Footbridges for higher wages

Lant Pritchett and other researchers often argue that development economists are too focused on one-off, micro interventions and fail to see the big picture. They are highly critical of the hype that develops around specific interventions following the release of studies using RCTs or other quasi-experimental methods to measure the impact of a specific program – microfinance, for example, had a big moment and, more recently, cash transfers have dominated many discussions of economic development.

Pritchett’s scorecard comparing first generation RCT practice to the approach of the non-RCT crowd is an especially brutal assessment of the micro development literature (second table in the link). He writes, “National Development leads to better well being. National development is ontologically a social process (markets, politics, organizations, institutions). RCTs have focused on topics that account for roughly zero of the observed variation in human development outcomes.”

There’s a lot that’s valid about this line of critique, although I think it’s more a call to be sure to contextualize learnings, ideally with qualitative research to investigate the how and why of a quantitative claim, rather than motivation to throw out the micro development approach altogether.

Besides, there is something so satisfying about how a small intervention can have a big impact.

Small bridges, big deal

Brooks and Donovan’s recent paper (full PDF here) found that building footbridges in Northern Nicaragua protected local workers from the typical wage loss seen during flooding, when travel routes are cut off, and even led to increased profits of local farmers.

Their primary finding is best seen through two graphics from the paper. The first shows the distribution of wage earnings before footbridge construction, and you can clearly see a massive disadvantage to those experiencing flooding. In the second, the gap has disappeared.

Figures 1 & 2: Distribution of wage earnings BEFORE footbridge construction

Figure 2: AFTER

They also find positive spillover effects. First, rural villagers were able to take higher paying jobs in nearby towns, increasing their wages and increasing the wages of those left behind, who faced less competition in the local labor market. (A similar mechanism to that found in the No Lean Season research, which offered select villagers incentives to migrate to cities for work and found positive income effects for those households and neighboring non-study households.)

Second, farmer profits increased. Not because of lower trade costs that allowed farmers to buy cheaper inputs, but because they were able to access new purchasing markets for their goods and diversify their income sources.

This paper is amazing because the data viz communicates clearly, the findings are meaningful and positive, and the idea for the research design had to have come from an intimate knowledge of the challenges facing rural citizens of Northern Nicaragua.

A national and local development tool

Infrastructure studies connect easily to those big questions about national development that anti-randomistas would prefer to focus on.While it won’t be footbridges in every location, there are lots of countries where road and transport infrastructure solutions are needed to promote both local and national development.

Papers like this one show how connectivity and access can be an important determinant of economic welfare via multiple mechanisms. Besides income effects like those measured in the Brooks and Donovan paper, there are possible effects for access to credit, healthcare, or other public services that isolated communities would otherwise miss out on.

Gaining entitlements with infrastructure and cash

There’s a seriously inspiring narrative in there – a simple change that leads to more options, more opportunities, more connectivity. As my colleague Sindy was discussing today, there is a pattern that interventions about increasing options and expanding opportunity, such as infrastructure improvements or cash transfers, seem more powerful to affect broad change than interventions targeting very narrow and specific goals.

Although, there is probably a gain in using both types of interventions at different times, or concurrently.

McIntosh and Zeitlin’s new paper compares a cash transfer program directly with a child nutrition program.The final line of their abstract made me think about paternalism and beneficiary preferences: “The results indicate that programs targeted towards driving specific outcomes can do so at lower cost than cash, but large cash transfers drive substantial benefits across a wide range of impacts, including many of those targeted by the more tailored program.”

People spend their money with different priorities than programs dictate and seem to get more out of it. That suggests to me that cash transfers (or infrastructure improvements) are a way to improve this baseline ability to provide for your household (“entitlements” à la Amartya Sen), while specific health or education interventions are more useful as public service-style campaigns to promote undervalued goods, such as immunizations.

A final thought

I’m generally curious how often Sen’s entitlements approach is explicitly applied to non-famine topics in development research. I’m guessing often. (A two-minute google led me to a PhD thesis called “Poverty as entitlement failures” that sounds interesting.)

Feminism contains multitudes: Annotated critique of WSJ op-ed on day care in Sweden

My annotated critique of “The Human Cost of Sweden’s Welfare State” – a poorly argued op-ed in the WSJ by psychoanalyst Erica Komisar.

Follow up research

  • Andersson, 1989: “Children with early day care (entrance before the age of 1) were generally rated more favorably and performed better than children with late entrance or home care.”
  • OECD report, 1999, p. 60: Acknowledges that children with poor immune systems or who are not good in group settings, could fare better at home or in home-style day cares (similar language to what the op-ed author uses). But points out that the increased feasibility of mothers staying home with young children for longer alleviates some concerns about mother-child early separation, giving parents flexibility to choose what option works best.
  • Another poorly supported op-ed from the Irish Times, 2011:

    “Working as a management consultant, Himmelstrand heard from women how sad they were about leaving their one-year-olds in daycare. He began to notice there were no children in the playgrounds during the day. If you walked down the street with a three-year-old toddler, people were amazed and disapproving the child was not in daycare.

