Their Job
The Job Satisfaction Paradox: Pluralistic Ignorance and the Myth of the "Unhappy Worker"
Paul Glavin & Scott Schieman
Social Psychology Quarterly, forthcoming
Abstract:
American media coverage of the "Great Resignation" may have contributed to a belief that job dissatisfaction is widespread in the United States, even though surveys show relatively high and stable levels of job satisfaction among American workers. Using data from the 2023 Quality of Employment Survey, we investigate whether individuals' beliefs about job dissatisfaction mirror empirical evidence or align more with media portrayals of widespread discontent. While most study participants expressed personal job satisfaction, over half believed that the majority of Americans were not at all satisfied, indicative of pluralistic ignorance -- a phenomenon involving a collective misperception about a group's norms or beliefs. Dissatisfaction beliefs were more common among remote workers and those with fewer work friendships. Moreover, believing in widespread job dissatisfaction was associated with lower organizational commitment, controlling for personal job satisfaction. We discuss the role of pluralistic ignorance in reconciling personal experiences with contrasting media representations of work and the economy.
Extraordinary Labor Market Developments and the 2022-23 Disinflation
Steven Davis
NBER Working Paper, June 2024
Abstract:
Two extraordinary U.S. labor market developments facilitated the sharp disinflation in 2022-23 without raising the unemployment rate. First, pandemic-driven infection worries and social distancing intentions caused a sizable drag on labor force participation that began to reverse in the first quarter of 2022, and perhaps earlier. As the reversal unfolded, it raised labor supply and reduced wage growth. Second, the pandemic-instigated shift to work from home (WFH) raised the amenity value of employment in many jobs and for many workers. This development lowered wage-growth pressures along the transition path to a new equilibrium with pay packages that recognized higher remote work levels and their benefits to workers. Surveys of business executives imply that the shift to WFH lowered average wage growth by two percentage points from spring 2021 to spring 2023. A direct inspection finds that average real wage growth from 2021 Q1 to 2024 Q1 in the U.S. economy was at least 3.5 to 4.4 ppts below the path suggested by pre-pandemic experience. This large shortfall in real wage growth aligns well with the interpretation of the 2022-23 disinflation offered here.
Automation, Career Values, and Political Preferences
Maria Petrova et al.
NBER Working Paper, July 2024
Abstract:
Career opportunities and expectations shape people's decisions and can diminish over time. In this paper, we study the career implications of automation and robotization using a novel data set of resumes from approximately 16 million individuals from the United States. We calculate the lifetime "career value" of various occupations, combining (1) the likelihood of future transitions to other occupations, and (2) the earning potential of these occupations. We first document a downward trend in the growth of career values in the U.S. between 2000 and 2016. While wage growth slows down over this time period, the decline in the average career value growth is mainly due to reduced upward occupational mobility. We find that robotization contributes to the decline of average local labor market career values. One additional robot per 1000 workers decreased the average local market career value by $3.9K between 2004 and 2008 and by $2.48K between 2008 and 2016, corresponding to 1.7% and 1.1% of the average career values from the year 2000. In commuting zones that have been more exposed to robots, the average career value has declined further between 2000 and 2016. This decline was more pronounced for low-skilled individuals, with a substantial part of the decline coming from their reduced upward mobility. We document that other sources of mobility mitigate the negative effects of automation on career values. We also show that the changes in career values are predictive of investment in long-term outcomes, such as investment into schooling and housing, and voting for a populist candidate, as proxied by the vote share of Trump in 2016. We also find further evidence that automation affected both the demand side and supply side of politics.
Ride-Sharing the Wealth: Effects of Uber and Lyft on Jobs, Wages and Economic Growth
Adam Koling et al.
Carnegie Mellon University Working Paper, June 2024
Abstract:
Between 2010 and 2019, Uber and Lyft launched in hundreds of cities across the United States. During that decade, these transportation network companies (TNCs) frequently asserted that their ridesourcing services brought increased jobs, wages and economic growth to the cities they served. Many such claims emphasized job flexibility for drivers, increased mobility for passengers, and the combined potential of both populations to stimulate economic activity. We test these claims by leveraging the staggered entry of Uber and Lyft across 167 service regions nationwide to estimate the aggregate effects on jobs, wages, and regional GDP. Given that the timing of treatment is staggered, we deploy three difference-in-differences approaches that generate consistent estimates in the presence of heterogeneous treatment effects: the Callaway & Sant'Anna estimator, the Sun & Abraham estimator, and stacked regression. Across all three methods, we find that Uber and Lyft entry caused (1) an increase in employment per working age population, especially for seasonal, temporary, or otherwise intermittent jobs; (2) an increase in earnings per working age population for intermittent jobs; and (3) an increase in gross domestic product (GDP) per capita. Our results are broadly consistent in sign, magnitude, confidence intervals, and statistical significance, across all three estimation methods. In addition to reporting point estimates and 95% confidence intervals, we discuss possible mechanisms of TNC economic impact with particular attention to challenges in estimating and interpreting the magnitudes of treatment effects.
Do Firing Costs Increase Human Capital Accumulation? Evidence From Germany
Toshitaka Maruyama
University of California Working Paper, May 2024
Abstract:
This paper presents new empirical evidence and a theoretical framework, which suggests that firing costs impede human capital accumulation within firms. To that end, I investigate the impact of a German reform in 2004 that removed firing costs exclusively for smaller establishments. Applying a difference-in-differences approach to administrative matched employee-employer data, I find that the targeted smaller establishments experienced an increase in the proportion of employees participating in training compared with others. To clarify the underlying mechanism and quantify the aggregate effect of the reform, I develop an on-the-job search model with human capital and firing costs. Reducing firing costs in this model stimulates job creation by firms, and thereby increases the probability of workers transitioning to firms in which their skills are more valuable. This encourages workers to accumulate human capital. The calibrated model suggests that the German reform could result in a 0.58% increase in aggregate productivity, with 0.49% attributed to human capital accumulation and the rest to more efficient resource allocation.
Is Software Eating the World?
Sangmin Aum & Yongseok Shin
NBER Working Paper, June 2024
Abstract:
When explaining the declining labor income share in advanced economies, the macro literature finds that the elasticity of substitution between capital and labor is greater than one. However, the vast majority of micro-level estimates shows that capital and labor are complements (elasticity less than one). Using firm- and establishment-level data from Korea, we divide capital into equipment and software, as they may interact with labor in different ways. Our estimation shows that equipment and labor are complements (elasticity 0.6), consistent with other micro-level estimates, but software and labor are substitutes (1.6), a novel finding that helps reconcile the macro vs. micro-literature elasticity discord. As the quality of software improves, labor shares fall within firms because of factor substitution and endogenously rising markups. In addition, production reallocates toward firms that use software more intensively, as they become effectively more productive. Because in the data these firms have higher markups and lower labor shares, the reallocation further raises the aggregate markup and reduces the aggregate labor share. The rise of software accounts for two-thirds of the labor share decline in Korea between 1990 and 2018. The factor substitution and the markup channels are equally important. On the other hand, the falling equipment price plays a minor role, because the factor substitution and the markup channels offset each other.