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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 – PowerPoint PPT presentation

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Title: The Demand for Home Equity Loans at Bank X*


1
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
2
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.
3
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)

4
  • 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.

5
  • 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

6
  • 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)

7
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
8
  • 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

9
  • 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.

10
  • 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

11
  • 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.

12
Stage 2 Predictive Ability Chart
13
Stage 2 Confidence Intervals Chart
14
Stage 2 Constant Variance Chart
15
Stage 2 Normal Probability Chart
16
Stage 2 Error Bars Chart
17
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.
18
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
19
  • 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.

20
  • 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.

21
  • 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

22
  • 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
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