In a nutshell

Program description

There are two types of cash transfer programs:

• Conditional cash transfers (CCTs), in which recipients receive cash only if they fulfill various requirements such as rates of school attendance or visits to health centers. There is a subset of CCTs in which the conditions are announced but are not formally monitored, so all participants receive a transfer regardless of compliance with the announced conditions.1
• Unconditional cash transfers (UCTs), in which selected participants receive funds without a requirement to meet additional conditions.

We have written up results relevant to the impacts of both UCTs and CCTs. Because of our interest in a group which conducts UCTs, we are particularly interested in study results which are more directly relevant to UCTs.

The appeal of cash transfers

Cash transfers are potentially attractive for individual donors because they allow the recipients of charity to choose how to spend funds allocated for them. Provided that local markets can supply it, if the recipients feel that they need food, they can use their cash to purchase it; if they need medical care, they can buy it. As we wrote in 2009:

Program track record

Summary

Below is a full list of the programs evaluated by randomized controlled trials (RCTs) that we found.2 This list includes basic information about the program and key findings from the RCT that studied the program. In the following sections we provide more detail on the studies and their findings.

A more detailed version of this table is available here (XLS); we also discuss each of these studies further below.

Micro evidence: Has this program been rigorously evaluated and shown to work?

The high-quality evidence on cash transfers is generally encouraging, showing meaningful impacts on consumption. We review 7 programs below: studies of four programs report measures of food consumption and studies of another two programs report measures for general consumption; all reported consumption measures are substantial and significant. We have not found consistent impacts on health or education (we did not consider health or education effects in programs where payments were conditional on health or education decisions).

For all tables, statistical significance is reported as follows: no stars is not statistically significant, one star indicates p<.1, two stars indicates p<.05, three stars indicates p<.01. For all impacts, unless otherwise listed, the impact refers to the relative treatment effect, i.e., the difference in outcome measures between intervention and control groups.

Unconditional transfers

We identified only one RCT of an unconditional cash transfer program (UCT): the Zomba cash transfer program. The treatment group was divided into two groups, one that received a CCT requiring school attendance, and another that received a UCT.

The study, discussed in four different papers to date, found the following impacts (sources in below table):

• Education: Receiving an unconditional cash transfer increased school enrollment by an average of .231 terms over a six-term period; no effect on attendance was detected.
• Marriage: Amongst girls who were dropouts at the start of the study, those offered a CCT were 11.3 percentage points (40.8%; p<0.01) less likely to be married at follow-up than those offered no treatment. There was no statistically significant impact on participants offered a CCT who were schoolgirls at the start of the study.
• Pregnancy: Amongst girls who were dropouts at the start of the study, those offered a CCT were 5.1 percentage points (31.5%25; p<0.05) less likely to be pregnant at follow-up than those offered no treatment. There was no statistically significant impact on pregnancy for those participants offered a CCT who were schoolgirls at the start of the study.
• Psychological effects: Among schoolgirls, during the study, there were significant differences in psychological distress: the CCT group experienced 6.3% less distress, and the UCT group experienced 14.3% less distress; both effects and the difference between them are statistically significant (p<0.05).

All results below are for the full group of participants, ages 13-22. The results are reported in proportions (except where noted) for the control group, and the results for the CCT and UCT participants are as compared to the control group results. So, for example, .047* (CCT), .039 (UCT), and .791 for control means that the control group results were 79.1%, the CCT results are 79.1%+4.7% and the UCT results are 79.1%+3.9%. In cases where outcomes were measured in standard deviation units, the interpretation of the impact does not depend on the control, which will generally be approximately 0 (i.e. the mean).

Unmonitored CCTs

There are two examples of RCTs for CCTs without monitoring. In other words, though the program was originally intended to be a normal, monitored CCT, the participants received cash whether or not they met the “required” conditions. Unmonitored CCTs may allow for a better comparison to UCTs than do the normal CCTs.

Note that results from these studies pertaining to the effect of transfers on consumption are discussed below.

Bono de Desarrollo Humano

Although the program did not impose any explicit conditions,43 many participants believed that they needed to meet conditions to obtain funds.44

The program was studied via two methods: a sample of households with poverty scores around the first quintile were studied with a randomized controlled trial, and a regression discontinuity analysis was conducted at the program's cutoff point (the second quintile of the poverty index).45

Summary of impacts:

• School enrollment: About 10% greater enrollment than in control group for the poorest quintile. No effect for the second quintile.
• Health: No statistically significant effects.
• Child labor: No statistically significant effect on total hours of work, but children who were selected to participate in the the program were 8 percentage points less likely to have engaged in economic activity within the past 7 days.

Programa Apoyo Alimentario

Programa Apoyo Alimentario compared a group that received cash transfers to a control group. The study also compared two groups that received in-kind transfers of food; results from those groups are not presented here.97 The participants’ fulfillment of conditions was not monitored.98 All impacts in the table represent ordinary least squares differences-in-differences, though units vary.99

The only statistically significant impact from the cash transfers on non-consumption measures was on the frequency of self-reported sickness, which was 9 percentage points less common for the treatment group. Slightly positive impacts were noted on height, anemia and weight as well.

Unconditioned impacts from CCTs

CCTs often measure a range of impacts, from enrollment in schools to information on nutritional intake, some of which are not conditional.109

Atencion a Crisis conditioned only on education but also found impacts for health, which are presented here, and consumption, which are presented below.

For Atencion a Crisis, statistically significant impacts were found on: consulting a doctor if sick, weight in last 6 months, and receiving vitamin A and deworming drugs in the last 6 months. The impact sizes range from 5-8.6%.

Atencion a Crisis:

Data on consumption (from CCTs)

It appears that while food consumption and overall consumption is higher in the treatment groups across the board, the size of the impact varies. Because of the differences in how the consumption impacts are reported across the studies, it is not possible to make a statement of the average treatment effect per unit of cash transferred.

We have compiled the data on consumption that we found in the chart below.

Longer-term effects of cash transfers

A study of long-term effects of Oportunidades presents data on several long-term measures, comparing the treatment group (which received transfers for 5.5 years, from 1998 to 2003) to a group which was initially a control group but started receiving transfers 18 months after the treatment group did (1999 to 2003).148

The study presents data on the following long-term outcomes:

• Long-term income: The group receiving 18 additional months of transfers showed 9.6% higher agricultural income than the other group and 5.7% higher consumption.149 The study also provides long-term changes in income from transfers, home production, money borrowed and outside income. It finds statistically significant changes in income from home production only.150 The study does not provide data on total long-term income.
• Long-term consumption: The group given 18 extra months of transfers showed a 5.6% higher level of total consumption than the other group.151

Oportunidades:

CCTs impact on health outcomes

The Cochrane review’s conclusion on CCTs specifically on health outcomes is:

Looking at non-health outcomes, we see mixed effects on school enrollment (ranging from little effect for some age groups for Opportunidades to an impact of 12.8% for all ages for RPS).156

Macro evidence: Has this program played a role in large-scale success stories?

