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The Role of Consumer Confidence in Determining Mortgage Delinquencies

Explore the relationship between consumer confidence and mortgage delinquencies in the US pre and post the Global Financial Crisis, examining factors such as income, unemployment rate, and household sentiment.

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The Role of Consumer Confidence in Determining Mortgage Delinquencies

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  1. The Role of Consumer Confidence in Determining Mortgage Delinquencies Dr. IKM Mokhtarul Wadud Deakin University, Australia Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  2. Introduction • Economic theory suggests prevalence of a range of effects of consumers’ expectation and sentiment formed at the individual and household level • on income, output, employment and financial market. • Anumber of studies recently examined into the relationship of consumer sentiment with other economic and financial variables (Aktar et al, 2011; Gupta et al., 2014; Fisher, L. A. and Huh, H., 2016; Baghestania and Palmer, 2017; Gelper, Lemmens, and Croux, 2007). • Microeconomic focus with regard to the dynamics in consumer sentiment and household welfare appears to be generally scanty in the extant literature. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  3. Introduction (continued) • With the growth of the world economy through phases of globalisation and expansive benefits of freer market orientations, the households and businesses tend to thrive in the new millennium. • However, households confront sever problems due to increased volatility in the financial market as well as during periods of recession such as the global financial crisis (GFC). • Over the same time, provision of loans has been easy with little or inadequate control. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  4. Introduction (continued) • In the US economy in particular, loan delinquencies due to a lax credit system in the years preceding the GFC translated into the outbreak of the sub-prime crisis. • Mian and Sufi (2009): the expansion of mortgage debt provided to the marginal borrowers over 2002 to 2005, despite sluggish or negative household income growth,  high growth in household debt and increase in mortgage default in the US by 2007. • Indeed, delienquencyincreased over the GFC period for borrowers across all income levels, viz., middle-income, high income, and prime borrowers(Adelino, Schoar and Severino, 2016). Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  5. Introduction (continued) • In this study • we examine the factors affecting loan delinquency rates in the US and specifically the generic effects of consumer sentiment on delinquencies for both the pre and post GFC period. • We provide both theoretical and empirical link between sentiment indicators and delinquencies rates for mortgage, credit card and auto loans for 51 US states over a period from 2003 through 2017. • The household pessimism and optimism early indication about likely financial difficulty (prosperity) experienced by household, subsequently missing (meeting) the arrears of payments. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  6. Introduction (continued) • When consumer sentiment improves investors, households and lending institutions become more optimistic about financial conditions including funding costs, cash flow positions and possible equity gain through monetary value of collateral probability of loan defaults declines. • However, over-optimism about the future  a negative impact on delinquency causing individuals or households to take-up loans beyond their capacities. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  7. Introduction (Continued..) • The notion of loan delinquency is two-fold: • Ability to pay hypo: suggests that a borrower defaults due to unexpected shocks such as job loss, health problems, family bereavement etc. • Strategic default: indicates circumstances when a borrower intensionally choose to default on the loan...Often to be the cases of property mortgage loans, with capital gains (Kau, Keenan, & Kim, 1993, 1994) Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  8. Introduction (continued) • In this study, our main variable of interest is consumer confidence or sentiment measured with their perception about past, present and future financial conditions of the households. • We also examine the effects of income, unemployment rate and a number of other variables. • We use index of consumer sentiment based on University of Michigan consumer confidence survey. • The index of consumer sentiment is based on five questions asked to the respondents reflecting both current and future household finance business conditions. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  9. Overview of Loan Delinquencies and Consumer Sentiment in the US • The subprime crisis raised household loans and consumer pessimism. • Empirical evidence show loan delinquency is tied with economic conditions and consumer sentiment. • As per NBER data, recessions from 1970s todate correspond to declining CCI: See Figure 1 Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  10. Figure 1: CCI and NBER recession in the US Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  11. Overview of Loan Delinquencies..(Continued) Figure 1: • The period of recession identified by the NBER beginning from the late 1970s. • Each period of recession corresponds to generally declining consumer confidence index (CCI). Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  12. Overview of Loan Delinquencies…(continued) • Mortgage and other loan delinquencies varied widely among the American states. • The US states classified based on Delinquency rates exhibit cultural diversity, socio-economic inequality and partisanship with major political parties. Table 1 : • The states (top ten)with high loan delinquency rates tend to possess more diversity, higher unemployment, larger volume of loans and are legislatively controlled by the democratic party. • The states (bottom ten) with lower delinquency rates have lower volume of loans, lower average unemployment rate and are mostly controlled by the Republican party. • Arguably, the pro-welfare policies/ ideologies of the democrats accompany higher delinquency. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  13. Table 1: Key socio-political and economic statistics of the states with high and low loan default rates Panel A: States with top 10 (high) loan default rates Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  14. Overview of Loan Delinquencies and Consumer Sentiment in the US (Continued) • The theoretical prediction of a positive association of delinquencies with regard economic growth is well supported with US data. Figure 2: • CSI has a general adverse relationship with loan delinquency rates in the US. • As evident, consumers' and households’ optimism about their current and future financial conditions is expected to reduce their loan delinquencies and vice versa. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  15. Figure 2: Consumer sentiment index and delinquency rates in the US Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  16. Literature • Limited understanding of loan delinquencies and the factors driving them. • studies addressing the role of consumer sentiment or confidence is rather scanty. • Three recent studies that we draw our work upon include Matsukata and Sbordone (2004) and Crook and Banasik (2012). • Firstly, Matsusaka and Sbordone (2004)  investigate the link between consumer sentiment and economic fluctuations using vector auto regressions (VAR). • This gives an initial platform to pose a question such as “does consumer sentiment can explain financial difficulties faced by household as well?” Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  17. Literature (continued) • Secondly, Crook and Banasik (2012) model aggregate delinquency behaviour for consumer credit (including credit card loans and other consumer loans) and for residential real estate loans • In US using aggregate level consumer credit data up until 2008 • Focus is on long term co-integrating relationships between economic fundamental and default behaviours • based on ability to pay hypothesis and strategic default choice hypothesis. • Thirdly, Mocetti and Viviano (2017) examine the relationship between income shocks and delinquency behaviour in the Italian mortgage market • find that bank lending policies are significantly tied with the quality of the selections of borrowers, hence delinquencies. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  18. Literature (continued) • As evident from the preceding discussion, there is a dearth in the extant literature linking loan delinquencies and consumer sentiment, which is a primary driver for aggregate demand, income and growth; • The contributions of our study: • We provide both theoretical and empirical evidence revealing nexus between consumer sentiment and loan delinquencies. • We consider consumer confident survey data (Univ. of Michigan), which makes up of two components, reflecting both fundamental micro and macroeconomic and sentiment of consumers. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  19. Literature (continued) • Third, we use a panel framework encompassing 51 American states, which provides a better understanding • of how the dynamics of individual states within United States explain household consumer credit delinquency in general and • mortgage, credit cards and auto loans delinquency rates, in particular. • Fourth, the diversity of individual states within US modelled in a panel framework could be a good reflection of how consumers’ perception shape their borrowing behaviour. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  20. The Analytical Model • A household decides whether to default (due to inability or strategically) on a loan repayment after taking the family utility and budget into account (Campbell et al., 2015). • Equity of a house Holmes and are Lacour-Little (2013), equity of a house, Etis: Et= MVt– Dt Eq.(1) MVt=Market value of the house and Dt= Total Debt. • MV rises due to increased value of the house and D falls with principal and interest repayments. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  21. The Analytical Model (continued) • Assuming MV0= initial market value, D0 = Debt and E0 = Equity • We can write,  Eq. (2) [Given E0 = MV0- D0] Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  22. The Analytical Model (continued) • Holmes et al. (2013) show that probability of negative equity depends on the changes in the purchase price of house, MVt - MV0 and changes in debt Dt-D0, such that, • Eq. (3) • Here X represents a set of control variables (such as house locations, house price cycles, house size or other maintenance cost, financial environment, interest rate, unemployment rate, etc.) Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  23. The Analytical Model (continued) • Dynan et al (2012) found that the more household can borrow, the higher house price increases. • Implies that due to the increase of the expectation on future economic outlook, household may borrow more to purchase houses and house price increases raisesboth and • In contrast, if the household expectation on future economic outlook declines, drops for given . Thus the equity could be negative. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  24. Combining Eq1 to Eq 3 • Equity rises with higher market value of property and/or lower debt. • The bigger the negative equity, the higher the probability of delinquency • The negative equity depends on house price and debt changes • Expectation on future economic outlook (and thus consumer confidence) activity is linked to E through MV and D. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  25. Econometric Method • GMM panel Model. • We examine the linkage between credit delinquency rates using a panel dynamic model of the following form: Eq. (4) Where, i =1,..,……,N and t =1,……..,T. and are unobserved individual and times specific effects. Household delinquency rate at period t and t-1, is the idiosyncratic term with E()=0, and ( and t=s xit represents the vector of regressors, comprising a set of independent variables observed at period t. