Three parts natural, seven parts man-made: Bayesian analysis of China’s Great Leap Forward demographic disaster (original) (raw)

Elsevier

Journal of Economic Behavior & Organization

Abstract

The millions of deaths that occurred during China’s great famine of 1959–1961 were the result of one of the world’s greatest civil demographic disasters. Two primary hypotheses have been advanced to explain the famine. One is that China experienced three consecutive years of bad weather while the other is that national policies were wrong in that they reduced and misallocated agricultural production. The relative importance of these two factors to the famine remains controversial among China scholars. This paper uses provincial-level demographic panel data and a Bayesian empirical approach in an effort to distinguish the relative importance of weather and national policy on China’s great demographic disaster. Consistent with the qualitative literature in this area, we find that national policy played an overall more important role in the famine than weather. However, we provide new quantitative evidence that weather was also an important factor, particularly in those provinces that experienced excessively wet conditions.

Introduction

The millions of excess deaths and lost births that occurred during China’s great famine of 1959–1961 were the result of one of the world’s greatest civil demographic disasters. Two primary hypotheses have been advanced to explain the famine. One is that China experienced three consecutive years of bad weather while the other is that national policies reduced and misallocated agricultural production (see, e.g., Yao, 1999 and Lin, 1985 for recent defenses of the respective hypotheses). The relative importance of these two factors to the famine remains widely discussed and, due to an extreme paucity of period data, highly controversial among China scholars. This paper complements existing qualitative literature by using provincial-level demographic panel data and a Bayesian empirical approach to provide new evidence on the relative importance of weather and national policy on China’s great famine.

The national policies in place during the famine of 1959–1961 were those of the “Great Leap Forward” (1958–1961) with their goal of achieving dramatic national economic growth.2 Policy campaigns advocated such wholesale economic changes as communal organization of rural labor, regional self-sufficiencies, and dual track (small- and large-scale) industrial investment and production. In China’s agricultural areas, these policies translated specifically into the formation of rural people’s communes, massive earth-working labor organizations, adoption of unorthodox cropping techniques, and accelerated “backyard steel” production campaigns. Altogether, these policies have been criticized for introducing overly aggressive grain procurement policies, ill-advised movements of labor out of agriculture, and poorly structured incentive systems that discouraged agricultural production. Moreover, in the Fall of 1958 Chairman Mao suspended the right of peasants to withdraw from their collectives. Lin argues that this particular national policy and the incentive effects it generated account for most of the agricultural crisis. The national policy hypothesis is that China was, during the famine period, a very misguided centrally planned economy: China’s government leaders promulgated a series of poorly conceived policies that regional bureaucrats implemented and that caused national famine and, consequently, extraordinary population losses.3

The weather hypothesis is that the years 1959–1961 were years of extremely bad weather that led to dramatic crop failures. This hypothesis was put forth very early by Chinese government officials as an explanation for the famine (Communist Party of China, 1981). Since that time, weather has also been suggested by several scholars as an important source of the famine.4 In a careful recent study, Yao concludes that “[weather] should explain a large proportion of the total loss of grain production in [1959–1961]” (p. 1367).

Our aim in this paper is to shed further light on the importance of weather in relation to national policy in the 1959–1961 famine. The approach we take is related to recent work by Lin and Yang (2000) that distinguishes the relative impact of national per-capita food availability and urban protection programs on the famine. As in that study, our empirical analysis is based on a panel of mortality rates at the provincial-level. The reason is that a province’s excess deaths (those above the “normal” level) are known to be closely tied to a province’s actual food availability (the amount of their grain output to which they were entitled) during famine periods (see, e.g., Bongaarts and Cain, 1982, Sen, 1981). While we would prefer to include detailed data on grain production and grain movements across regions in our analysis, no such data exist. On the other hand, demographic data for the famine period are well trusted, have been constructed by several different scholars, and are relatively clean and complete even at the level of the province.

National policy effects were quite heterogeneous across provinces. Reasons for this include “urban bias” (Lin and Yang, 2000), and the fact that some provinces were extremely radical in their support for central policies while others were more cautious (Teiwes, 1979, Teiwes, 1993). Such differences in local bureaucracies might have resulted in different implementations and consequences of national Leap policies. At the same time, others have suggested that certain policies in place at this time did have broad and fairly homogeneous effects. For example, the peasants’ loss of their right to exit cooperatives applied throughout China and affected agricultural productivity in most provinces in a similar way.

This research models a province’s mortality rate during the great famine as driven by three factors: (1) central policies common to all provinces, (2) the unique response of a province to that central policy, and (3) a province’s weather conditions. Our approach is to specify a model of provincial mortality rates that subsumes these three effects and then to take this model to annual mortality data that covers the years 1955–1965 for 28 of China’s 29 major provinces and large cities (we exclude Tibet). We then perform Bayesian inference using Markov Chain–Monte Carlo (MCMC) techniques.

