rafmacalaba/datause-encoder-data huggingface dataset:
regions and areas that have been left behind may be important to consider. The additional shock introduced by COVID-19 is expected to increase Tunisia’s poverty rate and inequality. This bunching of the population just above the poverty line has key implications in the face of a high risk that the country faces in the future. Many households could fall back into poverty due to environmental or economic shocks. Thus, mechanisms to protect this large, vulnerable subgroup should be a top priority.

# **References**

1. <u>https://www.worldbank.org/en/topic/poverty/brief/poverty-and-distributional-impacts-ofcovid-19-potential-channels-of-impact-and-mitigating-policies</u>

2. <u>https://blogs.worldbank.org/voices/covid-19-will-hit-poor-hardest-heres-what-we-can-doabout-it</u> 3. Ajwad, Mohamed Ihsan and Aran, Meltem A. and Azam, Mehtabul and Hentschel, Jesko, A Methodology Note on the Employment and Welfare Impacts of the 2007-08 Financial Crisis (June 28, 2013). Development Analytics Research Paper Series No. 1303, Available at SSRN: https://ssrn.com/abstract=2286698 or http://dx.doi.org/10.2139/ssrn.2286698 4. <mark>Dingel, Jonathan I., and Brent Neiman.</mark> _<mark>How many jobs can be done at home?</mark>_ <mark>No. w26948. National Bureau of Economic Research, 2020.</mark> 5. <mark>ElKadhi, Zouhair; Elsabbagh, Dalia; Frija, Aymen; Lakoud, Thouraya; Wiebelt, Manfred; and Breisinger, Clemens. 2020. The impact of COVID-19 on Tunisia’s economy, agri-food system, and households. MENA Policy Note 5. Washington, DC: International Food Policy Research Institute (IFPRI).</mark> 6. UNDP. Economic impact of COVID-19 in Tunisia. April 2020 7. UNICEF. Tunisie : Impact des mesures de confinement associées à la pandémie COVID-19 sur la pauvreté des enfants. July 2020 8. World Bank. How the coronavirus affects the poor in Tunisia: First findings. Vasco Molini and Adnen Lassoued. June 03, 2020 19
material welfare at least in the short term, especially for groups with large stakes in the old economic system. Standard economic and social statistics are unlikely to do justice to the significance of this adjustment and to capture adequately the empowerment dimension.

In view of these shortfalls of objective welfare measures, a substantive volume of research has emerged over the last decades that uses people’s own assessments to get at notions of individual well-being. The underlying idea is to rely on individuals and households themselves to define the level of well-being. Even though precise definitions of these concepts still remain elusive, psychologists and economists have used self-assessments as proxy measures of welfare and well-being. The approach has become so successful that subjective questions are now routinely included in household surveys, along with objective measures.

