rafmacalaba/datause-encoder-data huggingface dataset:
per square kilometer and per year over the period 1995-2010.<sup>8</sup> This is a strong instrument as is evidenced by the Kleibergen and Paap (2006) test (henceforth KP) statistic of 66 reported in the bottom panel of column 7 of Table 2. As was shown in Figure 1b areas buffeted by more intense lightning strikes have worse internet access. The 2SLS estimate of the impact of the internet on Daesh recruitment is statistically significant at the 10 percent level and is three times as large as its OLS counterpart. Our exclusion restriction hinges on the assumption that lightning strikes affect the propensity to join Daesh only through the availability and quality of internet. As lightning is correlated with rainfall ( _ρ_ = 0 _._ 63 in the data), which could affect economic development (e.g. through higher agricultural productivity), column 7 controls for averages of nighttime lights and rainfall over the period 1995-2010, which is also the time interval the instrumental variable is constructed from. Choosing lagged variables further mitigates the possibility that internet access has had an impact on nighttime lights, which could bias the first stage. In column 8, we revisit these results by controlling for delegation-level measures of radicalization into violent extremism used in column 5; if anything, doing so produces larger estimates for the of internet access.

**Robustness** Table 3 shows the results of a number of robustness checks. Where applicable, we present both OLS regression results (with delegation, age, and education fixed effects as in Table 2, column 6) in panel A and 2SLS estimates in panel B, using lightning strikes as instrument for internet access rates (as in Table 2, column 7).

We start by estimating three alternative specifications. In Table 2, column 7, we argued that satisfying the exclusion restriction requires controlling for GDP proxies and climatic data. We therefore added rainfall and nighttime light intensity variables as controls, and averaged these variables over the same time span as for the instrument, 1995-2010. We use 2014 averages instead to measure values of GDP and rainfall that are contemporaneous with the dependent variable. The estimated 2SLS coefficient for internet access (panel B, column 1), though slightly lower, is still significant at the 5 percent level. Next, we investigate whether the documented association between internet and jihadist recruitment could be driven by usage of other media.

> 8Yearly data on lightning strikes with the same level of geographical detail is not available (Manacorda and Tesei, 2020) and lightning strikes are highly serially correlated (Andersen et al., 2012).

