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About Me
I am an Assistant Professor of Finance at the NYU Stern School of Business. My research is at the intersection of macroeconomics and finance, with special focus on housing and mortgage markets, the links between the stock market and the macroeconomy, and the structure of corporate debt. You can find my research statement here. Working papers and publications can be found below, while the tabs above contain my CV, discussion slides, and teaching materials. Comments and feedback are always welcome. Email: dlg340@stern.nyu.edu Mailing Address: 44 W 4th St, Office 9-79 New York, NY 10012 |
Working Papers
The Mortgage Credit Channel of Macroeconomic Transmission (Updated February 2018; SSRN; Dynare Code)
Revise and Resubmit, Journal of Political Economy
Abstract: I investigate how the structure of the mortgage market influences macroeconomic dynamics, using a general equilibrium framework with prepayable debt and a limit on the ratio of mortgage payments to income — features that prove essential to reproducing observed debt dynamics. The resulting environment amplifies transmission from interest rates into debt, house prices, and economic activity. Monetary policy more easily stabilizes inflation, but contributes to larger fluctuations in credit growth. A relaxation of payment-to-income standards appears vital for explaining the recent boom. A cap on payment-to-income ratios, not loan-to-value ratios, is the more effective macroprudential policy for limiting boom-bust cycles.
Do Credit Conditions Move House Prices? (Updated November 2021; SSRN, Slides)
with Adam Guren
Revise and Resubmit, American Economic Review
Abstract: To what extent did an expansion and contraction of credit drive the 2000s housing boom and bust? The existing literature lacks consensus, with findings ranging from credit having no effect to credit driving most of the house price cycle. We show that the key difference behind these disparate results is the extent to which credit insensitive agents such as landlords and unconstrained savers absorb credit-driven demand, which depends on the degree of segmentation in housing markets. We develop a model with frictional rental markets that allows us to consider cases in between the extremes of no segmentation and perfect segmentation typically assumed in the literature. We argue that the relative elasticities of the price-rent ratio and homeownership with respect to an identified credit shock is a sufficient statistic to measure the degree of segmentation. We estimate this moment using three different credit supply instruments and use it to calibrate our model. Our results reveal that rental markets are highly frictional and closer to fully segmented, which implies large effects of credit on house prices. In particular, changes to credit standards can explain between 34% and 55% of the rise in price-rent ratios over the boom.
The Credit Line Channel (Updated August 2023; Virtual Finance Workshop, VoxEU, Slides)
with John Krainer and Pascal Paul
Revise and Resubmit, Journal of Finance
Abstract: Aggregate U.S. bank lending to firms expanded following the outbreak of COVID-19. Using loan-level supervisory data, we show that this expansion was driven by draws on credit lines by large firms. Banks that experienced larger credit line drawdowns restricted term lending more, crowding out credit to smaller firms, which reacted by reducing investment. A structural model calibrated to match our empirical results shows that while credit lines increase total bank credit in bad times, they redistribute credit from firms with high propensities to invest to firms with low propensities to invest, exacerbating the fall in aggregate investment.
How the Wealth was Won: Factor Shares as Market Fundamentals (Updated June 2022; Video: Virtual Finance Workshop. Media: Barron's, NY Times. Our decompositions of market equity are publicly available here.)
with Martin Lettau and Sydney Ludvigson
Revise and Resubmit, Journal of Political Economy
Abstract: Why does the stock market rise and fall? From 1989 to 2017, the real per-capita value of corporate equity increased at a 7.5% annual rate. We estimate that 44% of this increase was attributable to a reallocation of rewards to shareholders in a decelerating economy, primarily at the expense of labor compensation. Economic growth accounted for just 25% of the increase, followed by a lower risk price (18%), and lower interest rates (14%). The period 1952 to 1988 experienced less than one third of the growth in market equity, but economic growth accounted for more than 100% of it.
Financial and Total Wealth Inequality with Declining Interest Rates (Updated September 2023, Slides)
with Matteo Leombroni, Hanno Lustig, and Stijn Van Nieuwerburgh
Abstract: Financial wealth inequality and long-term real interest rates track each other closely over the post-war period. We investigate how much of the increase in measured inequality can be explained by the decline in rates, and what the implications are for inequality in total wealth (lifetime consumption). We estimate the exposure of financial portfolios to interest rates at the household level to show that there is enough heterogeneity in portfolio revaluations to explain 75% of the rise in financial wealth inequality since the 1980s. A standard incomplete markets model calibrated to these data implies that declining rates are not consumption neutral. Instead, the low-wealth young lose, while the high-wealth old gain.
