Author Archives: Gregori GV

Black Living Standards in South Africa before Democracy

Black Living Standards in South Africa before Democracy: New Evidence From Heights

By: Bokang Mpeta (Stellenbosch University), Johan Fourie (Stellenbosch University) and Kris Inwood (University of Guelph)

Abstract: Very little income or wage data was systematically recorded on the living standards of South Africa’s black majority during much of the twentieth century. This paper uses four data sets to document, for the first time, an alternative measure of living standards: the stature of black South Africans over the course of the twentieth century. We find evidence to suggest that the first three decades of the century were particularly bad, perhaps due to the increasingly repressive labour policies in urban areas and famine and land expropriation that weighted especially heavily on the Basotho. The decade following South Africa’s departure from the gold standard, a higher international gold price and the demand for manufactured goods from South Africa due to the Second World War seem to have benefited both black and white South Africans. The data also allow us to disaggregate by ethnicity within the black population group, revealing levels of inequality within race group that has been neglected in the literature. Finally, we compare black and white living standards, revealing the large and widening levels of inequality that characterised twentieth-century South Africa.

URL: https://econpapers.repec.org/paper/rzawpaper/670.htm

Distributed by NEP-HIS on: 2017-10-15

Review by: Gregori Galofré-Vilà (University of Bocconi and University of Oxford)

Almost forty years ago, a group of historians led by Robert Fogel began to explore the potential of anthropometric measurements for answering a range of historical questions, largely, but not limited to, those concerning health and wellbeing (Fogel et al. 1978). Although around 80% of the main variation in individual height may be genetic, it has long been recognised that variations in the mean heights of different groups of people owe much to economic, social, and environmental circumstances.

Since the early efforts of Robert Fogel, anthropometric data contributed to long-standing debates such as the health of slaves in the US South (Steckel 1977) and the living standards during the British Industrial Revolution (Floud et al. 1990). Meanwhile many historians began to explore the development of height in many countries. For instance, Komlos (1985) began the collection of data for the Habsburg Empire, Martínez-Carrión (1986) for Spain and Sandberg and Steckel (1987) for Sweden, just to name a few. For a recent review of the height literature see Galofré-Vilà (2018).

Perhaps, the most interesting discovery until now, as commented by Floud et al. in The Changing Body (2011) and Deaton in The Great Escape (2016), is that since the 1850s, or over the course of some 6-7 generations, heights in Europe and North America have progressed into previously uncharted territories. For instance, Dutch men, being today the tallest in the world, grew from 166.5 to 182.7 (or 1.2 cm per decade). Better diets, sanitary reforms, lower frequency of sickness and shorter workdays are also reflected in terms of longevity, and during the same period Dutch life expectancy grew from 36.6 to 77.8 (or 2.8 years per decade).

However, in less wealthy parts of the world these improvements have been less important –if we can talk in terms of improvements at all. For instance, Guntupalli (2007) showed that Indian heights increased from 163.2 cm to 165.1 cm between the 1910s and 1980s (or 0.3 cm per decade) and Moradi et al. (2013) found that heights in Ashanti (Ghana) increased from 167.7 cm to 168.8 cm (or 0.6 cm per decade). Indeed, today life expectancy in developing countries is clearly below Western standards (in 2014 life expectancy in India was 68 years and 61 in Ghana).

In a very interesting paper, Bokang Mpeta, Johan Fourie and Kris Inwood (2017) take advantage of height records to chart, for the first time, the living standards of black South Africans between the 1890s and the 1990s. They addressed three questions: (1) Were poor black living standards a result of apartheid-era polices, or did they worsen even before South Africa’s most infamous era? (2) When did white and black living standards diverge? and (3) Can we explain the level and trend within the black population over the twentieth century? As the authors point out, the height data here are especially helpful as data on more conventional or modern indicators are lacking.

Similar to the less wealthy parts of the world, they found that the height of black South Africans improved little across the twentieth century (1.3 cm between 1895 and 1985 or 0.1 cm per decade). Indeed, as Figure 1 shows, they discovered that between the 1890s and 1910s heights declined from nearly 168 cm to 167 cm and linked this decline to the white repression and regulations of land expropriation (for instance, the 1913 Native Land Act was particularly painful as it banned the ownership of land by the black population). They also stressed some negative effects of extractive institutions following the discovery of diamonds in Kimberly in 1867 and gold mines in Johannesburg in 1886.

