Big Data (BD) and the analysis thereof (i.e., Big Data Analytics, BDA) is considered of increasing importance, not only for big (tech) companies but also for small/medium-sized companies and, in particular, for new ventures. Despite or precisely due to its generally presumed relevance, the question arises whether applying BDA leads to better firm performance. Based on a large, representative sample of 3,700 German start-ups, we specifically study the adoption of BDA among start-ups and analyze its economic effects using various short- and longer-term performance measures. We show that start-ups adopting BDA significantly differ from non-adopters regarding their founders' age, education, team composition, and experience. Accounting for these differences, we then investigate the effect of adopting BDA on the new ventures' operating costs, sales, profits, survival rate, and (employee) growth. Our findings show that using BDA does not lead to a competitive advantage in terms of the classical short-term performance measures but is rather associated with greater sales/profit uncertainty, higher (personnel) costs, and a higher probability of failure. Yet, the increased risk of adopting BDA is at the same time compensated by a prospect for higher excess performance -- BDA-adopting start-ups perform significantly better than their peers at the 90%-quantile -- as well as by better expected longer-term performance, as measured by the start-ups' growth and by their ability to secure Venture Capital (VC). Our findings support the concept of a few Schumpeterian Entrepreneurs who adopt technology at the frontier of innovation and found high-risk start-ups with the prospect of high rewards.
Archives: IAB-Veranstaltungen
The costs and benefits of work after the retirement
Retirement marks a significant life transition, signaling the end of one's active work engagement and the beginning of a new phase of life. In the best-case scenario post-retirement life is characterized by increased time spend with friends and family, and a purpose in life that is perceived as meaningful. The reduced work load should be associated with improved health, because sources of physical and psychological stress should have far less impact. However, reality paints a different picture: The research on retirement shows a lot variation in retirement experiences, financial well-being, mental and physical health, social engagement, and overall life satisfaction.
The importance of pre-retirement occupations on individuals' lives cannot be overstated. However, the impact of occupations on people’s lives does not end with their retirement. Hence, I will propose a new perspective on employment and occupations by focusing on the retirees’ late life and end of life. In my presentation I will provide the theoretical foundations, why occupations (should) have a lasting impact. I will present a data source with which such analyses could be done and discuss outcome variables of interest. Examples for occupation-specific outcomes of interest are: years of life remaining after retirement, years in good health after retirement, years spend in loneliness, wealth, poverty, depression, political attitudes, decrease in cognitive capabilities, social networks, free-time activities, volunteering, housing, life satisfaction, etc.
From a policy perspective, understanding how different occupations influence post-retirement lives can inform retirement planning initiatives and social safety nets as well as occupation-specific training and safety regulations. On an individual level, insights gained from such research can assist individuals in making informed decisions about their vocational aspirations, careers, planned changes of occupations, retirement age, and financial preparations.
Quantifying Non-Sampling Variation: College Quality and the Garden of Forking Paths
Empirical economics papers report standard errors to take into account uncertainty associated with sampling variation but rarely consider non-sampling variation from researcher choices about measurement of key variables, functional form choice, identification strategy, and data set. In this paper, we review the literature on alternative methods for taking account of non-sampling variability, develop a typology of sources of non-sampling variation, and conduct an empirical exercise in which we estimate the relative and absolute importance of different types of non-sampling variation. The empirical exercise proceeds in the context of the literature that seeks to estimate the causal effect of college quality on educational and labor market outcomes.
The Dark Shadow of Benefit Reforms in the Open Economy
This paper analyzes the open-economy spillover effects of labor market reforms under incomplete insurance. Using microeconomic data, we document a boost in the tradable sector in the aftermath of the German Hartz IV reform. In our model, this phenomenon can be explained by an increase in household savings due to higher precautionary savings in response to the reduction in the generosity of unemployment insurance (Hartz IV). Besides reducing unemployment in the reforming country, lower unemployment benefits generate long-run negative consumption spillovers in a monetary union, which we call the dark shadow of labor market reforms. Our model can match various German trends post Hartz IV reform, such as: i) a lasting increase in net foreign asset position, ii) short-term expansion of the tradable sector relative to the non-tradable sector, and iii) continued depreciation of the real exchange rate. By contrast, simulations of German wage moderation result in qualitatively different open-economy effects that are not in line with the empirical patterns for Germany.
