Martin Ravallion, 1952-2022

I was saddened to learn earlier this week of the passing of the Australian economist Martin Ravallion on 24 December last year. Ravallion was probably best known as research director at the World Bank up until 2013, and was more recently a professor at Georgetown University. His main areas of research were the economics of poverty and inequality, and it is in that context where I got to read a lot of his work, especially as I was working on my PhD thesis (on the links between poverty and HIV/AIDS in Northeast Thailand. 

My students in the late 2000s and early 2010s got a big dose of Ravallion, as I assigned many of his readings to my graduate development economics class, when I was teaching at that level. In particular, he was a key contributor to debates on the use of the $1 per day global extreme poverty line, which all of my students from that class will have gotten very familiar with. Sadly, after giving up teaching development economics, I didn't have much occasion to read some of his more recent research. However, I have referenced Ravallion's work a couple of times on this blog (here and here). 

I haven't noticed a good obituary in any of the usual locations. However, Berk Ozler and David McKenzie have a great post on the Development Impact blog, reflecting on Ravallion's interactions with them. David Evans has reviewed Ravallion's broad research contributions on the CGD Blog. Ravallion was ranked in the top 100 economists, and the top development economist, by RePEc. He had a number of students, interns, and colleagues who have contributed greatly to development economics as well. His legacy will clearly go on for some time. He will be missed.

[HT: Marginal Revolution]

The new economics of fertility

When I was doing my Honours degree in economics, I encountered the economics of fertility for the first time. The standard model for fertility came from Nobel Prize winner Gary Becker, and suggested that fertility decisions were based on a trade-off between the number of children (quantity) and investment in those children's education (quality). The literature has since moved on, and this recent NBER Working Paper (forthcoming in the Handbook of Family Economics; ungated version here), by Matthias Doepke (Northwestern University), Anne Hannusch (University of Mannheim), Fabian Kindermann (University of Regensburg), and Michèle Tertilt (University of Mannheim)reviews the current state of the field. A good summary of the (long and detailed) paper is in the introduction:

We start by reviewing the regularities that inspired the first generation of economic models of fertility. These include a negative relationship between income and fertility; a link between the demographic transition and economic development; and, at a later stage of development, a negative relationship between women’s labor force participation and fertility. We argue that economic models based on two main ideas, relating to the quantity-quality tradeoff and the opportunity cost of mother’s time, were able to account for these regularities.

Based on empirical research of the past two decades, we then show that these regularities no longer characterize today’s data. The income-fertility relationship is now largely flat within many countries and increasing in the cross-section of high-income countries. Recent work on the quantity-quality tradeoff argues that it is no longer detectable in high-income countries. Meanwhile, the relationship between women’s labor force participation and fertility across countries has reversed. Even within countries, the relationship between women’s education and their fertility is no longer always decreasing...

The new facts about fertility behavior in high-income countries do not mean that the ideas of a quantity-quality tradeoff or of a central role of the opportunity cost of mothers’ time were wrong. The tradeoffs emphasized by these models still exist and continue to be important in explaining fertility behavior in many places, including lower-income countries. What has changed, however, is that these tradeoffs no longer drive the major variation in the data for high-income countries...

...in high-income countries, child labor has disappeared and education for most children continues past childhood into the adult years. These changes imply that the tradeoff inherent in quantity-quality models between sending children to school versus having more resources to raise a larger family has lost salience. Similarly, models based on women’s opportunity cost of time posit that raising more children requires mothers to spend less time working in the market. While this tradeoff still exists today, it has weakened as alternative forms of childcare have become more prominent. When childcare is provided by someone other than the mother—whether a hired nanny, a government-run kindergarten, or the child’s father—the cost of children is no longer linked as directly to the mother’s opportunity cost of time...

...the compatibility of family and career has become a key determinant of fertility in high-income economies. Where the two are easy to combine, many women have both a career and multiple children, resulting in high fertility and high female labor force participation. When career and family goals are in conflict, fewer women work and fewer babies are born. We point out four factors that help mothers combine a career with a larger family: the availability of public child care and other supportive family policies; greater contributions from fathers in providing childcare; social norms in favor of working mothers; and flexible labor markets. 

Doepke et al. also suggest some promising areas for future research on the economics of fertility, including research on parental time use and the intensity of parenting (probably using time use diary data or similar), extending existing models to account for the extended family and heterogeneity in family types (including same-sex couples), and exploring the macroeconomic consequences of sustained below-replacement fertility.

As well as being a thorough review of the literature, the paper also has some insights that are interesting in their own right, such as the unintended consequences of fertility treatments (or offsetting behaviour), where Doepke et al. note that:

...the very availability of IVF treatments causes women to delay their entire fertility planning further into later periods characterized by lower IVF success, thereby rendering the technology less effective.

