metadata: authors: 0: author: Boxho,Claire Elise
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2: author: Goldstein,Markus P.
3: author: Montalvao,Joao
4: author: Rouanet,Lea Marie
count: Mozambique,Cote d'Ivoire,Malawi
docna: 0: docna: Assortative Matching in Africa : Evidence
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docty: Policy Research Working Paper
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abstracts: cdata!: This paper documents novel evidence of
            positive assortative matching in African marriage markets
            along cognitive and socio-emotional skills, time and risk
            preferences, and education, using data from rural
            Mozambique, Cote d'Ivoire, and Malawi.
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display_title: Assortative Matching in Africa :
            Evidence from Rural Mozambique, Cote d'Ivoire, and Malawi
listing_relative_url: /research/2019/07/31265450/assortative-matching-africa-evidence-rural-mozambique-cote-divoire-malawi
topicv3: Education, Skills Development and Labor
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publishtoextweb_dt: 2019-07-22T00:00:00Z
historic_topic: Agriculture,Information and Communication Technologies,Education,Gender
no_of_pages: 17
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model_extractions: Policy Research Working Paper 8943

# Assortative Matching in Africa Evidence from Rural Mozambique, Côte d’Ivoire, and Malawi

_Claire Boxho Aletheia Donald Markus Goldstein Joao Montalvao Léa Rouanet_ Africa Region Gender Innovation Lab July 2019
Policy Research Working Paper 8943

# **Abstract**

This paper documents novel evidence of positive assortative matching in African marriage markets along cognitive and socio-emotional skills, time and risk preferences, and education, using data from rural Mozambique, Côte d’Ivoire, and Malawi.

This paper is a product of the Gender Innovation Lab, Africa Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at jmontalvao@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Assortative Matching in Africa: Evidence from Rural**

# **Mozambique, Côte d’Ivoire, and Malawi**<sup></sup>

Claire Boxho, Aletheia Donald, Markus Goldstein, Joao Montalvao, Léa Rouanet<sup>†</sup>

**Keywords:** Assortative matching, marriage market, cognitive skills, socio‐emotional skills.

**JEL Codes:** D1, I2, J1.

>  We thank participants at the CSAE Conference 2019. We gratefully acknowledge financial support from UN Women and the World Bank Group’s Umbrella Facility for Gender Equality. This paper is a product of the Africa Gender Innovation Lab. The views presented in this paper are those of the authors and do not represent those of the World Bank or its member countries. All errors remain our own.

> † All authors are based at the World Bank Africa Region Gender Innovation Lab. Emails: cboxho@worldbank.org; adonald@worldbank.org; mgoldstein@worldbank.org; jmontalvao@worldbank.org; lrouanet@worldbank.org.
_[Some] ... say we love those who are like ourselves._ – Aristotle 1934, p. 1155.

# **1. Introduction**

Marital sorting based on human capital has important implications for the creation, distribution, and inter‐generational transmission of welfare. While the literature finds evidence of this assortative matching – the tendency of men and women who marry to have similar human capital levels – most of this research has been conducted in rich country settings and has largely focused on sorting along educational attainment [e.g. Greenwood et al. 2014]. This is despite the growing literature emphasizing the economic importance of multiple human capital dimensions in both rich and poor contexts [e.g. Heckman et al. 2006, Liu 2013, Abay et al. 2017], as well as recent work on matching and marriage markets showing that sorting is multidimensional [e.g. Dupuy and Galichon 2014, Chiappori et al. 2018].

We present novel evidence of positive assortative matching along cognitive and socio‐emotional skills, time and risk preferences, and education using unique data from rural Mozambique, Côte d’Ivoire, and Malawi. In each country, the observed sorting patterns are robust to accounting for simultaneous sorting along the multiple, potentially correlated human capital dimensions. While assortative matching could in part be caused by frictions constraining the search for dissimilar partners, we find strong spousal similarity both overall and within villages. Moreover, against the notion that spouses grow alike over time, we find that sorting is equally strong when we restrict our analysis to younger couples. Taken together, the evidence thus suggests that assortative matching is the outcome of a marriage market equilibrium shaped by spouse preferences. To the best of our knowledge, we are the first to provide systematic evidence of assortative matching on multiple human capital dimensions in Africa.

# **2. Data**

# **2.1. Data Sources**

We exploit three data sources. First, we use data from a survey conducted in April and June 2016 across 150 randomly selected rural communities in the Tsangano, Angónia, Macanga, and 2
Chifunde districts of Mozambique. Within each community, a random sample of 20 female farmers were surveyed along with their husbands. The survey is the baseline of an ongoing randomized controlled trial to assess the effectiveness of a human capital program targeting female farmers. The survey elicited information on both spouses’ cognitive and socio‐emotional skills, as well as their time and risk preferences. The spouses were asked these modules separately and privately.

