This is from a new paper by Alicia Barriga and Nathan Fiala in World Development:
Results from the tests showed very high levels of DNA similarity (above 98%) and good performance in general, but highly variable quality in terms of the ability of the seed to germinate under standard conditions. We do not see differences in average outcomes across the distribution levels, though variation in seed performance does increase further down the supply chain.
The results of the tests point to potentially important issues for the quality of seeds. The variation in germination suggests that buying a random bag of seeds in this particular distribution chain can matter a lot for farmer’s production. The high rate of seed similarity suggests that the main concern among policy makers and researchers, that sellers add inert or low-quality material to the seeds, is likely not the case, at least for the maize sector in the districts we study. However, given the remoteness of these districts and the lack of any oversight in these areas, we believe the results are likely a lower bound for the country as a whole.
The supply chain analysis suggests that the quality of seed does not deteriorate along the supply chain. The quality is the same, on average, across all types of suppliers after leaving the breeders. However, we observe high variation of seeds’ performance results on germination, moisture, and vigor, suggesting that results are more consistent with issues of mishandling and poor storage of seeds, possibly related to temperature or quality controls, rather than sellers purposefully adulterating seeds. Variation on these indicators is usually associated with mishandling during transportation and storage.
As the authors note in the paper, African governments and their external donors have put a lot of effort in “certification and labeling so as to reduce the possibility of adulteration by downstream sellers”. Obviously, e-labels and systems of verifying seed authenticity in the fight against adulteration are important. But equally important is an understanding of how the seed distribution system works. And that is one of the major contributions of this paper. Corruption is not always the problem.
Interestingly, Uganda bests both Kenya and Tanzania on productivity in the cereal sector (I made the graph using FAO data). Despite starting off with relatively lower productivity and having gone through civil conflict beginning in the late 1970s, Uganda has since around 2007 clearly separated itself from both Kenya and Tanzania (and appears to have plateaued). Productivity in Kenya peaked in the early 1980s and has pretty much stagnated since. Tanzania’s figures appear to be trending upwards having collapsed in the early 2000s. There is likely an element of soil quality and general aridity involved in these trends. According to the FAO, Kenya and Tanzania use fertilizer at significantly higher rates than Uganda. For comparison, cereal yield in Vietnam is about 2.7 times higher than in Uganda.
Alex Tabarrok over at MR has a fantastic summary of some of the works of this year’s three Nobel Prize winners in Economics. This paragraph on one of Michael Kremer’s papers stood out to me:
My second Kremer paper is Population Growth and Technological Change: One Million B.C. to 1990. An economist examining one million years of the economy! I like to say that there are two views of humanity, people are stomachs or people are brains. In the people are stomachs view, more people means more eaters, more takers, less for everyone else. In the people are brains view, more people means more brains, more ideas, more for everyone else. The people are brains view is my view and Paul Romer’s view (ideas are nonrivalrous). Kremer tests the two views. He shows that over the long run economic growth increased with population growth. People are brains.
Here is the abstract from Kremer’s QJE paper:
The nonrivalry of technology, as modeled in the endogenous growth literature, implies that high population spurs technological change. This paper constructs and empirically tests a model of long-run world population growth combining this implication with the Malthusian assumption that technology limits population. The model predicts that over most of history, the growth rate of population will be proportional to its level. Empirical tests support this prediction and show that historically, among societies with no possibility for technological contact, those with larger initial populations have had faster technological change and population growth.
Read Tabarrok’s entire post here. Highly recommended.
Since Sunday I’ve been asking around if the Prize got any mention on local radio in Busia, Kenya — the cradle of RCTs, if you will, and where Kremer conducted field experiments. No word yet. Will report if I hear anything.
Berk Ozler over at Development Impact has a follow up post on GiveDirectly’s three-year impacts. The post looks at multiple papers analyzing results from the same cash transfer RCT in southwestern Kenya:
First, on the initial studies:
On October, 31, 2015, after the release of the HS (16) working paper in 2013, but before the eventual journal publication of HS (16), Haushofer, Reisinger, and Shapiro released a working paper titled “Your Gain is My Pain.” In it, they find large negative spillovers on life satisfaction (a component of the psychological wellbeing index reported in HS 16) and smaller, but statistically significant negative spillovers on assets and consumption. The negative spillover effects on life satisfaction, at -0.33 SD and larger than the average benefit on beneficiaries, imply a net decrease in life satisfaction in treated villages. Furthermore, the treatment (ITT) effects are consistent with HS (16), but the spillover effects are not. For example, the spillover effect on the psychological wellbeing index in Table III of HS (16) is approximately +0.1, while Table 1 in HRS (15) implies an average spillover effect of about -0.175 (my calculations: -0.05 * (354/100)). There appear to be similar discrepancies on the spillovers implied for assets and consumption in the HRS (15) paper and HS (16). I am not sure what to make of this, as HRS (15) is an unpublished paper – there must [be] a good explanation that I am missing. Regardless, however, these findings of negative spillovers foreshadow the three-year findings in HS (18), which I discuss next.
Then on the three-year findings:
As I discussed earlier this week, HS (18) find that if they define ITT=T-S, virtually all the effects they found at the 9-month follow-up are still there. However, if ITT is defined in the more standard manner of being across villages, i.e. ITT=T-C, then, there is only an effect on assets and nothing else.
… As you can see, things have now changed: there are spillover effects, so the condition for ITT=T-S being unbiased no longer holds. This is not a condition that you establish once in an earlier follow-up and stick with: it has to hold at every follow-up. Otherwise, you need to use the unbiased estimator defined across villages, ITT=T-C.
To nitpick with the authors here, I don’t buy that [….] lower power is responsible for the finding of no significant treatment effects across villages. Sure, as in HS (16), the standard errors are somewhat larger for across-village estimates than the same within-village estimates. But, the big difference between the short- and the longer-term impacts is the gap between the respective point estimates in HS (18), while they were very stable (due to no/small spillovers) in HS (16). Compare Table 5 in HS (18) with Appendix Table 38 and you will see. The treatment effects disappeared, mainly because the differences between T and C are much smaller now, and even negative, than they were at the nine-month follow-up.
And then this:
If we’re trying to say something about treatment effects, which is what the GiveDirectly blog seems to be trying to do, we already have the estimates we want – unbiased and with decent power: ITT=T-C. HS (18) already established a proper counterfactual in C, so just use that. Doesn’t matter if there are spillovers or not: there are no treatment effects to see here, other than the sole one on assets. Spillover estimation is just playing defense here – a smoke screen for the reader who doesn’t have the time to assess the veracity of the claims about sustained effects.
Bottom line: we need more research on UCTs, which GiveDirectly is already doing with a (hopefully) better-implemented really long-term study.
Well, public debt in African states is much higher if you take into account their revenue mobilization capacities. The bigger the informal sector, the lower the debt/revenues ratio.
Consider the case of Nigeria (from the FT):
Nigeria’s accumulated government debt is just 18.6 per cent of its annual economic output, one of the lowest levels in the world, implying that its debt burden is more than manageable. But is this a fair reflection of reality?
Using a different metric, the Nigerian government’s gross debt is 320 per cent of its annual revenues, according to figures from Fitch Ratings, one of the highest figures in the world and comfortably above the median of 196 per cent for countries in Africa and the Middle East that are rated by Fitch.
This is from a story in Kenya’s Standard Newspaper:
Martin Wepukhulu is a small-holder farmer in Trans Nzoia County, popularly described as Kenya’s breadbasket. To produce a two-kilogramme tin of maize known as gorogoro here, he spends about Sh25 on land preparation, seeds and fertilisers on his one-acre farm.
Some 270 kilometre away in Turkana County, one of Kenya’s poorest counties, is Loseny Nguono, a goat keeper, with two wives and 13 children. Turkana is one of the 23 counties affected by drought which has left close to 4 million people in danger of starvation.
Loseny receives Sh8,000 after every two months from the national government through the national safety net programme. He is willing to pay Martin a decent Sh70 for his gorogoro of maize. Unfortunately, neither Martin nor Loseny will get his wish. A reclusive government, ruthless cartels, dilapidated roads and marauding bandits conspire to ensure that while Martin sells his cereals at a low of Sh40, Loseny buys it at a high of Sh150.
It is great that Loseny has cash; and that unconditional cash transfers for social protection are increasingly becoming a mainstream policy option (notice that the story doesn’t even acknowledge the awesomeness of this reality). But the other lesson that we can learn from the story is that in order to get Loseny out of poverty we need good roads, properly functioning markets, and security. All these are public goods that must be provided through collective action, above and beyond the improvements in Loseny’s private consumption.
I came across Ingrid Kvangraven‘s very thoughtful review of Alternative Theories of Economic Development over at Developing Economics. The book sounds like a rehashing of the standard critiques of contemporary research in the field of development economics, some which tend to fall squarely in the caricature column. That said, caricatures can sometimes be useful in forcing us to reconsider core assumptions. In particular, I think the field of development economics has yet to deal with the problem of being “a tool-driven profession, where the tools determine the types of questions that are possible to ask as well as the type of analysis possible to carry out.”
