Non-Standard Errors
Albert J. Menkveld, Anna Dreber, Felix Holzmeister, Juergen Huber, Magnus Johannesson, Michael Koetter, Markus Kirchner, Sebastian Neusüss, Michael Razen, Utz Weitzel, Shuo Xia, et al.
Journal of Finance,
No. 3,
2024
Abstract
In statistics, samples are drawn from a population in a datagenerating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidencegenerating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
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U.S. Monetary and Fiscal Policy Regime Changes and Their Interactions
Yoosoon Chang, Boreum Kwak, Shi Qiu
IWH Discussion Papers,
No. 12,
2021
Abstract
We investigate U.S. monetary and fiscal policy interactions in a regime-switching model of monetary and fiscal policy rules where policy mixes are determined by a latent bivariate autoregressive process consisting of monetary and fiscal policy regime factors, each determining a respective policy regime. Both policy regime factors receive feedback from past policy disturbances, and interact contemporaneously and dynamically to determine policy regimes. We find strong feedback and dynamic interaction between monetary and fiscal authorities. The most salient features of these interactions are that past monetary policy disturbance strongly influences both monetary and fiscal policy regimes, and that monetary authority responds to past fiscal policy regime. We also find substantial evidence that the U.S. monetary and fiscal authorities have been interacting: central bank responds less aggressively to inflation when fiscal authority puts less attention on debt stabilisation, and vice versa.
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Non-Standard Errors
Albert J. Menkveld, Anna Dreber, Felix Holzmeister, Juergen Huber, Magnus Johannesson, Markus Kirchner, Sebastian Neusüss, Michael Razen, Utz Weitzel, et al.
Abstract
In statistics, samples are drawn from a population in a datagenerating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidencegenerating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
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“The Good News about Bad News”: Information about Past Organizational Failure and Its Impact on Worker Productivity
Sabrina Jeworrek, Vanessa Mertins, Michael Vlassopoulos
Leadership Quarterly,
No. 3,
2021
Abstract
Failure in organizations is very common. Little is known about whether leaders should provide information about past organizational failure to followers and how this might affect their future performance. We conducted a field experiment in which we recruited temporary workers to carry out a phone campaign to attract new volunteers and randomly assigned them to either receive or not to receive information about a failed mail campaign pursuing the same goal. We find that informed workers performed better, regardless of whether they had previously worked on the failed mail campaign or not. Evidence from a second field experiment with students asked to support voluntarily a campaign for reducing food waste corroborates the finding. We explore the role of leadership tactics behind our findings in a third online survey experiment. We conclude that information about past failure is unlikely to have a negative impact on work performance, and might even lead to performance improvement. Implications for future research on the relevance of leadership tactics when giving such information are discussed.
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Equity Crowdfunding: High-quality or Low-quality Entrepreneurs?
Daniel Blaseg, Douglas Cumming, Michael Koetter
Entrepreneurship, Theory and Practice,
No. 3,
2021
Abstract
Equity crowdfunding (ECF) has potential benefits that might be attractive to high-quality entrepreneurs, including fast access to a large pool of investors and obtaining feedback from the market. However, there are potential costs associated with ECF due to early public disclosure of entrepreneurial activities, communication costs with large pools of investors, and equity dilution that could discourage future equity investors; these costs suggest that ECF attracts low-quality entrepreneurs. In this paper, we hypothesize that entrepreneurs tied to more risky banks are more likely to be low-quality entrepreneurs and thus are more likely to use ECF. A large sample of ECF campaigns in Germany shows strong evidence that connections to distressed banks push entrepreneurs to use ECF. We find some evidence, albeit less robust, that entrepreneurs who can access other forms of equity are less likely to use ECF. Finally, the data indicate that entrepreneurs who access ECF are more likely to fail.
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Sovereign Default Risk, Macroeconomic Fluctuations and Monetary-Fiscal Stabilisation
Markus Kirchner, Malte Rieth
IWH Discussion Papers,
No. 22,
2020
Abstract
This paper examines the role of sovereign default beliefs for macroeconomic fluctuations and stabilisation policy in a small open economy where fiscal solvency is a critical problem. We set up and estimate a DSGE model on Turkish data and show that accounting for sovereign risk significantly improves the fit of the model through an endogenous amplication between default beliefs, exchange rate and inflation movements. We then use the estimated model to study the implications of sovereign risk for stability, fiscal and monetary policy, and their interaction. We find that a relatively strong fiscal feedback from deficits to taxes, some exchange rate targeting, or a monetary response to default premia are more effective and efficient stabilisation tools than hawkish inflation targeting.