13
|Second Regional Trade Facilitation Competitivess Credit<br>Jacques Morisset|
|---|
|StrengtheningAgri-Food Value Chains<br>Mohamed Medouar|
|StrengtheningAgri-Food Value Chains<br>Mohamed Medouar|
|StrengtheningAgri-Food Value Chains<br>Mohamed Medouar|
|StrengtheningAgri-Food Value Chains<br>Mohamed Medouar|
|StrengtheningAgri-Food Value Chains<br>Mohamed Medouar|
|StrengtheningAgri-Food Value Chains<br>Mohamed Medouar|
|Statistics for Decision Makingin Kosovo<br>Monica Robayo|
|Statistics for Decision Makingin Kosovo<br>Monica Robayo|
|Statistics for Decision Makingin Kosovo<br>Monica Robayo|
|AGRICULTURE POLICY MONITORING AND EVALUATION CAPACITY BBekzod Shamsiev|
|AGRICULTURE POLICY MONITORING AND EVALUATION CAPACITY BBekzod Shamsiev|
|West African Medicines RegulatoryHarmonization<br>Aissatou Diack|
|West African Medicines RegulatoryHarmonization<br>Aissatou Diack|
|West African Medicines RegulatoryHarmonization<br>Aissatou Diack|
|West African Medicines RegulatoryHarmonization<br>Aissatou Diack|
|NP Modernization of Rani Jamara Kulariya Irrigation Scheme - PhaseShyam KC|
|NP Modernization of Rani Jamara Kulariya Irrigation Scheme - PhaseShyam KC|
|NP Modernization of Rani Jamara Kulariya Irrigation Scheme - PhaseShyam KC|
|NP Modernization of Rani Jamara Kulariya Irrigation Scheme - PhaseShyam KC|
|NP Modernization of Rani Jamara Kulariya Irrigation Scheme - PhaseShyam KC|
|Agriculture Modernization Project<br>SergiyZorya|
|SUPPORT TO EXTRACTIVE INDUSTRIES TRANSPARENCY INITIATIVE CDavid Reinstein|
|SUPPORT TO EXTRACTIVE INDUSTRIES TRANSPARENCY INITIATIVE CDavid Reinstein|
|SUPPORT TO EXTRACTIVE INDUSTRIES TRANSPARENCY INITIATIVE CDavid Reinstein|
|SUPPORT TO EXTRACTIVE INDUSTRIES TRANSPARENCY INITIATIVE CDavid Reinstein|
|SUPPORT TO EXTRACTIVE INDUSTRIES TRANSPARENCY INITIATIVE CDavid Reinstein|
|SUPPORT TO EXTRACTIVE INDUSTRIES TRANSPARENCY INITIATIVE CDavid Reinstein|
|SUPPORT TO EXTRACTIVE INDUSTRIES TRANSPARENCY INITIATIVE CDavid Reinstein|
|SUPPORT TO EXTRACTIVE INDUSTRIES TRANSPARENCY INITIATIVE CDavid Reinstein|
|SUPPORT TO EXTRACTIVE INDUSTRIES TRANSPARENCY INITIATIVE CDavid Reinstein|
|BankingSector StrengtheningProject<br>Johanna Jaeger|
|BankingSector StrengtheningProject<br>Johanna Jaeger|
|BankingSector StrengtheningProject<br>Johanna Jaeger|
|BankingSector StrengtheningProject<br>Johanna Jaeger|
|BankingSector StrengtheningProject<br>Johanna Jaeger|
|BankingSector StrengtheningProject<br>Johanna Jaeger|
|Rwanda Improved Cookstoves Project<br>Pablo Cesar Benitez Ponce|
|Rwanda Improved Cookstoves Project<br>Pablo Cesar Benitez Ponce|
|Rwanda Improved Cookstoves Project<br>Pablo Cesar Benitez Ponce|
|GEF TurkeyIrrigation Modernization Project<br>Pieter Waalewijn|
|GEF TurkeyIrrigation Modernization Project<br>Pieter Waalewijn|
|GEF TurkeyIrrigation Modernization Project<br>Pieter Waalewijn|
|Malawi Agricultural Commercialization Project<br>Francisco Javier Obreque Arqueros|
|Malawi Agricultural Commercialization Project<br>Francisco Javier Obreque Arqueros|
|Malawi Agricultural Commercialization Project<br>Francisco Javier Obreque Arqueros|
|Malawi Agricultural Commercialization Project<br>Francisco Javier Obreque Arqueros|
saved more when they received their wages into their own account through direct deposit (Breza, et al., 2020). Likewise, workers in Afghanistan who automatically deposited part of their salary into a mobile savings account had higher savings and financial security than workers who did not (Blumenstock, et al., 2018).

In the realm of payments, receiving them directly into an account brings several benefits over receiving them in cash, including reduced transaction costs and increased safety. Teachers in Liberia, for example, saw the cost of collecting their money (including bus fare) reduced by 84 percent—from US$25 per paycheck to US$2—when they received their salaries as digital deposits. Because they no longer had to take time off to collect their wages, they were able to spend more time in the classroom (USAID, 2016). The teachers also experienced a safety benefit, as they were able to avoid traveling with cash in their pockets.

This safety connection between digital payments and crime has also been documented in highincome economies. For example, an analysis of 20 years of crime data from the US state of Missouri and nearby areas found that the introduction of digital safety net payments reduced burglary, assault, and larceny, lowering overall crime rates by about 9 percent (Wright, et al, 2017).

# **_3.1 Government payments as a driver of broader financial usage_**

In developing economies, many payments from the government—such as social transfer and wage payments—are still made in cash. However, in high-income economies they are typically paid into an account.<sup>4</sup> There is broad evidence showing that digitalizing these payments benefits both the government and the citizens receiving them. In India, for example, internal fraud and leakage from pension payments dropped by 47 percent when the country transitioned from cash to smart cards. Recipients spent less time collecting payments and received more money because of the fraud reductions. The government saved millions of dollars annually in administrative costs—more than enough to cover the cost of the new system (Muralidharan, et al., 2016).

Beyond South Asia, a study of safety net payments made primarily to women after a drought in Niger found that social benefits paid through mobile phones instead of in cash offered women

> 4 In the U.S., some government payments are made to cards that can only be used to make payments, but cannot be used to deposit money and are therefore not considered an account.

