| Abstract | Rural worker is a special Chinese terminology which refers to agricultural labors whose Hukou (Hukou is identification to control population migration) are in rural area but migrant to cities for nonagricultural jobs. This group of people has emerged due to the economic transition in China in early 1980s. It was estimated that in 2016 the total amount of rural workers in Chia is about 200million, which is 1.5% increased than last year (The Survey for Rural Workers, National Bureau of Statistics of China, 2015). Rural workers’ economic behavior have significant impact on China’s society and economic restructure, which is the focus of the policy maker.
This study conducts an in-site artefactual multiple price list (MPL) experiment in Szechwan and Henan provinces in China, which elicits rural workers’ risk attitudes. Based on the experimental data, we investigate the difference in risk attitude between generations and provinces. We construct the structural choice model and provide the maximum likelihood estimates of CRRA and CARA risk coefficients. We also evaluate the effect of a set of demographic factors on the risk attitude. Using the predicted risk coefficient as explanatory variable, we evaluate how heterogeneous risk attitudes affect rural workers decisions such as insurance purchase and job training participation.
The central of this study is comprised by extensive home visiting to over 330 rural households in rural China started from July, 2016 to May, 2017 in cities of Chengdu and Meishan in Sichuan Province and cities of Anyang, Jiaozuo, Zhengzhou and Zhumadian in Henan province. In total the experimental data is 330 which is comprised of eight towns in Sichuan province and ten towns in Henan provinces. The face-to-face interview include questions about growers’ detailed demographic information and a stylized multiple price list (MPL) game. Data shows that most experimental participators are male, household heads and have low education attainment. Most the participators take off farm job within the province and the average time of working is 8 years.
This study belongs to the strand of experimental economic literature which quantify the effect of individual risk attitudes on social-economic behaviors in rural and developing communities, such as Brick et al.(2011), Menapace, Colson & Raffaelli (2012), Galarza (2009), Hansen, Jacobsen &Lau (2016), Carlsson et al. (2013) and Liu (2013). In line with this research genre, this study utilizes in-site MPL experiment combined with in-depth survey to rural workers in China and examines the impacts of individual risk attitudes on individual economics behaviors such as insurance purchase. Results indicate Chinese rural workers exhibit relatively high degree of risk aversion. The CRRA risk coefficient estimate is 0.88, which is comparable to estimates in studies utilizing similar experimental methods such as Bricks, Visser and Burns (2011) (South Africa), Harrison et al. (2010) (Ethiopia, India and Uganda) and Galarza (2009) (Peru), Harrison et al. (2007) (Denmark). In addition, results indicate that the degree of risk aversion decreases with education level. The risk attitudes distribution are different between different generations, but there is no significant evidence for difference of risk attitude distribution between provinces. By using the predicted individual risk coefficients as explanatory variable, this study finds that the likelihood of insurance purchase increases in risk aversion, but the likelihood of training participation decreases in risk aversion. In addition, growers who are more risk-averse have a smaller social network.
The study adds to existing literature by first investigating the risk attitudes of Chinese rural workers. The methodology presents the expected utility theory of lottery choice decision as well as the structural choice model for empirical estimation. This paper also first empirically estimats the CRRA and CARA risk coefficient and makes comparison to the international evidences. This study provides a new angle to analyze Chinese rural workers’ economic behaviors.
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