Abstract
In the chapters to this point, price information collected in quarterly surveys by the American Chambers of Commerce Research Association has been combined with the CES quarterly surveys to create data sets from which price as well as total-expenditure elasticities have been estimated. However, because of the limited coverage of the ACCRA data, estimation has been restricted to a fairly high level of aggregation. While the price and total-expenditure elasticities obtained at this level are obviously of interest in their own right, one of the main findings with the CES data is that the presence or absence of prices in demand functions makes little difference to the estimates of total-expenditure elasticities. This apparent absence of an omitted-variables bias is an important result, for it suggests that estimates of total-expenditure elasticities at lower levels of aggregation, for which expenditure data are available but price information is not, can reasonably be assumed to be free of bias as well.
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Notes
- 1.
- 2.
Obviously expect Engel’s law to be confirmed for food consumed at home. Food consumed outside the home, on the other hand, is clearly another matter. We would expect the law to apply for employment-related outside-of-home food expenditures, but not necessarily for food expenditures associated with recreation and entertainment.
- 3.
Interestingly, with few exceptions (specifically, for electricity, telephone, health care, entertainment, and miscellaneous expenditures), the variability of the QR estimates is less than for OLS.
- 4.
Reminder: The modal value in this context refers to the mode of the distribution of residuals from the QR(median) regression, and represents the quantile at which the QR(mode) regression is estimated.
- 5.
Unless otherwise noted, text references are to QR elasticities.
- 6.
That the elasticity for aggregate apparel expenditure is larger than either of its constituents may seem an error. However, it must be kept in mind that the double-logarithmic equations of this chapter do not constitute an additive system; hence elasticities for aggregates are not budget-weighted averages of their components. Also, because some households have no expenditures for women and girls apparel, and similarly for men and boys, the data sets for the components are not exactly the same as for the aggregate.
- 7.
Included in this category are expenditures for new and used vehicles, gasoline and oil, vehicle finance charges, maintenance and repairs, insurance, rental, leases, licenses and related charges, and public transportation.
- 8.
At sufficiently high income, even cosmetic surgery probably becomes, for many, a necessity!
- 9.
The designation of the elasticity sets in terms of “necessities,” “near-luxuries,” and “luxuries” is obviously at odds with the long-standing convention in economics of defining necessities as goods with income elasticities between 0 and 1 and luxuries as goods with income elasticities greater than 1. However, when one thinks about it, the present characterization is no less arbitrary, and for present purposes seems much more useful.
- 10.
This detail is the 6-digit universal classification codes (UCCs).
- 11.
In this case (and for alcoholic beverages as well), strong habit formation (including addiction) is identified with physiological needs.
- 12.
Our thought in assigning this category to the large elasticity set was that expenditures within the category would be heavily motivated by entertainment and self-actualization needs. However, with hindsight it is probably the case that the expenditures in this category (which are not large to begin with) are dominated by expenditures for newspapers and magazines. Unfortunately, sub-aggregates at the 6-digit UCC level are not included on the BLS microdata CDs, so that checking whether this is in fact the case is not possible.
- 13.
Higher-order wants correlate with high income, which in turn allows for individual idiosyncrasies to manifest themselves.
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Taylor, L.D. (2010). Engel Curves for 29 Categories of CES Expenditure. In: Consumer Demand in the United States. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0510-9_11
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DOI: https://doi.org/10.1007/978-1-4419-0510-9_11
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