Labor supply and government programs: A cross-country analysis

Erosa, Andrés; Fuster, Luisa; Kambourov, Gueorgui

doi:10.1016/j.jmoneco.2011.10.006

Cited by 63 publications

(56 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Prior studies of aggregate hours worked across countries have almost exclusively focused on rich countries, and in particular on the United States and European countries (e.g., . Explanations of the U.S.-Europe gap in average hours have focused largely on differences in taxation (e.g., Rogerson, 2006;McDaniel, 2011;Bick and Fuchs-Schündeln, 2017), institutions (Alesina et al, 2005) and social security systems (Erosa et al, 2012;Wallenius, 2013;Alonso-Ortiz, 2014). Other studies have focused on understanding changes in hours worked over time, though these have also concentrated on rich countries.…”

Section: Related Literaturementioning

confidence: 99%

How do Hours Worked Vary with Income? Cross-Country Evidence and Implications

Bick

Fuchs‐Schündeln²,

Lagakos³

2016

View full text Add to dashboard Cite

This paper builds a new internationally comparable database of hours worked to measure how hours vary with income across and within countries. We document that average hours worked per adult are substantially higher in low-income countries than in high-income countries. The pattern of decreasing hours with income holds for both men and women, for adults of all ages and education levels, and along both the extensive and intensive margin. Within countries, hours worked per employed are also decreasing in the individual wage for most countries, though in the richest countries, hours worked are flat or increasing in the wage. Our findings imply that aggregate productivity and welfare differences across countries are larger than currently thought.

show abstract

Section: Related Literaturementioning

confidence: 99%

How do Hours Worked Vary with Income? Cross-Country Evidence and Implications

Bick

Fuchs‐Schündeln²,

Lagakos³

2016

View full text Add to dashboard Cite

show abstract

“…In the model as in the data, we focus on retired households, so that we can avoid dealing with the labor supply decision of the elderly. (For a study on this issue using SHARE, see Erosa et al (2012)). Thus, a household in the model starts out at age 65.…”

Section: Modelmentioning

confidence: 99%

Housing in Retirement Across Countries

Nakajima

Telyukova

2012

SSRN Journal

View full text Add to dashboard Cite

The "retirement saving puzzle" in the literature is a phenomenon in which many U.S.households have significant wealth late in life, contrary to the predictions of a simple life-cycle model. In this project, we examine cross-country differences in the saving behavior of retirees in order to weigh in on the discussion of the puzzle. First, we find that countries in our sample vary noticeably in terms of the extent of the puzzle: one group of countries, in South and Central Europe, look like the United States, while in Northern Europe, retirees spend down their wealth much more rapidly. Second, it appears that the rate of dissaving in retirement is correlated with the extent of public coverage of healthcare and long-term care, and these differences in saving happen predominantly through dissaving of financial assets, while housing assets are less affected. In a quantitative experiment using a life-cycle model of saving in retirement, we measure the role of out-of-pocket medical spending risk in accounting for differences in observed saving patterns among retirees in the United States and Sweden, considering housing and financial assets separately. The model predicts that this risk accounts, on average across age, for one-half of the difference in median net worth between United States and Sweden, and for about 70 percent of the difference in median financial assets. The role of risk diminishes with age, and is seen primarily in financial asset saving, while housing assets do not appear to respond to spending risk, suggesting that housing is not a precautionary asset.

show abstract

“…The reason why we do not deal with the extensive margin here is that retirement choices are already well understood withing the life cycle model. We know from related research that technological features such as nonconvexities in the mapping between hours and labor services (e.g., Rogerson and Wallenius (2009), Erosa et al (2011)) and institutional features such as social security rules (e.g., French (2005), Erosa et al (2012)) allow a match of extensive margin behavior late in the life cycle. It is the intensive margin pattern we document here that is less explored.…”

Section: Introductionmentioning

confidence: 99%

Revisiting wage, earnings, and hours profiles

Rupert

Zanella

2015

Journal of Monetary Economics

View full text Add to dashboard Cite

We document empirical life cycle profiles of wages, earnings, and hours of work for pay from the Panel Study of Income Dynamics, following the same workers for up to four decades. For six of the eight cohorts we analyze the wage profile does not decline with age (not before 65, at least), while the earnings profile always does. The discrepancy is explained by a sharp drop in the hours of work for pay profile beginning shortly after age 50, when many workers start a smooth transition into retirement by working progressively fewer hours. This pattern is not an artifact of staggered abrupt retirement, and is robust to attrition and selection-correction (i.e., taking into account that the composition of our sample, for a given cohort, changes over time). We explore the nontrivial restrictions on dynamic models of the aggregate economy that this evidence suggests, and we provide numerical profiles that can be readily used in quantitative macroeconomic analysis.

show abstract

Labor supply and government programs: A cross-country analysis

Cited by 63 publications

References 31 publications

How do Hours Worked Vary with Income? Cross-Country Evidence and Implications

How do Hours Worked Vary with Income? Cross-Country Evidence and Implications

Housing in Retirement Across Countries

Revisiting wage, earnings, and hours profiles

Contact Info

Product

Resources

About