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.

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.

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.

{Economics ∪ History} ∩ {North ∪ Fogel}

A Cliometric Counterfactual: What if There Had Been Neither Fogel nor North?

Claude Diebolt (Strasbourg University) and Michael Haupert (University of Wisconsin – La Crosse)

Abstract – 1993 Nobel laureates Robert Fogel and Douglass North were pioneers in the “new” economic history, or cliometrics. Their impact on the economic history discipline is great, though not without its critics. In this essay, we use both the “old” narrative form of economic history, and the “new” cliometric form, to analyze the impact each had on the evolution of economic history.

URL: http://d.repec.org/n?u=RePEc:afc:wpaper:05-17&r=his

Circulated by nep-his on: 2017-02-19

Revised by Thales Zamberlan Pereira (São Paulo)

Douglass North and Robert Fogel’s contribution to the rise of the “new” economic history is well known, but Diebolt and Haupert’s paper adds a quantitative twist to their roles as active supporters of cliometrics when there was still resistance to apply new methods to the study of the past. Economic theory and formal modeling marked the division between the “old” and the “new” economic historians in the 1960s, and Diebolt and Haupert use two metrics to track the transformation in the field: 1) the increased use of graphs, tables, and especially equations during North’s period as editor (along with William Parker) of the Journal of Economic History between 1961 and 1966; 2) the citation of Fogel’s railroad work, to measure the impact of his innovations in economic history methodology.

Before showing their results about the positive influence of North and Fogel on quantitative economic history, the authors present a brief history of cliometrics, beginning with the 1957 meeting of the Economic History Association (EHA). It was there that Alfred Conrad and John Meyer presented their two foundational papers, about the use of economic theory and statistical inference in economic history, and the economics of slavery in the antebellum South. From that meeting, William Parker edited what was probably the first book (released in 1960) of the cliometric movement.

It was during the 1960s, however, that larger changes would occur. First, Parker and North were appointed editors of the Journal of Economic History (JEH) in 1961 and began to promote papers that used more economic theory and mathematical modelling. Their impact appears in Figures 2 and 3, which show a measure of “equations per page” and “graphs, tables, and equations per page” in the JEH since its first issue in 1941.

As a way stay true to the spirit of the discussion, Diebolt and Haupert test the hypothesis if the period between 1961 and 1966 had an enduring effect in the increase of “math” in the JEH. Despite a noticeable increase in the North and Parker years, it was only in 1970 that a significant “level shift” occurs in the series, and Diebolt and Haupert argue that this could be interpret as a lag effect from the 1961-1966 period. Their finding that 1970 marks a shift in the methodology of papers published in the JEH is consistent with the overall use of the word cliometrics in other publications, as a NGRAM search shows.

https://books.google.com/ngrams/interactive_chart?content=cliometrics&year_start=1930&year_end=2000&corpus=15&smoothing=3&share=&direct_url=t1%3B%2Ccliometrics%3B%2Cc0

In addition to the editorial impact of Douglass North in the JEH, the second wave of change in economic history during the 1960s was Robert Fogel. In 1962, Fogel published his paper about the impact of railroads in American economic growth. The conclusion that railroads were not essential to America, along with the use of counterfactuals to arrive at that result, “attracted the attention of the young and the anger of the old” economic historians (McCloskey, 1985, p. 2). Leaving the long debate about counterfactuals aside, what Fogel’s work showed was that the economics methodology at the time was useful to overcome the limitations of interpreting history based only on what historical documents offered at face value.

Diebolt and Haupert’s paper, therefore, shows that cliometric research in the JEH had a positive exogenous shock with North as an editor, with Fogel supplying the demand brought by the new editorial guidelines. However, there is a complementary narrative about these developments that deserves to be mentioned. Many innovations in methodology brought to the field after 1960 came from researchers who were primarily concerned with economic growth, not only with historical events. This idea appears in the paper, when the authors argue that during his post-graduate studies, the starting point of Fogel’s research was about the “large processes of economic growth” (p.8). In addition, the realization that Fogel’s training program “was unorthodox for an economic historian” is also indicative that, in the 1960s, with computational power and new databases that extended to the 19th century, history was the perfect case study to test economic theory.

This exogenous impact in the field, with clear beneficial results, is similar to the role Daron Acemoglu and his many authors had in reviving economic history in the last decade to a broader audience. Acemoglu initial focus when he presented a different way to do research in economic history was in the present (i.e. long-run growth), not the past. It seems, therefore, that the use of mathematical models in economic history was not a paradigm shift in the study of history, but rather it followed the change from what was considered “being an economist” in the United States. After 1945, Samuelson’s Foundations of Economic Analysis set the standard for the type of training that econ students received, turning mathematical models as the dominant method in economics (Fourcade, 2009, p. 84). Cliometrics, by following this trend, created an additional way to do research in economic history.

https://books.google.com/ngrams/interactive_chart?content=Economic+models&year_start=1930&year_end=2000&corpus=15&smoothing=3&share=&direct_url=t1%3B%2CEconomic%20models%3B%2Cc0

One comparative advantage of the new economic historians, in addition to the “modern” training in economics, was something that can be called the Simon Kuznets effect. Both North and Fogel worked with Kuznets, and the development of macroeconomic historical databases at the NBER after the 1930s provided the ground to apply new methodologies to understand economic growth. In the first edition of the Journal of Economic History Kuznets already advocated the use of statistical analysis in the study of history (Kuznets, 1941). But the increase in popularity of models and statistics in economic history, especially in the 1970s (see Temin, 2013), seems to be related to its impact to understand the broader questions of economics. One notable example comes with Milton Friedman and Anna Schwartz’s monetary history of the United States, published in 1966. Friedman worked with Kuznets in the 1930s, and the book is the typical research in economic history with a focus on “contemporary” issues.

