Childhood Mortality & Nutritional Status as Indicators of Standard of Living: Evidence from World War I Recruits in the United States

This paper examines variations in stature and the Body Mass Index (BMI) across space for the United States in 1917/18, using published data on the measurement of approximately 890,000 recruits for the American Army for World War I. It also connects those anthropometric measurements with an index of childhood mortality estimated from the censuses of 1900 and 1910. This index is taken to be an indicator of early childhood environment for these recruits. Aggregated data were published for states and groups of counties by the Surgeon General after the war. These data are related to regional data taken primarily from the censuses of 1900 and 1910. The results indicate that early childhood mortality was a good (negative) predictor of height and the body mass index, while it is also possible to predict early childhood experience from terminal adult height. Urbanization was important, although the importance declined over time. Income apparently had little effect on health in this period.

Health, height, and the household at the turn of the twentieth century

This article examines the health and height of men born in England and Wales in the 1890s who enlisted in the army at the time of the First World War, using a sample of recruits from the army service records. These are linked to their childhood circumstances as observed in the 1901 census. Econometric results indicate that height on enlistment was positively related to socio-economic class, and negatively to the number of children in the household in 1901 and the proportion of household members who were earners, as well as to the degree of crowding. Adding the characteristics of the locality has little effect on the household-level effects. However local conditions were important; in particular the industrial character of the district, local housing conditions, and the female illiteracy rate. These are interpreted as representing the negative effect on height of the local disease environment. The results suggest that changing conditions at both household and locality levels contributed to the increase in height and health in the following decades

A stochastic multidimensional scaling procedure for the empirical determination of convex indifference curves for preference/choice analysis

The vast majority of existing multidimensional scaling (MDS) procedures devised for the analysis of paired comparison preference/choice judgments are typically based on either scalar product (i.e., vector) or unfolding (i.e., ideal-point) models. Such methods tend to ignore many of the essential components of microeconomic theory including convex indifference curves, constrained utility maximization, demand functions, et cetera. This paper presents a new stochastic MDS procedure called MICROSCALE that attempts to operationalize many of these traditional microeconomic concepts. First, we briefly review several existing MDS models that operate on paired comparisons data, noting the particular nature of the utility functions implied by each class of models. These utility assumptions are then directly contrasted to those of microeconomic theory. The new maximum likelihood based procedure, MICROSCALE, is presented, as well as the technical details of the estimation procedure. The results of a Monte Carlo analysis investigating the performance of the algorithm as a number of model, data, and error factors are experimentally manipulated are provided. Finally, an illustration in consumer psychology concerning a convenience sample of thirty consumers providing paired comparisons judgments for some fourteen brands of over-the-counter analgesics is discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45748/1/11336_2005_Article_BF02294463.pd