Brian A'Hearn

Quantifying Quantitative Literacy: Age Heaping and the History of Human Capital

Age data frequently display excess frequencies at round or attractive ages, such as even numbers and multiples of five. This phenomenon of age heaping has been viewed as a problem in previous research, especially in demography and epidemiology. We see it as an opportunity and propose its use as a measure of human capital that can yield comparable estimates across a wide range of historical contexts. A simulation study yields methodological guidelines for measuring and interpreting differences in age heaping, while analysis of contemporary and historical datasets demonstrates the existence of a robust correlation between age heaping and literacy at both the individual and aggregate level. To illustrate the method, we generate estimates of human capital in Europe over the very long run, which support the hypothesis of a major increase in human capital preceding the industrial revolution.

More international evidence on the historical properties of business cycles

This paper establishes stylized facts about business cycles in the late 19th century, using spectral analysis techniques which allow an intuitive description and analysis of cyclical structure in economic fluctuations. Analysis of industrial production data for 13 countries permits the following generalizations. In the advanced North Atlantic economies, a fairly regular long cycle with a periodicity of 7–10 years is identified in all countries. This component explains a substantial fraction of overall variation in industrial production. There is some evidence of a less regular, less powerful short cycle of 3–5 years duration. In peripheral economies experience is varied, but it is more often the short cycle that exercises greater influence. The long cycle component is shown to be highly correlated among the core economies, much less so between core and peripheral economies, and least of all among peripheral economies. The long cycle is more highly correlated among countries with important trading ties and those on a metallic monetary standard throughout the period.

Anthropometric Evidence on Living Standards in Northern Italy, 1730 1860

New estimates of mean stature indicate declining heights in Northern Italy from 1730 to 1860, corroborating recent findings of a deterioration in per capita GDP and real wages—though possibly calling into question its severity. The level of heights in the 1830s is respectable in international comparison. Estimated geographic and occupational effects show the influence of the disease environment, malnutrition, and income. Declining living standards suggest a Malthusian interpretation of the economy, in which even a relatively flexible agricultural sector was not quite able to keep up with the growing pressure of population on resources.John Komlos arranged the collection of the data analyzed here and made them available to me. I am also indebted to him for ongoing discussions about anthropometrics and helpful comments on this article. I am grateful to JA¶rg Baten, Giovanni Federico, Paolo Malanima, Gianni Toniolo, and Vincent Tassenaar for reading and commenting on the article, and to three anonymous referees for their com-ments. An earlier version of the article was presented at the Seminar for Economic History, University of Munich.

Height and the Normal Distribution: Evidence from Italian Military Data

Researchers modeling historical heights have typically relied on the restrictive assumption of a normal distribution, only the mean of which is affected by age, income, nutrition, disease, and similar influences. To avoid these restrictive assumptions, we develop a new semiparametric approach in which covariates are allowed to affect the entire distribution without imposing any parametric shape. We apply our method to a new database of height distributions for Italian provinces, drawn from conscription records, of unprecedented length and geographical disaggregation. Our method allows us to standardize distributions to a single age and calculate moments of the distribution that are comparable through time. Our method also allows us to generate counterfactual distributions for a range of ages, from which we derive age-height profiles. These profiles reveal how the adolescent growth spurt (AGS) distorts the distribution of stature, and they document the earlier and earlier onset of the AGS as living conditions improved over the second half of the nineteenth century. Our new estimates of provincial mean height also reveal a previously unnoticed “regime switch” from regional convergence to divergence in this period.

Russian Living Standards under the Tsars: Anthropometric Evidence from the Volga

The trend in mean height in the Russian province of Saratov is estimated for birth cohorts from 1755 to 1892 on the basis of newly gathered archival data and published sources. Heights fell in the late eighteenth century due an increasing burden of taxes and feudal dues. Stature increased slowly throughout the nineteenth century, offering no support for the hypothesis of an agrarian crisis that provoked or followed from the abolition of serfdom in 1861. Improving living conditions can be attributed to economic development, rising productivity in agriculture, and diversification of peasant economic activity into other sectors.

Internal Geography and External Trade: regional disparities in Italy, 1861-2011

This paper explores the interactions between external trade and regional disparities in the Italian economy since unification. It argues that the advantage of the North was initially based on natural advantage (in particular the endowment of water, intensive in silk production). From 1880 onwards the share of exports in GDP stagnated and then declined; domestic market access therefore became a key determinant of industrial location, inducing fast growing new sectors (especially engineering) to locate in regions with a large domestic market, i.e. in the North. From 1945 onwards trade growth and European integration meant that foreign market access was the decisive factor; the North had the advantage of proximity to these markets.

Improvements in Maximum Likelihood Estimators of Truncated Normal Samples with Prior Knowledge of O: A Simulation Based Study with Application to Historical Height Samples

Researchers analyzing historical data on human stature have long sought an estimator that performs well in truncated-normal samples. This paper reviews that search, focusing on two currently widespread procedures: truncated least squares (TLS) and truncated maximum likelihood (TML). The first suffers from bias. The second suffers in practical application from excessive variability. A simple procedure is developed to convert TLS truncated means into estimates of the underlying population means, assuming the contemporary population standard deviation. This procedure is shown to be equivalent to restricted TML estimation. Simulation methods are used to establish the mean squared error performance characteristics of the restricted and unconstrained TML estimators in relation to several population and sample parameters. The results provide general insight into the bias-precision tradeoff in restricted estimation and a specific practical guide to optimal estimator choice for researchers in anthropometrics.

On Historical Household Budgets

The paper argues that household budgets are the best starting point for investigating a number of big questions related to the evolution of the living standards during the last two-three centuries. If one knows where to look, historical family budgets are more abundant than might be suspected. And statistical techniques have been developed to handle the associated problems of small, incomplete, and unrepresentative samples. We introduce the Historical Household Budgets (HHB) Project, aimed at gathering data and sources, but also at creating an informational infrastructure that provides i) reliable storage and easy access to historical family budget data, along with ii) tools to configure the data as it is entered so as to harmonise it with present-day surveys.