rafmacalaba/datause-encoder-data huggingface dataset:
# T-able 1: Linking PPAs to policy development work

||**_PPA work_**|**_Broader wo_**<br>**_PPA work t_**<br>**_formulation_**|**_rk which helped to link_**<br>**_o national policy_**<br>|
|---|---|---|---|
|During<br>1998|- Ftundingfor PPAs agreed with DFID<br>-EarlyPPA work and pilot activities<br>- Commitmenit by PPA partner agencies<br>l<br>J<br>.<br>.|- Background<br>assessment, sec<br>resources and<br>poverty assess<br>- (and 1997) co<br>t~~~~~~~~(V|work in planning the poverty<br>uring donor commitment of<br>donor commitment to a shared<br>ment<br>llection of household survey data<br>LSS)|
|Jan 1999|WB and PPA partner agencies meet to discuss<br>scope of research and methodology|Link to global<br>research confir|"Consultations of the Poor"<br>med|
|Feb 1999|- PPA partner agencies join Poverty Working<br>Group asmembers<br>- World Bank travels to PPA study sites to request<br>local authoritypermission<br>for studies|Poverty Worki<br>- including PP|ng Group established and workplan<br>As - agreed|
|Marcli -<br>April|xsa~<br>1999<br>Ail|March: first me<br>to discuss plan<br>~~~~~~~~~~<br>on quant<br>~~~~~~~~~~<br>if|eting of Poverty Working Group<br>s to produce poverty assessment<br>~~~~based<br>itative (VLSS) data and qualitative<br>~~(PPA)<br>i|
|Junel|pr-|<br>norma<br>PWG meeting|<br>on<br>with presentations from some|
|July-<br>Sept|W-<br>Workshop in each of the PPA Provinces to feed<br>back findings (attended by PWG members,<br>especially central policymakers; provincial and<br>district authorities; community representatives;<br>I PPA agencies; other agencies active in poverty<br>reduction work in the area)<br>- National synthesis report drafted<br>- PPA site reports finalized, incorporating feedback<br>-from worksh.ops||- Analysis of quantitative (VLSS)<br>data<br>- National synthesis report<br>submitted to global "Voices of<br>the Poor" research team|
|Sept<br>1999|1National PPA synthesis report finalized based on<br>final site reports and feedback from the PWG||- Presentation and discussion of<br>PPA and VLSS findings to PWG<br>- Participation by 3 PWG<br>members at the Voice of the Poor<br>global workshop.<br>Il<br>**--**-I~~~~~~~~~~~~~~~~~~|
|Oct-Nov<br>1999<br>l|10.<br>. .**.**.<br>...<br>.|.fi<br>. ..**.**<br>.<br>. ..... ...... .....|... .**.**.... ..**.** **... ..**....................<br> <br>........<br>- PWG discusses and debates<br>draft of poverty assessment<br>-Changes<br>made to draft to<br>incorporate Government and<br>donor comments<br>..... ...........................................<br>...........|

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and whether s/he belongs to a household that was displaced by the conflict may turn out a relevant circumstance as well. With these considerations in mind, the following list of circumstances are used for HOI analysis: (1) urban or rural residence; (2) region (six in number); and (3) economic status (proxied by asset index) of the household; (4) gender of the child; (5) gender and age of household head; (6) education of household head (number of schooling years); (7) parental presence in the household; (8) number of children in the household, and presence of elderly; (9) exposure to the conflict.<sup>4</sup> Table 2 below reports the basic descriptive statistics for these circumstances.

All these circumstances are available from both CWIQ of 2007 and 2010, except for urban/rural and regions, which are not reported in the CWIQ 2010. Since direct information on ethnicity is not available from CWIQ 2007, region may be considered a reasonable proxy for ethnic differences.<sup>5</sup> The circumstances associated with the impacts of conflict are quite prevalent: around 30 percent of children do not have both parents and 82 percent are from households that were displaced by war in the 1990s. Several possible circumstances relating parental presence in the household can be analyzed. One possibility is that both parents are alive and living in the household; others include one parent absent from the household, either alive or dead, or both parent absent from the household, either alive or dead. As the effect on opportunities of parental absence may differ from, say, a living father sending remittances home vis-à-vis a dead mother, the most encompassing option is to analyze several circumstances and determine ex-post which

> 4 Similarly, a child‘s birth order may affect decisions on his or her education, as it is shown to do in terms of consumption decisions, school attendance and distribution of chores at home, for instance. However, no CWIQ reports this information. We use age as a proxy for birth order. Age is also a relevant circumstance, given that late entry in school is a common phenomenon in Liberia.

