| Field | Before | After |
|---|---|---|
| Field Trial Status | Before in_development | After on_going |
| Field Abstract | Before This experiment investigates the causal impact of exogenous income shocks on individuals' risk preferences, specifically focusing on higher-order risk attitudes such as prudence and temperance. Building on the theoretical framework of higher-order risk attitudes and motivated by mixed empirical evidence on the effect of shocks on risk behavior, the study employs a between-subjects design that orthogonally varies initial experimental endowments ($20, $60, or $100) and the occurrence of income shocks. Participants, recruited from a nationally representative online panel (Forthright Access), are randomly assigned to one of seven treatment conditions that systematically isolate income shocks from wealth effects. In Stage I, subjects learn about their endowment source; in Stage II, a risky investment task (adapted from Gneezy and Potters, 1997) elicits risk aversion via investment choices under uncertainty; and in Stage III, lottery selection tasks measure both basic risk preferences (following Eckel and Grossman, 2008) and higher-order attitudes (following Noussair et al., 2014). The experiment aims to test whether shock-induced variations in endowment generate distributions of risk preferences that differ from those arising solely from deterministic changes. Additionally, the study examines the interrelationships among risk aversion, prudence, and temperance across treatment conditions. Outcomes from this research will contribute to a clearer understanding of how exogenous shocks affect decision-making under uncertainty and inform both theoretical models and policy designs to mitigate shocks' economic impacts. | After This experiment investigates the causal impact of exogenous income shocks on individuals' risk preferences, specifically focusing on higher-order risk attitudes such as prudence and temperance. Building on the theoretical framework of higher-order risk attitudes and motivated by mixed empirical evidence on the effect of shocks on risk behavior, the study employs a between-subjects design that orthogonally varies initial experimental endowments ($20, $60, or $100) and the occurrence of income shocks. Participants, recruited from a nationally representative online panel (Forthright Access), are randomly assigned to one of seven treatment conditions that systematically isolate income shocks from wealth effects. In Stage I, subjects learn about their endowment source; in Stage II, a risky investment task (adapted from Gneezy and Potters, 1997) elicits risk aversion via investment choices under uncertainty; and in Stage III, lottery selection tasks measure both basic risk preferences (following Eckel and Grossman, 2008) and higher-order attitudes (following Noussair et al., 2014). The experiment aims to test whether shock-induced variations in endowment generate distributions of risk preferences that differ from those arising solely from deterministic changes. Additionally, the study examines the interrelationships among risk aversion, prudence, and temperance across treatment conditions. Outcomes from this research will contribute to a clearer understanding of how exogenous shocks affect decision-making under uncertainty and inform both theoretical models and policy designs to mitigate shocks' economic impacts. Follow-up experiment: In a subsequent within-subjects design, all participants begin with a $60 endowment and complete four rounds of the Investment Game to establish baseline risk preferences. They are then randomly assigned to one of three treatments: (i) WIN, where there is a 50% chance to gain $40 and reach $100; (ii) LOSS, where there is a 50% chance to lose $40 and end with $20; or (iii) Control-$60, where the endowment remains unchanged. Participants then repeat the Investment Game, allowing us to measure within-person changes in investment behavior before and after experiencing an economic shock. The study concludes with the same set of risk-aversion, prudence, and temperance elicitation tasks as the main experiment, enabling direct comparison between within- and between-subjects findings. |
| Field Trial End Date | Before June 21, 2025 | After September 17, 2025 |
| Field Last Published | Before May 14, 2025 01:22 PM | After August 31, 2025 09:59 PM |
