The Economy and Health in Historical Perspective

Paper Session

Sunday, Jan. 8, 2017 1:00 PM – 3:00 PM

Hyatt Regency Chicago, Grand Suite 5
Hosted By: American Economic Association
  • Chair: Brian Beach, College of William and Mary

Economic Conditions and Mortality: Evidence From 200 Years of Data

Adriana Lleras-Muney
,
University of California-Los Angeles
David Cutler
,
Harvard University
Wei Huang
,
Harvard University

Abstract

Using historical mortality data covering over 100 birth cohorts in 32 countries, this paper examines the short- and long- term effects of economic conditions on mortality. We confirm two seemingly contradictory patterns documented before. Poor economic conditions while growing up (from birth to age 25) significantly raise adult mortality. Yet contemporary downturns appear to decrease mortality. In addition we document some new findings. Poor economic conditions in adolescence have the largest adverse effect on adult mortality. We also find that although small expansions raise mortality, large expansions lower it. We rationalize these findings with a model of health investments that affect the stock of health, which in turn determines mortality. This simple model suggests that selection cannot explain the difference between the short- and long-term effects of good economic conditions. Instead economic conditions differentially affect the level and trajectory of both good and bad inputs into health. We investigate these implications by examining how several health inputs (income, pollution, behaviors and social relations) are affected by economic conditions. In line with previous work, shocks in adolescence have a large and lasting effect on adult incomes. Moreover higher government expenditures offset some of the negative effects of early-life economic fluctuations on health and incomes, consistent with the idea that these programs provide some form of insurance. Air pollution is strongly procyclical and helps explain the contemporaneous impact of economic conditions on mortality. Finally, data from the European Community Household Panel suggests that in addition to income, social integration improves with good economic conditions earlier in life, but does not support the idea that health behaviors do.

Yellow Fever and American Urban Development

Werner Troesken
,
University of Pittsburgh
Shawn McCoy
,
University of Nevada-Las Vegas

Abstract

This paper explores the effects of yellow fever on American urban growth. Before effective control measures were introduced around 1890, yellow fever epidemics frequently struck large port cities with high growth potential. These epidemics routinely killed 5 to 25 percent of the afflicted population. We show before 1890, populations in places with a history of yellow fever were falling relative to (or more precisely, converging with) populations in places without a history of yellow fever. However, after yellow fever was eradicated, populations in yellow-fever places began to diverge from, and grow much faster than, populations in places with no yellow fever. Overall, these results indicate that large places with high growth potential were the most likely to get hit with yellow fever, and that the risk of yellow fever hindered growth. Only with eradication of the disease did these high-growth places fully realize their long-term growth potential.

East Side Story: Historical Pollution and Persistent Neighborhood Sorting

Stephan Heblich
,
University of Bristol
Alex Trew
,
University of St. Andrews
Yanos Zylberberg
,
University of Bristol

Abstract

Why are the East sides of former industrial cities like London or New York poorer and more deprived? We argue that this observation is the most visible consequence of the historically unequal distribution of air pollutants across neighborhoods. In this paper, we geolocate nearly 5,000 industrial chimneys in 70 English cities in 1880 and use an atmospheric dispersion model to recreate the spatial distribution of pollution. First, individual-level census data show that pollution induced neighborhood sorting during the course of the nineteenth century. Historical pollution patterns explain up to 15% of within-city deprivation in 1881. Second, these equilibria persist to this day even though the pollution that initially caused them has waned. A quantitative model shows the role of non-linearities and tipping-like dynamics in such persistence.

Estimating the Recession-Mortality Relationship When Migration Matters

Vellore Arthi
,
University of Essex
Brian Beach
,
College of William and Mary
William Walker Hanlon
,
University of California-Los Angeles

Abstract

Are recessions good for health? A large literature following Ruhm (2000) addresses this question by applying a fixed-effects approach that implicitly assumes either that recessions do not generate a substantial migratory response, or that such responses are accurately reflected in intercensal population estimates. These assumptions may pose a serious methodological concern in settings, such as developing countries, that are characterized by weak social safety nets, mobile populations, and poor intercensal data. We illustrate this point by drawing on a natural experiment--the recession in Britain's cotton textile-producing regions caused by the U.S. Civil War (1861-1865--to provide evidence that migration-induced bias can substantially affect, and even reverse, estimates of the recession-mortality relationship. To deal with this bias, we propose a strategy based on accounting for mortality spillovers in migrant-receiving locations. Applying this methodology to our historical setting, we find evidence that, if anything, the recession we study increased mortality. In contrast, we show that existing approaches, which do not account for migration bias, would lead us to exactly the opposite conclusion. After adjusting for migration, we do find evidence that infant mortality fell, but this was offset by
large increases in mortality among the elderly.
Discussant(s)
Marcella Alsan
,
Stanford University
Joshua Lewis
,
University of Montreal
Amir Jina
,
University of Chicago
Atheendar Venkataramani
,
Massachusetts General Hospital
JEL Classifications
  • I1 - Health
  • N3 - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy