Application Barriers and the Socioeconomic Gap in Child Care Enrollment
Henning Hermes, Philipp Lergetporer, Frauke Peter, Simon Wiederhold
Abstract
Why are children with lower socioeconomic status (SES) substantially less likely to be enrolled in child care? We study whether barriers in the application process work against lower-SES children — the group known to benefit strongest from child care enrollment. In an RCT in Germany with highly subsidized child care (N = 607), we offer treated families information and personal assistance for applications. We find substantial, equity-enhancing effects of the treatment, closing half of the large SES gap in child care enrollment. Increased enrollment for lower-SES families is likely driven by altered application knowledge and behavior. We discuss scalability of our intervention and derive policy implications for the design of universal child care programs.
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Behavioral Barriers and the Socioeconomic Gap in Child Care Enrollment
Henning Hermes, Philipp Lergetporer, Frauke Peter, Simon Wiederhold
Abstract
Children with lower socioeconomic status (SES) tend to benefit more from early child care, but are substantially less likely to be enrolled. We study whether reducing behavioral barriers in the application process increases enrollment in child care for lower-SES children. In our RCT in Germany with highly subsidized child care (n > 600), treated families receive application information and personal assistance for applications. For lower-SES families, the treatment increases child care application rates by 21 pp and enrollment rates by 16 pp. Higher-SES families are not affected by the treatment. Thus, alleviating behavioral barriers closes half of the SES gap in early child care enrollment.
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Robot Adoption at German Plants
Liuchun Deng, Verena Plümpe, Jens Stegmaier
Jahrbücher für Nationalökonomie und Statistik,
No. 3,
2024
Abstract
Using a newly collected dataset at the plant level from 2014 to 2018, we provide the first microscopic portrait of robotization in Germany and study the correlates of robot adoption. Our descriptive analysis uncovers five stylized facts: (1) Robot use is relatively rare. (2) The distribution of robots is highly skewed. (3) New robot adopters contribute substantially to the recent robotization. (4) Robot users are exceptional. (5) Heterogeneity in robot types matters. Our regression results further suggest plant size, high-skilled labor share, exporter status, and labor shortage to be strongly associated with the future probability of robot adoption.
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Can Mentoring Alleviate Family Disadvantage in Adolescence? A Field Experiment to Improve Labor-Market Prospects
Sven Resnjanskij, Jens Ruhose, Simon Wiederhold, Ludger Woessmann, Katharina Wedel
Journal of Political Economy,
No. 3,
2024
Abstract
We study a mentoring program that aims to improve the labor-market prospects of school-attending adolescents from disadvantaged families by offering them a university-student mentor. Our RCT investigates program effectiveness on three outcome dimensions that are highly predictive of later labor-market success: math grades, patience/social skills, and labor-market orientation. For low-SES adolescents, the mentoring increases a combined index of the outcomes by over half a standard deviation after one year, with significant increases in each dimension. Part of the treatment effect is mediated by establishing mentors as attachment figures who provide guidance for the future. Effects on grades and labor-market orientation, but not on patience/social skills, persist three years after program start. By that time, the mentoring also improves early realizations of school-to-work transitions for low-SES adolescents. The mentoring is not effective for higher-SES adolescents. The results show that substituting lacking family support by other adults can help disadvantaged children at adolescent age.
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European Real Estate Prices
Michael Koetter, Felix Noth
IWH Technical Reports,
No. 3,
2022
Abstract
Real estate markets are pivotal to financial stability given their dual role as the underlying asset of crucial financial products in financial systems, such as mortgage loans and asset-backed securities, and the primary source of household wealth alike. As such, they also play traditionally a crucial role for the transmission of monetary policy. Imbalances and sudden corrections in real estate markets have been the root cause of many financial crises over the last decades. But whereas some national, often survey-based indicators of real estate prices are provided by central banks and statistical offices, a comprehensive collection of purchase prices, rents, and proxies for the liquidity of European real estate markets is lacking. The IWH European Real Estate Index (EREI) seeks to fill this void for residential property. This technical report describes the gathering and processing of sale and rental prices for properties in 18 European countries. We provide the general scrapeing step in the section before describing country-specific details for each country in separated sub-sections.
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European Real Estate Index (EREI) 2025
Michael Koetter, Felix Noth, Fabian Wöbbeking
IWH Technical Reports,
No. 1,
2025
Abstract
This Technical Report documents the construction and coverage of the IWH European Real Estate Index (EREI). Since 2018, we have used machine-learning methods to collect monthly listings of residential real estate available for sale or rent in up to 20 European countries. The Technical Report documents the cleaning and selection process and describes the data regarding coverage, moments, and frequencies to construct the EREI.
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