rafmacalaba/datause-encoder-data huggingface dataset:
**Figure 11 Share of economies allowing different modalities of foreign bank establishment**

<!-- Start of picture text --> 95<br>90<br>85<br>80<br>75<br>70<br>65<br>Acquisition of domestic entity 100% foreign-owned subsidiary Branching allowed<br>(control allowed) allowed<br>2008-11 2016<br>STRI 2008-11, 2016<br><!-- End of picture text --> Even though there are now fewer explicit restrictions on entry, scrutiny of foreign banks has remained intense or even been strengthened. For instance, even when the presence through branching is allowed, stringent regulatory conditions (e.g. imposition of endowment capital requirements, limitations on the expansion of the branching network) are imposed in a majority of economies. In addition, roughly a quarter of our sample now applies different licensing criteria for foreign banks. Finally, more than half of the economies in our sample subject foreign banks to either economic needs tests, investment screening requirements or non-automatic licensing approvals (even when all formal licensing criteria have been fulfilled).

**Figure 12 Share of economies with different types of restrictions on foreign banking (mode 3)**

<!-- Start of picture text --> 70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>Approval subject to Branching subject to Criteria to obtain a license<br>ENT/screening/non-automatic restrictions different for foreign banks<br>license<br>2008-11 2016<br>STRI 2008-11, 2016<br><!-- End of picture text -->

# **3.2.2  Telecommunications**

There continues to be a trend towards liberalization in telecommunications services, although a high level of competition was already achieved around 2008 (at least for the set of economies/regions covered). Liberalization since then has occurred mainly in fixed telecommunication services, as the mobile sector had already been opened prior to that date. The biggest liberalization occurred in low-income countries, such as Bangladesh. Policy convergence in the telecommunications sector across different levels of development is confirmed by the low level of correlation between the STRI and per capita income. We also see that economies at different levels of development have 21
Table 4: Robustness regressions for the difference in bank lending between 2006 and 2009, decomposed crisis experience<sup>_†_</sup>

||**D1**|**D2**|**D3**|**D4**|**D5**|**D6**|
|---|---|---|---|---|---|---|
|Currency crises|-0.180<br>(0.09)<sup>_∗∗_</sup>||||||
|Stock market crises||-0.120<br>(0.10)|||||
|Domestic debt crises|||-0.615<br>(0.24)<sup>_∗∗_</sup>||||
|Banking crises||||-0.302<br>(0.26)|||
|Princ. comp. 1 & 2|||||-3.209||
|(4 crises)|||||(1.35)<sup>_∗∗_</sup>||
|Princ. comp. 1 & 2||||||-2.213|
|(6 crises)||||||(1.18)<sup>_∗_</sup>|
|Host FE|Yes|Yes|Yes|Yes|Yes|Yes|
|Bank covariates|Yes|Yes|Yes|Yes|Yes|Yes|
|Home country covariates|Yes|Yes|Yes|Yes|Yes|Yes|
|1st-stage _F_|0.00|0.00|0.00|0.00|0.00|0.00|
|Underid. test|0.00|0.00|0.00|0.00|0.00|0.00|
|Weak id. test (rel. bias)|_<_5%|_<_5%|_<_10%|_<_5%|_<_5%|_<_5%|
|Overid. test|0.44|0.11|0.65|0.14|0.74|0.71|
|2nd-stage _F_|0.00|0.02|0.00|0.06|0.00|0.01|
|Estimation|IV|IV|IV|IV|IV|IV|
|Obs. (host countries)|346 (61)|346 (61)|346 (61)|346 (61)|346 (61)|346 (61)|

> _†_ The dependent variable is the difference in bank loan-to-asset ratios between 2006 and 2009. Heteroskedasticity and host country correlation-robust standard errors are reported in parentheses. A constant term was included in the regressions, but not reported. The underidentification test is the Kleibergen-Paap rk _LM_ , the weak identification test is the Kleibergen-Paap rk Wald _F_ , and the overidentification test is the Hansen _J_ .<sup>_∗_</sup> indicates significance at 10 percent level,<sup>_∗∗_</sup> indicates significance at 5 percent level, and<sup>_∗∗∗_</sup> indicates significance at 1 percent level.

principal components with eigenvalue greater than unity,<sup>27</sup> and use this as an alternative measure of crisis experience.

