2021 Wisconsin Real Estate Research Conference

June 10 and 11th, 2021 - Zoom

Thursday, June 10th: Zoom Code: 980 0891 3763
Time Speaker Affiliation Topic
11:50am - 12:00pm Gathering and Introductions
Section 1: Microstructure of Housing Markets
12:00pm -  1:00pm Jia Xie California State University, Fullerton Market Distortions with Collusion of Agents
 1:00pm -  2:00pm Anthony Lee Zhang Chicago Booth Liquidity in Residential Real Estate Markets
 2:00pm - 2:30pm Coffee/Tea Break
Section 2: Housing and Inequality
 2:30pm -  3:30pm Yongqiang Chu University of North Carolina, Charlotte The Color of Hedge Fund Activism
 3:30pm -  4:30pm Dan McMillen University of Illinois, Chicago Measures of Vertical Inequality in Assessments

Friday, June 11th: Zoom Code: 995 2915 3136
Time Speaker Affiliation Topic
10:20am - 10:30am Gathering and Introductions
Section 3: Mortgage Market
10:30am - 11:30am Haoyang Liu Federal Reserve Bank of New York Defragmenting Markets -  Evidence from Agency MBS
11:30am - 12:30pm Yildiray Yildirim City University of New York Deep Learning for disentangling Liquidity-constrained and Strategic Default
12:30pm -  1:30pm Coffee/Tea Break
Section 4: Housing Cycle, Financial Stability, Corporate Finance
 1:30pm -  2:30pm Timothy McQuade University of Colorado - Boulder The 2000s Housing Cycle With 2020 Hindsight - A Neo-Kindlebergerian View
 2:30pm -  3:30pm Amiyatosh Purnanandam University of Michigan Did Banks Pay "Fair" Returns to Taxpayers on TARP?
 3:30pm -  4:30pm Neng Wang Columbia University Leverage Dynamics under Costly Equity Issuance
 4:30pm -  4:40pm Wrap Up


Jia Xie (Mihaylo College of Business and Economics, California State University, Fullerton)

Market Distortions with Collusion of Agents

Abstract: We investigate housing market distortions with collusion of agents. The agency problem where agents sell clients’ houses with price discounts while their own with price premiums is quite straightforward. However, the issue that agents collaborate with each other to further maximize their own interests is elusive. When agents collude, the resulting market distortions may even be worse than previous studies suggested. Indeed, this paper finds that the agency problem and market distortions are much more severe with agent collusion, as both the discounts associated with clients’ houses and the premiums with agents’ own homes become much larger when the two agents collude each other.

Anthony Lee Zhang (Chicago Booth School of Business)

Liquidity in Residential Real Estate Markets

Abstract: We build a rich panel dataset tracking two measures of housing market liquidity: time-on-market and price dispersion. The two measures co-vary closely at seasonal and business-cycle frequencies, but there is substantial independent variation in the cross-section of counties. This suggests that the two measures reflect different dimensions of market liquidity. Using a housing search model, we show that time-on-market and price dispersion can be thought of as equilibrium outcomes from a supply and demand system for liquidity. Consistent with the model’s predictions, proxies for liquidity supply are negatively correlated with both measures, whereas a proxy for liquidity demand is negatively correlated with time-on-market, but positively correlated with price dispersion.

Yongqiang Chu (University of North Carolina at Charlotte)

The Color of Hedge Fund Activism

Abstract: Banks targeted by hedge fund activism reduce racial disparities in mortgage approval rates and interest rates. However, racial differences in mortgage foreclosure rates do not change, suggesting that the effect is not driven by changes in risk or risk preferences. We find that target banks experience higher turnovers of mortgage officers and open new bank branches to address the lending discrimination problem.

Dan McMillen (University of Illinois, Chicago)

Measures of Vertical Inequality in Assessments

Abstract: Standard measures of vertical inequity suggest that assessments are regressive in the sense that high-priced properties are often assessed at lower rates than low-priced properties. Conventional measures of measuring vertical inequality include a simple descriptive statistic – the price-related differential – and measures based on regressions. We show that regression based procedures are seriously flawed, with a bias that tends to imply regressivity even when it is not present. To supplement the price-related differential, we propose three approaches that focus on the entire distribution of assessments rather than attempting to provide a single measure to characterize the entire assessment process. The first is to compare Gini coefficients for sales prices and assessments. These statistics directly measure vertical inequality by determining whether the distribution of assessments is not as skewed toward low-value properties as are sales prices. Second, we show that the Suits Index, which has been used to analyze tax progressivity, can be used to analyze whether assessments are progressive or regressive. The third approach is to test formally whether the distribution of log sales prices is statistically different overall from the distribution of log assessed values. We compute all of the measures using data on sales prices and assessments for 48 large central city counties.

