rafmacalaba/datause-encoder-data huggingface dataset:
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- Canning, D. and Pedroni, P. (2004) “The Effect of Infrastructure on Long Run Economic Growth”, unpublished manuscript.

- Canning, D., 1999. "The Contribution of Infrastructure to Aggregate Output." The World Bank Policy Research Working Paper 2246.

- Collier, P. (2006): “African Growth: why a ‘Big Push’“ _Journal of African Economies_ Supplement 2, 188-211.

- Deininger, Klaus and Lyn Squire. 1996. "A New Data Set Measuring Income Inequality". _The World Bank Economic Review_ 10(3):565-591

- Demetriades, P. and Mamuneas, T., 2000. "Intertemporal Output and Employment Effects of Public Infrastructure Capital: Evidence from 12 OECD Economies." _The Economic Journal 110_ , 687–712.

- Desmarchelier, A. (2005): “Recent economic developments in Africa’s infrastructure sectors: the transport sector”, unpublished manuscript.

- Devarajan, S., W. Easterly and H. Pack (2003): “Low investment is not the constraint on African development”, _Economic Development and Cultural Change_ 51, 547-571.

- Diallo , A. and Q. Wodon (2004): “Access to Network-Based Infrastructure Services in Africa: Benefit and Marginal Benefit Incidence Analysis” The World Bank, Mimeo.

- Diao, X., and Y. Yanoma (2003): “Exploring regional dynamics in Sub-Saharan African agriculture”, IFPRI DSGD Discussion Paper 2.

- Durlauf, Steven N., Paul A. Johnson, and Jonathan R.W. Temple. 2005. “Growth Econometrics.” In: Aghion, Philippe, and Steven Durlauf (eds.) _Handbook of Economic Growth_ , Volume 1, Elsevier.

- Dynkelman, T. (2008): “Effects of rural electrification on employment: new evidence from South Africa”, unpublished manuscript.

- Easterly, W., 2001. “The Lost Decades: Explaining Developing Countries’ Stagnation in spite of Reform 1980-98.” _Journal of Economic Growth 6(2)_ , 135-157.

- Easterly, W., Servén, L., 2003. _The Limits of Stabilization: Infrastructure, Public Deficits, and Growth in Latin America_ . Stanford University Press.

- Elbadawi, I., T. Mengistae and A. Zeufack (2006): “Market access, supplier access and Africa’s manufactured exports”, World Bank Policy Research Working Paper 3942.

- Escobal, Javier, and Carmen Ponce (2000) “The benefits of rural roads: Enhancing income opportunities for the rural poor.” Group of Analysis for Development (GRADE) Working paper No. 40, November

- Esfahani, H. and Ramirez, M. (2003) “Institutions, Infrastructure and Economic Growth”. _Journal of Development Economics_ 70(2): _443-477_

- Estache, A. (2005): “What do we know about Sub-Saharan Africa’s infrastructure and the impact of its 1990s reforms”, unpublished manuscript.

- Estache, A. (2006): “Infrastructure: a survey of recent and upcoming issues”, unpublished manuscript.

32
# **1. Introduction**

Access to basic services and goods in Côte d’Ivoire is limited for children and the overall population. This report presents the findings of an effort to measure and analyze the equality of opportunities for children in Côte d’Ivoire, where ―opportunities‖ are defined in terms of access to basic goods and services in education and critical infrastructure facilities, such as clean water and sanitation. The use of the equality of opportunities framework involves looking beyond measures of _average_ access to basic goods and services. Rather, the measure that underpins the analysis, the Human Opportunity Index (HOI), also takes into account the extent to which _existing_ opportunities in the country are equitably distributed across children of different characteristics, such as gender, economic status, location, and family or parental attributes, which are all circumstances established at birth.

There are a number of compelling reasons why an in-depth country report for Côte d’Ivoire on the equality of opportunities is of interest to the Bank, country policy makers, and other stakeholders in Côte d’Ivoire’s development process. The most important among these reasons is that human development remains a challenge, because the country is still recovering from a series of civil conflicts and political instability. (See Box 1.) The numbers from recent household surveys report that almost half of the children from age 6 to15 years of age do not attend school. Moreover, around one-third of Ivoirian youth younger than age 16 lack access to basic goods, such as sanitation facilities and electric light in the home. Evidence presented in this report also shows that access is unevenly distributed across groups. Because access to basic goods and services represent the minimum level of opportunities a child would need to maximize his or her human and productive potential in life, the low and unequally distributed access severely jeopardizes opportunities for these children.