We find that national policy accounted for most of the excess deaths during the famine period and that there was substantial heterogeneity in its effect among regions. Moreover, our analysis provides new quantitative evidence on weather effects during the Leap period. Some have cast doubt on the importance of drought to the famine, particularly because engine-powered irrigation was increasingly common during that period (see, e.g., Lin, 1990, p. 1236). Others, however, have pointed out that many of China’s provinces experienced unusually severe typhoons and flooding during the Leap period, arguing that this led to significant crop failures (see, e.g., Chen, 2004). In fact, the regions we estimate to have been most adversely affected by weather are generally those that experienced unusually wet conditions.

Overall, we find that about 70% of all excess deaths can be tied to national policy effects. This result reflects a well-known view expressed by Chinese peasants of Hunan during their 1961 conversation with Liu Shaoqi, who was at the time a high leader of the People’s Republic of China. The peasants reported, “The great disaster was three parts natural, and seven parts man-made” (Liu, 1985).

Section snippets

Motivation

The primary hypotheses put forth to explain the 1959–1961 famine in China are that it was due to (1) the centralized policies adopted by China’s planners, (2) the way in which the provincial authorities implemented the central policies, and (3) “natural” causes, in particular bad weather. The fact that detailed weather and policy data are unavailable for this period has made it difficult to resolve the relative roles of these effects on the famine. However, since it seems widely accepted that

The data

The data used in our analysis are drawn from a set constructed from Chinese sources by the second author and described in detail in Sands and Buelow (1997). These same data were used by Peng (1987) and Lin and Yang (2000) in their Leap investigations. The data set includes annual crude birth rates, crude death rates, and net migration rates for 28 of China’s 29 provinces and major cities (Tibet is excluded for lack of data) and covers the years beginning in 1955 and ending in 1982. Our research

Results

We coded our Gibbs sampler in FORTRAN 90 and made extensive use of IMSL subroutines. We implemented the algorithm on a Pentium II 300

MHz workstation. We ran the Gibbs sampler for 40,000 cycles. A complete 40,000 cycle run took about 5

min of processor time. Inspection of the draw sequences satisfied us that the sampler had converged by cycle 20,000. Our findings are based on the sampler’s last 20,000 cycles. The FORTRAN software that we used and the complete draw sequences are available from the

Conclusion

This paper presented a first attempt to quantify the relative influences of national policy and weather on the deadly famine that occurred in China during the Great Leap Forward period. Our study was based on annual crude death rate data from 28 Chinese provinces over the years from 1955 to 1965. We adopted a parametric statistical approach and used Bayesian techniques to draw inferences about our models’ parameters. Although our analysis required several strong assumptions, we provided

Acknowledgements

We thank David Grether for his leadership, especially with respect to the standard he sets for careful and rigorous analysis of data. This paper benefited from the comments of Bob Cull and David Porter, as well as seminar participants at the University of Arizona, Georgia State University and George Mason University. A Gloria Olsen IFREE fellowship to the first author supported this research.

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For instance, the death rate in 1959 ranged from 6.9 per thousand people in Shanghai to 47 per thousand people in Sichuan province Table A3. The province-level heterogeneity is largely attributed to different extents of radicalism of provincial leaders in the implementation of the national policies during the leap period (Bramall, 2011; Houser et al., 2009). In our empirical strategy, we account for these regional differences.

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This tragic period is known as the Great Chinese Famine. Already, researchers have established that specific agricultural policies initiated by the GLF created some of the famine conditions (Bernstein, 1984; Chang and Wen, 1997; 1998; Fan et al., 2016; Houser et al., 2009; Jones and Poleman, 1962; Kung and Lin, 2003; Li and Yang, 2005; Lin, 1990; Lin and Yang, 2000; Liu, 2010b; 2010a; Liu et al., 2014; Meng et al., 2015; Yang, 1996; 2008). Additionally, political incentives facing top bureaucrats at the time have been shown to have driven the radical implementation of the GLF policies (Kung and Chen, 2011; Yang and Su, 1998; Yang et al., 2014).

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Examining the causal legacy of the Great Famine on economic disparities in China joins a growing literature linking historical events with current day economic performance, showing that history matters in understanding the contemporary development landscape (Acemoglu, Johnson, & Robinson, 2001; Banerjee & Iyer, 2005; Dell, 2010; Huillery, 2009; Nunn, 2008, 2009). Additionally, the IV strategy provides support for the critical role that political radicalism played in the severity of Great Famine: accentuating grain procurement and labor mobilization (Kung & Lin, 2003) and limiting exit rights from communes, among other GLF policies for rapid agricultural modernization (Bernstein, 1984; Houser et al., 2009; Kung & Chen, 2011; Lin, 1990; Lin & Yang, 1998, 2000; Meng et al., 2015; Riskin, 1998; Teiwes & Sun, 1999; Yang, 1996, 2010). The IV estimates that measure politically caused famine on subsequent growth and align directly with current thinking on causes of famine, specifically that famine arises in situations where citizens’ entitlement to food is interrupted (Liu, 2010a, 2010b; Sen, 1981). View all citing articles on Scopus

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