rafmacalaba/datause-encoder-data huggingface dataset:
||Infrastructure<br>rehabilitation and<br>construction|Rehabilitate and construct critical transportation,<br>communications, and electricity infrastructure to connect<br>thenorthto thenationalandregionaleconomy.|244,324.00|1,025,707.80|1,270,031.80|
|---|---|---|---|---|---|
||Private sector<br>development and<br>financing services|Create a business-enabling environment to support income<br>generation, trade, and employment creation.|6,956.10|14,331.30|21,287.40|
||Environmental<br>sustainability|Protect the fragile environment in northern Mali through<br>adapted recovery and development activities and a focus on<br>natural resource management.|25,100.00|41,541.10|66,641.10|
|**Total Socioecono**|**mic(CFAF, millions)**||**594,494**|**1,823,085.2**|**2,417,579.2**|
|**Percentage (%)**|||**77%**|**90%**|**86%**|
|**TOTAL MIEC**|||**772,398.6**|**2,033,106.3**|**2,805,504.90**|

_Source_ : World Bank 2016.

28 Table has been rearranged along the lines of the components of the Peace Accord.

29 The MIEC subcomponent ‘Displacement, returnees and resilience of host communities’ (42,054.1 CFAF million) is not included in this table since we are only looking at Governance, Security and Socioeconomic Development in this paper (components 1-3 of the Peace Accord), not component 4 which deals with Reconciliation, Justice and Humanitarian issues and includes return, repatriation and reintegration of the displaced population.

27
programs which are meant to cushion the impact of higher prices on the poor (World Bank 2008b). The third are programs and policies to boost domestic food production both over the immediate and medium run.

The present paper seeks to provide evidence on a few questions arising from the rise in global prices with a focus on sub-Saharan Africa. First to what extent have the poor in Africa been affected by these price rises? Second what types of policies have been put in place and how do responses in Africa differ from the rest of the world? Third, to what extent are the policies implemented in Africa targeted to the poor and how can they be improved?

The paper is divided into two main sections – poverty impacts and policy response. It starts by discussing a standard methodological approach to estimating the poverty impact of rising food prices. It then moves to presenting estimated changes in poverty due to higher prices, focusing on recent work in several African countries. This ‘poverty impact’ section concludes by illustrating the relevance of using poverty maps to show how the impact of these price rises varies within a country. The policy response section begins by comparing the way sub-Saharan African countries are responding to rising food prices with other countries. It also discusses the merits of possible policy responses by examining the extent to which three common responses – reducing import tariffs and expanding feeding and public works programs – benefit the poor.

# **2. Assessing the Distributional and Poverty Impact of Price Rises**

# **_2.1. Methodological Issues_**

The analysis of the distributional impact of price rises follows a simple methodology outlined by Singh et al. (1987) and Deaton (1989, 1997). Deaton (1989) defines a ‘net consumption ratio’ as the elasticity of the cost of living with respect to changes in prices. For net producers this elasticity is negative and for net consumers it is positive. In his work in Thailand Deaton showed that middle class farmers benefited most from a price rise relative to either the poorest or wealthy rural households. These methods were subsequently applied among others by Barret and Dorosh (1996) using data from Madagascar, Budd (1993) in Cote d’Ivoire and Klytchnikova and Diop (2006) in Bangladesh. The argument made is that the non-parametric techniques implicit in Deaton’s methodology do not impose any structure on the data and hence make full use of the information available. Analyses of the recent food price rises also use this method as well as simple summary statistics (Ivanic and Martin 2008 and Wodon et al. 2008a).

Deaton’s framework can be summarized as follows. The change in welfare following a change in prices for a household is: Δ _wi_ = Δ _p_ [( _PRi_ − _CRi_ ) +η _Li_ ]
first commitment period (2008-2012) or comply with their commitments during that period;

- Russia and Economies in transition stabilize their emissions at their 2015 emission levels until 2030, and they do not sell their surplus allowances during the first commitment period;

- Australia’s 2020 and 2030 emissions would be 10 percent and 20 percent below from its 1990 emission level.

It is possible to develop a large number of scenarios. However, we have limited to two plausible scenarios for the sake of clarity. One additional scenario which assumes developing countries to stabilize their CO2 emissions before 2020, say 2015, could be developed. Moreover, non-Annex I countries could be assumed not only stabilizing their emissions at the level of their 2020 or 2025 emissions but also reduce gradually thereafter. However, following the current post-Kyoto negotiations, such scenarios might be unlikely. Still, the study could be extended further to include these scenarios.