Haoyang Liu (Federal Reserve Bank of New York)

Defragmenting Markets: Evidence from Agency MBS

Abstract: Agency mortgage-backed securities (MBS) issued by Fannie Mae and Freddie Mac have historically traded in separate forward markets. We study the consequences of this fragmentation, showing that market liquidity endogenously concentrated in Fannie Mae MBS, leading to higher issuance and trading volume, lower transaction costs, higher security prices, and a lower primary market cost of capital for Fannie Mae. We then analyze a change in market design—the Single Security Initiative—which consolidated Fannie Mae and Freddie Mac MBS trading into a single market in June 2019. We find that consolidation increased the liquidity and prices of Freddie Mac MBS without measurably reducing liquidity for Fannie Mae; this was in part achieved by aligning characteristics of the underlying MBS pools issued by the two agencies. Prices partially converged prior to the consolidation event, in anticipation of future liquidity. Consolidation increased Freddie Mac’s fee income by enabling it to remove discounts that previously compensated loan sellers for lower liquidity.

Yildiray Yildirim (City University of New York)

Deep Learning for disentangling Liquidity-constrained and Strategic Default

Abstract: We disentangle liquidity-constrained default and the incentives for strategic default using Deep Neural Network (DNN) methodology on a proprietary Trepp data set of commercial mortgages. Our results are consistent during the severe Financial Crisis (2008) and the plausible economic catastrophe ensuing from COVID-19 pandemic (2020-2021). We retrieve the motive of default from observationally equivalent delinquency classes by bivariate analysis of default rate on Net operating income (NOI) and Loan-to-Value (LTV). NOI, appraisal reduction amount, prepayment penalty clause, balloon payment amongst others co-determine the delinquency class in highly nonlinear ways compared to more statistically significant variables such as LTV. Prediction accuracy for defaulted loans is higher when DNN is compared with other models, by increasing flexibility and relaxing the specification structure. These findings have significant implications for investors, rating agencies and policymakers.

Timothy McQuade (University of Colorado - Boulder)

The 2000s Housing Cycle With 2020 Hindsight: A Neo-Kindlebergerian View

Abstract: We re-examine the 2000s housing cycle with the benefit of a decade of additional data. With "2020 hindsight," the 2000s housing cycle is not a boom-bust but rather a boom-bust-rebound. At the city level, areas with the largest price increases during the boom had the largest busts but also the fastest growth after the trough in 2012 and as a result have had the largest price appreciation over the full cycle. A standard urban framework of house price growth determined by local income, amenities, and supply determinants fits the cross-section of city house price growth between 1997 and 2019. The implied long-run fundamental is correlated not only with long-run price growth but also with a strong boom-bust-rebound pattern. We interpret the episode in a neo-Kindlebergerian model where an asset cycle starts with an improvement in economic fundamentals, the stochastic trend growth of the "dividend" to living in a city. Agents learn about the trend by observing dividends but use diagnostic rather than rational updating. Diagnostic learning generates a boom from over-shooting of beliefs by home-buyers and lenders. A bust ensues when beliefs start to correct, exacerbated by a price-foreclosure spiral that drives prices below their long-run level. The rebound follows as prices converge to a path commensurate with higher fundamental growth. We calibrate the model to match the national boom-bust-rebound and show it also can account for the cross-city patterns.

Amiyatosh Purnanandam (University of Michigan)

Did Banks Pay "Fair" Returns to Taxpayers on TARP?

Abstract: Financial institutions received billions of dollars from the U.S. Treasury in the form of preferred equity under the Troubled Asset Relief Program (TARP) in 2008. Investments were made during a bad state, but the repayments came in a relatively good time. Comparing TARP's realized returns to private market securities with similar or lower risk over the same time period, we show that the recipients paid considerably lower returns to the taxpayers than the benchmarks. Consequently, the recipient banks enjoyed a subsidy of over $50 billion. The ex-post renegotiation of TARP contract terms were beneficial to the recipients, and soon after the repayment banks increased dividend payout and CEO compensation. While we do not evaluate the net social benefit of TARP, our results challenge the oft-cited narrative that taxpayers made profits on TARP investments from a purely financial standpoint.

Neng Wang (Columbia University)

Leverage Dynamics under Costly Equity Issuance

Abstract: We propose a theory of leverage dynamics based on a parsimonious model with a cashflow process subject to diffusion and jump shocks, external financing through short-term debt and equity, and crucially equity issuance costs. We show that both plausible average leverage outcomes and observed leverage dynamics can be explained by firms’ efforts to avoid incurring equity issuance costs. Paradoxically, it is the high cost of equity issuance that causes the firm to keep leverage low, in contrast to the predictions of Modigliani-Miller and Leland tradeoff and Myers’ pecking-order theories. The marginal source of external financing on an on-going basis is debt. Leverage can only increase as a result of losses. When the firm is at its target leverage any additional profit is paid out, and when leverage reaches the firm’s endogenous debt capacity any additional loss either triggers a costly recapitalization or a default. When leverage is close to the firm’s target, it tends to revert to target, but beyond a certain point the expected change in leverage is positive and the firm enters a leverage death spiral.

Keywords:Wisconsin, UW Madison, Real Estate, Summer, Conference, 2021   Doc ID:119496
Owner:Dayin Z.Group:Wisconsin School of Business
Created:2022-07-08 18:40 CSTUpdated:2022-07-08 19:05 CST
Sites:Wisconsin School of Business
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