Expectation Formation, Financial Frictions, and Forecasting Performance of Dynamic Stochastic General Equilibrium Models
Oliver Holtemöller, Christoph Schult
Abstract
In this paper, we document the forecasting performance of estimated basic dynamic stochastic general equilibrium (DSGE) models and compare this to extended versions which consider alternative expectation formation assumptions and financial frictions. We also show how standard model features, such as price and wage rigidities, contribute to forecasting performance. It turns out that neither alternative expectation formation behaviour nor financial frictions can systematically increase the forecasting performance of basic DSGE models. Financial frictions improve forecasts only during periods of financial crises. However, traditional price and wage rigidities systematically help to increase the forecasting performance.
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Selection Versus Incentives in Incentive Pay: Evidence from a Matching Model
Shuo Xia
SSRN Working Papers,
2018
Abstract
Higher incentive pay is associated with better firm performance. I introduce a model of CEO-firm matching to disentangle the two confounding effects that drive this result. On one hand, higher incentive pay directly induces more effort; on the other hand, higher incentive pay indirectly attracts more talented CEOs. I find both effects are essential to explain the result, with the selection effect accounting for 12.7% of the total effect. The relative importance of the selection effect is the largest in industries with high talent mobility and in more recent years.
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Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment
Katja Heinisch, Rolf Scheufele
Empirical Economics,
Nr. 2,
2018
Abstract
In this paper, we investigate whether there are benefits in disaggregating GDP into its components when nowcasting GDP. To answer this question, we conduct a realistic out-of-sample experiment that deals with the most prominent problems in short-term forecasting: mixed frequencies, ragged-edge data, asynchronous data releases and a large set of potential information. We compare a direct leading indicator-based GDP forecast with two bottom-up procedures—that is, forecasting GDP components from the production side or from the demand side. Generally, we find that the direct forecast performs relatively well. Among the disaggregated procedures, the production side seems to be better suited than the demand side to form a disaggregated GDP nowcast.
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Predicting Earnings and Cash Flows: The Information Content of Losses and Tax Loss Carryforwards
Sandra Dreher, Sebastian Eichfelder, Felix Noth
Abstract
We analyse the relevance of losses, accounting information on tax loss carryforwards, and deferred taxes for the prediction of earnings and cash flows up to four years ahead. We use a unique hand-collected panel of German listed firms encompassing detailed information on tax loss carryforwards and deferred taxes from the tax footnote. Our out-of-sample predictions show that considering accounting information on tax loss carryforwards and deferred taxes does not enhance the accuracy of performance forecasts and can even worsen performance predictions. We find that common forecasting approaches that treat positive and negative performances equally or that use a dummy variable for negative performance can lead to biased performance forecasts, and we provide a simple empirical specification to account for that issue.
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Optimizing Policymakers' Loss Functions in Crisis Prediction: Before, Within or After?
Peter Sarlin, Gregor von Schweinitz
Abstract
Early-warning models most commonly optimize signaling thresholds on crisis probabilities. The expost threshold optimization is based upon a loss function accounting for preferences between forecast errors, but comes with two crucial drawbacks: unstable thresholds in recursive estimations and an in-sample overfit at the expense of out-of-sample performance. We propose two alternatives for threshold setting: (i) including preferences in the estimation itself and (ii) setting thresholds ex-ante according to preferences only. Given probabilistic model output, it is intuitive that a decision rule is independent of the data or model specification, as thresholds on probabilities represent a willingness to issue a false alarm vis-à-vis missing a crisis. We provide simulated and real-world evidence that this simplification results in stable thresholds and improves out-of-sample performance. Our solution is not restricted to binary-choice models, but directly transferable to the signaling approach and all probabilistic early-warning models.
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Internal Governance and Creditor Governance: Evidence from Credit Default Swaps
Stefano Colonnello
IWH Discussion Papers,
Nr. 6,
2017
Abstract
I study the relation between internal governance and creditor governance. A deterioration in creditor governance may increase the agency costs of debt and managerial opportunism at the expense of shareholders. I exploit the introduction of credit default swaps (CDS) as a negative shock to creditor governance. I provide evidence consistent with shareholders pushing for a substitution effect between internal governance and creditor governance. Following CDS introduction, CDS firms reduce managerial risk-taking incentives relative to other firms. At the same time, after the start of CDS trading, CDS firms increase managerial wealth-performance sensitivity, board independence, and CEO turnover performance-sensitivity relative to other firms.
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Should Forecasters Use Real-time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence
Katja Heinisch, Rolf Scheufele
Abstract
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 survey 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.
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27.01.2017 • 10/2017
IWH-Industrieumfrage zum Jahresauftakt 2017: Ostdeutsche Hersteller gehen nach Aufschwung im Jahr 2016 von weiterhin günstigen Geschäftsaussichten aus
Die vom IWH befragten rund 300 Unternehmen des Verarbeitenden Gewerbes Ostdeutschlands gehen nach einem erfolgreichen Geschäftsjahr 2016 zuversichtlich in das neue Jahr. Die Umsätze stiegen im Jahr 2016 meist stärker als vor einem Jahr von ihnen erwartet. Bei den Konsumgüterherstellern war die Umsatzentwicklung besonders erfreulich. In allen Sparten war die Industriekonjunktur mit viel Schwung in das Jahr 2016 gestartet und bremste erst im späteren Verlauf des Jahres etwas ab. Mit Blick auf das Jahr 2017 zeigt sich die überwiegende Mehrheit der befragten Unternehmen aber wieder optimistisch. Die Ertragslage konnte sich im Jahr 2016 im Vergleich zum Vorjahr zwar nicht weiter verbessern, jedoch schafften es mehr Unternehmen, aus der Verlustzone zu kommen. Die Exportunternehmen, die in den Jahren zuvor eine besonders gute Performance gezeigt hatten, konnten diesmal nicht durchweg überdurchschnittlichen glänzen. Das soll im Jahr 2017 wieder aufgeholt werden, wie Umsatz- und Beschäftigungspläne zeigen. Insbesondere die größeren ostdeutschen Industrieunternehmen planen häufig, ihren Personal-bestand zu erhöhen.
Birgit Schultz
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