rafmacalaba/datause-encoder-data huggingface dataset:
# Growth

Calderón, César. 2009. “Infrastructure and Growth in Africa.” Policy Research Working Paper 4914, World Bank, Washington, DC.

- Escribano, Alvaro, J. Luis Guasch, and Jorge Pena. 2010. “Assessing the Impact of Infrastructure Quality on Firm Productivity in Africa.” Policy Research Working Paper 5191, World Bank, Washington, DC.

- Yepes, Tito, Justin Pierce, and Vivien Foster. 2009. “Making Sense of Africa’s Infrastructure Endowment: A Benchmarking Approach.” Policy Research Working Paper 4912, World Bank, Washington, DC.

# Information and communication technologies

Ampah, Mavis, Daniel Camos, Cecilia Briceño-Garmendia, Michael Minges, Maria Shkaratan, and Mark Williams. 2009. “Information and Communications Technology in Sub-Saharan Africa: A Sector Review.” AICD Background Paper 10, Africa Region, World Bank, Washington, DC.

- Gillwald, Alison, and Christoph Stork. 2008. “Towards Evidence-based ICT Policy and Regulation: ICT Access and Usage in Africa.” www.researchictafrica.net/index.php/ria-publications.

GSMA (GSM Association). 2009. _Taxation and the Growth of Mobile in East Africa_ ., London

- ITU (International Telecommunication Union). 2001. _The Internet in an African LDC: Uganda Case Study_ , International Telecommunications Union, Geneva

Mayer, Rebecca, Ken Figueredo, Mike Jensen, Tim Kelly, Richard Green, and Alvaro Federico Barra. 2009. “Connecting the Continent: Costing the Needs for Spending on ICT Infrastructure in Africa.” AICD Background Paper 3, Africa Region, World Bank, Washington, DC.

UBOS (Uganda Bureau of Statistics). 2006. _Uganda National Household Survey 2005/2006_ . Kampala

- UCC (Uganda Communications Commission). 2007. _Review of Sector Taxation Policies and Determining the Elasticity of Penetration and Price of the Various Telecommunication Services in Uganda._ Kampala— ——. 2009a. _Status of the Communications Market—December 2008_ . Kampala

- ———. 2009b. _A Review of the Post and Telecommunications Market 2008/09_ . Kampala

- ———. 2010. _Status of the Communications Market—December 2009_ . Kampala

- World Bank. 2009a. _Information and Communications for Development 2009: Extending Reach and Increasing Impact_ . Washington, DC: World Bank.

# Irrigation

- Heidecke, Claudia. 2006. Development and Evaluation of a Regional Water Poverty Index for Benin. IFPRI Discussion Paper 145, International Food Policy Research Institute. Washington DC

- Svendsen, Mark, Mandy Ewing, and Siwa Msangi. 2008. “Watermarks: Indicators of Irrigation Sector Performance in Africa.” AICD Background Paper 4, Africa Region, World Bank, Washington, DC.

52
firm. The survey and test instruments were designed by the World Bank’s research team in partnership with the government and country level psychometricians and research consultants. Our endline data collection took place two years after the completion of the first (main) phase of the intervention, enabling us to observe medium-term impacts on test scores.

Our study makes two distinct contributions. This study is the only the second of which we are aware to generate rigorous experimental evidence in a low-income setting on the impact of interventions to improve school leadership on learning and progression. If the interventions can positively influence student progression and test scores in Malawi, it will have important policy implications for governments in low-income countries. Second, we evaluate a government program at national scale, with leaders from 1,198 schools (more than one-fifth of all public primary schools) from all districts in Malawi participating, in contrast to pilot interventions generally evaluated at a small scale and in particular districts or regions<sup>3</sup> . This implies the results of the study are relevant to all public primary schools in Malawi and the evaluated approach, if successful, is likely to have similar impact on student achievement if scaled up.

# 2 Design

## 2.1 Research Question and General Hypothesis

Our research question is: Can student progression and students’ test scores improve as a result of a custom-designed multi-phase school leadership training program?

Our general hypothesis is: The intervention is expected to improve utilization of resources and the behavior of teachers, and create school cultures which meet the needs of over-age students, students with special needs, low-performing students, and girls; and as a result improve student progression and test scores (compared to control).

