rafmacalaba/datause-encoder-data huggingface dataset:
# **Figure 10: Public availability of supervisory reporting**

**a. Bank regulators/supervisors required to make public formal enforcement actions (% of respondents answering Yes)**

**b. Supervisors require banks to publicly disclose all fines and settlements resulting from non-compliance with regulations (% of respondents answering Yes)**

Source: Waves 4 and 5, BRSS.

Note: Off-shore financial centers are excluded from the calculations. DEV are developing countries. The number of countries for which we have a response for the specific item/question for both rounds appears in parentheses. * next to the number of countries represents a statistically significant difference in the mean values of a regional group in the two reference years at the 10% level using a two-tailed test.

Overall, we conclude that market discipline may have declined somewhat because of weaker incentives to monitor bank risk-taking. Deposit insurance coverage has increased and has also become more generous, especially for high-income OECD countries. This has likely encouraged banks – especially large banks – to take on excessive risk. Moreover, the information set available to assess the risk profile of banks did not improve significantly between BRSS round 5 and round 4.

# _2.3 Supervisory monitoring_

The GFC spurred debates about the adequacy of supervision in leading up to and the response to the crisis. On the one hand, the regulatory process has produced several reforms to address the issues uncovered by the crisis. The supervisory agencies, on the other hand, have seen the burden of their task increase because of an evolving, increasingly complex banking business that they now need to oversee. The BRSS responses summarized below show that, although there have been notable increases in the number and complexity of regulations after the crisis, there has not been a corresponding increase in supervisory powers 19
Policy Research Working Paper 6584

# **Abstract**

Using nationally representative household survey data from five countries—three from South Asia (Bangladesh, Pakistan, and Nepal) and two from Sub-Saharan Africa (Tanzania and Uganda)—this paper conducts a systematic assessment of the correlation between various measures of household food security and nutritional outcomes of children. The analysis, following the universally accepted and applied definition of food security, is based on some of the most commonly used indicators of food security. The results show that the various measures of household food security do appear to carry significant signals about the nutritional status of children that reside within the household. This result holds even after the analysis controls for a wide array of other socio-economic characteristics of the households that are generally also thought to be associated with the quality of child nutrition. If using these food security indicators as proxy measures for the underlying nutritional status of children is of some interest, then the results show that simple, cost-effective, and easyto-collect measures, such as the food consumption score or the dietary diversity score, may carry at least as much information as other measures, such as per capita expenditure or the starchy staple ratio, which require longer and costlier surveys with detailed food consumption modules. Across five different countries in South Asia and Africa, the results suggest that the food consumption score, in particular, performs extremely well in comparison with all other measures from the perspective of nutritional targeting as well as for monitoring nutritional outcomes.

This paper is a product of the Poverty Reduction and Equity Unit, Poverty Reduction and Economic Management Network. 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 stiwari@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
CÔTE D’IVOIRE’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE Compared with many other African countries, Côte d’Ivoire has relatively well-developed infrastructure backbones. It has a recognizable national grid for power and a national ICT backbone (figure 3). The northern regions of the country, despite having lower population densities than the rest of the country, are connected via backbones with the rest of the country. Côte d’Ivoire’s infrastructure backbones (including road, rail, power, and ICT) are generally integrated with those of neighboring Burkina Faso, but not with those of the neighboring coastal countries of Ghana and Liberia. However, the key road artery to Burkina Faso has deteriorated to poor condition.

This report begins with a review the main achievements and challenges in each of Côte d’Ivoire’s major infrastructure sectors (table 1). Thereafter, the financing of Côte d’Ivoire’s outstanding infrastructure needs will be discussed.