A few low and middle income countries have social entitlement programs that take the form of unconditional cash transfers. South Africa, for instance, has an Old Age Pension program that provides substantial cash transfers (more than twice the median income per capita for African households) to retirees.157 Including both the Old Age Pension and other programs, social support in South Africa makes up more than two thirds of the income of the bottom income quintile.158 There is some non-experimental evidence that unconditional cash transfers in South Africa have improved the health status (weight and height for age) of children.159

How cost-effective are cash transfers?

We do not have information about the cost-effectiveness of cash transfers as compared to other interventions.

On a per-person basis, cash transfers are costly relative to the health interventions we recommend most strongly. For instance, GiveDirectly, a cash transfer charity, gives poor households $1,000 over two years. For the Against Malaria Foundation (AMF), purchasing and distributing a single long-lasting insecticide-treated bed net costs approximately $5.50. Therefore, for the cost of Give Directly's transfer, AMF could provide 181 bednets covering approximately 326 people with nets for a little over 2 years.160 We believe that each person receiving a cash transfer likely benefits much more than they would from a bed net, but we doubt that they benefit proportionally to the higher cost.

Recommendations and concerns

What are the potential downsides of the intervention?

There are a few potential adverse effects of cash transfers:

• Inflation: a sudden injection of cash into an area may cause inflation. We have seen one paper investigating this issue, on Programa de Apoyo Alimentario. No significant effect on inflation was found. The program distributed cash to some villages and in-kind transfers to others. The size of the transfer was about 150 pesos per month161, which is 11.5% of per capita expenditure.162 In the villages randomly selected to receive cash transfers, 89% of villagers received them.163 The research used surveys of stores and households to measure prices of goods at baseline and one year after the cash transfers began.164

  The study reports the average prices of goods in villages where cash transfers are given compared to the price in control villages. The only price differences reported are for goods that are the same ones distributed by the program's in-kind arm (including goods such as flour, rice and beans)165 The price for these goods was 2.7% higher in villages receiving cash transfers than in control villages, after one year. The results were not statistically significant.166

  The authors measure whether there is a correlation between the remoteness of the village and the price effects.167 They find a positive correlation between remoteness and higher price inflation in villages where cash transfers are given, but the effect is not statistically significant.168

  One major question we have about the study is why the authors do not compare the prices of all goods (rather than just the prices for goods distributed by the in-kind arm), since they also measured the prices of many other goods.169

• Cash transfers could be used for alcohol or drugs, which may have adverse effects. Note that some in-kind aid may also lead to increased alcohol and drug purchases.

  The two randomized controlled trials that report spending on alcohol do not seem to find large increases due to cash transfers.170

• Cash transfers could discourage wage-earning work by adults. If adults can control the distribution of their work and leisure time, cash transfers may lead them to substitute some leisure for work, leading to a decrease in wages earned (but most likely not a decrease in overall income). Studies examining this question have, with one exception, not found that receiving cash transfers decreases adult wage-earning.171
• Giving cash to some and not others could possibly cause social unrest. We haven’t seen literature discussing this issue.
• Diversion of transfers to wealthier individuals. Certain types of aid (food aid, for example) have been documented to be stolen by well-off individuals rather than going to the intended recipients. It’s not clear to us whether this problem would be more or less of an issue in the case of cash transfers, and we would guess that the extent of the problem depends heavily on the method of making transfers.

What versions of the intervention are best?

There has been one RCT comparing physical cash transfers with electronic transfers to a recipient's cell phone.172 The study found that transferring money to cell phones was cheaper than transferring physical cash to individuals, though the initial cost of the cell phones made the cell phone transfer more expensive than handing out cash. Had the study continued longer, the cheaper ongoing costs of the cell phone transfer mechanism would have made up for the higher initial costs.173 The study also finds that recipients of the cell phone transfer recipients had to walk less than 25% as far, on average, as those who received physical cash in order to “cash out” their transfers (0.9 vs. 4.04 km).174 The cell phone transfers also appear to have increased the diversity of crops grown and consumed by people who received them, relative to the “placebo” group that just received physical transfers and a cell phone.175 The study did not find any adverse effects of using cell phone transfers relative to handing out physical cash.

Our process

• We searched google and JSTOR for the following phrases:
  • Cash transfers
  • Cash transfers meta-reviews
  • Cash transfer literature review
  • Unconditional cash transfers
  • Conditional cash transfers
  • Do cash transfers cause inflation?
  • Effects of cash transfers
• Read all meta-reviews closely, searched for additional papers published after the two main meta-reviews were published.
• Wrote up all results from RCTs, and continued to add new papers that were published during the course of the writing of this review.

We relied on two major meta-reviews in our research on CCTs: a World Bank review176 and a Cochrane review.177 Of the meta-reviews that we found, we relied on these two because they included a high percentage of RCTs and they presented the data from the studies clearly.

• Selection criteria: the World Bank review doesn’t include criteria for inclusion. The Cochrane review’s criteria are:

• In our research on UCTs, we found a chart summarizing the types of studies done on various programs prior to 2008. The methodologies of the studies are listed, and none of them are RCTs.179
• The Zomba cash transfer program, which is not included in the table because the results were published after 2008, is the only UCT program studied through an RCT that we have found, and it seems to be the only one done so far. There are several reasons to believe this:
  1. The Zomba cash transfer program study states that there has not been any similar experiment conducted previously.180
  2. A list of UCT programs in a meta-review that we found describes the methodology of each, and none of them are RCTs.181
  3. No other meta-reviews with sections on UCTs mention RCTs, and if there were further RCTs, we would expect the meta-reviews to point to them.182

Sources

• Adato, Michelle and Lucy Bassett. 2008. What is the potential of cash transfers to strengthen families affected by HIV and AIDS? A review of the evidence on impacts and key policy debates (PDF). Joint Learning Initiative on Children and HIV/AIDS.
• Aguero, Jorge M., Michael R. Carter, and Ingrid Woolard. 2009. The impact of unconditional cash transfers on nutrition: The South African child support grant (PDF). Working Paper.
• Aker, Jenny C., et al. 2011. Zap it to me: The short-term impacts of a mobile cash transfer program (PDF). Working Paper 268. Washington, D.C.: Center for Global Development.
• Angelucci, Manuela and Giacomo De Giorgi. Indirect effects of an aid program: How do cash transfers affect ineligibles' consumption? American Economic Review 99(1): 486-508.
• Baird, Sarah, Craig McIntosh, and Berk Ozler. 2011. Cash or condition? Evidence from a randomized cash transfer program. (PDF). This is the updated version of a working paper initially published as Policy Research Working Paper 5259. Washington, D.C.: The World Bank.
• Baird, Sarah, Jacobus de Hoop, and Berk Ozler. 2011. Income shocks and adolescent mental health (PDF). Policy Research Working Paper 5644. Washington, D.C.: The World Bank.
• Baird, Sarah et al. 2009. The short-term impacts of a schooling conditional cash transfer program on the sexual behavior of young women (PDF). Policy Research Working Paper 5089. Washington, D.C.: The World Bank.
• Baird, Sarah et al. 2012. Effect of a cash transfer programme for schooling on prevalence of HIV and herpes simplex type 2 in Malawi: a cluster randomised trial. The Lancet.
• Cunha, Jesse. 2011. Testing paternalism: Cash vs. in-kind transfers. (PDF). Working Paper.
• Cunha, Jesse, Giacomo De Giorgi and Seema Jayachandran. 2011. The Price Effects of Cash Versus In-Kind Transfers (PDF).
• Department for International Development. 2011. Cash transfers (PDF). DFID Evidence Paper.
• Duflo, Esther. 2003. Grandmothers and granddaughters: Old age pensions and intrahousehold allocation in South Africa. World Bank Economic Review 17(1): 1-25.
• Edmonds, Eric V. and Norbert Schady. 2011. Poverty alleviation and child labor (PDF). Forthcoming in American Economic Journal: Economic Policy.
• Fiszbein, Ariel and Norbert Schady. 2009. Conditional cash transfers: Reducing present and future poverty (PDF). Washington, D.C.: The World Bank.
• Gertler, Paul, Sebastian Martinez and Marta Rubio-Codina. 2012. Investing cash transfers to raise long-term living standards (PDF). American Economic Journal: Applied Economics 4(1): 1-32.
• Jaspars, Susanne and Paul Harvey. 2007. A review of UNICEF’s role in cash transfers to emergency affected populations (PDF). EMOPS Working Paper. New York: UNICEF.
• Lagarde, Mylene, Andy Haines, and Natasha Palmer. 2009. The impact of conditional cash transfers on health outcomes and use of health services in low and middle income countries. Cochrane Database of Systematic Reviews 2009, Issue 4. Summary available at http://www2.cochrane.org/reviews/en/ab008137.html (accessed October 7, 2011). Archived by WebCite® at http://www.webcitation.org/62Gez6Ow2.
• Macours, Karen, Norbert Schady, and Renos Vakis. 2008. Cash transfers, behavioral changes, and the cognitive development of young children: Evidence from a randomized experiment (PDF). Policy Research Working Paper 4759. Washington, D.C.: The World Bank.
• Maluccio, John A., and Rafael Flores. 2005. Impact evaluation of a conditional cash transfer program: The Nicaraguan Red de Protection Social (PDF). Research Report 141. Washington, D.C.: International Food Policy Research Institute.
• Oosterbeek, Hessel, Juan Ponce, and Norbert Schady. 2008. The impact of cash transfers on school enrollment: Evidence from Ecuador (PDF). Policy Research Working Paper 4645. Washington, D.C.: The World Bank.
• Paxson, Christina and Norbert Schady. 2007. Does money matter? The effects of cash transfers on child health and development in rural Ecuador (PDF). Policy Research Working Paper 4226. Washington, D.C.: The World Bank.
• Schady, Norbert and Jose Rosero. 2007. Are cash transfers made to women spent like other sources of income? (PDF). Policy Research Working Paper 4282. Washington, D.C.: The World Bank.
• Skoufias, Emmanuel, Mishel Unar, and Teresa González-Cossío. 2008. The impacts of cash and in-kind transfers on consumption and labor supply: Experimental evidence from rural Mexico (PDF). Policy Research Working Paper 4778. Washington, D.C.: The World Bank.
• World Health Organization. World malaria report (2011) (PDF).
• Woolard, Ingrid and Murray Leibbrandt. 2010. The evolution and impact of unconditional cash transfers in South Africa (PDF). Working Paper.
• Yablonski, Jennifer and Michael O’Donnell. 2009. Lasting benefits: The role of cash transfers in tackling child mortality (PDF). London: Save the Children.

• 1.

  See Bono de Desarrollo Humano (BDH) and Programa Apoyo Alimentario in the programs table below.

• 2.

  The only program with an RCT that we know about which we left out is a program which is gives cash to recipients for going to get the results of HIV tests. See Lagarde et al. 2009, Pg 17.

• 3. Transfer as % of per capita expenditures among all beneficiaries. Per capita expenditures are a measure of consumption. Fiszbein and Schady 2009, Pg 84.
• 4. Fiszbein and Schady 2009, Pg 268.
• 5. “Conditions:
  • Health
    • Compliance by all household members with the required number of preventive medical checkups.
    • Attendance of family member older than 15 years at health and nutrition lectures.
  • Education
    • School enrollment and minimum attendance rate of 80% monthly and 93% annually.
    • Completion of middle school.
    • Completion of grade 12 before age 22.”

  Fiszbein and Schady 2009, Pg 268.

• 6.

  Fiszbein and Schady 2009, Pg 19. Elsewhere, Fiszbein and Schady report figures for Oportunidades as high as 33% and notes, "The transfer amounts as a proportion of per capita expenditures (or consumption) are not the same across all tables in the report
  because of differences in the surveys used, including their coverage and year." Fiszbein and Schady 2009, Pg 110.

• 7. Fiszbein and Schady 2009, Pg 264.
• 8. “Conditions:
  • Health: Compliance with required frequency of health center visits; compliance enforced only in the 4 departments where PRAF is supported by the IDB; in the remaining 13 departments, households are encouraged only to send children to school/take them for health visit.
  • Education
    • School enrollment
    • Regular school attendance of at least 85%.”

  Fiszbein and Schady 2009, Pg 264

• 9. Fiszbein and Schady 2009, Pg 19.
• 10. Fiszbein and Schady 2009, Pg 272.
• 11. “Conditions:
  • Health
    • "Bimonthly health education workshops (all households).
    • Attendance at prescheduled health care visits every month (aged 0–2) or bimonthly (aged 3–5), adequate weight gain and up-to-date vaccinations (aged 0–5) for all households with children aged 0–5.
  • Education
    • Enrollment in grades 1–4 for children aged 7–13
    • Regular attendance of 85% (that is, no more than 5 absences without valid excuse every 2 months)
    • Grade promotion at end of school year.”