As Diebolt and Haupert claim, North and Fogel contribution is undeniable, but what about the contrafactual they propose in the title? Just as no single innovation was vital for economic growth, probably no economic historian was a necessary condition for cliometrics. Without North and Fogel, maybe the old economic historians would have had another decade, but by the 1970s the JEH would be under new management.

References

• Fourcade, M. (2009) Economists and Societies: Discipline and Profession in the United States, Britain, and France, 1890s to 1990s. Princeton, NJ: Princeton University Press.
• Kuznets, S. (1941) ‘Statistics and Economic History’, The Journal of Economic History, 1(1), pp. 26–41.
• McCloskey, D. N. (1985) ‘The Problem of Audience in Historical Economics: Rhetorical Thoughts on a Text by Robert Fogel’, History and Theory, 24(1), pp. 1–22. doi: 10.2307/2504940.
• Temin, P. (2013) The Rise and Fall of Economic History at MIT. Working Paper 13–11. Boston, MA: MIT. Available at: https://papers.ssrn.com/abstract=2274908 (Accessed: 29 May 2017).

Challenging the Role of Capital Adequacy using Historical Data

Bank Capital Redux: Solvency, Liquidity, and Crisis
By Òscar Jordà (Federal Reserve Bank of San Francisco and University of California Davis), Bjorn Richter (University of Bonn), Moritz Schularick (University of Bonn) and Alan M. Taylor (University of California Davis).

Abstract: Higher capital ratios are unlikely to prevent a financial crisis. This is empirically true both for the entire history of advanced economies between 1870 and 2013 and for the post-WW2 period, and holds both within and between countries. We reach this startling conclusion using newly collected data on the liability side of banks’ balance sheets in 17 countries. A solvency indicator, the capital ratio has no value as a crisis predictor; but we find that liquidity indicators such as the loan-to-deposit ratio and the share of non-deposit funding do signal financial fragility, although they add little predictive power relative to that of credit growth on the asset side of the balance sheet. However, higher capital buffers have social benefits in terms of macro-stability: recoveries from financial crisis recessions are much quicker with higher bank capital.

URL: http://econpapers.repec.org/paper/nbrnberwo/23287.htm

Distributed by NEP-HIS on: 2017-05-07

Review by Tony Gandy (London Institute of Banking and Finance)

In 1990-1991 I started a new job, having nearly completed my PhD (which I fully admit I took longer than it should). I joined The Banker, part of the Financial Times group, and proceeded to cover bank statistics, research and bank technology (the latter being a bit of a hobby). Thanks to the fine work of my predecessor, Dr. James Alexander, we had been through a statistical revolution and had revamped our Top 1000 listings of the world’s biggest banks, moving to a ranking based on capital rather than assets. This was the zeitgeist of the moment; what counted was capital, an indicator of capacity to lend and absorb losses. We then also ranked banks by the ratio of loss absorbing capital to total assets to show which were the “strongest” banks. We were modeling this on the progress made by the Basel Committee on Banking Supervision in refocusing banking resilience on to this important ratio, so called capital adequacy and the acknowledging the development and launch of the original Basel Accord.

All well and good, the role of capital was to absorb losses. It seemed on the face of it, that whichever bank had the most capital, and which ever could show the best capital adequacy ratio was clearly the most robust, prudent and advanced manager of risk and the one able to take on more business.

As the years progressed, Basel 1.5, II, 2.5, III and, arguably, IV have each added to or detracted from the value of capital as a guide to robustness. However, the principle still seemed to stand that, if you had a very large proportion of capital, you could absorb greater losses making the bank and the wider economic system more robust. Yes, OK there were weaknesses. Under the original Accord, only the only risk being worries about was credit risk and in only a very rudimentary way. This seemed odd given that one of the events which led to the Basel Accord was the failure and subsequent market meltdown caused by the failure of Bankhaus Herstatt [1] (Goodhart 2011), but it was hard to see how that was in isolation a credit event. Nevertheless, through all the subsequent crises and reforms to the Basel Accords, the principle that a higher proportion of quality capital to assets held by a bank was a good thing.

Jordà, Richter, Schularick and Taylor challenge the assumption that greater capital adequacy can deflect crisis, though they do find that higher initial capital ratios have a great benefit in the post crisis environment. In this working paper, Jordà et al. create a data set focusing on the liability side of bank balance sheets covering a tight definition of Common Equity Tier 1 capital (paid up capital, retained profit and disclosed reserves), deposits and non-core funding (wholesale funding). This is a powerful collection of numbers. They have collated this data for 14 advanced economies from 1870 through to 2013 and for three others for a slightly shorter period.

One note is that it would have been interesting to see a little more detail on the sources of the data used. Journal papers and academic contributions are acknowledged throughout, but other sources are covered by “journal papers, central bank publications, historical yearbooks from statistical offices, as well as archived annual reports from individual banks”. Bank statistics can be a complex area, some sources have sometimes got their definitions wrong (one annual listing of bank capital had an erratum which was nearly as long as the original listings, not mine I hasten to add and maybe my memory, as a rival to that publication, somewhat exaggerates!), so a little more detail would be useful. Also, further discussion of the nature of disclosed reserves would be interesting as one of the key concerns of bank watchers in the past has been the tendency of banks to not disclose reserves or their purposes.