Figure 1: Height development of black South Africans between 1895 and 1990. Source: Mpeta, Fourie, Inwood (2017).

Yet, it seems that a reversal occurred when South Africa left the Gold Standard (in December 1932) and, due to the increases in the international price of gold, the prospects of employment for black people rapidly improved, with heights increasing from 167 cm to 168 cm during the 1930s and 1940s. Feinstein (2005) also observed that the Second World War created a powerful stimulus to local industries and gold mining, creating opportunities for many to sell goods abroad. However, this short-lived period of improvement somewhat slowed down after the 1950s, reaching 168.5 cm in the 1970s and followed the electoral victory of the National Party in 1948. The apartheid and new institutional reforms such as the 1959 Promotion of Black Self-Government Act (which among other things abolished parliamentary representation for Blacks) seem also to have worsened black living standards.

There are also additional interesting features of the paper. Black males born towards the end of apartheid were nearly 7 cm shorter than white males. However, this might not be surprising because, as the authors explain, infant mortality in the Cape Colony was two times higher for black Africans and the wages paid to white miners were almost eight times higher than those paid to black miners. They also find differences in height by nearly 2 cm between black ethnicities.

As seen in Figure 1 above, in order to have sufficient data to cover a century, the authors use four separate sets of data. First, the heights of men who joined the South African Army between 1940 and 1945 (and born between 1890 and 1922). Second, the heights derived from dead bodies deposited in regional hospitals of South Africa that were unclaimed (with birth years estimated between 1897 and 1980). Finally, the height data compiled in two modern health surveys: the 1998 South African Demographic and Health Survey (DHS) and the 2008 National Income Dynamics Study (NIDS). As the authors point out at different points in the paper, all these sources potentially carry different issues of selection and representativeness. For instance, there is almost no information on who these 500 dead men were and whose bodies were unclaimed. Indeed, this is a rather limited dataset with, on average, 6 men for each birth year. Meanwhile, medical surveys such as the DHS are based on men who were in a household at the time of the interview and married to a woman aged 15-49 (with single men neglected from the survey). Indeed, the differences between these two overlapping surveys after 1960 are rather curious.

The first sample, the military one, is perhaps the most controversial in light of recent papers from Bodenhorn, Guinnane and Mroz (2017) about sample selection bias. In a nutshell, these authors highlight the idea that height records coming from voluntary armies can be a biased sample of the underlying population because varying conditions of the economy and trade brought forward, at different times, recruits from different social classes. Mpeta, Fourie and Inwood (2017) seem rather confident that sample selection is not a concern here because heights and wages moved together and unemployment was rather low in the 1940s. Yet, Bodenhorn et al.’s argument requires the data to have been derived from men who were recruited over a relatively long period of time and Mpeta et al.’s black time-trends between 1895 and 1920 are derived from a shorter period of recruitment (1940-1945). Here, it would be interesting to know more about differences in economic conditions within that short-period of rapid economic growth and social change.

Indeed, the decline in black living standards seen between 1895 and 1920 is not universally accepted. For instance, in Why Nations Fail, Acemoglu and Robinson (2012) observe that “the development of the mining economy and the expansion of European settlement had other implications for the development of the area. Most notably, they generated demand for food and other agricultural products and created new economic opportunities for native Africans both in agriculture and trade”; at least, as the authors explain, until 1913 with the Native Land Act. The decline in stature found between the 1890s and 1910s might also be explained by the composition of age in the sample. Whenever we seek to derive time-trends from samples of army recruits who were recruited over relatively short periods of time, the time-trends appear to show a decline. This raises a question about the extent to which men who join the army at older ages are as representative of their birth cohorts as men who join at younger ages.
Despite these and other comments, and the limitation of data to pursue further econometric analysis, for now, we should be really grateful to the authors for charting a new African country in the height literature and for providing new material to ponder.

Acknowledgements

I thank María Gómez-León and Bernard Harris for valuable comments on a first draft of the column.

List of references

Acemoglu, D., J. Robinson. 2012. Why Nations Fail: The Origins of Power, Prosperity, and Poverty. New York: Crown Business.

