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  • Reply to: The importance of study design (why did a CCT program have no effects on schooling or HIV?)   15 hours 34 min ago
    Thanks for the comment.

    On the issue of you changing your mind, obviously that is not necessary: given theory and other extant evidence, the findings from one extra study may do very little to change our priors about a causal relationship - that's OK. What is not OK, however, is to have a sentence on the first page of the paper (under the Interpretation sub-section of the Summary) that goes: "Keeping girls in school is important to reduce their HIV-infection risk." This does not follow from your RCT. Put in other words, if this paper can make that statement in its abstract, so can any other paper that contains data on HIV and school enrollment status. Even if the authors put that sentence in the abstract, the editor should not have allowed it. I thought that biomedical journals were much better at sticking to a reporting template and minimizing speculation.

    On hindsight being 20/20, sure, that is true. However, it's hard to chalk up the large number of things that accumulated to produce the null results as coincidental and all due to back luck - some of it, such as study setting and eligibility for the target population could have certainly been adapted between conception in 2008-09 and the actual start of recruitment in 2011 (about five years prior to eventual publication). Similarly, UCTs could be part of the trial...

    Finally, yes, potential impacts on gender-based violence are important. But, the paper disinuguishes itself from the rest of the literature by its focus on HIV incidence, rather than self-reported sexual behavior or HIV prevalence. Then, the findings on the secondary outcomes must be subject to the same scrutiny on self-reported outcomes elsewhere in the literature.


  • Reply to: The importance of study design (why did a CCT program have no effects on schooling or HIV?)   16 hours 28 min ago

    Hi Berk
    Thank you for your commentary. I certainly will say in this case hindsight is 20/20. When we first started designing this trial in 2008/2009 we knew a few things: 1) there was a pretty strong evidence base that CCTs increased school attendance, esp for girls; 2) our formative research in South Africa showed that completing high school was associated with lower HIV prevalence in young South African women (we can debate how that is not the same at attendance or incidence); 3) we were working in a very poor area of South Africa; 4) that formative qualitative work suggested that financial barriers were significant contributors to girls dropping out of school and 5) school attendance among 16 and older girls was around 80%.

    So things we DID debate beforehand:
    1) Is South Africa the right place to do a CCT trial based on school attendance? Yes attendance and enrollment are very high in South Africa- much higher than in other parts of the region. That said there was still pretty significant drop out in the later years after mandatory schooling and schooling appeared to be protective against HIV. Given this we felt the question was still valid. Perhaps we need to consider if CCTs for schooling are only really useful in low attendance areas (what is that cutoff?)

    2) Yes we knew that the area was poor but didn't actually know how many homes were getting the Child Support Grant. That said, we did think that providing cash to the adolescent girls themselves (something the CSG does not do) would make a difference. And given that the amount we gave to the girls and household member is equivalent to expenditure per capita (and the CSG) it seemed it would make a difference. Maybe it was not enough- we can discuss actually if any amount of cash is ever enough in some settings where self-esteem and fitting in are being derived from material/aspirational goods and survival sex is less prevalent.

    3) Cluster randomized vs individual- yes, we did feel the individual trial offered greater power for an HIV incidence outcome BUT we also felt that the main mechanism through which the trial would impact HIV was through schooling and that the reason girls were not attending school was financial. If the reason they were not attending was financial then in theory peer effects should not have impacted attendance. We have a forthcoming paper by Rosenberg et al. showing that there were Hawthorne and selection effects in the cohort over time. We did not anticipate this. Our study did have pretty minimal contact with participants and little educational components compared to many HIV prevention trials.

    4) Regarding differential retention- yes, we should have better anticipated that the control group in an individual randomized trial would not be happy about getting the control arm (that said in our pilot study people said they were ok with being randomized to the control arm). Either way, I do think some girls who we lost basically decided to drop out of the study as soon as they opened the envelope and saw that they were in the control arm. We had very intensive retention procedures (can talk about all the various things we did to make attending assessment visit attractive), followed people when they moved, dropped out, no matter the outcome and have outcomes for almost everyone originally enrolled- it was that they refused to come back. Cluster randomization might have helped reduce the differential. We did conduct inverse probability weights to account for this and the result did not change.

    5) We have 3 papers in submission right now examining school attendance and HIV incidence with robust longitudinal methods. There seems to be very strong evidence that school attendance is protective against HIV and we have explored the mechanisms through which schooling is protective and the results are not surprising but I think are robust and add to the evidence base that schooling is protective.

    6) the CCT did have important impacts on gender based violence and we also have a paper in submission exploring pathways through which the intervention reduced physical violence from male partners among girls getting the cash. The results are also important.

    So...not sure where I need to change my mind. I still do think staying in school reduces HIV risk. That said, are CCTs the most effective intervention to reduce HIV in young girls in this area in South Africa?- probably not. And I agree that UCTs for older girls may be more effective for this purpose. Of course this is almost 10 years after we conceived of the study and have learned a lot about cash transfers and HIV risk in that time. If only we had all this knowledge when we embarked on the trial 10 years ago :)

  • Reply to: Is bigger better? Agriculture edition   1 day 17 hours ago

    A broad comment on farm productivity and family welfare.

    When interpreting the debate over productivity and farm size, we should recognize that the welfare implications at the household level (not the farm as production unit) depend on a wider context of rural income sources, level of development, and importantly the opportunity cost of management and family labor dedicated to the farm. The situation in sub-Saharan Africa is likely very different than that of middle-income countries in Latin America. The analysis based on land productivity tends to overlook that, while smaller farmers might have higher land productivity, total income generated by the farm would not allow the family to exit poverty. Out-migration or diversifying farm family labor off-farm is one way of increasing total income; the other is to expand farm size. Both are occurring in high- and middle-income countries. By contrast, according to Hazell, farm size in low-income countries is shrinking. One could be seeing both an increase in land productivity and a stagnation in household welfare.

  • Reply to: Is bigger better? Agriculture edition   5 days 7 hours ago

    Research about measuring agricultural productivity is hugely important, but can I ask why we're still talking about the farm size-productivity relationship? Redistributive land reform isn't a policy issue anymore. Large scale agricultural investment is, but variations in productivity over the existing land distribution would tell us very little about how an investor with vastly different access to capital and technology would fare. Not to mention, does anyone expect that we're going to find a farm size-productivity relationship that's generalizable across contexts in any meaningful way?

    Meanwhile, there is still hundreds of millions of dollars being spent on research looking at agricultural productivity using household-survey based measures. It would be tremendously valuable to know what these findings say about that- are there adjustments that should be made to these datasets? Do we need to be using higher-cost approaches to measurement, with fewer studies as a result?

  • Reply to: Is bigger better? Agriculture edition   5 days 12 hours ago

    I was at a recent conference on structural transformation at Yale, at which Andrew Foster and Mark Rosenzweig presented a new (not yet) paper called Input Transaction Costs, Mechanization, and the Mis-allocation of Land: The Irrelevance of the IR. They've been working on this topic for a while and across a series of different papers, but the punchline here is that there's a U shaped relationship that is generally missed because surveys don't measure enough farms above 10 acres, which is where increasing returns to scale start to kick in in their data. They rationalize this with a model of fixed costs in hiring outside labor but also increasing returns to scale in capital (think bigger, more efficient tractors) that generate first a part of the farm size distribution with decreasing returns as farmers switch from inside to outside labor, then increasing returns as they mechanize more and more.