rafmacalaba/datause-encoder-data huggingface dataset:
# **_The Impact of HIV/AIDS_**

For some countries, especially countries in southern Africa, assumptions about AIDS mortality can have a significant impact on the projected size of the youth population. The population projections of the U.N. Population Division include projections about AIDS mortality and about the potential impact of anti-retroviral treatment. The population projections incorporate the UNAIDS model that is used to project the course of the epidemic in the 60 countries with high HIV prevalence (UNAIDS Reference Group on Estimates, Modelling and Projections, 2002). The complete set of projections also includes an alternative projection in which it is assumed that there is no AIDS mortality. These alternative “No HIV/AIDS” projections are made for the 60 countries with high HIV prevalence, with projections made from 1980 to 2050. Figure 6 shows the medium variant projection, which includes AIDS mortality, and the alternative “No AIDS” projection for three countries with high HIV prevalence – Botswana, South Africa, and Zambia. These projections use the 10-24 age group, rather than the 12-24 age group, since single year of age estimates are not available for the “no AIDS” projections.

Figure 6 demonstrates that AIDS mortality has a substantial impact on the size of the youth population in these southern African countries. There is little difference in the two projections in 2000, but by 2010 the projections begin to diverge. In Botswana, for example, the youth population is projected to peak around 2005 by the medium variant projection, but under the alternative “No AIDS” projection it would have continued increasing for several more decades. The medium variant youth population in 2015 in Zambia is projected to be about 15% lower than it would have been in the absence of HIV/AIDS.

> <sup>7</sup>
extremely labor-intensive. Fuelwood and _teff_ flour must be sourced in villages that may be far from roads. Each household CCT round then takes two to four hours to complete, because it is necessary for households to cook _injera_ on both the Mirt and traditional stoves on the same day in the same kitchen. For those households who received Mirt stoves, but did not participate in CCTs, we use the village average per-minute fuelwood savings from the appropriate CCT round as noted above. We calibrate all information to one week time periods, because _injera_ tends to not be cooked every day (Dresen et al., 2014). Other data on household characteristics, demographics and cooking environments, including cooking locations, are collected using a household survey.

It is unfortunately not possible to electronically monitor surface temperature of the threestone technology, because the stones are often moved and disturbed, which can destroy monitors by force or by getting them too close to fires and exceeding temperature tolerances. We therefore implicitly assume that adjusting for differences in fuelwood consumption the time to cook a unit of _injera_ is the same regardless of the technology. This exact assumption was tested during the CCTs and as discussed in Gebreegziabher et al. (2015) there is no statistical difference between the time to bake 4kg of _teff_ flour into _injera_ on the Mirt and traditional three-stone stoves.

We acknowledge that using the measured per-minute CCT savings as an estimate of per-unit time fuelwood savings supposes limited leakage in which households do not fully substitute the ICS for the traditional technology.<sup>5</sup> Indeed, it is even possible that fuel use could increase due to leakage and we acknowledge that our identification strategy does not strictly preclude large leakage effects. That said, three features of the Mirt stove mitigate leakage. <mark>First, the Mirt stove is highly specialized for</mark> _<mark>injera</mark>_ <mark>baking, which makes it very unlikely that it will be shifted to other uses. As shown in Figures 1 and 2, for example, the cooking area is very large and cannot accommodate small pots. Waste gases can be utilized to cook stews and coffee, but the stove is designed for this to be done in conjunction with</mark> _<mark>injera</mark>_ <mark>baking.</mark> <mark>Second, using the SUM we find that the Mirt stove is on average used two to three times per week, which is a very traditional and extremely typical interval for</mark> _<mark>injera</mark>_ <mark>baking in areas without refrigeration. Indeed it is also almost exactly the mean baking interval reported in</mark> Gebreegziabher et

> 5 In the energy literature such leakage is often called “rebound” effects.  In the results section we discuss the effect of alternative assumptions about leakage.

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and underdeveloped and poorly maintained infrastructure (World Bank, 2007). The inconsistent agricultural performance has direct implications for living standards, given the predominantly rural nature of the country and its heavy reliance on agriculture.