Firm Debt Covenants and the Macroeconomy: The Interest Coverage Channel (Updated July 2019; SSRN, Slides)
Abstract: Interest coverage covenants, which set a maximum ratio of interest payments to earnings, are among the most popular provisions in firm debt contracts. For affected firms, the amount of additional debt that can be issued without violating these covenants is highly sensitive to interest rates. Combining a theoretical model with firm-level data, I find that interest coverage limits generate strong amplification from interest rates into firm borrowing and investment. Importantly, most firms that have interest coverage covenants also face a maximum on the ratio of the stock of debt to earnings. Simultaneously imposing these limits implies a novel source of state-dependence: when interest rates are high, interest coverage limits are tighter, amplifying the influence of interest rate changes and monetary policy. Conversely, in low-rate environments, debt-to-earnings covenants dominate and transmission is weakened.
Managing a Housing Boom (Updated January 2022; Slides)
with Jason Allen
Abstract: We investigate how macroprudential policies intended to dampen rises in debt and house prices are influenced by segmentation in the housing and mortgage market. We develop a modeling framework with two mortgage submarkets: a government-insured sector with loose LTV limits and tight PTI limits, and an uninsured sector displaying the reverse pattern. This form of heterogeneity is modeled after the Canadian mortgage system, but is common in countries around the world. This multi-market structure implies that house prices are much more responsive to increases in latent demand, allowing for larger booms. While tightening payment-to-income (PTI) limits is highly effective at dampening a housing boom in a one-sector system, tightening these limits in the insured sector only is much weaker, due to substitutions into the uninsured sector. In contrast, the effect of tightening loan-to-value (LTV) limits in the uninsured sector is strengthened by market segmentation, causing price-rent ratios to fall, while the same tightening in the insured sector would counterproductively cause price-rent ratios to rise.
Regulatory Arbitrage or Random Errors? Implications of Race Prediction Algorithms in Fair Lending Analysis (Updated August 2023)
with Sabrina Howell, Cangyuan Li, and Emmanuel Yimfor
Abstract: Proxies for race are commonly used in settings where race cannot be observed directly. In the context of small business lending, we examine the standard race prediction algorithm (BISG), which regulators use to assess compliance with fair lending laws. The algorithm relies on an individual’s name and geographical location. If these features are correlated with socioeconomic characteristics, BISG errors could bias fair lending assessments and incentivize lenders to manipulate who they serve, specifically to lend to non-Black borrowers who are falsely predicted to be Black by BISG. We explore these issues using two datasets: proprietary loan application data from an online small business loan marketplace and loan data from the Paycheck Protection Program. We develop a measure of perceived race using images, which we show better correlates with self-identified race than BISG. BISG poorly predicts whether an individual is Black, generating more false classifications than correct ones, and these errors are systematically related to measures of socioeconomic advantage. For example, BISG has especially high false positive rates when classifying Black applicants in areas with high racial animus, where fair lending evaluation may be most critical. In a horse race, image-based race predicts loan approval, while BISG-based race does not, showing that BISG fails to capture important characteristics linked to race that are observable to lenders. There is large variation across lenders in the rate at which they lend to individuals who BISG erroneously assigns to the wrong racial group, leading them to appear more or less compliant with fair lending rules than they would using image-based race. Overall, our study documents the systematic biases in race proxies that rely on name and geography and highlights their implications for racial disparities in lending.
What Explains the COVID-19 Stock Market? (Updated August 2020)
with Josue Cox and Sydney Ludvigson
Revise and Resubmit, Quarterly Journal of Finance
Abstract: What explains stock market behavior in the early weeks of the coronavirus pandemic? Estimates from a dynamic asset pricing model point to wild fluctuations in the pricing of stock market risk, driven by shifts in risk aversion or sentiment. We find further evidence that the Federal Reserve played a role in these fluctuations, via a series of announcements outlining unprecedented steps to provide several trillion dollars in loans to support the economy. As of July 31 of 2020, however, only a tiny fraction of the credit that the central bank announced it stood ready to provide in early April had been extended, reinforcing the conclusion that market movements during COVID-19 have been more reflective of sentiment than substance.
The Mortgage Credit Channel of Macroeconomic Transmission (Updated February 2018; SSRN; Dynare Code)
Revise and Resubmit, Journal of Political Economy
Abstract: I investigate how the structure of the mortgage market influences macroeconomic dynamics, using a general equilibrium framework with prepayable debt and a limit on the ratio of mortgage payments to income — features that prove essential to reproducing observed debt dynamics. The resulting environment amplifies transmission from interest rates into debt, house prices, and economic activity. Monetary policy more easily stabilizes inflation, but contributes to larger fluctuations in credit growth. A relaxation of payment-to-income standards appears vital for explaining the recent boom. A cap on payment-to-income ratios, not loan-to-value ratios, is the more effective macroprudential policy for limiting boom-bust cycles.