> 5 Liberia has several ethnic groups. The population is divided in Kpelle 20 percent, Bassa 14 percent, Gio 8 percent, Kru 6 percent and 52 percent spread over 12 other ethnic groups. Kpelle in central and western Liberia is the largest ethnic group. Grebo and Kru are concentrated in the southern area, Bassa in the Grand Bassa area, and smaller groups such as Loma and Gbandi in Lofa. http://www.globalsecurity.org/military/world/liberia/maps.htm .

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- **Indicators:** These are usually, but not necessarily, constructed from statistics. They are simple numbers comparable over time and space that have a clear link with policy implications.

- **Indexes:** These are constructed as weighted combinations of indicators and usually are used to describe an overall performance. For instance, the City Development Index (CDI) was developed as a prototype for Habitat II to rank cities according to their level of development. The CDI is based on five sub-indices (City Product, Infrastructure, Waste Management, Health and Education), the total value of which ranges from 0 to 100.

# **5.2 Raw Data: Existing and Potential Sources of Data**

Even though there is a common understanding that time and cross-section comparable data are fundamental to construct useful indicators, most countries fail in this first stage. Typically this happens because cities lack the capacity (skills and funding) to collect accurate data directly at the local level, or lack the resources to transform national data using appropriate weights.

The data that are currently and usually available come from censuses, national household surveys, demographic, health, and living standards measurement surveys, vital statistics registries, administrative or infrastructure data available from public or private companies in charge of services, or specific surveys. The census is the most important source of data providing information at the city level. However, due to its high cost it is usually collected with long lags (typically every 5 or 10 years).

Household surveys include social and economic data at the household or individual level but they are usually representative at the State level, and no disaggregation at the local level is possible.

New city indicators will need to:

- Increase the capacity and improve management information systems at the local level to collect and analyze the already existing data in standardized methods.  This will allow for transversal and longitudinal comparisons.

- If new data need to be collected, they have to be incorporated in one of the existing city systems to guarantee the continuity of its collection.

- Promote waves of data collection in a routine manner and independent of external funding to guarantee continuity in data gathering.

- Emphasize to city officials the importance of indicators for the management and planning of cities. Successful examples of cities using indicators are key to providing motivation and incentives to collect data and construct indicators in a systematic way.

- Begin incorporating GIS techniques in future data collection to permit a better understanding of geographical changes over time.

# **5.3 Characteristics of City Indicators**

Good data are a necessary but not sufficient ingredient for the construction of good indicators. The following are characteristics that an indicator must possess for it to be accurate, timely and relevant for policy purposes:

**<mark>Aspects</mark>** **<u><mark>of Good City Indicators</mark></u>**

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||**Brazil**|**Chile**|**Colom-**<br>**bia**|**Costa**<br>**Rica**|**Mexico**|**Russian**<br>**Federati**<br>**on**|**South**<br>**Africa**|**EU27**|**OECD**|
|---|---|---|---|---|---|---|---|---|---|
|-- Unemployment rate,55-64(% of the labour force)|7.|9<br>6.9|10.5|<br>12.0|<br>2.6|3.6|11.2|5.2|<br>5.2|
|-- Incidence of long-term unemployment, 55-64 (% of total||||||||||
|unemployment)|-|-|7.9|<br>7.1|<br>2.6|26.0|68.6|47.9|<br>38.7|
|**Employability**||||||||||
|<br>-- Share of 55-64 with tertiary education (% of the age||||||||||
|group)|1|5<br>16|16|<br>21|<br>15|50|15|26|<br>29|
|Absolute (% of all employed in the age group)|-|33|-|-|17|-|-|40|<br>41|
|Relative to employedpersons aged 25-54(ratio)|-|0.67|-|-|0.50|-|-|0.81|<br>0.79|

Source: OECD older worker scoreboard, https://www.oecd.org/employment/ageingandemploymentpolicies.htm 41
Policy Research Working Paper 7213