# 3.1 FARM INPUT SUBSIDY PROGRAM<sup>7</sup>

In an effort to combat poverty and boost national and household food security, the Malawian government has embarked on an ambitious annual fertilizer and seed subsidy program known as the Farm Input Subsidy Program (FISP), starting with the 2005/06 agricultural season. The FISP is financed by the government with international donor support utilized in the form of overall budget support (Chirwa et al., 2011). The agency leading the design and implementation of the FISP is the Ministry of Agriculture and Food Security (MoAFS). The primary objectives of the program are to achieve food self-sufficiency and to increase income among resource-poor smallholder beneficiaries through increased maize and legume production driven by access to improved agricultural inputs.

The focus of our analysis is the 2009/10 agricultural season, which is driven by data availability. During this season, the government subsidized a total of 161,500 metric tons of maize fertilizer, 8,700 metric tons of improved maize seed, and 1,600 metric tons of legume seed (Dorward and Chirwa, 2011b). The cost of the program corresponded to 8.2 percent and 62 percent of the national budget and the agriculture budget, respectively (Lunduka et al., forthcoming). Ideally, each beneficiary was entitled to (i) a 50-kilogram bag of Urea fertilizer, (ii) a 50-kilogram bag of 23:21:0 fertilizer, (iii) a 5-kilogram bag of improved maize seed or a 10 kilogram bag of openpollinated variety (OPV) maize seed, and (iv) a 1-kilogram bag of legume seed (groundnuts, beans, soya beans, or pigeon peas). Each component of the subsidized input package was associated with a unique coupon that was color coded and had specific security features and district-specific serial numbers.

The program was designed to reach 1.6 million beneficiaries during the 2009/10 season and was set up for each beneficiary to pay (i) 500 Malawi Kwacha (MK) for each bag of fertilizer (representing an approximately 95 percent subsidy), and (ii) up to 100 MK for the bag of maize seed.<sup>8</sup> Each beneficiary could also access a 2-kg bag of legume seed for free. The subsidized inputs could have been obtained through the Agricultural Development and Marketing Corporation (ADMARC) outlets, the Smallholder Fertilizer Revolving Fund Malawi (SFRFM) locations, and registered private input dealers.

> 7 Unless otherwise stated, the details on the FISP features and implementation during the 2009/10 season presented in this section are based on MoAFS (2009) and the interview that was conducted on February 24, 2012 with Christine Mtambo, the National Coordinator of the Malawi FISP, MoAFS.

> 8 The exchange rate for the IHS3 period is MK150 = US$1.

8
<!-- Start of picture text -->
-2 0 2 4 6 0 1 2 3 4 5<br>Proportional Wholesale Price Differences wtih Respect to Delhi Proportial Wholesale Price Absolute Differences with Respect to Delhi<br>Source: Authors’ calculations.  Source: Authors’ calculations.<br>2 4<br>1.5 3<br>1 2<br>Density Simple Differences .5 Density Absolute Differences 1<br>0 0<br><!-- End of picture text -->

All prices are disperse, but some are more disperse than others.

Aggregate indicators of retail price dispersion mask substantial heterogeneity across products. Within states and for a given year, prices of pulses tend to show the lowest dispersion levels (differences with respect to Delhi) among all products considered. For example, tur arhar, moong, masur or urad show dispersion levels between 15 and 19 percentage points lower than bananas – the product with the highest level of dispersion after potatoes (Figure 5).

Figure 5: Differences in price dispersion by product relative to bananas (percentage points) <!-- Start of picture text --> 5%<br>0%<br>‐5%<br>‐10%<br>‐15%<br>‐20%<br>‐25%<br>Note: The columns represent regression coefficients of<br>commodity dummies on absolute price differences,<br>controlling for year and state effects. Lines show the<br>confidence interval for the coefficients. The omitted<br>commodity is bananas. Source: Authors’ calculations .<br>Tur Arhar Moong Masur Urad Mustard Oil Rice Gram Groundnut Oil Coconut Oil Onion Potato<br><!-- End of picture text --> Dispersion also varies across states. For a given product in a given year, prices in the northeast state of Nagaland show the highest differences with respect to Delhi (about 13 percentage points higher than those of the baseline ‐ Andhra Pradesh). The lowest differences are observed in cities in Madhya Pradesh, at about 4 percentage points below the differences of the baseline (Figure 6).

