Drilling and Debt
Erik P. Gilje, Elena Loutskina, Daniel Murphy
Journal of Finance,
No. 3,
2020
Abstract
This paper documents a previously unrecognized debt‐related investment distortion. Using detailed project‐level data for 69 firms in the oil and gas industry, we find that highly levered firms pull forward investment, completing projects early at the expense of long‐run project returns and project value. This behavior is particularly pronounced prior to debt renegotiations. We test several channels that could explain this behavior and find evidence consistent with equity holders sacrificing long‐run project returns to enhance collateral values and, by extension, mitigate lending frictions at debt renegotiations.
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Phillips Curve and Output Expectations: New Perspectives from the Euro Zone
Giuliana Passamani, Alessandro Sardone, Roberto Tamborini
DEM Working Papers,
No. 6,
2020
published in: Empirica
Abstract
When referring to the inflation trends over the last decade, economists speak of "puzzles": a “missing disinflation” puzzle in the aftermath of the Great Recession, and a ”missing inflation” one in the years of recovery to nowadays. To this, a specific "excess deflation" puzzle may be added during the post-crisis depression in the Euro Zone. The standard Phillips Curve model, in this context, has failed as the basic tool to produce reliable forecasts of future price developments, leading many scholars to consider this instrument to be no more adequate. The purpose of this paper is to contribute to this literature through the development of a newly specified Phillips Curve model, in which the inflation-expectation component is rationally related to the business cycle. The model is tested with the Euro Zone data 1999-2019 showing that inflation turns out to be consistently determined by output gaps and and experts' survey-based forecast errors, and that the puzzles can be explained by the interplay between these two variables.
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Foreign Bank Ownership and Income Inequality: Empirical Evidence
Manthos D. Delis, Iftekhar Hasan, Nikolaos Mylonidis
Applied Economics,
No. 11,
2020
Abstract
Using country-level panel data over 1995–2013 on within-country income inequality and foreign bank presence, this paper establishes a positive relation between the two, running from higher foreign bank presence to income inequality. Given that foreign bank participation increased by 62% over the period 1995 to 2013, our baseline results imply a 5.8% increase in the Gini coefficient on average over this period, ceteris paribus. These results are robust to the inclusion of country and year fixed effects and to the use of restrictions on foreign bank entry in the host countries as an instrumental variable. We show that this positive effect is channelled through the lack of greenfield entry and the associated lower levels of competition.
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Does Machine Learning Help us Predict Banking Crises?
Johannes Beutel, Sophia List, Gregor von Schweinitz
Journal of Financial Stability,
December
2019
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 metric, 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 efficiently, 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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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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Aktuelle Trends: Der Rückgang der Exporte nach Russland betrifft alle Bundesländer und ist nur zum Teil durch die Sanktionen der EU gegenüber Russland zu erklären
Oliver Holtemöller, Martina Kämpfe
Wirtschaft im Wandel,
No. 2,
2019
Abstract
In den vergangenen 20 Jahren waren die deutschen Exporte nach Russland in Relation zur gesamten Wertschöpfung zweimal rückläufig: zunächst im Jahr 2009 und dann wieder seit etwa dem Jahr 2012, also bevor die Europäische Union 2014 erstmals Handelssanktionen gegenüber Russland verhängte. Betroffen sind alle Bundesländer, der Rückgang dauert meist bis in die heutige Zeit an. Die Sanktionen dürften nur einen Teil des Rückgangs erklären. Vielmehr schwächte sich die Nachfrage nach Investitions- und Konsumgütern aus Russland mit dem Ölpreisverfall und der damit verbundenen Abwertung des Rubels Ende 2014 deutlich ab. Dies betraf nicht nur Deutschland, sondern beispielsweise auch China, das an Sanktionen gegenüber Russland nicht beteiligt ist. Erst 2016, als der Ölpreis wieder stieg, setzte eine teilweise Erholung der russischen Importe ein.
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Resolving the Missing Deflation Puzzle
Jesper Lindé, Mathias Trabandt
Abstract
We propose a resolution of the missing deflation puzzle. Our resolution stresses the importance of nonlinearities in price- and wage-setting when the economy is exposed to large shocks. We show that a nonlinear macroeconomic model with real rigidities resolves the missing deflation puzzle, while a linearized version of the same underlying nonlinear model fails to do so. In addition, our nonlinear model reproduces the skewness of inflation and other macroeconomic variables observed in post-war U.S. data. All told, our results caution against the common practice of using linearized models to study inflation and output dynamics.
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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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Avoiding the Fall into the Loop: Isolating the Transmission of Bank-to-Sovereign Distress in the Euro Area and its Drivers
Hannes Böhm, Stefan Eichler
Abstract
We isolate the direct bank-to-sovereign distress channel within the eurozone’s sovereign-bank-loop by exploiting the global, non-eurozone related variation in stock prices. We instrument banking sector stock returns in the eurozone with exposure-weighted stock market returns from non-eurozone countries and take further precautions to remove any eurozone crisis-related variation. We find that the transmission of instrumented bank distress, while economically relevant, is significantly smaller than the corresponding coefficient in the unadjusted OLS framework, confirming concerns on reverse causality and omitted variables in previous studies. Furthermore, we show that the spillover of bank distress is significantly stronger for countries with poorer macroeconomic performances, weaker financial sectors and financial regulation and during times of elevated political uncertainty.
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Channeling the Iron Ore Super-cycle: The Role of Regional Bank Branch Networks in Emerging Markets
Helge Littke
IWH Discussion Papers,
No. 11,
2018
Abstract
The role of the financial system to absorb and to intermediate commodity boom induced windfall gains efficiently presents one of the most pressing issues for developing economies. Using an exogenous increase in iron ore prices in March 2005, I analyse the role of regional bank branch networks in Brazil in reallocating capital from affected to non-affected regions. For the period from March 2004 to March 2006, I find that branches directly exposed to this shock by their geographical location experience an increase in deposit growth in the post-shock period relative to non-affected branches. Given that these deposits are not reinvested locally, I further show that branches located in the non-affected region increase lending growth depending on their indirect exposure to the booming regions via their branch network. Even tough, these results provide evidence against a Dutch Disease type crowding out of the non-iron ore sector, further evidence suggests that this capital reallocation is far from being optimal.
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