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Author:Zimmermann, Thomas 

Discussion Paper
Ten years later – Did QE work?

By November 2008, the Global Financial Crisis, which originated in the residential housing market and the shadow banking system, had begun to turn into a major recession, spurring the Federal Open Market Committee (FOMC) to initiate what we now refer to as quantitative easing (QE). In this blog post, we draw upon the empirical findings of post-crisis academic research's including our own work's to shed light on the question: Did QE work?
Liberty Street Economics , Paper 20190508

Working Paper
Claim Dilution in the Municipal Debt Market

Using loan-level municipal bank lending data, we examine the debt structure of municipalities and its response to exogenous income shocks. We show that small, more indebted, low-income, and medium credit quality counties are particularly reliant on private bank financing. Low income counties are more likely to increase bank debt share after an adverse permanent income shock while high income counties do not shift their debt structure in response. In contrast, only high income counties draw on their credit lines after adverse transitory income shocks. Overall, our paper raises concerns about ...
Finance and Economics Discussion Series , Paper 2018-011

Working Paper
Did QE Lead Banks to Relax Their Lending Standards? Evidence from the Federal Reserve's LSAPs

Using confidential loan officer survey data on lending standards and internal risk ratings on loans, we document an effect of large-scale asset purchase programs (LSAPs) on lending standards and risk-taking. We exploit cross-sectional variation in banks? holdings of mortgage-backed securities to show that the first and third round of quantitative easing (QE1 and QE3) significantly lowered lending standards and increased loan risk characteristics. The magnitude of the effects is about the same in QE1 and QE3, and is comparable to the effect of a one percentage point decrease in the Fed funds ...
Finance and Economics Discussion Series , Paper 2017-093

Working Paper
Bottom-up Leading Macroeconomic Indicators: An Application to Non-Financial Corporate Defaults using Machine Learning

This paper constructs a leading macroeconomic indicator from microeconomic data using recent machine learning techniques. Using tree-based methods, we estimate probabilities of default for publicly traded non-financial firms in the United States. We then use the cross-section of out-of-sample predicted default probabilities to construct a leading indicator of non-financial corporate health. The index predicts real economic outcomes such as GDP growth and employment up to eight quarters ahead. Impulse responses validate the interpretation of the index as a measure of financial stress.
Finance and Economics Discussion Series , Paper 2019-070

Working Paper
Publication Bias and the Cross-Section of Stock Returns

We develop an estimator for publication bias and apply it to 156 hedge portfolios based on published cross-sectional return predictors. Publication bias adjusted returns are only 12% smaller than in-sample returns. The small bias comes from the dispersion of returns across predictors, which is too large to be accounted for by data-mined noise. Among predictors that can survive journal review, a low t-stat hurdle of 1.8 controls for multiple testing using statistics recommended by Harvey, Liu, and Zhu (2015). The estimated bias is too small to account for the deterioration in returns after ...
Finance and Economics Discussion Series , Paper 2018-033

Working Paper
Employment Effects of Unconventional Monetary Policy : Evidence from QE

This paper investigates the effect of the Federal Reserve's unconventional monetary policy on employment via a bank lending channel. We find that banks with higher mortgage-backed securities holdings issued relatively more loans after the first and third rounds of quantitative easing (QE1 and QE3). While additional volume is concentrated in refinanced mortgages after QE1, increases are driven by newly originated home purchase mortgages and additional commercial and industrial lending after QE3. Using spatial variation, we show that regions with a high share of affected banks experienced ...
Finance and Economics Discussion Series , Paper 2018-071

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