Jordà et al.’s findings are stark. Firstly, and least surprisingly, bank leverage has greatly increased. The average bank capital ratio in the dataset shows that in early period it hovered at around 30% of unadjusted assets, falling to 10% in the post war years and more recently hovering around 5-10%.

Source: Jordà et al. (2017)

Next, they consider the relevance of capital adequacy as a protection for banks and a predictor of a banking system’s robustness; does a high, prudent, level of capital reduce the chances of a financial crisis? The authors note the traditional arguments that higher levels of capital could indicate a robust banking system able to absorb unexpected losses and thus reducing the chance of a financial crisis, but also note that high capital levels could equally indicate a banking system taking greater risks and therefore needing greater amounts of capital to survive the risks. They find no statistical link between higher capital ratios and lower risk of systemic financial crisis, indeed, they find limited evidence that it could be the reverse. It’s worth noting a second time: Increasing capital ratios do not indicate a lower risk of a financial crisis

The authors do note, however, that high levels and rapidly increasing loan-to-deposit ratios are a significant indicator of future financial distress. Clearly, funding a bubble is a bad idea, though it can be hard to resist.

However, capital can have a positive role. The paper finds that systems which start with higher levels of leverage (and consequently lower capital ratios) will find recovery after a crisis harder as banks struggle to maintain solvency and liquidate assets at a greater rate. Thus, while a high capital adequacy ratio may not be a protection against a systemic crisis, it can provide some insight into the performance of an economy after a crunch as banks with higher capital ratios may not face the same pressure to sell and further deflate asset prices and economic activity. Therefore, capital can have a positive role!

Source: Jordà et al (2017)

I won’t pretend to understand fully the statistical analysis presented in this paper, however, while many, including those at the Basel Committee, have recognised the folly of tackling only prudential control through a purely credit risk-focus on capital adequacy and have introduced new liquidity, leverage and scenario planning structure to deflect other routes to crisis. Nevertheless, Jordà et al. provide a vital insight into what is still the very core of the prudential control regime: the value, or not, of capital in providing protection to banks and banking systems. Its role may not be what we expected, its value being in a post-crisis environment and not a pre-crisis environment where higher requirements could have been expected to head-off problems. Instead they find that it is credit booms and indicators of them, such as rapidly rising Loan to Deposit ratios which are better indicators of looming crisis, and capital is more relevant to making brief the impact of an unravelling bubble.

On a more practical note, this fascinating paper offer those who teach prudential regulation to bankers or students a wealth of data and challenges to consider, a welcome resource indeed.

Notes:

[1] The other main response was the more appropriate formation of the first netting services and then the Continuously Linked Settlement Bank as a method of improving operations to remove the risk which became known as “Herstatt Risk”.

References
Goodhart, Charles (2011) The Basel Committee on Banking Supervision: a history of the early years, 1974–1997. Cambridge University Press, Cambridge, UK

 

The Data We Have vs. the Data We Need: A Comment on the State of the “Divergence” Debate (Part II)

How Well Did Facts Travel to Support Protracted Debate on the History of the Great Divergence between Western Europe and Imperial China?

By: Kent Deng (London School of Economics), Patrick O’Brien (London School of Economics)

Abstract: This paper tackles the issue of how reliable the currently circulated ‘facts’ really are regarding the ‘Great Divergence’ debate. Our findings indicate strongly that ‘facts’ of premodern China are often of low quality and fragmented. Consequently, the application of these ‘facts’ can be misleading and harmful.

URL: http://econpapers.repec.org/paper/pramprapa/77276.htm

Distributed by NEP-HIS on: 2017-03-19

Review by: Kenneth Pomeranz (University of Chicago)

(continued)

Comparative Consumption

 

This brings us, finally, to consumption.  As noted at the beginning of this comment, I agree that this is the most promising area for future research that might illuminate comparative living standards.  It is hard to know where really definitive data would come from: since the Chinese state did not systematically tax any major consumer goods except salt, and very little that ordinary people used was imported, we are unlikely to find data anywhere near as reliable as what we have for liquor, sugar, tobacco, etc., in various European countries.  Nonetheless, it is not that hard to imagine data that would help us make some progress in this area.^[1]  And the area where O’Brien and Deng concentrate here – calories from grain – is, of course, fundamental, and there are various ways to generate estimates.  (It should be noted, however, that in unequal societies, the grain consumption of the poor is likely to be a lagging indicator of overall economic divergence –changes in the lives of the first and second quartiles of the income distribution could produce significant differences in average incomes well before the food intake of the poor in one society began to significantly outpace that of their counterparts in another.)  Thus, I applaud the attempt to see what we can learn by focusing on estimates of poor people’s incomes in kilocalories.  I have strong doubts, however, about the conclusion that Deng and O’Brien reach about this matter.

First, it is worth noting that various estimates have been made, which suggest that at least in this area, Chinese poor people (and perhaps some others elsewhere) were no worse off than their Western European counterparts. I have discussed several of them elsewhere, and little would be served by repeating that effort here.^[2] 

O’Brien and Deng disagree, and rely upon a paper they published  in Journal of World History (2015).  That paper takes estimates of the likely income from a typical-sized tenant farm in the 18^th-19^th century Yangzi Delta, as calculated by Philip Huang, Robert Brenner and Christopher Isett, Robert Allen, and myself, and suggests that they converge upon a range of likely incomes that falls considerably short of the incomes of English laborers at the same time. I do not think that that is the most reasonable inference to be drawn from this data.