The results using the measure constructed from our four included classes of crises are reported in column (D5). Moreover, since PCA decompositions effectively resolve the problem of excess correlation between different crisis categories, we can now add the final two (initially dropped) categories of crises into the construction of a PCA measure; the results from this expanded measure are reported in column (D6). Overall, the PCA decompositions validate the results obtained in the baseline: greater crisis experience tends to reduce the change in the loan-to-asset ratio resulting from the crisis.<sup>28</sup>

> 27In our data, the first two principal components explain more than 75 percent of the data, and are the only two whose eigenvalues exceed the value of one. In our composite PCA measures, we use their variance proportion as the weight for each respective component.

> 28Additional specifications with additional decompositions are provided in appendix, and the results therein confirm the main conclusions discussed here.

26
**Table 4 –Growth spillover effects among inland provinces**

|Dependent variable:<br>)<br>ln(<br>)<br>ln(<br>1<br>,<br>,<br>−<br>−<br>_t_<br>_i_<br>_t_<br>_i_<br>_y_<br>_y_|(1)|(2)|(2')|(3)|(3')|
|---|---|---|---|---|---|
|)<br>ln(<br>1<br>, −<br>_t_<br>_iy_|-0.137*** <br>(-5.20)|-0.136***<br>(-5.06)|-0.131***<br>(-4.86)|-0.187***<br>(-3.84)|-0.188***<br>(-3.85)|
|)<br>ln(<br>,_t_<br>_i_<br>_DP_|-0.254***|-0.292***|-0.307***|-0.337***|-0.374***|
||(-3.11)|(-3.44)|(-3.60)|(-2.83)|(-3.18)|
|)<br>ln( ,_t_<br>_is_|-0.013|-0.010|-0.013|-0.052*|-0.066**|
||(-1.02)|(-0.71)|(-0.95)|(-1.87)|(-2.48)|
|)<br>ln(<br>,_t_<br>_in_|-0.798*|-0.686*|-0.692*|-0.659|-0.914|
||(-1.95)|(-1.70)|(-1.70)|(-0.79)|(-1.11)|
|_t_<br>_i_<br>_GAWINML_,||0.208**<br>(2.24)||||
|_t_<br>_i_<br>_GAWINFL_,||||0.221*<br>(1.67)||
|Constant|2.678***<br>(3.58)|3.002***<br>(3.85)|3.138***<br>(4.01)|3.371***<br>(3.25)|3.697***<br>(3.61)|
|Observation number|360|348|348|154|154|
|AdjustedRsquare|0.5325|0.5533|0.5460|0.6285|0.6200|

Note: _t_ -students are in parentheses. * significant at 10 percent ; ** significant at 5 percent ; *** significant at 1 percent.

The significance of the positive spillover effects holds for the Chinese provinces as a whole, as well as for the different sub-groups. However, some provinces have more significant spillover effects on the others. In this case, the relatively less advanced coastal provinces act as “locomotives” that pull and push the development of their neighbors. Some provinces benefit from the spillover effects disproportionately, for example, the relatively more developed central provinces enjoy the pushing and pulling effects from their neighbors. In this regard, the polarization of the most developed coastal provinces and the catching-up of the relatively rich central provinces could be expected due to the strong spillover effects that they enjoy.

17
# **<mark>Table C.4b: Comparison of modal class assignments across the 4-class and the 5-class models for relations with customers</mark>**

|Read by rows: from 4-class (row) t|o 5-class<br>Class|(column)<br>Class|<br>Class 3|Class 4|Class 5||
|---|---|---|---|---|---|---|
||1|2||||Total|
|Pure bilateralism|**89.42**|0.65|0.1|8.87|0.97|100|
|Bilateralism with private support|8.7|**51.75**|0.48|33.86|5.21|100|
|Bilateralism with weak support|1.54|6.28|**84.1**|0.15|7.94|100|
|Weak comprehensive governance|15.73|10.13|1.1|56.73|16.32|100|
|Total|54.58|14.17|11.65|15.94|3.66|100|
|Read by columns: from 5-class (col|umn) to<br>|4-class (ro<br>|w)<br>||||
||Class|Class|Class 3|Class 4|Class 5||
||1|2||||Total|
|Pure bilateralism|**94.43**|2.65|0.47|32.06|15.28|57.64|
|Bilateralism with private support|3.84|**87.98**|0.99|51.16|34.33|24.09|
|Bilateralism with weak support|0.38|6.02|**98.1**|0.12|29.52|13.59|
|Weak comprehensive governance|1.35|3.35|0.44|16.65|20.88|4.68|
|Total|100|100|100|100|100|100|
|Estimated class membership probab<br>|ilities an<br>|d standar<br>|d errors<br>||||
|Pure bilateralism|0.565|0.032|Class 1|0.4739|0.0422||
|Bilateralism with private support|0.145|0.025|Class 2|0.1152|0.0267||
|Bilateralism with weak support|0.242|0.000|Class 3|0.2205|0.0305||
|Weak comprehensive governance|0.050|0.008|Class 4|0.1579|0.0264||
||||Class 5|0.0325|0.0088||