The following section of this report introduces the underlying concept, properties, and empirical methods for estimating the Human Opportunity Index. Section 3 presents the data and analytical choices made. Section 4 presents the main results related to opportunities, and section 5 presents the results from a fiscal policy analysis to better understand the financial implications of improving of opportunities (in particular, access to education), using an equality of opportunity–based approach.

2
approximately 0.3 SD, and in science, by almost 0.4 SD. For the 12<sup>th</sup> grade, the gap is the smallest, around 0.2 SD, and is not statistically different from zero.

# **Figure 1. The actual and expected achievement of secondary school students in Warsaw**

<!-- Start of picture text --> 10th grade 11th grade 12th grade<br>math actual math actual math actual<br>math expected math expected math expected<br>science actual science actual science actual<br>science expected science expected science expected<br>reading actual reading actual reading actual<br>reading expected reading expected reading expected<br>460 480 500 520 540 560 500 520 540 560 580 520 540 560 580<br><!-- End of picture text --> Source: Jakubowski et al., 2022.

We separate the effects of the pandemic and the structural reform by comparing achievement changes in the cohorts affected by both events (10<sup>th</sup> and 11<sup>th</sup> grade) to changes in the 12<sup>th</sup> grade affected by the pandemic only. We regress the PISA 2003-2018 scores on the results from 2021, adjusted for the expected minimum achievement gain over one year of education. The regression equation is given by: P 0 1 1011 2 101112 3G G G 4S PPAA YY = ββ + ββ YY + ββ YY + ββ + ββ SS The structural reform effect is captured by 2, which measures the difference between students who followed the new and the old school structure. The estimate of the learning loss is given by ββ 1. We also control for student gender and socioeconomic status to minimize individual variance ββ 4
# **4 Data and estimation method**

In this section, we define key dependent and independent variables. Other variables will be defined in the results section, as needed.

## **4.1 FDI data**

For model (1), our proxy for _FDIijst_ is the sector-specific bilateral cumulated value of the capital investments made by firms to establish a new production or processing manufacturing facility in a foreign country. This variable should capture a large fraction of the initial fixed costs incurred by MNEs to produce abroad when establishing a foreign affiliate _ex nihilo_ .<sup>29</sup> For model (2), in addition to the bilateral volume of greenfield FDI, we use as the dependent variable the bilateral number of greenfield FDI projects or the average size of the bilateral greenfield projects conditional on positive FDI. They represent measures of the extensive and intensive margins of FDI respectively.

Our FDI data come from the _fDi Markets_ database compiled by fDi Intelligence, a division of the Financial Times.<sup>30</sup> This database is the most comprehensive source of firm-level information on cross-border greenfield investment available, covering all countries and sectors worldwide since 2003. Data include the name of the country in which the firm engaging in greenfield FDI is headquartered, the name of the destination country, the year of investment, the recipient sector, the function (nature) of the FDI project, the type of project (new, expansion, co-location), and the capital investment (capital expenditures) associated with the project.<sup>31</sup> There is no minimum investment size for a project to be included but the equity stake of the foreign investor cannot be lower than 10%. Data are collated through daily searches of Financial Times newswires and internal information sources, other media sources, project data received from industry organizations and investment agencies,

> 29As previously indicated, other fixed costs to produce and sell the goods may be incurred before or after this cross-border investment. While our dependent variable does not include these costs in principle, they play a role in firms’ ability to self-finance their capital expenditures abroad.

> 30http://www.fdimarkets.com/

> 31Data on capital investment are based on the investment the company is making at the time of the project announcement or opening. The data include estimates for capital investment (derived from algorithms) when a company does not release the information. These estimates may introduce measurement error in our main dependent variable, the sector-specific bilateral value of FDI, generating larger variances in our estimators.