As they note in their current publication, I wrote to O’Brien and Deng after their  paper was published, largely agreeing with their methodology but questioning their data.  They apparently do not think the difference over data is important, since quickly continue “Nevertheless, these procedure provided us with figures for levels and changes in the standard of living for peasant households in Jiangnan from circa 1600 to circa 1829.” This, I think, misses the significance of the disagreement on data, which is easily stated.  Allow me to quote from the letter I wrote at the time, adding only some boldfaced type for emphasis, and a few explanations of reference in square brackets::

    “…    The key is Row 3 [of Table 4, pages 248-253]: ‘Area cultivated: mu,’ where you suggest that Huang, Brenner and Isett and I all accept an average farm size of 7.5 mu.  Brenner and Isett, of course, simply accepted Huang’s figure: they were all working together,  Brenner reads no Chinese and Isett (B and H’s student) had never worked on the Yangzi Delta.  So that is really one assertion that the farm size was 7.5 mu.  In your notes to that row you suggest that I also accept that figure; there is no direct citation for that point, but earlier you cite my “Facts Are Stubborn Things” essay.   But here’s what I wrote there, referring back to my essay in the first round of our debate [that is, my debate with Huang] (“Beyond the East-West Binary):

‘  …while I accepted Huang’s average farm size of  7.5 mu for purposes of our initial discussion, this  prevailed (if at all) only in the Delta’s most crowded prefectures, where people mostly grew cotton or mulberries.  The larger Delta I discuss had 59,000,000 registered cultivated mu circa 1770, or 10.5 mu  per 5-member farm family. [1]   This confirms Li Bozhong’s estimate that mid-Qing Jiangnan farms averaged 10 mu…’

 

And indeed, the 7.5 mu figure seems very unlikely to be right.  Consider, just for starters, that the sources you cite for 1820 give farm sizes of either 9.0 or 10 mu (depending on what definition one uses for Jiangnan);  it is widely agreed that there was no new land cleared in Jiangnan after the mid-18^th century (further intensification took the form of more double-cropping), and while population figures are not very reliable, there was almost certainly some increase.  (Cao Shuji’s figures (2000, 5:691-92)  suggest a 38% increase from 1776 to 1850, with the rate of increase faster in the earlier years,  for instance; I think that is probably too high, but you see the point.) It thus seems pretty implausible that farmed acreage per family would have been anywhere from 1/6 to ¼ less in 1750 than it would be 70 years later.

Since I think you [Deng and O’Brien] have accurately reported the other figures in your table, the consequences of this one change would be quite significant.  Using 10 mu per family for 1750 would raise the estimate of caloric income in my data from 2,438 to 3,251; using 10.5 raises it to 3,413.  Thus, instead of more or less agreeing with Brenner and Isett, my numbers come to be 30-40 % above theirs – and over 80% above Huang’s (rather than about 33%). Perhaps more importantly, if you turn to your table 6, making this change would mean that instead of having a rough consensus on Jiangnan caloric intake that had already fallen a bit below English farm laborers (if one assumes they ate wheat) or significantly behind them (if they ate oats), you would be back to two views: one based on Huang’s data, that suggested what I have just said, and one which placed the caloric intake of Jiangnan farmers even with English farm laborers if they consumed oats, and still well ahead of them if they consumed wheat.  Significant divergence on this particular measure (admittedly one that lagged others) would be pushed well into the 19^th century.  (In fact, if we accept Li or Allen’s work, as summarized in your column for 1800-1849, it would still not have happened in that period.).The difference is therefore quite significant…”

 

Moreover, I would add,  the adjustment I suggested in this missive would sharply alter the picture of change over time in the Yangzi Delta, yielding a more likely picture that has different comparative implications.  Without the correction, Deng and O’Brien’s data suggest a fairly sharp decline in living standards between 1600 and 1750, with a recovery to roughly 1600 levels by 1829.^[3]   This, however, seems unlikely, since it was widely agreed that 1750 was near the middle of a prosperous era, while 1829 was (as already noted) part of an era of crisis.  (Whether the 1620s were part of a good period or not is less settled.^{[4] )}     If we instead adjust the 1750 farm size figures as I have suggested, we have a probable improvement of living standards between 1620 and 1750 (perhaps even a large improvement), followed by either stasis or decline between 1750 and the 1820s; this would be much more in line both with the testimony of contemporary voices and the views of most historians.  And if that is right, it would also fit the picture of an East/West divergence  that came late but gathered steam quickly: not only because first Britian and then other parts of Northwestern Europe surged, but because the most prosperous parts of China began to fall into crisis.

Obviously, we would like comparisons of living standards, even among the poor, to go beyond caloric intake; and attempts have been made, by a number of us, to look quantitatively at cloth, sugar, tea, and a few other goods, and more impressionistically at tobacco, various forms of entertainment, and so on.   But for the time being, those discussions are nowhere near consensus; and in the world of the late 18^th century, basic calories still loomed quite large in any case.  And there, I would respect, correcting the error noted above suggests that the balance of available research still suggests comparability until quite late. (Huang’s numbers have other serious problems, which I have discussed elsewhere.[5])    Until we get beyond basic calories in discussing the poor – and get much better estimates, on the Chinese side, of the distribution of income,[6] so we know more about what comparisons of the poor do and do not tell us, our picture of comparative consumption will remain quite inadequate for settling our debates, even if it remains the most promising area for further research; and as long as our understanding of consumption remains so inadequate, I would be loath to shut the door on the other approaches that Deng and O’Brien encourage us to abandon.

