Car Consumer Demand Sensitivity to Income Term Paper

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Introduction

Macroeconomic research has historically identified the relationship between consumer income and consumption, which is largely attributable to changes in macroeconomic policy. According to demand theory, higher level of income increases the demand of the product, and therefore consumption. Moreover, price theory of demand posits that an increase in price will reduce the demand of the product and vice versa, taking a cetirus paribus assumption. This paper tries to understand the consumer demand sensitivity to income of the consumer for automobiles.

Previous research has been conducted to understand the consumer demand for automobiles (Wetzel & Hoffer, 1982; Berry, Levinsohn, & Pakes, 2004). Cramer (1973) found that the consumer demand for a product is sensitive to changes with different income levels, and that price elasticity of the product changes at different income levels and vice versa.

The study conducted by Wetzel & Hoffer (1982) has shown that the demand and price elasticity of automobiles differ significantly due to change in styling, gasoline prices, and demographic changes. Berry, Levinsohn, & Pakes (2004) also demonstrate how preference and demand for products change with change in the attributes in household data.

Here automobiles consider only new cars. Therefore, the research question that is being addressed is whether consumer demands income sensitive. Further, the paper will also develop the demand function for new cars in the US. The paper will first address the data that is being used for the research. Then a discussion on the methodology applied for the research is talked about. After this, the paper presents the analysis of the data using regression analysis, and presents the research findings. The following section describes the data collection, description and methodology used for the research.

Methodology

The data that is analysed for the study is presented is extracted from the U.S. Bureau of Labor Statistics (2010) database. The data that is being used for the study are consumer purchase of new car from 1990 to 2008 (Table 1). Further, the purchase of cars figure is also categorized for the consumer level of income.

Table 1: Consumer purchase of new cars and income before tax from 1990 to 2008.

New Car Purchase based on Income
Consumer Purchase of New CarsLess than $5,000$5,000 to $9,999$10,000 to $14,999$15,000 to 19,999$20,000 to $29,999$30,000 to $39,999$40,000 to $49,999$50,000 to $69,999$70,000 and moreCars Price IndexDisposable Income
199011592102384459158261262153100118.328937
199110783441384196348231033171200124.130729
199211312042314212166801196183418353546126.930786
199312163942262687187901320156120503643129.831890
1994139136027245168111621329245219552948133.933098
199511981552826118167551085143220142899134.133864
199612095853682185628581278148219413153135.434864
19971229602245444089761579168219152865133.636684
19981383421208692648691953119521503550131.938358
199916284194797999619961237176917813773131.340652
200016055749158875011681453189619863434132.841532
20011685749396678688972150218762097357213244587
2002175342234768711417621446205422643433129.546934
2003205251028875051812361470142526544832129.548596
200417482792945124509131237133722543477131.752287
20051931445213963821213937133923174012131.856304
20061798798725263397019849271761382712858101
2007157225518153373161978890115083199126.260858
20081305023920153761072790912282567128.961774

Therefore, we get the number of cars purchased by consumers based on their income. The income groups that are used are ‘Less than $5,000’, ‘$5,000 to $9,999’, ‘$10,000 to $14,999’, ‘$15,000 to 19,999’, ‘$20,000 to $29,999’, ‘$30,000 to $39,999’. ‘$40,000 to $49,999’, ‘$50,000 to $69,999’, and ‘$70,000 and more’. Then data on commodity price index for cars are quarried from the U.S.

Bureau of Labor Statistics (2010) database. Data on disposable income i.e. income after tax for individuals has been derived from U.S. Bureau of Labor Statistics website for 1990 through 2008. Table 2 presents the descriptive statistics of the data. The table shows that the mean purchase of cars in the period 1990 to 2008 for different income groups.

Table 2: Descriptive Statistics.