13
15

# _Table 2: Dependent variables_

|VARIABLE|1991|1993|1997|2000||Ally|ears||Description|
|---|---|---|---|---|---|---|---|---|---|
||Mean|Mean|Mean|Mean|Mean|sd|Min.|Max.||
|PCINC|1,154.30|1,353.86|1,432.97|1,880.03|1,457.23|1,889.63|0.00|69,259.55|Total household income from all sources divided by number<br>|
|_natural log_|6.54|6.53|6.62|6.74|6.61|1.67|0.00|11.15|of household members (1989 prices)|
|_Δ natural log_|-|-0.01|0.01|0.03|0.01|0.72|-4.36|4.77||
|EARN_PCINC|1,034.17|1,166.00|1,212.45|1,553.79|1,249.88|1,840.37|0.00|68,413.88|Total income from salaries, business income, agriculture,<br>|
|_natural log_|6.31|6.16|6.01|6.07|6.13|2.18|0.00|11.13|fishing, and handicrafts, asset rentals, and other minor items,<br>|
|_Δ natural log_|-|-0.10|-0.07|-0.01|-0.05|0.84|-4.30|4.54|divided by number of householdm embers (1989 prices)|
|UNEARN_PCINC|157.18|187.86|220.53|326.24|225.81|575.75|0.00|10,120.39|Total income from pensions, welfare payments, transfers|
|_natural log_|2.30|2.39|2.64|2.57|2.49|2.79|0.00|9.22|from friends and family, gifts from the workplace, and other<br>1989 i|
|_Δ natural log_|-|0.04|0.08|0.02|0.05|1.08|-3.95|3.97|sources ( prces)|
|TOTHRS_HD|38.05|31.27|28.51|24.20|30.40|24.70|0.00|138.00|Average number of hours worked by head of household per<br>|
|_natural log_|3.16|2.78|2.68|2.35|2.74|1.56|0.00|4.93|week during last year, including primary and secondary<br>lt d h dti|
|_Δ natural log_|-|-0.36|-0.24|-0.41|-0.34|1.66|-6.40|6.56|empoymen an ome proucon|
|TOTHRS_PARTIC|62.87|50.98|45.68|38.55|49.32|48.93|0.00|476.00|Dummy variable for whether the head of household is<br>working (TOTHRS_HD > 0)|
|TOTHRS_NONHD|3.59|3.22|3.06|2.67|3.13|1.65|0.00|6.17|Total hours worked by non-head household members per<br>|
|_natural log_|-|-0.38|-0.25|-0.41|-0.35|1.73|-6.73|6.07|week on average during the last year|
|_Δ natural log_|0.87|0.80|0.79|0.72|0.79|0.41|0.00|1.00||
|OOP|5.65|5.59|9.53|7.40|7.12|85.65|0.00|2,774.77|Total health care expenditures during last month, net of any<br>|
|_natural log_|0.19|0.11|0.18|0.19|0.17|0.82|0.00|7.93|reimbursement from health insurance (1989 prices)|
|_Δ natural log_|-|-0.04|0.01|0.01|-0.01|0.38|-3.76|3.71||

_n = 2,719 (1991), 2,715 (1993), 3,089 (1997), 2,798 (2000) Note: 365 observations dropped for earned and unearned income_
Policy Research Working Paper 8120

# **Abstract**

Deliberative institutions have gained popularity in the developing world as a means by which to make governance more inclusive and responsive to local needs. However, a growing body of evidence suggests that persistent gender inequality may limit women’s ability to participate actively and influence outcomes in these forums. In response, policy makers have tried to induce women’s participation by leveraging the group-based format of self-help groups, which can build women’s social capital and develop their sense of political efficacy and identity. This paper evaluates the impact of one such intervention, known as the Pudhu Vaazhvu Project, on women’s civic participation in rural Tamil Nadu. Using _text-as-data_ methods on a matched sample of transcripts from village assembly meetings, the analysis finds that the Pudhu Vaazhvu Project significantly increases women’s participation in the _gram sabha_ along several dimensions —meeting attendance, propensity to speak, and the length of floor time they enjoy. Although women in the Pudhu Vaazhvu Project villages enjoy greater voice, the study finds no evidence that they are more likely than women in control villages to drive the broader conversational agenda or elicit a relevant response from government officials.

