The Demand for Home Equity Loans at Bank X*

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The Demand for Home Equity Loans at Bank X
An MBA 555
Project Laura Brown Richard Brown Jason
Vanderploeg bank name withheld for
proprietary reasons
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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.
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Project Objective

• Construct a demand model
• for variables affecting
• the volume of equity loans
• (demand variable Q),
• focusing especially on the effect of
• the bank prime loan rate
• (demand variable P)

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• 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.

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• Overview of Methodology
• Stage 1
• Collected monthly data sets (2003 to August 2006)
• Created independent dummy variables to test
  pattern behavior
• Used stepwise regression and practical
  considerations to eliminate variables
• Stage 2
• Used OLS to test the 4 basic assumptions of
  regression analysis
• Generated regression charts
• Stage 3
• Generated estimation model
• Identified and interpreted elasticities
• Summarized final results

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• Stage 1
• Variables Examined
• Volume of Home Equity loans
• Bank Loan Prime Rate
• Federal Funds Rate
• of Houses Sold
• Median Price of Houses Sold
• Consumer Loans _at_ Commercial Banks
• Total of Loan Units
• Firm Advertising
• Residential Energy Consumption
• Transportation Energy Consumption
• Money Supply (Stocks)

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Stage 1 Definition of Remaining
Variables Variable Type Hypothesized
Sign Demand for Home Equity Loans Dependent Bank
Prime Loan Rate (Proxy) Exogenous Negative Money
Supply (Stocks) Exogenous Negative Total
Units Endogenous Positive Advertising Endogeno
us Positive Fed Funds Rate Exogenous Negative Co
nsumer Price Index Exogenous Positive Consumer
Loans _at_ Comml Banks Exogenous Negative Median
Price of Houses Sold Exogenous Positive
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• 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 2.290
• Money Supply (Stocks) 2.091
• Total Units 1.142
• Average VIF for model 1.841

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• 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 Reject
• Rho Positive Do Not Reject
• Rho Negative Reject
• Using First Differences to remove the
  autocorrelation did not improve the model.

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• 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

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• 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.

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Stage 2 Predictive Ability Chart
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Stage 2 Confidence Intervals Chart
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Stage 2 Constant Variance Chart
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Stage 2 Normal Probability Chart
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Stage 2 Error Bars Chart
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Stage 3 Estimated 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.
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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
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• 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 lt 1 are inelastic, values gt1 are
  elastic.

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• Stage 3
• Elasticities, cont.
• The model reveals that home equity loans are
  price inelastic
• Parameter estimate for bank loan prime rate
  -0.268
• A 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
  elastic
• relative to the availability of other funding for
  consumer
• spending.
• 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.

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• 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

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• Appendix A
• Excerpts from Industry Literature
• Home-Equity Borrowing Stalls As the Housing
  Market Cools
• Ruth 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