College Choice, Selection and Allocation Mechanisms: A Structural Empirical Analysis
We use rich microeconomic data on performance and choices of students at college entry to analyze interactions between the selection mechanism, eliciting college preferences through exams, and the allocation mechanism. We set up a framework in which success probabilities and student preferences are shown to be identified from data on their choices and their exam grades under exclusion restrictions and support conditions. The counterfactuals we consider balance the severity of congestion and the quality of the match between schools and students. Moving to deferred acceptance or inverting the timing of choices and exams are shown to increase welfare. Redistribution among students and among schools is also sizeable in all counterfactual experiments.
Should Forecasters Use Real‐time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence
German Economic Review,
In this paper, we investigate whether differences exist among forecasts using real‐time or latest‐available data to predict gross domestic product (GDP). We employ mixed‐frequency models and real‐time data to reassess the role of surveys and financial data relative to industrial production and orders in Germany. Although we find evidence that forecast characteristics based on real‐time and final data releases differ, we also observe minimal impacts on the relative forecasting performance of indicator models. However, when obtaining the optimal combination of soft and hard data, the use of final release data may understate the role of survey information.
09.07.2019 • 17/2019
IWH rated "very good" and recommended for further funding
The Halle Institute for Economic Research (IWH) – Member of the Leibniz Association has been providing remarkable research and policy advice services for many years and should therefore continue to receive joint basic funding by Federal government and the Länder in future. This was the conclusion of today's meeting of the Senate of the Leibniz Association. At the end of the evaluation, the Institute was rated "very good" in all areas.
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An Evaluation of Early Warning Models for Systemic Banking Crises: Does Machine Learning Improve Predictions?
IWH Discussion Papers,
This paper compares the out-of-sample predictive performance of different early warning models for systemic banking crises using a sample of advanced economies covering the past 45 years. We compare a benchmark logit approach to several machine learning approaches recently proposed in the literature. We find that while machine learning methods often attain a very high in-sample fit, they are outperformed by the logit approach in recursive out-of-sample evaluations. This result is robust to the choice of performance measure, crisis definition, preference parameter, and sample length, as well as to using different sets of variables and data transformations. Thus, our paper suggests that further enhancements to machine learning early warning models are needed before they are able to offer a substantial value-added for predicting systemic banking crises. Conventional logit models appear to use the available information already fairly effciently, and would for instance have been able to predict the 2007/2008 financial crisis out-of-sample for many countries. In line with economic intuition, these models identify credit expansions, asset price booms and external imbalances as key predictors of systemic banking crises.
Zu den rentenpolitischen Plänen im Koalitionsvertrag 2018 von CDU, CSU und SPD: Konsequenzen, Finanzierungsoptionen und Reformbedarf
Zeitschrift für Wirtschaftspolitik,
In the coalition agreement from February 7, 2018, the new German federal government drafts its public pension policy, which has to be evaluated against the background of demographic dynamics in Germany. In this paper, the consequences of public pensions related policy measures for the German public pension insurance are illustrated using a simulation model. In the long run, the intended extensions of benefits would lead to an increase in the contribution rate to the German public pension insurance of about two and a half percentage points. Referring to pension systems of other countries, we discuss measures in order to limit this increase in the contribution rate.
Inference in Structural Vector Autoregressions when the Identifying Assumptions are not Fully Believed: Re-evaluating the Role of Monetary Policy in Economic Fluctuations
Journal of Monetary Economics,
Point estimates and error bands for SVARs that are set identified are only justified if the researcher is persuaded that some parameter values are a priori more plausible than others. When such prior information exists, traditional approaches can be generalized to allow for doubts about the identifying assumptions. We use information about both structural coefficients and impacts of shocks and propose a new asymmetric t-distribution for incorporating information about signs in a nondogmatic way. We apply these methods to a three-variable macroeconomic model and conclude that monetary policy shocks are not the major driver of output, inflation, or interest rates.
IWH hosts award-winning US economist The renowned Max Planck-Humboldt Research Award 2019 goes to Ufuk Akcigit,...
Gender Equality & Anti-Discrimination
Equal Opportunities at IWH ...
Joint Economic Forecast
Joint Economic Forecast The joint economic forecast is an instrument for evaluating...
Establishing Evidence-based Evaluation Methods for Subsidy Programmes in Germany (EVA-KULT)
Establishing Evidence-based Evaluation Methods for Subsidy Programmes in Germany (EVA-KULT) ...