From Income to Consumption Inequality? Looking through the Lens of Motor Vehicle Purchases Accessible Data
Figure 1: Changes in New Vehicle Purchases by County, 2002-2017
Figure 1 illustrates the geographic variation in average annual changes in motor vehicle spending estimates among US counties between the first quarter of 2002 and the first quarter of 2017. We use model-level counts of vehicle registrations in each county that were recorded as “retail purchases” and we merge these data with the 2016 manufacturer’s suggested retail prices (MSRPs) for each make and model to create county-level spending aggregates. The blue shaded areas indicate increases, while red-yellow shades represent declines. While the majority of counties recorded decreases, gains were concentrated in the Mountain States and the American South.
Note: Annualized changes in new vehicle registrations between 2002q1 and 2017q1.
Source: IHS Markit, new vehicle registration data.
Figure 2: Varying Patterns of New Vehicle Purchases Across the Income Distribution
Figure 2 shows the pattern of new motor vehicle spending across counties in different terciles of the income distribution. The income terciles are based on the county average personal income per capita between 1969 and 2000. Per capita vehicle purchases in top-income counties showed noticeable declines in 2005 and 2006, before the onset of the Great Recession. And while spending in top-income counties moved up again early in the recovery, it has since flattened out at levels well below the pre-recession peak. By contrast, counties in the middle and bottom income terciles registered smaller absolute declines during the Great Recession, and spending in these bins has almost completely recovered back toward pre-recession levels. As a result of these patterns, counties in the top income tercile account for about two-thirds of all registrations, but their share has slightly declined relative to 2002.
Note: Number of registrations is weighted by 2016 MSRP vehicle prices and deflated by new motor vehicle price index.
Source: IHS Markit.
Figure 3: Measures of Dispersion in Consumption and Income (Variance of Logs)
The top panel of figure 3 shows the cross-county dispersion of (log) vehicle consumption. Our measure of the dispersion in vehicle purchases dropped by about 5 percent (0.05 log points) between 2002 and 2011; thereafter, the dispersion began rising again, and by the beginning of 2017 it had moved up close to the levels observed early in the sample. For comparison, the right panel of figure 3 illustrates county-based estimates of per-capita income inequality. Income dispersion, by contrast, appears to have trended up steadily over the past 15 years.
Note: Across-county dispersion in (log) vehicle registrations.
Source: IHS Markit, BEA data.
Figure 4: Changes in Within-Group Consumption Inequality and Income Inequality
Figure 4 depicts our estimates of within-group inequality for both income and consumption, where all estimates are indexed to zero in 2002. For each year, we estimated a regression of the dispersion in consumption or income on a variety of demographic controls for each county, including population; the net migration rate; the age, sex, and race composition; the employment level; and the number of establishments. The residual sum of squares from these regressions represents the dispersion in income or consumption that cannot be explained by differences in observable county characteristics, or within-group component of inequality. We find that the within-group component has remained fairly constant for consumption inequality, even as it has risen substantially for income inequality.
Note: Changes in residual within-county variation for registrations and income after controlling for demographics characteristics; 2002 values are normalized to zero.
Source: IHS Markit, Census, CBP, and BEA.