New Car Purchase based on Income
Consumer Purchase of New CarsLess than $5,000$5,000 to $9,999$10,000 to $14,999$15,000 to 19,999$20,000 to $29,999$30,000 to $39,999$40,000 to $49,999$50,000 to $69,999$70,000 and moreCars Price IndexDisposable Income
Mean1477.42350.89273.00496.79636.58881.631200.841542.841774.213091.05129.9842675.53
Standard Error68.1049.9224.4244.7052.6946.0556.3992.65159.60274.290.932505.98
Standard Deviation296.84217.59106.46194.84229.66200.74245.79403.85695.691195.614.0810923.33
Kurtosis-1.11-0.070.34-0.400.07-0.90-0.740.173.303.772.57-1.10
Skewness0.360.380.52-0.490.280.50-0.380.18-1.87-1.88-1.380.51
Count191919191919191919191919
Confidence Level(95.0%)143.07104.8851.3193.91110.6996.75118.47194.65335.31576.261.965264.88

The standard deviation for the data is high, and the skewness is mostly positive only for some income groups it is negative. The car price index has low relatively low standard deviation.

Berry, Levinsohn, & Pakes (2004) have shown in their research that the demand function for a product may alter considerably due to the introduction of a another variable into the demand function. In this paper, disposable income along with annual prices index of cars is used as the variables to determine the demand for the cars, which are differentiated, based on the income of the individual.

The data is analysed using regressions analysis. The main purpose of the paper is to see how the demand for new car purchase is affected by changes in income of individual and price. Apart from this, the paper also identifies how demand is affected by changes in price based on the income group the consumer belongs to. The analysis of the data is presented in the following section.

Analysis

First, a regression analysis is done on the overall purchase of new cars and how it changes with car price index and disposable income is done.

Table 3: Regression analysis of new car purchase and car price index and individual disposable income.

Regression Statistics
Multiple R0.705
R Square0.497
Adjusted R Square0.434
Standard Error223.348
Observations19
ANOVA
dfSSMSFSignificance F
Regression2787865.101393932.5507.8970.004
Residual16798151.53149884.471
Total181586016.632
CoefficientsStandard Errort StatP-valueLower 95%Upper 95%
Intercept-838.991684.79-0.500.63-4410.582732.60
Cars Price Index11.7712.930.910.38-15.6539.18
Disposable Income0.020.003.820.000.010.03

The regression analysis shows that the demand for the automobiles demand for new cars variance in the analysis is 49%. The data analyzed is statically significant at 0.004 (<0.05) at 95% level of significance. The demand function that can be derived from the regression analysis is:

  • New Car demand = -838.99 + 11.77*Car Price Index +0.02 Disposable Income (1)

Therefore, the demand function derived for cars has a positive intercept for car prices, which refutes the demand function. The relationship between car purchase and disposable income is found to be positive with intercept being 0.02.

Figure1 shows that individuals belonging to higher income groups have purchased greater number of cars on an average over the period 1990 through 2008. Therefore, the figure makes it clear that there is a difference in demand for cars with changes in income of individual. In order to understand how the demand function will vary with changes in income and price regression analysis is done for purchase of cars for different income groups and car price index and disposable income.

As there are 9 groups, the analysis may become cumbersome. In order to make it simpler, the data for the different groups are clubbed into 3 groups i.e. less than 20,000, 20,000 to 70,000, and more than equal 70,000.

Mean purchase of new cars for different income levels
Figure 1: Mean purchase of new cars for different income levels

The regression analysis for the income group below $20,000, the r-square is found to be 2.1% (Table 4). Further the analysis is not found to be statistically significant as the F value is 0.83 (>0.05) at 95% significance level. The analysis shows that in this income group, consumer demand for new cars is positively related to car price index and negatively related to disposable income.

Table 4: Regression analysis for income group Less than 20,000.

Regression Statistics
Multiple R0.147633012
R Square0.021795506
Adjusted R Square-0.100480056
Standard Error501.7297228
Observations19
ANOVA
dfSSMSFSignificance F
Regression289742.2485944871.12430.1782490780.838372895
Residual164027723.436251732.7147
Total184117465.684
CoefficientsStandard Errort StatP-valueLower 95%Upper 95%
Intercept211.11488983784.7072680.0557810350.956206874-7812.1060518234.335831
Cars Price Index13.3296398229.052425880.4588133150.652539357-48.2587513474.91803099
Disposable Income-0.0043700560.010838219-0.4032079470.692132101-0.0273460540.018605942

The second group is income of $20,000 to $70,000 (Table 5). The analysis gives a r-square of 48% indicating greater reliability. F-value is 0.005 which is statistically significant at 95%. The analysis can be utilized to find the estimated demand function for new cars for individuals belonging to this particular income group.

