«Refinancing Mistakes? Sumit Agarwal, Richard J. Rosen, and Vincent Yao November 2012 WP 2013-02 Why Do Borrowers Make Mortgage Refinancing Mistakes? ...»
Why Do Borrowers Make Mortgage
Federal Reserve Bank of Chicago
Sumit Agarwal, Richard J. Rosen,
and Vincent Yao
Why Do Borrowers Make Mortgage Refinancing Mistakes?
Sumit Agarwal, Richard J. Rosen, and Vincent Yaoα
Refinancing a mortgage is often one of the biggest and most important financial decisions that
people make. Borrowers need to choose the interest rate differential at which to refinance and, when that differential is reached, they need to take the steps to refinance before rates change again. The optimal differential is where the interest saved by refinancing equals the sum of refinancing costs and the option value of refinancing. Using a unique panel data set, we find that approximately 59% of borrowers refinance sub-optimally – with 52% of the sample making errors of commission (choosing the wrong rate), 17% making errors of omission (waiting too long to refinance), and 10% making both errors. Financially sophisticated borrowers make smaller mistakes, refinancing at rates closer to the optimal rate and waiting less after mortgage rates reach the borrowers’ trigger rates. Evidence suggests borrowers learn from their refinancing experiences as they make smaller mistakes on their second refinancing than on their first one.
Keywords: Household Finance, Mortgages, Refinance, Option Value, Financial Crisis, Rational Inattention JEL classification: G11, G21 We would like to thank Caitlin Kearns for excellent research assistance. Additionally, we would also like to thank Gene Amromin, Zahi Ben-David, Souphala Chomsisengphet, John Driscoll, Doug Evanoff, Erik Hurst, David Laibson, Amit Seru, and seminar participants at the Federal Reserve Bank of Chicago, and the Federal Reserve Board for helpful comments and suggestions. The views expressed in this research are those of the authors and do not necessarily represent the policies or positions of the Federal Reserve Bank of Chicago, the Federal Reserve System, or Fannie Mae.
α Agarwal: National University of Singapore, firstname.lastname@example.org; Rosen: Federal Reserve Bank of Chicago, email@example.com; and Yao: Fannie Mae, firstname.lastname@example.org.
1. Introduction Refinancing a mortgage is as American as apple pie. Over the period 2000–09, Americans took out 52 million mortgages to finance the purchase of new homes, but 71 million to refinance existing mortgages (henceforth, refis).1 That is, there were 1.4 refis for every mortgage for a home purchase. Given that purchasing a home is generally the biggest financial decision a household makes, that makes the choice of when to refinance a major event for most households (Campbell, 2006). Research suggests that people often make poor financial decisions (Campbell, Jackson, Madrian, and Tufano, 2011). We explore whether this is true for refis as well. As we describe next, much of the existing literature focuses on whether people leave money on the table (Choi, Madrian, and Laibson, 2011) – what we call an error of commission. But, as we show here, during the refinancing process, households also make errors of omission – that is, by failing to refinance at the optimal time. When thinking about the costs of sub-optimal financial decision-making, it is important to focus on both errors of commission and errors of omission.2 Research on errors of commission suggests that consumers often make financial mistakes.
For example, many individuals do not hold checking accounts (Hilgert et al., 2003) or take out payday loans at astronomical interest rates when cheaper forms of credit are available (Agarwal, Skiba, and Tobacman, 2009). More broadly, it is puzzling that less than 30 percent of U.S.
households directly participate in equity markets (Cole and Shastry, 2009; Li, 2012) and among those who do hold stocks, many have highly concentrated portfolios and trade excessively (Korniotis and Kumar, 2011).
1 These numbers are based on the authors’ calculations from data that mortgage lenders are required to file under the Home Mortgage Disclosure Act (HMDA).
2 The cost of a suboptimal decision for mortgage of $200,000 with an interest rate differential of 200 basis points can be a few thousand dollars – a substantial fraction of the homeowner’s disposable income (Agarwal, Driscoll, and Laibson, 2012).