| Field Intervention (Public) | Before We use a controlled economic experiment to assess the relationship between shocks and higher-order risk attitudes. Particularly, we study if previous apparent discrepancies are generated by the impossibility of field data separating the effects of the income shocks on wealth from those with risk attitudes. To do so, we propose a between-subjects experiment in which we vary the amount of initial experimental endowments (wealth) that subjects receive and the occurrence or non-occurrence of the shock. To capture these relationships from a broader set of subjects than college students, the experiment is implemented via Forthright Access, an online platform with a representative sample of the U.S. population. To capture whether endowment shocks affect our subjects' decision processes, we record decision times and overinvestment attempts. We exogenously isolate shocks from wealth to assess their independent effect on higher-order risk preferences. We implement an experiment with seven randomly assigned treatments between subjects, as described in Table 1. Table 1. Treatments Endowment\Shock Deterministic Shock $20 Deterministic-$20 Negative Shock-$20 (Negative shock from a 50% chance of a ($20, $60) bundle) $60 Deterministic-$60 Positive Shock-$60 (Positive shock from a 50% chance of a ($20, $60) bundle) Negative Shock-$60 (Negative shock from a 50% chance of a ($60, $100) bundle) $100 Deterministic-$100 Positive Shock-$100 (Positive shock from a 50% chance of a ($60, $100) bundle) | After We use a controlled economic experiment to assess the relationship between shocks and higher-order risk attitudes. Particularly, we study if previous apparent discrepancies are generated by the impossibility of field data separating the effects of the income shocks on wealth from those with risk attitudes. To do so, we propose a between-subjects experiment in which we vary the amount of initial experimental endowments (wealth) that subjects receive and the occurrence or non-occurrence of the shock. To capture these relationships from a broader set of subjects than college students, the experiment is implemented via Forthright Access, an online platform with a representative sample of the U.S. population. To capture whether endowment shocks affect our subjects' decision processes, we record decision times and overinvestment attempts. We exogenously isolate shocks from wealth to assess their independent effect on higher-order risk preferences. We implement an experiment with seven randomly assigned treatments between subjects, as described in Table 1. Table 1. Treatments Endowment\Shock Deterministic Shock $20 Deterministic-$20 Negative Shock-$20 (Negative shock from a 50% chance of a ($20, $60) bundle) $60 Deterministic-$60 Positive Shock-$60 (Positive shock from a 50% chance of a ($20, $60) bundle) Negative Shock-$60 (Negative shock from a 50% chance of a ($60, $100) bundle) $100 Deterministic-$100 Positive Shock-$100 (Positive shock from a 50% chance of a ($60, $100) bundle) To further investigate within-subject changes in risk attitudes following economic shocks, we will conduct a follow-up experiment with new participants recruited through Forthright Access. In Task 1, all participants will begin with a $60 endowment and complete four rounds of the Investment Game (Gneezy & Potters, 1997) to establish baseline risk preferences. In Task 2, participants will be randomly assigned to one of three treatments that determine their post-shock endowment: WIN: 50% probability of keeping $60, 50% probability of gaining $40 (final endowment = $100). LOSS: 50% probability of keeping $60, 50% probability of losing $40 (final endowment = $20). C$60: Guaranteed $60 endowment (control). After the shock assignment, participants will complete four additional rounds of the Investment Game, allowing us to measure within-subject changes in the proportion of the endowment invested in the risky asset. Finally, in Task 3, participants will complete 18 rounds of risk-elicitation tasks (Eckel & Grossman, 2008; Noussair et al., 2012) to measure risk aversion, prudence, and temperance, followed by a brief social preferences questionnaire. |
| Field Intervention End Date | Before June 21, 2025 | After September 17, 2025 |
| Field Primary Outcomes (End Points) | Before 1. Risky Investments Choices 2. Lottery choice 3. Risk Aversion Measure 4. Prudence Measure 5. Temperance Measure | After 1. Risky Investments Choices 2. Lottery choice 3. Risk Aversion Measure 4. Prudence Measure 5. Temperance Measure 6. Change in amount invested before vs. after the shock treatment. |
| Field Primary Outcomes (Explanation) | Before 1. Risky Investment Task (Gneezy and Potters, 1997): The primary outcome is the proportion of the endowment invested in the risky asset, where a higher proportion indicates greater risk tolerance, while a lower proportion shows higher risk aversion. 2. Eckel and Grossman Gamble Task (2008): The primary outcome is the choice of a gamble from six ordered lotteries, where higher numbers indicate lower risk aversion. 3. Risk Aversion Measure (Noussair et al., 2014): Risk aversion will be measured as the number of safe choices made among the five decisions involving a sure payoff and a risky lottery. 4. Prudence Measure (Noussair et al., 2014): Prudence will be measured as the number of prudent choices made among the five decisions for prudence. 