The scenarios considered in this study have been developed in line with the longterm stabilization paths considered in the most existing studies. For example, IPCC (2007) projects that a scenario to stabilize CO2 concentrations between 440 ppm and 485 ppm requires global CO2 emissions in 2050 to be limited to -30 percent to +5 percent of 2000 level. Stern (2006) suggests that stabilizing CO2 concentrations around 440 to 500

-22-
of well-being that this measure cannot hope to capture, and we say nothing here about how responsive these other dimensions may be to growth.

While the NSS surveys are highly comparable over time by international standards, there is a particular comparability problem in the rounds since the early 1990s. While most of the surveys have used a uniform recall period of 30 days for all consumption items, seven of the survey rounds in the post-1991 period have instead used a mixed-recall period (MRP), with longer (one year) recall for some (mainly non-food) items.<sup>27</sup> On a preliminary investigation of the data we found that the use of a mixed recall period increased the mean and reduced inequality, implying lower poverty measures. All our regressions below include a control for MRP survey rounds.

**_Poverty lines and price indices:_** We report results for two poverty lines.  Following Datt and Ravallion (2011), one line is that originally defined by the Planning Commission (1979), and endorsed by Planning Commission (1993). This poverty line is anchored on a nutritional norm of 2,400 calories per person per day in rural areas and 2,100 calories for urban areas, and corresponds to a per capita monthly expenditure of Rs. 617 and Rs. 922 (rounded to the nearest rupee) in rural and urban areas respectively at 2011-12 prices.<sup>28</sup> The second poverty line corresponds to the rupee value of the international poverty line of $1.25 per person per day at 2005 PPP dollars, and are equivalent to rural and urban per capita monthly expenditures of Rs. 732 and Rs. 1,115 at 2011-12 prices.<sup>29</sup> The second set of lines are thus about 20% higher than the first set of lines.

The nominal values of the poverty lines for different NSS rounds are evaluated using separate urban and rural price indices. Our price indices are mainly based on the all-India Consumer Price Index for Industrial Workers (CPIIW) as the deflator for the urban sector, and the all-India Consumer Price Index for Agricultural Laborers (CPIAL) as the deflator for the

> 27 In particular, one-year reference is used for clothing, bedding, footwear, education, medical (institutional) and durable goods. Mixed reference periods have been used for seven NSS rounds in our data, viz., rounds 55, 56, 57, 58, 59, 60 and 62.

> 28 The original Planning Commission lines correspond to rural and urban per capita monthly expenditures of Rs. 49 and Rs. 57 at 1973-74 prices. At 2005 purchasing power parity (PPP), these lines have a value of $1.03 per day in 2005. See Ravallion (2008) for further discussion, including comparisons with a higher international poverty line.

> 29 Neither set of lines is directly comparable to India’s current official “Tendulkar” poverty lines. At 2005 PPP, the Tendulkar lines have a value of $1.17 per day in 2005, incorporating a lower cost of living differential rural and urban areas than the original Planning Commission lines on which our poverty line series is based. The Tendulkar poverty lines are only available after 1993-94.

8
Of course, an exercise such as this is sensitive to several assumptions. In particular, the labor market penalty associated with having been stunted at age 36 months (drawn from Hoddinott et al. 2013) appears to be quite high. We estimate that the program would have a benefit/cost ratio of greater than one if hourly wages for those who were stunted are 0.75 or less than those who were not stunted. Further we have simplified the cost implications of switching from a household to a village targeting mechanism. Adding more households to the beneficiary rolls would undoubtedly increase total administrative cost to some degree, yet at the same time the adoption of a village-based targeting rule may require far less household information to be collected and so would likely provide savings in this dimension. Finally, other welfare benefits from stunting aversion, such as increased longevity and non-pecuniary benefits from increased educational attainment and higher cognitive ability, are not accounted for in this exercise but would serve to increase benefits without affecting the cost of program expansion.

85
# <u>Criterion (1)</u>

When separating economic and social spending as ratios of GDP, according to Criterion 1, only economic spending appears to be positive for growth. The results are presented in Tables 3 and 4<sup>60</sup> .

Table 3 (OLS with annual data) shows that the coefficients for both economic and social expenditures are positive but only the one of economic public spending is statistically significant at 10 percent, indicating **a positive effect on growth of economic public spending in the short term** .

The results also indicate that there is a strong positive effect of macroeconomic stability on growth as the coefficient obtained for inflation is negative and statistically very significant at a 1 percent level.

Table 4 (OLS and SURE with 3-year average) presents similar results in terms of coefficients with economic public expenditures being statistically significant at 5 percent and 1 percent, respectively. This may indicate that **economic public expenditures not only have a transitional effect on growth but also affect its path over the mediumterm**<sup>61</sup> .

Regarding the positive effect of macroeconomic stability on growth, the coefficients obtained using three-years averages corroborate those reported in Table 3. The negative sign for inflation is statistically significant at a 5 and 1 percent level respectively, **indicating the vital importance of maintaining macroeconomic stability to sustain growth over the medium-term** .