31
# Well spent: How governance determines the effectiveness of infrastructure investments

## **Martin Kornejew**<sup>**1,2**</sup> **, Jun Rentschler**<sup>**1**</sup> **, Stéphane Hallegatte**<sup>**1**</sup> **,**

_1Global Facility for Disaster Reduction and Recovery, World Bank, Washington DC, USA_ _2Bonn Graduate School of Economics, University of Bonn, Germany_

**Acknowledgements:** This background paper contributes to the World Bank’s flagship report _Lifelines: The Resilient Infrastructure Opportunity_ . It has benefited from helpful comments, feedback, and inputs by Asif Islam, Marie Hyland, Jason Russ, and Joshua Wimpey.

**JEL classification:** H54, D73, O17

**Keywords:** governance; infrastructure; investment
Table 1V.9

# Factory Autoniation Sample: Usefulness of Collective Marketing Support

|____________________|**Early**<br>|Exporters||**Late**<br>Expo|rters|**Large**<br>Export|ers|
|---|---|---|---|---|---|---|
|1. Number of Firms|6||||4||
|2. Average Relative Importance of Support by Public<br>or Non Profit Agency for your Firm to Penetrate<br>Export Markets.||||_|||
|a. At First Export|1.5||2.0||2.0||
|b. In 1991|1.7||1.9||2.0||
|3. Proportion of Finms Receiving Service Provided by<br>such an Agency and its Relative Usefulness.|Ever<br>Used|Usfl|Ever<br>Used|Usfl|Ever<br>Used|Usfl|
|Infonnation on Export Opportunities|.50|2.7|.50|3.2|.75|3.3|
|Introduction of Buyers|.33|3.5|.40|3.0|.75|3.3|
|Participation in Domestic Trade Fair|.33|4.0|.50|3.8|.75|3.7|
|Participation in Overseas Trade Fair|.83|4.2|.20|4.5|.50|4.0|
|Support of Exploratory Marketing Trips|.16|4.0|0|-|.25|4.0|
|Export-ImportAgency|0|-|0|-|0|-|
|Obtaining Foreign Standards|0|-|.20|5.0|.25|5.0|
|Overseas Distribution of Promotional Material|.50|2.7|.30|3.3|.75|3.7|
|Joint Venture 1echnology Ties with Foreign Firm|0|-|.20|4.0|.25|5.0|

Ever used = Average probability of ever having used. Usfl = Average usefulness score on a scale of 1 (low) to 5 (high).

Note: Early exporters began exporting before 1984. Late exporters began after 1984.

**b6**
# **Table S26. Estimated total number of households without access to basic necessities and average household-level incidence of lack of access**

||Unable to<br>Access<br>Medicine|Unable to<br>Access Staple|Unable to<br>Access Soap|
|---|---|---|---|
|Total|5,132,974|11,151,785|4,075,418|
||(253,575)|(448,490)|(276,591)|
|Mean|0.204|0.243|0.124|
||(0.010)|(0.010)|(0.008)|
|Observations|4,604|6,793|5,298|

_Note_ : Each column reports the estimated total number of households without access to basic necessities and average household-level incidence of lack of access. Inability or ability to access a basic necessity is conditional on the household needing the item or attempting to purchase the item. Note that the question regarding soap was not asked in Ethiopia. Data are only from the first phone survey round in each country. Standard errors on the estimates are in parenthesis.