  Fiszbein and Schady 2009, Pg 272.

• 12. Fiszbein and Schady 2009, Pg 20.
• 13. Fiszbein and Schady 2009, Pg 270.
• 14. “Conditions:
  • Education
    • Enrollment in grades 1–6 for children aged 7–15
    • Regular attendance of 85%, (that is, no more than 5 absences without valid excuse every 2 months)
    • Deliver teacher transfer to teacher.
  • Other
    • For occupational training: household needed to decide on member who takes course, and payment is conditional on attendance at course.
    • For the business grant: business plan approved by technical team in the Ministry of Family”

  Fiszbein and Schady 2009, Pg 270.

• 15. Fiszbein and Schady 2009, Pg 20.
• 16. Fiszbein and Schady 2009, Pg 258.
• 17. “Conditions:
  • Health
    • Children aged 0–5: bimonthly visits to health posts for growth and development checkups and immunizations.
  • Education
    • School enrollment for children aged 6–15
    • School attendance at least 90% of school days
    • Must be enrolled in school and have attendance at basic education classes of at least 80% (including both justified and unjustified absences).”

  Fiszbein and Schady 2009, Pg 258.

• 18. Fiszbein and Schady 2009, Pg 19.
• 19. Dates not listed in study. Skoufias, Unar, and Gonzalez-Cossio 2008
• 20.

  "Localities were randomly assigned into three treatment groups and one control group. Two of the treatment groups were assigned to receive food transfers with and without receiving a health and nutrition education package, and a third to a cash transfer of equal value to the food basket plus the education package...The PAL program offers nutrition and health education sessions (platicas), as well as participation in program-related logistic activities. However, given that attendance of the platicas is not a requirement for the receipt of the benefits, the PAL program is essentially an unconditional transfer program...The original food basket transferred consists of the following basic products: powdered fortified milk (8 packages of 240 gr. each), beans (2 kg), rice (2 kg), corn flour (3 kg), soup pasta (6 packages of 200 g), vegetable oil (1 lt.), cookies (1 kg), corn starch (100 g), chocolate drink in powder) (400 g), cereals (ready-to-eat) (200 g), and sardines (2 cans of 425 gr. each). The basket offers approximately 400 calories per day per capita for an average household of 4.2 equivalent adults.” Skoufias, Unar, and Gonzalez-Cossio 2008, Pgs 8-9.

• 21.

  Skoufias, Unar, and Gonzalez-Cossio 2008, Pg 15.

• 22.

  Baird, McIntosh, and Ozler 2011.

• 23.

  “Monthly school attendance for all girls in the CCT arm was checked and payment for the following month was withheld for any student whose attendance was below 80% of the number of days school was in session for the previous month.” Baird, McIntosh, and Ozler 2011, Pg 9.

• 24.

  “The average offer to the households consisted of $10/month – for a total of $100 for the school year transferred in equal amounts for 10 months. $10/month represents roughly 15% of total monthly household consumption in our sample households at baseline, which places this program in the middle-to-high end of the range of relative transfer sizes for conditional cash transfer programs elsewhere.” Baird et al. 2009, Pg 12.

• 25. The baseline percentage for dropouts was .444 and the control group dropouts experienced an increase of .162. Baird et al. 2009, Table 5, Pg 29.
• 26. As reported by teacher. Baird, McIntosh, and Ozler 2011, Table III, Pg 43.
• 27. As reported by school ledgers. Baird, McIntosh, and Ozler 2011, Table V, Pg 45
• 28. Baird, McIntosh, and Ozler 2011, Table VI, Pg 46.
• 29. Baird, McIntosh, and Ozler 2011, Table VI, Pg 46.
• 30. Baird, McIntosh, and Ozler 2011, Table VI, Pg 46.
• 31. Baird, McIntosh, and Ozler 2011, Table VI, Pg 46.
• 32. As measured for those who were in school at the beginning of the study. Baird, de Hoop, and Ozler 2011, Table 3, Pg 36.
• 33. As measured for those who were in school at the beginning of the study. Baird, de Hoop, and Ozler 2011, Table 3, Pg 36.
• 34.

  Baird et al. 2009, Table 4, Pg 28.

• 35.

  "Dropouts at baseline" and "schoolgirls at baseline" refers to the participants who had dropout or in-school status when the baseline measurements were taken).

• 36. Baird et al. 2009, Table 5, Pg 29.
• 37.

  "Dropouts at baseline" and "schoolgirls at baseline" refers to the participants who had dropout or in-school status when the baseline measurements were taken)

• 38.

  Baird et al., "Effect of a cash transfer programme for schooling on prevalence of HIV and Herpes Simplex 2 in Malawi," Pg 6-7.

• 39.

  Note that p-values are not included in the paper

• 40.

  "The study was not powered to detect eff ects on HIV prevalence in baseline dropouts." Baird et al., "Effect of a cash transfer programme for schooling on prevalence of HIV and Herpes Simplex 2 in Malawi," Pg 6-7.

• 41.

  Baird et al., "Effect of a cash transfer programme for schooling on prevalence of HIV and Herpes Simplex 2 in Malawi," Pg 6.

• 42.

  P-values are not included in the paper.

• 43.

  "In this paper we evaluate the impact of a cash transfer to the poorest 40 percent families on school enrollment in Ecuador. While the program aims at increasing school attendance and visits to health care centers, the program does not impose any explicit requirement for children of treated families to attend school or visit health centers." Oosterbeek, Ponce and Schady 2008, Pg 1.

• 44.

  "While the formal rules of the program make it an unconditional program, this appears not to be the case in the perception of a substantial part of the potential beneficiaries. Before the actual implementation of the program there was a publicity campaign, which mentioned the need for households to enroll their children in school and take them to health care centers. Some surveys indicate that 1/3 of the beneficiaries state that they believe that the transfers are conditional, so that they will probably respond to the program as if it poses explicit requirements with regard to school enrollment and visits to health care centers." Oosterbeek, Ponce and Schady 2008, Pg 2.

• 45.

  "An interesting feature of the design of the program’s impact evaluation is that it consists of a randomized experiment and of a regression discontinuity design. In the experiment 1309 families around the first quintile of the poverty index were randomly assigned to treatment and control groups. For the regression discontinuity design data were collected from 1221 families around the second quintile of the poverty index, which is the program’s threshold for eligibility." Oosterbeek, Ponce and Schady 2008, Pg 2.