# **Abstract**

This paper extends the micro evidence on the impact of income shocks on civil conflict using data across Nigerian states over the past decade. The paper uses an innovative empirical strategy matching household survey, oil production, and domestic and international price data to capture three separate channels linking income changes to conflict. Price increases of consumed items have a significant conflict-inducing effect consistent with the hypothesis that they reduce real incomes and thus the opportunity cost of fighting. Failure to include this consumption impact severely biases (toward zero) the conflict-reducing effect of price rises of agricultural commodities via production. In addition, oil price hikes increase conflict intensity in oil producing areas, consistent with the “rapacity” hypothesis. However, this effect disappears in the period after the agreement granting amnesty to militant groups in oil-producing areas. The paper also discusses the importance of factors mediating the impact of the shocks on conflict and a number of policy implications following the analysis. Finally, the empirical strategy is employed to unveil a strong relationship between income shocks and violence in the current Boko Haram conflict. The analysis suggests some policy implications, which may be relevant for the Nigerian context and beyond.

This paper is a product of the Trade and Competitiveness Global Practice 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 mcali@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
2018). It should be noted that van Berchum et al. (2020) applied one design condition per polder, whereas different parts of the coastline may have varying wave exposure in terms of fetch, water depth, and coastline angle with respect to the dominant wave direction.

_Table 3. Design conditions (surge levels and incoming significant wave heights, Hm0) from IWM (2018) and associated embankment crest height from van Berchum et al. (2020) at sites with potential for developing mangrove belts seaward from embankments._

|Site|Polder|Location|Surge [mPWD]|Hm0[m]|Required crest height [m]|
|---|---|---|---|---|---|
|number|||2-M|2-M|2-M|
|1|55/4|Galachipa|4,9|3,7|6,3|
|2|55/3|Galachipa|5,1|2,3|5,9|
|3|56/57|Bhola|5|3,0|6,1|
|4|73/2|Hatiya South|4,9|3,4|6,2|
|5|66/3|Khangona|4,8|2,1|5,5|
|6|69|Boro Moheshkhali|4,4|2,7|5,4|

- 3.2. Modeling approach

The method to include the effect of mangroves on embankment designs is schematized in Figure 3.2, and consists of the following steps:

- Propagating waves from the offshore boundary to the toe of the structure (Equations 4-6 of Appendix B)

- Estimating potential vegetation failure (Equations 2 and 11-14 of Appendix B)

- Designing embankment using propagated waves as input, specifically:

- The crest height of the embankment (Equation 7 of Appendix B), and

- The size of the blocks of the slope (Equation 8 of Appendix B)

- Estimating the shear stresses at the toe of the structure (Equation 9-10 of Appendix B).

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above the interpolated target, and an increase represents an increase in substance consumption. If the value is negative, the country is “in compliance.”<sup>10</sup> We merge these country-year emissions data to our data on RTAs and RTA content and construct a “stacked” country-level panel with a _±_ 3 year event window around signature of any RTAs. We consider every RTA that a country signs and include three years before and three years after. If a country signs multiple RTAs in adjacent years, each of _±_ 3 year event windows enter into the analysis data set separately and are stacked or pooled. The resulting panel consists of 265 RTAs and 874 individual seven-year country sequences. We only consider RTAs signed after the Montreal Protocol was signed in 1987, which also corresponds with the start of ODS consumption reporting in most countries.

# **3 Empirical Strategy**

We consider two types of linkages between RTAs and the Montreal Protocol. First, we investigate “participation linkages,” referring to the potential for trade agreement content to induce accession to the Montreal Protocol or its Amendments. Because the Montreal Protocol bans trade in ODSrelated products with countries not party to the Protocol, countries may include provisions in trade agreements to ensure their trading partner’s status with the Protocol to maximize gains from trade liberalization.

The Montreal Protocol is made up of the original 1987 treaty and five amendments introducing new substances (1990, 1992, 1997, 1999, and 2016), each of which needs to be ratified by a country’s legislature. Figures A.16 – A.18 in the Appendix display histograms of the years in which the original treaty and its amendments were ratified. Besides the most recent amendment in 2016, all five amendments and the original treaty exhibit near-universal ratification. If a country has not ratified an amendment, it is considered a non-party for the substances included in that amendment (Brack, 2017). For example, TCA was introduced in the London Amendment of 1990. If a country had ratified the Montreal Protocol but not the London Amendment, it could trade CFC-

> `10` Results using non-interpolated targets are quite similar to reported results and are available upon request.

