Research Interests: applied econometrics, finance, and macroeconomics, household finance: household consumption, saving/borrowing, and investments
Links: Personal Website
PhD, Massachusetts Institute of Technology, 1995; BA, University of Oxford, 1991; BSE, Princeton University, 1988
Christian R. and Mary F. Lindback Teaching Award (University of Pennsylvania), 2006; David W. Hauck Undergraduate Teaching Award (Wharton), 2004; Marc and Sheri Rapaport Undergraduate Core Teaching Award (Wharton), 1997, 2003, 2007, 2011; Undergraduate Excellence in Teaching Award (Wharton), 2004, 2005, 2008; MBA Core Curriculum Teaching Award, 1998, 1999, 2000
Wharton: 1995-present (named Michael L. Tarnopol Professor, 2008; named Michael L. Tarnopol Associate Professor, 2007-08; named Gilbert and Shelly Harrison Term Assistant Professor of Finance, 2000-2002)
National Bureau of Economic Research, 2001-present; Visiting Scholar, Federal Reserve Bank of Philadelphia, 2002-; Co-director, NBER Working Group on Household Finance, 2009-; Co-editor, SSRN Household Finance eJournal, 2010-;
Abstract: For households that face a possibility of moving across MSAs, the risk of home owning depends critically on the covariance of the sale prices of their current houses with the purchase prices of their likely future houses. We find empirically that households tend to move between highly correlated MSAs, significantly increasing the distribution of expected correlations in real house price growth across MSAs, and so raising the “moving-hedge” value of owning. We also find that tenure decisions are sensitive to this hedging value, with households being more likely to own, ceteris paribus, when their hedging value is greater due to higher expected correlations and likelihoods of moving.
Jonathan A. Parker, Nicholas S. Souleles, David S. Johnson, Robert McClelland (Working), Consumer Spending and the Economic Stimulus Payments of 2008.
Abstract: We measure the response of household spending to the economic stimulus payments (ESPs) disbursed in mid-2008, using special questions added to the Consumer Expenditure Survey and variation arising from the randomized timing of when the payments were disbursed. We find that, on average, households spent about 12-30% (depending on the specification) of their stimulus payments on nondurable expenditures during the three-month period in which the payments were received. Further, there was also a substantial and significant increase in spending on durable goods, in particular vehicles, bringing the average total spending response to about 50-90% of the payments. Relative to research on the 2001 tax rebates, these spending responses are estimated with greater precision using the randomized timing variation. The estimated responses are substantial and significant for older, lower-income, and home-owning households. We further extend the literature in two ways. First, we find little evidence that the propensity to spend varies with the method of disbursement (paper check versus electronic transfer). Second, we evaluate a complementary methodology for quantifying the impact of tax cuts, which asks consumers to self-report whether they spent their tax cuts. The response of spending to the ESPs is indeed largest for self-reported spenders. However, self-reported savers also spent a significant fraction of the payments.
Sumit Agarwal, Souphala Chomsisengphet, Chunlin Liu, Nicholas S. Souleles (Working), Benefits of Relationship Banking: Evidence from Consumer Credit Markets.
Abstract: This paper empirically examines the benefits of relationship banking to banks, in the context of consumer credit markets. Using a unique panel dataset that contains comprehensive information about the relationships between a large bank and its credit card customers, we estimate the effects of relationship banking on the customers’ default, attrition, and utilization behavior. We find that relationship accounts exhibit lower probabilities of default and attrition, and have higher utilization rates, compared to non-relationship accounts, ceteris paribus. Such effects become more pronounced with increases in various measures of the strength of the relationships, such as relationship breadth, depth, length, and proximity. Moreover, dynamic information about changes in the behavior of a customer’s other accounts at the bank, such as changes in checking and savings balances, helps predict and thus monitor the behavior of the credit card account over time. These results imply significant potential benefits of relationship banking to banks in the retail credit market.
Abstract: A number of studies have pointed to various mistakes that consumers might make in their consumption-saving and financial decisions. We utilize a unique market experiment conducted by a large U.S. bank to assess how systematic and costly such mistakes are in practice. The bank offered consumers a choice between two credit card contracts, one with an annual fee but a lower interest rate and one with no annual fee but a higher interest rate. To minimize their total interest costs net of the fee, consumers expecting to borrow a sufficiently large amount should choose the contract with the fee, and vice-versa. We find that on average consumers chose the contract that ex post minimized their net costs. A substantial fraction of consumers (about 40%) still chose the ex post sub-optimal contract, with some incurring hundreds of dollars of avoidable interest costs. Nonetheless, the probability of choosing the sub-optimal contract declines with the dollar magnitude of the potential error, and consumers with larger errors were more likely to subsequently switch to the optimal contract. Thus most of the errors appear not to have been very costly, with the exception that a small minority of consumers persists in holding substantially sub-optimal contracts without switching.
Nicholas S. Souleles, Sumit Agarwal, Chunlin Liu (2007), The Reaction of Consumer Spending and Debt to Tax Rebates – Evidence from Consumer Credit Data, Journal of Political Economy, 115(6).
David S. Johnson, Jonathan A. Parker, Nicholas S. Souleles (2006), Household Expenditure and the Income Tax Rebates of 2001, American Economic Review, 96(5), December 2006.