• 46. "The main stated objective of the program is to improve the formation of human capital among poor families in Ecuador. The program has two components: education and health. The education component aims at children from the ages of 6 to 15 to enroll in school and attend at least 90% of the school days. The health component aims at children under 6 years old to attend health centers for medical check-ups. Unlike other programs in Latin America, up until 2006 the program had no mechanisms to verify attendance in school and in health care centers. Families are not taken off program rosters if their school-aged children are not enrolled in school or fail to attend classes regularly. " Oosterbeek, Ponce and Schady 2008, Pgs 3-4
• 47. "The main stated objective of the program is to improve the formation of human capital among poor families in Ecuador. The program has two components: education and health. The education component aims at children from the ages of 6 to 15 to enroll in school and attend at least 90% of the school days. The health component aims at children under 6 years old to attend health centers for medical check-ups. Unlike other programs in Latin America, up until 2006 the program had no mechanisms to verify attendance in school and in health care centers. Families are not taken off program rosters if their school-aged children are not enrolled in school or fail to attend classes regularly.” Oosterbeek, Ponce and Schady 2008, Pgs 3-4. No specific ages are listed for the enrollment claims, so it is plausible that all ages are included.
• 48. "Around the first quintile of the poverty index the cash transfer of US$ 15 per month increases school enrollment from 75% to 85%. Around the second quintile the cash transfer has no impact and school enrollment remains 85%." Oosterbeek, Ponce and Schady 2008, Pg 12. Note that the second quintile estimate is from a regression discontinuity analysis, not an RCT.
• 49. "Around the second quintile the cash transfer has no impact and school enrollment remains 85%" Oosterbeek, Ponce and Schady 2008, Pg 12. Statistical significance and the 10.3% figure found in Fiszbein and Schady 2009, Pg 17, Table 4. They do not appear in Oosterbeek, Ponce and Schady 2008.
• 50. Elevation-adjusted hemoglobin, height, fine motor control, TVIP score (receptive vocab), long-term and short-term memory, visual integration, and behavioral problems scale. Paxson and Schady 2007, Table 3, Pg 43.
• 51. These ages are the ones for which all 8 measures were recorded. It's not clear if some of the tests were also given to other age groups. Paxson and Schady 2007, Pg 43.
• 52. "The main results for children’s outcomes, presented in Table 3, show modest treatment effects. The estimated treatment effects for individual outcomes are statistically significant only for fine motor control, which is predicted to be 16 percent of a standard deviation higher among the treatment group than in the control group, and long-term memory, which is predicted to be 19.2 percent of a standard deviation higher among the treatment group. Note, however, that all the effects are positive, regardless of the controls that are included. The average effect size for the measures of physical outcomes (hemoglobin, height, and final motor control) is 10.6 percent of a standard deviation with a standard error of 4.9 percent, while the average program effect for the cognitive and behavioral measures (vocabulary recognition, long-term memory, short-term memory, visual integration, and the behavior problems scale) is 10.1 percent of a standard deviation, with a standard error of 7.1 percent. Results are similar when the extended set of controls is included." Paxson and Schady 2007, Pg 18.
• 53. Fiszbein and Schady 2009, Pg 146.
• 54. Z score points. Fiszbein and Schady 2009, Pg 146.
• 55. Z score points. Fiszbein and Schady 2009, Pg 146.
• 56. Z score points. Fiszbein and Schady 2009, Pg 146.
• 57. Z score points. Fiszbein and Schady 2009, Pg 146.
• 58. Z score points. Fiszbein and Schady 2009, Pg 146.
• 59. Z score points. Fiszbein and Schady 2009, Pg 146.
• 60. Fiszbein and Schady 2009, Pg 137.
• 61. Fiszbein and Schady 2009, Pg 137.
• 62.

  Edmonds and Schady 2011, Table 2, Pg 31.

• 63.

  This is actually a regression-estimated counterfactual for the population that actually received the cash transfers. No actual control group means were reported. Edmonds and Schady 2011, Table 2, Pg 31.

• 64.

  This is the “intention to treat” (ITT) estimate (merely comparing the people who won and lost the lottery). Because there was significant noncompliance with the lottery results, lottery winners were only 32.7 percentage points more likely to receive cash transfers than lottery losers. This should not bias the reported results for the impact of winning the lottery, but it makes them a lower bound estimate of the effect of actually receiving a cash transfer. Edmonds and Schady 2011, Table 2, Pg 31.

• 65.

  This is the “local average treatment effect” estimate, which assesses the effect of actually receiving a cash transfer for the portion of the experimental population that received the cash transfers as a result of the experiment (about 32.7% of the treatment group). Edmonds and Schady 2011, Table 2, Pg 31.

• 66.

  Edmonds and Schady 2011, Table 2, Pg 31.

• 67.

  This is actually a regression-estimated counterfactual for the population that actually received the cash transfers. No actual control group means were reported. Edmonds and Schady 2011, Table 2, Pg 31.

• 68.

  This is the “intention to treat” (ITT) estimate (merely comparing the people who won and lost the lottery). Because there was significant noncompliance with the lottery results, lottery winners were only 32.7 percentage points more likely to receive cash transfers than lottery losers. This should not bias the reported results for the impact of winning the lottery, but it makes them a lower bound estimate of the effect of actually receiving a cash transfer. Edmonds and Schady 2011, Table 2, Pg 31.

• 69.

  This is the “local average treatment effect” estimate, which assesses the effect of actually receiving a cash transfer for the portion of the experimental population that received the cash transfers as a result of the experiment (about 32.7% of the treatment group). Edmonds and Schady 2011, Table 2, Pg 31.

• 70.

  Edmonds and Schady 2011, Table 2, Pg 31.

• 71.

  This is actually a regression-estimated counterfactual for the population that actually received the cash transfers. No actual control group means were reported. Edmonds and Schady 2011, Table 2, Pg 31.

• 72.

  This is the “intention to treat” (ITT) estimate (merely comparing the people who won and lost the lottery). Because there was significant noncompliance with the lottery results, lottery winners were only 32.7 percentage points more likely to receive cash transfers than lottery losers. This should not bias the reported results for the impact of winning the lottery, but it makes them a lower bound estimate of the effect of actually receiving a cash transfer. Edmonds and Schady 2011, Table 2, Pg 31.

• 73.

  This is the “local average treatment effect” estimate, which assesses the effect of actually receiving a cash transfer for the portion of the experimental population that received the cash transfers as a result of the experiment (about 32.7% of the treatment group). Edmonds and Schady 2011, Table 2, Pg 31.

