Notes

Notes

1. An economy’s aggregate productivity is a weighted sum of firm-level productivity, in which the weights are firms’ market, employment, or value-added shares. 2. Hopenhayn (1992) finds that about a third of the jobs and more than 40 percent of

US manufacturing firms exited the market and then were replaced by new entrants during each five-year period. Haltiwanger, Jarmin, and Miranda (2013) show that, conditional on survival, young firms grow faster than older and more established firms. 3. Jones (2016) shows that the gap in income per capita across countries has been growing since the 1960s despite some stability in the first decade of the twenty-first century (see figure below). Interestingly, Jones (2016, 37–38) finds that “the poorest countries in 1960 such as Ethiopia were only about 32 times poorer than the United

States. By 2011, there are many countries with relative incomes below this level, and both Niger and the Central African Republic were more than 64 times poorer than the United States.”

1.4

Standard deviation 1.3

1.2

1.1

1.0 Standard deviation of log GDP per person (left scale)

Ratio of GDP per person, 5th Richest to 5th Poorest (right scale) 60

50

40 Ratio

30

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 20

Source: Jones 2016, © Elsevier. Note: Data from The Penn World Tables 8.0, calculated against a stable sample of 100 countries.

4. Following the availability of micro data sets, a large body of literature documents evidenceofconsiderableandpersistentproductivitydispersionamongproducersin narrowly defined industries. In addition, low-productivity producers coexist with their high-productivity counterparts in the long run. The pioneering work in the literature is Bernard and Jensen (1995). 5. Lewis (1954) develops the first dual sector economic model. 6. In their literature survey on how distortions influence the effect of international trade in developing countries, Atkin and Khandelwal (2019) distinguish between market-leveldistortionsandfirmandsectoraldistortions.Theformeraffectallfirms that are in operation and encompass factors in the labor market, including human

capital, capital markets, input markets (material, land, and other inputs), domestic market frictions, and information and knowledge asymmetries. The latter refer to factors that lead to distortions, affecting firms and sectors to varying extents, and include the high informality of firms, presence of politically connected firms as well as business groups and family firms, and imperfect competition and markups. 7. In Jones et al. (2019b), productivity is measured by labor productivity and defined as real value added per worker in 2010 US dollars. 8. Abreha (2019) and Bigsten and Gebreeyesus (2009) for Ethiopia; Bigsten et al. (2004) for selected countries in Sub-Saharan Africa; Halpern, Koren, and Szeidl (2015) for Hungary; Kasahara and Lapham (2013) and Kasahara and Rodrigue (2008) for Chile; and Van Biesebroeck (2005) for selected countries in Sub-Saharan

Africa. 9. There is a distinction between inward and outward FDI spillovers. The former refer to effects in the host country, whereas the latter denote their counterparts in the source country. Because almost all Sub-Saharan African countries are net recipients of FDI and are the focus of analysis, the discussion in the report on FDI is entirely about inward FDI and Sub-Saharan African countries as hosts. 10. Forexample,Haskel,Pereira,andSlaughter(2007)forUKmanufacturingandKeller and Yeaple (2009) for US manufacturing firms. 11. Because of the large size of the informal economy and lack of data, studies that directly address the issue of agglomeration effects in Sub-Saharan African countries are insufficient. More empirical studies are needed to arrive at some consensus on the magnitude and determinants of agglomeration economies in these countries. 12. Paganini (2016) shows that misallocation spans sectors outside manufacturing and, as illustrated in the following table, the less substitutable inputs are, the larger the degree of misallocation in a given sector.

Index / Sector Elasticity of substitution Mean Standard deviation Minimum Maximum Kurtosis Number of observations

Marginal product of capital (MPK)

agriculture 1.31 –0.97 1.35 –3.90 3.00 3.00 179

Manufacturing 0.46 –1.15 3.10 –11.70 10.67 3.58 1981 tertiary 0.38 0.64 4.53 –16.00 12.78 3.00 1467

Hsieh-Klenow index of distortions (HK)

agriculture 1.31 0.24 4.62 –7.11 5.34 5.20 179

Manufacturing 0.46 –12.00 2.91 –26.00 –1.63 3.75 1981 tertiary 0.38 –15.00 3.77 –33.38 –1.92 3.92 1467

Source: Paganini 2016. Note: The marginal product of capital (MPK) and the Hsieh-Klenow index of distortions (HK) are expressed in logarithms. These calculations assume a CES technology. CES = constant elasticity of substitution.

13. TheLargeandMediumManufacturingIndustryandElectricityIndustriesSurveyof

Ethiopian firms reveals that about 30 percent of them considered lack of market demand as a constraint for their operations and full productive capacity utilization over 1996–2011 (Abreha 2017).