“…See http://www.statistik.at/web_de/statistiken/wirtschaft/produktion_und_bauwesen/konjunkturdaten/index.html. SeeHuber et al (2017) for corroborating macroeconomic evidence of relatively stable employment compared to output in the recent economic crisis in Austria.…”
To estimate demand for labor, we use a combination of detailed employment data and the outcomes of procurement auctions, and compare the employment of the winner of an auction with the employment of the second ranked firm (i.e. the runner-up firm). Assuming similar ex-ante winning probabilities for both firms, we may view winning an auction as an exogenous shock to a firm's production and its demand for labor. We utilize daily data from almost 900 construction firms and about 3,000 auctions in Austria in the time period 2006 until 2009. Our main results show that the winning firm significantly increases labor demand in the weeks following an auction but only in the years before the recent economic crisis. It employs about 80 workers more after the auction than the runner-up firm. Most of the adjustment takes place within one month after the demand shock. Winners predominantly fire fewer workers after winning than runner-up firms. In the crisis, however, firms do not employ more workers than their competitors after winning an auction. We discuss explanations like labor hoarding and productivity improvements induced by the crisis as well discuss implications for fiscal and stimulus policy in the crisis.
“…See http://www.statistik.at/web_de/statistiken/wirtschaft/produktion_und_bauwesen/konjunkturdaten/index.html. SeeHuber et al (2017) for corroborating macroeconomic evidence of relatively stable employment compared to output in the recent economic crisis in Austria.…”
To estimate demand for labor, we use a combination of detailed employment data and the outcomes of procurement auctions, and compare the employment of the winner of an auction with the employment of the second ranked firm (i.e. the runner-up firm). Assuming similar ex-ante winning probabilities for both firms, we may view winning an auction as an exogenous shock to a firm's production and its demand for labor. We utilize daily data from almost 900 construction firms and about 3,000 auctions in Austria in the time period 2006 until 2009. Our main results show that the winning firm significantly increases labor demand in the weeks following an auction but only in the years before the recent economic crisis. It employs about 80 workers more after the auction than the runner-up firm. Most of the adjustment takes place within one month after the demand shock. Winners predominantly fire fewer workers after winning than runner-up firms. In the crisis, however, firms do not employ more workers than their competitors after winning an auction. We discuss explanations like labor hoarding and productivity improvements induced by the crisis as well discuss implications for fiscal and stimulus policy in the crisis.
“…However, this comes at the disadvantage of discontinuities of the distribution of g it at -2 and 2. Among others, Huber et al (2017) noted the econometric problems when applying simple (employment weighted) OLS to firm-level growth rates (Davis et al, 1996), as well as Tobit estimations. They propose an alternative maximum likelihood estimator that treats continuing firms, entrants and exiting firms separately, allowing for consistent estimates of the determinants of net job creation and aggregate average marginal effects for specific groups of firms.…”
Section: Empirical Modelmentioning
confidence: 99%
“…Equation ( 4) reveals that in applying the growth rate by Davis et al (2016) it is possible to separately estimate models for entry, exit and continuing firms, which can then be added together using (4) as in Huber et al (2017).…”
Section: Empirical Modelmentioning
confidence: 99%
“…The empirical analysis is based on the Austrian Social Security Database (ASSD), a widely used administrative data set (seeZweimüller et al, 2009, for a detaileddescription and Fink et al, 2010 illustrating how firm information can be extracted) in empirical research (see, e. g.,Card et al, 2007;Del Bono et al, 2012;Huber and Pfaffermayr, 2010;Huber et al, 2017). The dataset covers all firm-worker links in the form of labor market histories based on social security contributions in Austria between 1972 and 2018.…”
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