• 74.

  Edmonds and Schady 2011, Table 2, Pg 31.

• 75.

  This is actually a regression-estimated counterfactual for the population that actually received the cash transfers. No actual control group means were reported. Edmonds and Schady 2011, Table 2, Pg 31.

• 76.

  This is the “intention to treat” (ITT) estimate (merely comparing the people who won and lost the lottery). Because there was significant noncompliance with the lottery results, lottery winners were only 32.7 percentage points more likely to receive cash transfers than lottery losers. This should not bias the reported results for the impact of winning the lottery, but it makes them a lower bound estimate of the effect of actually receiving a cash transfer. Edmonds and Schady 2011, Table 2, Pg 31.

• 77.

  This is the “local average treatment effect” estimate, which assesses the effect of actually receiving a cash transfer for the portion of the experimental population that received the cash transfers as a result of the experiment (about 32.7% of the treatment group). Edmonds and Schady 2011, Table 2, Pg 31.

• 78.

  Edmonds and Schady 2011, Table 2, Pg 31.

• 79.

  This is actually a regression-estimated counterfactual for the population that actually received the cash transfers. No actual control group means were reported. Edmonds and Schady 2011, Table 2, Pg 31.

• 80.

  This is the “intention to treat” (ITT) estimate (merely comparing the people who won and lost the lottery). Because there was significant noncompliance with the lottery results, lottery winners were only 32.7 percentage points more likely to receive cash transfers than lottery losers. This should not bias the reported results for the impact of winning the lottery, but it makes them a lower bound estimate of the effect of actually receiving a cash transfer. Edmonds and Schady 2011, Table 2, Pg 31.

• 81.

  This is the “local average treatment effect” estimate, which assesses the effect of actually receiving a cash transfer for the portion of the experimental population that received the cash transfers as a result of the experiment (about 32.7% of the treatment group). Edmonds and Schady 2011, Table 2, Pg 31.

• 82.

  Edmonds and Schady 2011, Table 2, Pg 31.

• 83.

  This is actually a regression-estimated counterfactual for the population that actually received the cash transfers. No actual control group means were reported. Edmonds and Schady 2011, Table 2, Pg 31.

• 84.

  This is the “intention to treat” (ITT) estimate (merely comparing the people who won and lost the lottery). Because there was significant noncompliance with the lottery results, lottery winners were only 32.7 percentage points more likely to receive cash transfers than lottery losers. This should not bias the reported results for the impact of winning the lottery, but it makes them a lower bound estimate of the effect of actually receiving a cash transfer. Edmonds and Schady 2011, Table 2, Pg 31.

• 85.

  This is the “local average treatment effect” estimate, which assesses the effect of actually receiving a cash transfer for the portion of the experimental population that received the cash transfers as a result of the experiment (about 32.7% of the treatment group). Edmonds and Schady 2011, Table 2, Pg 31.

• 86.

  Edmonds and Schady 2011, Table 2, Pg 31.

• 87.

  This is actually a regression-estimated counterfactual for the population that actually received the cash transfers. No actual control group means were reported. Edmonds and Schady 2011, Table 2, Pg 31.

• 88.

  This is the “intention to treat” (ITT) estimate (merely comparing the people who won and lost the lottery). Because there was significant noncompliance with the lottery results, lottery winners were only 32.7 percentage points more likely to receive cash transfers than lottery losers. This should not bias the reported results for the impact of winning the lottery, but it makes them a lower bound estimate of the effect of actually receiving a cash transfer. Edmonds and Schady 2011, Table 2, Pg 31.

• 89.

  This is the “local average treatment effect” estimate, which assesses the effect of actually receiving a cash transfer for the portion of the experimental population that received the cash transfers as a result of the experiment (about 32.7% of the treatment group). Edmonds and Schady 2011, Table 2, Pg 31.

• 90.

  Edmonds and Schady 2011, Table 2, Pg 31.

• 91.

  This is actually a regression-estimated counterfactual for the population that actually received the cash transfers. No actual control group means were reported. Edmonds and Schady 2011, Table 2, Pg 31.

• 92.

  This is the “intention to treat” (ITT) estimate (merely comparing the people who won and lost the lottery). Because there was significant noncompliance with the lottery results, lottery winners were only 32.7 percentage points more likely to receive cash transfers than lottery losers. This should not bias the reported results for the impact of winning the lottery, but it makes them a lower bound estimate of the effect of actually receiving a cash transfer. Edmonds and Schady 2011, Table 2, Pg 31.

• 93.

  This is the “local average treatment effect” estimate, which assesses the effect of actually receiving a cash transfer for the portion of the experimental population that received the cash transfers as a result of the experiment (about 32.7% of the treatment group). Edmonds and Schady 2011, Table 2, Pg 31.

• 94. Schady and Rosero 2007, Table 3, Pg 23.
• 95. Baseline for treatment group: mean for households who lost the lottery (.538) plus the difference (-.013). Schady and Rosero 2007, Table 1, Pg 21.
• 96. Double difference, Model 4. Schady and Rosero 2007, Table 3, Pg 23.
• 97.

  “Localities were randomly assigned into three treatment groups and one control group. Two of the treatment groups were assigned to receive food transfers with and without receiving a health and nutrition education package, and a third to a cash transfer of equal value to the food basket plus the education package.” Skoufias, Unar, and Gonzalez-Cossio 2008, Pg 8.

• 98.

  “The PAL program offers nutrition and health education sessions (platicas), as well as participation in program-related logistic activities. However, given that attendance of the platicas is not a requirement for the receipt of the benefits, the PAL program is essentially an unconditional transfer program... The original food basket transferred consists of the following basic products: powdered fortified milk (8 packages of 240 gr. each), beans (2 kg), rice (2 kg), corn flour (3 kg), soup pasta (6 packages of 200 g), vegetable oil (1 lt.), cookies (1 kg), corn starch (100 g), chocolate drink in powder) (400 g), cereals (ready-to-eat) (200 g), and sardines (2 cans of 425 gr. each). The basket offers approximately 400 calories per day per capita for an average household of 4.2 equivalent adults.” Skoufias, Unar, and Gonzalez-Cossio 2008, Pg 8-9.

• 99. Cunha 2011, Pg 43.
• 100. Evaluated for ages 0-6. Cunha 2011, Pg 43.
• 101. Cunha 2011, Pg 41.
• 102. Cunha 2011, Table 8, Pg 43.
• 103. Cunha 2011, Pg 41.
• 104. Cunha 2011, Table 8, Pg 43.
• 105. Cunha 2011, Pg 41.
• 106. Cunha 2011, Table 8, Pg 43.
• 107. Cunha 2011, Pg 41.
• 108. Cunha 2011, Table 8, Pg 43.
• 109.

