Automation and the Future of Work. Aaron Benanav
employment consistently fell below the rate of growth of the total workforce, the manufacturing employment share started its downward trend.
Figure 2.1. French Manufacturing Sector, 1950–2017
Source: Conference Board, International Comparisons of Productivity and Unit Labour Costs, July 2018 edition.
This disaggregation helps explain why automation theorists falsely perceive productivity to be growing at a rapid pace in manufacturing. Productivity growth rates have been high relative to output growth rates, but not because productivity has been growing more rapidly than before—which would be a sure sign of accelerating automation. On the contrary, the key to this trend is that output has been growing much more slowly than before. The same pattern can be seen in the statistics of other countries: no absolute decline in levels of manufacturing production took place—more and more was produced—but the rate at which output grows declined, so output growth came to be consistently slower than productivity growth (Table 2.1). As industrial output growth rates fell below corresponding productivity growth rates in country after country, quantitative declines in economic indicators became qualitative in their effects: manufacturing employment shares fell progressively. Worsening economic stagnation thus combined with a limited technological dynamism to generate labor’s global deindustrialization.
Table 2.1. Manufacturing Growth Rates, 1950–2017
| Output | Productivity | Employment | ||
| USA | 1950–73 | 4.4% | 3.1% | 1.2% |
| 1974–2000 | 3.1% | 3.3% | -0.2% | |
| 2001–17 | 1.2% | 3.2% | -1.8% | |
| Germany | 1950–73 | 7.6% | 5.7% | 1.8% |
| 1974–2000 | 1.3% | 2.5% | -1.1% | |
| 2001–17 | 2.0% | 2.2% | -0.2% | |
| Japan | 1950–73 | 14.9% | 10.1% | 4.3% |
| 1974–2000 | 2.8% | 3.4% | -0.6% | |
| 2001–17 | 1.7% | 2.7% | -1.1% | |
Source: Conference Board, International Comparisons of Productivity and Unit Labour Costs, July 2018 edition.
Such “output-led” deindustrialization is impossible to explain in purely technological terms.20 In their search for alternative perspectives, economists have mostly preferred to describe this trend as a harmless evolutionary feature of advanced economies.21 However, that perspective is itself at a loss to explain extreme variations in the GDP per capita levels at which this supposedly evolutionary economic shift has taken place. Deindustrialization unfolded first in high-income countries in the late 1960s and early 1970s, at the tail end of a period in which levels of income per person had converged across the United States, Europe, and Japan. In the decades that followed, deindustrialization then spread “prematurely” to middle-and low-income countries, with larger variations in incomes per capita (Figure 2.2).22 In the late 1970s, deindustrialization arrived in southern Europe; much of Latin America, parts of East and Southeast Asia, and southern Africa followed in the 1980s and ’90s. Peak industrialization levels in many poorer countries were so low that it may be more accurate to say that they never industrialized in the first place.23
Figure 2.2. Global Waves of Deindustrialization, 1950–2010
Source: Groningen Growth and Development Centre, 10-Sector Database, January 2015 edition.
By the end of the twentieth century, it was possible to speak of a global wave of deindustrialization: worldwide manufacturing employment rose in absolute terms by 0.4 percent per year between 1991 and 2016, but that was much slower than the overall growth of the global labor force, with the result that the manufacturing share of total employment declined by 3 percentage points over the same period.24 China is a key exception, but only a partial one (Figure 2.3). In the mid 1990s, Chinese state-owned enterprises shed millions of workers, sending manufacturing-employment shares on a steady downward trajectory.25 China reindustrialized, in employment terms, starting in the early 2000s, but then it began to deindustrialize once again in the mid 2010s. Its manufacturing-employment share has since dropped significantly, from 19.3 percent in 2013 to 17.2 percent in 2018. If deindustrialization cannot be explained by either automation or the internal evolution of advanced economies, what could be its source?
Figure 2.3. Deindustrialization in China, India and Mexico, 1980–2017
Source: Conference Board, International Comparisons of Productivity and Unit Labour Costs, July 2018 edition.
Blight of Manufacturing Overcapacity
What the economists’ accounts fail to register in their explanations of deindustrialization is also what is missing from the automation theorists’ accounts. The truth is that rates of output growth in manufacturing have tended to decline, not only in this or that country, but worldwide (Figure 2.4).26 In the 1950s and ’60s, global-manufacturing production expanded at an average annual rate of 7.1 percent per year, in real terms. That rate fell progressively to 4.8 percent in the 1970s and to 3.0 percent between 1980 and 2007. From the 2008 crisis up to 2014, manufacturing output expanded at just 1.6 percent per year, on a world scale—that is, at less than a quarter of the pace achieved during the post-war “golden age.”27 It is worth noting that these figures include the dramatic expansion of manufacturing productive capacity in China.
Figure 2.4. World Manufacturing and Agricultural Production, 1950–2014
Source: World Trade Organization, International Trade Statistics 2015, Table A1a, World Merchandise Exports, Production and GDP, 1950–2014.
Again, it is the incredible degree of slowdown in the rate at which manufacturing production expands, visible on the world scale, that explains why manufacturing-productivity growth appears to have advanced at a rapid clip, even though it