8
TABLE 1

# Sensitivity Results for Basic Variables

Non-Oil Countries Regressions on Growth of Per Capita Income 1960-1989

||Beta|Stan.Err.<br>T-Stat|N|Re|Cther Incl. Vars.*|
|---|---|---|---|---|---|
|Investment<br>|Share<br>of <br>|GDP<br>(INV)<br><br>||||
|High??|19.555|2.845<br>6.87|89|56|STDI, BMP, GOV|
|Low|12.762|3.070<br>4.16|97|46|XSG,LIT,REVC|
|RealGDPp|ercapita|in1960<br>(RGDP60)||||
|<br>High|<br>-.299|<br><br>.138<br>2.16|97|-50|LAAM,XSG,GOV|
|Low|-.541|142<br>3.82|78|- 60|<br>GDC, BMP,LIT|
|Growth<br>in<br>|Population<br>|(GPO)<br><br>||||
|<br>High|<br>131|221<br>59|100|.84|x22,LAAM,PRI|
|Low|-.546|234<br>2.33|90|-56|<br>X,BMP,MIX|
|Secondary|School Enr|ollment Ratio<br>in 1960<br>(SEC)||||
|High|3.708|1.222<br>3.04|84|-55|X,GOV,GDC|
|Low|.572|1.208<br>47<br>Regression on Investment<br>S|91<br>hare|64<br> 1960-19|BMP,LAAM,AFRICA<br>89|
||Beta|Stan.Err.<br>T-Stat|N|rR?|Other Incl. Vars.+*|
|Real GDP p|er capita|in 1960<br>(RGDP60)<br>1960-1989||||
|High|.007|003<br>2.23|85|.07|GbdC,SOC,STDI|
|Low|-.010|.005<br>2.15|89|625|CIVL, BMP, GOV|
|Growth<br>in|Population|(GPO)<br>1960-1989||||
|<br>High|<br>006|007<br>.82|93|25|CIVL,LAAM,<br>BMP|
|Low|-.016|006<br>2.65|86|09|SOC ,STDI,GDCc|
|Secondary|School Enr|ollment Ratio<br>in 1960<br>(SEC)|1960|-1989||
|High|059|.042<br>1.39|84|-15|CIVL,GDC,GOV|
|Low|-.003|039<br>+07|90|21|BMP,GOV,CIVL|

* INV, RGDP60. GPO, and SEC included in all Growth regressions ** no additional variables included in the Investment regressions

2lthe high beta is the coefficient from regression which obtains the highest beta bound in the extreme bounds analysis. The low beta is from the regression which obtains the lowest beta bound. 22the underlined variables show additional variables which make the coefricient of interest insignificant or change sign. In this case the regression of GYP on INV,RGDP,SEC,GPO, and X yields an insignificant coefficient on GP).

36
# **Addressing Educational Disparity:**

## **Using District level Education Development Indices (EDI) for equitable resource allocations in India**

### **Dhir Jhingran and Deepa Sankar**

### **Introduction:**

The challenge of development work in the social sector in India today is one of bridging huge disparities across regions of the country, gender and social groups. Unless national and state policies specifically target to address these disparities, achieving ‘equality in outcomes’, which is the real goal for human development in education and health will only remain a pipe dream. While inputs, in terms of financial resources and administrative attention, can alone not make a big impact, it is essential that policy and program designs in these crucial social sectors promote a strong equity oriented approach that ensures that regions and population groups that have been lagging behind receive much higher attention and resources. Providing a more equitable distribution of public resources and effort would be a prerequisite for bridging gaps in education, health and other key human development indicators. Persisting with an ‘equal, non-discriminatory’ approach towards investments and attention will not help us move towards achieving some degree of equality in outcomes.

This may seem quite logical and rational, but is often not included as a central piece of national or state policy and program designs. Apart from the commitment to equitable allocation of resources, one of the prerequisites of an equity-oriented approach to social sector investments is that there is strong commitment to making the planning in these sectors more evidence based. Improved targeting of resources and effort can happen only when reliable data is collected and analyzed regularly to understand: (a) the present situation of different regions and social groups on indicators reflecting key outcomes; (b) past trends in investments and outcomes; and (c) the gaps that need to be bridged in terms of key outcomes. This would help identify the kind of enhanced inputs and outputs required for areas and groups that are lagging behind enabling planners to make evidence-based decisions and preferential allocation of funds or design special interventions for specific pockets or groups. This is not to say that enhanced investments or improved design of schemes would directly result in improved outcomes. Outcomes in the social sector are the result of complex processes that need attention. These processes will need to be studied for translating outlays to some outcomes. The identification of key deficits and the recognition of the need for prioritized focused attention in some areas is the first step towards bridging disparities.

