Measuring Ownership, Control, and Use of Assets

Abstract

Assets generate and help diversify income, alleviate liquidity constraints, and are key inputs into empowerment. Despite the importance of individual-level data on asset ownership, and the fact that most assets are owned by individuals, either solely or jointly, researchers typically collect micro data on asset ownership at the household level. Through a review of the existing approaches to data collection and the relevant literature on survey methodology, this study presents an overview of the current best practices for collecting individual-level data on the ownership and control of assets in household and farm surveys in low- and middle-income countries. The paper provides recommendations in three areas: (1) respondent selection, (2) definition and measurement of access to and ownership and control of assets, and (3) measurement of quantity, value, and quality of assets. It identifies open methodological questions that can be answered through further research.

KEYWORDS:

• Gender
• asset ownership
• wealth
• survey methodology
• household surveys

JEL Codes:

• C8
• D31
• J16

ACKNOWLEDGMENTS

This paper is part of a broader collaboration on methodological experimentation among several researchers from the World Bank Gender Innovation Lab, the World Bank Living Standards Measurement Study (LSMS), the International Food Policy Research Institute (IFPRI), the International Rescue Committee, and Oxford University to improve the measurement of time use, women’s agency, and ownership and control of assets – three key constructs in women’s empowerment, known both for their centrality in the current policy debate on gender equality and for the challenges posed by their measurement. The broader collaboration aims to achieve three goals: (1) shed light on the relative quality of the existing methods of measuring these constructs; (2) design and test new ideas to measure these constructs; and (3) generate evidence on which measurement method is most appropriate given the policy and research question at hand. The funding for Doss and Kieran was provided by the CGIAR Research Program on Policies, Institutions, and Markets (PIM) led by IFPRI. The funding for Kilic was provided by the World Bank Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) program.

Notes

1 For instance, Agnes Quisumbing, N. Kumar, and J. Behrman (2018) find that, in Bangladesh, weather-related shocks impact men’s assets more than women’s assets, but shocks related to illness have a larger impact on women’s assets. In Uganda, drought shocks affect women’s assets, but not men’s assets.

2 Evidence has demonstrated that secure land rights increase agricultural production at the household level, but very little research exists on this topic at the individual level. Markus Goldstein and Christopher Udry (2008) find that in Ghana, women farmers had less secure land rights than men and were thus less likely to leave their land fallow due to their increased risk of losing land that they were not actively farming. Agnes Quisumbing et al. (2001) reveal, also in Ghana, that women were more likely to invest in land with secure property rights by planting cocoa trees. While more research is needed to understand the conditions under which strengthening women’s property rights will increase aggregate agricultural productivity and sustainable management practices (Doss 2018), sufficient evidence has demonstrated that livelihood interventions that do not recognize the gender asset gap run the risk of exacerbating inequalities (Meinzen-Dick et al. 2014, 2019). See also Michael O’Sullivan’s (2017) review of gender and property rights in Africa.

3 Although water is also important, the access to and control over water is a substantially different issue with an extensive literature that is beyond the scope of this paper.

4 Common property could include forests, rangelands, or water systems. The extent to which these assets are controlled by men, women, or jointly, as well as the resulting implications for livelihood strategies or empowerment (such as through leadership in the group tasked with the common property management) can be explored (Meinzen-Dick et al. 2014).

5 Only rarely do enumerators ask to see copies of the ownership documents.

6 In addition, some property such as land may be held by a community as common property. There are a range of issues regarding how to obtain data on common property that are beyond the scope of this study.