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The Effects of Fiscal Policy in an Estimated DSGE Model – The Case of the German Stimulus Packages During the Great Recession
Andrej Drygalla, Oliver Holtemöller, Konstantin Kiesel
Macroeconomic Dynamics,
No. 6,
2020
Abstract
In this paper, we analyze the effects of the stimulus packages adopted by the German government during the Great Recession. We employ a standard medium-scale dynamic stochastic general equilibrium (DSGE) model extended by non-optimizing households and a detailed fiscal sector. In particular, the dynamics of spending and revenue variables are modeled as feedback rules with respect to the cyclical components of output, hours worked and private investment. Based on the estimated rules, fiscal shocks are identified. According to the results, fiscal policy, in particular public consumption, investment, and transfers prevented a sharper and prolonged decline of German output at the beginning of the Great Recession, suggesting a timely response of fiscal policy. The overall effects, however, are small when compared to other domestic and international shocks that contributed to the economic downturn. Our overall findings are not sensitive to considering fiscal foresight.
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The Joint Dynamics of Sovereign Ratings and Government Bond Yields
Makram El-Shagi, Gregor von Schweinitz
Journal of Banking and Finance,
2018
Abstract
Can a negative shock to sovereign ratings invoke a vicious cycle of increasing government bond yields and further downgrades, ultimately pushing a country toward default? The narratives of public and political discussions, as well as of some widely cited papers, suggest this possibility. In this paper, we will investigate the possible existence of such a vicious cycle. We find no evidence of a bad long-run equilibrium and cannot confirm a feedback loop leading into default as a transitory state for all but the very worst ratings. We use a bivariate semiparametric dynamic panel model to reproduce the joint dynamics of sovereign ratings and government bond yields. The individual equations resemble Pesaran-type cointegration models, which allow for valid interference regardless of whether the employed variables display unit-root behavior. To incorporate most of the empirical features previously documented (separately) in the literature, we allow for different long-run relationships in both equations, nonlinearities in the level effects of ratings, and asymmetric effects in changes of ratings and yields. Our finding of a single good equilibrium implies the slow convergence of ratings and yields toward this equilibrium. However, the persistence of ratings is sufficiently high that a rating shock can have substantial costs if it occurs at a highly speculative rating or lower. Rating shocks that drive the rating below this threshold can increase the interest rate sharply, and for a long time. Yet, simulation studies based on our estimations show that it is highly improbable that rating agencies can be made responsible for the most dramatic spikes in interest rates.
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Information Feedback in Temporal Networks as a Predictor of Market Crashes
Stjepan Begušić, Zvonko Kostanjčar, Dejan Kovač, Boris Podobnik, H. Eugene Stanley
Complexity,
September
2018
Abstract
In complex systems, statistical dependencies between individual components are often considered one of the key mechanisms which drive the system dynamics observed on a macroscopic level. In this paper, we study cross-sectional time-lagged dependencies in financial markets, quantified by nonparametric measures from information theory, and estimate directed temporal dependency networks in financial markets. We examine the emergence of strongly connected feedback components in the estimated networks, and hypothesize that the existence of information feedback in financial networks induces strong spatiotemporal spillover effects and thus indicates systemic risk. We obtain empirical results by applying our methodology on stock market and real estate data, and demonstrate that the estimated networks exhibit strongly connected components around periods of high volatility in the markets. To further study this phenomenon, we construct a systemic risk indicator based on the proposed approach, and show that it can be used to predict future market distress. Results from both the stock market and real estate data suggest that our approach can be useful in obtaining early-warning signals for crashes in financial markets.
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"The Good News about Bad News": Information about Past Organisational Failure and its Impact on Worker Productivity
Sabrina Jeworrek, Vanessa Mertins, Michael Vlassopoulos
Abstract
Failure in organisations is a very common phenomenon. Little is known about whether past failure affects workers’ subsequent performance. We conduct a field experiment in which we follow up a failed mail campaign to attract new volunteers with a phone campaign pursuing the same goal. We recruit temporary workers to carry out the phone campaign and randomly assign them to either receive or not receive information about the previous failure and measure their performance. We find that informed workers perform better – in terms of both numbers dialed (about 14% improvement) and completed interviews (about 20% improvement) – regardless of whether they had previously worked on the failed mail campaign. Evidence from a second experiment with student volunteers asked to support a campaign to reduce food waste suggests that the mechanism behind our finding relates to contextual inference: Informing workers/volunteers that they are pursuing a goal that is hard to attain seems to add meaning to the work involved, leading them to exert more effort.
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