rafmacalaba/datause-encoder-data huggingface dataset:
However, he questions the causal link between relieving financial constraints and the higher levels of investment because he observes a rise in private transfers among households. In regard to unconditional transfers or noncontributory pensions, there is evidence that supports the contribution of pensions to relieving credit constraints as in the case of blacks in South Africa (Berg, 2013). Moreover, the randomized control trial conducted by Haushofer and Shapiro (2013) sheds light on how regular unconditional transfers, as opposed to lump-sum transfers, are more well suited to encouraging long-term investment. There are four papers which are probably the closet to our study. First, Soares, Ribas, and Osório (2010), who evaluate Brazil’s Bolsa Família and find that it raised female labor force participation by 4.3 percentage points, even though they do not discuss this result further. Fogel and Paes de Barros (2010) find for the same program, using aggregate data of Brazilian municipalities, that labor force participation increased by 2-4 percentage points for males. Results for females are also positive, yet not significant and smaller in magnitude. Next, Skoufias, Unar and González de Cossio (2013) exploit the experimental design of Mexico’s Food Support Program (Programa de Apoyo Alimentario, PAL) on labor supply. Although they find no significant effects of the PAL on total labor market participation, their estimates show that PAL have a significant negative effect on the participation of males in agricultural activities which translated into a shift into participation in non-agricultural activities. They argue that PAL provide partial insurance (reduce down-side risks) for food consumption that allows program beneficiaries to allocate less time into agricultural production and more towards more risky non-agricultural activities. Finally, Martinez (2004), in an unpublished paper, finds that Bolivia’s Bonosol Program boosted food consumption among rural households by more than what could be purchased with the amount of the transfers. He concludes that the additional funds are likely being used to invest in agricultural inputs.

Most other papers on the labor market impacts of noncontributory pensions find the opposite effect, or no effect at all. A decline in overall labor supply is documented in Aguila et al. (2012) and Galiani, Gertler, and Bando (2014), who explore pension programs in Mexico. However, the magnitude of the decline varied considerably; it was 4.3 percentage points in Yucatan, Mexico (work for pay) (Aguila et al. 2012), though Galiani, Gertler, and Bando (2014) find that the share of working individuals who received benefits through Mexico’s Adultos Mayores Program fell by 20 percent after the expansion in coverage. Other kinds of programs produce more nuanced effects. In the same Adultos Mayores Program, Juarez and Pfutze (2015) find a reduction of similar magnitude among male recipients only, mainly driven by poorer beneficiaries. In Mexico City, Juarez (2010) finds that the effect of a nutrition 3
percent in the Middle East and North Africa.<sup>3</sup> In developing countries, survey data indicate that unemployment rate is highest among youth in MENA and LCR. In SSA and SAR the overall unemployment rate for youth remains low particularly due to the large share of youth in rural areas characterized by low unemployment rate. If fact, even in SSA and SAR, the youth unemployment is high in urban areas.

**Figure 4: Youth unemployment varies with income and educational level**

# **Youth average unemployment by quintile**

<!-- Start of picture text --> 25<br>20<br>15<br>10<br>5<br>0<br>first second third fourth fifth<br>quintile<br>Youth average unemployment by education level<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>Income quintile<br>no educationprimary incompleteprimary completesecondary incompletesecondary completemore than secondary<br>Unemployment rate<br>Unemployment rate<br><!-- End of picture text --> As figure 4 shows the unemployment rate among youth in developing countries also varies according to the income level of the households where they reside and according to their educational level. On average, the youth unemployment rate increases

> 3 ILO (2004).

12
**Figure 5: The empirical distribution of start-up capital shows there are many production choices**

<!-- Start of picture text --> 0 5000 10000 15000<br>Start-up Capital in 2008 USD<br>25<br>20<br>15<br>10<br>Percent of Firms<br>5<br>0<br><!-- End of picture text -->

**Source:** Sri Lankan Longitudinal Survey of Enterprises, Baseline data. Graph is restricted to the bottom 90% of firms in terms of start-up capital.