## 2.2 Theoretical Framework

Poor outcomes in education in low-income countries reflect systemic resource limitations, poor utilization of resources, and weaknesses in education production (Hanushek, 1987; Delprato and Antequera, 2021). We employ the term _education production function_ (Bowles, 1970;

> 3 For example, the previous experimental study which reports learning impacts, Blimpo et al. (2015), employs a total of 273 schools across all treatment and control groups.

3
d) Non-routine manual tasks Argentina Uruguay <!-- Start of picture text --> 0.5 0.5<br>0.2 0.2<br>-0.1 -0.1<br>1998 2003 2015 1995 2003 2015<br>-0.4<br>-0.4<br>-0.7<br>-0.7<br>after 81 80-76 75-71<br>after 81 80-76 75-71<br>70-66 65-61 60-56<br>55-51 70-66 65-61 60-56<br><!-- End of picture text --> Conversely, in observing the variation in the relative importance of routine manual tasks in employment this suggests that although this shows a stable trend for all cohorts greater than 1971, the incline becomes negative for younger cohorts. Something similar, though of a lesser magnitude, is observed in the intensity of non-routine manual tasks.

In both cases, during the period under study a greater decline can be seen in the youngest cohorts, which suggests that on one hand, the young are directing their entrance into the labor market towards occupations which are less intensive in terms of non-routine manual tasks, and on the other hand, that as this group of workers has a greater capacity for adaptation they replace occupations intensive in these types of tasks with those more cognitively intense.

With respect to the relative importance of routine cognitive tasks, again the youngest cohort is that which defines the trend of the change, while the older generations remain relatively constant in the tasks which they perform in their occupations.

e) Routine cognitive tasks Argentina Uruguay

- 23 -
is based on data that is nationally representative and caveat the data appropriately. For EGRA, only a sub-set of countries have nationally representation data. Of 72 countryyear observations, 42 are nationally representative. We produce the linking function based on countries that took part in nationally representative tests to guarantee population overlap. We apply the linking function to all countries with nationally representative EGRA results producing internationally comparable results. We also apply this linking function to non-national EGRA assessments. While we have confidence in the former estimates, we caveat the latter estimates. We exclude TIMSS results for Yemen which TIMSS highlighted as having a flooring effect and has an unrealistically low score. Our HLO Yemen score is thus derived from EGRA data. For Sri Lanka, we use a score derived from the National Assessment which was linked to TIMSS (Dundar et al., 2017). In the case of China and India we validate or extrapolate nationally representative data, described in Annex 3 and 4.

Second, tests should measure similar proficiencies. We link across precise subjects (math, reading and science) to ensure proficiency overlap. For EGRA, since it often has multiple languages of instruction, we only include scores for tests where the language of instruction is the same as the language of the test. This ensures we capture underlying cognitive skills rather than language effects.

Third, test differences should capture difficulty differences rather than country-fixed effects. We address this assumption in a few ways. As noted above, we link tests across doubloon countries that participate in tests that are nationally representative. The reliability of this linking exercise increases the larger the set Y ∩ X, the number of countries that take both tests being linked. Each update increases this overlap, making the inclusion of new countries in this update significant.

A novel contribution of this update which increases the reliability of this last assumption is the fixing of our conversion rate across a 15-20-year interval for recent years from 20002017. This enables us to increase the sample size in the set Y ∩ X for each doubloon index. For example, if Botswana participates in SACMEQ I and II as well as TIMSS 2003 and TIMSS 2007, we now have four data points instead of two, and two rounds of conversion factors instead of one between SACMEQ and TIMSS. In fixing the conversion factor, we assume that the relationship between tests stays constant across rounds. This assumption is reasonable and is true by design for RSATs and ISATs since the mid 1990s. This is not the case prior to the 1990s, limiting our ability to apply a fixed conversion factor to earlier data. The fixing of conversion factors increases the likelihood that we capture test-specific rather than country-specific differences. It further guarantees that any changes in test scores over this interval are due to realized progress rather than changing conversion factors.

13
and find that growth in sectors that rely more intensively on unskilled labor have the greatest contribution to reducing poverty rates. The empirical results show that agriculture is the most effective poverty-reducing sector, followed by construction and manufacturing. Mining, utilities, and services do not have a statistically significant impact on poverty alleviation. These results highlight that in some countries, growth might be insufficient to reduce poverty if it is concentrated in sectors that are not intensive in unskilled labor, such as oil and mining.