Bibliography

Allen, Robert.  2000. “Economic Structure and Agricultural Productivity in Europe, 1300 – 1800,” European Review of Economic History 4:1 (April, 2000),

Allen, Robert. 2004. “Mr. Lockyer Meets the Index Number Problem: The standard of Living in Canton and London in 1704,”  July 2004, available at http://www. iisg.nl/hpw/papers/allen.pdf, accessed December 7, 2008

Allen, Robert. 2009a. The British Industrial Revolution in Global Perspective. Cambridge: Cambridge University Press.

Allen, Robert. 2009b. “Agricultural Productivity and Rural Incomes in England and the Yangzi Delta, ca. 1620-1820,” Economic History Review 62:3 (August), pp. 525-550.

Allen, Robert et.al., 2011.  Robert Allen, Jean-Pascal Bassino, Debin Ma, Christine Moll-Murata, and Jan LuitenVan Zanden, “Wages, Prices and Living Standards in China 1738-1925: In Comparison with Europe, Japan, and India,” Economic History Review 64:1 (February), pp. 8-38.

Baten, Joerg. et al.  2010.  Joerg Baten, Debin Ma, Stephen Morgan and Qing Wang, “Evolution of Living Standards and Human Capital in China in the 18^th – 20^th Centuries: Evidences From Real Wages, Age-Heaping, and Anthropometrics,” Explorations in Economic History 47, pp. 347-359.

Benedict, Carol. 2011.  Golden-Silk Smoke: A History of Tobacco in China 1550- 2010. Berkeley: University of California Press.

Brenner, Robert and Christopher Isett. 2002. “England’s Divergence from the Yangzi Delta: Property Relations, Microeconomics, and Patterns of Development,” Journal of Asian Studies 61:2 (May), pp. 609-662.

Broadberry, Stephen, Hanhui Guan and David Daokui Li. 2014. “China, Europe, and the Great Divergence: A Study in Historical National Accounting, 980 – 1850,” http://eh.net/eha/wp-content/uploads/2014/05/Broadberry.pdf.

 

Chang Chung-li (Zhang Zhongli). 1962. The Income of the Chinese Gentry.  Seattle: University of Washington Press.Deng, Kent G., and Patrick K. O’Brien. 2015. “Nutritional Standards of Living in England and the Yangtze Delta (Jiangnan), circa 1644 – circa 1840: Clarifying Data for Reciprocal Comparisons,” Journal of Wor;d History 26:2 (June), pp. 233-267.

Guan Hanhui and David Daokui Li.  2010. “Mingdai GDP ji jiegou shitan,” (A Study of  GDP and its Sturcture in China’s Ming dynasty),” Zhongguo jingji jikan 9:3 (April), pp. 787-829,   http://en.cnki.com.cn/Article_en/CJFDTotal-JJXU201003003.htm
Huang, Philip. 1990. The Peasant Family and Rural Development in the Lower Yangzi Region, 1350-1988.  Stanford: Stanford University Press.

Huang, Philip C.C.  2002a. “Development or Involution in Eighteenth Century Britain and China?  A Review of Kenneth Pomeranz’s The Great Divergence: China, Europe and the Making of the Modern World Economy,”  Journal of Asian Studies 61:2 (May), pp. 501-538.

Huang  Philip. C.C.  2003. “Further Thoughts on Eighteenth-Century Britain and China: Rejoinder to Pomeranz’s Response to My Critique,” Journal of Asian Studies 62:1 (February), pp. 157-167.

Lal, Deepak. 1998. Unintended Consequences: The Impact of Factor Endowments, Culture, and Politics on Long-Run Economic Performance.  Cambridge: MIT Press, 1998.
Landes, David. 1998.  The Wealth and Poverty of Nations.  New York: Norton.

Lee, James, Cameron Campbell and Wang Feng. 2002. “Positive Check or Chinese Checks?” Journal of Asian Studies 61:2  (May), pp. 591-607.

Li Bozhong and Jan Luiten Van Zanden. 2012. “Before the Great Divergence? Comparing the Yangzi Delta and the Netherlands at the Beginning of the Nineteenth Century,” Journal of Economic History 72:4 (December), pp. 956-989.

Li Wenzhi and Jiang Taixin, 2005.  Zhongguo dizhu zhi jingji lun (Essays on the Chinese Landlord Economy). Beijing: Zhongguo shehui kexue chubanshe,

Liu, William Guanglin. 2015.  The Chinese Market Economy 1000-1500,  Albany: State University of New York Press.

 Ma,Debin. 2004. “Modern Economic Growth in the Lower Yangzi in 1911-1937: a Quantitative, Historical, and Institutional Analysis” (Discussion paper 2004-06-002, Foundation for Advanced Studies on International Development, Tokyo.

Maddison, Angus. 2001.  The World Economy: A Millenmial Perspective.  Paris: OECD.

Maddison, Angus. 2003. The World Economy: Historical Statistics. Paris: OECD.

 

Moll-Murata, Christine. 200. “Chinese Guilds from the Seventeenth to the Twentieth Centuries: An Overview,”  International Review of Social History 53, Supplement, pp. 213-247.

 

Morgan, Stephen. 2004.  “Economic Growth and the Biological Standard of Living in China 1880-1930,” Economic and Human Biology 2:2

Pomeranz, Kenneth. 2000.  The Great Divergence: China, Europe, and the Making of the Modern World Economy.  Princeton: Princeton University Press.