Household decisions that are suboptimal have potentially important effects on individual welfare. There also can be significant social ramifications arising from poor financial decisionmaking. The sharp decline in housing markets and the associated rise in mortgage defaults surrounding the recent financial crisis in the United States arguably were due, at least to some degree, to poor financial decision-making behavior by some households. Despite the growing salience of the issue of household financial decision-making, our current understanding of exactly how individuals make their financial decisions is limited.
optimally requires solving a complicated system of partial differential equations. 3 This can prove to be problematic because significant cognitive ability often is needed to properly make optimal financial choices (Agarwal and Mazumder, 2013). The complexities in determining the optimal time to refinance lead many, including financial advisors, to rely on rules of thumb, that is, simplified solutions. Often, for example, financial advisers advocate the use of a net present value (NPV) rule that says borrowers should refinance their mortgages when the net present value of the interest saved exceeds the cost of refinancing. This rule ignores the potentially large loss in value from exercising the option to refi today rather than in the future (Agarwal, Driscoll, and Laibson, 2012). This paper explores how errors in refinancing are related to borrower characteristics.
Refinancing a mortgage requires not only that a borrower select an interest rate at which she is willing to refinance, but that she take the actions necessary to refi (such as contacting a broker or bank and completing paperwork). Agarwal, Driscoll, and Laibson (2012) argue that borrowers do not actively monitor mortgage rates and, even if they notice that the mortgage rate has reached their “trigger rate” for refinancing optimally, they may not immediately refi because 3 See Dunn and McConnell (1981a, 1981b), Dunn and Spatt (2005), and Hendershott and Van Order (1987).
Agarwal et al., 2007 and Korniotis and Kumar; 2011). Some delay may be the optimal response for busy borrowers – what some refer to as rational inattention (e.g., Sims, 2003; Reis, 2006).
We show that many borrowers do not refinance immediately when their trigger rate is reached, and discuss whether this may reflect rational inattention or a more costly form of distraction.
To most clearly show the relationship between refinancing mistakes and borrower characteristics, we focus on borrowers who refinance in order to reduce mortgage payments.
Our sample does not include borrowers who refinance in order to extract equity from their homes – a common practice that can be used to increase current consumption (Greenspan and Kennedy, 2008; Hurst and Stafford, 2004). When borrowers want to use their homes as a “piggy bank” this way, it changes the way they should think about when to refinance.4 For this reason, we exclude refis where borrowers extract equity from our analysis.
Using a unique sample of people who choose to refi during 1998–2011, we find that 52% of refinancers do so at a rate that was at least 50 basis points from what we estimate as the optimal refi rate for that borrower (errors of commission) and about 17% of borrowers waited at least six months or longer before they refinanced (errors of omission). Overall, 59% of refinancers make at least one error, while 10% make both errors. Most borrowers, including those who make large mistakes, refinance at a rate differential that is too small, that is, when the interest rate on the refinanced mortgage is not sufficiently below the initial mortgage rate.
We show that the errors of commission in choosing the refinancing rate and of omission in the timing of refinancing are correlated with borrower sophistication. Smaller mistakes are associated with borrowers having larger FICO credit scores and higher income – variables that 4 See, Dunn and McConnell (1981a, 1981b), Dunn and Spatt (2005), Hendershott and Van Order (1987), Chen and Ling (1989), Follain, Scott, and Yang (1992), Yang and Maris (1993), Stanton (1995), Longstaff (2004), and Deng and Quigley (2006).
sophisticated borrowers refinance at interest rates closer to their respective optimal refinancing rate and spend less time with the average mortgage rate below that optimal rate before they refinance their initial mortgage. We confirm that borrowers also make smaller mistakes when mortgages are more important to them (as measured by the ratio of the mortgage size to the borrower’s income).
Our paper is broadly related to the growing literature that finds evidence linking the creation of the real estate bubble in the early 2000s to misaligned incentives of intermediaries and individuals - e.g., Keys, Mukherjee, Seru, and Vig (2010), Ben-David (2011), and Jiang, Nelson, and Vytlacil (2012).