For instance, I love most of the exciting micro work in development economics, but would certainly be interested in reading more books or papers covering big picture macro topics in developing countries. I also realize that economists from developing countries are the best-placed (in terms of incentives and access to information) to try and answer some of the big picture questions that do not always lend themselves to empirical analyses.
Here are some excerpts:
The editors also emphasize the increasing focus on methods in the field of development economics, rather than theory and history (in line with my own observation). The editors argue that the field has developed into a tool-driven profession, where the tools determine the types of questions that are possible to ask as well as the type of analysis possible to carry out. For example, as pointed out by Viner (1937), increasing returns was removed from international trade theory because it was not compatible with equilibrium. As Paul Krugman (1991) puts it: Economics came to “follow the line of least mathematical resistance”.
The editors also find that the basic fact of uneven development tends to be reduced to models of “dualism,” which implies less attention to the differentiation internal to sectors, and patterns of interaction of different groups of classes within and across sectors. Furthermore, when it is discovered that certain institutions are different from “the norm” in developing countries, they are highlighted and explained using the same basic analytical tools developed for the norm. This type of Economics is what the editors call a National Geographic view of the broader process of development, as only snapshots of particular institutions or economic activities are separated for the analysis.
Angus Deaton of Princeton University has won the Nobel Prize in Economics. Tyler Cowen over at MR summarized Angus Deaton’s immense contribution to the study of consumption, human welfare, and development:
A brilliant selection. Deaton works closely with numbers, and his preferred topics are consumption, poverty, and welfare. “Understanding what economic progress really means” I would describe as his core contribution, and analyzing development from the starting point of consumption rather than income is part of his vision. That includes looking at calories, life expectancy, health, and education as part of living standards in a fundamental way. I think of this as a prize about empirics, the importance of economic development, and indirectly a prize about economic history.
Think of Deaton as an economist who looks more closely at what poor households consume to get a better sense of their living standards and possible paths for economic development. He truly, deeply understands the implications of economic growth, the benefits of modernity, and political economy. Here is a very good non-technical account of his work on measuring poverty (pdf), one of the best introductions to his thought.
Deaton’s book, The Great Escape: Health, Wealth, and the Origins of Inequality is a must read for those interested in development.
Some readers of the blog may recall Deaton’s summer square off with Rwanda’s Health Minister Agnes Binagwaho over his comments on the Boston Review blog.
Deaton’s selection is a timely nod to the study of BIG PICTURE development.
This paper examines the extent to which locally informed intermediaries can be exploited and provided with incentives to change the health-seeking behavior of pregnant women in rural Kenya. Despite Kenya being the largest and most advanced economy of East Africa, maternal and infant health outcomes are typical for those of other sub-Saharan countries, which lag significantly behind the developed world. There is evidence that antenatal care (ANC) is associated with improved maternal health outcomes, yet the majority of women in rural Kenya fail to meet recommendations for ANC timing and use, despite the availability of government subsidized healthcare. I examine whether a local intermediary, whose own incentives might oppose those of the government, can be co-opted to assist the government’s objective of increasing women’s ANC utilization.
I use a randomized controlled trial (RCT) to evaluate a program, which provides financial incentives for TBAs to encourage pregnant women to seek ANC at a formal medical facility. Competition between the TBAs and the formal clinics makes the effect of the program an empirical question, as there is no guarantee that the TBAs will respond to the incentive.
I find that living in a TBA treatment village increases the likelihood of attending the recommended number of visits by 20.7%. Women living in TBA treatment villages are 4.4 percentage points more likely to attend the recommended number of visits than women living in control villages, who attend the recommended number of visits 21.3% of the time. The results of this experiment, the first to study the extent to which TBAs can be motivated to encourage women to attend the prenatal clinic, could have important policy implications. The program’s success suggests that despite having a risk of losing clients, TBAs can be utilized as intermediaries of health facilities. Furthermore, finding that TBAs can induce pregnant women to attend ANC visits indicates that cultural norms, which discourage women going to ANC visits, can be overcome with relatively small financial incentives. By increasing the demand for formal maternal healthcare, TBAs’ encouragement of ANC attendance by women may help achieve improved maternal and child health outcomes.
That’s Georgetown’s Nisha Rai, in an excellent paper on the possibilities of integrating the use of traditional birth attendants with the formal healthcare system in Kenya (and developing countries in general). You can find a summary of the paper at the Bank’s Development Impact blog here.