|The distinguishing feature of subjective measures is that they are based on a<br>person’s self-assessment. This raises the question whether they are consistent<br>and change systematically with objective measures. For example, a person’s<br>self-assessed economic situation may stay unchanged even though her con-<br>sumption increases, either because her expectations have increased or because<br>her position relative to her reference group has remained the same. To avoid<br>such pitfalls in the assessment of well-being across a group of individuals on<br>the basis of subjective indicators, one needs to assume that individuals:<br>e are able to understand and answer consistently questions about own situa-<br>tion, and<br>e provide responses that are comparable.<br>While some evidence suggests that these conditions typically hold within a<br>common cultural context, it is generally difficult to verify these assumptions.<br>Furthermore, the reliability of any given welfare indicator can be severely<br>undermined by measurement problems (Deaton (1997)). Therefore, it is im-<br>portant to validate whether observed changes are real or reflect data problems<br>(Baulch and Hoddinott (2000)). One possibility is to investigate whether co-<br>variates display asimilar pattern. Therefore, an analysis ofsubjective measures<br>is best conducted jointly with an investigation of objective indicators, drawing<br>on a wide range of welfare measures.<br>Timor-Leste became the first new state of the third millennium on May 20,<br>2002, following a quarter century ofoccupation. The population endorsed the<br>birth ofthis nationon August 30, 1999when, withaturnout of98 percent, 78.5<br>percent of the registered electorate voted for independence from Indonesia.<br>The announcement ofthe ballot results was followed by violence that wreaked<br>physical destruction and human terror throughout the territory. Up to three-<br>quartersofthepopulationwasdisplacedintheweeksfollowingtheballot|
|---|
and Kennan, 2004; Candau et al. 2004)—that compliance costs are not a big issue.<sup>26</sup> Overall, allowing for rules compliance costs, we no longer have any real losses for African LDCs in total, though we do for individual countries. What this says then is that on net, EU preferences do not really offer benefits to African LDCs. To the extent individual countries benefit, blocking multilateral reductions to maintain these benefits really involves hurting some (neighboring) countries, with no real net benefits for the region as a whole. It also points to the need for country-by-country analysis and assessments of the potential impacts of preference erosion.<sup>27</sup> The results from Tables 6 and 7 imply that the magnitude of any transfer needed to offset (or compensate for) the effect of erosion is much smaller in a context where all OECD countries liberalize than in a bilateral EU context. LDCs do stand to lose from tariff reductions in sectors or products where preferences matter. However, they also stand to benefit from improved access to OECD markets; a process that at least partially, and often substantially, offsets the more direct losses on a bilateral basis from erosion of preference margins. We should note that this offset is most likely to be an underestimate, because of the assumption that developing countries themselves do not liberalize. Independent of the welfare economic implications of this assumption, as noted previously, it is an appropriate constraint to impose given the political economy-cum-negotiating context in which the preference erosion question is placed. The issue at hand is the magnitude of erosion of benefits that stem from removal of an explicit development-motivated policy that has been put in place by OECD countries. From this perspective it is not relevant that there are other sources of offsetting market access and/or terms of trade gains—be it from liberalization by other developing countries or own liberalization.

Finally, it is informative to place our estimates in the context of ongoing changes in the trading system. Table 8 compares our estimates of preference erosion to a set of estimates (based on the application of the same basic computational model by Francois 26 We can note in passing that this implies that the compliance cost estimate obtained in Section 3 will in fact be higher than 4 percent on average for manufactures. This also biases upward our calculation of the potential value of erosion.

> 27 IMF (20003) concludes that individual LDCs may suffer more than average due the concentration of their exports in products that enjoy deep preferences. Of the LDCs, Cape Verde, Haiti, Malawi, Mauritania, and São Tomé and Príncipe are found to be the most vulnerable to preference erosion. Alexandraki and Lankes (2004) conclude that six middle-income countries—Belize, Fiji, Guyana, Mauritius, St. Kitts and Nevis, St. Lucia— would also be significantly affected, with predicted export declines ranging from 11.5 percent for Mauritius to 7.8 percent for Fiji.

21
Policy ReseaRch WoRking PaPeR 4838

# **Abstract**

Using a unique sample of net domestic product data for districts in India, I investigate the connection between banking sector development, human capital, and economic growth at the sub-national level. Using disaggregate data avoids many of the omitted variable problems that plague cross-country studies of the financegrowth connection and facilitates an instrumentation strategy. The findings show that the growth of many districts in India is financially constrained due to lack of banking sector development, and that the relationship between finance and growth may be non-linear. For the districts in the sample, moving from the 75th percentile of credit/net domestic product to the 25th percentile implies an average loss of 4 percent in growth over the 1990s. This indicates that the gains from increased banking sector outreach may be large. The analysis shows that human capital deepening can reduce the effect of the financial constraint and help decouple growth from financial development. In a district at the 25th literacy percentile, the implied growth loss due to a constrained banking sector is twice as large as in a district at the 75th literacy percentile. Thus, higher levels of human capital may activate alternative growth and production channels that are less finance intensive.

This paper—a product of the Financial and Private Sector Vice Presidency—is part of a larger effort in the department to understand the role that banking sector outreach plays in economic development. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at jkendall1@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
main regulatory responsibilities ( _Comisión Nacional de Energía_ ), the Board of Directors is composed of sector ministers and headed by the line minister.<sup>5</sup> F Moreover, in both countries, the heads of the agencies in charge of the enforcement of quality standards and consumer complaints ( _Superintendencia_ ) are also appointed and removed by the President with no involvement of other institutions. These factors differentiate Chile and Colombia from other countries of the region in which the Board is composed of members that are not policy formulator’s authorities. Nevertheless, this observation is a reflection on the design of the agency and does not speak about the real impact of government in the agency’s decision-making, which is especially addressed in the Informal Autonomy Index. In our framework, we assume that an agency whose Board is composed of ministers will tend to be less independent from the government than an agency that is integrated by non-public official members.

