rafmacalaba/datause-encoder-data huggingface dataset:
Table B11: Heterogeneous treatment effect on malaria awareness

||Depend|ent variable: Y =|1(Malaria is a pro|blem)|
|---|---|---|---|---|
||(1)<br>OLS|(2)<br>OLS|(3)<br>OLS|(4)<br>OLS|
|Sub-sample|All|All|Male|Female|
|Treatment|0.045|-0.035|0.008|-0.054|
||(0.065)|(0.047)|(0.076)|(0.046)|
|Treatment x ndvi = 1|-0.064||||
||(0.078)<br>[0.668]||||
|Treatment x ndvi = 2|-0.005<br>(0.093)||||
||[0.516]||||
|Treatment x work = 1||0.127**|0.053|0.166**|
|||(0.058)|(0.097)|(0.073)|
|||[0.041]|[0.285]|[0.075]|
|Work||-0.020|0.029|-0.037|
|||(0.049)|(0.083)|(0.056)|
|ndvi = 1|0.277***<br>(0.101)||||
|ndvi = 2|0.286**||||
||(0.140)||||
|Observations|1499|1273|535|876|

Note: *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1. One observation per household. The dependent variable is an indicator variable equal to 1 if the respondent reported that malaria is an issue in their community and zero otherwise. Columns (1)-(4) report the difference between treatment and control groups using OLS regression (model 2) and the coefficients on interactions between the treatment status and vegetation index dummies in Column (1) and between the treatment status and the employment status in Columns (2)-(4). Standard errors clustered at village level are reported in parentheses. All specifications include controls for gender, age, education and marriage status of the respondent, household size, tribe and religion, information about access to water, dwelling characteristics, sub-zone dummies and village characteristics (size and share of women living in the village). The p-value for the F-test of _treatment_ + _tinteraction_ = 0 is reported in square brackets.

27
non-project firms. This study shows the importance of integrating both qualitative and quantitative sampling techniques to obtain a sample representative of the population with the specific desired characteristics. Such quantitative sampling techniques help to ensure that qualitative samples meet standards in being adequately representative, and contribute to ensuring that claims regarding the implications of these findings for wider populations are well founded.

**b) Tailored concepts:** Qualitative analysis may be useful to explore the dimensions of the indicators used in the design. Definitions of concepts such as ‘corruption’, ‘justice’ or ‘transparency’ may vary widely across individuals, locations or sectors. Exploring the meanings of indicators according to the context and incorporating them into the quantitative data collection methods is not only critical to obtain accurate data from surveys, but also plays a key role in establishing and explaining causation.

As an example, the concept of ‘delay’ in clearing goods in a border post may have different meanings depending on the sector and for people working at different points in the distribution channel. For importers of ultra-fresh products, a ‘delay’ might be understood as more than one day, while for other sectors (e.g., processed food), it might represent more than three days. Also, the definition may vary per location.

Hence, understanding the dimensions of the indicators in their context (and for different personnel within a given context) is necessary to understand what is intended to being measured. Rao and Woolcock (2003) describe how a survey on the incidence of domestic violence in India generated rates far below expectations. Initial survey results suggested that the incidence of household violence in India was even lower than in the US, but when researchers conducted qualitative analysis of this issue they found that domestic violence was understood differently relative to the context (e.g., a slap would not be considered as domestic violence by the average Indian household). Hence, the survey questions and results were inaccurate and did not reflect an accurate domestic violence situation. Even though quantitative approaches can be applied to measure changes in these outcomes, understanding the definitions of concepts is key to establishing valid quantitative measures for these concepts (i.e., to ensuring high ‘construct validity’).

13
**Figure 5. The ratio between the high and low values of capital costs**

Note: Author’s calculations are based on data from Lazard (2019), NREL (2019), IRENA (2020), IEA (2015), and EIA (2018).