7 We discuss the appropriate unit of analysis in more detail later on in the article.

8 Arm 1, “business-as-usual,” interviewed the individual who, following the enumerator’s introduction of the survey, was identified to be the “most knowledgeable” household member. This respondent was asked about the assets owned by each member of the household, exclusively or jointly with others within or outside the household, in each asset class. Arm 2 interviewed the randomly selected member of the principal couple while Arm 3 interviewed the principal couple together. The questionnaire for Arm 2 and Arm 3 was otherwise identical with respect to Arm 1. Arm 4 and Arm 5 each interviewed up to four adult household members, 18 years and older attempts were made to conduct the interviews simultaneously. In each case, an attempt was made to conduct the interview without others present. Identical to Arms 1 through 3, each respondent in an Arm 4 household was asked independently about the assets owned by each member of the household, exclusively or jointly with others within or outside the household, in each asset class. In contrast, Arm 5 only inquired about the assets owned by the respondent, exclusively or jointly with others within or outside the household, in each asset class. Another household member’s potential joint ownership of an asset was identified only conditional on the respondent’s identification of himself or herself as an owner of that asset.

9 Among the men respondents from Arm 5 households, similar treatment effects, in terms of direction, magnitude, and statistical significance, were observed in the analysis of (overall and joint) documented and (joint) economic ownership of dwellings and agricultural land as well as (joint) reported ownership of livestock and financial accounts.

10 While it would be possible to ask a proxy respondent to provide information on each household member, this has not yet been done in the context of the DHS and the WEAI.

11 An open empirical question is whether women are more likely to report joint ownership if the legal system supports and enforces it and less likely to do so where the enforcement is weak and customary law prevails, as observed in many countries across Africa.

12 Even with the documentation, the intrahousehold “truth” regarding who exerts control over a given asset may not line up with which household members are listed in the records as owners. This discrepancy could be due to (1) proxy owners intentionally being listed in the records, (2) lags in the updating of the records following asset transfers, and/or (3) temporal variation in intrahousehold control of the asset in question. Another complication, particularly related to land in Africa, could be the disconnect between de jure legislation, which guarantees property rights irrespective of sex, and de facto recognition and implementation of property rights at the local level. If the de facto arrangements prevail over the state laws in a way that discriminates based on gender and age and exhibit spatial variation in accordance with social norms, it is not clear that the identification of asset owner(s) based on official records would be binding at the micro level.

13 The UN EDGE international guidelines on individual-level measurement of asset ownership and control are expected to expand on these scenarios and their implications for fieldwork design and sampling.

14 At least one exception in reliable self-reported asset quantification is farmer-reported land area measurement (Carletto, Gourlay, and Winters 2015; Carletto et al. 2016).

15 A related strand of research is interested in relative household and individual welfare gains associated with (1) balancing the relative bargaining power of spouses versus (2) enhancing intrahousehold cooperation among them. While the latter may be proxied by individual-level data on joint asset ownership, the comparable scope of information on exclusive ownership could help define the former. Nancy McCarthy and Talip Kilic (2017) develop a non-cooperative bargaining model that presents conditions under which relatively large gains would be expected from moving to more equitable bargaining power versus achieving intra-household cooperation. They test their model’s predictions using the LSMS-ISA data from Malawi, and specifically the individual-disaggregated data on control of income. The authors find that relative to increasing wives’ bargaining power (defined as the share of total disjoint (male + female) income that is under women’s control), improving cooperation between spouses (defined as the share of total household income that is under joint control) exerts larger and statistically significant positive impacts on total household income and consumption expenditures per capita, as well as the share of household consumption devoted to public goods.

Additional information

Notes on contributors

Cheryl Doss

Cheryl Doss is Associate Professor and Senior Departmental Lecturer in Development Economics in the Department of International Development at Oxford University. She was previously employed at Yale University.

Caitlin Kieran

Caitlin Kieran is a PhD student at the Department of Agricultural and Resource Economics at the University of California, Davis. She was previously employed at the International Food Policy Research Institute.

Talip Kilic

Talip Kilic is Senior Economist, as part of the Living Standards Measurement Study (LSMS) Team at the Data Production and Methods Unit of the World Bank Development Data Group. He is based at the World Bank Center for Development Data in Rome, Italy.