The Demand for Home Equity Loans at Bank X* An MBA 555 Project
Laura BrownRichard BrownJason Vanderploeg
*bank name withheld for proprietary reasons
Introduction
The current market for home equity loans is highly competitive. Due to the massive housing slowdown, demand for equity transactions has also slowed, forcing companies to re-strategize in a changing environment. We have endeavored to develop a model to better equip Bank X decision makers as they pursue strategies for capturing a larger share of the market within the banks national footprint.
Project ObjectiveConstruct a demand modelfor variables affecting
the volume of equity loans (demand variable Q), focusing especially on the effect of
the bank prime loan rate (demand variable P)
Hypotheses Tested
H1 = The demand for home equity loans is explained by interest rates offered by banks (prime rate)
H2 = The demand for home equity loans is explained by consumer purchasing power.
H3 = The demand for home equity loans is explained by public consumer economic indicators (stock market)
H4 = The demand for home equity loans is explained by advertising expenses.
Overview of Methodology
Stage 1
Collected monthly data sets (2003 to August 2006)Created independent & dummy variables to test pattern behaviorUsed stepwise regression and practical considerations to eliminate variables
Stage 2
Used OLS to test the 4 basic assumptions of regression analysisGenerated regression charts
Stage 3
Generated estimation modelIdentified and interpreted elasticitiesSummarized final results
Stage 1
Variables Examined
Volume of Home Equity loansBank Loan Prime RateFederal Funds Rate# of Houses SoldMedian Price of Houses SoldConsumer Loans @ Commercial BanksTotal # of Loan UnitsFirm AdvertisingResidential Energy ConsumptionTransportation Energy ConsumptionMoney Supply (Stocks)
Stage 1
Definition of Remaining Variables
VariableTypeHypothesized Sign
Demand for Home Equity LoansDependentBank Prime Loan Rate (Proxy)ExogenousNegativeMoney Supply (Stocks)ExogenousNegativeTotal UnitsEndogenousPositiveAdvertisingEndogenousPositiveFed Funds RateExogenousNegativeConsumer Price IndexExogenousPositiveConsumer Loans @ Comml BanksExogenousNegativeMedian Price of Houses SoldExogenousPositive
Stage 2
Assumption of Non-Collinearity
Multicollinearity, as measured by VIF, takes place when an independent variable correlates with other independent variables. VIF under 10 is preferred, and under 5 is ideal.
Parameter VIFs:Bank Loan Prime Rate 2.290Money Supply (Stocks) 2.091Total Units 1.142
Average VIF for model 1.841
Stage 2
Assumption of Absence of Autocorrelation
OLS requires that the residual error terms show no discernible pattern. The assumption is violated when the Durbin-Watson test shows either + or - autocorrelation.
The model revealed evidence of auto correlation.Rho: Pos & Neg RejectRho: Positive Do Not RejectRho: Negative Reject
Using First Differences to remove the autocorrelation did not improve the model.
Stage 2
Assumption of Constant Variance
Constant variance means that all random error terms have the same variance and are not correlated to one another. The null hypothesis of Whites test assumes this homeskedasticity is in place. At 95% confidence, a p-value of 0.05 or higher allows us to accept the null hypothesis.
The p-value for Whites in our model was 0.094
Stage 2
Assumption of Normality
Normality describes the fact that remaining random error terms exhibit a normal distribution. The chart for residual error terms should produce a line angled at approximately 45 degrees.
The models correlation for normality was .992, well above the critical value of .977.
Stage 2
Predictive Ability Chart
Stage 2
Confidence Intervals Chart
Stage 2
Constant Variance Chart
Stage 2
Normal Probability Chart
Stage 2
Error Bars Chart
Stage 3Estimated Model and Results
All data sets were entered into WinORS. After a stepwise regression, Ordinary Least Squares and logarithmic transformation, the following model was constructed for quantity of home equity loans:
lnQHE = f(-.0268Ln(P) .2188Ln(M) + .977Ln(U))
The F-statistic which measure the explanatory power of the model was found to be significant at 371.1.
The p-value was 0.00001, showing that the model is statistically significant at a 99.9% confidence level.
Stage 3
Estimated Model and Results, cont.
The coefficient of determination R2 measures the degree of variation in the dependent variable that can be explained by variation in the independent variables.
Our model showed excellent scores:
R2 = 96.532%Adjusted R2 = 96.272%
Stage 3
Elasticities
Elasticities measure the % change in the dependent variable, given a 1% change in the independent variable.
In the multiplicative demand model elasticities are revealed to be constant at all points on the demand curve.
Parameter estimates represent the elasticities of the independent variables.
Absolute values < 1 are inelastic, values >1 are elastic.
Stage 3Elasticities, cont.
The model reveals that home equity loans are price inelastic:
Parameter estimate for bank loan prime rate = -0.268A 10% increase in the prime rate would result in just 2.7% decrease in the demand for home equity loans. This parameter is inelastic.
The model also reveals that home equity loans are elasticrelative to the availability of other funding for consumerspending.
Parameter estimate for money supply = -2.188 A 10% increase in the availability of alternative funding would result in a 21.9% decrease in the demand for home equity loans.
Stage 3 Conclusions
Demand is not heavily affected by interest rate change, so the bank can take advantage of the inelastic relationship and achieve higher revenues.H1 is accepted
Alternative funding sources for consumer spending has an inverse relationship to the demand of home equity loans. In a bullish market, consumers dont borrow against their equity.H3 is accepted
Consumer purchasing power and firm advertising has little statistical significance in the demand for home equity loans.H2 and H3 are rejected
Appendix AExcerpts from Industry Literature
Home-Equity Borrowing Stalls As the Housing Market CoolsRuth Simon
The slowdown in home-equity borrowing is leading to weaker sales in some markets for autos, building materials and electronics
As rates go up there is unknown future demand for home equity loans
During the housing boom, demand for home-equity lines of credit climbed sharply as property values rose