Bodenhorn, H., T. W. Guinnane, and T. A. Mroz, “Sample-Selection Biases and the Industrialization Puzzle,” Journal of Economic History, 77(1), 171-207.

Deaton, A. 2013. The Great Escape: Health, Wealth, and the Origins of Inequality. Princeton University Press.

Feinstein, C.H. 2005. An Economic History of South Africa. Conquest, Discrimination and Development. Cambridge University Press.

Floud, R., K. W. Wachter, and A. Gregory. 1990. Height, Health and History: Nutritional Status in the United Kingdom, 1750-1980 (Cambridge University Press).

Floud, R., R. W. Fogel, B. Harris, and S. C. Hong. 2011. The Changing Body: Health, Nutrition, and Human Development in the Western World since 1700. Cambridge University Press.

Fogel, R. W., S. Engerman, J. Trussell, R. Floud, and C. L. Pope. 1978. “The Economics of Mortality in North America, 1650-1910: A Description of a Research Project,” Historical Methods 11:2, 75-108.

Galofré-Vilà, G. 2018. “Growth and Maturity: A Quantitative Systematic Review and Network Analysis in Anthropometric History,” Economics and Human Biology 28, 107-118.

Guntupalli, A. M. 2007, Anthropometric Evidence of Indian Welfare and Inequality in the 20th century, Doctoral diss., Tübingen University.

Komlos, J. 1985. “Stature and Nutrition in the Habsburg Monarchy: The Standard of Living and Economic Development in the Eighteenth century,” The American Historical Review 90:5, 1149-1161.

Martínez-Carrión, J. M. 1986. “Estatura, nutrición y nivel de vida en Murcia, 1860-1930,” Revista de Historia Económica – Journal of Iberian and Latin American Economic History 4:1, 67-97.

Moradi, A., Austin, G., Baten, J. 2013. “Heights and Development in a Cash‐Crop Colony: Living Standards in Ghana, 1870‐1980,” unpublished manuscript.

Mpeta, B., Fourie, J., and Inwood, K. 2017. “Black Living Standards in South Africa before Democracy: New Evidence from Heights,” Stellenbosch Economic Working Papers 10/2017.

Sandberg, L. G., and R. H. Steckel. 1987. “Heights and Economic History: the Swedish case,” Annals of Human Biology 14:2, 101-110.

Steckel, R. H. 1977. The Economics of U.S. Slave and Southern White Fertility. Doctoral diss., University of Chicago.

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Beggar-thy-neighbouring-drinker: Effects of Prohibition on American Infant Mortality in the 1930s

Infant Mortality and the Repeal of Federal Prohibition

By: David S. Jacks (Simon Fraser University), Krishna Pendakur (Simon Fraser University), and Hitoshi Shigeoka (Simon Fraser University).

Abstract: Exploiting a newly constructed dataset on county-level variation in Prohibition status from 1933 to 1939, this paper asks two questions: what were the effects of the repeal of federal prohibition on infant mortality? And were there any significant externalities from the individual policy choices of counties and states on their neighbors? We find that dry counties with at least one wet neighbor saw baseline infant mortality increase by roughly 3% while wet counties themselves saw baseline infant mortality increase by roughly 2%. Cumulating across the six years from 1934 to 1939, our results indicate an excess of 13,665 infant deaths that could be attributable to the repeal of federal Prohibition in 1933.

URL: http://www.nber.org/papers/w23372

Distributed by NEP-HIS on: 2017-05-21

Review by: Gregori Galofré-Vilà (University of Bocconi and University of Oxford)

In 1919, the National Prohibition Act (also known as Volstead Act), which passed with the support of American rural protestants and social progressives, mandated that “no person shall manufacture, sell, barter, transport, import, export, deliver, furnish or possess any intoxicating liquor.” The 1920s became the decade when Al Capone operated in the Canadian and Mexican borders smuggling alcohol with the well-known subsequent boost to organized crime.  President Roosevelt lifted Prohibition in 1933, although its rejection was through local referendums or elections. The repeal of Prohibition in some parts of the country divided the US into ‘dry’ and ‘wet’ areas. In dry areas, people either abstained, or were forced to buy alcohol sometimes from toxic homebrews of methanol at illegal underground bars or from ‘wet’ neighbouring counties. Meanwhile, in ‘wet’ areas, the party was on! Interestingly enough, the end of the Prohibition created what epidemiologists call ‘a natural experiment’. These experiments arise from historical events that affect some people, communities or societies, but not others. This divergence offers the possibility of learning how political choices ultimately affect people’s lives, for better or for worse.

