Abstract:
In this thesis mainly anthropometric indicators are used to investigate several aspects of living standards and inequality in global and historical perspective. Chapter two uses anthropometric information as an indicator for human health and welfare in 156 countries spanning the period 1810-1989. The findings suggest that regional height levels around the world were fairly uniform throughout most of the 19th century, with two exceptions: above-average levels in Anglo-Saxon settlement regions and below-average levels in Southeast Asia. After 1880, substantial divergences began to differentiate other regions. In addition, the determinants of these divergences are assessed. The analysis suggests that protein availability was a core variable for human health and welfare as measured with anthropometric indices. Moreover, disease environment, lactose tolerance, and geography also played an important role. Those variables reduced the unobservable world differences in height by more than a half.
Chapter three also deals with the determination of living standards. In contrast to chapter two, however, it emphasizes the role of state efficiency. It evaluates the quality of a country’s institutions by estimating the economic efficiency of their governments. We measure state efficiency by evaluating the process which transforms a given number of endowments, such as capital, labor power, and land, into welfare. Both an anthropometric yardstick, namely adult male height, and a monetary one (per-capita GDP) are applied to capture different kinds of human well-being. The Data Envelopment Analysis (DEA) is used in order to calculate efficiency values for 62 countries on a decadal basis between the 1850s and the 1980s.
In general, the results suggest that state efficiency increased among industrialized countries. Both Latin American (early 20th century) and African (post WWII) economies start on a relatively high level but show a systematic decline in the course of the 20th century. In Africa, former British colonies have done worse compared to their counterparts under French rule. In several countries we find wars, particularly occupation, violence and political instability to have a remarkable negative – sometimes even permanent – influence on state efficiency, as in the cases of Spain, Greece and Colombia. In this regard, typical characteristics of successful states seem to be agricultural specialization, redistribution and a homogeneous population.
Chapter four shows the interaction between inequality and living standards. It is argued that – according to the theory of diminishing returns to income – aggregate welfare is at its maximum if all resources are equally distributed among individuals in a society. In order to test this hypothesis the relationship between the Coefficient of Height Variation (CV) and average height is studied. The height CV is a measure of welfare inequality. It is an alternative to conventional yardsticks and it allows measuring inequality and economic development, both for countries and periods where conventional data are not available.
Using panel data on 105 countries during the past two centuries, the results indicate a systematic negative and concave relationship between inequality and average height, which can serve as a basis for the understanding of the consequences of economic inequality. An analysis of the correlates under study reveals that the influence of inequality has almost the same strength as per-capita income. After we distinguished between world regions and between birth decades the relationship still holds. An alarming finding is the increasing negative influence of inequality on average height during the post-WWII period.
Chapter five investigates anthropometric inequality in further detail. First, a literature review of anthropometric studies of within-country inequality is provided. Afterwards, the paper discusses the relationship between skill premia and inequality indicators based on height variation. Skill premia describe the wage gap between an unskilled and a skilled building worker, while height CVs display the variance in net nutrition. The results of this chapter indicate that the two measures are correlated and that CV values are suitable to estimate skill premia. We supplement the existing literature by an additional tool, namely the estimation of skill premia based on the coefficient of height variation (CV).