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- Paterson, I., Rinc ́on-Aznar, A., Sellner, R., Brandl, M.-B. & Robinson, C. (2013), ‘Regulation of services industries and ICT diffusion: Accounting for upstream and downstream linkages’, _SERVICEGAP Discussion Papers_ (DP23).

- Sampi, J., Jooste, C. & Vostroknutova, E. (2021), Identification properties for estimating the impact of regulation on markups and productivity, Policy Research Working Paper Series 9523, The World Bank.

**URL:** _https://EconPapers.repec.org/RePEc:wbk:wbrwps:9523_

- Van Reenen, J. (2010), The economic impact of ICT, Iterim Report 2007-0020, Smart.

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<!-- Start of picture text --> Average distance to access public Average distance to access public<br>transport (residence area) transport (cross country)<br>2.5 7<br>6<br>2<br>5<br>1.5 4<br>1 3<br>2<br>0.5<br>1<br>0 0<br>ADDIS ABABA AMBO ASELA SHASHEMENE JIMMA GIMBI DILA DIRE DAWA METU NEGELE ADIGRAT ADWA AXUM DEBERE MARKOS DEBRETABOR GONDER HARAR HOSAENA JIJIGA MEKELE ADDIS ABABA AMBO ASELA SHASHEMENE JIMMA GIMBI DILA DIRE DAWA METU NEGELE ADIGRAT ADWA AXUM DEBERE MARKOS DEBRETABOR GONDER HARAR HOSAENA JIJIGA MEKELE<br><!-- End of picture text --> Source: WMS, 2011

**What is the impact of agglomeration?** It was Marshall (1919) who was the first to formally identify the benefits of agglomeration. Clusters of firms that are predominantly in the same sector can take advantage of localization economies. These include sharing of sector-specific inputs, skilled labor and knowledge. Thus, costsaving externalities are maximized when a local industry is specialized. The MarshallArrow-Romer (Marshall 1890, Arrow, 1962, Romer 1986) models predict that such externalities predominantly occur within the same industry. Therefore, if an industry is subject to localization externalities, firms within that industry should benefit from spillovers, growing faster and possibly, creating more employment.

An overall large size of the urban agglomeration and its more diverse industry mix is also thought to provide external benefits beyond those realized within a single sector or due to a tight buyer-supplier network<sup>10</sup> (Henderson 2003). Chinitiz (1961) and Jacobs (1969) proposed that important knowledge transfers primarily occur across industries and the diversity of local industry mix is important for these externality benefits. These benefits are related to the diversity of the industrial mix within a city. These include access to specialized industries and services, availability of a large labor pool with multiple specializations, inter-industry information transfers and the availability of less costly general infrastructure. Cities also provide a larger home market for end products, make it easier to attract skilled employees who are attracted by urban amenities not available in smaller towns, and support a large number of complementary service providers such as financial and legal advisers, advertising and real estate services.

The table below lists the top 5 cities in terms of intra-industry and industrial diversity in 2012. Clearly, Addis Ababa tops both rankings – not only is the strength of intraindustry clustering (measured by the localization variable) strongest within the city, but it also ranks the lowest on the Herfindahl Index, indicating high levels of industrial diversity.

> 10 Firms in a given industry could also benefit from firms in related industries. Such inter-industry agglomeration is often related to inter-industry linkages, buyer-supplier networks and opportunities for efficient subcontracting (see Venables 1996). However, owing to a lack of a national input-output matrix, it has not been possible to study inter-industry clustering.

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likely to have joint land rights as older sons tend to be given preference in inheriting land rights (Bezu and Holden 2014b; Kosec et al. 2018), and women living with adult sons have land rights jointly with them.

**Table 4. Prevalence of Agricultural Landholdings by Household Type and Sex of Respondent**

||1.<br>Head of H|ousehold|||2.<br>Sex of|Respondent|
|---|---|---|---|---|---|---|
||Male|Female|||Men|Women|
|=1 if landholding<br>household|**93.8%**|**84.7%**||=1 if landholder|**73.2%**|**70.0%**|
|=1 if documented<br>landholding household|**83.0%**|**74.4%**||=1 if documented<br>landholder|**54.6%**|**47.7%**|
|_Number of households_|_2,157_|_785_||_Number of respondents_|_3,122_|_3,350_|
||3.<br>Househo|ld Sex Com|position||4.<br>Marit<br>Hous|al Status of<br>ehold Head|
||Dual adult|Female-<br>only|Male-<br>only||Married<br>male-headed|Single female-<br>headed|
|=1 if landholding<br>household|**93.5%**|**82.0%**|83.3%|=1 if landholding<br>household|**94.2%**|**86.3%**|
|=1 if documented<br>landholding household|**83.5%**|**70.0%**|56.3%|=1 if documented<br>landholding household|83.6%|78.9%|
|_Number of households_|_2,402_|_436_|_104_|_Number of households_|_1,999_|_522_|