**Table 1 Achievements and challenges in Côte d’Ivoire’s infrastructure sectors**

||Achievements|Challenges|
|---|---|---|
|Air transport|Good airport infrastructure|Improving safety and security standards|
|ICT|Highly competitive mobile market with very high<br>levels of penetration|Establishing competitive access to submarine cables<br>Extending GSM signal and Internet coverage into rural<br>areas|
|Ports|Port of Abidjan has the potential to be a<br>regional maritime hub|Expanding capacity to deal with traffic growth Moving ahead<br>with institutional reform|
|Power|Well-developed power system and established<br>regional power exporter<br>Longstanding and successful experience with<br>private participation|Expanding generation capacity to improve reliability of<br>power supply<br>Addressing growing financial shortfall due to under-pricing<br>of power|
|Railways|The rail concession (SITARAIL) has boosted<br>traffic and performance|Rebalancing financial structure of the railway concession<br>Finding alternative funding for rehabilitation backlog|
|Roads|Second generation road sector institutional<br>reforms are in place|Securing adequate funding for road maintenance and<br>rehabilitation|
|Irrigation||Expanding irrigated area and rehabilitating abandoned<br>perimeters|
|Water and sanitation|Longstanding and successful ―affermage‖<br>(lease contract) has expanded access and<br>boosted performance|Adjusting tariffs to stem growing hidden costs of utility<br>Raising access to improved sanitation|

Source: AICD.

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Where ��� is the time spent by mother � at time � in a given activity (housework, paid work, child needs or sleep), the vector ��� is a set of her observable characteristics, the terms �� and �� are indicator variables for rounds 3 and 4 of the LEAPS survey. The coefficient �� captures the effect of the program one year after program implementation and the coefficient �� captures the effect of the program two years after program implementation. Given that I estimate this relationship using the subsample of eligible households in both treatment and control districts, these two coefficients represent the intent-to-treat effect of the program. The term �� reflects an individual fixed effect and incorporates the influence of time-invariant regressors – measured and unmeasured – on mother’s time use.<sup>15</sup>

# **c. Results**

In columns 1 and 2 of Table 5, I first examine the extensive margin – whether the fraction of mother’s who report participating in housework changes differentially across treatment and comparison samples. I compare mothers from households with eligible girls in the treatment district with mothers from households with eligible girls in the comparison districts. Column 1 ignores the availability of panel data and presents results from pooled ordinary least squares (OLS) regression. Column 2 allows for a fixed effect at the level of the mother – the unit of analysis in this table. In both cases there is no difference over time in the fraction of mothers who report spending time in household work when one compares households with eligible children in the treatment district and the comparison districts. The mean level of participation in housework at baseline is 97 percent. This suggests that any differences in the intensive margin –

> 15 This fixed effects difference-in-differences estimator is an improvement over the difference estimator employed in Skoufias and Parker (2001) since I am now able to adjust for pre-program differences directly and am able to examine if the effect persists.

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# Rapid Urban Growth in Flood Zones: Global Evidence since 1985

**Jun Rentschler**<sup>**1**</sup> **, Paolo Avner**<sup>**1**</sup> **, Mattia Marconcini**<sup>**2,3**</sup> **, Rui Su**<sup>**1**</sup> **, Emanuele Strano**<sup>**3**</sup> **, Louise Bernard**<sup>**4**</sup> **, Capucine Riom**<sup>**4**</sup> **, Stephane Hallegatte**<sup>**1**</sup>

1 The World Bank, Washington DC, USA 2 German Aerospace Center (DLR), Munich, Germany 3 Mindearth, Biel, Switzerland 4 London School of Economics and Political Science, London, UK

**Key words:** Urbanization, floods, exposure, adaptation, climate change **JEL classification:** R12, Q54, O18

**Acknowledgments:** This study has benefited from feedback and inputs by Richard Damania, Vivien Deparday, Keith Garrett, Caroline Gevaert, Niels Holm-Nielsen, Brenden Jongman, Nancy Lozano Gracia, Srilakshmi Ramesh, Lucy Southwood, and Michalis Vousdoukas. It was supported by the Global Facility for Disaster Reduction and Recovery (GFDRR).
# _Outputs: Relative Trends Inside and Outside Millennium Villages_

_Chronic malnutrition_ . Figure 7 shows that in all three countries, stunting rates for small children fell in the rural areas of the regions in which the Millennium Villages are located. In Ghana, stunting declined at the MV intervention site at the same rate as in the surrounding region. In Kenya and Nigeria, stunting fell much more at the MV intervention site than in the surrounding region.

