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The influence of spouses on household decision making under risk: an experiment in rural China

Abstract

We study household decision making in a high-stakes experiment with a random sample of households in rural China. Spouses have to choose between risky lotteries, first separately and then jointly. We find that spouses’ individual risk preferences are more similar the richer the household and the higher the wife’s relative income contribution. A couple’s joint decision is typically very similar to the husband’s preferences, but women who contribute relatively more to the household income, women in high-income households, and women with communist party membership have a stronger influence on the joint decision.

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Notes

  1. The experiment of Ashraf (2009) was also run in a developing country (the Philippines). She showed that financial decisions of spouses are influenced by whether the (experimental) income is known to the other spouse and whether spouses communicate about how to spend the experimental earnings before making a final decision on how to use them. Hence, the focus of Ashraf’s (2009) study is clearly different from ours.

  2. Kachelmeier and Shehata (1992) also ran a high-stakes experiment on risky decision making in China. They focused on the question of how the level of incentives affects revealed risk preferences. The experiment was run with students from Peking University, and is thus unrelated to household decision making. Tanaka et al. (2010) studied individual risk and time preferences in households in Vietnam, but were not interested in the joint decisions of couples and their determinants.

  3. For instance, Baker et al. (2008) and Masclet et al. (2009) report that groups are more risk averse in lottery choices than individuals, while Harrison et al. (2005) find no significant difference between individuals and groups, and Zhang and Casari (2011) find that groups are less risk averse than individuals. Shupp and Williams (2008) seem to offer some reconciliatory evidence by reporting that the average group is more risk averse than the average individual in high-risk situations, but groups tend to be less risk averse in low-risk situations. There is also research investigating whether (randomly formed) groups violate expected utility theory to the same degree as individuals do (e.g., Bone 1998: Bone et al. 1999, 2004, Rockenbach et al. 2007). While no clear-cut bottom line has resulted from this strand of literature, it seems fair to conclude that groups are not considerably better in avoiding violations of axioms of rationality than individuals.

  4. 1 US Dollar corresponded to 7.42 Chinese Yuan at the time of running the experiment (November 2007).

  5. In order to prevent villagers from spreading the word about the experiment within a village, we employed 20 interviewers. All interviewers were selected and their training was supervised by one of the authors, a native Chinese. Among the 20 interviewers, 12 were recruited from a local university, Guizhou University. They were able to understand and speak local village dialects, and one of them was present in each pair of interviewers. Three of the interviewers had worked in a similar risk experiment project before and were therefore chosen to give a two hour-training lecture for all other interviewers. After this lecture, two of them came to a stage to simulate an experiment and how it should be conducted (e.g., how to explain the experimental task, how to respond to questions and which questions interviewers should expect). Then all other interviewers had to come to the stage as well and simulate a real experiment. Those who made mistakes (such as, e.g., being unclear or suggestive) received more training until they could properly conduct the experiment.

  6. This happened in around 20 cases, probably because some households were engaged in the rice harvest at that time.

  7. The regional average in Majiang is around 3,500 Yuan (according to information from local cadres).

  8. This fraction is higher than the national average party membership of about 6 %, however there is significant volatility of party membership, which is often heavily influenced by local traditions (Guo and Bernstein 2004).

  9. The experiment also included two stages on the elicitation of time preferences. They are analyzed separately in a companion paper (see Carlsson et al. 2012), for which reason we do not report these data here.

  10. Note that we randomly reshuffled the pairs of experimenters each day in the field to avoid any experimenter effects. Furthermore, we balanced the genders of the two experimenters in each household and instructed the experimenters to switch back and forth between interviewing the wife and interviewing the husband when moving from one household to the next.

  11. Note that the fraction of inconsistent choices ranged from 5 % to 13 % in Holt and Laury (2002), depending upon treatment. Between 9 % and 23 % of all choices were inconsistent in de Palma et al. (2011). In Bateman and Munro (2005), 6 % of the participants chose strictly dominated options. It is also noteworthy that in our experiment making decisions as a couple did not affect the rate of consistent choices, most likely because individual consistency rates are already at a high level.

  12. When the high payoff from the safe (risky) option was 100 USD (192.50 USD), 15 % of all subjects in Holt and Laury (2002) chose the safe option nine times and only shifted to the risky option in the final, tenth choice (when there is no longer risk involved). In their treatment with very high stakes—with the high payoff in the safe (risky) option yielding 180 USD (346.50 USD)—Holt and Laury (2002) observed that even 40 % of their subjects chose the safe option nine times.

  13. All tests reported in the paper are double-sided unless otherwise stated.

  14. There are also a number of variables that we do not have information about that could explain differences in risk attitudes, such as height and subjective health.

  15. We did some robustness checks in which we included all inconsistent choices (by assigning the median switching point between the first and the last time a subject switched as an inconsistent subject’s switching point). The results presented in Sect. 4 are robust to such an approach. In order to be conservative (and because it is not unambiguous how to extract a switching point from inconsistent choices) we report in the paper only data for consistent choices.

  16. The dependent variable is between zero and nine, since the maximum difference in the number of safe choices is nine.

  17. A model by Mazzocco (2004) can explain how differences in the spouses’ individual risk attitudes can lead to more extreme choices of the household than those made by either of the spouses. Hence, couples that make more extreme decisions than either spouse individually can not simply be dismissed as having made a mistake. A paper by Eliaz et al. (2006) also shows that decisions in groups (like families) can lead to choice shifts that yield more extreme outcomes than the decisions of individual group members.

  18. Given the discrete choice set, it is clear that with an odd difference in the number of safe choices between the husband and the wife, category (c) is not feasible. When applying the χ 2 test, we therefore correct for the possibility of different probabilities of the five possible categories.

  19. We also estimated a model with years of marriage replaced by age of females since there is high correlation between age of females and length of marriage, but results remain robust to such a change.

  20. Using model II yields similar results.

  21. We also ran a third model (an ordered probit like model I) in which we transformed the number of safe choices into ranges of relative risk aversion r for the utility function U(x)=x 1−r(1−r) of monetary payoff x (see Holt and Laury 2002, for more details on the transformation) and then defined the dependent variable as the couple’s joint relative risk aversion being (1) closer to the husband’s relative risk aversion, (2) equally distant from both spouses’ relative risk aversion, or (3) closer to the wife’s relative risk aversion. The results of such a specification remain qualitatively (with respect to signs and significances) identical to model I.

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Correspondence to Matthias Sutter.

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We have received valuable comments from four anonymous referees, the editor (Jordi Brandts), and Francisco Alpizar, Dinky Daruvala, Jintao Xu, and seminar participants at the University of Gothenburg. Financial support from Sida to the Environmental Economics Unit at the University of Gothenburg is gratefully acknowledged.

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Carlsson, F., Martinsson, P., Qin, P. et al. The influence of spouses on household decision making under risk: an experiment in rural China. Exp Econ 16, 383–401 (2013). https://doi.org/10.1007/s10683-012-9343-7

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  • DOI: https://doi.org/10.1007/s10683-012-9343-7

Keywords

  • Household decision making
  • Risk
  • Experiment in the field
  • China

JEL Classification

  • C91
  • C92
  • C93
  • D10