If you know a policymaker in the health ministry of a developing country, please have them read this paper.
What is the cost of not having economic history at MIT? It can be seen in Acemoglu and Robinson, Why Nations Fail (2012). This is a deservedly successful popular book, making a simple and strong point that the authors made originally at the professional level over a decade before (Acemoglu, Johnson and Robinson, 2001). They assert that countries can be “ruled by a narrow elite that have [sic] organized society for their own benefit at the expense of the vast mass of people” or can have “a revolution that transformed the politics and thus the economics of the nation … to expand their economic opportunities (Acemoglu and Robinson, 2012, pp. 3-4).”
The book is not however good economic history. It is an example of Whig history in which good policies make for progress and bad policies preclude it. Only transitions from bad to good are considered in this colorful but still monotonic story. The clear implication is that if countries can copy the policies of English-speaking countries, they will prosper. No consideration is given to Britain’s economic problems over the past half-century or of Australia’s relative decline for a century.
Also, to be honest, one of the reasons I am into development (and the politics around it) is because of my fascination with economic history. I wish more development practitioners and theorists alike cared a little bit more about economic history. At the very least, looking at how things really actually worked out in the past serves to temper the urge to completely fall for the latest fad within the development industry.
Nigerian Ngozi Okonjo-Iweala is definitely the dream candidate for the Bank. But the realities of U.S. domestic politics and foreign policy concerns are stacked against her nomination to the presidency of the Bank. It will be hard for the U.S. to selflessly relinquish an important tool of foreign policy and influence in the Bank’s presidency.
If Obama backs down, he will be criticized for being soft in the face of international pressure. If he nominates a non-American, he will still be criticized as an apologist for those who hate America (real or imagined) and a believer in American decline.
Obama’s incentive is to get his nominee become World Bank President. Full stop.
So far those rooting for Ngozi (including yours truly) have questioned Jim Yong Kim’s credibility (he is/was not a fan of neo-liberalism) and competence (he is not an Economics PhD; but a mere MD, PhD) as World Bank president.
Here is quoting a post over at the Duck of Minerva for a more balanced take:
If Dr. Kim criticized the growth agenda of the structural adjustment era, so what? This has all become mainstreamed into the Bank’s own philosophy of pro-poor growth.Does it take a PhD in Economics to run the World Bank successfully? If selected, Dr. Kim would be the leader with the most hands-on development experience that the Bank has ever possessed. He would be as or more experienced in the field as serious contenders that were mooted in advance like Susan Rice, Hillary Clinton, or Pepsico CEO Indra Nooyi (ok, maybe Larry Summers knows more but Summers always know more than anybody). As Daron Acemoglu and Jim Robinson pointed out on their blog [Why Nations Fail]: “Perhaps all of Mr. Kim’s critics prefer the status quo where the World Bank is run by ex-warmongers (Robert McNamara), bankers (James Wolfensohn) or career civil servants (Robert Zoelick). Wait wasn’t that the World Bank that they loved to criticize?”
You don’t have to denigrate Dr. Kim to praise the other candidates. The strongest case is that while Dr. Kim is a good candidate, Dr. Okonjo-Iweala is the dream candidate. She’s from a large developing country, knows the issue well, understands the complex world of global finance, and is intimately familiar with the culture and organization of the Bank. And, for her supporters, the changing nature of the international system has made this practice of the U.S. having the automatic right to appoint the Bank’s president an anachronism.
The Economist has joined a string of internet commentators in endorsing Nigerian Minister of Finance to become the next president of the World Bank. Contrasted against the resume of Obama’s choice for the Bank, Ngozi wins. By miles.
According to the Economist:
The World Bank is the world’s premier development institution. Its boss needs experience in government, in economics and in finance (it is a bank, after all). He or she should have a broad record in development, too. Ms Okonjo-Iweala has all these attributes, and Colombia’s José Antonio Ocampo has a couple. By contrast Jim Yong Kim, the American public-health professor whom Barack Obama wants to impose on the bank, has at most one.
However, it is interesting that in all the debate no one has talked about HOW Ngozi will change the Bank’s operations, besides insinuations that she has hands on experience in transforming Nigeria’s public finances, coupled with her previous experience at the Bank.
More importantly, what would be the cost to Nigeria if they lose Ngozi? Is this important at all?
Ngozi leading the bank will probably make a difference. However, I think that support for her candidacy has thus far been too one-sided. Nigeria, like much of the developing world, does not have much influence on the Bank’s board. Nigeria also stands to lose one of its ablest technocrats just when it is striving to reform its public finances. These considerations should matter too, I think.