Do Credit Conditions Move House Prices? (Updated November 2021; SSRN, Slides)
with Adam Guren
Revise and Resubmit, American Economic Review
Abstract: To what extent did an expansion and contraction of credit drive the 2000s housing boom and bust? The existing literature lacks consensus, with findings ranging from credit having no effect to credit driving most of the house price cycle. We show that the key difference behind these disparate results is the extent to which credit insensitive agents such as landlords and unconstrained savers absorb credit-driven demand, which depends on the degree of segmentation in housing markets. We develop a model with frictional rental markets that allows us to consider cases in between the extremes of no segmentation and perfect segmentation typically assumed in the literature. We argue that the relative elasticities of the price-rent ratio and homeownership with respect to an identified credit shock is a sufficient statistic to measure the degree of segmentation. We estimate this moment using three different credit supply instruments and use it to calibrate our model. Our results reveal that rental markets are highly frictional and closer to fully segmented, which implies large effects of credit on house prices. In particular, changes to credit standards can explain between 34% and 55% of the rise in price-rent ratios over the boom.
The Credit Line Channel (Updated August 2023; Virtual Finance Workshop, VoxEU, Slides)
with John Krainer and Pascal Paul
Revise and Resubmit, Journal of Finance
Abstract: Aggregate U.S. bank lending to firms expanded following the outbreak of COVID-19. Using loan-level supervisory data, we show that this expansion was driven by draws on credit lines by large firms. Banks that experienced larger credit line drawdowns restricted term lending more, crowding out credit to smaller firms, which reacted by reducing investment. A structural model calibrated to match our empirical results shows that while credit lines increase total bank credit in bad times, they redistribute credit from firms with high propensities to invest to firms with low propensities to invest, exacerbating the fall in aggregate investment.
How the Wealth was Won: Factor Shares as Market Fundamentals (Updated June 2022; Video: Virtual Finance Workshop. Media: Barron's, NY Times. Our decompositions of market equity are publicly available here.)
with Martin Lettau and Sydney Ludvigson
Revise and Resubmit, Journal of Political Economy
Abstract: Why does the stock market rise and fall? From 1989 to 2017, the real per-capita value of corporate equity increased at a 7.5% annual rate. We estimate that 44% of this increase was attributable to a reallocation of rewards to shareholders in a decelerating economy, primarily at the expense of labor compensation. Economic growth accounted for just 25% of the increase, followed by a lower risk price (18%), and lower interest rates (14%). The period 1952 to 1988 experienced less than one third of the growth in market equity, but economic growth accounted for more than 100% of it.
Financial and Total Wealth Inequality with Declining Interest Rates (Updated September 2023, Slides)
with Matteo Leombroni, Hanno Lustig, and Stijn Van Nieuwerburgh
Abstract: Financial wealth inequality and long-term real interest rates track each other closely over the post-war period. We investigate how much of the increase in measured inequality can be explained by the decline in rates, and what the implications are for inequality in total wealth (lifetime consumption). We estimate the exposure of financial portfolios to interest rates at the household level to show that there is enough heterogeneity in portfolio revaluations to explain 75% of the rise in financial wealth inequality since the 1980s. A standard incomplete markets model calibrated to these data implies that declining rates are not consumption neutral. Instead, the low-wealth young lose, while the high-wealth old gain.
Firm Debt Covenants and the Macroeconomy: The Interest Coverage Channel (Updated July 2019; SSRN, Slides)
Abstract: Interest coverage covenants, which set a maximum ratio of interest payments to earnings, are among the most popular provisions in firm debt contracts. For affected firms, the amount of additional debt that can be issued without violating these covenants is highly sensitive to interest rates. Combining a theoretical model with firm-level data, I find that interest coverage limits generate strong amplification from interest rates into firm borrowing and investment. Importantly, most firms that have interest coverage covenants also face a maximum on the ratio of the stock of debt to earnings. Simultaneously imposing these limits implies a novel source of state-dependence: when interest rates are high, interest coverage limits are tighter, amplifying the influence of interest rate changes and monetary policy. Conversely, in low-rate environments, debt-to-earnings covenants dominate and transmission is weakened.
