Austrian Social Security Database

Zweimüller, Josef; Winter‐Ebmer, Rudolf; Lalive, Rafael; Kühn, Andreas; Wuellrich, Jean-Philippe; Ruf, Oliver; Büchi, Simon

doi:10.2139/ssrn.1399350

Cited by 102 publications

(85 citation statements)

References 2 publications

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“…More precisely, we chose the most likely match by first ensuring consistency of the industry classification, second ensuring consistency of the type of employment (blue -vs. white-collar), and finally, if the match was still ambiguous, we simply chose the longest employment spell in question. 13 The following figures highlight the high accident rates of our subgroup (all refer to the year 2000).…”

Section: Datamentioning

confidence: 98%

“…Since we assume that q −q γ is increasing in q, there is a unique value for q s that satisfies equation (13). For q < q s the gain in safety (q s − q s γ )(α w + α f ) due to the investment is too small to cover the cost γ.…”

Section: Lemma 2 It Is Socially Optimal To Invest In Safety Measures mentioning

confidence: 99%

“…In this sample, 97.8 % of occupational accidents observed in the AUVA data could be matched to a corresponding employment record in the ASSD data. 13 In the empirical analysis we work with longitudinal 12 Note, however, that 3.4 % workplace accidents cannot be matched unambiguously. This occurs when an individual holds more than one job.…”

Section: Datamentioning

confidence: 99%

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Recessions are bad for workplace safety

Boone¹,

Ours²,

Wuellrich³

et al. 2011

Journal of Health Economics

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Workplace accidents are an important economic phenomenon. Yet, the pro-cyclical fluctuations in workplace accidents are not well understood. They could be related to fluctuations in effort and working hours, but workplace accidents may also be affected by reporting behavior. Our paper uses unique data on workplace accidents from an Austrian matched worker-firm dataset to study in detail how economic incentives affect workplace accidents. We find that workers who reported an accident in a particular period of time are more likely to be fired later on. And, we find support for the idea that recessions influence the reporting of moderate workplace accidents: if workers think the probability of dismissals at the firm level is high, they are less likely to report a moderate workplace accident.

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Section: Datamentioning

confidence: 98%

Section: Lemma 2 It Is Socially Optimal To Invest In Safety Measures mentioning

confidence: 99%

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Recessions are bad for workplace safety

Boone¹,

Ours²,

Wuellrich³

et al. 2011

Journal of Health Economics

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“…Our empirical analysis is based on administrative register data from the Austrian Social Security Database (ASSD), which combines detailed longitudinal information on employment and earnings of all private sector workers in Austria (Zweimüller et al, 2009). The data set includes the universe of private sector workers in Austria covered by the social security system.…”

Section: Data Descriptionmentioning

confidence: 99%

Analysing plant closure effects using time-varying mixture-of-experts Markov chain clustering

Frühwirth‐Schnatter¹,

Pittner²,

Wéber³

et al. 2018

Ann. Appl. Stat.

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In this paper, we study data on discrete labor market transitions from Austria. In particular, we follow the careers of workers who experience a job displacement due to plant closure and observe -over a period of forty quarters -whether these workers manage to return to a steady career path. To analyse these discrete-valued panel data, we develop and apply a new method of Bayesian Markov chain clustering analysis based on inhomogeneous first order Markov transition processes with time-varying transition matrices. In addition, a mixture-of-experts approach allows us to model the prior probability to belong to a certain cluster in dependence of a set of covariates via a multinomial logit model. Our cluster analysis identifies five career patterns after plant closure and reveals that some workers cope quite easily with a job loss whereas others suffer large losses over extended periods of time.

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“…As in the U.S., the Austrian UI system specifies a benefit level that is proportional to earnings in a base period prior to job loss, subject to a minimum and maximum. We study the effects of the kinks at the minimum and maximum benefit levels, using data on a large sample of jobless spells from the Austrian Social Security Database (see Zweimüller et al (2009)). Simple plots of the data show relatively strong visual evidence of kinks in the relationship between base period earnings and the durations of joblessness at both kink points.…”

Section: Introductionmentioning

confidence: 99%

Inference on Causal Effects in a Generalized Regression Kink Design

et al. 2015

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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. www.econstor.eu Terms of use: Documents in D I S C U S S I O N P A P E R S E R I E S ABSTRACTInference on Causal Effects in a Generalized Regression Kink Design * We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. This design arises in many institutional settings where a policy variable (such as weekly unemployment benefits) is determined by an observed but potentially endogenous assignment variable (like previous earnings). We provide new results on identification and estimation for these settings, and apply our results to obtain estimates of the elasticity of joblessness with respect to UI benefit rates. We characterize a broad class of models in which a sharp "Regression Kink Design" (RKD, or RK Design) identifies a readily interpretable treatment-on-the-treated parameter (Florens et al. (2008)). We also introduce a "fuzzy regression kink design" generalization that allows for omitted variables in the assignment rule, noncompliance, and certain types of measurement errors in the observed values of the assignment variable and the policy variable. Our identifying assumptions give rise to testable restrictions on the distributions of the assignment variable and predetermined covariates around the kink point, similar to the restrictions delivered by Lee (2008) for the regression discontinuity design. We then use a fuzzy RKD approach to study the effect of unemployment insurance benefits on the duration of joblessness in Austria, where the benefit schedule has kinks at the minimum and maximum benefit level. Our preferred estimates suggest that changes in UI benefit generosity exert a relatively large effect on the duration of joblessness of both low-wage and high-wage UI recipients in Austria. JEL Classification:C13, C14, C31

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Austrian Social Security Database

Cited by 102 publications

References 2 publications

Recessions are bad for workplace safety

Recessions are bad for workplace safety

Analysing plant closure effects using time-varying mixture-of-experts Markov chain clustering

Inference on Causal Effects in a Generalized Regression Kink Design

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