The rest of the paper is organized as follows. In section 2, we review the literature, and in section 3, we provide a description of the data we use. The main results are presented in section
4. Finally, we present our conclusions in section 5.
2. Literature Review Refinancing has long been of interest to both practitioners and researchers interested in the valuation of mortgage-backed securities and researchers interested in consumer choice.
Dickinson and Heuson (1994) and Kau and Keenan (1995) provide extensive surveys.
There is an extensive literature deriving the optimal time for a borrower to refinance. The initial work in this area used continuous time option valuation models (Dunn and McConnell, 1981a, 1981b). Later papers relaxed some of the assumptions of the early models, such as by
These papers implicitly solved for the optimal refinancing differentials as solutions to partial differential equations, which were evaluated numerically. Finally, Agarwal, Driscoll, and Laibson (2012; henceforth, ADL) derived a closed-form solution for the optimal interest rate at which to refinance. 6 We use the ADL model to derive the optimal refi rate used in our paper.
It soon became apparent that borrower behavior deviated in significant ways from the predictions of the models described in these papers. As we describe here, there can be many reasons why borrowers refinance when the rate differential is too small. However, participants in the mortgage-backed securities industry had long noticed that some consumers did not refinance even after very large drops in mortgage rates. The failure of this group to exercise “in the money” options led them to be labeled “woodheads.” Some borrowers exhibited the opposite problem: They refinanced even when rates had risen. These discrepancies were picked up in estimates of the hazard rates of default (Green and Shoven, 1986; Schwartz and Torous 1989, 1992, 1993; Giliberto and Thibodeau, 1989; Richard and Roll, 1989).
To resolve these puzzle, some researchers, as reported in their studies, added additional complexity to the option-pricing model to address the issues raised in the previous paragraph.
Archer and Ling (1993) add heterogeneity in transaction costs. Stanton (1995) adds both heterogeneity in transaction costs and an exogenous probability of prepayment. Downing, Stanton, and Wallace (2005) allow variations in housing price to affect prepayment of mortgages. In hazard rate estimates of prepayment of mortgages, LaCour-Little (1999) and 5 See also Dunn and Spatt (2005), Chen and Ling (1989) and Follain, Scott and Yang (1992).
6 ADL (2012) compare their interest rate differentials with those computed numerically by Chen and Ling (1989), who do not make many of our simplifying assumptions. They find that the two approaches generate recommendations that differ by fewer than 10 basis points. Moreover, Follain, Scott, and Yang (1992) characterize the differentials they derive as implying “that the commonly used ‘rule of thumb’—refinance if the interest rate declines by 200 basis points—is a fair approximation.”
Several researchers, including Hurst (1999) and Hurst and Stafford (2004), have empirically examined refis for consumption smoothing purposes. A borrower can use a refi to smooth consumption by cashing out some of the home equity as part of the process. We do not want to examine refinancings where consumption smoothing plays a major role, so we restrict our attention to refis where there is at most minimal equity cash out.
LaCour-Little (1999) distinguishes among various sources of prepayment – for example, borrower mobility, liquidity demand, and interest-rate-driven rate-term refinancing – using a loan-level data set that provides “pure” refinancing behavior as opposed to “general” prepayment behavior. After excluding prepayments that might be for reasons other than a reduction in expected interest payments, LaCour-Little (1999) concludes that borrower and loan characteristics are significant factors driving prepayment behavior. This finding is especially true if the option is “at the money” as opposed to “in the money” or “out of the money.” Bennett, Peach, and Peristiani (2000) simulate the threshold at which individuals will refinance a mortgage loan conditional not only on the market conditions but also on individual borrower characteristics. For example, they predict that a person with good credit history and 70% loan-tovalue ratio could refinance at an interest rate differential of 70 basis points to 140 basis points.
We extend the approach in LaCour-Little (1999) by examining the relationship between the decision to refinance and characteristics of borrowers and loans.
There is a missing piece to many of the analyses discussed thus far: Borrowers often wait too long to refinance. Stanton (1995) develops a model of mortgage prepayment where mortgage holders face heterogeneous transaction costs. The model indicates that mortgage holders act as