Can the risky investment game predict real world investments?

Arbeitspapier

The incentivized risky investment game has become a popular tool in lab-in-the-field experiments for its simplicity and ease of comprehension compared to some of the more complex Multiple Choice List approaches that have been more commonly used in laboratory experiments. We use a field experiment to test whether the game can predict real world investments by the same subjects based on the assumption that the game can provide a reliable measure of risk tolerance and that risk tolerance is an important predictor of investment behavior. The results show that the game cannot predict investment behavior in our sample. There are two reasons for this. First, we find substantial measurement error and low correlation when the game is repeated one year later for the same subjects. Measurement error is so large in our sample that the "obviously related instrumental variable" (ORIV) approach of Gillen, Snowberg and Yariv (2019) could not remedy the problem. Second, the game appears to suffer from low asset integration due to narrow bracketing, explaining its limited predictive power and the failure to detect attenuation bias due to measurement error. Subjects'cognitive memory of the game played one year earlier is strongly positively related to investment intensity in the game and this result is much enhanced when correcting for the endogeneity of cognitive memory

Object Details

• ISBN: 978-82-7490-302-9
• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Centre for Land Tenure Studies Working Paper ; No. 05/22

Classification and Topics

• Classification: Wirtschaft ; Field Experiments ; Design of Experiments: General
• Subject: risky investment game ; field experiment ; prediction ; measurement error ; cognitive memory ; Ethiopia

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Holden, Stein Terje ; Tilahun, Mesfin
• Event: Veröffentlichung
• (who): Norwegian University of Life Sciences (NMBU), Centre for Land Tenure Studies (CLTS)
• (where): Ås
• (when): 2022

Further information

• Handle: http://hdl.handle.net/10419/262027
• Last update: 10.03.2025, 11:44 AM CET