Once we allow for many different production technologies, each with a different initial starting cost, then the overall production technology convexifies relatively rapidly. For example, Figure 6 shows the analog of Figure 3, but with 10 rather than 2 production technologies. While the outer curve, shown in bold, still has areas of locally increasing returns, these have flattened out and the curve is much smoother than with 2 technologies. As one moves from 10 to 100 or 1000 different production choices, the overall production choice set will then become more and more convex.

16
22 Next we consider the most commonly used least-square growth rate (LSGR) pt ocedure. Using (2.6), we obtained the welfare weights as for t _2_ 2, k being the constant of proportionality. This equation implies that vt = 0 for t (1 2 )and positive (negative) for t being greater (less) than 2 This is a peculiar welfare function, it gives negative weights to the utilities enjoyed by the countries in the first half of the total period. To highlight this peculiarity, let us consider a simple example of income streams of two countries in five periods; country 1: 100, 200, 300, 400, and 500; country 2: 100, 100, 300, 400, and 500. Country 1 clearly enjoys a greater level of welfare than country 2, because its income in period 2 is twice (incomes in other periods being the same). Therefore, the aggregate growth of country 1 must be higher than that of country 2. The least-squares growth rates for countries 1 and 2 were computed to be 48 and 58 percent, respectively; implying that the higher the growth rate, the lower the aggregate welfare. This possible inverse relationship between aggregate growth rate and aggregate welfare is clearly unacceptable. LSGR is used widely by the World Bank and many other international organizations. Despite its popularity, the procedure is found to be unsuitable from the welfare point of view.
Policy ReseaRch WoRking PaPeR 4298

# **Abstract**

Irrigation management transfer is an important strategy among donors and governments to strengthen farmer control over water and irrigation infrastructure. This study seeks to understand whether irrigation management transfer is meeting the promise of its commitments. The authors use data from a survey of 68 irrigator associations and 1,020 farm households in the Philippines to estimate the impact of irrigation management transfer on irrigation association performance and on rice yields. They also estimate a stochastic frontier production function to assess contributions to technical efficiency. There are three main results. First, the presence of irrigation management transfer is associated with an increase in maintenance activities undertaken by irrigation associations. Second, by increasing local control over water delivery, the presence of irrigation management transfer is associated with a 2-6 percent increase in farm yields. Rice production in irrigation management transfer areas is greater even after controlling for various differences among rice farmers in transfer and non-transfer areas. Third, irrigation management transfer is, at a minimum, poverty-neutral, and may even give the asset-poor a small boost in terms of rice yields. The authors speculate that this boost may be a result of increased timeliness of water delivery and better resolution of conflicts related to illegal use.

This paper—a product of the Environment Department—is part of a larger effort in the department to understand the linkages between poverty and environment. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Alexandra Sears, room MC5-206, telephone 202-458-2819, fax 202-5221735, email address asears@worldbank.org. Policy Research Working Papers are also posted on the Web at http://econ. worldbank.org. The authors may be contacted at Sbandyopadhyay@worldbank.org or Mxie@worldbank.org. August 2007. (52 pages) _The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
**Table 1: Number of** **_Nikkeijin_ in Brazil** **<u>(1923-2006, estimates)</u>**

|Year|Number|
|---|---|
|1923|39,249|
|1932|133,358|
|1940|205,850|
|1958|430,151|
|1976|800,000|
|1986|1,075,133|
|1996|1,444,889|
|2006|1,941,810|

Source: Carvalho (2003).