5. Temperance Measure (Noussair et al., 2014): Temperance will be measured as the number of temperate choices made among the five decisions for temperance. Following previous literature (Deck & Schlesinger, 2010; Ebert & Wiesen, 2014; Noussair et al., 2014; Xu et al., 2024), the number of risk-averse, prudent, and temperate choices will be interpreted as a measure of the strength of these higher-order risk attitudes. | After 1. Risky Investment Task (Gneezy & Potters, 1997): The proportion of the participant’s endowment invested in the risky asset in each round. A higher proportion indicates greater risk tolerance; a lower proportion indicates greater risk aversion. 2. Lottery Choice (Eckel & Grossman, 2008): Choice of one out of six ordered lotteries, with higher-numbered lotteries corresponding to lower risk aversion. 3. Risk Aversion Measure (Noussair et al., 2014): Number of safe choices (0–5) in paired decisions between a sure payoff and a risky lottery. Higher counts indicate stronger risk aversion. 4. Prudence Measure (Noussair et al., 2014): Number of prudent choices (0–5) in decisions designed to detect a preference for smoothing consumption across uncertain states. 5. Temperance Measure (Noussair et al., 2014): Number of temperate choices (0–5) in decisions designed to detect a preference for reducing exposure to compound risks. 6. Change in Risky Investment Before vs. After Shock Treatment (Experiment 2): The within-subject change (ΔY) in the proportion of the actual endowment invested in the risky asset before and after experiencing the shock (endowment change). This captures how an exogenous gain or loss affects risk-taking behavior in the investment task. Following prior literature (Deck & Schlesinger, 2010; Ebert & Wiesen, 2014; Noussair et al., 2014; Xu et al., 2024), the number of risk-averse, prudent, and temperate choices is interpreted as the strength of the corresponding higher-order risk attitude. |
| Field Experimental Design (Public) | Before We use a controlled economic experiment to assess the relationship between shocks and higher-order risk attitudes. We study whether previous apparent discrepancies are generated by the impossibility of field data separating the effects of income shocks on wealth from those with risk attitudes. To do so, we propose a between-subjects experiment in which we vary the amount of initial experimental endowments (wealth) that subjects receive and the occurrence or not of the shock. There is a 10% chance of receiving a payment. After completing all tasks, participants will spin a digital roulette to determine if they are selected for payment, with one round randomly chosen to determine their payment. | After We use two controlled online economic experiments to assess the relationship between shocks and higher-order risk attitudes. The first is a between-subjects design, varying both the initial endowment ($20, $60, or $100) and the occurrence or non-occurrence of an economic shock. The second is a within-subjects design in which all participants start with the same initial endowment and are then randomly assigned to experience a positive shock, negative shock, or no shock. This allows us to measure within-subject changes in risky investment and compare across treatment arms to assess the effects of shocks on prudence and temperance. In both experiments, participants have a 10% chance of receiving a payment. After completing all tasks, participants spin a digital roulette to determine if they are selected for payment, with one round randomly chosen to determine their payoff. |
| Field Planned Number of Observations | Before 1,050 individuals | After 1,050 individuals for the between-subjects experiment design. 440 individuals for the within-subjects experiment design. |
| Field Sample size (or number of clusters) by treatment arms | Before 1,050 individuals, 150 subjects per treatment | After 1,050 individuals, 150 subjects per treatment arm 440 individuals, 88 subjects per treatment arm |
| Field Power calculation: Minimum Detectable Effect Size for Main Outcomes | Before Based on power calculations and previous studies (Cohn et al., 2015), which found an effect size of d=0.42, we estimate we will need 100 participants per cell to detect a slightly smaller effect size (d=0.35), considering that our conditions and experimental design differ. Since online participants often fail standard attention checks, we will over-sample to account for dropouts and incomplete session studies. | After For the between-subjects design, based on power calculations and previous studies (Cohn et al., 2015), which found an effect size of d=0.42, we estimate we will need 100 participants per cell to detect a slightly smaller effect size (d=0.35), considering that our conditions and experimental design differ. Since online participants often fail standard attention checks, we will over-sample to account for dropouts and incomplete session studies. For the within-subjects experiment design, a power analysis by simulation indicates that detecting the same effect size as in our previous experiment (Cohen’s d = 0.35) with 80% power requires 66 individuals per treatment arm. In our previous work, approximately 90% of participants were classified as risk-averse; however, for robustness checks restricted to this group, we assume a more conservative proportion of 80%. Based on this assumption, and allowing for potential dropouts or incomplete sessions, we will recruit 88 participants per treatment arm. |