Just for the record, I am one of those who think that it would be really cool to have Ngozi lead the Bank (despite the fact that she probably will not).
Update: I just came across some interesting thoughts on Ngozi’s nomination over at Africa is A Country (H/T Chad).
Baird, McIntosh and Ozler have an upcoming paper in the QJE investigating the differential impacts of conditional and unconditional cash transfer in Malawi:
Starting with schooling outcomes, we find that although dropout rates declined in both treatment arms, the effect in the UCT arm is 43% as large as that in the CCT arm. Evidence from school ledgers for students enrolled in school also suggests that the fraction of days attended in the CCT arm is higher than the UCT arm. Using independently administered tests of cognitive ability, mathematics, and English reading comprehension, we find that although achievement is significantly improved in all three tests in the CCT arm compared with the control group, no such gains are detectable in the UCT arm. The difference in program impacts between the two treatment arms is significant at the 90% confidence level for English reading comprehension. In summary, the CCT arm had a significant edge in terms of schooling outcomes over the UCT arm: a large gain in enrollment and a modest yet significant advantage in learning.
The paper then gets nuanced:
When we turn to examine marriage and pregnancy rates, however, unconditional transfers dominate. The likelihood of be- ing ever pregnant and ever married were 27% and 44% lower in the UCT arm than in the control group at the end of the 2-year intervention, respectively, whereas program impacts on these two outcomes were small and statistically insignificant in the CCT arm.
……….. Our findings show that UCTs can improve im- portant outcomes among such households even though they might be much less effective than CCTs in achieving the desired behav- ior change.
Check it out here.
I doubt my microeconomics prof. (Kyle) reads this blog so I am gonna go ahead and quote a section of an email he just sent out (which also just made my evening):
For fun for those of you still reading, you can find a lyrical justification of monotonicity in consumer choice in the song Society by Jerry Hannan. This was covered by Eddie Vedder of Pearl Jam for the film Into the Wild. The free version can be listened to here jerryhannan.com. The justification is contained in this stanza:
“There’s those thinking, more or less, less is more
But if less is more, how you keepin’ score
Means for every point you make your level drops
Kinda like you’re starting from the top
You can’t do that.”
QED. There you go. An indie folk proof for rational preferences.
Here’s Jerry Hannan’s “Society” on youtube:
Rodrik has a finding that reinforces the importance of politics and other macro conditions for economic development. He points out the existence of the paradox of unconditional convergence at the industry level but not at the national level. Rodrik stresses the importance of structural change that channels labor into the right industries. To this we should add political change that provides certainty and the requisite legal and physical infrastructure for economic growth.
Industries that thrive in poorly run places – like telecoms, banks and construction firms in Nigeria or Kenya’s retail giants – do so despite their governments. Non-existent roads, underdeveloped railway systems, sporadic and expensive electricity, bad schools, legal uncertainty and massive amounts of political risk all serve to limit the extent to which within-industry gains can be extended to other sectors.
The massive uptake of mobile telephones across Africa suggests that consumerism in SSA is alive and well, just under-exploited. Sectors like textiles, agriculture and construction remain largely untouched because of cheap imports and bad regulation.
Development is a complex enterprise that requires massive amounts of (implicit) coordination. There has to be a link between California’s Silicon Valley, Massachusets’ Route 128 and New York’s Wall Street, in addition to other growth clusters. In this game synergy is King. The provision of the legal, human capital and physical infrastructure to facilitate coordination of this scale is largely dependent on well-functioning governance structures.
Poor countries have access to new technologies already developed elsewhere so should grow more rapidly than richer economies. This is one of the implications of standard growth models, as well as of common sense.
But in reality, there is no automatic tendency for economic “convergence” among countries at different levels of income. Convergence depends instead on a number of additional determinants. It is only those developing nations with the “appropriate” preconditions – for example, adequate schooling or physical investment – that manage to absorb new technologies sufficiently rapidly and therefore to catch up. In the language of growth economics, there is conditional convergence, but not unconditional convergence.
When we look at the same question at the level of individual industries rather than countries a surprising finding emerges. Suppose we focus on, say, plastics, furniture, or the auto industry in developing countries. Does productivity in these (and other) industries experience automatic convergence with the technological frontier? Or is convergence once again conditional, depending on a host of country-level variables?
The interesting (and I think new) finding is that productivity convergence appears to be unconditional at the industry level – at least for manufacturing industries and for the period since the 1980s.