The Gender Wage Gap Among Those Born in 1958: A Matching Estimator Approach
Most studies estimating the gender wage gap rely on linear regression of log hourly earnings. Estimates often condition on potentially endogenous regressors such as labour market experience and family formation. Exploiting prospective data on a cohort born in 1958 we estimate the gender wage gap over the life-course between age 23 and 63, departing from the literature in two ways. First, we use matching estimators which are rarely used in the literature. Like regression analyses matching relies on observed data to recover the effect of gender on earnings, but by explicitly considering the issue of common support it is more transparent in its treatment of men as counterfactuals for women. We examine the importance of the common support issue for the size of the gender wage gap. Second, we condition on pre-labour market variables to avoid conditioning on endogenous choice variables, such as family formation, which are made, in part, with knowledge regarding one’s potential earnings. We argue our data are well-suited to the task because they contain a wide array of prospective data collected at birth, then at ages 7, 11 and 16, which might conceivably confound estimates of the GWG. In contrast to findings in the literature in which the regression-adjusted GWG is considerably smaller than the raw gap, we find differences in log hourly mean earnings between men and women are of roughly similar size and, in some cases, wider than raw gaps conditioning on pre-labour market variables. This is the case whether we use matching or linear estimation techniques. However, the PSM estimated GWG is above the raw gap when cohort members are in their 40s, 50s and 60s. The implication is that women have pre-labour market traits which reduce their earnings later in life relative to men. The gap follows an inverted-u shape over the life-course, reaching its maximum of around. .45 log points at age 42, after which it begins to decline, though it remains large among cohort members in their 60s.
Joint work with: Francesca Foliano, Heather Joshi, Bozena Wielgoszewska and David Wilkinson
Hiring and the Dynamics of the Gender Gap
In this study, we examine how the same vacating opportunity translates differently for male and female full-time workers. By utilizing matched employer-employee data from Germany, our empirical approach leverages 30,000 unforeseen worker deaths spanning from 1980 to 2016 which enables us to explore how firms react to exogenous vacancies. We find that when a position becomes vacant, female replacements have starting wages that are 20 log points lower compared to their male counterparts. Even after considering the pre-hire wage of replacement workers, half of this gap persists. The gender disparity in opportunities cannot be attributed to workload redistribution among other coworkers. Over time, the gap tends to widen on average and remains stable even for those who remain employed full-time in the subsequent five years after being hired.
Labor market beliefs and the gender wage gap
We study the role of labor market beliefs in the gender pay gap. We find that, on average, women expect to receive lower salaries than men and also expect to receive fewer offers when employed. Gender differences in expectations explain a sizable fraction of the residual gap in reservation wages. We estimate a partial equilibrium job search model that incorporates worker heterogeneity in beliefs about the wage offer distribution, arrival rates, and separation rate. Counterfactual exercises show that labor market beliefs play an important role in the gender wage gap, but matter little for the gender differences in welfare. Eliminating gender differences in the actual offer distribution, by contrast, decreases the gender gap in pay and welfare.
Urban Labor Markets and Local Income Inequality
Urban labor markets provide agglomeration advantages to workers and firms. However, the distributional consequences are not fully understood. Agglomeration benefits are unevenly shared among low- and high-skilled workers. At the same time, many large urban labor markets around the world have experienced strongly rising housing costs in recent decades, especially for renters and young first-time homebuyers, putting these groups at risk of being priced out of the local labor market. The workshop aims to bring together junior and senior researchers working on these and related issues and welcomes both empirical and theoretical contributions. The list of topic includes, but is not limited to
- Distributional consequences of agglomeration benefits
- Labor market outcomes and housing affordability
- Highly-local income inequality
- Spatial extent of local labor markets and commuting patterns
- Neighborhood effects and segregation
- Interactions between local housing and labor markets
International Workshop on Establishment Panel Analyses
Celebrating the 30th anniversary of the IAB Establishment Panel Survey, this workshop invites empirical contributions using either the IAB Establishment Panel, one of its derivatives (LPP/LIAB), or other matched employer-employee data. Research projects from all areas of labour market research are welcome, including personnel economics, sociology and economics of vocational education and training, industrial relations, or industrial economics. Papers may address research questions in any of these areas as well as methodological questions.
Equity and Efficiency of Childcare Subsidies: A Dynamic Structural Approach
Numerous governments provide income-contingent childcare subsidies. In this paper, we estimate the dynamic marginal efficiency cost of redistribution (MECR) associated with a large-scale program of this kind in Germany, and compare them with the MECR associated with the benchmark redistributive tool, the income tax. To do so, we integrate methods from public finance theory into a dynamic structural heterogeneous-household model of childcare demand and maternal labor supply. We also incorporate social mobility concerns into the MECR and find the MECR of the childcare subsidies to be significantly lower at the margin, suggesting that childcare subsidies are the more efficient redistributive tool.