  “Conditional cash transfers (CCTs) are programs that transfer cash, generally to poor households, on the condition that those households make prespecified investments in the human capital of their children. Health and nutrition conditions generally require periodic checkups, growth monitoring, and vaccinations for children less than 5 years of age; perinatal care for mothers and attendance by mothers at periodic health information talks. Education conditions usually include school enrollment, attendance on 80–85 percent of school days, and occasionally some measure of performance. Most CCT programs transfer the money to the mother of the household or to the student in some circumstances.” Fiszbein and Schady 2009, Pg 1.

• 110. Fiszbein and Schady 2009, Pg 147
• 111. Fiszbein and Schady 2009, Pg 147
• 112. Fiszbein and Schady 2009, Pg 147
• 113. Fiszbein and Schady 2009, Pg 147
• 114. Macours, Schady and Vakis 2008, Table 6, Pg 39.
• 115.

  The table is not very clear, but elsewhere the authors seem to indicate that the table refers to ages 0-6. "Table 6 shows that overall food expenditures increased among treated households, and expenditures on nutrient-rich food such as animal proteins, fruit and vegetables increased more than proportionally. Treatment effects on indicators of food intake of individual children under the age of 7 show a similar pattern." Macours, Schady and Vakis 2008, Pg 17.

• 116. Macours, Schady and Vakis 2008, Table 6, Pg 39.
• 117. Macours, Schady and Vakis 2008, Table 6, Pg 39.
• 118. Macours, Schady and Vakis 2008, Table 6, Pg 39.
• 119. Macours, Schady and Vakis 2008, Table 6, Pg 39.
• 120. Macours, Schady and Vakis 2008, Table 6, Pg 39.
• 121. Macours, Schady and Vakis 2008, Table 6, Pg 39.
• 122. Macours, Schady and Vakis 2008, Table 6, Pg 39.
• 123. Macours, Schady and Vakis 2008, Table 6, Pg 39.
• 124. Macours, Schady and Vakis 2008, Pg 43.
• 125. Angelucci and De Giorgi 2009, Table 1
• 126. Angelucci and De Giorgi 2009, Table 1,
• 127.

  "We find that household per capita consumption in 2003 is 10.84 pesos higher for original treatment households, and this difference is statistically significant (first column in Table 5). This impact amounts to a 5.6 percent increase in consumption for treatment households, even 4 years after controls started receiving program benefits [and 5.5 years after treatment groups began receiving benefits]." Gertler, Martinez, Rubio-Codina 2012, Pg 16.

• 128.

  Gertler, Martinez, Rubio-Codina 2012, Table 5, Pg 16.

• 129.

  Gertler, Martinez, Rubio-Codina 2012, Table 8, Pg 19.

• 130.

  Maluccio and Flores 2005, Pg 27, Table 4.1.

• 131.

  Baseline for treatment group. Maluccio and Flores 2005, Pg 27, Table 4.1.

• 132.

  Difference in differences between 2000 and 2002 and treatment and control. Maluccio and Flores 2005, Table 4.1, Pg 27.

• 133.

  Maluccio and Flores 2005, Table 4.3, Pg 30.

• 134. Baseline for treatment group. Maluccio and Flores 2005, Table 4.3, Pg 30.
• 135.

  Difference in differences between 2000 and 2002 and treatment and control. Maluccio and Flores 2005, Table 4.3, Pg 30.

• 136.

  Macours, Schady and Vakis 2008, Pg 39.

• 137.

  Macours, Schady and Vakis 2008, Pg 39.

• 138. Macours, Schady and Vakis 2008, Pg 39.
• 139. Macours, Schady and Vakis 2008, Pg 39.
• 140. Skoufias, Unar, and Gonzalez-Cossio 2008, Table 1, Pg 39.
• 141. Skoufias, Unar, and Gonzalez-Cossio 2008, Table 2, Pg 40. Because the outcome variable in the regressions is ln(monthly food consumption per capita), we can take e^coefficients to get the percentage impact of treatment on monthly food consumption per capita. e^0.157=1.17; e^0.183=1.20.
• 142. Skoufias, Unar, and Gonzalez-Cossio 2008, Table 1, Pg 39.
• 143. Skoufias, Unar, and Gonzalez-Cossio 2008, Table 2, Pg 40. Because the outcome variable in the regressions is ln(total monthly consumption per capita), we can take e^coefficients to get the percentage impact of treatment on monthly food consumption per capita. e^0.139=1.149; e^0.171=1.186.
• 144. Cunha 2011, Table 2, Pg 37.
• 145. Cunha 2011, Table 4, Pg 39.
• 146. 352.43+192.88 = 545.31. Cunha 2011, Table 2, Pg 37.
• 147. Cunha 2011, Table 4, Pg 39.
• 148.

  "The identification in this paper relies on experimental variation in program treatment, generated through the Oportunidades randomized evaluation. The evaluation
  sample includes all households in 506 rural communities in 7 states. Communities were randomly assigned to treatment (320 communities) and control (186 communities)
  groups, which were phased into the program at different points in time as part of the program’s national scale-up. Eligible households in treatment communities. The study also compares the two groups in the short term, before the control group received transfers. began receiving benefits starting in March/April of 1998, while eligible households in control communities were incorporated in November/December of 1999." Gertler, Martinez, and Rubio-Codina 2012, Pg 5-6.

• 149.

  "...we estimate that an 18-month exposure to the program resulted in a 9.6 percent increase in agricultural income." Gertler, Martinez, and Rubio-Codina 2012, Pg 2.
  Consumption data from Gertler, Martinez and Rubio-Codina 2012, Table 4, Pg 14.

• 150. Gertler, Martinez, and Rubio-Codina 2012, Table 5, Pg 16.
• 151. "We find that even 4 years after households in the control group were incorporated into the program, consumption levels for the original treatment households were 5.6 percent higher than for the original control households. This result suggests that returns on investments made by treatment households during the initial 18-month experimental period did in fact translate into improvements in long-term living standards." Gertler, Martinez, and Rubio-Codina 2012, Pg 2.
• 152.

  Gertler, Martinez and Rubio-Codina 2012, Table 4, Pg 14.

• 153.

  Gertler, Martinez and Rubio-Codina 2012, Table 5, Pg 16.

• 154.

  Gertler, Martinez and Rubio-Codina 2012, Table 5, Pg 16.