We took up the case of _Sarva Shiksha Abhiyan (_ SSA- the Indian government’s Elementary Education for All Mission) to understand how this flagship program relates investments to spatial and social group based disparities. The case study looks at the following questions: 2
WPS3939

# **Earthquake Vulnerability Reduction Program in Colombia A Probabilistic Cost-benefit Analysis**

_Francis Ghesquiere, World Bank Luis Jamin, University of Los Andes Olivier Mahul, World Bank_<sup>1</sup>

## **Abstract**

Cost-benefit analysis is a standard tool for determining the efficiency of planned projects. However, one of the major difficulties in risk mitigation investments is that benefits are by nature uncertain. In this context, the standard approach relying on the average value of benefits may provide an incomplete picture of the efficiency of the risk mitigation project under consideration. This paper presents a probabilistic cost-benefit analysis relying on a catastrophe risk model. It produces risk metrics such as the exceedance probability curve of the benefit-cost ratio, thus providing the decisionmaker with a more complete risk analysis of the net benefits of the project. This is illustrated with the earthquake vulnerability reduction project in Colombia.

**Key words:** Colombia, cost-benefit analysis, disaster risk management, earthquake, probabilistic risk models.

## World Bank Policy Research Working Paper 3939, June 2006

_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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

> 1 Corresponding author: MC 9-904; 1818 H Street, NW; Washington, D.C. 20433.  Phone: (202) 458-8955. Email: <u>omahul@worldbank.org.</u>
Policy Research Working Paper 11080

# **Abstract**

This paper examines rural non-farm employment in Rajasthan, India, using multiple surveys and administrative data. The analysis covers three key aspects: individual and district-level determinants of participation in non-farm activities, the relationship between non-farm employment and household welfare, and barriers faced by rural enterprises. The findings show that secondary education strongly predicts participation in non-farm activities, particularly in skilled service sector jobs. However, women and socially marginalized groups face significant barriers in accessing non-farm employment, especially in higher-paying occupations. Households with members in regular non-farm employment, particularly in services, show significantly higher consumption levels, while casual non-farm work yields welfare levels similar to agricultural labor. Rural enterprises face multiple constraints, with lack of local demand and limited access to credit emerging as key barriers to business performance. The results suggest that although non-farm employment can substantially improve household welfare, access to better-paying opportunities remains highly unequal. Policy interventions should ad-dress both human capital development and structural barriers to create more inclusive access to non-farm employment opportunities.

This paper is a product of the Agriculture and Food Global Department. 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 fdarko@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
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48
13 The rice NACs over the 1972-74 period fell by more than two-fifths for both highincome and developing countries. The NAC falls for wheat were not as severe as for rice, but were still substantial at more than one-quarter for high-income countries and nearly one-third for developing countries. The extent of annual decline in the NACs in the most recent price spike is slightly less than in the 1970s except for high-income wheat, and not quite as rapid: between 2005 and 2008 the NAC for rice fell 29 percent for high-income countries and 36 percent for developing countries, and for wheat it fell around 37 percent for both high-income and developing countries (Table 5). That slightly smaller and slower decline also is consistent with the fact that there were smaller and slower proportionate rises in the international prices of those cereals in 2005-08 than in the early 1970s.

Turning to all covered farm products (bottom segment of Table 5), the NAC for developing countries fell by 16 percent in the first two years before rising by half that amount in the subsequent two years of the 1970s’ spike period. The fall for high-income countries was almost the same (14 percent) but it more than recovered in the subsequent two years. As for the mid-1980s price slump period, the NAC rise for all farm products was larger for highincome countries and smaller for developing countries in1984-86 than the fall in 1972-74, consistent with the findings discussed above from Table 4(b) and Figure 3(a).

Table 6 allows an easy comparison between the mid-1980s, and the two upward price spike periods, of annual price changes in NACs. It also suggests there is little difference not only in the magnitude but also in the timing of the responses of food-importing and foodexporting countries. That is the case not only for rice and wheat (illustrated in figure 3(b)) but also for all products included in the World Bank’s database, shown at the bottom of Table 6.

In Table 7 the NRAs have been decomposed into the various border and domestic measures for developing and high-income countries, for all products covered by the World Bank’s database, following the methodology in Croser and Anderson (2010). The annual
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