Figure 6: Differences in price dispersion by state relative to Andhra Pradesh (percentage points) <!-- Start of picture text --> 20%<br>15%<br>10%<br>5%<br>0%<br>‐5%<br>‐10%<br><!-- End of picture text --> Note: the columns represent regression coefficients of state dummies on absolute price differences, controlling for year and commodity effects. Lines show the confidence interval for the coefficients. The omitted state is Andhra Pradesh. Source: Authors’ calculations.

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Policy Research Working Paper 7077

# **Abstract**

There is an increasing recognition that investment in human development at an earlier age can have a significant impact on the lifetime earnings capacity of an individual. This notion is the basis for the popularity of conditional cash transfer programs to help boost child health and education outcomes. The evidence on the impact of conditional cash transfers on health and education outcomes, however, is mixed. This paper uses panel data from a pilot project and evaluates the impact of conditional cash transfers on consumption, education, and nutrition outcomes among poor rural families in Bangladesh. Given implementation challenges the intervention was not able to improve school attendance. However the analysis shows that the pilot had a significant impact on the incidence of wasting among children who were 10–22 months old when the program started, reducing the share of children with weight-forheight below two standard deviations from the World Health Organization benchmark by 40 percent. The pilot was also able to improve nutrition knowledge: there was a significant increase in the proportion of beneficiary mothers who knew about the importance of exclusively breastfeeding infants until the age of six months. The results also suggest a significant positive impact on food consumption, especially consumption of food with high protein content.

This paper is a product of the Social Protection and Labor Global Practice Group. 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://econ.worldbank.org. The authors may be contacted at isharif@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
<!-- Start of picture text --> MB actual consumption<br>@ mean expected consumption<br>A: Poor and vulnerable — variance of expected consumption<br>(chronic poor) B: Poor, but likely non-<br>—ii—ouo vulnerable<br>z3£w C: Non-poorvulnerableand not<br>§33 ——_@_H-<br>=<br>D: Non-poor, but vulnerable<br>(risk induced)<br>E: Non-poor, but vulnerable<br>(poverty induced)<br>Poverty line<br><!-- End of picture text -->
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- Leitold, Roxana et al. (2021). “Flood risk reduction and climate change adaptation of manufacturing firms: Global knowledge gaps and lessons from Ho Chi Minh City”. _International Journal of Disaster Risk Reduction_ 61, 102351.

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Table 6: Key results, impact of participation by region in established conservancies

||_Kunene_|_Caprivi_|
|---|---|---|
|**1. Simple Comparison Without Control:**|||
|a) Mean Household Income|1667*|5110**|
|(Changes in proportion)|(0.24)|(0.69)|
|b) Mean Per Capita Income|177|849**|
|(Changes in proportion)|(0.10)|(0.60)|
|c) Mean Household Expenditure|286**|218|
|(Changes in proportion)|(0.49)|(0.17)|
|d) Mean Per Capita Expenditure|54**|7|
|(Changes in proportion)|(0.41)|(0.03)|
|**2. Multivariate Analysis**(Changes in proportion)**:**|||
|a) Household Income|0.08|0.20|
|b) Per Capita Income|0.10|0.25|
|c) Household Expenditure|0.11|-0.21|
|d) Per Capita Expenditure|0.15|-0.13|
|**3. Instrumental Variable Method**(Changes in proportion)**:**|||
|a) Household Income|-0.69|0.50|
|b) Per Capita Income|-0.34|0.50|
|c) Household Expenditure|0.29|-1.21**|
|d) Per Capita Expenditure|0.45|-1.31**|
|**4. Propensity Score Matching:**|||
|a) Household Income|2961|1238|
|b) Per Capita Income|656|16|
|c) Household Expenditure|206|28|
|d)Per Capita Expenditure|55|9|

Note:

1.        Extreme values of income and expenditure were excluded.  Households with annual income above 50,000 Namibian dollars and monthly expenditure above 10,000 Namibian dollars were excluded as extreme values. Households reporting zero income or expenditure were also excluded.

