Abstract
This paper analyzes the evolution of the labor share of income in Asia, a region where countries have experienced steep declines and increases as well as stable labor income shares in the quarter-century since 1990. An innovation of this study is to expand the standard drivers of labor shares—technological advance, trade, institutions, and policies—by considering whether the exposure to routine jobs has also played a role in the evolution of the labor share of income. The more exposed a country is to routinization, the greater is the probability that ICT capital substitutes mid-skilled jobs, lowering the overall wage share of workers. Using a new dataset on the exposure to routinization, the study finds that it is an important determinant of the evolution of labor shares in developed Asian economies, where the initial exposure was high, but not in developing Asian economies where the share of routine jobs was small.
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Notes
- 1.
The data for the labor share of income are from official sources and Dao et al. (2017). Official data are unavailable for certain Asian countries, including India, Bangladesh, and Cambodia.
- 2.
Technological progress affects the labor share by lowering the user cost of capital and inducing firms to substitute capital for labor (with the impact on the labor share depending on the elasticity of substitution between labor and capital). The user cost of capital is the opportunity cost of using rather than selling the existing capital and is a positive function of the price of capital, the interest rate, the depreciation rate, and the expected decline in the price of capital. More efficient technology for producing investment goods lowers the price of capital and thus the user cost. A decline in interest rates or capital depreciation rates could play a similar role to technological progress in lowering the user cost of capital.
- 3.
- 4.
We draw on a measure of routinization developed in Das and Hilgenstock (2018); see also Das (2018). This measure begins with a score for the routinizability of every occupation that Autor and Dorn (2013) created and then computes an occupation-weighted score for each sector in a country and an aggregate score for the country. The routinization scores vary over time as the occupation weights change.
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- 6.
This assumption implies that the tasks that, for example, a babysitter performs present inherent challenges to computerization, while those that an assembly plant worker performs are inherently automatable, regardless of the industry or the time when they are performed. Importantly, note that the assumed intrinsic quality of the task is distinct from whether the task is actually automated, which may indeed vary with time or across industries or countries.
- 7.
These are weighted averages, with weights given by value added, and we calculate them separately for developed and developed economies. For example, for developed economies, the weights are the share of an industry’s value added in the total value added of that industry across all developed economies. We use the same weighting scheme for developing economies.
- 8.
Following a large literature, we measure the relative price of investment goods as the ratio of the investment deflator to the consumption deflator. In a two-sector economy, consisting of a capital goods sector and a consumption goods sector (e.g., Whelan 2000), a declining relative price of investment can result from either an increase in productivity in the investment goods sector or a decline in productivity in the consumption goods sector and leads to an increase in the employment of investment goods in production relative to factors used in consumption goods (which may include labor as well as other factors of production).
- 9.
Feenstra (2002) proposed the skill bias of ICT as the main explanation for the rising wage premium of skilled workers. Feenstra argued that, as routine tasks were automated and offshored, the composition of the remaining production in developed economies became more skill-intensive, raising the demand for high-skilled workers and generating a skilled wage premium. The growth of low-skilled labor and the “twisting” of the wage distribution has led to the additional observation that the skill bias of ICT lies behind labor market polarization.
- 10.
- 11.
In contrast, non-routine, low-skilled tasks, like construction and babysitting, require either physical proximity or face-to-face interaction, making them unsuitable for offshoring.
- 12.
This is distinct from the stylized finding that the price level of investment goods is higher in developing economies (Hsieh and Klenow 2003). The factors behind this differential evolution may be related to the high dependence on capital imports in developing countries, where local currency prices are subject to import tariffs; the commodity intensity of imports; non-trade barriers and transportation costs; and the volatility of exchange rates (Dao et al. 2017).
- 13.
This is a widely used metric of value-added trade, which includes measures of both backward linkages (defined as the share of foreign value added in gross exports, which captures the extent of offshoring of intermediate inputs used in exports) and forward linkages (defined as the share of exports consisting of intermediate inputs that trading partners use for the production of their exports to third countries, which is a measure of the extent of vertical specialization). See for example Koopman et al. (2014) and Dao et al. (2017).
- 14.
- 15.
Backward linkages capture the extent of offshoring of intermediate inputs used in exports, and we define them as the share of foreign value added in gross exports. Forward linkages measure the extent of vertical specialization, and we define them as the share of exports consisting of intermediate inputs that trading partners use for the production of their exports to third countries (see Koopman et al. 2014).
- 16.
The larger impact of offshoring in receiving developing economies could reflect the fact that the reallocation of displaced workers in advanced economies from manufacturing to low-skill (but labor-intensive) service industries (as Autor and Dorn 2013 showed) may itself raise the labor share and work against the negative effect of offshoring, while, in developing economies, the reallocation effect (from labor to more capital-intensive jobs) is more unambiguous. Another reason is that imported intermediate inputs may increase the labor share in some tasks/sectors in developed countries through their positive effect on productivity if such tasks have a relatively low elasticity of substitution.
- 17.
- 18.
See Jaumotte et al. (2013).
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Das, M. (2019). Does the Exposure to Routinization Explain the Evolution of the Labor Share of Income? Evidence from Asia. In: Fields, G., Paul, S. (eds) Labor Income Share in Asia. ADB Institute Series on Development Economics. Springer, Singapore. https://doi.org/10.1007/978-981-13-7803-4_2
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