| Field Intervention (Hidden) | Before In Stage I, subjects learn their endowment and the source of it. In Stage II, subjects will perform an investment task for 4 rounds to measure their risk aversion (Gneezy & Potters 1997). This tool has previously been employed to assess risk tolerance for economic shocks (Cohn et al., 2015; Holden & Tilahun, 2021). In this simple risk elicitation task, participants will be asked how much of their initial endowment, based on the random treatment assignment in Stage I ($20, $60, $100), they wish to invest in a risky option and how much to keep. The invested amount yields a dividend of 2.5 or 5.0, depending on the round, with a 50% probability. The decision maker keeps the money not invested. In Stage III, subjects will perform an additional lottery selection task to measure attitudes toward risk (Eckel and Grossman, 2008). More specifically, subjects select a lottery of their preference from six available options (Eckel and Grossman, 2008). Each lottery has the same outcome probabilities but varies the payments of the low and high outcomes. Subsequently, subjects complete 17 binary selection lotteries designed to capture higher-order risk attitudes following Noussair et al. (2014). Table 2 describes the 17 lottery decisions presented in are grouped into four parts: five choices to assess risk aversion by comparing a sure payoff with a risky lottery; five choices to measure prudence, defined as the preference to assign unavoidable risks to higher income states rather than lower ones; five choices to assess temperance, reflecting the preference to spread independent risks across states rather than concentrating them; and two additional choices to test relative risk aversion and prudence under expected utility theory. The choice of the left lottery indicates risk aversion, prudence, and temperance. Left Lottery Right Lottery Risk Aversion 1 20 [65_5] Risk Aversion 2 25 [65_5] Risk Aversion 3 30 [65_5] Risk Aversion 4 35 [65_5] Risk Aversion 5 40 [65_5] Prudence 1 [(90+ [20_-20]) _60] [(90_ (60+ [20_-20])] Prudence 2 [(90+ [10_-10]) _60] [(90_ (60+ [10_-10])] Prudence 3 [(90+ [40_-40]) _60] [(90_ (60+ [40_-40])] Prudence 4 [(135+ [30_-30]) _90] [(135_ (90+ [30_-30])] Prudence 5 [(65+ [20_-20]) _35] [(65_ (35+ [20_-20])] Temperance 1 [(90+ [30_-30]) _ (90+ [30_-30])] [(90_ (90+ [30_-30] + [30_-30])] Temperance 2 [(90+ [30_-30]) _ (90+ [10_-10])] [(90_ (90+ [30_-30] + [10_-10])] Temperance 3 [(90+ [30_-30])_(90+[50_-50])] [(90_ (90+ [30_-30] + [50_-50])] Temperance 4 [(30+ [10_-10]) _ (30+ [10_-10])] [(30_ (30+ [10_-10] + [10_-10])] Temperance 5 [(70+ [30_-30]) _ (70+ [30_-30])] [(70_ (70+ [30_-30] + [30_-30])] Ra_EU1 [40_30] [50_24] Prud_EU2 [(50+ [25_-25]) _30] [(50_ (30+ [15_-15])] Finally, participants complete a short questionnaire to assess sociodemographic and personality dimensions relevant to risk and shock behavior. Table 3 briefly provides a chronology of the tasks with the number of choices or questions per task and source. Table 3. Chronology of tasks Task Observed choices per subject Source Task 1 Risk Aversion 8 Gneezy & Potters (1997) Task 2 RA Simple 1 Eckel and Grossman 2008 Task 2 Risk Aversion 5 Noussair et al., (2014) Task 2 Prudence 5 Noussair et al., (2014) Task 2 Temperance 5 Noussair et al., (2014) Task 2 RA EU1 1 Noussair et al., (2014) Task 2 PRudEU2 1 Noussair et al., (2014) Questionnaire (Ten-Item Personal Information) 10 Gosling, S. D., Rentfrow, P. J., & Swann, W. B., Jr. (2003). Further descriptions of our experimental tasks can be found in Eckel & Grossman (2008), Gneezy & Potters (1997), and Noussair et al. (2014). The Forthright Access panel provides additional socio-demographics, including age, nationality, residency, education, ethnicity, employment, gender, income, marital status, political ideology, religion, sexual orientation, etc. | After In Stage I, subjects learn their endowment and the source of it. In Stage II, subjects will perform an investment task for 4 rounds to measure their risk aversion (Gneezy & Potters 1997). This tool has previously been employed to assess risk tolerance for economic shocks (Cohn et al., 2015; Holden & Tilahun, 2021). In this simple risk elicitation task, participants will be asked how much of their initial endowment, based on