_Gross primary school attendance_ . Figure 8 shows different trends in gross primary school attendance across the three countries. In the regions where the MVs are located, attendance increased greatly in Kenya and Ghana, while dropping in Nigeria. At the MV intervention site in Kenya, attendance rose somewhat more rapidly than in the surrounding region. At Ghana’s MV site, attendance rose less than in the surrounding area. Finally, at Nigeria’s MV site, attendance rose while attendance in the surrounding area was nearly flat.<sup>10</sup> _Mobile phone ownership_ . Mobile phone ownership has skyrocketed across all three countries, as Figure 9 shows. In Kenya and Ghana, mobile phone ownership rose about as much at the MV intervention sites as in the surrounding areas. In Nigeria, it rose somewhat more at the MV site than in the surrounding area.

_Malaria prevalence_ . MVP (2010c) documents declines in malaria prevalence among all ages, from 50 to 8 percent in Sauri, 28 to 13 percent in Pampaida, and 15 to 6 percent in Bonsaaso. Malaria tests are not administered as part of the DHS, so definitive figures on malaria trends are not available. Thus we cannot construct a figure for malaria like the other figures. However, there is suggestive evidence that malaria rates have dropped in Kenya overall, where the MVP site decline is greatest. First, in the DHS data, the percentage of children under 5 reporting fever during the last two weeks—a very rough indicator of malaria prevalence<sup>11</sup> —dropped from 40.6 to 23.7 percent nationally and from 48.5 to 24.8 percent in rural areas of Nyanza, where Sauri is

> 10 The gross attendance ratio is difficult to interpret, and a high ratio is not unambiguously positive. Ratios above 1 (such as those for Kenya and Ghana) indicate the presence of underage and/or overage children—that is, primary school attendees outside the age range 6 to 11—and an increase in grade repetition can increase the ratio.

> 11 For example, Ashraf, Fink, and Weil (2010) use changes in DHS data on fever occurrence as a rough proxy for changes in malaria morbidity in Zambia.

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take each gender into account separately, and for the consumption regressions. We do not face a weak instrument problem, as indicated by the results from the weak instruments test (Kleibergen-Paap). In addition, the coefficient estimates for the instrumental variables have the expected signs. The incidence of covariate violent shocks is more likely in municipalities with higher land concentrations and no presence of the native population during colonial times—that is, in what was previously frontier land. Additionally, more isolated rural districts with lands of lesser quality have a higher likelihood of experiencing a covariate violent shock.

Before describing the effects of violent shocks on time use, labor market attachment and aggregate consumption, let us discuss the evidence for the exogeneity of our chosen instruments. Because we have two variables to instrument violent shocks, the system is over-identified, allowing us to perform the relevant exogeneity tests. We report the Hansen test. For time use, displayed in Tables 18 to 20, the Hansen test suggests that the instruments are exogenous at standard confidence levels, and therefore that our instrumental variables are exogenous. For formal labor markets, displayed in Table 21, the instruments appear exogenous for both categories. Finally, for aggregate consumption, reported in Table 22, the Hansen test shows we cannot reject the hypothesis of endogenous instruments. Given the results discussed above, we are confident that our chosen instruments are both relevant and exogenous, and hence we are able to identify the local effect of violent shocks.

Table 18 presents the OLS and IV results for the effect of a violent shock on the time use of a household head and spouse. When we use OLS as an estimation strategy, it seems as if the violent shock has no effect on time use for any of the categories. However, when we instrument, we find that as a response to violent shocks, households decrease their time spent on farm work and increase their labor supply for off-farm nonagricultural activities as well as leisure, domestic chores and taking care of children. An increase of one standard deviation on the incidence probability of a conflict shock decreases the time spent on the farm by 0.12 standard deviations, while time spent in 27
the existence of clear appeal procedures, etc.). The indicators are taken from a thorough review by the OECD of available country-level information on the capacities and procedural requirements of customs and other agencies that oversee trading activities. The OECD indicators have been usefully employed in studies of the impact of policies on trade flows and implied trade costs.<sup>5</sup> Our innovation is to estimate their impact on outcomes at the border. This allows a better understanding of the likely effects of trade facilitation policies and other variables on border outcomes.

