برون سپاری و ویژگی های شغلی سرمایه انسانی
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|18861||2013||19 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Review of Economic Dynamics, Available online 19 December 2013
I document that workers in newly tradable service occupations possess more occupation-specific human capital and are more highly educated than workers in previously tradable occupations. Motivated by this observation, I develop a dynamic equilibrium model with labor market frictions and specific human capital to study the labor adjustment process after a trade shock. When calibrated to match the increase in U.S. trade between 1990 and 2010, the model suggests that (1) output increases immediately after a trade shock and converges quickly to the steady state; (2) labor market institutions likely play a larger role in the adjustment process than specific human capital; (3) the short run distributional effects are small if the labor market is flexible, even in the presence of specific human capital.
Technological progress has led to considerable changes in the organization of the production process – tasks traditionally completed in close physical proximity can now be spatially separated and carried out independently, thus spurring offshoring of intermediate processes or tasks. This development differs from past trade experiences as many newly tradable tasks are performed by high-skill service occupations.1 This has spurred a debate between two opposing viewpoints. One focuses on the long term gains and maintains that offshoring is productivity-enhancing. The other viewpoint stresses potential short term losses and warns about the disruptive effects of offshoring of high skill tasks. In this paper, I speak to both sides of this debate. I first provide systematic evidence on the human capital possessed by workers employed in newly tradable service occupations. I document that these workers are on average much better educated – 70% of them have some education past high school – than the average worker in the U.S. labor force. They also accumulate significantly more occupation specific human capital, as indicated by their almost 5 times higher returns to 10 years of occupational tenure than for the average worker.2 Specific human capital is particularly relevant in the context of worker reallocation due to high-skill offshoring: were reallocated workersʼ human capital mostly general, their loss in productivity would likely be small, as workers would be able to apply most of their knowledge to new tasks. However, if workers who are exposed to increased offshoring have relatively more occupation specific human capital, they will be less willing to switch occupations since occupational switches bring about the destruction of these specific skills. Motivated by this observation, I build on work by Kambourov (2009) and develop a small open economy model in which workers acquire human capital specific to the tasks they complete.3 Worker reallocation after a trade shock is not only costly because of the loss of any specific human capital, but also because of the risk of unemployment and the time it takes to find a suitable new line of work. To capture these costs, the model features search frictions and a match-specific productivity shock. This structure allows the model to quantify the aggregate gains from trade, as well as the distributional effects from a trade shock. Specific human capital generates short run distributional effects which differ from the long run effects; the labor market frictions and the idiosyncratic productivity draw generate increased unemployment and job-shopping along the transition path. After calibrating the model to match occupational turnover and the returns to occupational tenure observed in the U.S., I use the model to assess the labor market implications of the surge in trade in goods and services observed between 1990 and 2010. The dynamic nature of the model allows me to quantify not only the short run impact, but also the entire transition to the new steady state. The most important finding is that, even if the full magnitude of the trade shock is introduced at once (instead of the more staggered fashion observed in the data), the labor market impact of this “tradability revolution” is small. Almost 60% of the output gains are realized within one year and 90% of the transition is concluded four to five years after the shock. As a result of this fast transition, the distributional effects are small as well: almost all workers see the net present value of their earnings increase immediately, only highly skilled workers in production occupations see the value of their future earnings fall by about 0.9%. In the long run, the competitive nature of the labor market leads to an equalization of expected earnings across all occupations.4 To further investigate the relative importance of specific human capital and labor market institutions, I conduct three counterfactual experiments. First, I introduce the increase in trade in goods and the increase in trade in services separately. Second, I simulate the response to the trade shock in an otherwise identical economy without specific human capital. Last, I increase the labor market frictions and decrease worker turnover relative to the baseline economy. Taken together, these experiments suggest that, in the case of the U.S., the flexible labor market plays a bigger role in the adjustment process than does the specific human capital of workers in high skill service occupations. With flexible labor markets, worker reallocation is fast. This dampens the adverse effects on the workers who stay in their occupations – typically the workers with the highest level of specific skills. The relatively small role of specific human capital can be explained by two facts: first, while workers in tradable service occupations have relatively high specific human capital, its loss is still small compared to the output loss associated with unemployment. Second, even in offshored service occupations, many workers have not yet acquired the narrow specific human capital that would be lost upon an occupation switch. In the model, as in the data, only about 40% of all workers spent enough time in an occupation to have acquired the highest level of specific human capital. The model predicts that these workers remain in their occupation and retain their specific skills. In other words, the average specific human capital of switchers is lower than that of stayers.
نتیجه گیری انگلیسی
In this paper, I document that workers in newly tradable service occupations are more educated and possess more occupation specific human capital than workers in previously tradable occupations. Building on this insight, I develop a model of a small-open economy in which labor market frictions and occupation-specific human capital play key roles in determining labor reallocation after a trade shock. The calibrated model is then used to assess the implications of increased trade in high skill services on the U.S. labor market between 1990 and 2010. While lost specific human capital takes several years to reacquire, the magnitude of the specific human capital loss appears to be small relative to the output loss associated with unemployment and both are small relative to the aggregate gains from trade. The findings suggest that labor market institutions are a more important determinant of the short run dynamics than is the specificity of human capital. In an economy with flexible labor markets, workers with little specific human capital switch into occupations that received a positive trade shock, while the most productive workers (i.e. those with a good occupation match and much specific human capital) decide to stay in their occupations. This reallocation assures that the economy can exploit its comparative advantage, while at the same time it dampens the adverse effect on the skilled workers who stay in their occupations. In an economy with more severe labor market frictions and institutions limiting workers turnover, workers are more reluctant to switch occupations and the distributional effects are stronger as a result – workers in offshored occupations potentially see the present value of their incomes fall. These results suggest that trade in high skill services is not much different than trade in goods. As with all trade, there are long run gains from exploiting oneʼs comparative advantage. While the idea of substantial short-run costs stemming from the destruction of specific human capital in offshored occupations carries intuitive appeal, it is not likely to be borne out in the data for the US economy from 1990–2010. Output losses from labor reallocation and ensuing unemployment are larger than losses from specific human capital because lowest skilled workers are those most likely to switch occupations, even in the case of high skill service trade. As discussed in the previous section, occupation specific human capital is assumed not to be portable across 3-digit occupations – or, alternatively, high skill trade does not lead to offshoring of entire occupation groups of “close” occupations all at once. Were this not the case, the role of specific human capital would likely be downward biased and the short run distribution effects would be more pronounced. Due to the nature of 3-digit occupations and the U.S. also exporting (inshoring) high skill services, these assumptions are unlikely to be routinely violated. Unfortunately, a consideration of portability of specific human capital, and more generally the question of “closeness” between occupations, goes beyond the scope of this paper and is left for future research.