• 155. Lagarde, Haines, and Palmer 2009, Pg 2.
• 156. For a fuller account of all the impacts of CCTs, see one of the following literature reviews:
  • Fiszbein and Schady 2009.
  • Lagarde, Haines, and Palmer 2009.
• 157. “The south african OAP scheme provides a generous benefit to retirees in that country. The value of the transfer is more than twice median per capita income for African (black) households.” Fiszbein and Schady 2009, Pg 120.
• 158. “It is striking that fully two-thirds of income to the bottom quintile comes from social assistance grants, with most of this income coming from child grants (the Child Support Grant, the Foster Care Grant and the Care Dependency Grant combined). As households move up the income distribution, labour market income becomes increasingly important and reliance on social assistance is commensurately reduced.” Woolard and Leibbrandt 2010, Pgs 19-20.
• 159.
  • "The results suggest that the pensions received by women increased the weight for height of girls by 1.19 standard deviations but did not significantly increase that of boys. Pensions received by men are not associated with an improvement in the nutritional status of either girls or boys." Duflo 2003, Pg 5.
  • "This paper has shown that these targeted, unconditional CSG [South Africa Child Support Grant] payments have bolstered early childhood nutrition as signalled by child height-for-age." Aguero, Carter, and Woolard 2009, Pg 27.
• 160.
  • $1,000/$5.50/bednet = 181 bednets distributed
  • 181 bednets cover 326 people because each bednet typically covers 1.8 people. World Health Organization, "World Malaria Report (2011)," Pg 28.
  • Although long-lasting insecticide-treated bed nets are manufactured to last five years, they tend to decay under use and are expected to last an average of 2.22 years.
• 161.

  "...the cash transfer was 150 pesos per month." Cunha, de Georgi, and Jayachandran 2011, Pg 13.

• 162.

  Skoufias, Unar, and Gonzalez-Cossio 2008, Pg 15.

• 163.

  About 89 percent of households in the in-kind and cash villages were eligible to receive transfers (and received them). Cunha, de Georgi, and Jayachandran 2011, Pg 12.

• 164.

  "The data for our analysis come from surveys of stores and households conducted in the experimental villages by the Mexican National Institute of Health both before and after the program was introduced. Baseline data were collected in the final quarter of 2003 and the first quarter of 2004, before villagers knew they would be receiving the program. Follow-up data were collected two years later in the final quarter of 2005, about one year after PAL transfers began in these villages. Our measure of post-program prices comes from a survey of local food stores. Enumerators collected prices for fixed quantities of 66 individual food items, from a maximum of three stores per village, though typically data were collected from one or two stores per village." Cunha, de Georgi, and Jayachandran 2011, Pg 14-15.

• 165.

  Cunha, de Georgi, and Jayachandran 2011, Table 1, Pg 33.

• 166.

  Cunha, de Georgi, and Jayachandran 2011, Table 2, Pg 35.

• 167.

  "Finally, we examine how these price effects differ depending on how geographically isolated the village is. First, isolated villages are typically less integrated with the world economy, so local supply and demand should matter more in the determination of prices (i.e., supply curves are steeper). Second, there is likely to be less competition on the supply side (i.e., among grocery shops) in these remote and typically smaller villages, which can make prices more responsive to transfers. For both of these reasons, the price effects of transfers may be more pronounced in remote villages, and we indeed see this pattern in the data. Since poorer villages are also typically more isolated (World Bank, 1994), these findings suggest that transfer programs targeting the ultra-poor may inherently have important
  pecuniary effects."

  Cunha, de Georgi, and Jayachandran 2011, Pg 3.

• 168.

  Cunha, de Georgi, and Jayachandran 2011, Table 6, Pg 38.

• 169.

  "Our final data set contains 6 basic PAL goods (corn flour, rice, beans, pasta, oil, fortified milk), 3 supplementary PAL goods (canned fish, packaged breakfast cereal, and lentils), and 51 non-PAL goods" Cunha, de Georgi, and Jayachandran 2011, Pg 15.

• 170.
  • “For alcohol consumption, while both [in-kind and cash transfer] treatments induced statistically significant increases (1.73 pesos per [adult equivalent] under in-kind transfers and 2.89 under cash) they are also indistinguishable from each other.” Cunha 2011, Pg 22. According to Pg 36, 10 pesos roughly equal 1 U.S. dollar.
  • Maluccio and Flores 2005, Pg 32. Alcohol and tobacco make up 0.5% of food expenditures, and the effect of cash transfers was small (0.1% of food expenditures) and statistically insignificant.

  Note that both studies point out the unreliability of survey data about alcohol consumption.

• 171.

  “In practice, CCTs appear to have had, at most, modest disincentives for adult work. Two studies (Parker and Skoufias 2000; Skoufias and di Maro 2006) examine the effects of Oportunidades on adult labor supply; neither finds evidence of disincentive effects. The data used by Edmonds and Schady (2008) suggest that the BDH program in Ecuador had no effects on adult labor supply; in a similar vein, Filmer and Schady (2009c) report that adult labor supply was largely unaffected by the CESSP program in Cambodia. Only in Nicaragua is there some evidence of significant negative effects on adult work: Maluccio and Flores (2005) show that the RPS resulted in a significant reduction in hours worked by adult men in the preceding week (by about 6 hours), with no effect among adult women.” Fiszbein and Schady 2009, Pgs 117-119.

• 172.

  Aker et al. 2011.

• 173.

  "Excluding the cost of the mobile phones, the per-recipient cost of the zap intervention falls to $8.80 per recipient. Thus, while the initial costs of the zap program were significantly higher, variable costs were 30 percent higher in the manual cash distribution villages." Aker et al. 2011, Pg 12.

• 174.

  Aker et al. 2011, Pg 10.

• 175.

  Aker et al. 2011, Tables 4 and 5.

• 176. Fiszbein and Schady, “Conditional Cash Transfers”
• 177.

  Lagarde et al. 2009, “The impact of conditional cash transfers on health outcomes and use of health services in low and middle income countries.”

• 178.

  Lagarde, Haines, and Palmer 2009, Pg 1.

• 179.

  Adato and Bassett 2008, Pg 231-232.

• 180.

  “The ideal experiment to answer this question – i.e. a randomized controlled trial with one treatment arm receiving conditional cash transfers, another receiving unconditional transfers, and a control group receiving no transfers – has not previously been conducted anywhere,” Baird, McIntosh, and Ozler 2010, Pg 3.

• 181.

  This list is not explicitly stated to be comprehensive, but this seems to be a reasonable assumption. See Adato and Bassett 2008, Appendix, Pg 31-32.

• 182.
  • Department for International Development 2011, Pg 49-51.
  • Adato and Bassett 2008.