Working Paper: NBER ID: w1455
Authors: James Trussell; Kenneth Wachter
Abstract: Data on human height can provide an index that may measure more accurately changes in the standard of living than the more conventional real wage index. Height data, like those on real wages, are relatively abundant and extend back to the seventeenth century. In a previous paper, we developed and tested procedures for estimating the mean and standard deviation of the distribution of human height when the sample is distorted to an unknown extent by missing observations at lower heights. The purpose of this analysis is to extend our techniques so that the covariates of height can be estimated. Such an extension is necessary when trying to draw inferences about the causes of shifts over time in the height distribution so that changes in sample composition can be controlled.
Keywords: No keywords provided
JEL Codes: No JEL codes provided
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| immigration (F22) | average height of Americans (I14) |
| being born in the South (J79) | height among U.S. soldiers in 1850 (J45) |
| being born in Germany (J19) | height among Swedish conscripts (H56) |
| height covariates (C21) | height distribution (I14) |
| sample composition shifts (C46) | observed changes in height (J11) |
| naive regression estimates (C29) | misleading conclusions about height and covariates (C29) |