Why Is the Roy-Borjas Model Unable to Predict International Migrant Selection on Education? Evidence from Urban and Rural Mexico
Stefan Leopold, Jens Ruhose, Simon Wiederhold
World Economy,
forthcoming
Abstract
The Roy-Borjas model predicts that international migrants are less educated than nonmigrants because the returns to education are generally higher in developing (migrant-sending) than in developed (migrant-receiving) countries. However, empirical evidence often shows the opposite. Using the case of Mexico-U.S. migration, we show that this inconsistency between predictions and empirical evidence can be resolved when the human capital of migrants is assessed using a two-dimensional measure of occupational skills rather than by educational attainment. Thus, focusing on a single skill dimension when investigating migrant selection can lead to misleading conclusions about the underlying economic incentives and behavioral models of migration.
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Forecast Combination and Interpretability Using Random Subspace
Boris Kozyrev
IWH Discussion Papers,
No. 21,
2024
Abstract
This paper investigates forecast aggregation via the random subspace regressions method (RSM) and explores the potential link between RSM and the Shapley value decomposition (SVD) using the US GDP growth rates. This technique combination enables handling high-dimensional data and reveals the relative importance of each individual forecast. First, it is possible to enhance forecasting performance in certain practical instances by randomly selecting smaller subsets of individual forecasts and obtaining a new set of predictions based on a regression-based weighting scheme. The optimal value of selected individual forecasts is also empirically studied. Then, a connection between RSM and SVD is proposed, enabling the examination of each individual forecast’s contribution to the final prediction, even when there is a large number of forecasts. This approach is model-agnostic (can be applied to any set of predictions) and facilitates understanding of how the aggregated prediction is obtained based on individual forecasts, which is crucial for decision-makers.
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Safety Net or Helping Hand? The Effect of Job Search Assistance and Compensation on Displaced Workers
Daniel Fackler, Jens Stegmaier, Richard Upward
IWH Discussion Papers,
No. 18,
2023
Abstract
We provide the first systematic evidence on the effectiveness of a contested policy in Germany to help displaced workers. So-called “transfer companies” (Transfergesellschaften) employ displaced workers for a fixed period, during which time workers are provided with job-search assistance and are paid a wage which is a substantial fraction of their pre-displacement wage. Using rich and accurate data on workers’ employment patterns before and after displacement, we compare the earnings and employment outcomes of displaced workers who entered transfer companies with those that did not. Workers can choose whether or not to accept a position in a transfer company, and therefore we use the availability of a transfer company at the establishment level as an IV in a model of one-sided compliance. Using an event study, we find that workers who enter a transfer company have significantly worse post-displacement outcomes, but we show that this is likely to be the result of negative selection: workers who lack good outside opportunities are more likely to choose to enter the transfer company. In contrast, ITT and IV estimates indicate that the use of a transfer company has a positive and significant effect on employment rates five years after job loss, but no significant effect on earnings. In addition, the transfer company provides significant additional compensation to displaced workers in the first 12 months after job loss.
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Why Is the Roy-Borjas Model Unable to Predict International Migrant Selection on Education? Evidence from Urban and Rural Mexico
Stefan Leopold, Jens Ruhose, Simon Wiederhold
Abstract
The Roy-Borjas model predicts that international migrants are less educated than nonmigrants because the returns to education are generally higher in developing (migrant-sending) than in developed (migrant-receiving) countries. However, empirical evidence often shows the opposite. Using the case of Mexico-U.S. migration, we show that this inconsistency between predictions and empirical evidence can be resolved when the human capital of migrants is assessed using a two-dimensional measure of occupational skills rather than by educational attainment. Thus, focusing on a single skill dimension when investigating migrant selection can lead to misleading conclusions about the underlying economic incentives and behavioral models of migration.
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Where STEM Graduates Stem From? The Intergenerational Transmission of Comparative Skill Advantages
Eric A. Hanushek, Babs Jacobs, Guido Schwerdt, Rolf van der Velden, Stan Vermeulen, Simon Wiederhold
VoxEU,
Juni
2023
Abstract
The standard economic model of occupational choice following a basic Roy model emphasizes individual selection and comparative advantage, but the sources of comparative advantage are not well understood. We employ a unique combination of Dutch survey and registry data that links math and language skills across generations and permits analysis of the intergenerational transmission of comparative skill advantages. Exploiting within-family between-subject variation in skills, we show that comparative advantages in math of parents are significantly linked to those of their children. A causal interpretation follows from a novel IV estimation that isolates variation in parent skill advantages due to their teacher and classroom peer quality. Finally, we show the strong influence of family skill transmission on children’s choices of STEM fields.
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Where Do STEM Graduates Stem from? The Intergenerational Transmission of Comparative Skill Advantages
Eric A. Hanushek, Babs Jacobs, Guido Schwerdt, Rolf van der Velden, Stan Vermeulen, Simon Wiederhold
IWH Discussion Papers,
No. 13,
2023
Abstract
The standard economic model of occupational choice following a basic Roy model emphasizes individual selection and comparative advantage, but the sources of comparative advantage are not well understood. We employ a unique combination of Dutch survey and registry data that links math and language skills across generations and permits analysis of the intergenerational transmission of comparative skill advantages. Exploiting within-family between-subject variation in skills, we show that comparative advantages in math of parents are significantly linked to those of their children. A causal interpretation follows from a novel IV estimation that isolates variation in parent skill advantages due to their teacher and classroom peer quality. Finally, we show the strong influence of family skill transmission on children’s choices of STEM fields.
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Evidence-based Support for Adaptation Policies in Emerging Economies
Maximilian Banning, Anett Großmann, Katja Heinisch, Frank Hohmann, Christian Lutz, Christoph Schult
Low Carbon Economy,
No. 1,
2023
Abstract
Climate change is increasingly evident, and the design of effective climate adaptation policies is important for regional and sectoral economic growth. We propose different modelling approaches to quantify the socio-economic impacts of climate change on three vulnerable countries (Kazakhstan, Georgia, and Vietnam) and design specific adaptations. We use a Dynamic General Equilibrium (DGE) model for Vietnam and an economy-energy-emission (E3) model for the other two countries. Our simulations until 2050 show that selected adaptation measures, in particular in the agricultural sector, have positive implications for GDP. However, some adaptation measures can even increase greenhouse gas emissions. Focusing on GDP alone can lead to welfare-reducing policy decisions.
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BigTech Credit, Small Business, and Monetary Policy Transmission: Theory and Evidence
Yiping Huang, Xiang Li, Han Qiu, Dan Su, Changhua Yu
IWH Discussion Papers,
No. 18,
2022
Abstract
This paper provides both theoretical and empirical analyses of the differences between BigTech lenders and traditional banks in response to monetary policy changes. Our model integrates Knightian uncertainty into portfolio selection and posits that BigTech lenders possess a diminishing informational advantage with increasing firm size, resulting in reduced ambiguity when lending to smaller firms. The model suggests that the key distinction between BigTech lenders and traditional banks in response to shifts in funding costs, triggered by monetary policy changes, is more evident at the extensive margin rather than the intensive margin, particularly during periods of easing monetary policy. Using a micro-level dataset of small business loans from both types of lenders, we provide empirical support for our theoretical propositions. Our results show that BigTech lenders are more responsive in establishing new lending relationships in an easing monetary policy environment, while the differences in loan amounts are not statistically significant. We also discuss other loan terms and the implications of regulatory policies.
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