**Table 2: Japanese emigrants to Latin American countries**

||**1899**|**-1941**|**Post**|**-1945**|**T**|**otal**|
|---|---|---|---|---|---|---|
||**number**|**share(%)**|**number**|**share(%) **|**number **|**share(%)**|
|Total|257,575|100.00|86,427|100.00|344,002|100.00|
|Argentina|5,398|2.10|12,066|13.96|17,464|5.08|
|Bolivia|202|0.08|6,357|7.36|6,559|1.91|
|Brazil|202,025|78.43|53,555|61.97|255,58|74.30|
|Chile|519|0.20||0.00|519|0.15|
|Colombia|229|0.09||0.00|229|0.07|
|Cuba|686|0.27||0.00|686|0.20|
|Dominica||0.00|1,39|1.61|1,39|0.40|
|Mexico|14,476|5.62|671|0.78|15,147|4.40|
|Panama|415|0.16||0.00|415|0.12|
|Paraguay|521|0.20|9,612|11.12|10,133|2.95|
|Peru|33,07|12.84|2,615|3.03|35,685|10.37|
|Uruguay|18|0.01||0.00|18|0.01|
|Venezuela|12|0.00||0.00|12|0.00|
|Others|4|0.00|161|0.19|165|0.05|

Source: Compiled from the data in Carvalho (2003).

26
# S. Frequency of Data Collection: The Essence of Monitoring

The CILSS results on the incidence of poverty very clearly demonstrate the importance of monitoring changes in poverty and welfare annually. While the direction of change in poverty in CMte d'Ivoire was not unexpected in light of the macro-economic evolution in the country, the magnitude of the year-by-year changes and the speed with which the macro-economic decline in 1987 and 1988 was transmitted to the household level, were surprising. These changes would not have been picked-up if the survey had not been repeated each year.

This being said, it is clear that monitoring should not take place with a survey of the complexity of the CILSS. Like many aspects of management, the complexity of data management increases more than linearly with the amount of data that needs to be managed and the potential for error likewise increases exponentially. An integrated household survey with full income and expenditure accounting can provide a useful benchmark or starting point for successive monitoring exercises, but it need not be repeated every year. We suggest therefore that an integrated survey of the CILSS-type be undertaken every four or five years, if the country has the analytic capacity to take full advantage of the data. In the intervening years, a much simpler survey could be used to monitor the evolution of welfare and poverty. The key variable to be monitored is household expenditure, for conceptual reasons and because our research indicates that it reacts rapidly to changes in the macro-economic environment. Beyond that it is also necessary to include basic needs indicators because they do not necessarily evolve in the same direction or show the same regional or socio-economic patterns. Depending upon the policy priorities in the country, we suggest that a set of well-chosen indicators, which rarely would need to number more than 15 or 20, would be adequate to do the job. The "priority analysis" proposed in Demery, Ferroni and Grootaert (forthcoming) has some suggestions for the selection of such indicators.

15
# **1. Introduction**

Marital trajectories in Senegal are often discontinuous. Divorce is frequent and widowhood is a common predicament for women, due in particular to the fact that women marry older men. In 2006/2007, spousal age gaps (male age minus female) averaged 11.2 in urban and 12.9 in rural areas. At the same date, around 18.5% of ever married adult women were currently widows or had remarried after widowhood and 13.2% were currently divorced or remarried following a divorce.<sup>2</sup> Women confronted with divorce or widowhood most often remarry, and may well face one, or more, further marriage dissolutions during their lives. Remarriage appears to take place relatively rapidly: the median duration between widowhood and remarriage among those who remarry is one year. For those who are divorced it is two years.

Given how common these broken trajectories are, it is of interest to ask how they affect women’s well-being. Work by economists on marital dissolution in low-income countries is relatively sparse and hardly exists for the African context, particularly with respect to divorce. There has been a bit more attention to widowhood, often indirectly through the study of female headed households (Appleton 1996 (Uganda); Chapoto et al. 2011 (Zambia); Horrell and Krishnan 2007 (Zimbabwe); and van de Walle 2013 (Mali)). Other social sciences provide the core of our knowledge in this domain for Africa. As divorces are sometimes instigated by women, they are likely not to be universally detrimental to women’s welfare. In fact, it has been suggested that early divorces may be a means for women both to escape family authority, and to climb the social ladder.<sup>3</sup> Indeed, first and usually early, marriages are often arranged with attending benefits to both families and may be experienced as a constraint from which one can be freed through divorce. Once divorced, given the lower stakes in terms of bride price for divorcees, women have more room for choosing their next partner (Dial 2008; Hertrich 1994; Locoh and Thiriat 1995; Yade 2007).<sup>4</sup> In contrast, widowhood, ensuing from adverse circumstances rather than choice, is universally seen as unfavorable to a woman’s situation (Locoh and Thiriat 1995).