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  26. Econometric Method (continued) • The dependent variable in equation (4) represents delinquency of the households with state level mortgage delinquency rate (MORG_DEL) credit card delinquency rate (CRDCARD_DEL) automobile loan delinquency rate (AUTO_DEL). • The independent variables = vector Xit = real house price (HPI), consumer confident index (CSI) to proxy for expectation of current and future economic outlook, lending rates for mortgage, credit card and auto loans, state level personal income per capita, state level per capita personal consumption expenditure (PCEXPD), state level unemployment rate (UNEMP_RATE), home ownership per state (HOWN). Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  27. Econometric Method (continued) Estimation Issues • First, the delinquency rates and consumer sentiment are presumed to be endogenously determined by unexpected shocks in household or personal income and employment opportunity inherent endogeneity. • Second, the time-invariant individual state characteristics (), such as diversity, political affiliations and value system may be correlated with the explanatory variables. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  28. Econometric Method (continued) • As a remedy, we create a set of instruments (lag of independent variables and dependent variable) with strict exogeneity assumption under difference GMM proposed by Arellano and Bond (1991) as follows: • However, this result in an additional endogeneity bias that is the correlations of lag of dependent variable and the error term. • The solution to this problem is to introduce second lag of dependent variable and lag of other independent variables as possible instruments. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  29. Data and Variables • We define delinquent loans as those past due 90 + days or more and still incurring interest as well as those in nonaccrual status. These are measured as a percentage of the end-of–period loans. • The mortgage delinquency rates are based on the National Delinquency Survey (NDS) and are extracted from Reserve Bank of New York (FRBNY: consumer credit panel). Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  30. Data and Variables (continued) • Consumers’ optimism or pessimism about consumers’ current and future financial conditions, which is the key variable of interest in our study, is constructed using the University of Michigan survey of consumer confidence. • As per this survey, the consumer sentiment index (CSI) is based on five core questions representing both current and future economic and financial conditions. • The detailed methods and calculation of index of consumer sentiment are provided in the website, The Survey of Consumers Attitudes (SCA), University of Michigan. (Available at monthly, quarterly and annual frequency.) Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  31. Data and Variables (continued) • We use annual data for 2003-2017 period. • The index of consumer sentiment is divided into two parts, viz., (a) the current condition and (b) the index of consumer expectations. The current component of the index of consumer sentiment (CSI_CURR) is based on questions number (1) and (5) of the survey. While index of consumer expectation (CSI_EXP) is based on questions 2 through 4. • In this study, to align with the “ability to pay hypothesis” we also use state level per capital personal income (INCOM_PCAPITA) and unemployment rates (UNEMP_RATE) as other variables of interest. • For robustness check, we further use household median income (MEDIN_HH) in current dollar for the respective states, available at annual frequency. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  32. Data and Variables (continued) • The control variables include • house price index (HPI), which is a weighted, repeat-sales index , meaning that it measures average price changes in repeat sales or re-financings on the same properties. • PCEXPD, is per capita personal consumption expenditure by state in current dollars. • State-wise home ownership (HOWN) rate measured as the percentage of owner-occupied homes relative to total number of homes. • 15-Year Fixed Rate Mortgage Average (MORG_RATE). For robustness check, this is replaced by 5/1 –Year adjustable rate mortgage rate average in the US (MORG_RATE_AMR), which is a hybrid of a fixed mortgage rate for initial five years and an adjustable rate to change on yearly basis in the subsequent years for the remaining term of the loan. • Interest rates on credit cards and automobile loans are represented as CRCARD_RATE and AUTO_RATE, respectively. • MORG_L and CRCARD_L indicate total amount of home loan and credit card loan, respectively. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  33. Data and Variables (continued) • Data are extracted from a number of sources including, • US Department of Labor • US Census Bureau • US Federal House Financing Agency (FHFA) • Federal Reserve Banks of New York • Federal Reserve Bank of St. Luis • The Survey of Consumer attitudes of the University of Michigan.  Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  34. Table: 2: the description of the variables and expected signs Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  35. Results and Discussions • Table 3: the mean differences of selected characteristics of the states classified as high mortgage delinquency and low mortgage delinquency states. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  36. Table 3: Simple Parametric Test for Mean Difference of State characteristics between high mortgage delinquencies and low Mortgage delinquency rates Note: *** and * represent significance at 1%, and 10% levels, respectively. We report selected mean value and corresponding t-value for each variable from parametric test. