Ms Dita Eckardt

Ms Dita Eckardt

PhD Candidate in Economics

Department of Economics

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English, French, German
Key Expertise
Labor Economics, Applied Microeconomics

About me

Research interests
Labor Economics, Applied Microeconomics (primary)
Public Economics, Applied Econometrics (secondary)

Job market paper
Are Chemists Good Bankers? Returns to the Match between Training and Occupation
Awarded the Royal Economic Society Junior Symposium Best Paper Award, April 2019

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Individuals are often trained in a specific field but work in another. This paper analyzes the returns to different training-occupation combinations. To this end, I use an administrative employment panel which contains the apprenticeship training for a large sample of workers in Germany. In this context, 70% of individuals with at least upper-secondary education hold apprenticeships, and 40% of these work in occupations they were not trained for. I combine the administrative data with historical data on occupation-specific vacancies to causally identify the returns. To implement the identification strategy, I set up an augmented Roy model and extend existing control function approaches to deal with selection in a two-stage, high-dimensional setting. The results suggest that workers trained in their current occupation earn 10-12% more than workers trained outside their occupation, and that not controlling for selection leads to substantial negative bias. I find considerable heterogeneity in the estimated returns and use task content data to show that returns to training-occupation combinations are decreasing in the task distance between training and occupation. Finally, I argue that ex-ante imperfect information may lead to training choices that are suboptimal ex-post and find that, as a result, 4-6% of wages are foregone for the average worker. Back-of-the-envelope calculations suggest that retraining programs could be very effective in addressing this friction.

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Publications and additional papers

Additional Working Paper:

Temporal-­Difference Estimation of Dynamic Discrete Choice Models (with K. Adusumilli)

Abstract: We propose a new algorithm to estimate the structural parameters in dynamic discrete choice models. The algorithm is based on the conditional choice probability approach, but uses the idea of Temporal-Difference learning from the Reinforcement Learning literature to estimate the different terms in the value functions. In estimating these terms with functional approximations using basis functions, our approach has the advantage of naturally allowing for continuous state spaces. Furthermore, it does not require specification of transition probabilities, and even estimation of choice probabilities can be avoided using a recursive procedure. Computationally, our algorithm only requires a low-dimensional matrix inversion. We find that it is substantially faster than existing approaches when the finite dependence property does not hold, and comparable in speed to approaches that exploit this property. For the estimation of dynamic games, our procedure does not require integrating over the actions of other players, which further heightens the computational advantage. We show that our estimator is consistent, and efficient under discrete state spaces. In settings with continuous states, we propose locally robust corrections in order to achieve parametric rates of convergence. Preliminary Monte Carlo simulations confirm the workings of our algorithm.

Research In Progress:

Training, Occupations, and the Effects of Graduating in a Recession

Abstract: A large body of evidence shows that labor market entry conditions have persistent effects on careers of graduates in a variety of settings. This project studies the effects of adverse entry conditions on apprentices. To this end, I use an administrative employment panel which contains the apprenticeship training for a large sample of workers in Germany, a context in which 70% of individuals with at least upper-secondary education hold apprenticeships. I then use variation in the local unemployment rate at time of graduation to study the effects of entry conditions on wages. Preliminary results suggest that apprentices suffer large initial wage losses when graduating in a recession which gradually fall and fully disappear after ten years of work experience. These effects display important heterogeneity, with higher-paying trainings generally suffering less. One underlying mechanism appears to be the selection of workers into occupations. Apprentices graduating in a recession, and particularly those trained in lower-paying occupations, are significantly less likely to start work in their training occupation, which in turn leads to substantial negative effects on wages. These results have important implications for policies aimed at mitigating the effects of adverse labor market entry conditions for young workers.

Worker Retraining Programs (with E. Ilzetzki)

Abstract: Skilled labor shortages during World War II were filled largely by unexperienced workers coming from unemployment, entrants into the workforce (women, youths), or workers transitioning from other occupations (e.g. agriculture). The U.S. War Manpower Commission (WMC) had a number of programs to train workers and help workers relocate to other regions to address these shortages. We are currently digitizing archival resources to investigate the effectiveness of these public programs in addressing mismatches between employers’ needs and the skills of the extant workforce. Modern sectoral transformation due to technology and trade has spurred renewed policy interest in worker retraining. In this regard, World War II can be viewed as a large, sudden, (albeit partly transient) sectoral transformation that created a mismatch between labor demand and the human capital of the extant labor force. Investigating what worked (and what didn’t) in the government’s attempts to address this mismatch may shed light on these modern policy questions, and help gain a better understanding of the labor market’s matching function more generally. There was some local variation in exposure to these job training programs that we expect will allow identification of their effects during World War II.


Placement Officer
Professor Mark Schankerman

Professor Alan Manning
Dr Johannes Spinnewijn

Professor Alan Manning
Dr Johannes Spinnewijn
Professor John Van Reenen

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+44 (0)7708091282

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Department of Economics,
London School of Economics and Political Science,
Houghton Street, London WC2A 2AE