultaneously results in all observations being dropped. This is because the unionization variable is available for only a small number of countries. The results are, however, similar for most agglomeration and business environment variables if we drop the unionization variable while only using true variables for the other variables. The main difference is that different investment climate variables become statistically significant (control of corruption, power outages and overdrafts), while others become statistically insignificant (crime and skilled workers). Results are available from the authors on request.