Finally, it is interesting to notice that the negative effect of total fiscal revenues on growth that was detected in earlier regressions becomes particularly significant for nontax revenues when using this specification. It is possible to interpret this result on the basis of country evidence indicating that non-tax fees levied by the government in both economic and social sectors may have been more detrimental to growth that tax compliance obligations<sup>62</sup> .

# <u>Criterion (2)</u>

When disaggregating total public spending to distinguish between _a priori_ productive and unproductive spending (Criterion 2), the results indicate that, in fact, it is productive

> 60 Due to the small sample and data limitations, it is not possible to obtain coherent findings using the GMM method with this criterion.  Better results are later found using Criteria 2.

> 61 These results should, however, be interpreted with some caution, given that the sample size drops significantly as a result of data averaging.

> 62 For example, this may be particularly relevant in Singapore where a formal welfare system has never been established and the government has used a compulsory savings scheme to allocate funds to some workers’ compensation benefits.

15
January 2015. Eligible households received their first payment in June 2015, the second in October, and the third in January 2016.

Instead of sticking to a quarterly schedule, operational issues delayed the fourth and fifth transfers, which took place in July 2016 and January 2017. The sixth and seventh transfers were made in the spring 2017, while the last transfer happened at the end of the following school year and just before the endline, in June 2018.

# 6. Data

Baseline data was collected between May and August 2014 and endline data was collected four years later, between May and August 2018. The sample from the control villages included households who would have been eligible, i.e., were poor and had children. Unfortunately, because of coding errors in the household roster in the endline data, we are only able to follow households, but not individuals, across both survey waves, limiting our ability to conduct individual-level panel analyses.

# 7. Sample balance at baseline and household characteristics

In Table 2 we show the baseline balance of the sample in terms of education measures. At baseline, the characteristics of treatment and control villages were similar. The education module of the baseline surveyed children aged between 5 and 15 years old, although two-thirds of the surveyed children were aged 10 and below, in both waves. The total number of children surveyed in the first wave is 11,350.

Table 2 shows that there are no differences, at the baseline, between treated and control villages for the following variables: age of children, proportion of girls, tests scores in mathematics, French and Raven (an ability measure) and whether the child can read. Household size is significantly higher in control villages (9.4 vs 9.0). Finally, within the control group, 4 percent are from “other ethnicities” versus 2 percent in the treatment group. These are the only significant differences between the groups at baseline, and we do not expect these differences to drive our results.

# 8. Attrition

Attrition between the baseline and the endline is almost non-existent. We had 4,697 households at the baseline, and we have 7 more households by the endline. However, we lost 3 households in the control villages, and gained 10 in the treated villages. Gained households are in fact households that split but that we managed to follow.

In any case, the empirical strategy does not use the panel structure of the data, as children aged between waves. Any child aged above 11 years old interviewed at the baseline is not interviewed 7
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- **Kaur, Supreet.** 2019. “Nominal Wage Rigidity in Village Labor Markets.” _American Economic Review_ , 109(10): 3585–3616.

- **Kline, Patrick, Neviana Petkova, Heidi Williams, and Owen Zidar.** 2019. “Who Profits from Patents? Rent-Sharing at Innovative Firms.” _Quarterly Journal of Economics_ , 134(3): 1343–1404.

- **Kramarz, Francis, and Thomas Philippon.** 2001. “The Impact of Differential Payroll Tax Subsidies on Minimum Wage Employment.” _Journal of Public Economics_ , 82(1): 115– 146.

- **Kreiner, Claus Thustrup, Jakob Roland Munch, and Hans Jørgen WhittaJacobsen.** 2015. “Taxation and the Long Run Allocation of Labor: Theory and Danish Evidence.” _Journal of Public Economics_ , 127(1): 74–86.

- **Krueger, Alan B, and Lawrence H Summers.** 1988. “Efficiency Wages and the InterIndustry Wage Structure.” _Econometrica_ , 56(2): 259–293.

- **Kugler, Adriana, and Maurice Kugler.** 2009. “Labor Market Effects of Payroll Taxes in Developing Countries: Evidence from Colombia.” _Economic Development and Cultural Change_ , 57(2): 335–358.

- **Ku, Hyejin, Uta Sch ̈onberg, and Ragnhild C Schreiner.** 2020. “Do Place-Based Tax Incentives Create Jobs?” _Journal of Public Economics_ , 191: 104105.

- **Lamadon, Thibaut, Magne Mogstad, and Bradley Setzler.** 2022. “Imperfect Competition, Compensating Differentials, and Rent Sharing in the US Labor Market.” _American Economic Review_ , 112(1): 169–212.

