IWH-DPE Call for Applications – Fall 2020 Intake
Vacancy The Halle Institute for Economic Research (IWH) is one of Germany’s leading economic research institutes. The IWH focuses on research in macroeconomics, financial…
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IWH-DPE Call for Applications – Fall 2020 Intake
Vacancy The Halle Institute for Economic Research (IWH) is one of Germany’s leading economic research institutes. The IWH focuses on research in macroeconomics, financial…
See page
Competition and Moral Behavior: A Meta-Analysis of Forty-Five Crowd-Sourced Experimental Designs
Anna Dreber, Felix Holzmeister, Sabrina Jeworrek, Magnus Johannesson, Joschka Waibel, Utz Weitzel, et al.
Proceedings of the National Academy of Sciences of the United States of America (PNAS),
No. 23,
2023
Abstract
Does competition affect moral behavior? This fundamental question has been debated among leading scholars for centuries, and more recently, it has been tested in experimental studies yielding a body of rather inconclusive empirical evidence. A potential source of ambivalent empirical results on the same hypothesis is design heterogeneity—variation in true effect sizes across various reasonable experimental research protocols. To provide further evidence on whether competition affects moral behavior and to examine whether the generalizability of a single experimental study is jeopardized by design heterogeneity, we invited independent research teams to contribute experimental designs to a crowd-sourced project. In a large-scale online data collection, 18,123 experimental participants were randomly allocated to 45 randomly selected experimental designs out of 95 submitted designs. We find a small adverse effect of competition on moral behavior in a meta-analysis of the pooled data. The crowd-sourced design of our study allows for a clean identification and estimation of the variation in effect sizes above and beyond what could be expected due to sampling variance. We find substantial design heterogeneity—estimated to be about 1.6 times as large as the average standard error of effect size estimates of the 45 research designs—indicating that the informativeness and generalizability of results based on a single experimental design are limited. Drawing strong conclusions about the underlying hypotheses in the presence of substantive design heterogeneity requires moving toward much larger data collections on various experimental designs testing the same hypothesis.
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Hedge Fund Activism and Internal Control Weaknesses
David Folsom, Iftekhar Hasan, Yinjie (Victor) Shen, Fuzhao Zhou
China Accounting and Finance Review,
No. 4,
2022
Abstract
Purpose: The aim of the paper is to investigate the associations between hedge fund activism and corporate internal control weaknesses.
Design/methodology/approach: In this paper, the authors identify hedge fund activism events using 13D filings and news search. After matching with internal control related information from Audit Analytics, the authors utilize ordinary least square (OLS) and propensity score matching (PSM) to analyze the data.
Findings: The authors find that after hedge fund activism, target firms report additional internal control weaknesses, and these identified internal control weaknesses are remediated in subsequent years, leading to better financial-reporting quality.
Originality/value: The findings indicate that both managers and activists have incentives to develop a stronger internal control environment after targeting.
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05.08.2021 • 21/2021
IWH Bankruptcy Update: Bankruptcies in Germany Fall to an All-time Low
The number of corporate bankruptcies in Germany fell to a historic low in July, and are not anticipated to trend higher in August, according to IWH’s leading indicators. The IWH Bankruptcy Update, published by the Halle Institute for Economic Research (IWH), provides monthly statistics on corporate bankruptcies in Germany.
Steffen Müller
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Should Forecasters Use Real‐time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence
Katja Heinisch, Rolf Scheufele
German Economic Review,
No. 4,
2019
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 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.
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For How Long Do IMF Forecasts of World Economic Growth Stay Up-to-date?
Katja Heinisch, Axel Lindner
Applied Economics Letters,
No. 3,
2019
Abstract
This study analyses the performance of the International Monetary Fund (IMF) World Economic Outlook output forecasts for the world and for both the advanced economies and the emerging and developing economies. With a focus on the forecast for the current year and the next year, we examine the durability of IMF forecasts, looking at how much time has to pass so that IMF forecasts can be improved by using leading indicators with monthly updates. Using a real-time data set for GDP and for indicators, we find that some simple single-indicator forecasts on the basis of data that are available at higher frequency can significantly outperform the IMF forecasts as soon as the publication of the IMF’s Outlook is only a few months old. In particular, there is an obvious gain using leading indicators from January to March for the forecast of the current year.
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Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment
Katja Heinisch, Rolf Scheufele
Empirical Economics,
No. 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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Attracting Early-Stage Investors: Evidence From a Randomized Field Experiment
Shai B. Bernstein, Arthur Korteweg, Kevin Laws
Journal of Finance,
No. 2,
2017
Abstract
This paper uses a randomized field experiment to identify which start-up characteristics are most important to investors in early-stage firms. The experiment randomizes investors? information sets of fund-raising start-ups. The average investor responds strongly to information about the founding team, but not to firm traction or existing lead investors. We provide evidence that the team is not merely a signal of quality, and that investing based on team information is a rational strategy. Together, our results indicate that information about human assets is causally important for the funding of early-stage firms and hence for entrepreneurial success.
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