Table 5: Regression analysis for income group 20,000 to 70,000.

Regression Statistics
Multiple R0.695248283
R Square0.483370174
Adjusted R Square0.418791446
Standard Error859.31571
Observations19
ANOVA
dfSSMSFSignificance F
Regression211054162.95527081.4527.4849751270.005074997
Residual1611814775.83738423.4895
Total1822868938.74
CoefficientsStandard Errort StatP-valueLower 95%Upper 95%
Intercept-18088.647186482.092381-2.7905568310.013093884-31830.06907-4347.225278
Cars Price Index187.250256649.75827593.7631982470.00169974181.76742456292.7330887
Disposable Income-0.0199506220.018562687-1.0747701380.298419003-0.059301760.019400517

The demand function, thus, found is:

  • New Car Demand = -18088 + 187.25 *Car Price Index – 0.019 Disposable Income (2)

The demand function shows that the demand for new cars is highly price sensitive and is positively related to price index. Further, it is negatively related to disposable income and is less sensitive to changes in disposable income.

For this income group, i.e. income more than 70,000, gives an r-square of 54% (Table 6). The analysis explains 54% of the variance in demand of new cars in the regression. The regression is statistically significant at 95% level (F-value is 0.001<0.05).

Table 6: Regression analysis for income group More than 70,000.

Regression Statistics
Multiple R0.740203882
R Square0.547901787
Adjusted R Square0.491389511
Standard Error852.6700272
Observations19
ANOVA
dfSSMSFSignificance F
Regression214097818.147048909.0729.6952701380.001745269
Residual1611632738.8727046.1752
Total1825730556.95
CoefficientsStandard Errort StatP-valueLower 95%Upper 95%
Intercept-21847.214076431.961877-3.3966641110.003686021-35482.36405-8212.064094
Cars Price Index177.520261349.373460723.5954591530.0024223472.85320096282.1873216
Disposable Income0.0436652070.0184191292.37064450.0306560940.0046183980.082712016

Therefore, the regression gives the statistically significant estimated function for future prediction, which is actually the demand curve for this particular income group. The estimated demand function is as follows:

  • New car demand = -21847.21 + 177.52*Car Price Index + 0.04*Disposable Income (3)

Equation (3) shows the demand for new cars for people belonging to an income groups above $70,000. The demand function shows that demand is price sensitive and is positively related to price. Further, the demand has a positive relation with disposable income, however, it has a low sensitivity to income.

Conclusion

The above analysis shows that the demand for new cars in US is positively related to price index of cars from 1990 to 2008. As the result is statistically significant, the relation can be said to hold for all time-period for the US consumer demand for new cars.

Further, this relation between new car demand and price is found to be consistent across the three income groups studied in the research, as all have positive relation. The demand for new cars all over US is found to be positively related to disposable income. This finding, however, varies across the three income groups. The positive relation is found to hold only in case of the income group ‘More than 70,000’.

Therefore, it indicates that at lower income levels, demand for new cars has a negative income elasticity. This research therefore, shows that the demand for new cars in the US is sensitive to changes in price and income positively. However, variances in the demand and income, price relation occurs due to changes in income level of the consumers.

References

Berry, S., Levinsohn, J., & Pakes, A. (2004). Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car Market. Journal of Political Economy, vol. 112, no. 1 , 68-105.

Bureau of Labor Statistics. (2010). Databases, Tables & Calculators by Subject. Web.

Cramer, J. S. (1973). Interaction of Income and Price in Consumer Demand. International Economic Review, Vol. 14, No. 2 , 351-363.

Wetzel, J., & Hoffer, G. (1982). Consumer Demand for Automobiles: A Disaggregated Market Approach. Journal of Consumer Research, Vol. 9 , 195-199.

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