_Notes_ : Tests of equality of means were conducted between (1) male- and female-headed households, (2) male and female landholders, (3) dual adult and female-only households, and (4) single female-headed and married male-headed households. Significant differences at p<0.05 are in bold. Household sampling weights are used.

**Figure 2. Landholding Respondents Who Are Joint Landholders by Household Type, Percent**

<!-- Start of picture text --> Joint landholder<br>97.7 97.4<br>91.2 93.4 93.2<br>37.0<br>16.4<br>Men (n=1,727) Women Men (n=122) Women (n=469) Men (n=1,786) Women Women (n=246)<br>(n=1,352) (n=1,575)<br>Male headed household Female headed household Dual adult household Female-only<br>household<br><!-- End of picture text --> _Notes:_ Household sampling weights are used. Based on respondents’ self-reporting, 80 percent of male landholders in femaleheaded households are adult sons of household heads.

# **a) Gender Difference in Area of Agricultural Landholding**

There is a gender difference in land size by households. Male-headed households’ landholding size is about 35 percent larger than that held by female-headed households (Table 5).<sup>16</sup> These differences in land area persist across the expenditure distribution (see Appendix 8). Female-headed and female-only household landholdings 16 A recent study reached the same result using 2016 land registry data in the Tigray region (Holden and Tiluhan 2020). They also found that women own half of all landholdings, which also corroborates our findings.

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SIERRA LEONE‘S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

**Table 14.  Sierra Leone’s potential gains from greater operational efficiency**

||ICT|Power|Transport|WSS|Total|
|---|---|---|---|---|---|
|Underrecovery of costs|n.a.|0.0|11.2|7.6|18.8|
|Overstaffing|—|2.4|n.a.|—|2.4|
|Distribution losses|n.a.|24.2|n.a.|2.9|27.1|
|Undercollection|n.a.|8.3|—|0.9|9.2|
|Low budget execution|0.0|1.4|6.6|0.0|8.0|
|Total|0.0|36.3|17.8|11.4|65.5|

_Source_ : Derived from Foster and Briceño-Garmendia 2009. n.a. = not applicable; — = not available Underpricing of power and water in Sierra Leone is less burdensome than in other low-income fragile countries. There does not appear to be a cost-recovery problem in Sierra Leone in the power sector as of 2010. In the water sector, as of 2007, Guma Valley Water Company‘s average tariffs stood at $0.22 per cubic meter versus estimated $0.65 per cubic meter average cost recovery tariff. The macroeconomic burden of 0.5 percent of GDP is comparable to what is found in other fragile states (figure 23).

**Figure 23. Underpricing of power and water is less burdensome in Sierra Leone than in comparator countries**

Financial burden of underpricing as percentage of GDP <!-- Start of picture text --> 2.0<br>1.5<br>1.0<br>0.5<br>0.0<br>Power Water<br>Sierra Leone LIC-Fragile<br>Percenatage of GDP<br><!-- End of picture text --> _Source_ : Derived from Briceño-Garmendia and others 2009.

How affordable are cost-reflective tariffs? With a tariff of $0.31 per kilowatt-hour and a monthly subsistence consumption of 50 kilowatt-hours, the associated utility bill comes to $15.50 per month. Based on the distribution of household budgets in Sierra Leone, monthly utility bills at these levels would be affordable by less than 40 percent of the population (figure 24). However, the share of the population that could afford the service is much higher than the share of the population that already has the service, suggesting that Sierra Leone has scope to increase coverage before affordability would become a serious impediment. Strikingly, a more limited subsistence-consumption level of 25 kilowatt-hours per month for power—which is sufficient to meet the most basic needs—would cost $7.80 per month and would be affordable to half of the population. Subsistence consumption of four cubic meters per month for water would cost $2.60 per month and would be affordable for most of the population.

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