53
9 degree in which the shape of a polygon deviates from its equal-area circle. It is calculated as the share of the total area of the urban extent that is inside the equal-area circle about its center of gravity (Angel et al., 2010b). An _Exchange_index_ equal to 1 corresponds to a perfect circle. As the _Exchange_index_ moves towards 0, the shape of the polygon becomes irregular, elongated, and noncompact. The smoothness of the perimeter is measured with the _Perimeter_index_ , which indicates how smooth is the perimeter of the urban extent. It is calculated as the ratio of the perimeter of the equal-area circle and the perimeter of the shape (Angel et al., 2010b). A _Perimeter_index_ equal to 1 indicates a totally smooth perimeter, found in a perfect circle. A _Perimeter_index_ close to 0 indicates a highly irregular perimeter, which is very common in natural/organic cities located in rugged topography. Finally, the level of fullness is quantified with the _Fullness_index_ , which measures the presence of built-up areas within the urban extent as a fraction of the urban extent area. It is calculated as the fraction of the total area of the urban extent that is built-up. This measure can be understood as the complement of measures such as porosity or sprawling (Burchfield et al., 2006). A _Fullness_index_ equal to 1 corresponds to a totally compact/built-up city. A _Fullness_index_ close to 0 represents a sprawling city with lots of empty spaces within its borders. In this study, the _Fullness_index_ was calculated using the built-up presence by epoch layers from Global Human Settlement Layer project (GHSL) at 250 meters of spatial resolution for 1990, 2000 and 2014 (Pesaresi et al., 2015; Pesaresi et al., 2016).

Next, we study two dimensions of a city structure related to two dimensions of connectivity: first, the structure given by the layout of the road network, and second, the connectedness of its segments. We measure urban structure with the _Circuity_avg_ , which takes values close to 1 when the streets in the network are mostly straight lines, and greater than 1 when the streets are curvier/organic. This metric is calculated as the average ratio between an edge length and the straight-line distance between the two nodes it links (Boeing, 2017). Regarding the connectivity we applied the two most popular metrics for assessing connectivity: _Intersection_density_ and the _Street_density_ ; _Intersection_density_ is calculated as the sum of all edge lengths divided by the area (Boeing, 2017), and _Street_density_ is calculated as the sum of all edges in the undirected representation of the graph (in km) divided by the area in Km<sup>2</sup> (Boeing, 2017). Both metrics inform about the ease of movement across the city (Boeing, 2017). High values of these two measures are associated to high rates of walking and use of nonmotorized transport modes (Cervero, 1997).
3.15 Other guality indicators: Several other indicators describe changes in education quality. Kakwani, et.al. (1990) use student/teacher ratios as a proxy for education quality, implying that a lower ratio in IAL countries (35 in 1980-85 versus 39 in 1970-75) reflects a positive quality effect from ib.e adjustment process. On the other hand, Lockheed, Verspoor, et.al. (1990) argue that class size reduction in the 25-45 range in fact has little impact on education quality. Declining student/teacher ratios in adjusting countries suggests only that teacher recruitment is much less responsive to macroeconomic shocks (recession or adjustment) than is the demand for education. Internal efficiency indicators such as test scores, repeater rates, dropout rates, completion rates, and years to produce a graduate also reveal quality changes. Two reports provide internal efficiency indicators for a large number of countries (Lockheed, Verspoor, et.al., 1990; World Bank, 1988c), but do not examine the impact of adjustment programs. On average, repeater and completion rates (in primary education) improved slightly for all developing countries.

# BOX 111.6: Education equityrural yersus urban

Morocco offers a unique comparison of primary education indicators between rural and urban areas. Trends during the 1980s were similar for the two sreas, except for the gross enrollment rate: the urban rate declined and the rt. . te increased. By building schools and bouses for teachers in rural areas, L rocro's first Education SECAL (1986) sought to narrow the gap between urban r rural areas, and to improve rural and female enrollment rates. The gap between the two areas remained significant in 1988 according to all three indicators. It may be too soon, after only two years of sector adjustment, for equity improvements to be measurable.

<!-- Start of picture text --> 1980 1988<br>Urban Rural Urban Rural<br>Student/teacher ratio 40 33 30 22<br>Gross enrollment rate (t) 124 49 96 52<br>Girls as % of enrollments 45 24 46 29<br>Sowrc: World Bank (1989a).<br><!-- End of picture text -->

## EquiE y

3.16 Adjustment programs that alter education financing also affect equity. For example, changes in the intrasectoral allocation of public resources by level affect education supply and demand, particularly with respect to the poor who benefit the most from basic education. The literature provides only country-specific evidence (annex 1). Costa Rica cut per student expenditures in primary education more than in secondary or tertiary education. Ghana protected per student primary spending, although enrollment growth did not keep pace with population growth (box 111.4). Several sources mention that the effects of decreasing public financing may be offset by increasing contributions from user fees and 30
**Policy, Reserch, and** **_Extwna_ Affairs**

**Population, Heauth, and Nutrition WPS 456**

- This paper a product of the Population, Health, and Nutrition Division, Population and Human - Resources Department is part of a larger study in PRE of African health policy. A policy paper is being written based on the study. Copies of this paper are available free from the World Bank, 1818 H Street NW, Washington DC 20433. Please contact Zarine Vania, room S6-266, extension 33664 (38 pages with tables).