Studies conducted for individual countries support the results of Loayza and Raddatz (2010). Ravallion and Datt (1996) find that for India in the second half of the 20<sup>th</sup> century, growth in agriculture and services was correlated with declines in poverty in both rural and urban areas, while industrial growth did not have a systematic impact on poverty. Ravallion and Chen (2007) find that agriculture growth was the most important driver for poverty alleviation in China. For Indonesia, Suryahadi, Suryadarma, and Sumarto (2009) find that growth in the service sector was strongly correlated with poverty reduction in rural and urban areas, while agriculture growth was correlated with poverty declines in rural areas. Ivanic and Martin (2018) find that in poor countries, productivity gains in agriculture are generally—although not always—more effective in reducing global poverty than the productivity gains in industry or services of equivalent size. However, the effectiveness of the former fades as average income rises.

# **_Capital intensity_**

If growth is generated in sectors that are intensive in capital or innovative skill, such growth could provide higher returns to capital and entrepreneurs than to labor. Indeed, in recent years, the labor share of output across advanced and emerging market economies has fallen as a result of capital deepening and technological progress (Dao, Das, and Koczan 2019). Moreover, Piketty (2015) finds that the return on capital is higher than the growth rate of GDP in many country episodes, leading to higher inequality, as capital owners tend to be at the top of the income distribution. Using historical data from the United States and Europe, Piketty provides evidence that the difference between the return to capital (r) and the growth rate of GDP (g) has the effect of amplifying wealth inequality over time. Since wealth is highly concentrated at the top of the income distribution, the high return to capital relative to GDP growth increases the ratio of wealth to GDP, increasing the extent of inequality.

However, even if the driving sector is capital-intensive, it could have positive spillovers to the poor, provided it simulates enough growth in more labor-intensive sectors. Conversely, under some circumstances, strong productivity growth in labor-intensive agriculture could reduce demand for rural labor, thereby increasing poverty and the number of urban unemployed.

19
low. For the latter, new forms of skill measurement are currently being pioneered, including with the PIAC study of the OECD and the STEP skill measurement study at the World Bank.<sup>2</sup> This paper is structured as follows. The next section recaps the main features of the methodology, including a description of the mechanism employed to map the occupational structure of economies into measures of skill intensity. The third section provides information on the household surveys being used in our analyses while the fourth section presents results, both for the cross-country comparison of different ‘stocks’ of skills as well for several countries for which we are able to track skill developments over time. The final section concludes.

# **2. Methodology**

We build here on the pioneering work of Autor et al (2003) followed by Acemoglu and Autor (2010), which provides an objective measure of the evolution of the skill content embedded in the employed US labor force. Measuring the human capital stock of nations through such assessment is a significant innovation compared to cruder measures such as the average years of schooling of a population.<sup>3</sup> The analysis relies on information on the skill content per occupation which is generated based on the Occupational Information Network (O*NET), a database constructed with support from the US Department of Labor/Employment and Training Administration. The O*NET characterizes different occupations in the US economy in terms of two types of factors. The first is _worker-oriented_ factors, which include worker characteristics, worker requirements, and experience requirements. The second is _joboriented_ factors, which are comprised of occupational requirements, workforce characteristics and occupation-specific information. O*NET hence records various requirements for each individual occupation, derived from evaluations by peers and measured on a scale of 1 to 5.<sup>4</sup>

> 2 The Skills Toward Employment and Productivity (STEP) Skills Measurement Study is an initiative of the World Bank to help countries measure levels and distributions of cognitive, technical and non-cognitive skills among adults; quantify the mismatch between the skills of the adult population and employers’ needs; and assess how skills of individuals affect labor market outcomes. STEP skill measurement instruments collect information from participant countries through harmonized individual and employer surveys and by using comparable implementation protocols and technical standards. 3 In addition to Autor, Levy and Murnane (2003) and Acemoglu and Autor (2010), see Handel (2007) for an application and discussion of the embedded-skill measurement method..

> 4 Occupations in this scheme are then collapsed into the Standard Occupational Classification (SOC) used by the Census Bureau resulting in information for 974 different SOC occupations.

**4**
mal and informal sectors, sheds light on previous studies, which consistently found that premiums for the formal sector were greater for prices than for rents. We show that the difference between the two premiums precisely reflects the risk faced by investors.