There are multiple reasons for the variations of capital costs for the given technology type. Capital costs vary because of different technological configurations. Solar PV panels based on amorphous and crystalline silicon technologies are very different. Gas-fired power generation technologies are either open cycle type or combined cycle type. The former has only one turbine per unit, whereas the latter uses two turbines, one gas turbine and another steam turbine. As such the capital costs would be different between these technologies. For coal, different types of combustion technologies, such as pulverized combustion, fluidized bed combustion, and integrated gasification technology, are possible, and the capital costs of coal-based technologies are different across the technologies. In biomass, the capital costs of technology are vastly different depending on what type of biomass feedstock is used. Technologies burning rice-husk are much cheaper than technologies using municipal solid waste (IRENA, 2018). Costs of reservoir type 23
SUDAN’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

# What else can be done?

Sudan’s funding gap is large relative to the size of its economy, and enormous with respect to its current level of spending. Nevertheless, there are a number of options that could make it more manageable, including raising additional finance, taking additional cost-cutting measures, and lengthening the period of time allotted for meeting the illustrative infrastructure targets. In any case, given the magnitude of the gap, difficult decisions will have to be taken regarding the prioritization of the different investments.

There are realistic prospects for increasing the flow of resources to infrastructure. Although not all components of the required infrastructure platform are suitable for private finance (particularly roads, water, and sanitation), other components may be (for example, ICT, power generation, and ports). Challenges for attracting private investors are conspicuous particularly due to the country risks linked to the instability of the country, repeated violations of the rule of law, and the very poor ranking of Sudan’s governance compared to its peers in Africa.

Sudan has captured private investment commitments worth around 1 percent of its GDP, predominantly in the ICT sector. Many other African countries have done significantly better in this area (figure 33). Countries such as the Democratic Republic of Congo, Liberia, Nigeria, Uganda, Kenya, and Senegal have all captured between 1.8 and 2.5 percent of GDP, while the most successful country in this regard—Guinea-Bissau—has captured in excess of 3.0 percent of GDP.

**Figure 33. Many African countries capture more private investment than Sudan**

<!-- Start of picture text --> 3.5<br>3.0<br>2.5<br>2.0<br>1.5<br>1.0<br>0.5<br>0.0<br>Power ICT Transport Water<br>% GDP<br><!-- End of picture text --> _Source:_ PPI Project Database. (http://ppi.worldbank.org), in current $ millions.

Adopting lower-cost technologies could substantially reduce the cost of meeting the posited infrastructure targets, and help make the funding gap manageable. Meeting the MDGs for water supply and sanitation with lower-cost technologies than previously used (such as stand posts, boreholes, and improved latrines), could reduce the associated price tag from $1,701 million to $889 million each year. Similarly, meeting transport connectivity standards using lower-cost road-surfacing technologies (such as single-surface treatment) together with a rural policy that narrows its focus exclusively to provide 100 percent accessibility currently active (as opposed to potential) agricultural land postponing, could reduce

> <sup>45</sup>
# **ANNEX Figure 3 ‐ SSA Exports to Developing Countries**

<!-- Start of picture text --> Total exports in per capita terms<br>(in current US$)<br>80.00<br>70.00<br>60.00<br>50.00<br>40.00<br>30.00<br>20.00<br>10.00<br>0.00<br>China Gulf countries India Other<br>2000 2007<br>Total exports in % of GDP<br>1.20<br>1.00<br>0.80<br>0.60<br>0.40<br>0.20<br>0.00<br>China Gulf countries India Other<br>2000 2007<br><!-- End of picture text --> Source: Author’s calculations.

30
A second factor frequently spoken of is distance. This is clearly related to the question of migration to and from neighbors discussed above, but even for non-contiguous countries, distance is often felt to matter. Calculating distances as great circle distances between the geographical centres of our 226 countries, as given in the CIA World Fact Book, the main body of Table 11 reports the average distance travelled within each cell of the regional bilateral matrix. The distances for the various bilateral country-to-country links are weighted together by the amount of migration for that link. Of course, the distances are exogenous features of geography, so, for example, the distance from South Asia to North America is inevitably about 12,000 kilometers. Hence, there is not much to be read from the numbers per se. It is true that North-North migrants (in the top left of the matrix) generally have to travel smaller distances than South-South migrants (lower right) or North-South or South-North ones, but with Oceania among the Northern set, the difference is not huge. The mean distance for all migrants in the world is 4,225 kilometers.

27
of sulfur combine with oxygen to form sulfates, and,with water vapor to form aerosols of sulfurous and sulfuric acid. These acid mists can irritate the respiratory systems of humans and animals. Therefore, a high concentration of S02 can affect breathing, and may aggravate existing respiratory and cardiovascular disease. Sensitive populations include asthmatics, individuals with bronchitis or emphysema, children, and the elderly.

