Lu Liu

• Julia Fonseca and Lu Liu (2024), Mortgage Lock-In, Mobility, and Labor Reallocation, Journal of Finance. Abstract

  We study the impact of rising mortgage rates on mobility and labor reallocation. Using individual-level credit record data and variation in the timing of mortgage origination, we show that a 1 p.p. decline in mortgage rate deltas (Δr), measured as the difference between the mortgage rate locked in at purchase and the current market rate, reduces moving rates by 0.68 p.p, or 9%. This effect is economically meaningful and implies that projected rate increases until 2033 will reduce moving by 25%. Moreover, we show that this relationship is nonlinear: once Δr is high enough, households’ alternative of refinancing without moving becomes attractive enough that moving probabilities no longer depend on Δr. Lastly, we find that mortgage lock-in attenuates household responsiveness to shocks to employment opportunities, measured as MSA-level wage growth and instrumented with a shift-share instrument. The responsiveness of moving rates to wage growth is half as large for households who are more locked in (below-median Δr) than for those who are less locked in. We provide causal estimates of mortgage lock-in effects, highlighting unintended consequences of monetary tightening with long-term fixed-rate mortgages on mobility and labor markets.

• Jack Fisher, Alessandro Gavazza, Lu Liu, Tarun Ramadorai, Jagdish Tripathy (2024), Refinancing Cross-Subsidies in the Mortgage Market, Journal of Financial Economics, 158 (8). Abstract

  In household finance markets, inactive households can implicitly cross-subsidize active households who promptly respond to financial incentives. We assess the magnitude and distribution of cross-subsidies in the mortgage market. To do so, we build a structural model of household mortgage refinancing and estimate it on rich administrative data covering the stock of outstanding mortgages in the UK. We estimate sizeable cross-subsidies that flow from relatively poorer households and those located in less-wealthy areas towards richer households and those located in wealthier areas. Our work highlights how the design of household finance markets can contribute to wealth inequality.

  Description
  Journal of Financial Economics
• Lu Liu (Under Revision), The Demand for Long-Term Mortgage Contracts and the Role of Collateral. Abstract

  Long-term fixed-rate mortgage contracts protect households against interest rate risk, yet most countries have relatively short interest rate fixation lengths. Using administrative data from the UK, the paper finds that the choice of fixation length tracks the life-cycle decline of credit risk in the mortgage market: the loan-to-value (LTV) ratio decreases and collateral coverage improves over the life of the loan due to principal repayment and house price appreciation. High-LTV borrowers, who pay large initial credit spreads, trade off their insurance motive against reducing credit spreads over time using shorter-term contracts. To quantify demand for long-term contracts, I develop a life-cycle model of optimal mortgage fixation choice. With baseline house price growth and interest rate risk, households prefer shorter-term contracts at high LTV levels, and longer-term contracts once LTV is sufficiently low, in line with the data. The mechanism helps explain reduced and heterogeneous demand for long-term mortgage contracts.

  Description
  Revise & Resubmit, Review of Economic Studies.
• Steffen Andersen, Cristian Badarinza, Lu Liu, Julie Marx, Tarun Ramadorai (2022), Reference Dependence in the Housing Market, American Economic Review, 112 (10), pp. 3398-3440. Abstract

  We quantify reference dependence and loss aversion in the housing market using rich Danish administrative data. Our structural model includes loss aversion, reference dependence, financial constraints, and a sale decision, and matches key nonparametric moments, including a “hockey stick” in listing prices with nominal gains, and bunching at zero realized nominal gains. Households derive substantial utility from gains over the original house purchase price; losses affect households roughly 2.5 times more than gains. The model helps explain the positive correlation between aggregate house prices and turnover, but cannot explain visible attenuation in reference dependence when households are more financially constrained.

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  SSRN
• Lu Liu, Non-Salient Fees in the Mortgage Market. Abstract

  This paper studies supply-side product pricing when consumers underreact to non-salient fees. Using comprehensive data on issued and offered mortgages in the UK, I document that lenders differ substantially in the fees they charge, and that borrowers appear less overall cost-sensitive to products with fees. In order to distinguish from demand factors such as unobservable preferences or product characteristics, I show that lenders pass on firm-specific funding cost shocks via fees, but not interest rates, consistent with strategic pricing of fees, and maintaining competitive prices in the salient price dimension, interest rates. I further find heterogeneity in pricing across lenders: those who rely on high fees tend to have higher funding cost, lower return on equity and larger branch networks, in line with a specialization equilibrium in which high-cost lenders are able to match with less cost-sensitive consumers.

Past Courses

• FNCE2510 - Fnce of Buyouts & Acqs

  The course focuses on financial tools, techniques, and best practices used in buyouts (financial buyers) and acquisitions (strategic buyers). While it will touch upon various strategic, organizational, and general management issues, the main lens for studying these transactions will be a financial one. It will explore how different buyers approach the process of finding, evaluating, and analyzing opportunities in the corporate-control market; how they structure deals and how deal structure affects both value creation and value division; how they add value after transaction completion; and how they realize their ultimate objectives (such as enhanced market position or a profitable exit). The course is divided into two broad modules. The first module covers mergers and acquisitions, and the second one studies buyouts by private equity partnerships. FNCE 2030 or FNCE 2070 are recommended.

• FNCE9260 - Empirical Meth Corp Fn

  The course will cover a variety of micro-econometric models and methods including panel data models, program evaluation methods e.g. difference in differences, matching techniques, regression discontinuity design, instrumental variables, duration models, structural estimation, simulated methods of moments. The structure of the course consists of lectures, student presentations, and empirical exercises. Published studies will be utilized in a variety of fields such as corporate finance, labor economics, and industrial organization to illustrate the various techniques. The goal of the course is to provide students with a working knowledge of various econometric techniques that they can apply in their own research. As such, the emphasis of the course is on applications, not theory. Students are required to have taken a graduate sequence in Econometrics, you should be comfortable with econometrics at the level of William Green's "Econometric Analysis of Cross-Section and Panel Data".

• Homer Hoyt Dissertation Award (American Real Estate and Urban Economics Association, AREUEA), 2024
• Arthur Warga Award, Best Paper in Fixed Income (SFS Cavalcade), 2023
• Marshall Blume Prize, 1970

Knowledge @ Wharton

• Overwhelmed by Too Many Choices When Shopping? Wharton Retail Expert Weighs In, Knowledge @ Wharton - 12/19/2024
• Michael Lee, Oatly North America’s EVP & Executive Creative Director, Knowledge @ Wharton - 12/19/2024
• Why Anchor Institutions Are Vital to Local Economies, Knowledge @ Wharton - 12/17/2024
• Is the American Dream of Homeownership Still Within Reach?, Knowledge @ Wharton - 12/17/2024
• Even Under Trump, AI Governance Is Here to Stay, Knowledge @ Wharton - 12/17/2024
• 2024 Ripple Rewind (Part 2), Knowledge @ Wharton - 12/17/2024
• What Are the Best Countries of 2024?, Knowledge @ Wharton - 12/16/2024
• Your Pride Could Affect Your Workplace Reputation, Knowledge @ Wharton - 12/12/2024
• Samantha Baker, VP of Commerce at theSkimm, Knowledge @ Wharton - 12/12/2024
• NFL Stats & Analysis with Ben Solak, Knowledge @ Wharton - 12/11/2024