Based on conversations with women, numerous anecdotes in the press, and the literature on the consequences of divorce and widowhood in OECD countries (Amato 2000; Sevak et al. 2003), one may expect to find negative consequences associated with all types of

> 2 The statistics given here are based on PSF1 data (described below).

> 3 Recently, more economists are showing an interest in the links between divorce and social mobility (Cherchye et al. 2016).

> 4 In our data, the average bride price paid for marrying a divorcee is about half that paid for a woman in her first marriage.

2
Policy Research Working Paper 8983

# **Abstract**

Attributing a rental value to the dwellings of homeowners is essential in various contexts, including distributional analysis and the compilation of national accounts, consumer price indexes (CPIs), and purchasing power parity indexes. One of the methods for making the attribution is to use homeowner estimates of the market rental value they would pay (receive) for their dwellings if these were rented. This is known as homeowner self-assessed rent. However, homeowner estimates may not be accurate because of the way questions aimed at soliciting such information are phrased, the sentimental attachment of the homeowners to the properties, lack of information about rental markets, and other reasons. Yet, researchers and practitioners often neglect to ascertain the accuracy of homeowner assessments. This study argues that comparing unconditional or conditional means may be misleading if one has not ascertained whether the observable characteristics of homeowner and tenant dwellings are similar. Using Peruvian data from 2003 to 2017, the study tests the accuracy of self-assessed rental values with matching estimators. In Metropolitan Lima, homeowners typically provide accurate estimates of the rental market values of their dwellings. In rural areas, market rental values are underestimated by homeowners in more instances. The direction and magnitude of the inaccuracies in Metropolitan Lima and in rural areas are comparable and range between −25 percent and −20 percent.

This paper is a product of the Poverty and Equity Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at mranzani@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **ANALYZING COMMUNITY RESPONSES TO HIV AND AIDS: OPERATIONAL FRAMEWORK AND TYPOLOGY**

Rosalía Rodriguez‐García, Réne Bonnel, N’Della N’Jie, Jill Olivier, F. Brian Pascual, and Quentin Wodon<sup>1</sup> The World Bank <u>Keywords:</u> Community response, community characterization, operational framework, community typology, HIV and AIDS _This study contributes to the Evaluation of the Community Response to HIV and AIDS led by the Global HIV/AIDS Program Team, HNP, HDN. This work is a collaboration of the World Bank with DFID and the UK Consortium for AIDS and Development._ 1 The authors are staff or consultants with the Global HIV/AIDS Program team, HNP and Development Dialogue on Values and Ethics team in the Human Development Network at the World Bank. The paper benefited from a consultative process carried out with the UK Consortium for AIDS and International Development that included specialists, civil society organizations, and development partners. The authors wish to thank and acknowledge the reviewers listed in the appendix for providing useful comments and insights on previous versions of this paper. The authors would also like to acknowledge the support of David Wilson, Director for HIV and AIDS at the World Bank. The opinions expressed in this paper are those of the authors only and need not represent the views of the World Bank, its Executive Directors of the countries they represent. Support from DFID is gratefully acknowledged.

1
countries provides the most reliably exogenous variation on when countries serve on the UNSC across our sample period.<sup>8</sup> We make use of this exogeneity by replicating our results for Africa.