Pomeranz, Kenneth. 2002 “Beyond the East-West Binary: Resituating Development Paths in the Eighteenth Century World,”  Journal of Asian Studies 61:2 (May, 2002), pp. 539-590.

Pomeranz, Kenneth.  2003“Facts Are Stubborn Things: A Response to Philip Huang,”  Journal of Asian Studies  62:1 (February, 2003).: 167-181.

Pomeranz, Kenneth. 2006.  “Standards of Living in Rural and Urban China: Preliminary Estimates for the Mid-18^th and Early 20^th Centuries.”  Paper for Panel 77, World Economic History Congress, Helsinki.

Pomeranz, Kenneth. 2011. “Development with Chinese Characteristics?” Convergence and Divergence in Long-Run and Comparative Perspective.” European University Institute (Florence) Max Weber Programme, Working Paper 2011/06.

 

Pomeranz, Kenneth. 2013. “Skills, Guilds, and Development: Asking Epstein’s Questions to East Asian Institutions,” in Maarten Prak and Jan Luiten van Zanden, eds., Technology, Skills, and the Pre-Modern Economy in the East and West: Essays Dedicated to the Memory of S.R. Epstein  (Leiden: E.J. Brill), pp. 93-127.

 

Rawski, Evelyn.  1972.  Agrarian Change and the Peasant Economy of South China.  Cambridge: MA: Harvard University Press.

 

Xue Yong. 2006. . “Agrarian Urbanization: Social and Economic Changes in Jiangnan from the Eighth to the Nineteenth Century” Yale University Ph. D. dissertation.

Yang Guozhen, Ming Qing tudi qiyue yanjiu  (Research on land contracts in the Ming and Qing)  Beijing: Renmin chubanshe, 1988,

Zhang Peiguo. 2002.   Jindai Jiangnan xiangcun diquan de lishi renleixue yanjiu. (A Historical Anthropology of Rural Village Land Rights in Jiangnan.)  Shanghai: Renmin chubanshe.

 

 

 

 

 

 

[1] See Benedict 2011:49, lending cautious support to my conjecture that tobacco acreage stagnated or declined between the late 18^th and early 20^th centuries, greatly reducing per capita output (and thus allowing us to use early 20^th century figures to conservatively approximate 18^th century consumption).  Thomas Rawski has suggested that we could approach this issue more rigorously if we found a long run of tobacco prices to compare with those for grain: something which hasn’t happened yet, but is certainly possible.

[2] See Pomeranz 2000:36-40,Pomeranz 2002, and Pomeranz 2003.. See also Lee, Campbell and Wang 2002. More recent work on height, longevity, etc., is largely restricted to the 19^th and 20^th centuries, and has little to say about the Yangzi Delta in particular, but tends to suggest that the parts of China that are represented in the data were at or above the middle of a European distribution in the early 19^th century.  See for instance Morgan 2004; Baten et. al. 2010..

[3] This effect is partly the result of the choice of data discussed here, but it is also partly the result of the fact that the data for 1600 and 1829 include estimates from Li Bozhong, who tends to be optimistic in his view of Delta conditions, while the section of the table for 1750 does not; at the same time, Philip Huang, the most pessimistic of the scholars in this debate, is cited in the 1750 section of the table, but not in the other two.

[4]For a recent overview that takes a relatively dour view of the late Ming (though it does accept that it represented a very significant recovery from ehat it considers a catastrophic early and mid-Ming), see Liu 2015.

[5] Pomeranz 2002, 2003.

[6] I made an extremely quick and crude attempt in Pomeranz 2003.  An earlier and partial attempt is Chang 1955.

The Data We Have vs. the Data We Need: A Comment on the State of the “Divergence” Debate (Part I)

How Well Did Facts Travel to Support Protracted Debate on the History of the Great Divergence between Western Europe and Imperial China?

By: Kent Deng (London School of Economics), Patrick O’Brien (London School of Economics)

Abstract: This paper tackles the issue of how reliable the currently circulated ‘facts’ really are regarding the ‘Great Divergence’ debate. Our findings indicate strongly that ‘facts’ of premodern China are often of low quality and fragmented. Consequently, the application of these ‘facts’ can be misleading and harmful.

URL: http://econpapers.repec.org/paper/pramprapa/77276.htm

Distributed by NEP-HIS on: 2017-03-19

Review by: Kenneth Pomeranz (University of Chicago)

Kent Deng and Patrick O’Brien have done us all a service by taking a step back from the conclusions drawn by different participants in the so-called “great divergence debate” to focus  on the types and quality of our data, and on some conceptual problems with the application of modern measurements such as GDP to economies that were radically different from ours – in part because they were incompletely monetized.  I find myself agreeing with most of their criticisms of both GDP and real wage comparisons, and have some of my own to add. Not surprisingly, then, I share their preference for research on comparative consumption – which was a big part of my approach in The Great Divergence – and agree that this is where we have the best prospects for making further progress on these issues.  But I am not as ready as they seem to be to completely discard approaches based on GDP or real wage estimates; and perhaps more importantly, I would significantly modify their assessment of where our discussion of consumption and popular living standards currently stands.