The second, and probably more significant, effect of S02 is traceable to the impact of fine particulates on mortality and morbidity. A review of recent evidence by the US Environmental Protection Agency suggests that fine particulates are the source of the worst health damage from air pollution. In the case of China, there is reason to believe that 30-40% of fine particulates are in the form of sulfates from S02 emissions.

While Xu's results and the available data have led us to focus on S02, we also recognize the potential contribution of total suspended particulates (TSP) to atmospheric concentrations of fine particulates (FP). For Beijing and Shenyang, we interpret Xu's weak results for TSP to mean that measured total suspended particulates in those cities do not have a substantial FP component. Nevertheless, we recognize that this may not be true in other cases. Therefore, our policy scenarios include projections for industrial TSP emissions, both for China as a whole and for our five cities.

# 4.4 **Projecting Abatement Costs**

Abatement costs are projected from our econometric analyses of Chinese factory data for several air and water pollutants. The major determinants are pollutant type; industry sector; ownership; scale of abatement activity (related to the volume of discharge); pollutant concentration in the waste stream; and degree of abatement (or percent reduction in pollutant concentration). At the city level, we use our results to project incremental costs for degrees of abatement ranging from 10% to 90%.

Data on fine particulate emissions are not available, so we have used S02 as a proxy because S02 emissions have a significant fine particulate content. However, as Figure 20 shows, S02 reduction is considerably more expensive than abatement of particulates. To avoid severe bias in our benefit/cost assessment, we therefore consider the costs of air pollution abatement for both S02 and particulates. We recognize that our analysis understates the benefits of direct removal of fine particulates, since these represent only a part of total volume for S02. In any case, our results provide an extremely strong benefit/cost rationale for air pollution abatement.

21
Karp, L. and J. Zhang (2005). Regulation of Stock Externalities with Correlated Abatement Costs. _Environmental and Resource Economics_ , 32, 273-299.

Karp, L. and J. Zhang (2012). Taxes versus Quantities for a Stock Pollutant with Endogenous Abatement Costs and Asymmetric Information. _Economic Theory_ , 49, 371-409.

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38
our sample are reported in the Online Appendix. 49.0 percent of subjects are female. As of 2007, subjects had completed an average of 8.5 years of schooling; 69.6 percent had completed primary school, and 14.4 percent had completed secondary school. 23.2 percent of subjects were still enrolled in school at the time that they were surveyed.

# **2.2 Kenya’s Post-Election Crisis**

The 2008 post-election crisis was a period of violence and political instability following the Kenyan presidential election of December 27, 2007. The two leading candidates in the election were Raila Odinga (the son of Kenya’s first vice president), and the incumbent president, Mwai Kibaki (himself a former vice president). For several months preceding the election, opinion polls placed the opposition candidate, Odinga, ahead of Kibaki (World Bank 2008, Munene and Otieno 2007). As election day neared, the polling gap between Odinga and Kibaki narrowed to what, in some polls, appeared to be a statistical dead heat (World Bank 2008, Agina 2007, Otieno 2007, Standard Team 2007). At the time of the elections, both international observers and members of the opposition made allegations of electoral irregularities; however, after a few days, Kibaki was declared the winner and sworn into office (World Bank 2008, Waki 2008, McCrummen 2007, BBC News 2007). Opposition supporters organized protests; rioting and violent clashes with police ensued, and the violence soon escalated and took on a strong ethnic dimension (World Bank 2008, World Bank 2010b, Van Praag 2010, Waki 2008, BBC News 2007). By the time Kibaki and Odinga signed a power-sharing agreement at the end of February, 2008, more than one thousand people had been killed, and hundreds of thousands had been internally displaced (World Bank 2008, World Bank 2009, World Bank 2010a, World Bank 2012, BBC 2008a, BBC 2008b).

As discussed above, all KLPS2 respondents were residing in Busia District, in Kenya’s Western Province near the Ugandan border, in 1998; 73 percent were still living in Busia District at the time of the KLPS2 survey, and many others happened to be there during the post-election crisis (because they had returned to their family homes to celebrate the Christmas holiday or to vote). As a result, most were spared the worst of the post-election violence: though protests, riots, and assaults took place throughout Kenya, the most affected areas were Rift Valley Province and the more urban districts across the country. According to the official report of the Commission of Inquiry on Post 7
# **Appendix 1: Timeline**

# _Applications_

February 9, 2016: BIG Platform launched to start receiving applications December, 2016: BIG Platform registrations close for the first year

# _Induction workshops_

Lagos workshops held in March, May, August and December 2016 Abuja workshops held in May, August, and November 2016 One firm located in Abuja also attended the Enugu induction workshop in November 2016

# _Interventions_

Training workshops: April/May 2017 to June/July 2017 for most firms.