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  37. Results and Discussions (continued) • In Table 4, the estimates of difference panel GMM models for mortgage delinquency have been reported. • Compared to the base model, model 2, 3 and 4 are estimated with unemployment rates and the variants of consumer sentiment indices. • As per the base model, per capita income exerts a significant negative effect on the mortgage delinquency rates. • Estimates of model 2, 3 and 4 provide overwhelming evidence of highly significant and positive effect of unemployment rate on delinquency rates. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  38. Table 4: Estimates of Difference panel GMM for mortgage delinquency Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  39. Results and Discussions (continued) • Current CSI exerts negative and significant effect on the mortgage default rates., as revealed by the estimates of model 2. We also observe a significant and negative impact current component of CSI index. • A fall in delinquency rates due to one unit increase in current CSI implies relative awareness of the consumers about the economy that warrants lower mortgage delinquency • Among the control variables, the estimates reveal highly significant and positive impact of the house price index, mortgage rate and volume of mortgage on the mortgage delinquency rates, which comply with expectations due to the perceived direct link of these variables with the delinquency rates. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  40. Results and Discussions (continued) • Table 5 presents estimates of the models for the states with higher delinquency rates. • Per capita income has significantly adverse impact on delinquency. • Unemployment also has a highly significant and expected positive impact on delinquency rates across the three models. • Delinquency rates rises significantly with increase in overall CSI and expected CSI whereas delinquency rates fall with improved current CSI. • Optimism about the future seems to convince people to tilt their decision for borrowing more thereby succumbing to mortgage delinquency. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  41. Table 5: Panel GMM estimates for mortgage delinquency models for higher delinquency states Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  42. Results and Discussions (continued) • Table 6 reports the estimates of the models of mortgage delinquencies for the states with lower delinquency rates are. • Per capita income has significant negative impact as expected. However, delinquency rates vary more with respect to income in high default rate states. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  43. Results and Discussions (continued) • Higher unemployment also significantly induces higher mortgage delinquency in the low delinquency rate states. • The CSI and its current and expected components appear to provide unequivocal evidence of significant and negative effect on mortgage delinquency rates • Bhutta et al. (2017) showed that despite the decline in the US house prices and rise in mortgage default over 2007 to 2009, borrowers’ decision to continue paying until they are in dire situations is driven by emotional and behavioural factors of the borrowers. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  44. Table 6: Panel GMM estimates of mortgage delinquency models for lower delinquency states Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  45. Results and Discussions (continued) • Table 7 reports results of quantile regressions. • For brevity’s sake, we report the estimates for every 20thquantile. • The results indicate that CSI has a negative and highly significant impact on mortgage delinquency and that these impacts are almost uniform across the quantiles, ranging from -0.055 to -0.065. • This indicates that consumer sentiment does not pose differential effects on the mortgage delinquency rates of the American states with various rates of mortgage delinquencies. • This is a plausible result in view of faster information flow and factor mobility, which are likely to induce coherent changes in mortgage delinquencies in response to changing consumer sentiments. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  46. Results and Discussions (continued) • The impact of changes of unemployment is positive and significant. • Higher house prices exert adverse and significant impact on the delinquency rates. • Loans have relatively larger positive and significant impact on mortgage delinquency especially at higher quantiles. • Finally, the effects of interest rates on mortgages, MORG_L and income seem to be significant at lower quantiles and insignificant at higher quantiles. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  47. Table 7. Quantile process regression estimates of mortgage delinquency Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  48. Results and Discussions (continued) • Table 8: Including CSI current • CSI current has a highly significant and positive effect on the mortgage delinquency rates …. with similar magnitude of the effects. • The effect of unemployment is positive and highly significant for all quantiles… higher in higher quantiles of mortgage delinquencies…American states with higher delinquency rates are more sensitive to changes unemployment rates. • Similarly, higher house prices reduce mortgage delinquencies in various states of US and these effects are higher in upper quantiles. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  49. Table 8. Quantile process regression estimates of mortgage delinquency with current CSI Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

  50. Results and Discussions (continued) • Table 9 reports mortgage delinquency rates with expected CSI. • The effects of expected CSI are highly significant and negative. • Also, these effects are similar across the quantiles. • Unemployment has highly significant and positive effect on mortgage delinquencies, with the magnitude of these effects rising in higher quantiles. • Higher house prices significantly lowers mortgage delinquency rates. Contrarily, mortgage loan exert large and increasingly higher positive impact on mortgage delinquency rates in the American states. Seminar Series, Department of Economics, JKKNIU, Trishal, Bangladesh. 23 January 2019

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