Is an informed husband a better husband?


This page in:

Husbands and wives sometimes do not agree. In a post about a year ago, I talked about how this disagreement seemed to be associated with welfare outcomes for women, boys and girls. An intriguing new paper by Nava Ashraf, Erica Field, Alessandra Voena and Roberta Ziparo argues that asymmetric information may be exacerbating this disagreement and shows how providing information can help couples get to a better place…and reduce fertility.

The setting is Lusaka, Zambia. National fertility rates are on the high side, with 5.3 children per woman aged 15-49. In this context, as in many others, men would prefer, on average, to have more children than women (in Ashraf and co’s sample, men would like 4.43, women 4.19). Maternal mortality is high: 1 in 59 Zambian women die giving birth. And men are less aware of the factors that contribute to maternal mortality than women. For example, 84.6 percent of women identify advanced maternal age as a risk factor, but only 74.3 percent of men do.

So, this adds up to a situation where men are less informed about a risk they want their wife to take. And she can’t effectively communicate this risk to him.

Enter the treatment. Ashraf and co. work with some health facilities in Lusaka to deliver three variants of a program. For the control group both members of a couple get family planning (FP) information. In one treatment group, the couple gets FP information, and the man gets some additional information on maternal mortality and its risk factors. In the second group, the wife gets this additional information.  The paper has a nice thoughtful discussion as to why this design was chosen (e.g. to avoid differential selection stemming from women who would go to a workshop versus men who would make this choice). And it means that in what follows we are looking at the impact of getting FP versus FP plus maternal mortality.

Most of the couples (perhaps encouraged by both a 5 dollar transport subsidy and a 1 in 10 chance to win a small electric stove) come: attendance clocks in at 73 percent.

So what happens? When the man gets the additional maternal mortality information, his wife is 5.2 percentage points (significant at 10 percent) less likely to be pregnant at endline (a bit under a year after the intervention was completed. This amounts to a 43 percent reduction relative to the control group. If his wife got the information, she is not significantly less likely to be pregnant – but the point estimate here is 4 percentage points and not statistically different from the husband being treated.

Demand is where significant differences start to emerge. Husbands who got the maternal mortality information are 7.3 percentage points (significant at 10 percent) less likely to want more children. On the other hand, if their wife got the information there is no significant impact (on husband’s demand) and it’s statistically different from the husband being treated. So, there is a more clear fertility preference move for husbands getting this information. And these men are also less likely to believe that their wife wants another child.

Maybe they are talking more. Indeed, when Ashraf and co. look at this, they find that men who were treated were 13 percentage points (or 27 percent) more likely to communicate about maternal mortality risks to their partner. And their partners were 7.7 percentage points (significant at 10 percent) more likely to communicate about these risks to them. On the other hand, if the wife was treated we see none of this communication.

Interestingly, the men who were treated report a decline of 9.4 percentage points in agreement on contraception use, but a 7.2 percentage point increase in the probability that they tried to get their spouse to use contraception and a 5.1 percentage point increase in their spouse trying to convince them. These discussions seem to be lively ones.

Now let’s go back to that first result. There is a bit of a puzzle in that there is no significant difference in the fertility declines for men getting the maternal mortality information versus their wives. In the interesting model that Ashraf and co. build in the paper, transfers from the husband to the wife play a role in dealing with the incongruity in their preferences. And to this metric Ashraf and co. now turn. They find that when the husband gets the information, there is no change in the transfers he gives his wife. On the other hand, when she gets the information, his transfers to her drop – both in the likelihood that they happen (13 percentage points) and in amount (40 percent). So maybe he gives in to her on fertility, but he’s also giving her lower transfers.

Ashraf and co. also look at marital satisfaction. When the husband gets the maternal mortality information, both the husband and the wife report a significant increase in happiness with the marriage. When the wife gets the information, she does not report an increase in this, but he does.

This is a cool paper, showing that we have to take the gender dynamics seriously if we want to tackle issues like fertility. In this instance, it’s a case of a relatively simple intervention making meaningful progress in not only reducing the chance of pregnancy, but also shifting preferences, improving communication, and making folks happier in their marriage. As Ashraf and co. argue, we still have some ways to go to understand these things better (e.g. they ask what would happen if we provided the information to them both as a couple), but for now this helps us get a handle on how asymmetric information and differing preferences can make things sticky.



Markus Goldstein

Lead Economist, Africa Gender Innovation Lab and Chief Economists Office

Join the Conversation