Abstract: Using questions expressly added to the Consumer Expenditure Survey, we estimate the change in consumption expenditures caused by the 2001 federal income tax rebates and test the permanent income hypothesis. We exploit the unique, randomized timing of rebate receipt across households. Households spent 20 to 40 percent of their rebates on nondurable goods during the three-month period in which their rebates arrived, and roughly two-thirds of their rebates cumulatively during this period and the subsequent three-month period. The implied effects on aggregate consumption demand are substantial. Consistent with liquidity constraints, responses are larger for households with low liquid wealth or low income.
Gary B Gorton and Nicholas S. Souleles (2006), Special Purpose Vehicles and Securitization, The Risks of Financial Institutions, Eds. Carey, M. and Stulz, R. Chicago: University of Chicago Press for the NBER, 2006.
Abstract: This paper analyzes securitization and more generally special purpose vehicles (SPVs), which are now pervasive in corporate finance. The first part of the paper provides an overview of the institutional features of SPVs and securitization. The second part provides a model to analyze the motivations for using SPVs, and the conditions under which SPVs are sustainable. We argue that a key source of value to using SPVs is that they help reduce bankruptcy costs. Off-balance sheet financing involves transferring assets to SPVs, which reduces the amount of assets that are subject to bankruptcy costs, since SPVs are carefully designed to avoid bankruptcy. Off-balance sheet financing is most advantageous for sponsoring firms that are risky or face large bankruptcy costs. SPVs become sustainable in a repeated SPV game, because firms can implicitly commit to subsidize or bail out their SPVs when the SPV would otherwise not honor its debt commitments, despite legal and accounting restrictions to the contrary. The third part of the paper tests two key implications of the model using unique data on credit card securitizations. First, riskier firms should securitize more, ceteris paribus. Second, since investors know that SPV sponsors can bail out their SPVs if there is a need, in pricing the debt of the SPV investors will care about the risk of the sponsor defaulting, above and beyond the risk of the SPVs assets. We find evidence consistent with these implications.
Abstract: This paper takes a portfolio view of consumer credit. Default models (credit-risk scores) estimate the probability of default of individual loans. But to compute risk-adjusted returns, lenders also need to know the covariances of the returns on their loans with aggregate returns. Covariances are independently relevant for lenders who care directly about the volatility of their portfolios, e.g. because of Value-at-Risk considerations or the structure of the securitization market. Cross-sectional differences in these covariances also provide insight into the nature of the shocks hitting different types of consumers. We use a unique panel dataset of credit bureau records to measure the ‘covariance risk’ of individual consumers, i.e., the covariance of their default risk with aggregate consumer default rates, and more generally to analyze the cross-sectional distribution of credit, including the effects of credit scores. We obtain two key sets of results. First, there is significant systematic heterogeneity in covariance risk across consumers with different characteristics. Consumers with high covariance risk tend to also have low credit scores (high default probabilities). Second, the amount of credit obtained by consumers significantly increases with their credit scores, and significantly decreases with their covariance risk (especially revolving credit), though the effect of covariance risk is smaller in magnitude. It appears that some lenders take covariance risk into account, at least in part, in determining the amount of credit they provide.
Todd Sinai and Nicholas S. Souleles (2005), Owner Occupied Housing as a Hedge Against Rent Risk, Quarterly Journal of Economics, Vol. 120, number 2 (May 2005), pp. 763-789.
Abstract: The conventional wisdom that homeownership is very risky ignores the fact that the alternative, renting, is also risky. Owning a house provides a hedge against fluctuations in housing costs, but in turn introduces asset price risk. In a simple model of tenure choice with endogenous house prices, we show that the net risk of owning declines with a household's expected horizon in its house and with the correlation in housing costs in future locations. Empirically, we find that both house prices, relative to rents, and the probability of homeownership increase with net rent risk.
This is an intermediate-level course in macroeconomics and the global economy, including topics in monetary and international economics. The goal is to provide a unified framework for understanding macroeconomic events and policy, which govern the global economic environment of business. The course analyzes the determinants and behavior of employment, production, demand and profits; inflation, interest rates, asset prices, and wages; exchange rates and international flows of goods and assets; including the interaction of the real economy with monetary policy and the financial system. The analysis is applied to current events, both in the US and abroad. Students cannot receive credit for taking both FNCE 101 and ECON 102. Wharton students are required to take FNCE 101. Honors sections require MATH 114 as a prerequisite.
Integrates the work of the various courses and familiarizes the student with the tools and techniques of research.
This is a doctoral level course on macroeconomics, with special emphasis on intertemporal choice under uncertainty and topics related to finance. Topics include: optimal consumption and saving, the stochastic growth model, q-theory of investment, (incomplete) risk sharing and asset pricing. The course will cover and apply techniques, including dynamic programming, to solve dynamic optimization problems under uncertainty. Numerical solution methods are also discussed.
This course may be offered (and taken by a student) several times a year with varying topics.
Economic recovery in the U.S. will be slow and require continued relief beyond the current measures, according to experts at Wharton.Knowledge @ Wharton - 3/31/2020
For Jon Hartley, the power of economic forces and how they are applied has been an ongoing passion. Before he came to Wharton for his MBA, his interests led him to the Federal Reserve, investment management, Jeb Bush’s 2016 Presidential campaign, and even the NFL as a statistical analyst….Wharton Stories - 05/05/2017