Can Africa Be a Manufacturing Destination? Labor Costs in Comparative Perspective Alan Gelb, Christian J. Meyer, Vijaya Ramachandran, and Divyanshi Wadhwa Abstract Our central question is whether African countries can break into global manufacturing in a substantial way. Using a newly-constructed panel of firm-level data from the World Bank’s Enterprise Surveys, we look at labor costs in a range of low and middle income countries in Africa and elsewhere. Using fixed effects and random effects models, we estimate a set of labor costs, both actual and hypothetical—what would labor costs for Sub-Saharan African firms look like if they were located outside of Africa? What would Bangladesh’s labor costs be if it was located on the African continent? Our results suggest that for any given level of GDP, labor is more costly for firms that are located in Sub-Saharan Africa. However, we also find that there are a few countries in Africa that, on a labor cost basis, may be potential candidates for manufacturing—Ethiopia in particular stands out. We conclude with thoughts on the future of manufacturing in Africa. Keywords:Africa, industrialization, labor, manufacturing JEL Codes:D2, L6, O14 Working Paper 466 October 2017 www.cgdev.org Can Africa Be a Manufacturing Destination? Labor Costs in Comparative Perspective Alan Gelb Center for Global Development Christian J. Meyer European University Institute Vijaya Ramachandran Center for Global Development Divyanshi Wadhwa Center for Global Development The authors are grateful to Tom Bundervoet, Ranil Dissanayake, Louise Fox, Matthew Johnson-Idan, David Lam, Todd Moss, Maryam Nejad, Alexis Smallridge, Francis Teal, an anonymous external reviewer, and seminar participants at the DFID-IZA Growth and Labor Markets in Low Income Countries Workshop at Oxford University, the DFID economist seminar series, the World Bank’s Trade and Competitiveness Learning Week, and the Research in Progress series at the Center for Global Development. We owe a special debt to Joshua Wimpey at the World Bank for his guidance regarding the Enterprise Surveys dataset. All errors are, of course, ours alone. This document is an output from a project funded by the UK Department for International Development (DFID) and the Institute for the Study of Labor (IZA) for the benefit of developing countries. The views expressed are not necessarily those of DFID or IZA. Alan Gelb, Christian J. Meyer, Vijaya Ramachandran, and Divyanshi Wadhwa. 2017. “Can Africa Be a Manufacturing Destination? Labor Costs in Comparative Perspective.” CGD Working Paper 466. Washington, DC: Center for Global Development. https://www. cgdev.org/publication/can-africa-be-manufacturing-destination-labor-costs-comparative- perspective Center for Global Development The Center for Global Development is an independent, nonprofit policy 2055 L Street NW research organization dedicated to reducing global poverty and inequality Washington, DC 20036 and to making globalization work for the poor. Use and dissemination of this Working Paper is encouraged; however, reproduced copies may not be 202.416.4000 used for commercial purposes. Further usage is permitted under the terms (f) 202.416.4050 of the Creative Commons License. www.cgdev.org The views expressed in CGD Working Papers are those of the authors and should not be attributed to the board of directors, funders of the Center for Global Development, or the authors’ respective organizations. Contents Abstract ............................................ 2 Acknowledgements ..................................... Introduction ......................................... 1 Data .............................................. 3 Descriptive Results ..................................... 6 Statistical Analysis ..................................... 10 Regression Results ..................................... 15 Can Ethiopia Be The New China? ............................ 24 Conclusion ........................................... 27 Appendix A: Results of Fixed Effects Models ..................... 30 Appendix B: Results from a Survey of Manufacturing Workers in Ethiopia .. 33 References ........................................... 45 List of Tables 1 Variables Definitions ................................. 6 2 Descriptive statistics ................................. 7 3 Comparing countries ................................. 10 4 Weighting scheme................................... 14 5 Random effects model ................................ 20 6 Random effects model: Unit labor cost....................... 21 7 Random effects model: weighted (synthetic control)................ 23 A1 Fixed effects model: Africa.............................. 31 A2 Fixed effects model: Comparator .......................... 32 A3 Age........................................... 34 List of Figures 1 Analytical sample................................... 5 2 Median labor cost v. GDP per capita........................ 9 3 Ratio of labor cost and GDP per capita v. GDP per capita............ 9 4 Methodology flow chart................................ 12 5 Predicted labor cost per worker (Full sample) ................... 16 6 Predicted labor cost per worker (Africa sample).................. 17 7 Predicted labor cost per worker (Comparator sample)............... 17 8 Median predicted labor cost per worker using random effects coefficients . 26 9 Number of Children (Female Respondents)..................... 34 10 Highest level of education completed ........................ 35 11 Safety net vs. long-term career ........................... 36 12 Status of Dwelling .................................. 40 13 Pressure to Share Income............................... 42 14 Family turns to worker for help ........................... 43 15 Worker turns to family for help ........................... 44 Introduction Industrial location responds to many factors, including geography, transport, logistics and ease of integration into global value chains, domestic market size and agglomeration potential, labor and management skills, policy quality, and more recently ICT readiness (digitization, robotics, AI). On most of these measures, African countries do not perform strongly. Certain industries can of course, draw on a rich and diverse natural resource base. As the Africa Mining Vision emphasizes, resource-rich African countries can encourage forward and backward linkages, especially to small and medium size enterprises, in these industries (Hausmann et al., 2008). Tourism, another rapidly-growing export sector, can also stimulate local industrial and service firms. The \footloose" industries that have typically served as the entry point for industrialization generally involve labor-intensive segments of industrial value chains. For the African manufac- turing sector to succeed, labor costs need to be competitive. Given that poor countries usually have cheap labor, African countries should have some of the cheapest labor in the world. The question is|do they, and if so, is African labor cheap enough to compensate for other, less fa- vorable, factors? Several papers have shed light on these questions. Fox et al (2017) argue that the past decade has seen economic activity shift into higher-productivity sectors but that this structural transformation has seen labor shift into services rather than into industry. S¨oderbom and Teal, along with various coauthors, have written extensively on the efficiency of firms in the manufacturing sector in Africa as well as on the relationship between workers skills and the ability to export (Siba et al., 2012; S¨oderbom and Teal, 2004; S¨oderbom, 2003; S¨oderbom and Teal, 2000). Page (2012) argues that industrialization in Africa can be sped up by focusing on exports, agglomeration externalities and investments in the capabilities of the firm. Tybout (2000) and Van Biesebrock (2005) explore the determinants of productivity of firms including the relationship between firm size and productivity. Ceglowski et al (2015) find that unit labor 1 costs in most Sub Saharan African countries are high relative to China. They argue that this, combined with a weak business climate, means that most African countries will not become competitive in manufacturing in the near future. Labor costs cannot be considered in isolation as a determinant of competitiveness. Switzerland, for example, ranks at the top of the World Economic Forum's Global Competitiveness Index (GCI). With an outstanding business environment, rich technical and management skills and excellent location, it can sustain a large manufacturing industry, and one not based on natural resources, despite very high costs of labor. Policy quality and predictability, administrative capacity, human, institutional and governance capital, physical and financial infrastructure, and location can be taken as important indicators of the quality and sophistication of a country's business environment. Some of these indicators are difficult to measure and there is no unique way to combine them into a single index, but many of them correlate quite strongly with GDP per capita. One option, then, is to take this as a proxy for the physical and institutional capacity of the country and the human capital embedded in its workforce. Thus, a comparison of labor cost per worker, given GDP per capita, may help to indicate how well a country can compete on the basis of low labor costs, taking into account its general level of development relative to competitors. An alternative approach could be to take an indicator like the GCI to represent