Consistent with previous studies, we find the difference in rents between the formal and informal sectors to be important. Once observed characteristics of the dwellings and of the neighborhood are controlled for, there is still a 35 percent gap between the two sectors. This figure is comparable, although larger, than those found by Jimenez (1984) and Friedman, Jimenez and Mayo (1988) for the Philippines. This difference may be explained only by unobservable characteristics of the dwellings, as well as by the different ways in which housing characteristics interact in the formal and informal sectors. However, since the variables we use in our hedonic regressions are similar to those used in previous papers, one can suppose that this high premium reflects idiosyncratic conditions of the rental market in the informal sector in Pune. Exploiting datasets from other cities in India could give us indications whether this high premium is particular to Pune city, or if it reflects conditions prevailing in the rental markets throughout India. Further empirical studies are needed to better understand what drives those differences across countries or regions.

We believe that our very simple investment model can be extended in many fruitful ways. An obvious extension consists in going beyond our literary discussion in section 4 to consider endogenous land prices. Other insights could be obtained by introducing heterogeneity in the degree of uncertainty on informal investment (that is more categories of informal land), or in the opportunity cost of capital (to reflect the difference between private households with no or limited access to alternative portfolio choices and firms with potentially high returns on financial investments). Consider the latter case. If one finds that firms (supposed to have higher opportunity cost of capital) only invest in the formal sector, this would mean that returns in the informal sector are not high enough to compensate for the higher risk on investment there. Methods similar to ours would thus underestimate the eviction risk.

27
Policy Research Working Paper 8389

# **Abstract**

Using surveys and administrative data from post-war Liberia, the hypothesis that peacekeeping deployments build peace “from the bottom up’’ through contributions to local security and local economic and social vitality was tested. The hypothesis reflects official thinking about how peacekeeping works via “peacebuilding.’’ A quasi-experiment was created by applying coarsened exact matching to administrative data used in mission planning, identifying sets of communities that were similarly likely to receive peacekeeping bases. The analysis finds nothing to support claims that deployments increase local security and finds only modest effects on economic or social vitality. Nongovernmental organizations tend to work in areas where deployments are not present, contrary to the hypothesis. Thus, it is less likely that peacekeepers build peace from the bottom up, leaving mechanisms such as signaling and deterrence at the level of leaders as worthy of more attention. For policy, peacekeeping missions should reevaluate their methods for providing local security.

This paper is a product of the Impact Evaluation Team, Development Research 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 emvukiyehe@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
decision-making power to subnational governments and their legal ability to raise revenues from different instruments in a country (Vincent, 2020).

With these combined datasets, we estimated how individuals living within a 50 km radius from an active or an inactive mine assess government performance in several public policy areas, including improving living standards, job creation, health and education services, as well as a composite indicator of public services as a whole. We also investigated how the geographical closeness to a mine affects the individual expectation of their living standards in the future (referred to as optimism).

The results from the baseline suggested that residents living within a 50 km radius to an active mine are less likely to approve government performance in improving living standards, jobs creation, health services, and public services delivery. In addition, they are also less likely to be optimistic about their future living standards. While the results are more mitigated for the distance to an inactive mine, they point to the dissatisfaction of nearby with the government handling water and sanitation and a decrease in optimism about the future.

In comparison to non-active mine, active mining statistically reduces the probability of approving government performance in the afore-mentioned policy areas and public services as a whole. In addition, the ‘ _active_ ’ status of a nearby mine also decreases the optimism of the respondents in the Afrobarometer surveys.

We then moved onto exploring the effects of local governance. The results confirm our hypothesis on the confoundedness of the quality of local institutions. We found that effective corruption, measured by the incidence of bribe payment at the local level and the sentiment of distrust in local government councillors, amplifies the negative effects of the geographical closeness to an active mine. The higher the incidence of bribe payment or level of distrust in local governments in a community located within a 50km radius from an active mine, the higher the likelihood of citizens being dissatisfied with government performance. Both variables also render the respondents even more pessimistic about the future.

Finally, we examined the interplay between decentralization and effective corruption in how they jointly influence the local effects of mining. The results indicate that a higher level of decentralization could, to some extent, alleviate the adverse local effects of natural resources on socio-economic outcomes. However, these positive marginal effects considerably diminish in the presence of corruption. Exploring the interplay of Decentralization and local government, we found that, regardless of the level of decentralization (high or low), a high incidence of bribe payment leads to the worse impact of natural resources on individual perception of government performance. On the other hand, when corruption is low, a higher level of decentralization is preferable.

30