Figure 1 ok

To explore the health impacts of the repeal of the National Prohibition Act, Jacks, Pendakur and Shigeoka (2017) created a newly county-level dataset on variations in prohibition status from 1933 to 1939, and related it to previous data on infant mortality from Fishback et al. (2011) and to additional controls (such as retail sales, New Deal spending, urbanisation and so on). They addressed two questions: (1) what were the effects of the repeal of federal Prohibition on infant mortality?; and (2) were there any significant externalities from the individual policy choices of counties and states on their neighbours? In relation to the first question, they found that the effects were quite small: from 1934 until 1939, there was an excess of 13,665 infant deaths (or 1.2 additional deaths per 1,000 live births) that could be attributed to the repeal of the Prohibition in 1933. Indeed, Fishback found that the effects of the New Deal or climatic variations had greater impact on infant mortality (Fishback 2007; 2011). As for the second question, their results indicated that cross-border policy externalities were likely to be important, and that the impact of the prohibition status of individual county on infant mortality was driven by the prohibition status of its neighbours, with higher results on infant mortality for dry counties bordering with wet neighbours.

A very interesting feature of the paper is the methodological approach used in order to recognise the possibility of policy externalities across county borders. Due to spillovers and the open economy, it was not only the county’s choice (the county’s status with regards to prohibition), but, indeed, the prohibition status of its neighbours. Hence, they distinguished among counties that allow the sale of alcohol within their borders (‘wet’ counties), ‘dry’ countries with also ‘dry’ neighbours, and ‘dry’ counties next to a wet neighbours (‘dryish’ counties). In addition to several robustness tests, I particularly like the border-pair discontinuity design considering neighbouring county-pairs. This approach follows a modification of the methodology developed by Dube et al. (2010). The idea is that given the social and economic similarities between neighbouring counties, these are likely to be a good suitable control group as they share common, but unobserved county characteristics with the treatment group. In other words, in this identification strategy, the prohibition status of counties within a county-pair is uncorrelated with the differences in residual infant mortality in either county. This strategy, in turn, gets rid of the need for instrumental variables to limit biases imparted by unobserved or unmeasured confounders correlated with Prohibition.

Figure 2

While this is a really interesting paper, given the small effects, it is possible that the hypothesised causal mechanism between Prohibition, maternal alcohol consumption during pregnancy (from which no data exist) and infant mortality does not fully capture the effects of the Prohibition on health. If that is the case, the selection of infant mortality data is likely to be underestimating the causal effect of Prohibition on health. For example, in The Body Economic, Stuckler and Basu (2013) argued that during the Great Depression the states with the most stringent Prohibition campaigns lowered adult drinking related deaths by around 20% and also diminished suicides rates substantially. Yet, the fact that Jacks et al. (2017) have been able to find effects of the Prohibition on infant mortality highlights the relevance of the Prohibition on health and warrants further research, a research nested into the wider literature of the Great Depression and the New Deal.

References

Dube, A., T.W. Lester, and M. Reich (2010), “Minimum Wage Effects Across State Borders.” Review of Economics and Statistics 92(4), 945-964.

Fishback, P.V., M.R. Haines, and S. Kantor (2007), “Births, Deaths, and New Deal Relief during the Great Depression.” Review of Economics and Statistics 89(1), 1-14.

Fishback, P.V., W. Troesken, T. Kollmann, M. Haines, P. Rhode, and M. Thomasson (2011), “Information and the Impact of Climate and Weather on Mortality Rates During the Great Depression.” In The Economics of Climate Change (Eds G. Libecap and R. Steckel). Chicago: University of Chicago Press, 131-168

Jacks, D.S., K. Pendakur, and H. Shigeoka (2017), “Infant Mortality and the Repeal of Federal Prohibition.” NBER Working Paper No. 23372

Stuckler, D. and S. Basu (2015) The Body Economic: Why Austerity Kills. Basic Books.