Seite - (000032) - in Disrupted Development and the Future of Inequality in the Age of Automation

22 L. SCHLOGL AND A. SUMNER say that a conceptualization of ST has three discernible dimensions framed around a shift toward higher productivity activities. These are sectoral, factoral, and integrative. The first dimension—the sectoral aspects of ST—is about the inter- and intra-reallocation of sectoral activ- ity toward higher productivity. The second dimension is the factoral aspects of ST and is about the composition or drivers of economic growth in terms of a shift of factors of production toward higher produc- tivity activities. Third are the integrative aspects of ST. This is the extent of integration in terms of the global economy and a shift from forms of incorporation—trade deficits and capital inflows that come with liabili- ties (for example, profit repatriation or debt repayment)—toward trade surpluses. The Groningen Growth and Development Centre (GGDC) 10-Sector Database (version 2014) developed by Timmer, de Vries, and de Vries (2015) provides a long-run, comparable dataset on value-added, employment and exports for ten economic sectors covering thirty-three developing countries covering the period since the 1950s. The GGDC 10-Sector Database covers eleven countries in Africa; eleven in Asia; nine in Latin America; and two in the Middle East and North Africa. The GGDC 10-Sector Database can thus be used to consider ST over time in developing countries.1 Additionally, the specific limitations of the GGDC 10-Sector Database are discussed by Diao, McMillan, Rodrik, and Kennedy (2017, pp. 4–6) who note the following: (i) the data broadly include all employ- ment regardless of formality or informality, but the extent to which the value-added data do so depends on the quality of national sources (see Timmer et al. 2015); (ii) the quality of data from poor countries and Africa in particular is questioned, though it is noted that Gollin (2014) have shown high correlations between national accounts data and sec- toral measures of consumption which is reassuring, and the African countries in the GGDC dataset are those with the strongest national statistical offices; (iii) the measurement of labor inputs is not by hours but number of employees in a sector: thus seasonality might lead to an underestimation of labor productivity in agriculture for example, though it is noted that Duarte and Restuccia (2010) find a correlation between hours worked and employment shares in a set of twenty-nine developed and developing countries; and (iv) if labor shares differ greatly across economic activities, then comparing average labor productivity can be misleading.