    He also found educational standards were slipping in Sweden, and rates of psychological distress and psychosomatic illnesses among teens had gone up dramatically, not to mention disruptive behaviour in schools.”

  • Institute of Marriage and Family in Canada, 2015 blog post by Himmelstrand from a site with the tag line “Latest developments in family friendly research”: Not much research has been done on the Sweden day care system since the 70s and 80s. Highlights some staffing issues I saw mentioned elsewhere, as well, and again mentions the shaming of parents who don’t put their kids in pre-schools. Actually has citations, but most in Swedish and couldn’t follow-up on them.
  • Another Himmelbrand op-ed, 2013: “A study done a few years ago showed that today even socially stable middle class families have problems with their children.” Okay… that’s literally always true of any family. What kinds of problems qualify here? He doesn’t elaborate, but uses this as supposed evidence of poor parenting skills. Research in Swedish, can’t follow-up.
  • Perusing various chat boards and blogs: There does seem to be a general consensus that there’s pressure to fit in and do what other parents are doing across the board in Sweden that stands out to foreign and Swedish parents alike. And a few different posters mentioned pressure to put kids in day care, but never before age 1 unless you’re a crazy foreigner. BUT, there may be a correlation between those who post online about child care and those who feel alienated by the mainstream thought on it. So hard to judge whether the pressure is meaningful, and also whether it’s gov’t promoted or peer-enforced if it is a big deal.

Ӧzler: Decrease power to detect only a meaningful effect

Photo by Val Vesa on Unsplash

Reading about power, I found an old World Bank Impact Evaluations blog post by Berk Ӧzler on the perils of basing your power calcs in standard deviations without relating those SDs back to the real life context.

Ӧzler summarizes his main points quite succinctly himself:

“Takeaways:

  • Think about the meaningful effect size in your context and given program costs and aims.
  • Power your study for large effects, which are less likely to disappear in the longer run.
  • Try to use all the tricks in the book to improve power and squeeze more out of every dollar you’re spending.”

He gives a nice, clear example to demonstrate: a 0.3 SD detectable effect size sounds impressive, but for some datasets, this would really only mean a 5% improvement which might not be meaningful in context:

“If, in the absence of the program, you would have made $1,000 per month, now you’re making $1,050. Is that a large increase? I guess, we could debate this, but I don’t think so: many safety net cash transfer programs in developing countries are much more generous than that. So, we could have just given that money away in a palliative program – but I’d want much more from my productive inclusion program with all its bells and whistles.”

Usually (in an academic setting), your goal is to have the power to detect a really small effect size so you can get a significant result. But Ӧzler makes the opposite point: that it can be advantageous to only power yourself to detect what is a meaningful effect size, decreasing both power and cost.

He also advises, like the article I posted about yesterday, that piloting could help improve power calculations via better ICC estimates: “Furthermore, try to get a good estimate of the ICC – perhaps during the pilot phase by using a few clusters rather than just one: it may cost a little more at that time, but could save a lot more during the regular survey phase.”

My only issue with Ӧzler’s post is his chart, which shows the tradeoffs between effect size and the number of clusters. His horizontal axis is labeled “Total number of clusters” – per arm or in total, Bert?!? It’s per arm, not total across all arms. There should be more standardized and intuitive language for describing sample size in power calcs.

“Obviously” in academic writing

Academic writing is full of bad habits. For example, using words like “obviously,” “clearly,” or “of course.” If the author’s claim or reasoning really is obvious to you, these words make you feel like you’re in on the secret; you’re part of the club; you’ve been made a part of the “in” group.

But when you don’t know what they’re talking about, the author has alienated you from their work. They offer no explanation of the concept because it seems so simple to them that they simply won’t deign to explain themselves clearly to those not already “in the know.”

Part of an academic’s job is to clearly explain every argument in their papers. It is lazy and exclusionary to imply readers should already understand a concept or a path of reasoning.

At worst, it just makes you sound rude and superior:

“Advertising is, of course, the obvious modern method of identifying buyers and sellers.” – Stigler, “The Economics of Information”

He really doubled-down on how evident this fact is, which only tells the reader how smart he thinks he is. The sentence could have read, “Advertising is the preferred modern method of identifying buyers and sellers,” and could have included a citation.

On the other hand, a non-exclusionary use of “obviously”:

“Obviously, rural Ecuador and the United States are likely to differ in a large number of ways, but the results in this (and other recent) papers that show a shifting food Engel curve point to the risks inherent in assuming that the Engel curve is stable.” – Shady & Rosero paper on cash transfers to women

The authors had previously compared two papers from two very different contexts; they use “obviously” to acknowledge the potential issues with comparing these two settings. This is an acceptable use case because the statement that follows actually is obvious and is bringing any reader on board by acknowledging a possible critique of the argument. It is an acknowledgement of possible lack on the author’s part, rather than a test of the reader’s intelligence or prior knowledge.