We are, quite simply, unlikely to find any data that is good enough to lay these disputes  to rest.  I agree that the chances of finding significantly better consumption data are higher than are our chances of finding everything we would need to construct truly persuasive GDP estimates, and that the problems with treating wages as representative of living standards in a society like 18^th century China are quite severe,  even if we could resolve the more narrowly empirical problems with the wage data themselves (e.g. unstated but significant in-kind components, differences in the currencies in which Chinese wages and prices are often quoted, uncertainty about the length of the “day” in day wages, and so on).  But at the moment, the consumption data also have significant problems; so while this may well be where we want to concentrate future research efforts, that  does not mean that this is the only metric we should be tracking as we make our best guesses about the current state of this controversy.  (We could, of course, theoretically all agree not to comment on this controversy until we  know more, but that seems unrealistic, given how many other issues it touches upon.)   So I would be inclined to keep the wage data, and even the GDP estimates, in play in this discussion, even though I share Deng and O’Brien’s sense that the consumption data are stronger (and even though those data are more favorable to the position I took in my 2000 book).  Let me briefly review each of these areas.

 

Comparative GDP Estimates

 

I would not disagree with Deng and O’Brien’s critique of the GDP approach, or of Maddison’s figures in particular: the latter were based on far too narrow an evidentiary base for much of the world and much of history.  I think, however, it is worth noting that there have been some more recent attempts to estimate GDPs, which have the advantage both of somewhat better data and of attempting to construct GDP figures for the Yangzi Delta, rather than for China. Given the points that some of us have made repeatedly about the vastly different scales of China and any single European nation, and about the advantages of comparing the most developed region of a continent-sized China with the richest regions of Europe rather than insisting on national units, these numbers seem to be worth at least some attention.
For instance, a recent paper by Stephen Broadberry, Hanhui Guan and David Daokui Li suggests that Britain must have overtaken the Yangzi Delta in per capita GDP by the first quarter of the 18^th century.^[1]  This is, of course, materially different from my claim in The Great Divergence that the Yangzi Delta had not fallen significantly behind until well into the second half of the 18^th century, and maybe not until 1800 (though my conclusions were based on estimates of consumption, longevity, and basic human well-being, rather than GDP).  Nor has this paper found a way around all the problems with historical GDP and comparisons between very different societies to which Deng and O’Brien have pointed.(These include the radically different market baskets of these two societies, which had relatively little trade between them, the very different degree to which the government tracked various kinds of production, and others; to which I would add, large differences in the degree to which various goods and services passed through the market.)  Still, I would not want to simply discard such work, given the difficulties that dog other approaches. Moreover, I think it is noteworthy that a debate between an early and a late 18^th century divergence represents a considerably different intellectual landscape than the one we would have if we relied on Maddison’s GDP numbers,^[2] or on the non-quantitative work of David Landes, Deepak Lal, and various others – or for that matter, on an earlier attempt by Guan and Li to estimate comparative GDPs, which had previously claimed that a huge gap already existed in the 15^th century.^[3]  An earlier paper by Debin Ma suggested that the per capita GDP of the Lower Yangzi  — which he defines slightly more broadly than I do, so that it includes some poorer areas – probably exceeded that of China in general by about 50% in 1750:^[4] such an adjustment, patched onto Maddison’s data, would leave the Delta behind Britain, but by considerably less (in percentage terms) than, say, Germany lags Norway today, or the U.S. lags Luxembourg (when nobody argues that this makes either Germany or the U.S. a “backward” economy fundamentally different from the “advanced” ones, as we used to think China was relative to early modern Europe.). Similarly, a study by Li and Van Zanden, based on data for the 1820s, finds Holland well ahead of two counties in the Delta for which there are particularly good data in those years; but as  they note, the 1820s were a period of both agricultural crisis due to natural disasters and depression in the cloth trade, the second biggest sector of that region.  They suggest that if we had data for 1800, it would show a smaller gap, but still a significant one, with Holland perhaps 50 or even 70% higher in per capita GDP.^[5] Admittedly, that is far from the rough parity I had originally suggested at 1800, and would now be inclined to put at somewhere around 1750 instead; there are some plausible adjustments that I think would narrow the gap further, but that is not really the point for now.  Instead I would emphasize that despite continuing disagreements and continuing data problems – the latter of which will probably never be fully solved – we have made some progress in narrowing the range of plausible answers about when and how much divergence occurred in these terms.  Even if GDP is a seriously flawed measure for purposes of this debate, I am not sure we want to throw it out entirely.

Real Wage Comparisons

The wage data is similarly vexed, and Deng and O’Brien have, I think, explained very convincingly some reasons for skepticism.  But let me add two more, extend the discussion of another, and suggest a possible implication of how we might read this imperfect data in conjunction with the even more imperfect GDP data.

The first additional cause for skepticism in Robert Allen’s own reconstruction of real wages based on prices and wages recorded by the supercargo of an East India Company ship docked in Guangzhou during the trading season of 1704.  Using the same basic approach as he and his co-authors use on the larger data set they compiled a bit later, Allen arrives at the conclusion that the real wages here were roughly equal to those in London at the same time – and Guangzhou, it is generally agreed, was not quite as wealthy as the Yangzi Delta.  (Allen 2004).  Let me make clear that I am not saying that these data give the correct picture,  and the other data a false one: there are certainly reasons why the Guangzhou data could be unrepresentative.^[6] But these are at least prices and wages that we know were actually paid by individuals in private markets, and that should be relatively free of unreported in-kind benefits.  (Chinese workers would certainly not have lived on a British ship, and are unlikely to have eaten British food.) By contrast, the Chinese data in the later and better-known 5 author paper on early modern wages around the world are from administrative reports of prevailing wages, with no evidence that the reporters actually made any sort of survey, and no data at all on in-kind compensation.  I would thus not be quick to throw out the Guangzhou material just because it is a smaller database – and that it gives a figure which is so much higher than those derived from the other data seems lke a good reason to doubt the data overall.  There is also something highly suspicious about the lack of difference between the wage rates for different parts of China in the administrative data, when every qualitative source we know of agrees that there were very large regional differences in material living standards.  Again, this is not sufficient reason to discard these data when we have so few; on the contrary, they represent the best large-scale data set that we have, and the authors have used them to make interesting claims.  But I think we need to be very careful about how we use them for this particular debate.