Managing a Housing Boom (Updated January 2022; Slides)
with Jason Allen
Abstract: We investigate how macroprudential policies intended to dampen rises in debt and house prices are influenced by segmentation in the housing and mortgage market. We develop a modeling framework with two mortgage submarkets: a government-insured sector with loose LTV limits and tight PTI limits, and an uninsured sector displaying the reverse pattern. This form of heterogeneity is modeled after the Canadian mortgage system, but is common in countries around the world. This multi-market structure implies that house prices are much more responsive to increases in latent demand, allowing for larger booms. While tightening payment-to-income (PTI) limits is highly effective at dampening a housing boom in a one-sector system, tightening these limits in the insured sector only is much weaker, due to substitutions into the uninsured sector. In contrast, the effect of tightening loan-to-value (LTV) limits in the uninsured sector is strengthened by market segmentation, causing price-rent ratios to fall, while the same tightening in the insured sector would counterproductively cause price-rent ratios to rise.
Regulatory Arbitrage or Random Errors? Implications of Race Prediction Algorithms in Fair Lending Analysis (Updated August 2023)
with Sabrina Howell, Cangyuan Li, and Emmanuel Yimfor
Abstract: Proxies for race are commonly used in settings where race cannot be observed directly. In the context of small business lending, we examine the standard race prediction algorithm (BISG), which regulators use to assess compliance with fair lending laws. The algorithm relies on an individual’s name and geographical location. If these features are correlated with socioeconomic characteristics, BISG errors could bias fair lending assessments and incentivize lenders to manipulate who they serve, specifically to lend to non-Black borrowers who are falsely predicted to be Black by BISG. We explore these issues using two datasets: proprietary loan application data from an online small business loan marketplace and loan data from the Paycheck Protection Program. We develop a measure of perceived race using images, which we show better correlates with self-identified race than BISG. BISG poorly predicts whether an individual is Black, generating more false classifications than correct ones, and these errors are systematically related to measures of socioeconomic advantage. For example, BISG has especially high false positive rates when classifying Black applicants in areas with high racial animus, where fair lending evaluation may be most critical. In a horse race, image-based race predicts loan approval, while BISG-based race does not, showing that BISG fails to capture important characteristics linked to race that are observable to lenders. There is large variation across lenders in the rate at which they lend to individuals who BISG erroneously assigns to the wrong racial group, leading them to appear more or less compliant with fair lending rules than they would using image-based race. Overall, our study documents the systematic biases in race proxies that rely on name and geography and highlights their implications for racial disparities in lending.
What Explains the COVID-19 Stock Market? (Updated August 2020)
with Josue Cox and Sydney Ludvigson
Revise and Resubmit, Quarterly Journal of Finance
Abstract: What explains stock market behavior in the early weeks of the coronavirus pandemic? Estimates from a dynamic asset pricing model point to wild fluctuations in the pricing of stock market risk, driven by shifts in risk aversion or sentiment. We find further evidence that the Federal Reserve played a role in these fluctuations, via a series of announcements outlining unprecedented steps to provide several trillion dollars in loans to support the economy. As of July 31 of 2020, however, only a tiny fraction of the credit that the central bank announced it stood ready to provide in early April had been extended, reinforcing the conclusion that market movements during COVID-19 have been more reflective of sentiment than substance.
Publications
Financial Fragility with SAM? (Published Version, SSRN; Slides; Non-Technical Summary)
with Tim Landvoigt and Stijn Van Nieuwerburgh
Journal of Finance, Vol. 76(2), pp. 651-1052, December 2020
Abstract: Shared Appreciation Mortgages feature mortgage payments that adjust with house prices. They are designed to stave off borrower default by providing payment relief when house prices fall. Some argue that SAMs may help prevent the next foreclosure crisis. However, the home owner's gains from payment relief are the mortgage lender's losses. A general equilibrium model where financial intermediaries channel savings from saver to borrower households shows that indexation of mortgage payments to aggregate house prices increases financial fragility, reduces risk-sharing, and leads to expensive financial sector bailouts. In contrast, indexation to local house prices reduces financial fragility and improves risk-sharing.
Rare Shocks, Great Recessions (Published Version, Appendix)
with Vasco Curdia and Marco Del Negro.
Journal of Applied Econometrics, Vol. 29(7), pp. 1031-1052, November/December 2014.
Winner: 2016 Richard Stone Prize, awarded to the best paper with substantive econometric application in the 2014 and 2015 volumes of the Journal of Applied Econometrics.