To allow comparability with existing research, our analysis closely follows the approach in Clemens et al. (2012), adding our variables of interest to their models. Clemens et al. show that the most prominent previous attempts to control for the potential endogeneity of aid rely on invalid instruments. Instead of suggesting more valid ones, they address the potential endogeneity of aid by differencing the regression equation and lagging aid, so that it can reasonably be expected to cause growth rather than being its effect. Thus, they assume that the main (short‐term) effects of aid on growth occur, on average, one four‐year‐period after its disbursement. We base our analysis on their permutations of Burnside and Dollar (2000)—the study that arguably gained most attention in the recent literature on aid and growth. While we believe (as do Clemens et al. 2012) that OLS regressions are superior to two‐stage least squares regressions with questionable instruments, we stress that our estimate of whether aid affects growth could be biased in either direction,<sup>9</sup> and we refrain from interpreting the aid‐growth relationship as causal. Instead, we focus on how temporary UNSC‐membership causally changes the effect of aid on growth.

In terms of timing, we follow Clemens et al. (2012) and assume that disbursed aid on average takes one four‐year‐period to become effective in increasing or decreasing economic 8. For Africa, Vreeland, and Dreher (2014) find representation to be more likely for those countries with higher debt service payments, larger GNI per capita, greater voting alignment with the United States in the UNGA, and more corruption, controlling for country fixed effects. We control for these variables either in all regressions or in the robustness section.

> 9. For example, donors might grant more aid to a new reform‐oriented government. Increased growth resulting from these reforms could then spuriously be attributed to the increases in aid. On the other hand donors might give more aid to countries where they anticipate shocks to reduce future growth rates.

11
# Table9

# Hmemuim of **hthgy Eamrn** (in). **by AM** Gnx. Selected Coefficijats: **Fill** Tim. Nle. S1aaiod Wrklm GQIpetes of OMeral and **Votiaxl Sools** - Israeli CGEm. 1983

# (Selected Coefficients)

||Age (Gr|c:<br>25-29|Are Gr(|.:<br>30-34|AMe Gnr|m: 35-39|Age Qr:|g:<br>40-44|Age Gr|a:<br>45-49|
|---|---|---|---|---|---|---|---|---|---|---|
||Direct<br>Mathing|Wider<br>MatciArs|Direct<br>Matchirgs|Wider<br>Matddis|Direct<br>Matchings|Wider<br>Matchirgs|Direct<br>Matchins|Wider<br>Matcings|Direct<br>_Matcdrhg_|Wider<br>_s Matchings_|
|P.CERr|-0.007|-0.007|0.028|0.028|0.034|0.033|-0.133|-0.134|0.01|0.002|
||(0.22)|(0.21)|(0.65)|(0.65)|(0.71)|(0.69)|(1.96)|(1.97)|(0.01)|(0.03)|
|.CERr|0.084|0.083|0.049|0.052|0.114|0.111|0.073|-0.074|0.062|0.066|
||(2.50)|(2.48)|(1.22)|(1.28)|(2.52)|(2.47)|(1.15)|(1.16)|(1.05)|(1.11)|
|BAG|0.167|0.167|0.093|0.100|0.136|0.135|0.049|-0.041|0.101|0.107|
||(4.20)|(4.22)|(1.88)|(2.02)|(2.34)|(2.34)|(0.64)|(0.54)|(1.38)|(1.45)|
|Wc. M|0.040|0.042|0.107|0.069|0.088|0.090|0.152|0.115|0.143|0.105|
||(1.66)|(1.84)|(3.89)|(2.72)|(2.80)|(3.18)|(3.35)|(2.85)|(3.03)|(2.58)|
|%Wx. U|-0.015|-0.025|-0.055|-0.064|0.028|0.013|-0.027|-0.042|0.041|0.044|
||(0.74)|(1.17)|(2.35)|(2.64)|(1.08)|(0.50)|(0.79)|(1.16)|(1.16)|(1.15)|
||4,500|4,500|3,776|3,776|2,778|2,778|1,492|1,492|1,333|1,133|
|R2|0.084|0.085|0.107|0.104|0.147|0.148|0.195|0.194|0.195|0.194|

t values in parentheses

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