Older home sellers receive lower returns than younger ones. Homes sold by older people have fewer major renovations but higher rates of poor upkeep. Older sellers are also more likely to sell off-MLS (``pocket listings'') and to investors, leading to lower prices. These patterns suggest that older sellers may be disproportionately disadvantaged by agents' incentive to maximize fees through generating high sale volume instead of maximizing sale prices. Age-related cognitive declines make the elderly more vulnerable. For causal evidence, we show that reforms making private listings more transparent reduced both the prevalence of pocket listings and the magnitude of the age gap in returns. 

Economic models often assume that agents always know the market value of their assets. We use residential property tax assessment as a laboratory to test this assumption for housing. We first show that assessed market value (AMV) is a noisy proxy for transaction-based market values (TMV). Innovations in AMV are less volatile, are weakly correlated with, and lag innovations in TMV. An AMV-based, national-level house price index has shallower troughs and shorter peaks than its TMV-based counterpart. We merge in credit bureau data to test whether homeowners use AMVs, as signals of housing wealth, to make consumption decisions. Using local mass reassessments as an instrument, we find that AMV changes causally effect the likelihood that households take out a new home equity line of credit (HELOC) with a similar economic magnitude as TMV changes. A partial equilibrium calibration exercise suggests that innovations in AMV can explain approximately 1% of annual HELOC origination. Overall, our results suggest that homeowners do not fully know the value of their homes.

This paper studies the May 2023 change in the conforming mortgage upfront guarantee fee schedule. Consistent with incomplete pass-through, lenders raise rejection rates and sell fewer loans to the GSEs when fees rise. For small-dollar mortgages (SDM), pass-through is near zero and rejection rates are more sensitive to fee increases. This implies that the overall incomplete pass-through is partly driven by liquidity-constrained borrowers and that the inequality in mortgage access via higher rejection rates on SDMs is partly driven by lenders' inability to pass costs onto SDM borrowers. Without offsetting effects from fee cuts, fee hikes reduced aggregate mortgage origination by 8%.

This paper compares the careers of Ivy League athletes to those of their non-athlete classmates. Combining team-level information on all Ivy League athletes from 1970 to 2021 with resume data for all Ivy League graduates, we examine both post-graduate education and career choices as well as career outcomes. In terms of industry choice, athletes are far more likely to go into business and Finance related jobs than their non-athlete classmates. In terms of advanced degrees, Ivy League athletes are more likely to get an MBA and to receive it from an elite program, although they are less likely to pursue an M.D., a Ph.D., or an advanced STEM degree. In terms of career outcomes, we find that Ivy League athletes outperform their non-athlete counterparts in the labor market. Athletes attain higher terminal wages and earn cumulatively more than non-athletes over the course of their careers controlling for school, graduation year, major, and first job. In addition, they attain more senior positions in the organizations they join. We also find that athletes from more socioeconomically diverse sports teams and from teams that have lower academic admissions thresholds have higher career outcomes than non-athletes. Collectively, our results suggest that non-academic human capital developed through athletic participation is valued in the labor market and may support the role that prior athletic achievement plays in admissions at elite colleges.   

In 2021, the U.S. Treasury instituted hard caps to reduce Government-Sponsored Enterprise exposure to second-home and investment-property mortgages, leading to declines in their purchase of affected mortgages. The policy lowered credit supply to affected housing investors, with higher interest rates and lower originations. Bank and non-bank lenders display a similar supply response, suggesting that deposits offer no advantage in mortgage lending. Lenders adjust at the portfolio level by reallocating mortgage credit across local markets, suggesting that they manage credit provision market-by-market. Rental housing supply and condominium prices decline while rents increase, consistent with higher financing costs in the rental market from the policy.

This paper proposes a non-pecuniary measure of career achievement, seniority. Based on a database of over 130 million resumes, this metric exploits the variation in how long it takes to attain job titles. When non-monetary factors influence career choice, assessing career attainment via non-wage measures, such as seniority, has significant advantages. Accordingly, we use our seniority measure to study labor market outcomes of VC-backed entrepreneurs. Would-be founders experience accelerated career trajectories prior to founding, significantly outperforming graduates from same-tier colleges with similar first jobs. After exiting their start-ups, they obtain jobs about three years more senior than their peers who hold (i) same-tier college degrees, (ii) similar first jobs, and (iii) similar jobs immediately prior to founding their company. Even failed founders find jobs with higher seniority than those attained by their non-founder peers. 