# **A. Political autonomy:**

This element of an agency’s autonomy reflects the level of independence of the agency from political authorities. Its focus is on the independence of the agency’s decision-making from authorities in charge of policy formulation, namely the line minister. It includes issues such as the mechanism to select agencies’ directors, the renewability of directors’ mandates, the number of directors that have not completed their terms, the reasons directors leave their positions, the interference of the minister in the agency’s decisions, and the composition of the agency’s budget.

**<mark>Figure 8: Political Autonomy Index</mark>**

<!-- Start of picture text --> Political Autonomy Index<br>Source: LAC Electricity Regulatory Governance Database, The World Bank, 2007.<br>1<br>.8<br>.6<br>Index (0-1) .4<br>.2<br>0<br>T1 BRA R D NIC BOL PER C R ESV T2 ARG URU MEX PAN T&T GUA JAM HON BAR ECU COL CHI<br><!-- End of picture text --> The Political Autonomy Index has the largest number of countries among Tier 3 agencies. It could be understood from this finding that the independence of agencies from political authorities is the most significant deficiency of agencies in terms of their autonomy. Only Brazil is among Tier1 countries.

Tier 3 countries present a wide variety of agencies. There are agencies from which we would expect their positioning among T3 such as Ecuador, Honduras, and Chile. Nevertheless, countries with a good overall performance in the ERGI and the Autonomy Index such as Trinidad and Tobago and Argentina are also part of this group of agencies.

> <sup>5</sup> In the case of Colombia’s _Comisión de Regulación de Gas y Energía_ , the Board is also composed of five experts appointed by the President of the country.

- 21 -
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BENIN’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

# Ports

## **Achievements**

Port security plans are being put in place in the Port of Cotonou. The steps taken to date have been fairly basic, for example, constructing higher walls around the port, implementing strict controls at port gates, introducing floodlighting at the quayside, requiring all port workers to carry identity cards, and having a port security officer on guard 24 hours a day. These measures enabled Cotonou to earn the ISPS (International Ship and Port Facility Security) code, following a visit by the U.S. Coast Guard.

**Table 5. Port indicators for the Port of Cotonou and selected other ports**

|Port|Unit|Lomé,<br>Togo|Cotonou,<br>Benin|Dakar,<br>Senegal|Abidjan,<br>Côte d'Ivoire|Tema,<br>Ghana|Apapa,<br>Nigeria|Harcourt,<br>Nigeria|
|---|---|---|---|---|---|---|---|---|
|Container cargo - total<br>handled|TEU,annual|460,000|158,201|331,191|500,119|420,000|336,308|7,900|
|Container dwell time|Days|13|12|7|12|25|42|30|
|Truck turn-round time|Hours|4|6|5|2.5|8|6|24|
|General cargo vessel<br>pre-berth waitingtime|Hours||48|24|2.9|9.6|36|38.4|
|General cargo vessel<br>turnaround time|Hours||48|60|2.2|48|40.8|45.6|
|Craneproductivity|Containers<br>per hour|─|─|─|18|13|12|─|
|Craneproductivity|Tonnes per<br>hour|23|15|─|16|14|9|8|
|Container cargo<br>handlingcharge|US$ per TEU|220|180|160|260|168|155|─|
|General cargo<br>handlingcharge|US$ per ton|9|9|15|14|10|8|8|
|Bulk dry handling<br>charge (ship to gate or<br>rail)|US$ per ton|5|5|5|5|3|||
|Adequate road access<br>present|0=no;1=yes|0|0|0||0|0|0|
|Landlord model is used|0=no;1=yes|1|0|0|1|1|1|1|

_Source_ : AICD ports database downloadable from http://www.infrastructureafrica.org/aicd/tools/data. _Note_ : Data are as of 2006. — = data not available.

