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Culture and gender gaps in preferences, beliefs and behaviour
Last registered on April 26, 2021


Trial Information
General Information
Culture and gender gaps in preferences, beliefs and behaviour
Initial registration date
April 26, 2021
Last updated
April 26, 2021 10:34 AM EDT

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Primary Investigator
Renmin University of China
Other Primary Investigator(s)
PI Affiliation
University of Bath
Additional Trial Information
In development
Start date
End date
Secondary IDs
Using exogenous variation in culture (male-biased vs pro-female/egalitarian tribes), this project aims to analyze (i) the relevance of culture via heterogeneity in gendered beliefs for gender differences in outcomes, (ii) intergenerational transmission of beliefs, (iii) the role of cultural heterogeneity in assortative mating, and (iv) the role of cultural heterogeneity in political participation.
External Link(s)
Registration Citation
Golan, Jennifer and Jing You. 2021. "Culture and gender gaps in preferences, beliefs and behaviour." AEA RCT Registry. April 26. https://doi.org/10.1257/rct.7604-1.0.
Experimental Details
This project uses exogenous variations of gender-bias stemming from differences in culture among different ethnic groups. The project will conduct the Implicit Association Test (IAT) for adults and children separately, in order to measure their gender-related stereotypes. This project will also use a survey instrument to elicit preferences for the adults and children, respectively. The survey also includes standard socioeconomic and demographic information, psychological characteristics, and measures explicitly gender-related norms, attitudes and beliefs.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
1. Implicit gender-related stereotypes and beliefs through IAT.
2. Explicit gender views:
(1) Self-reported gender-bias index (Anderson, 2008).
(2) Elicited gender stereotypical thinking (Bian et al., 2017).
3. Gender difference in risk/ pro-sociality/equality preferences of parents and children.
(1) Risk attitudes: the multiple-price list format (Eckel and Grossman, 2008 for adults, Andreoni et al., 2020 for children).
(2) Loss aversion in risky choice tasks: Trautmann and Vlahu (2013), adapted from Fehr and Goette (2007), for adults.
(3) Time preferences: the multiple-price list format (e.g., the IFLS design; Chuang and Schechter, 2015; Andreoni et al., 2019) for both adults and children.
(4) Social preference: Sutter et al. (2018) for both adults and children.
(5) Positive reciprocity and altruism: Falk and Hermle (2018) for adults.
(6) Willingness to compete: Niederle and Vesterlund (2007) for both adults and children.
(7) Cultural thought: analytic or holistic thinking, individualistic or collective thinking in Talhelm et al. (2014) for both adults and children.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
(1) Economic well-being for adults only: income, consumption, assets, agricultural inputs and outputs.
(2) Behaviour: fertility, human capital investment, time allocation, labour allocation, educational outcomes, adoption of new agricultural technology, borrowing, participation to rural cooperatives, political participation, and social interactions.
(3) Psychological well-being: happiness, satisfaction, aspirations (La Farrara, 2019; Lybbert and Wydick, 2018).
(4) Cognition (Raven’s matrices, the numerical stroop test, the colour and word stroop test).
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
This project exploits the exogenous variation in culture caused by different ethnic groups. Ethnic groups are classified as patrilineal and matrilineal groups according to various culture-related (informal) institutions. These are based on SIGI categories (https://www.genderindex.org/methodology/), including discrimination in family (e.g., marriage arrangements and inheritance), restricted physical integrity (e.g., son preferences and domestic violence) and restricted access to productive and financial resources (e.g., intrahousehold decision making over finances and attitudes towards labour market participation). It is hypothesised that gender-biased institutions guiding succession would contribute to gender differences in social preferences and behaviour. This would be re-produced across generations and may become particularly relevant to children once they reach puberty.
Experimental Design Details
Not available
Randomization Method
We adopt stratified randomisation based on ethnic groups and locations.
(1) We collected a trial survey among 170 key informants out of Yunnan and Sichuan provinces in March 2020 for livelihood arrangements of ethnic groups and various (informal) institutions guiding succession such as marriage, decision making in family, and inheritance norms. We constructed indices and rank ethnic groups by their extent of male-biasedness.
(2) The data are also matched to (formal) institutional categories proxied by SIGI variables (https://www.genderindex.org/methodology/). Using the information of the Ethnographic ATLAS on social structure, which gives an indication of the extend of “egalitarian” structure, we selected matrilineal and patrilineal ethnic groups and within each category there are ethnic groups of different extents of “egalitarian” structures.
(3) Given that many ethnic groups are not covered in ATLAS, we also referred to ethnography and cultural anthropology for the origins of ethnic ancestors, the linguistic system, culture and norms. We selected ethnic groups having not been covered by ATLAS or our trial interview but practising apparently matrilineal and patrilineal norms. The proposed set of sample ethnicities consists of Mosuo, Jinuo, Bulang, Jingpo, Dong, Dulong, Dai, Deang (i.e., Benglong in ATLAS), Yao, Lisu, Miao, Yi, Achang, Bai, Nu, Lahu, Tujia, Hani, Tibetan, Mongol, and Han.
(4) For each ethnic group, we consult the China Ethnicity Statistical Yearbook 2019 and use the list of main residential provinces for ethnic groups and the lists of ethnic autonomous towns, counties and prefectures in each province. Based on these lists, we select the main residential province and prefecture for each ethnic group and within the prefecture, randomly select the ethnic autonomous towns and counties according to the population and economic development. Particularly for each ethnic group, we sample at least two different counties, in order to capture any within-group variations as a result of decades of inter-ethnic mixing due to different residential locations.
Randomization Unit
Household level
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
Sample size: planned number of observations
1,000 households
Sample size (or number of clusters) by treatment arms
600 households of patrilineal ethnic groups, and 400 households of pro-female or matrilineal ethnic groups
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB Name
Academic Board of the School of Agricultural Economics and Rural Development, Renmin University of China
IRB Approval Date
IRB Approval Number
IRB Name
Social Sciences Research Ethics Committee, University of Bath
IRB Approval Date
IRB Approval Number