Experimentation and Job Choice

Antonovics, Kate; Golan, Limor

doi:10.1086/663356

Cited by 64 publications

(61 citation statements)

References 25 publications

(46 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the other hand, the match quality of the job and thus wage growth within the job cannot be entirely foreseen ex-ante. Risk-averse individuals who change jobs less frequently, have fewer opportunities to learn about their own abilities and preferences because they obtain less information with respect to their fit to different job requirements (Farber and Gibbons, 1996;Antonovics and Golan, 2012;Papageorgiou, 2014).…”

Section: Introductionmentioning

confidence: 99%

Risk Attitudes, Job Mobility and Subsequent Wage Growth During the Early Career

2017

View full text Add to dashboard Cite

Die Dis cus si on Pape rs die nen einer mög lichst schnel len Ver brei tung von neue ren For schungs arbei ten des ZEW. Die Bei trä ge lie gen in allei ni ger Ver ant wor tung der Auto ren und stel len nicht not wen di ger wei se die Mei nung des ZEW dar.Dis cus si on Papers are inten ded to make results of ZEW research prompt ly avai la ble to other eco no mists in order to encou ra ge dis cus si on and sug gesti ons for revi si ons. The aut hors are sole ly respon si ble for the con tents which do not neces sa ri ly repre sent the opi ni on of the ZEW.

show abstract

Section: Introductionmentioning

confidence: 99%

Risk Attitudes, Job Mobility and Subsequent Wage Growth During the Early Career

2017

View full text Add to dashboard Cite

show abstract

“…2 Conceptually, learning might di¤er across occupations because of level di¤erences in the variance of individual ability generated from non-random sorting into occupations or because the technology or tasks in each occupation a¤ect the speed at which employers learn. 3 The 1 An exception is Altonji (2005) who presents a framework in which the rate of employer learning depends on the skill level of the job to show how, in this environment, statistical discrimination at the time of hire a¤ects employment rates and wage growth, but he does not test the model empirically. In addition, Antonovics and Golan (2007), motivate the idea of "job shopping" within …rms using a model in which learning di¤ers across jobs.…”

Section: Introductionmentioning

confidence: 99%

“…3 The 1 An exception is Altonji (2005) who presents a framework in which the rate of employer learning depends on the skill level of the job to show how, in this environment, statistical discrimination at the time of hire a¤ects employment rates and wage growth, but he does not test the model empirically. In addition, Antonovics and Golan (2007), motivate the idea of "job shopping" within …rms using a model in which learning di¤ers across jobs. 2 Matching models, such as Jovanovic's (1979a) model, also generate increased wage dispersion with experience.…”

Section: Introductionmentioning

confidence: 99%

“…The analysis I use help in distinguishing between the learning and occupational matching hypotheses. 3 Consider the following example: Suppose that the true cross-sectional productivity variance in occu-1 main contribution of the paper is to provide evidence that initial occupational assignments are associated with di¤erent learning parameters. The occupational analysis provides several pieces of evidence that distinguish the learning hypothesis from other competing hypotheses, such as on-the-job training (OJT), and improved match quality with experience.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Does Employer Learning Vary by Occupation?

Mansour

2012

Journal of Labor Economics

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract Models in which employers learn about the productivity of young workers, such as Altonji and Pierret (2001), have two principal implications: First, the distribution of wages becomes more dispersed as a cohort of workers gains experience; second, the coe¢ cient on a variable that employers initially do not observe, such as the Armed Forces Quali…cation Test (AFQT) score, grows with experience. If employers'learning varies signi…cantly across occupations, both of these indicators of learning should covary positively across groups de…ned by a worker's occupational assignment at labor market entry. This paper tests this implication of the employer learning model using data from the NLSY and CPS. I …nd that occupations with high growth in the variance of residual wages over the …rst ten years of the worker's career are also the occupations with high growth in the AFQT coe¢ cient, con…rming the learning perspective. Interestingly, occupations that my analysis characterizes as having a low level of employer learning are not occupations where employers know little about the worker after ten years of experience; instead they appear to be occupations where employers have already learned about the worker's AFQT score at the time of hire. I provide several pieces of evidence that occupational assignment a¤ects the learning process independently from education and that the results are not driven by workers'occupational mobility. Terms of use: Documents inJEL Codes: J24, J31, J71, J62

show abstract

“…Their paper treated occupations as lotteries, where the lotteries were affected by the choice of major. In this paper, we follow a more conventional route and treat occupations as choices, consistent with, e.g., Miller (1984), Siow (1984), Keane and Wolpin (1997), Antonovics and Golan (2012) and van der Klaauw (2012).…”

mentioning

confidence: 99%

Recovering Ex Ante Returns and Preferences for Occupations Using Subjective Expectations Data

et al. 2014

View full text Add to dashboard Cite

We show that data on subjective expectations, especially on outcomes from counterfactual choices and choice probabilities, are a powerful tool in recovering ex ante treatment effects as well as preferences for different treatments. In this paper we focus on the choice of occupation, and use elicited beliefs from a sample of male undergraduates at Duke University. By asking individuals about potential earnings associated with counterfactual choices of college majors and occupations, we can recover the distribution of the ex ante monetary returns to particular occupations, and how these returns vary across majors. We then propose a model of occupational choice which allows us to link subjective data on earnings and choice probabilities with the non-pecuniary preferences for each occupation. We find large differences in expected earnings across occupations, and substantial heterogeneity across individuals in the corresponding ex ante returns. However, while sorting across occupations is partly driven by the ex ante monetary returns, non-monetary factors play a key role in this decision. Finally, our results point to the existence of sizable complementarities between college major and occupations, both in terms of earnings and non-monetary benefits.

show abstract

Experimentation and Job Choice

Abstract: This paper examines optimal job choices when jobs differ in the rate at which

Cited by 64 publications

References 25 publications

Risk Attitudes, Job Mobility and Subsequent Wage Growth During the Early Career

Risk Attitudes, Job Mobility and Subsequent Wage Growth During the Early Career

Does Employer Learning Vary by Occupation?

Recovering Ex Ante Returns and Preferences for Occupations Using Subjective Expectations Data

Contact Info

Product

Resources

About