Consulting: Phase 1 (Needs assessment and growth plan) – January-April 2017 for most firms Phase 2 (80 hours assistance) – May 2017-February 2018 Insourcing and Outsourcing: Grant signing events – March 13 and 24, 2017 Subsidies received – March/April 2017 to December/March 2018 for most firms

# _Surveys_

First follow-up: March-June 2018 - corresponds to approximately one year after interventions started Second follow-up: February-June 2019 (86% in February/March) - corresponds to approximately two years after interventions started, and over one year after interventions ended Business Service Provider survey – 333 providers interviewed November 2017-June 2018 _GEM Project closing:_ March 29, 2019.

_Social media quality measured:_ October 2019.

||2017|201|8||2|019||
|---|---|---|---|---|---|---|---|
|2016 J|F<br>M A M J<br>J<br>A S<br>O N D J|F<br>M A M J<br>J|A S|O N D J|F<br>M A M J|J<br>A S|O N D|
|Applications||||||||
|Induction workshops||||||||
|_Interventions_||||||||
|Training workshops||||||||
|Consulting||||||||
|Insourcing||||||||
|Outsourcing||||||||
|_Follow-up Data Collection_||||||||
|Follow-up 1||||||||
|Follow-up 2||||||||
|Service Provider Survey||||||||
|Social Media||||||||

46
# _Outcome-Based Governance Indicators_

The right-hand panel of Table 1 lists a selection of indicators that measure governance outcomes. As we noted, the majority of existing governance indicators fall in this category. Moreover, several of the sources of rules-based indicators of governance also provide outcome-based measures. The Global Integrity Index is a clear example in this respect, as it pairs up indicators of the existence of various rules and procedures with indicators of their effectiveness in practice. It is not the only one, however. The Database of Political Institutions for example not only measures such constitutional rules as the presence of a parliamentary system, but also outcomes of the electoral process such as the extent to which one party controls different branches of government, or the fraction of votes received by the president. Similarly, the Polity-IV database records a number of outcomes, including for example the effective constraints on the power of the executive.

The remaining outcome indicators range from the highly specific to the quite general. The Open Budget Index is an example of the former, reporting data on over 100 different indicators of the budget process across countries, ranging from whether budget documentation contains details of assumptions underlying macroeconomic forecasts, to the documentation of budget outcomes relative to budget plans. Other somewhat less specific sources include the Public Expenditure and Financial Accountability Indicators constructed by aid donors with inputs of recipient countries, and several large cross-country surveys of firms including the Investment Climate Assessments of the World Bank, the Executive Opinion Survey of the World Economic Forum, and the World Competitiveness Yearbook of the Institute for Management Development, which ask firms fairly detailed questions about their various interactions with the state.

Examples of more general assessments of broad areas of governance include ratings provided by several commercial sources including Political Risk Services (PRS), the Economist Intelligence Unit, and Global Insight-DRI. PRS for example provides ratings in 10 areas that can be identified with governance, such as "democratic 12
Policy Research Working Paper 6626

# **Abstract**

Regression discontinuity designs applied to a set of household surveys from the 1980–90s allow to examine whether Côte d’Ivoire’s aggregate wealth was translated at the borders of neighboring countries. At the border of Ghana and at the end of the 1980s, large discontinuities are detected for consumption, child stunting, and access to electricity and safe water. Border discontinuities in consumption can be explained by differences in cash crop policies (cocoa and coffee). When these policies converged in the 1990s, the only differences that persisted were those in rural facilities. In the North, cash crop (cotton) income again made a difference for consumption and nutrition (the case of Mali). On the one hand, large differences in welfare can hold at the borders dividing African countries despite their assumed porosity. On the other hand, border discontinuities seem to reflect the impact of reversible public policies rather than intangible institutional traits.

This paper is a product of the Partnerships, Capacity Building Unit, Development Economics Vice Presidency. 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 denis.cogneau@psemail.eu.

_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