## **Challenges**

The Port of Cotonou is operating under the pressure of growing demand; by 2005 demand was almost twice the port’s designed capacity. Demand for general cargo and dry bulk handling grew 140 percent between 1996 and 2005, from 2.03 million tons handled to 4.84 million (76 percent dry bulk and 24 percent general cargo, figure 9a). The port’s design capacity is 2.3 million tons per year, but as of 2005 it was handling an excess of more than 2.5 million tons per year. Between 1996 and 2005 container tonnage (exports and imports) increased 340 percent, from 5.5 million tons in 1995 to 2.4 in 2005 (figure 9b), most due to the large increase in imports destined for Niger and Nigeria. In fact, transit traffic represents 46 percent of all traffic, of which 84 percent is traffic to Niger and Nigeria.

14
living adjustments made to enhance the comparability of living standards between urban and rural areas – or across different regions of large countries – change as well.

This paper documents as extensively as possible the various changes in all of these domains, which were used in constructing a new global count of the extremely income poor for the year 2012, using the new 2011 PPPs. This global count underpins the World Bank’s recent poverty update in Cruz et al. (2015) and World Bank (2015a), and is based on a new international poverty line set at $1.90 a day (per capita) in 2011 PPPs. This line was derived in accordance with our best judgment of how to maintain the real value of the $1.25 line (at 2005 PPPs) in poor countries, so as to preserve the integrity of the “goalposts” for international targets such as the SDGs and the World Bank’s own goals. Specifically, the values of the fifteen poverty lines that underpinned the $1.25 line were taken in local currency units in 2005, and inflated to 2011 prices using the best available domestic price or costs-of-living indices. The resulting values were converted to USD using 2011 PPPs. A simple average of these numbers yielded $1.88, which we rounded to $1.90. A number of alternative approaches – including taking the local currency lines corresponding to $1.25 (in 2005 PPPs) in 101 developing countries, inflating them to 2011 using domestic CPIs, and then converting them to USD with the 2011 PPPs – yield results that are either exactly equal to $1.90, or very close.

In addition to changes in the line, we have documented in some detail which price indices were used for each of the 131 countries included in the exercise, with particular emphasis on those where the number differs from the indices reported in the World Development Indicators. We have also discussed those cases where adjustments are made to consumption or income vectors to account for spatial differences in the cost of living within countries, including China, India, Indonesia and countries in Latin America, the Caribbean, Europe and Central Asia.

The combined result of these various changes for the year 2011 is that the global headcount rate changes from 14.5% (with respect to the $1.25 line, at 2005 PPPs) to 14.1% (with respect to the $1.90 line, at 2011 PPPs). This change corresponds to 28 million people. For 2012, the reference year for the new count, the incidence is 12.7%, corresponding to 897 million persons. The regional profile of poverty changes only moderately, with the new method yielding slightly lower poverty in the poorest regions (notably Sub-Saharan Africa and South Asia), and slightly higher poverty in middle-income regions (notably Latin America and the Caribbean, and Europe and Central Asia). Trends over time between 1990 and 2012 are very similar using the 39
be rewarding for host communities. Improved employment outcomes, for instance, boost economic prosperity as indicated by our result of increased asset ownership among hostcommunity members. Existing evidence suggests that employment goes along with other benefits such as improved psychological well-being (for example, Hussam _et al._ , 2022). Improved economic empowerment of women has also been associated with progress toward other development outcomes (e.g., Hsieh _et al._ , 2019). This finding opposes results from public opinion surveys showing that some host-community members are concerned that IDPs will reduce their employment prospects (Pape and Sharma, 2019) and further supports an overwhelming evidence base concerning the favorable implications of refugee integration efforts (Marbach _et al._ , 2018; Fasani _et al._ , 2021).

Our evidence suggests that additional investments in local IDP support systems are required. Development interventions must address the potential male backlash against economically empowered women in the form of increased risk of domestic violence which is reported in this paper. This objective may be achieved in various ways. For instance, timely investments in health and human capital for adolescent girls were shown to reduce intimate partner violence faced by these girls after marriage (Chatterjee and Poddar, 2022). Similarly, providing adolescent girls with vocational training and information on sex, reproduction, and marriage can result in increased bodily integrity (Bandiera _et al._ , 2020).