The estimation of these impacts is complicated by two key features of the data. The first issue is that the main outcome variable, the reported number of days necessary to clear customs, is a discrete variable that typically takes low values including ‘1’. Our interest is actually in a latent variable, time in customs, but the data are only reported in units of days. We adopt a discrete time transition model that allows us to estimate the effects of policy and other variables on a latent continuous variable representing time. The second issue is that the OECD trade facilitation indicators, our primary independent variables of interest, have many missing observations. Moreover the missing data do not occur randomly; missing policy data are most common in the part of the sample in which our interest is highest, in developing countries. To address the second issue we implement multiple imputation methods that have been developed for use in situations like ours. The discrete time transition model and multiple imputation procedures can be implemented jointly, and we do so.

The OECD data group into 12 policy bundles the vast array of policies and procedures used by border agencies around the world. Of these bundles, we find two that are linked, in a statistically significant manner, to lower reported values of time in import customs: indicators of _Good governance and impartiality_ and _Automation_ . The 12 indicators are important collectively, but the model suggests that these two policy measures affect the days-in-customs variable individually, even after controlling for other policy and non-policy data. On the export side the results are a bit weaker. The _Good governance and impartiality_ variable is again important, although with somewhat lower levels of statistical confidence than in the case of imports. The significance of the coefficients on the Good governance indicator across specifications is notable because we include a sizable array of control variables, including the other 11 trade facilitation indicators as well as general measures of the quality of national governance. Good governance and impartiality in customs agencies seems to matter for private sector perceptions of the time required to clear customs.

> 5See Mo ̈ıs ́e et al. (2011) and Mo ̈ıs ́e and Sorescu (2013), respectively.

2
The authors test four different indicators as proxies of the port efficiency, including: (i) country specific port efficiency index from _The Global Competitiveness Report_<sup>10</sup> ; (ii) total square number of largest seaports by country, normalized by the product of exporting country’s population and area; (iii) GDP per capita of the exporting country; and (iv) the same infrastructure index as that used by Limao and Venables (2001). Their regression shows that all the four port efficiency indicators have significantly negative coefficients. The improvement in port efficiency leads to reduction of the transport costs. For other variables, the containerization ratio, directional imbalances and total liner import volume have negative coefficients, while distance and weight value have positive ones. The signs of the coefficients agree with the theoretical prediction.

Blonigen and Wilson (2008) adopt an innovative methodology to estimate the efficiency of major ports in the world including the United States. Using the port-to-port, HS 6-digit commodity based import statistics of the United States, this study explored the efficiency of trading partners’ ports by estimating the regression of port-to-port import charges on partner’s and U.S. port-specific fixed effects, as well as a explanatory variables. Their regression has portto-port U.S. import charges in HS 6-digit commodity codes, as the dependent variable; and the dummy variables of the partner’s and U.S. ports, the distance, weight, value per unit, containerization ratio, trade imbalances and some of the products of the variables, as independent variables.

The exporters’ port-specific dummy variables in the regression should reflect their fix-effect, i.e. the cost efficiency/inefficiency for each port of the trading partners with the ports in the U.S. Then, they test the estimated port efficiency measures by applying them to the regression of portto-port bilateral trade gravity model, as an explanatory variable, obtaining a significantly negative coefficient. This confirms that their estimated port efficiency measurements reflect the transport costs, which have an explanatory power on the bilateral trade.

> 10 _The Global Competitiveness Reports_ of the World Economic Forum publish every year the questionnaire survey results on various items related to the country’s competitiveness, including the port efficiency indicators to measure the quality of infrastructure of ports and airports. The indicators reflect more or less subjective views of the respondent executives in the countries, as they are asked to respond by assigning points on the efficiency in their countries.

13