Among owner-occupied single-family homes in the United States that enjoy the same set of property tax-funded amenities and pay the same statutory property tax rate, owners of inexpensive houses pay almost 50% higher effective tax rates than owners of expensive houses because tax assessments are regressive with respect to house price. Using a near-national data set, I provide empirical evidence that assessment regressivity is partially caused by valuation methods that do not fully incorporate important pricing information such as neighborhood characteristics. Systematic sorting across neighborhoods implies that economically disadvantaged households disproportionately bear the cost of this valuation problem. The findings potentially have important implications for wealth inequality and other forms of ad valorem tax.

Rising homeowners’ insurance prices increase housing and debt service costs, while household coverage adjustments may increase exposure to expense shocks. Using novel data linking mortgages to insurance policies, we develop a quality-adjusted price index showing that the menu of insurance costs increased 18 percent more than premium expenditure growth from 2013-2022. During this period, households responded by increasing deductibles and reducing coverage relative to structure values, leaving them more exposed to financial shocks. Our estimates reveal low household demand elasticities for insurance features, though these elasticities increase significantly during home purchases, refinancing, or when households receive updated property valuations. These findings suggest inattention and information frictions substantially influence insurance decisions. Policy implications favor behavioral nudges and regular property assessments over price-based interventions to reduce household financial vulnerability in insurance markets. Credit utilization results suggest that households self-insure when faced with higher insurance costs.

This paper exploits the scheduled expiration dates of property tax breaks to study how homeowners' credit consumption and debt payment behavior respond to anticipated expense shocks. When tax breaks end, credit card balance, home equity credit line balance, new debt inquiries, and mortgage balance do not change, implying that credit consumption is smooth. However, homeowners become persistently delinquent on their student loan payments, which suggests that the marginal utility of consumption and from staying current on other debt (e.g., mortgage, auto, and credit card) is larger than the disutility from becoming delinquent on student loan payments. When budget constraints bind, student loans lie at the bottom of the debt repayment preference ranking. The results also show that expense shocks matter for student loan repayment, even for homeowners. 

Do college alumni networks within a firm confer labor market benefits? Using data from a large online job platform, we construct a panel data of workers' job histories and the size of undergraduate alumni networks at their firms. We assess whether having a larger alumni network at the firm impacts their future job outcomes with a saturated fixed effects model. We find that larger alumni networks increase an individual's likelihood of promotion, moving firms, and job title improvement in the 3 to 5 years after moving. Our analysis supports productivity gains and referrals as plausible mechanisms of these effects. Understanding college alumni networks as a dimension of the returns to college has important implications for human capital investment decisions, such as college enrollment and college choice.

Model risk captures the uncertainty in model-derived point estimates of unobserved risks and has implications for financial markets. This paper studies model risk in the setting of residential physical risk assessment by comparing outputs of two prominent risk modelers, CoreLogic (CL) and First Street Foundation (FSF). We document five stylized facts about model risk in physical risk models, defined as the absolute difference in the two modelers' estimates of average annual loss (AAL) for the same property and set of perils (flood, hurricane wind, and wildfire). (i) For the average single-family residence (SFR), model risk is expected to cost approximately \$300 per year, which is roughly equal to the mean of each modeler's AAL estimates. (ii) Aggregating the estimates up to the tract or the county level does not substantially reduce the disagreement. (iii) Model risk is disproportionately borne by economically vulnerable households. (iv) There is little association between model risk and insurance premiums, which are four to ten times more sensitive to the variation in CL's risk estimates than FSF's, suggesting that insurers mostly use data from one modeler to price insurance contracts and ignore model risk. (v) Net in-migration rates are highest in places with the highest levels of model risk, implying that aggregate migration decisions ignore model risk. Taken together, these facts imply that uncertainty about modeled estimates of physical risk is not appropriately priced in housing markets.