The observed reduction in women’s acceptance of domestic violence as a result of distant Boko Haram attacks is an encouraging finding and can boost the effectiveness of these investments by helping daughters select into healthier partnerships. Even though the backlash of the partner to increased female employment is not offset by these desirable impacts, the influence of women on their sons is arguably greater, and their sons’ behavior as a partner in a relationship will therefore potentially be different. Women’s reduced acceptance of intimate partner violence may also be directly leveraged in group training for women and men, community-mobilization interventions, and combined livelihood and training interventions for women (Ellsberg _et al._ , 2015; Gram _et al._ , 2021; Jewkes _et al._ , 2008). There are also successful examples of interventions targeting men to re39
# VII. Appendix

Table A1. Comparison of predictors used for Proxy Means Testing models in South Asia

|Variables|||Sri Lanka||Bangladesh|Pakistan|
|---|---|---|---|---|---|---|
||Model 1|Present<br>Study<br>Model 2|Model 3|Narayan &<br>Yoshida<br>(2005)|Sharif<br>(2009)|Hou<br>(2008)|
|_HH demographics_<br>|||||||
|Household size<br>|X|X|X|X|X|X|
|Dependency ratio|X|X|X||||
|Highest education level (split into grade 10, O‐|X|X|X||||
|level, A‐level and degree)|||(partial)||||
|Member age||||X|X|X|
|_Head characteristics_|||||||
|Age|X|||X|X|X|
|Education|X|||X|X|X|
|Occupation|X|||X|X|X|
|Marital status|X|||X|X|X|
|Gender|X|||X|X|X|
|_HH assets_|||||||
|Computer|X|X|X||X||
|Cooker|X|X|X|X|||
|Electric fan|X|X|X|X||X|
|Refrigerator|X|X|X|X|X||
|Land phone|X|X|||X||
|Washing machine|X|X|X||||
|Water pump|X|X|||||
|Motorcycle|X|X|X|X|X||
|Car/van|X|X|X|X|||
|Three‐wheeler|X|X|X||||
|Four‐wheel tractor|X|X||X|X||
|Tube well|X|X||||X|
|TV||||X|X|X|
|Cattle/livestock||||X|X|X|
|Bicycle||||X||X|
|Radio/CD or cassette player||||X|||
|Sewing machine||||X|||
|Watch|||||X||
|Air conditioner|||||X||
|_Housing quality and facilities_|||||||
|Bedrooms per person|X|X|X|X|X|X|
|Type of latrine|X|X||X|X|X|
|Drinking water source: inside unit|X|X|||||
|Electricity for lighting|X|X|||X|X|
|Have floor tiles/terasso|X|X|X||||
|Have walls of brick/kabok/cement|X|X||X|X|X|
|Have water pump|X|X|||||
|Type of roof|||||X|X|
|Type of fuel for cooking||||X|X||

24
17

# FIGURE _5_

<!-- Start of picture text --> Impact of Interest Rate Adjustment<br>on Total Nominal Subsidies<br>60<br>5<br>50-<br>L 40 The arsa between the two curves represents<br>subsidy savings:<br>= 1 \ 16~13 Billion Forints in nominal terms, or<br>E 30 45 Billion Forints in real terms (in Jan-1989 value)<br>20-<br>10- i<br>1990 2025<br><!-- End of picture text --> initial subsidies **A** revised subsidies <!-- Start of picture text -->
|Savings Achieved through Progressive|<br>Interest Rate Adjustments l<br>20- -0.5<br>i8- r 1-n 1992 and 1993, 0.4% of GDP Could be saved 0.45<br>through this option. 0l 4<br>16 ts . _ -0.4<br>.!14- / -0.35<br>0 o12 t. , -0.3 IL<br>rC savings in Billion -- savings in %/ of GDP<br><!-- End of picture text -->
<!-- Start of picture text --> 30<br>3<br>E><br>>3 2<br>3<br>§ 15<br>FS<br>oO<br>3A 10<br>5 5<br>a ° Se2005Say2006ge2007a2008See Se2009ee2010 2011ee2012 ee Se2013eee2014See2015 Ce2016Beems2017Revert2018 See2019Peewee!2020<br>Year<br><!-- End of picture text --> <!-- Start of picture text --> 30><br>§<br>E 255<br>3 20-<br>§5154<br>SsS<br>28 105<br>a 55<br>__ 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020<br>ol]een<br>[== Year<br><!-- End of picture text -->