Sadly, the economics of fertility (and population economics more generally) continues not to get the attention it deserves. At least, the state of the art is now summarised in one place.

[HT: Marginal Revolution, last year]

The effect of computer-based testing on measured student achievement

The coronavirus pandemic meant an immediate shift to online assessment, including online tests. So, I initially thought that this 2019 article by Ben Backes and James Cowan (both American Institutes for Research), published in the journal Economics of Education Review (ungated earlier version here), would be rather interesting. However, it turns out that Backes and Cowan are interested in something slightly different - whether computer-based testing (rather than online testing per se) biases measures of student achievement downwards. Their setting is Massachusetts high schools, where:

In 2015, some districts began transitioning to the PARCC [Partnership for Assessment of Readiness for College and Careers] assessment. These districts had the choice of using the paper or online version of the test, and nearly half administered the online format in 2015 or 2016.

Backes and Cowan essentially compare average student performance when the test is conducted in a computer-based mode, with average student performance when the test is conducted on paper. Their sample of students:

...includes about half of all students enrolled in Grades 3 through 8 between 2011 and 2016 and 88 percent of students in schools administering the PARCC in 2015 and 2016...

That's about 1.1 million student-year observations in some of their analyses. They find that:

...students administered an online exam score systematically lower than if they had taken the test on paper. In particular, students taking the online version of PARCC scored about 0.10 standard deviations lower in math and about 0.25 standard deviations lower in English language arts (ELA) than students taking the paper version of the test...

Our estimates of mode effects in math and ELA represent extremely large changes in measured student learning: up to 5.3 months of learning in math and 11.0 months of learning in ELA in a 9 month school year...

And there is some evidence for heterogeneity of the effects:

While we find little systematic evidence of variation in treatment effects by student demographic group in math, we find that ELA mode effects are stronger for students at the bottom of the achievement distribution, for English language learners, and for special education students.

Overall, there is a robust difference in the performance of students between when the exam is computer-based and when it is paper-based. Students do much better in the paper-based test. However, Backes and Cowan aren't able to explain why. There is some evidence that the effect reduces as students become familiar with the computer-based mode, although the effect is still rather large in the second year. That suggests that student unfamiliarity with computers might be at play. However, that is quite speculative.

I had hoped this study (based on its title) would tell us a bit about whether online testing was biased in some way (in either direction). However, all it really tells us is that combining the results of tests that were conducted using different modes is pretty fraught, and we should only do so with great caution. That is an important result, especially as tests such as those that Backes and Cowan study are often used to rank school districts, schools, and even teachers, in terms of performance. However, despite the importance the results are not particularly surprising.

The unintended consequence of requiring sesame to be noted on food labels

The AP reported last week:

A new federal law requiring that sesame be listed as an allergen on food labels is having unintended consequences — increasing the number of products with the ingredient.

Food industry experts said the requirements are so stringent that many manufacturers, especially bakers, find it simpler and less expensive to add sesame to a product — and to label it — than to try to keep it away from other foods or equipment with sesame.

As a result, several companies — including national restaurant chains like Olive Garden, Wendy’s and Chick-fil-A and bread makers that stock grocery shelves and serve schools — are adding sesame to products that didn’t have it before. While the practice is legal, consumers and advocates say it violates the spirit of the law aimed at making foods safer for people with allergies...

Under the new law, enforced by the Food and Drug Administration, companies must now explicitly label sesame as an ingredient or separately note that a product contains sesame. In the U.S., ingredients are listed on product packaging in order of amount. Sesame labeling has been required for years in other places, including Canada, Europe, Australia and New Zealand.

If the ingredients don’t include sesame, companies must take steps to prevent the foods from coming in contact with any sesame, known as cross-contamination.

When it comes to food labelling and the choice of ingredients, a rational food producer will choose the option that is the lowest cost (assuming that there is no revenue difference between selling products that do or do not contain sesame). Essentially, with this new law they have to weigh up two options: (1) re-configuring their plant to avoid cross-contamination, and not having to label their products as containing sesame; and (2) adding a small amount of sesame flour to their products, and including sesame in the ingredient list. Clearly, for many producers, the first option is lower cost. They comply with the new law, and importantly they avoid any costs associated with consumers having allergic reactions to their products (because the product label should warn those consumers away).

It's unfortunate that sesame consumers will now find it more difficult to find products that they will not have an allergic reaction to, but this was entirely foreseeable, especially given that this is not the first time that producers have reacted in this way:

Some large companies previously have added other allergens to products and updated their labels. In 2016, Kellogg’s added traces of peanut flour to some cookies and crackers, prompting protests.

 [HT: Marginal Revolution]