The Unassuming Economist

From a new VOX post by David Autor:

“Labour markets in US cities today are vastly more educated and skill-intensive than they were 50 years ago, but urban non-college workers now perform much less skilled work than they did. This column shows that automation and international trade have eliminated many of the mid-skilled non-college jobs that were disproportionately based in cities. This has contributed to a secular fall in real non-college wages.”

“Figure 2 depicts the aggregate relationship between population density and occupational structure at the level of 722 commuting zones (CZs) covering the contiguous US states between 1970 and 2015.

The three panels of this figure report the CZ-level share of employment among working-age adults into the three broad occupational categories described above: traditionally low-education, low-wage services, transportation, labourer, and construction workers; traditionally mid-education, middle-wage occupations made up of clerical, administrative support, sales, and production workers; and high-education, high-wage, professional, technical, and managerial workers.

The horizontal axis is the natural log of population density (the number of residents divided by CZ land area). For consistency, I used each zone’s population density in 1970 throughout, and the data are weighted by the count of working-age adults in each CZ. Each plotted point in the bin-scatter represents approximately 5% of all workers in each year.

The rising set of upward-sloping curves in the right panel show that while denser CZs have traditionally been more intensive in high-skill work, the level and slope of this relationship between density and skill-intensity has risen consistently over multiple decades. The overlapping downward-sloping curves in the left panel show that the fraction of workers engaged in low-skill occupations has historically been much smaller in high-density CZs, and this pattern has changed little over decades. In the middle panel, the fan-shaped set of curves show that the denser CZs were exceptional in the 1970s for having far more middle-skill work than suburban and rural CZs. But this exceptional feature attenuated. By 2015, the densest CZs had less middle-skill work than the suburbs or rural areas.”

From a new IMF working paper by Reda Cherif and Fuad Hasanov:

“Industrial policy is tainted with bad reputation among policymakers and academics and is often viewed as the road to perdition for developing economies. Yet the success of the Asian Miracles with industrial policy stands as an uncomfortable story that many ignore or claim it cannot be replicated. Using a theory and empirical evidence, we argue that one can learn more from miracles than failures. We suggest three key principles behind their success: (i) the support of domestic producers in sophisticated industries, beyond the initial comparative advantage; (ii) export orientation; and (iii) the pursuit of fierce competition with strict accountability.”

From a new IMF working paper by Dilyana Dimova:

“The labor share in Europe has been on a downward trend. This paper finds that the decline is concentrated in manufacture and among low- to mid-skilled workers. The shifting nature of employment away from full-time jobs and a rollback of employment protection, unemployment benefits and unemployment benefits have been the main contributors. Technology and globalization hurt sectors where jobs are routinizable but helped others that require specialized skills. High-skilled professionals gained labor share driven by productivity aided by flexible work environments, while low- and mid-skilled workers lost labor share owing to globalization and the erosion of labor market safety nets.

The value-added share accrued to labor commonly known as the labor share—the ratio of labor compensation (wages and benefits) to national income—has been on a downward trend in the EU in the last couple of decades (Figure 1). This trend is observed both in recession-hit Advanced Economies (AE) like Ireland, Portugal and Spain as well as in economically prosperous Germany and the Netherlands (Figure 1, upper panels), and began around 2012–13 after the Great Recession (GR). In New Member States (NMS), Estonia, Hungary, Latvia and Lithuania experienced a decline in 2009–15 and are on the rebound (Figure 1, lower panels). Other NMS economies such as Croatia, Poland and Romania have yet to return to their 2002 levels. The positive exception is Bulgaria whose labor share has been on an upward trend due to an economic deepening from relatively low levels.

This paper looks at the evolution of the labor share by industry and by skill level and considers the effect of various structural factors on the EU-wide stagnation and erosion of the labor share. Following Dao et al. (2017), first a shift-share analysis is used to demonstrate the extent to which the downward trend in the labor share is driven by within-sector/skill category declines or by changes across sectors/skill category. The analysis establishes that within-sector/skill category changes account for the majority of labor share fluctuations and provides justification for the structural factor analysis. Then the paper quantifies the extent to which structural drivers track changes in the labor share in 28 EU-member countries, representing both advanced economies and transitional economies, in a cross-country panel study that uses disaggregated data for twelve industry sectors and three skill categories.”

 

From a new IMF working paper:

“In the last decade, over half of the EU countries in the euro area or with currencies pegged to the euro were hit by large risk premium shocks. Previous papers have focused on the impact of these shocks on demand. This paper, by contrast, focuses on the impact on supply. We show that risk premium shocks reduce the output level that maximizes profit. They also lead to unemployment surges, as firms are forced to cut costs when financing becomes expensive or is no longer available. As a result, all countries with risk premium shocks saw unemployment surge, even as euro area core countries managed to contain unemployment as firms hoarded labor during the downturn. Most striking, wage bills in euro area crisis countries and the Baltics declined even faster than GDP, whereas in core euro area countries wage shares actually increased.”

From a new VoxChina post:

“Many developing countries adopt industrial policies favoring upstream sectors. Liu (2018) shows these policies might enhance aggregate production efficiency. When sectors form a production network, market imperfections generate distortions that compound through input demand linkages, accumulating into upstream sectors and creating an incentive for well-meaning governments to subsidize these sectors. The study proposes the measure “distortion centrality,” which is a sufficient statistic that can guide policy interventions in arbitrary networks. Distortion centrality predicts sectors that were promoted in South Korea in the 1970s and modern-day China, suggesting that these policies might have generated positive aggregate effects.”

“I find that the heavy and chemical sectors promoted by South Korea in the 1970s were upstream (as visibly evident from Figure 2E) and had significantly higher distortion centrality than non-targeted sectors, suggesting that government interventions contributed positively to aggregate economic performance.

In modern-day China, non-state-owned firms in sectors with higher distortion centrality have significantly better access to loans, receive more favourable interest rates, and pay lower taxes. These sectors also tend to have more state-owned enterprises, to which the government directly extends credit and policy subsidies.

My quantitative analysis reveals that in China, differential sectoral interest rates, tax incentives, and funds given to state-owned enterprises all generate positive aggregate effects and, taken together, improve aggregate efficiency by 4.8%. Moreover, distortion centrality correlates negatively with sectoral size, suggesting that promoting large sectors would lead to aggregate losses.”