2. Statistical significance of the coefficients are indicated by * for 5 percent and ** for 1 percent.

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Several factors are identified by the study, including: (i) poor management; (ii) lack of resources (both human and financial); (iii) lack of staff expertise to implement the mandates; and (iv) the weak sanctioning environment. To address these weaknesses, several recommendations are put forward in the study. With regards to donor support, the study points out that they could help the government streamline procedures and improve the country’s administrative capacity to account for public funds (e.g. computerization of the financial management systems). Donors might also work together with civil society and the private sector to sensitize them about the negative impact of corruption on the development of the country and promote active engagement of all stakeholders in monitoring government activities and supporting changes in practices.

A PE study was also carried out to understand how political factors may influence economic diversification in Zambia, especially in tourism, livestock development and metal fabrication (Taylor, 2010). The tourism sector appears to suffer from neglect, notwithstanding statements of it being a priority sector, and is characterized by weak capacity and mismanagement of resources, which have undermined the sectors capacity to grow and produce jobs. Although Tourism has been promoted as the third pillar of the Zambian economy since the 1970s, there has been relatively little investment in the sector. In the livestock sector, the deficiencies in veterinary service, which has necessitated bans on the movement of cattle, may have exaggerated the presence of disease and favored the interests of the dominant players in this sector. In this context, the study recommends using a more grassroots approach, which might be more feasible politically because it will not be seen as benefiting or empowering political rivals, and focusing on interventions in rural areas.

# **4. How useful are PE studies for tasks managers?**

Based on these studies, findings and recommendations, several task team leaders (TTLs)<sup>8</sup> were interviewed to assess how PE analysis had or had not changed the way they support the design and implementation of projects and the nature of policy dialogue in Zambia in their respective areas. The discussions were valuable for assessing the utility of the PE studies and drawing some lessons from the Zambian case study.

> 8 Infrastructure (electricity, water, and telecommunications), agriculture, private sector, procurement and financial management were included.

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2 The Rise and Fall of Training and Visit Extension: An Asian Mini-drama with an African Epilogue

# <u>Abstract</u>

The paper reviews the origins and evolution of the Training and Visit (T&V) extension system, which was promoted by the World Bank in the period 1975-1998 in over 50 developing countries. The discussion seeks to clarify the context within which the approach was implemented, and to analyze the causes for its lack of sustainability and its ultimate abandonment. The paper identifies some of the challenges faced by the T&V approach as being typical of large public extension systems, where issues of scale, inadequate interaction with the agricultural research systems, inability to attribute benefits, weak accountability, and lack of political support tend to lead to incentive problems among staff and managers of extension, and limited budgetary resources. The different incentives and outlook of domestic stakeholders and external donor agencies are reviewed as well. The main cause of the T&V system’s disappearance is attributed to the incompatibility of its high recurrent costs with the limited budgets available domestically, leading to fiscal unsustainability. The paper concludes with some lessons that apply to donor-driven public extension initiatives, and more generally to rural development fads. The role of timely, independent, and rigorous evaluative studies is specifically highlighted.
regressions to contrast with the ones for SMEs. Throughout, the sample used is a pure cross-section in that each country and firm is included only once. The most recent round of ES available for the country is used. The firms were surveyed between 2006 and 2018. For our baseline regressions, the sample consists of 12,980 firms spread across 85 countries.

# 2.1 _Estimation methodology_

The baseline regression exercise involves estimating the following equation: where subscript _i_ denotes the firm, _j_ the country to which the firm belongs. _Y_ is a dummy variable indicating R&D activity during the last year (defined below); _Informal Competition_ is a measure of competition that the firm faces from the informal sector firms. _YFE_ is a set of dummy variables for the survey year (Year fixed effects) and _IFE_ denotes dummy variables for the industry to which the firm belongs (Industry fixed effects). _Firm Controls_ and _Country Controls_ include various firm- and country-level controls, respectively (discussed below). _u_ is the error term.

Unless stated otherwise, logit estimation method is used for estimating the above equation.<sup>3</sup> All regressions use Huber-White robust standard errors clustered on the country or on the subnational level as appropriate.<sup>4</sup> We pay due attention to endogeneity concerns (details below).

> 3 The only exception is the two-stage instrumental variables (IV) estimation in section 4.4. For this estimation, the IV probit method is used.

> 4 In one robustness check (section 4.2), we exploit variation at the sub-national level. In these regressions, the standard errors are clustered at the corresponding sub-national level.

9