Microeconomic Factors Including Inflation, SUV

¶ … microeconomic factors including inflation, SUV collateral or trade-in value, significant oil and gas price fluctuations as quantified by the average U.S. price of a gallon of gasoline, and the impact of automaker incentives on the sales of SUV sales throughout the last fourteen months. These microeconomic factors are captured in quantitative form and analyzed using a series of statistical analysis routines from the Statistical Software Package for the Social Science (SPSS). A methodology based on the use of R.L. Polk vehicle sales data in addition to use of data from the AutoData database (2008) and the Global Insight Databases (2008) which is an information service from J.D. Power. The Monthly Review (2008) is used for the specific fuel pricing used in this analysis as well. Using R.L. Polk data the high gas consumption cars will be the mid-size SUV segment. The dynamics of this market where body-on-frame vs. unibody construction make it ideal for being a significant independent variable in the analysis. For purposes of completing the R.L. Polk vehicle analysis these are the models by each type of SUV:

Body on Frame SUVs (more towing power, less fuel efficient) included in the Analysis

CHEVROLET - TRAIL BLAZER

CHEVROLET - TRAILBLAZER EXT

CHEVROLET - TRAILBLAZER SS

FORD - EXPLORER

GMC - ENVOY XL DENALI

KIA - SORENTO

NISSAN - PATHFINDER

TOYOTA - 4 RUNNER

Unibody SUVs (less towing power, more fuel efficient) included in the Analysis

CHEVROLET - EQUINOX

FORD - FREESTYLE

HONDA - PILOT

HYUNDAI - SANTA FE

NISSAN - MURANO

SUBARU - B9 TRIBECA

TOYOTA - HIGHLANDER

Methodology

R.L. Polk's Insight database (2008) was first used to gather the last fourteen months (from June, 2007 to July, 2008) of new vehicle sales and registrations for the two groups of SUVs, the median U.S. gas price using the Monthly Energy Review (2008). Using the data contained in the R.L. Polk Insight database (2008) and the J.D Power PIN database (2008) a series of data tables were constructed and analyzed. The data set of financing variables was specifically from JD Power's PIN Financing Database. Results of queries into each of these databases were extracted into Microsoft Excel files and then imported in SPSS Version 15 for Windows.

As defined the null and alternative hypotheses are presented below:

Ho: There is a negative relationship between high oil price and car sales and leasing value.

H1: There is a positive relationship between high oil price and car sales and leasing value.

Initial Results

The data sets were entered into SPSS Version 15 and a correlational analysis was completed computing distances between variables using Pearson Correlation to measure similarities. The resulting Proximity Matrix is shown below:

Rescaled Reversed Absolute Correlation between Vectors of Values

TOTAL MIDSIZE SUV UNIT SALES Average U.S. Gas Price Total Down Percent Financed Total Down (%) Trade in (%) Type of Sale Cash (%) Type of Sale Finance (%) Type of Sale Lease (%) Type of Sale Purchase (%) Vehicle Price Less Customer Cash Rebate TOTAL MIDSIZE SUV UNIT SALES 1.000.743.674.756.741.399.749.352.464.464.381 Average U.S. Gas Price.743 1.000.856.799.797.236.423.903.487.487.737 Total Down.674.856 1.000.011.010.711.482.959.566.566.867% Financed.756.799.011 1.000.000.692.561 1.000.650.650.739 Total Down (%).741.797.010.000 1.000.684.561.985.642.642.755 Trade in (%).399.236.711.692.684 1.000.824.656.964.964.886 Type of Sale Cash (%).749.423.482.561.561.824 1.000.900.146.146.562 Type of Sale Finance (%).352.903.959 1.000.985.656.900 1.000.398.398.589 Type of Sale Lease (%).464.487.566.650.642.964.146.398 1.000.000.438 Type of Sale Purchase (%).464.487.566.650.642.964.146.398.000 1.000.438 Vehicle Price Less Customer Cash Rebate.381.737.867.739.755.886.562.589.438.438 1.000 This is an absolute dissimilarity matrix

From this initial correlation analysis using Pearson's Correlation Matrix for testing similarities the data suggests that consumers continue to purchase unibody SUVs, putting less money down and leasing to get the lower payment so their budgets can cushion the wide gas price fluctuations occurring during the 14-month period of analysis.

Next a partial correlation analysis was completed using two-tailed test of significance controlling for U.S. gas price, using the variables of total midsize SUV unit sales, average U.S. gas price, total down payment, percent financed, total down payment amount, percent financed, total down payment percentage, trade in percentage, percentage of sales in cash, that were financed, and that were leased. Finally the vehicle price less customer incentives and rebates (cash and incentives) are used as the variables to complete the partial correlation.

Table 2 Partial Correlation Descriptive Statistics

Mean

Std. Deviation

TOTAL MIDSIZE SUV UNIT SALES

Total Down

Percent Financed

Total Down (%)

Trade in (%)

Type of Sale Cash (%)

Type of Sale Finance (%)

Type of Sale Purchase (%)

Type of Sale Lease (%)

Vehicle Price Less Customer Cash Rebate

Average U.S. Gas Price