Executive Compensation, Macroeconomic Conditions, and Cash Flow Cyclicality
Stefano Colonnello
Finance Research Letters,
November
2020
Abstract
I model the joint effects of debt, macroeconomic conditions, and cash flow cyclicality on risk-shifting behavior and managerial wealth-for-performance sensitivity. The model shows that risk-shifting incentives rise during recessions and that the shareholders can eliminate such adverse incentives by reducing the equity-based compensation in managerial contracts. Moreover, this reduction should be larger in highly procyclical firms. These novel, testable predictions provide insights into optimal shareholder responses to agency costs of debt throughout the business cycle.
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Measuring the Indirect Effects of Adverse Employer Behaviour on Worker Productivity – A Field Experiment
Matthias Heinz, Sabrina Jeworrek, Vanessa Mertins, Heiner Schumacher, Matthias Sutter
Economic Journal,
Nr. 632,
2020
Abstract
We conduct a field experiment to study how worker productivity is affected if employers act adversely towards their co-workers. Our employees work for two shifts in a call centre. In our main treatment, we lay off some workers before the second shift. Compared to two control treatments, we find that the lay-off reduces the productivity of unaffected workers by 12%. We find suggestive evidence that this result is not driven by altered beliefs about the job or the management’s competence, but caused by the workers’ perception of unfair employer behaviour. The latter interpretation is confirmed in a prediction experiment with professional HR managers. Our results suggest that the price for adverse employer behaviour goes well beyond the potential tit for tat of directly affected workers.
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Epidemics in the Neoclassical and New Keynesian Models
Martin S. Eichenbaum, Sergio Rebelo, Mathias Trabandt
Abstract
We analyze the effects of an epidemic in three standard macroeconomic models. We find that the neoclassical model does not rationalize the positive comovement of consumption and investment observed in recessions associated with an epidemic. Introducing monopolistic competition into the neoclassical model remedies this shortcoming even when prices are completely flexible. Finally, sticky prices lead to a larger recession but do not fundamentally alter the predictions of the monopolistic competition model.
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Dynamic Equity Slope
Matthijs Breugem, Stefano Colonnello, Roberto Marfè, Francesca Zucchi
University of Venice Ca' Foscari Department of Economics Working Papers,
Nr. 21,
2020
Abstract
The term structure of equity and its cyclicality are key to understand the risks drivingequilibrium asset prices. We propose a general equilibrium model that jointly explainsfour important features of the term structure of equity: (i) a negative unconditionalterm premium, (ii) countercyclical term premia, (iii) procyclical equity yields, and (iv)premia to value and growth claims respectively increasing and decreasing with thehorizon. The economic mechanism hinges on the interaction between heteroskedasticlong-run growth — which helps price long-term cash flows and leads to countercyclicalrisk premia — and homoskedastic short-term shocks in the presence of limited marketparticipation — which produce sizeable risk premia to short-term cash flows. The slopedynamics hold irrespective of the sign of its unconditional average. We provide empirical support to our model assumptions and predictions.
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Comparing Financial Transparency between For-profit and Nonprofit Suppliers of Public Goods: Evidence from Microfinance
John W. Goodell, Abhinav Goyal, Iftekhar Hasan
Journal of International Financial Markets, Institutions and Money,
January
2020
Abstract
Previous research finds market financing is favored over relationship financing in environments of better governance, since the transaction costs to investors of vetting asymmetric information are thereby reduced. For industries supplying public goods, for-profits rely on market financing, while nonprofits rely on relationships with donors. This suggests that for-profits will be more inclined than nonprofits to improve financial transparency. We examine the impact of for-profit versus nonprofit status on the financial transparency of firms engaged with supplying public goods. There are relatively few industries that have large number of both for-profit and nonprofit firms across countries. However, the microfinance industry provides the opportunity of a large number of both for-profit and nonprofit firms in relatively equal numbers, across a wide array of countries. Consistent with our prediction, we find that financial transparency is positively associated with a for-profit status. Results will be of broad interest both to scholars interested in the roles of transparency and transaction costs on market versus relational financing; as well as to policy makers interested in the impact of for-profit on the supply of public goods, and on the microfinance industry in particular.
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Trade, Misallocation, and Capital Market Integration
Laszlo Tetenyi
IWH-CompNet Discussion Papers,
Nr. 8,
2019
Abstract
I study how cross-country capital market integration affects the gains from trade in a model with financial frictions and heterogeneous, forward-looking firms. The model predicts that misallocation among exporters increases as trade barriers fall, even as misallocation decreases in the aggregate. The reason is that financially constrained productive exporters increase their production only marginally, while unproductive exporters survive for longer and increase their size. Allowing capital inflows magnifies misallocation, because unproductive firms expand even more, leading to a decline in aggregate productivity. Nevertheless, under integrated capital markets, access to cheaper capital dominates the adverse effect on productivity, leading to higher output, consumption and welfare than under closed capital markets. Applied to the period of European integration between 1992 and 2008, I find that underdeveloped sectors experiencing higher export exposure had more misallocation of capital and a higher share of unproductive firms, thus the data is consistent with the model’s predictions. A key implication of the model is that TFP is a poor proxy for consumption growth after trade liberalisation.
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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,
Nr. 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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Pricing Sin Stocks: Ethical Preference vs. Risk Aversion
Stefano Colonnello, Giuliano Curatola, Alessandro Gioffré
European Economic Review,
2019
Abstract
We develop an ethical preference-based model that reproduces the average return and volatility spread between sin and non-sin stocks. Our investors do not necessarily boycott sin companies. Rather, they are open to invest in any company while trading off dividends against ethicalness. When dividends and ethicalness are complementary goods and investors are sufficiently risk averse, the model predicts that the dividend share of sin companies exhibits a positive relation with the future return and volatility spreads. An empirical analysis supports the model’s predictions. Taken together, our results point to the importance of ethical preferences for investors’ portfolio choices and asset prices.
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An Evaluation of Early Warning Models for Systemic Banking Crises: Does Machine Learning Improve Predictions?
Johannes Beutel, Sophia List, Gregor von Schweinitz
Abstract
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.
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Central Bank Transparency and the Volatility of Exchange Rates
Stefan Eichler, Helge Littke
Journal of International Money and Finance,
2018
Abstract
We analyze the effect of monetary policy transparency on bilateral exchange rate volatility. We test the theoretical predictions of a stylized model using panel data for 62 currencies from 1998 to 2010. We find strong evidence that an increase in the availability of information about monetary policy objectives decreases exchange rate volatility. Using interaction models, we find that this effect is more pronounced for countries with a lower flexibility of goods prices, a lower level of central bank conservatism, and a higher interest rate sensitivity of money demand.
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