Risk Preferences Around the World

Abstract

We present results from a large-scale international survey on risk preferences conducted in 53 countries. In all countries, we find, on average, an attitude of risk aversion in gains and of risk seeking in losses. The degree of risk aversion shows significant cross-country differences. Moreover, risk attitudes in our sample depend not only on economic conditions but also on cultural factors, as measured by the Hofstede dimensions individualism and uncertainty avoidance. The data may also serve as an interesting starting point for further research on cultural differences in behavioral economics. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2013.1869 . This paper was accepted by Peter Wakker, decision analysis.

Cash Holdings and Financing Decisions Under Ambiguity

“…The average ambiguity aversion across these countries is provided by Rieger, Wang and Hens (2014) and is mapped into the parameter c. We found a positive correlation (0.566) between leverage and ambiguity bias (see Figure 6), which is consistent with our results. …”

“…Recent work by Rieger, Wang and Hens (2014) employs a methodology to measure the average ambiguity aversion across different countries, and this methodology might be adapted to our framework in order to estimate the level of the ambiguity aversion.…”

Stake effects on ambiguity attitudes for gains and losses

“…Indeed, the stake effects on risk we found correspond closely to effects obtained in China (Fehr-Duda et al 2010), India (Binswanger 1980), the US (Holt and Laury 2002), France (Lefebvre et al 2010), and the UK (Bouchouicha and Vieider 2016). Given that absolute risk attitudes between these countries have been found to differ (Rieger et al 2014;L'Haridon and Vieider 2016), while stake effects on risk attitudes were (qualitatively) the same, we believe that our results on stake effects will generalize to different countries.…”

Value-at-risk under ambiguity aversion

“…The incorporation of ambiguity was achieved by building on the method developed by Lapied (2010a, 2010b), which is theoretically founded and, at the same time, parsimonious enough to be easily calibrated to real-world data (see So 2017). However, as Agliardi et al (2016) showed, the model relevant parameter can be mapped to a measure of average ambiguity aversion as proposed in Rieger et al (2015), which provides a convincing proxy for ambiguity aversion bias.…”