This paper is a product of the Poverty and Inequality 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 vrao@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 --> 2014 2017<br>medicines_chid] mother_education 7=<br>mother_education |]is mother_age |=<br>staff_imci] wealth | i’<br>wealth | division |]7’<br>division] staff_imci7 i’<br>mediaAcess 7 staff_growthmonitoring 7 ii<br>mother_age | medicines_child | i<br>staff_growthmonitoring | equipment_basic 7 Hi<br>curativecare_child | I amenities_basic 7 Hl<br>equipment_basic 7 Hill visitedByGovHealthWorker 7 Hil<br>0 5 10 15 0 5 10 15 20<br>Relative importance Relative importance<br><!-- End of picture text -->
# 6. References

Acemoglu, D. and D. Autor, 2011. “Skills, Task and Technologies: Implications for Employment and Earning”. Handbook of Labor Economics. Elsevier, pp: 1043-1171 Apella, I. and G. Zunino, 2017. “Technological Change and The Labor Market in Argentina and Uruguay. A Task Content Analysis”. Policy Research Working Paper 8215, World Bank, Washington D.C.

Apella, I. 2016. “Employment-GDP Elasticity in Argentina During 2004-2014”. International Journal of Social Science Studies 4(3): 74-84 Brews, P and C. Tucci, 2004. “Exploring the structural effects of internetworking”, Strategic Management Journal 25(5): 429–451.

Hardy, W., R. Keister and P. Lewandowski, 2015. “Do Entrants Take It All? The Evolution of Task Content of Job in Poland”. IBS Working Paper 10, Poland.

International Labour Organization, 2016. Non-standard employment around the world: understanding challenges, shaping prospects. International Labour Office, Geneva.

International Labour Organization, 2015. Non-standard forms of employment. Report for discussion at the Meeting of Experts on Non-Standard Forms of Employment. International Labour Office, Geneva. February, 2015.

Kalleberg, A. L., 2009. “Precarious Work, Insecure Workers – Employment Relations in Transition”, American Sociological Review, 74 (1): 1-22.

Keister, R. and P. Lewandowski, 2016. “A Routine Transition? Causes and Consequences of the Changing Content of Jobs in Central and Eastern Europe”. _IBS Policy Paper 5/2016, Poland._ Kirkpatrick, I. and K. Hoque, 2006. “A Retreat from Personal Employment? Accounting for the Rise of Professional Agency Work in the UK Public Services”, Work, Employment and Society 20(4): 649-666 Kunda, G., S. Barley and J. Evans, 2002. “Why do Contractors Contracts? The Experience of Highly Skilled Technical Professionals in a Contingent Labor Market”, Industrial and Labor Relations Review 55(2): 234-61.

Maurizio, R., 2015. “Non-standard forms of employment in Latin America: Prevalence, characteristics, and impacts on wages”, Conditions of Work and Employment Series 75, International Labour Organization.

Nesheim, T., et al., 2007. “Externalizing the core: Firms’ use of employment intermediaries in the information and communication technology industries”, in Human Resource Management 46(2): 247–264 von Hippel, C. et al., 1997. “Temporary employment: Can organizations and employees both win?”, Academy of Management Executive 11(1): 93–104.

Schmid, G. 2010. “Non-Standard Employment and Labour Force Participation: A Comparative View of the Recent Development in Europe” IZA Discussion Paper 5087.

Page 43 of 51
medium/large freight forwarders and 30% for small freight forwarders. Therefore, the size of the shipments is similar regardless of the size of the freight forwarder but the frequency of trading is higher for medium/large freight forwarders which also have a more diversified portfolio of clients.