Few people in Sub-Saharan Africa have access to essential drugs. And where drugs are available, they are inequitably distributed and improperly used. The main problems -- and possible solutions -- are: Drugs are distributed through the private sector, nonprofit organizations, and govcmments. The private sector consists of a large proportion of unqualified illicit peddlers of drugs who dispense adulterated or expired drugs without prescription. Pharmacies run by qualified pharmacists are a small minority. Nonprofit organizations -- usually humanitarian, secular, or religious -- and public agencies run by govemments also distribute drugs.

African countries do not have the capacity to produce the drugs they need. Phannaceutical industries in Africa depend on imported raw materials that are expensive when bought in small quantities. It is generally cheaper to import generic drugs than to produce them locally. The paper discusses procurement strategies that have resulted in savings in several countries.

Drugs are wasted due to poor storage conditions, inadequate security, and deficient inventory control systems. Proper selection, quantification, storage, and inventory management of drugs could alleviate this problem.

Drugs are also wasted because of inappropriate and over-prescription, and noncompliance by patients. Efforts to involve prescribers in using standard treatment schedules and to inform patients about the proper use of drugs could result in improved efficiency.

Africa has special characteristics in its landuse pattems. population density, and road infrastructure that affect the distribution of drugs. Counterfeit drugs and difficulties in financing essential drugs are also serious problems. The advent of AIDS has presented new challenges in the provision of essential drugs.

Thc PRE Working Paper Serics disseminates the findings of work under way in the Bank's Policy, Research. and External Affairs Complex. An objectivc of the scries is to get thesc findings out quickly, even if presentations are Iess than fully polished. The findings, interprctations, and conclusions in these papers do not necessarily represcnt official Bank policy.

Produced at the PRE Dissemination Center
pending on i) how land titles are granted and ii) the extent to which the program merely formalizes and secures existing land rights, versus giving women greater ownership and control over household land.

If land titling is done in a way that increases female control over household plots, we expect a negative impact on fertility due to various mechanisms. Following the bargaining framework, we can consider that women who are granted property rights benefit from an increase in bargaining power in the household, and therefore can act on their fertility preferences (Field, 2003; Bose and Das, 2023). Given that women’s desired family size is smaller than men’s desired family size in most developing settings, we can therefore expect a reduction in fertility. In addition, Galiani and Schargrodsky (2010) find that a law allocating land titles to occupants of a poor suburban area of Buenos Aires—which were awarded to both the household head and to his/her spouse—translated into a 20% reduction in the number of offspring in the households. With formalized land rights, poor couples gained a secure saving instrument which reduced the need to use children as future insurance. By protecting families’ long-term access to their home and land, and possibly also increasing access to credit, the reform may also have further reduced the old-age-security motive for fertility. However, if the land titling is done in a way that does not give women greater control or ownership over land, but simply secures the male household heads’ land rights, women might be incentivized to have a son in order to secure land tenure in case of widowhood. Since customary inheritance regimes typically give sons, but not wives, the ability to inherit land, having a son is therefore the only way to make sure she will benefit from the land newly formalized in case of widowhood.

# **3 Data and Methodology**

This paper uses data from six impact evaluations (IEs) conducted by the World Bank’s Africa Gender Innovation Lab (GIL) between 2009 and 2018. Three of the evaluations examined the impacts of programs aimed at increasing female entrepreneurs’ profits through business skills trainings, while the other three focused on land titling programs geared towards strengthening household property rights and asset ownership. These IEs were selected from amongst a larger set of completed GIL IEs based on the following inclusion criteria: (i) the intervention did not include a women’s empowerment component and focused only on income and assets, (ii) the intervention generated a significant, positive effect on women’s income, profits or asset (land) ownership, (iii) the time interval between intervention and follow-up survey was at least 12 months and (iv) the follow-up survey included variables on pregnancy or children. All six IEs had income or wealth as primary outcome variables, and although data on other potential outcomes (e.g., standard measures of bargaining power) were collected, the IEs found either no or limited impacts in these areas, allowing for a clean identification of mechanisms (Campos et al., 2017; Goldstein et al., 2018; Alibhai et al., 2019; 9