Deleveraging and Consumer Credit Supply in the Wake of the 2008–09 Financial Crisis
Reint E. Gropp, J. Krainer, E. Laderman
International Journal of Central Banking,
Nr. 3,
2019
Abstract
We explore the sources of the decline in household nonmortgage debt following the collapse of the housing market in 2006. First, we use data from the Federal Reserve Board's Senior Loan Officer Opinion Survey to document that, post-2006, banks tightened consumer lending standards more in counties that experienced a more pronounced house price decline (the pre-2006 "boom" counties). We then use the idea that renters did not experience an adverse wealth or collateral shock when the housing market collapsed to identify a general consumer credit supply shock. Our evidence suggests that a tightening of the supply of non-mortgage credit that was independent of the direct effects of lower housing collateral values played an important role in households' non-mortgage debt reduction. Renters decreased their non-mortgage debt more in boom counties than in non-boom counties, but homeowners did not. We argue that this wedge between renters and homeowners can only have arisen from a general tightening of banks' consumer lending stance. Using an IV approach, we trace this effect back to a reduction in bank capital of banks in boom counties.
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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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Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks
Christiane Baumeister, James D. Hamilton
American Economic Review,
Nr. 5,
2019
Abstract
Traditional approaches to structural vector autoregressions (VARs) can be viewed as special cases of Bayesian inference arising from very strong prior beliefs. These methods can be generalized with a less restrictive formulation that incorporates uncertainty about the identifying assumptions themselves. We use this approach to revisit the importance of shocks to oil supply and demand. Supply disruptions turn out to be a bigger factor in historical oil price movements and inventory accumulation a smaller factor than implied by earlier estimates. Supply shocks lead to a reduction in global economic activity after a significant lag, whereas shocks to oil demand do not.
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Price-cost Margin and Bargaining Power in the European Union
Ana Cristina Soares
IWH-CompNet Discussion Papers,
Nr. 4,
2019
Abstract
Using firm-level data between 2004 and 2012 for eleven countries of the European Union (EU), we document the size of product and labour market imperfections within narrowly defined sectors including services which are virtually undocumented. Our findings suggest that perfect competition in both product and labour markets is widely rejected. Levels of the price-cost margin and union bargaining power tend to be higher in some service sectors depicting however substantial heterogeneity. Dispersion within sector and across countries tends to be higher in some services sectors assuming a less tradable nature which suggests that the Single Market integration is partial particularly relaxing the assumption of perfect competition in the labour market. We report also figures for the aggregate economy and show that Eastern countries tend to depict lower product and labour market imperfections compared to other countries in the EU. Also, we provide evidence in favour of a very limited adjustment of both product and labour market imperfections following the international and financial crisis.
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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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The Income Elasticity of Mortgage Loan Demand
Manthos D. Delis, Iftekhar Hasan, Chris Tsoumas
Financial Markets, Institutions and Instruments,
Special Issue: 2016 Portsmouth – Fordham Conferenc
2019
Abstract
One explanation for the emergence of the housing market bubble and the subprime crisis is that increases in individuals’ income led to higher increases in the amount of mortgage loans demanded, especially for the middle class. This hypothesis translates to an increase in the income elasticity of mortgage loan demand before 2007. Using applicant‐level data, we test this hypothesis and find that the income elasticity of mortgage loan demand in fact declines in the years before 2007, especially for the mid‐ and lower‐middle income groups. Our finding implies that increases in house prices were not matched by increases in loan applicants’ income.
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Expectation Formation, Financial Frictions, and Forecasting Performance of Dynamic Stochastic General Equilibrium Models
Oliver Holtemöller, Christoph Schult
Historical Social Research,
Special Issue: Governing by Numbers
2019
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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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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Too Connected to Fail? Inferring Network Ties from Price Co-movements
Jakob Bosma, Michael Koetter, Michael Wedow
Journal of Business and Economic Statistics,
Nr. 1,
2019
Abstract
We use extreme value theory methods to infer conventionally unobservable connections between financial institutions from joint extreme movements in credit default swap spreads and equity returns. Estimated pairwise co-crash probabilities identify significant connections among up to 186 financial institutions prior to the crisis of 2007/2008. Financial institutions that were very central prior to the crisis were more likely to be bailed out during the crisis or receive the status of systemically important institutions. This result remains intact also after controlling for indicators of too-big-to-fail concerns, systemic, systematic, and idiosyncratic risks. Both credit default swap (CDS)-based and equity-based connections are significant predictors of bailouts. Supplementary materials for this article are available online.
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