- **Laun, Lisa.** 2017. “The Effect of Age-Targeted Tax Credits on Labor Force Participation of Older Workers.” _Journal of Public Economics_ , 152(1): 102–118.

- **Lester, Richard.** 1967. “Pay Differentials by Size of Establishment.” _Industrial Relations_ , 7(1): 57–67.

- **Manning, Alan.** 2013. _Monopsony in Motion._ Princeton University Press.

- **Moscarini, Giuseppe, and Fabien Postel-Vinay.** 2018. “On the Job Search and Business Cycles.” IZA Discussion Paper 11853.

**OECD.** 2022 _a_ . “Taxing Wages 2022.” `https://www.oecd.org/tax/ taxing-wages-20725124.htm` .

41
respect to _퐸푡,푗_ , the event dummy. The number of lags for the dependent variable and the event dummy is denoted by p and set to 2 for estimation. This specification controls for country specific trends, lagged event dummies and past values of the dependent variable.

For our purpose, the potential endogeneity bias caused by contemporaneous interaction between financial sector variables and climate and environmental related natural disasters could reasonably be dismissed. It is unlikely that changes in banking sector asset quality, profitability and capital adequacy, for instance, can trigger natural disaster events, at least in the same year and several years after. In the longer run, when one’s focus is on transition risks, this direction of causality becomes more likely. Nonetheless, to guard against possible reverse causation between financial sector variables and disasters, lagged financial sector variables are used as controls.

# **5 Empirical results**

## **5.1 Non-performing loans**

We find that severe climate and environmental related natural disaster episodes lead to an increase in the level of system-wide NPLs to total gross loans, and the effects can be persistent (figure 3 and table 3). We consider two types of severe disaster episodes: a country-year identified by the EM-DAT database as associated with an official declaration of a state of emergency(as calls for international assistance are relatively rare) and a country-year consisting of multiple types of disaster episodes. As shown in figure 1, for the entire sample, the system-wide NPLs are estimated to have increased by 0.37 percentage point on impact after a disaster episodes associated with an official declaration of emergency. Two to three years after an episode with multiple types of disasters, the cumulative increase in system-wide NPLs stands at 0.56-0.6 percentage point on average. The magnitudes may seem to be modest, but at the country level, our estimates are probably biased against finding results of larger magnitude as most disaster episodes tend to affect selected regions within a country. This effect is likely due to the impact of disasters on repayment capacity of borrowers and damages to underlying collateral and hence on credit risks.

9
# **1. Introduction**

Every year, billions of dollars are spent to provide services to the poor in low-income countries. Unfortunately, there is a long-standing record of failures in delivery systems, whether in education, health, or other sectors. Empowerment of local communities in school management has received growing attention from both academics and practitioners in developing countries as part of a broad and global program to improve service delivery to the poor by involving them directly in the delivery process (World Bank 2004). The quality of local school management has been shown to be strongly associated with favorable education outcomes across countries (Bloom et al. 2014). In Africa, countries including Ghana, Niger, Senegal, Madagascar, Kenya, Rwanda, and Mozambique have already embraced variants of school autonomy in their education systems (Bruns, Filmer & Patrinos 2011).

In this research, we assess the medium-run impact of a program seeking to empower local communities in school management in The Gambia. On the one hand, local leadership may have significant additional information relative to the central authorities about local needs, local politics, and other constraints. Local management also may increase accountability (Bruns, Filmer & Patrinos 2011), as was observed and demonstrated with a school-based management and accountability program in Mexico (Gertler, Patrinos, & Rubio-Codina 2012). These would suggest that the program may be effective in improving student learning. On the other hand, local leadership or members of the community may also lack the competency (relative to central leadership) to design or implement the processes necessary to tackle local problems, suggesting that the program could be ineffective. The net effect of such a policy is ambiguous.<sup>3</sup> This paper uses a large field experiment in The Gambia to evaluate and draw lessons from a comprehensive school management and capacity building program – called Whole School Development (WSD). The intervention and subsequent data collection were carried out between 2007 and 2011.

In WSD schools, principals, certain teachers, and members of the communities received comprehensive training in school management. During this training, the schools' stakeholders (including the community) developed school management plans addressing short- and long-term goals in each of these areas. A national semi-autonomous WSD unit associated with the Ministry of Education guided them. In order to help schools initiate the implementation of their plans, the Ministry of Education provided a grant worth approximately US$500. To separate the effect of the grant from that of the training, another set of schools received a grant of the same size without the accompanying training component (called Grant-only schools).

> 3 Retrospective evaluations of such complex programs present many challenges, but early evidence from El Salvador’s community-managed schools program found positive impacts on participation and language skills (Jimenez and Sawada 1999).

2