Second, we use data from a survey conducted in June‐July 2016 across 180 villages in the Bas‐ Sassandra, Comoé, Lacs and Lagunes districts of Côte d’Ivoire. The survey is the baseline of an ongoing randomized controlled trial to assess the impact of improving rubber farmers’ access to technologies and markets. The survey elicited information on the socio‐emotional skills, and time and risk preferences of the farmers that applied to the program, as well as of their spouses. The spouses were asked these modules separately and privately.

Third, we use data from the second wave of the Malawi Third Integrated Household Panel Survey (IHPS), conducted in 2013. This is a publicly available longitudinal survey that is representative of the Malawian population. For the rural sub‐sample, the survey elicited information on the cognitive and socio‐emotional skills of up to two plot managers. These are typically the husband and the wife, which are the focus of our analysis.

In each country, we restrict the sample to couples for whom we observe the corresponding skills and preferences of both spouses, as well as the other covariates used in the analysis. This results in working samples of 2,280 couples in Mozambique, 1,407 couples in Côte d’Ivoire, and 531 couples in Malawi.

# **2.2. Measuring Skills and Preferences**

Socio‐emotional skills were measured in the three countries by asking respondents to rate their level of agreement with different attitudinal statements (see Appendix A1). In Mozambique and Malawi, these items elicit abilities commonly associated with an entrepreneurial mindset, such as perseverance, locus of control, and optimism: some of the items are identical or similar between the two countries, but not all of them. In Côte d’Ivoire, these items focus on self‐esteem 3
and agricultural self‐efficacy. For each country, we construct a composite socio‐emotional ability index that is the normalized z‐score of the first principal component of the different items (correcting for acquiescence‐bias and reversing negatively‐coded items).<sup>1</sup> Cognitive skills were measured in Mozambique and Malawi using Digit Span Tasks (see Appendix A2). Respondents were asked to repeat in the same order as many digits as they could from a list of digits read by the enumerator. This task captures short‐term memory and is commonly thought to be an important dimension of IQ. The final cognitive ability measure equals the number of correct digits that the respondent is able to repeat.

Time preferences were measured in Mozambique and Côte d’Ivoire using different versions of an intertemporal multiple price list (see Appendix A3). Respondents were asked to make sequential choices between payment tomorrow and in a month’s time, with increasing relative rates of return for waiting. We use these choices to construct a time preference score, where higher values correspond to more patience. In Mozambique, this measure equals the point where the respondent switches to choosing the later payment. In Côte d’Ivoire, this measure equals the number of instances where the respondent allocates strictly more value to the later payment than the sooner payment.

Risk preferences were measured in Mozambique and Côte d’Ivoire by asking respondents to choose from a menu of crop choices under varying returns and risk scenarios (see Appendix A4). In Mozambique, respondents chose among eight crops, each with distinct returns under a “good” and a “bad” farming season occurring with probability 50%. In Côte d’Ivoire, respondents were presented five different rainfall scenarios with probability of adequate rainfall increasing from 10 to 100%. For each scenario, the respondent chose among two crops with differing drought‐ susceptibility. For both countries, a higher score means higher risk aversion.

Appendix Table A1 presents summary statistics for all the variables used in the analysis.

> 1 We compute the acquiescence score of each respondent by averaging across the mean of positively‐coded items and the mean of negatively‐coded items (before reversing them), then subtract each respondent’s acquiescence score from each of their individual item responses.

4
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positive unconditional within‐couple correlations for each human capital characteristic in each country. Columns 2 to 4 show this finding is robust to sequentially conditioning on the remaining human capital characteristics and ages of both spouses, household characteristics, and community fixed effects.

Our preferred specification is in Column 4 with the full set of controls. This shows that a 1sd increase in the male spouse’s socio‐emotional ability is associated with a .44‐.60sd increase in the female spouse’s socio‐emotional ability. The within‐couple correlations for the other traits are somewhat smaller, but still highly statistically significant: .23‐.41sd for cognitive ability, .28‐ .29sd for patience, .21‐.36sd for risk aversion, and .36‐.39sd for years of education.

As another robustness check, Column 5 restricts the sample to couples where the wife is under 30 years old, proxying for more recently formed couples. If the observed sorting patterns are primarily explained by spousal socialization, say through imitation and learning, these patterns should be attenuated among younger couples. The results show no significant evidence of such heterogeneity: the within‐couple correlations for these sub‐samples are still large (and quite similar in terms of magnitudes).<sup>2</sup>

# **4. Discussion**

Human capital shapes one’s economic life. We present novel, robust and systematic evidence that men and women in rural Africa are positively assortatively matched on education, cognitive and socio‐emotional skills, and time and risk preferences. While more work is needed to identify the precise causal mechanisms and marriage market dynamics shaping this pattern, future research should also examine its implications for households’ welfare distribution and inequality, as well as the resulting inter‐generational transmission of welfare and inequality (as parents may pass some of these traits to their children). Our results provide new input for the design and targeting of human capital policy interventions.

> 2 This finding is robust to alternative female spouse ’ s age cutoff points to define the younger couples ’ sub‐samples.

6