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Importing, exporting and performance in sub-Saharan African manufacturing firms

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This paper examines productivity differences between internationally trading and non-trading firms using data on a sample of firms from 19 sub-Saharan African countries. The paper provides the first evidence of whether exporters, importers and two-way traders perform better than non-traders, and whether there are differences in performance between different types of trading firms in sub-Saharan Africa. Our results indicate that exporters, importers and two-way traders perform better than non-exporters, non-importers and non-two-way traders. We further find that two-way traders perform better than importers only or exporters only, results largely consistent with recent results for other countries and regions. Considering information on export starters, continuers and exiters we also present some evidence suggesting that there is no significant difference in performance between export continuers and starters.

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  1. In response to such empirical studies theoretical models such as that of Melitz (2003) were developed that provided a rationale for the observed positive relationship between export status and firm productivity, with firms in these models self-selecting into export markets due to sunk costs of exporting.

  2. Indeed, a large empirical literature at the country and industry level has examined the importance of knowledge spillovers through imports and found them to be economically significant both between developed countries, and also from developed to developing countries (for seminal studies see Coe and Helpman 1995; Coe et al. 1997).

  3. Much of this recent literature on importing and performance has concentrated on the firm-level effects of offshoring. In addition to allowing firms to acquire inputs at lower costs and to acquire inputs embodying a higher level of technology, offshoring of production gives firms the opportunity to allocate their resources to the activities where they are most productive, helping to increase specialisation and benefit from economies of scale. Despite such benefits there are also likely to be costs to the firm from offshoring. Such costs may include those related to differences in language, management culture and legal systems, as well as the search costs involved in finding partners in distant and foreign markets.

  4. Such costs may include search costs as firms seek potential foreign suppliers, as well as costs related to the inspection of goods, negotiation and contract formulation, as well as to acquisition and customs procedures.

  5. See Antras and Helpman (2004) who develop a model similar to Melitz (2003) in which it is assumed that there are fixed costs to importing, and which results in the self-selection of firms into importing.

  6. Recently—as data have become available—studies have begun to consider the trade-productivity relationship for services firms also (see Wagner 2012, Table 3) for a review of these studies and Foster-McGregor et al. (2012) for evidence in SSA).

  7. This dataset has been used elsewhere to consider different aspects of the relationship between firm performance and the way that a firm serves a foreign market. Foster et al (2013) for example use this dataset to examine whether SSA firms that serve foreign markets through FDI perform better than those serving foreign markets through exporting. Results are found to differ between manufacturing and services firms.

  8. A separate literature exists suggesting that foreign-owned firms perform better than domestically owned ones (see for example Harris 2002; Harris and Robinson 2003; Yasar and Morrison Paul 2007). Following existing studies we define a firm as foreign owned if more than 10 % of the equity of the firm is owned by non-residents.

  9. Defined as the ratio of technical, administrative and sales workers in total employment.

  10. For an introduction to quantile regression models see Buchinsky (1998) and Koenker and Hallock (2001).

  11. The data used in this paper are confidential, but not exclusive. In order to gain access to the data researchers will need to contact UNIDO and sign a confidentiality agreement. Once this agreement has been signed the authors would be happy to share the sample of data used in their analysis. The Stata programs used to estimate all of the results in the paper are also available from the authors on request.

  12. TFP is estimated by assuming a constant capital share of one-third. In particular, TFP is defined as: \( TFP = VA / (EMP^{2/3} FA^{1/3} ) \), where \( VA \) is value added, \( EMP \) refers to total employment and \( FA \) to total fixed assets.

  13. All monetary values are expressed in US dollars, using the average exchange rate over the previous 3 years (2009–2011).

  14. Defined as the ratio of net (pre-tax) profit to revenue (multiplied by 100).

  15. We also test for differences in the median of our performance measures across these groups using the Statal package ‘cendif’. The results are not reported for reasons of brevity, but are largely similar to those using the test of means.

  16. The premia are calculated from the estimated coefficients on the trade dummies as \( 100(e^{\beta } - 1) \), where \( \beta \) is the estimated coefficient.


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Correspondence to Neil Foster-McGregor.

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The views expressed herein are those of the author(s) and do not necessarily reflects the views of the United Nations Industrial Development Organization.



See Tables 11 and 12.

Table 11 Number of firms in sample by country
Table 12 Number of firms in sample by industry

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Foster-McGregor, N., Isaksson, A. & Kaulich, F. Importing, exporting and performance in sub-Saharan African manufacturing firms. Rev World Econ 150, 309–336 (2014).

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