It is crucial that most Chinese did not rely on wages for their income – as O’Brien and Deng note.  But we also know quite a bit about  the likely relationship between these wages and peasant earnings.  All our evidence suggests that tenant farmers earned a great deal more than agricultural laborers, even if the latter were able to find year-round employment. This conclusion is confirmed whether we look at estimates of money earnings, convert wages into cash and compare to farm yields net of rent and other expenses, or consider key social indicators – including the especially lowly status of wage laborers, and the fact that most tenants were able to marry and raise families, and most agricultural laborers could not.^[7]  And in a society without strong guilds or unions, there is no reason to think that unskilled wages in town would be much higher than in the countryside.  (This would be particularly true in the Yangzi Delta, where towns were very densely distributed across the map, so that almost any rural resident could bid for an unskilled job in a town without going very far.^[8] )  Indeed, in the admittedly limited data we have, the difference between the earnings of a farmer with an average-sized tenancy and a wage laborer are on the order of 2.5 – 3.0:1.  Under the circumstances, wages are a very poor guide to popular living standards: and comparing them to wages in England or Holland, where proletarians made up a large portion of the labor force by the 18^th and especially the 19^th century, represents a comparison between the bottom of the income distribution in one place and something approaching to middle in the other. ^[9]

But even if these wages do not tell us much about comparative living standards, they might nonetheless tell us something about trends in comparative labor productivity. Significantly, estimates of rural incomes and rural labor productivity suggest that the Yangzi Delta was still on a par with England and Holland on these measures even as late as the 1820s.^[10] This would place it far above the rest of Europe – including, of course, a number of countries that began mechanized industrialization and sustained per capita growth well before China did.^[11]  Delta agriculture was also still well ahead in total factor productivity in agriculture as late as 1820.^[12] When taken together with the evidence already discussed which suggests a relatively late divergence, and therefore a fairly sudden widening of the gap once it manifested itself  – since nobody doubts that it was quite large by the mid-19^th century – this would at least suggest that we should not probably be looking at agriculture to explain the divergence.  It also suggests, as Robert Allen has argued in his discussion of British industrialization, that it was higher wages in the growing urban sector that pulled up rural wages, necessitating labor-saving innovations in agriculture, rather than agriculture creating an enlarged urban work force by shedding workers on its own.^[13]  It does not appear that urban demand exerted a comparably strong effect on rural Chinese wages, even though the barriers to rural-urban migration – whether in the form of exclusionary institutions or urban dis-amenities – were comparatively weak in Qing times;^[14] instead, the most likely reason not to leave was that, as noted above, most rural people earned far more than unskilled wage laborers in either city or countryside, and nothing was pushing up urban wages fast enough to overcome this disincentive.  A significant gap in urban real wages – if confirmed by further studies that can more fully overcome the problems described by Deng and O’Brien – might then be significant not as a sign of a difference in living standards that already existed, but as a sign of urban changes in Europe that were beginning to create such differences.

(to be continued…)

Notes

[1] Broadberry, Guan and Li 2014..

[2] Maddison 2001: 42, suggesting that Western Europe overtook China ca. 1300.

[3] Guan and Li  had previously argued (2010) that China was far behind by the 15^th century, if not earlier, and had fallen even further behind over the succeeding centuries. See also Landes 1998, Lal 1998.

[4] Ma 2004. Compare Maddison 2003: 262.for an interpellated UK figure.

[5] Li and Van Zanden 2012:973,

[6] It is true, for  instance, that not every Chinese worker in Guangzhou was able to offer his services to the  foreigners who docked there, perhaps reducing competition and driving up wages.  Bt quite a few could – numerous memoirs from foreigners who visited Guangzhou in this period speak about foreigners being besieged by crowds of potential porters and other service providers. Nor is it clear why any restrictions would have driven up the price of labor more than it did that of the many kinds of provisions for which Lockyer records prices paid, and which Allen uses to create the denominator of his real wage.

[7] I review some of this data in Pomeranz 2006, and Pomeranz 2011. On the strength of tenant rights, which helped make this income differential durable, see  for instance Rawski 1972 Li Wenzhi and Jiang Taixin 2005;Yang Guozhen 1988; Zhang Peiguo 2002.

[8] On the distribution of towns across space see Xue Yong 206: 319, and 302-346, 432-475 for a discussion of various estimates of urbanization in the Yangzi Delta more generally.

[9] Pomeranz 2011.

[10] Allen 2009b; Li and Van Zanden 2012.

[11] For intra-European comparisons, see Allen 2000..

[12] Li and Van Zanden 2012:975; Allen 2009b.

[13] Allen 2009a.

[14] On Chinese guilds in this period, see Moll-Murata 2009, Pomeranz 2013. Though our data is thus far inconclusive, China does not appear to have had a pronounced “urban graveyard effect” – that is clear evidence of worse health and higher mortality in cities, providing a disincentive to migration that had to be overcome by significant wage differentials, as was the case in early modern and industrializing Europe.