Mr. John C Bluedorn, Francesca Caselli, Mr. Niels-Jakob H Hansen, Mr. Ippei Shibata, and Marina M. Tavares
Using individual-level data for 30 European countries between 1983 and 2019, we document the extent and earning consequences of workers’ reallocation across occupations and industries and how these outcomes vary with individual-level characteristics, namely (i) education, (ii) gender, and (iii) age. We find that while young workers are more likely to experience earnings gains with on-the-job sectoral and occupational switches, low-skilled workers’ employment transitions are associated with an earnings loss. These differences in earnings gains and losses also mask a high degree of heterogeneity related to trends in routinization. We find that workers, particularly low-skilled and older workers during recessions, experience a severe earning penalty when switching occupations from non-routine to routine occupations.
Cristian Alonso, Mr. Andrew Berg, Siddharth Kothari, Mr. Chris Papageorgiou, and Sidra Rehman
This paper considers the implications for developing countries of a new wave of technological change that substitutes pervasively for labor. It makes simple and plausible assumptions: the AI revolution can be modeled as an increase in productivity of a distinct type of capital that substitutes closely with labor; and the only fundamental difference between the advanced and developing country is the level of TFP. This set-up is minimalist, but the resulting conclusions are powerful: improvements in the productivity of “robots” drive divergence, as advanced countries differentially benefit from their initially higher robot intensity, driven by their endogenously higher wages and stock of complementary traditional capital. In addition, capital—if internationally mobile—is pulled “uphill”, resulting in a transitional GDP decline in the developing country. In an extended model where robots substitute only for unskilled labor, the terms of trade, and hence GDP, may decline permanently for the country relatively well-endowed in unskilled labor.
This paper extends the Schumpeterian model of creative destruction by allowing followers’ cost of innovation to increase in their technological distance from the leader. This assumption is motivated by the observation the more technologically ad- vanced the leader is, the harder it is for a follower to leapfrog without incurring extra cost for using leader’s patented knowledge. Under this R&D cost structure, leaders innovate to increase their technological advantage so that followers will eventually stop innovating, allowing leadership to prevail. A new steady state then emerges featuring both leaders and followers innovating in few industries with low aggregate growth.
This paper uses a DSGE model to simulate the impact of technological change on labor markets and income distribution. It finds that technological advances offers prospects for stronger productivity and growth, but brings risks of increased income polarization. This calls for inclusive policies tailored to country-specific circumstances and preferences, such as investment in human capital to facilitate retooling of low-skilled workers so that they can partake in the gains of technological change, and redistributive policies (such as differentiated income tax cuts) to help reallocate gains. Policies are also needed to facilitate the process of adjustment.
International Monetary Fund. Western Hemisphere Dept.
This Selected Issues paper proposes a simple nowcast model for an early assessment of the Salvadorian economy. The exercise is based on a bridge model, which is one of the many tools available for nowcasting. For El Salvador, the bridge model exploits information for the period 2005–17 from a large set of variables that are published earlier and at higher frequency than the variable of interest, in this case quarterly GDP. The estimated GDP growth rate in the 4th quarter of 2017 is 2.4 percent year-over-year, leading to an average GDP growth rate of 2.3 percent in 2017. This is in line with the GDP growth implied by the official statistics released two months later, in March 23, 2018.
The typical size distribution of manufacturing plants in developing countries has a thick left tail compared to developed countries. The same holds across Indian states, with richer states having a much smaller share of their manufacturing employment in small plants. In this paper, I explore the hypothesis that this income-size relation arises from the fact that low income countries and states have high demand for low quality products which can be produced efficiently in small plants. I provide evidence which is consistent with this hypothesis from both the consumer and producer side. In particular, I show empirically that richer households buy higher price goods while larger plants produce higher price products (and use higher price inputs). I develop a model which matches these cross-sectional facts. The model features non-homothetic preferences with respect to quality on the consumer side. On the producer side, high quality production has higher marginal costs and requires higher fixed costs. These two features imply that high quality producers are larger on average and charge higher prices. The model can explain about forty percent of the cross-state variation in the left tail of manufacturing plants in India.
Using Chilean data, we document that for resource-rich small open economies the effects of terms of trade shocks on the wage gap (between skilled and unskilled workers) depend on factor intensities in the non-tradable sector, following the model in Galiani, Heymann, and Magud (2010). For a skilled-intensive non-tradable sector we show that improvements in the terms of trade benefit skilled workers. We also show that this relation holds at the industry level: the wage gap widens in skilled-intensive sectors while it shrinks in unskilled-intensive ones, the more so as terms of trade volatility decreases.
This paper extends the q-theory of investment to model explicitly the decision of firms to invest in intangibles and measures the contribution of intangible goods to the overall capital stock in the U.S. The model highlights the embodiment of intangible goods in tangibles and the role of relative price movements in the measurement of the contribution of each type of investment to the overall capital stock. The downward trend in the aggregate investment deflator series reported by national accounts is found to have a significant downward bias in the 90s. The model also shows that the growth in the overall capital stock from the late-80s until 2000 was driven mainly by an increase in the contribution of intangibles. However, the contribution of intangibles fell consistently after 2000. These results underscore the importance of accounting for the movements in the price of intangibles rather than focusing only on their rising share in overall investment.
Increases in core inflation owing to the VAT hike were smaller than expected, initially constituting a puzzle and leading to speculation about delayed increases or competitive pressures. Given Germany’s large size and openness, spillover interactions appear to have increased over time. In the midst of a strong recovery, Germany is facing shortages of labor, the emigration of high-skilled labor, and a reduction in immigration. Germany’s traditionally insider-dominated corporate governance system has undergone substantial reforms, leading to a pronounced strengthening of control by outsiders.