Abstract: We estimate a DSGE model where rare large shocks can occur, by replacing the commonly used Gaussian assumption with a Student's t distribution. Results from the Smets and Wouters (2007) model estimated on the usual set of macroeconomic time series over the 1964-2011 period indicate that 1) the Student's t specification is strongly favored by the data even when we allow for low-frequency variation in the volatility of the shocks, and 2) the estimated degrees of freedom are quite low for several shocks that drive U.S. business cycles, implying an important role for rare large shocks. This result holds even if we exclude the Great Recession period from the sample. We also show that inference about low-frequency changes in volatility -- and in particular, inference about the magnitude of Great Moderation -- is different once we allow for fat tails.
Financial Fragility with SAM? (Published Version, SSRN; Slides; Non-Technical Summary)
with Tim Landvoigt and Stijn Van Nieuwerburgh
Journal of Finance, Vol. 76(2), pp. 651-1052, December 2020
Abstract: Shared Appreciation Mortgages feature mortgage payments that adjust with house prices. They are designed to stave off borrower default by providing payment relief when house prices fall. Some argue that SAMs may help prevent the next foreclosure crisis. However, the home owner's gains from payment relief are the mortgage lender's losses. A general equilibrium model where financial intermediaries channel savings from saver to borrower households shows that indexation of mortgage payments to aggregate house prices increases financial fragility, reduces risk-sharing, and leads to expensive financial sector bailouts. In contrast, indexation to local house prices reduces financial fragility and improves risk-sharing.
Rare Shocks, Great Recessions (Published Version, Appendix)
with Vasco Curdia and Marco Del Negro.
Journal of Applied Econometrics, Vol. 29(7), pp. 1031-1052, November/December 2014.
Winner: 2016 Richard Stone Prize, awarded to the best paper with substantive econometric application in the 2014 and 2015 volumes of the Journal of Applied Econometrics.
Abstract: We estimate a DSGE model where rare large shocks can occur, by replacing the commonly used Gaussian assumption with a Student's t distribution. Results from the Smets and Wouters (2007) model estimated on the usual set of macroeconomic time series over the 1964-2011 period indicate that 1) the Student's t specification is strongly favored by the data even when we allow for low-frequency variation in the volatility of the shocks, and 2) the estimated degrees of freedom are quite low for several shocks that drive U.S. business cycles, implying an important role for rare large shocks. This result holds even if we exclude the Great Recession period from the sample. We also show that inference about low-frequency changes in volatility -- and in particular, inference about the magnitude of Great Moderation -- is different once we allow for fat tails.
Inactive/Legacy Papers
Origins of Stock Market Fluctuations (Updated October 2016; VoxEU, MarketWatch; SSRN)
with Martin Lettau and Sydney Ludvigson
Superseded by "How the Wealth was Won: Factor Shares as Market Fundamentals."
Abstract: Three mutually uncorrelated economic disturbances that we measure empirically explain 85% of the quarterly variation in real stock market wealth since 1952. A model is employed to interpret these disturbances in terms of three latent primitive shocks. In the short run, shocks that affect the willingness to bear risk independently of macroeconomic fundamentals explain most of the variation in the market. In the long run, the market is profoundly affected by shocks that reallocate the rewards of a given level of production between workers and shareholders. Productivity shocks play a small role in historical stock market fluctuations at all horizons.
Origins of Stock Market Fluctuations (Updated October 2016; VoxEU, MarketWatch; SSRN)
with Martin Lettau and Sydney Ludvigson
Superseded by "How the Wealth was Won: Factor Shares as Market Fundamentals."
Abstract: Three mutually uncorrelated economic disturbances that we measure empirically explain 85% of the quarterly variation in real stock market wealth since 1952. A model is employed to interpret these disturbances in terms of three latent primitive shocks. In the short run, shocks that affect the willingness to bear risk independently of macroeconomic fundamentals explain most of the variation in the market. In the long run, the market is profoundly affected by shocks that reallocate the rewards of a given level of production between workers and shareholders. Productivity shocks play a small role in historical stock market fluctuations at all horizons.
Work in Progress
Quantitative Tightening: Challenges of Two-Dimensional Monetary Normalization (Slides)
with Vadim Elenev and Miguel Faria-e-Castro
Quantitative Tightening: Challenges of Two-Dimensional Monetary Normalization (Slides)
with Vadim Elenev and Miguel Faria-e-Castro
Non-Academic Articles
Here’s Why Adding $310 Billion to the Second Round of PPP Won’t Fix It
Marker/Medium, April 23, 2020
A Traditional Economic Stimulus Won't Work. Here's What Might
Marker/Medium, March 24, 2020
Here’s Why Adding $310 Billion to the Second Round of PPP Won’t Fix It
Marker/Medium, April 23, 2020
A Traditional Economic Stimulus Won't Work. Here's What Might
Marker/Medium, March 24, 2020