the random treatment assignment in Stage I ($20, $60, $100), they wish to invest in a risky option and how much to keep. The invested amount yields a dividend of 2.5 or 5.0, depending on the round, with a 50% probability. The decision maker keeps the money not invested. In Stage III, subjects will perform an additional lottery selection task to measure attitudes toward risk (Eckel and Grossman, 2008). More specifically, subjects select a lottery of their preference from six available options (Eckel and Grossman, 2008). Each lottery has the same outcome probabilities but varies the payments of the low and high outcomes. Subsequently, subjects complete 17 binary selection lotteries designed to capture higher-order risk attitudes following Noussair et al. (2014). Table 2 describes the 17 lottery decisions presented in are grouped into four parts: five choices to assess risk aversion by comparing a sure payoff with a risky lottery; five choices to measure prudence, defined as the preference to assign unavoidable risks to higher income states rather than lower ones; five choices to assess temperance, reflecting the preference to spread independent risks across states rather than concentrating them; and two additional choices to test relative risk aversion and prudence under expected utility theory. The choice of the left lottery indicates risk aversion, prudence, and temperance. Left Lottery Right Lottery Risk Aversion 1 20 [65_5] Risk Aversion 2 25 [65_5] Risk Aversion 3 30 [65_5] Risk Aversion 4 35 [65_5] Risk Aversion 5 40 [65_5] Prudence 1 [(90+ [20_-20]) _60] [(90_ (60+ [20_-20])] Prudence 2 [(90+ [10_-10]) _60] [(90_ (60+ [10_-10])] Prudence 3 [(90+ [40_-40]) _60] [(90_ (60+ [40_-40])] Prudence 4 [(135+ [30_-30]) _90] [(135_ (90+ [30_-30])] Prudence 5 [(65+ [20_-20]) _35] [(65_ (35+ [20_-20])] Temperance 1 [(90+ [30_-30]) _ (90+ [30_-30])] [(90_ (90+ [30_-30] + [30_-30])] Temperance 2 [(90+ [30_-30]) _ (90+ [10_-10])] [(90_ (90+ [30_-30] + [10_-10])] Temperance 3 [(90+ [30_-30])_(90+[50_-50])] [(90_ (90+ [30_-30] + [50_-50])] Temperance 4 [(30+ [10_-10]) _ (30+ [10_-10])] [(30_ (30+ [10_-10] + [10_-10])] Temperance 5 [(70+ [30_-30]) _ (70+ [30_-30])] [(70_ (70+ [30_-30] + [30_-30])] Ra_EU1 [40_30] [50_24] Prud_EU2 [(50+ [25_-25]) _30] [(50_ (30+ [15_-15])] Finally, participants complete a short questionnaire to assess sociodemographic and personality dimensions relevant to risk and shock behavior. Table 3 briefly provides a chronology of the tasks with the number of choices or questions per task and source. Table 3. Chronology of tasks Task Observed choices per subject Source Task 1 Risk Aversion 8 Gneezy & Potters (1997) Task 2 RA Simple 1 Eckel and Grossman 2008 Task 2 Risk Aversion 5 Noussair et al., (2014) Task 2 Prudence 5 Noussair et al., (2014) Task 2 Temperance 5 Noussair et al., (2014) Task 2 RA EU1 1 Noussair et al., (2014) Task 2 PRudEU2 1 Noussair et al., (2014) Questionnaire (Ten-Item Personal Information) 10 Gosling, S. D., Rentfrow, P. J., & Swann, W. B., Jr. (2003). Further descriptions of our experimental tasks can be found in Eckel & Grossman (2008), Gneezy & Potters (1997), and Noussair et al. (2014). The Forthright Access panel provides additional socio-demographics, including age, nationality, residency, education, ethnicity, employment, gender, income, marital status, political ideology, religion, sexual orientation, etc. The follow-up study uses a within-subject design to measure changes in individual risk attitudes before and after an exogenous shock. All participants begin with a $60 endowment and complete four rounds of the Investment Game (Gneezy & Potters, 1997) to establish baseline risk preferences. Participants are then randomly assigned to one of three treatments: WIN – 50% chance of keeping $60, 50% chance of gaining $40 (ending with $100) LOSS – 50% chance of keeping $60, 50% chance of losing $40 (ending with $20) C$60 – guaranteed $60 (control) After treatment assignment, participants complete four additional rounds of the Investment Game to capture post-shock investment behavior. Lastly, they perform the same higher-order risk preference tasks as our previous experiment with a between-subjects design (Eckel & Grossman, 2008; Noussair et al., 2014), allowing comparison of pre- and post-shock measures for risk aversion, prudence, and temperance. |
| Field | Before | After |
|---|---|---|
| Field Document | Before |
After
Relationship between shocks and HORA_September2025.docx
MD5:
a70993a1e06747d3385bed3bc2dce2e4
SHA1:
8b6f7030b7958ec3682bfbda3592556f9f1e7fea
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| Field Title | Before | After Relationship between Shocks and HORA |
| Field | Value |
|---|---|
| Field Document |
Value
Relationship between shocks and HORA .docx
MD5:
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SHA1:
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|