Downward Rigidity in the Wage for New Hires

Hazell, Jonathon; Taska, Bledi

doi:10.2139/ssrn.3728939

Cited by 41 publications

(45 citation statements)

References 90 publications

(100 reference statements)

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“…16 If firms post a higher wage for the same job when the labor market is tight, we might expect to see inflationary pressures due to rising labor costs. To operationalize this concept, we consider vacancies posted by the same firm for the same job over time following a similar methodology to Hazell and Taska (2020) who use posted wages to analyze downward wage rigidity. To ensure that we are identifying the same position we match on firm, job title, location, and 5-digit occupation code (further details on the data are provided in the Appendix).…”

Section: Underlying Wage Growth and Job-filling Ratementioning

confidence: 99%

“…Second, we study wage growth based on vacancies posted by the same firm for the same job over time, to minimize the role of composition bias and influence of worker characteristics. This measure also provides a forward-looking measure of wage growth since it captures new hires' wages as documented by Hazell and Taska (2020). We ?find that posted wage growth shows similar patterns across occupations with different exposures to the pandemic, suggesting broad-based changes, rather than additional compensation for jobs that pose health risks to workers.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The Unemployment-Inflation Trade-off Revisited: The Phillips Curve in COVID Times

Crump¹,

Eusepi²,

Giannoni³

et al. 2022

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We estimate the natural rate of unemployment, often referred to as u*, in the United States using data on labor market flows, short-term and long-term inflation expectations and a forwardlooking New-Keynesian Phillips curve for the 1960-2021 period. The natural rate of unemployment was at around 4.5% before the onset of the pandemic and increased to 5.9% by the end of 2021. This pronounced rise was primarily informed by strong wage growth rather than changes in inflation expectations. Despite the rise in the natural rate of unemployment, the secular trend of unemployment continued to fall and stands at around 4.2% reflecting ongoing secular developments which have been pushing down the unemployment rate over the last 30 years. Our model forecasts strong wage growth to moderate only sluggishly continuing to put upward pressure on inflation in the medium-run. We project underlying inflation to remain 0.5 percentage points above its long-run trend by the end of 2023 even if long-run inflation expectations remain well anchored.Given the importance of wage growth for the inflation outlook, we examine detailed micro data on job-filling rates, posted wages for vacant positions, and workers' reservation wages. In particular, we construct a composition-bias free measure of wage growth at the employer-job level using Burning Glass Technologies data and document strong wage growth for both teleworkable and non-teleworkable jobs. Moreover, we find that workers' reservation wages increased substantially after the pandemic. Our empirical analysis suggests that the strong wage growth is likely not a one-time adjustment of additional compensation for jobs that pose health risks to workers but rather reflects a tight labor market accompanied with a changing work-leisure trade-off.

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Section: Underlying Wage Growth and Job-filling Ratementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Unemployment-Inflation Trade-off Revisited: The Phillips Curve in COVID Times

Crump¹,

Eusepi²,

Giannoni³

et al. 2022

View full text Add to dashboard Cite

show abstract

“…AI algorithms process and identify patterns in vast amounts of unstructured data (for example, speech data, text, or images), and this allows them to perceive their environment and take actions to achieve some specific goal.2 Papers byAlekseeva et al (2020) andBabina et al (2020), discussed below, also apply Burning Glass data to study AI use.3 The BG data have been used in several recent papers. A non-exhaustive list of recent papers that use the Burning Glass data includesHershbein and Kahn (2016), Azar et al (2018), Modestino, Shoag, and Ballance (2019),Hazell and Taska (2019) andDeming and Noray (forthcoming).…”

mentioning

confidence: 99%

Ai and Jobs: Evidence from Online Vacancies

et al. 2020

Self Cite

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We study the impact of AI on labor markets, using establishment level data on vacancies with detailed occupational information comprising the near-universe of online vacancies in the US from 2010 onwards. We classify establishments as "AI exposed" when their workers engage in tasks that are compatible with current AI capabilities. We document rapid growth in AI related vacancies over 2010-2018 that is not limited to the Professional and Business Services and Information Technology sectors and is significantly greater in AI-exposed establishments. AIexposed establishments are differentially eliminating vacancy postings that list a range of previously-posted skills while simultaneously posting skill requirements that were not previously listed. Establishment-level estimates suggest that AI-exposed establishments are reducing hiring in non-AI positions even as they expand AI hiring. However, we find no discernible impact of AI exposure on employment or wages at the occupation or industry level, implying that AI is currently substituting for humans in a subset of tasks but it is not yet having detectable aggregate labor market consequences.

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“…Using the average new-hire wage at the state-quarter level, the authors showed the two datasets have a correlation of almost 1 (.97), suggesting aggregated pay data in BGT closely reflect those in representative surveys. Additional tests comparing BGT pay data to the Quarterly Workforce Indicators data also show a close match (Hazell and Taska 2019). Thus, on this aggregate level, BGT pay closely tracks pay in other datasets.…”

Section: Datamentioning

confidence: 74%

“…First, pay listed in the job posting may not accurately reflect the actual pay offered to new hires. To assess this, a recent paper compared the pay in BGT's job postings to wages for new hires in the Current Population Survey (CPS) and found the two sources to be highly consistent (Hazell and Taska 2019). Using the average new-hire wage at the state-quarter level, the authors showed the two datasets have a correlation of almost 1 (.97), suggesting aggregated pay data in BGT closely reflect those in representative surveys.…”

Section: Bgt As a Source Of Pay Datamentioning

confidence: 99%

Values and Inequality: Prosocial Jobs and the College Wage Premium

Wilmers

Zhang²

2022

Am Sociol Rev

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Employers often recruit workers by invoking corporate social responsibility, organizational purpose, or other claims to a prosocial mission. In an era of substantial labor market inequality, commentators typically dismiss these claims as hypocritical: prosocial employers often turn out to be no more generous with low-wage workers than are other employers. In this article, we argue that prosocial commitments in fact inadvertently reduce earnings inequality, but through a different channel than generosity. Building on research on job values, we hypothesize that college graduates are more willing than nongraduates to sacrifice pay for prosocial impact. When employers appeal to prosocial values, they can thus disproportionately reduce pay for higher-educated workers. We test this theory with data on online U.S. job postings. We find that prosocial jobs requiring a college degree post lower pay than do standard postings with exactly the same job requirements; prosocial jobs that do not require a college degree, however, pay no differently from other low-education jobs. This gap reduces the aggregate college wage premium by around 5 percent. We present a variety of supplementary evidence using labor market data, worker survey responses, and a vignette experiment with hiring managers. The findings reveal an unintended consequence of employers’ embrace of prosocial values: it offsets macro-level inequality.

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Downward Rigidity in the Wage for New Hires

Cited by 41 publications

References 90 publications

The Unemployment-Inflation Trade-off Revisited: The Phillips Curve in COVID Times

The Unemployment-Inflation Trade-off Revisited: The Phillips Curve in COVID Times

Ai and Jobs: Evidence from Online Vacancies

Values and Inequality: Prosocial Jobs and the College Wage Premium

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