**Table 3. Import Shipment Numbers and Values, and Diversification across Clients** **<u>Panel A. Import Shipment Numbers and Values</u>**

||Number of<br>freight<br>forwarders|Average<br>number of<br>import<br>shipments<br>per year|Median<br>number of<br>shipments<br>per year|Standard<br>deviation of<br>number of<br>shipments<br>per year|Average value<br>of an import<br>shipment (in<br>euros)|Median value<br>of an import<br>shipment (in<br>euros)|Standard<br>deviation of<br>an import<br>shipment (in<br>euros)|
|---|---|---|---|---|---|---|---|
|Small|138|2,170|800|5022|15,454|15,000|10,284|
|Medium/Large|12|29,609|8,405|57,054|14,894|15,000|11,750|
|Total|150|4,365|1,000|17,869|15,416|15,000|10,335|
|||**Panel B. D**|**iversificati**<br>|**on across**<br>|**Clients**<br>|||
||||Number of<br>freight<br>forwarders|Share of<br>business that<br>involves the<br>largest client ‐<br>average|<br> <br>Share of<br>business that<br>involves the<br>largest client ‐<br>median|||
||Small||134|32%|30%|||
||Mediu|m/Large|12|33%|23%|||
||Total||146|32%|30%|||

Source: Authors’ calculations based on data from the Survey of Serbian Freight Forwarders.

Freight forwarders listed all the sectors which account more than 20% of their import shipments and the majority reported raw materials and manufactures as being their main import sectors, as seen in Figure 2. Less than a fifth of the freight forwarders reported agricultural products or food, tobacco, beverages as accounting more than 20% of their import shipments.

9
# **Section 1 Introduction**

With current trends in reduction in maritime transport cost and more advanced logistics technology that compensates for the handicap of intercontinental distance, lack of direct sea-access presents growing challenges to the global integration and growth prospects of many landlocked developing countries (LLDCs). At present, about one out of five countries in the world is landlocked<sup>2</sup> . The problem mostly affects the poorest countries: 20 out of 54 low-income economies are landlocked, with a majority of them in SubSaharan Africa, while only three high-income economies out of 35 are landlocked (not counting European micro-states and dependencies<sup>3</sup> ).

The case of LLDCs has naturally received special attention, including a specific set of development priorities (as spelled out in the Almaty program, see next sections). The problem of being landlocked has been analyzed mostly at a macro-level with a focus on the dependence over transit countries and on LLDCs’ transport cost disadvantage. Hence, emphasis has traditionally been set on three kinds of measures: (1) transport infrastructure at the national level, (2) international laws and treaties, and (3) cross-border cooperation.

Notwithstanding the relevance of current approaches, there is a strong case for a deeper analytical and micro-economic understanding of the transit systems serving LLDCs as well as many activities in coastal countries. Indeed, transit logistics is complex, involves many public and private participants and requires adequate procedures and responsibilities. Its performance is determined by a wide range of policies, implementation mechanisms, or organizations of services. This paper tries to develop a comprehensive understanding of how these factors translate into costs. It is rooted in the World Bank Group operational activities: country audits, partnership programs, corridor and trade facilitation projects, and use a substantial amount of data from these various sources.

> 2 43 out of 193 internationally recognized sovereign states. 3

> four landlocked countries are micro-states in Europe: Andorra, San Marino, Vatican, and Lichtenstein.

3
Schogl and classroom characteristics. Data on four school characteristics are analyzed in this paper: (a) whether or not the school was located in Manila, (b) school size, as indicated by the total number of students enrolled in the school, (c) student teacher ratio and (d) type of school (primary, grades 1-6 only, or primary plus secondary, grades 1-10). Two teacher background characteristics are analyzed: (a) teaching experience and (b) extent of post-secondary science education. Class size, defined as the number of students in the class, is also included.

Material and non-material inputs. Three inputs are examined: learning time, textbooks and laboratories. The indicator of learning time was the number of weekly hours the teacher reported teaching science to the sample class. The indicator of textbgok use was the consensus of the students and teacher on frequency of use. If the teacher indicated the 'the prescribed textbook" was "very important" in determining what he or she taught on a day to day basis, and at least 50% of the students in the class agreed that they "often" used a science textbook during a lesson, the class was coded as a "high textbook use" class; 32% of all classes were so categorized. The indicator of laboratory use was the teacher's report on the amount of science teaching to the sample class that took place "in a room or laboratory eguiRped for science teaching and/or student practical work" (Emphasis added). If the teacher indicated that 50% or more of his or her science teaching took place in a laboratory, the class was coded as a "high laboratory use" class; 42% of all classes were so categorized.

20