rafmacalaba/datause-encoder-data huggingface dataset:
countries as well as emigrants returning and visiting family from high malaria settings could both impact malaria incidence. There are detailed case data available from Richard Toll district where each case was investigated and travel information was included on the infected individual based on survey data. Out of 161 cases, there are 9 cases where the traveler was from outside of Senegal, or only 5.59% of cases. The small impact of international migration likely arises from the fact that while some of Senegal's neighbors such as Mali have a higher malaria incidence (89 cases per 1000), the only international border near the pre-elimination districts studied here is Mauritania, which has a lower incidence rate than northern Senegal of only 0.4 cases per 1000. Nevertheless, future work could try to incorporate the impact of international travelers.

# 7 Conclusion

The paper quanties the negative externality of population movement on disease incidence and reversing gains in elimination in Senegal, and it proposes a cost-eective targeting strategy. This type of study is made possible by new big data collected by telecommunications companies making the measurement of short term movement possible and the initiative taken by the Ministry of Health to collect surveillance data on a monthly level for each health post. These data made it possible to study how short term movement into low-malaria areas increases incidence. The study nds that for each imported case of malaria per 1000, there are around 1.7 cases of malaria per 1000 reported at health post areas in the pre-elimination districts. Using these ndings, I calculate that implementing a policy in certain destination areas and targeting travelers from the most cost-eective districts during particular months results in the largest drop in cases (over 50% as many cases treated or averted as compared to the next best strategy). To our knowledge, this is the rst study to evaluate the cost eectiveness of dierent types of targeting schemes for malaria directed at travelers.

While the work here focuses on malaria, it is possible to implement this type of model 38
from establishing barriers to an efficient banking system by reducing I&R factors. However, as we have seen in the recent crisis, the inter-connectedness of the banking system and its capital allocation role, have been misjudged by banks and policy makers alike.

Therefore, the lower spreads in the U.S. might have been the result of underestimating the macro risk as well as the micro, or counterparty risk in the banking sector. Perhaps there was a structural problem or a miscalculation of the inter-connectedness between the banking sector (micro) and the economy in general (macro).

# **_5.5 Brazil and the BRIC Countries_**

Brazil consistently had higher micro spreads than the NIM of each BRIC country. Figure 12 shows that Brazil’s micro-factors in all years, except in 1996, are higher than the total spread in the other BRICs. Spreads in Brazil are unlikely to come down significantly unless the micro-factors are addressed. In absolute terms, macro spreads in Brazil are just a little higher than China’s macro-factors in line with their high growth rates and growth potentials.

We observe from Figure 12 that India had similar NIM spreads as Brazil in 1995 but by 2007 it had almost half the spreads as in Brazil. However, we detect that during the crisis in 2008 and 2009 spreads in India and Brazil converge. Perhaps banks in both countries measured risk in similar ways since both countries are part of the BRICs bloc and their growth is perceived to move in tandem.

## **Figure 12. BRICs NIM and Brazil’s I&R**

<!-- Start of picture text --> 18<br>16<br>14<br>12<br>10<br>8<br>6<br>4<br>2<br>0<br>1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009<br>BRAZIL NIM CHINA_NIM INDIA_NIM RUSSIA_NIM BRAZIL I&R (Micro)<br>Percentage points<br><!-- End of picture text --> _Source_ : Authors’ calculations based on BankScope data Furthermore, we observe that Brazil’s macro-factors play a smaller role in 2009 (Figure 13a) than in 2008 (Figure 13b), but not significantly. At the same time, China’s macro and micro-factors remained more or less constant in 2008 and 2009. The crisis did not seem to affect significantly spreads in China, perhaps because the Chinese government had tighter control over the financial sector and the overall 25
Policy Research Working Paper 5969

# **Abstract**

Historically, development banks have been an important instrument of governments to promote economic growth by providing credit and a wide range of advisory and capacity building programs to households, small and medium enterprises , and even large private corporations, whose financial needs are not sufficiently served by private commercial banks or local capital markets. During the current financial crisis, most development banks in Latin America, followed by Asia, Africa, and Europe, have assumed a countercyclical role by scaling up their lending operations exactly when private banks experienced temporary difficulties in granting credit to the private sector. Despite the importance of development banks during crisis and non-crisis periods, little is known about them. This survey examines how development banks operate, what their policy mandates are, what financial services they offer, which type of clients they target, how they are regulated and supervised, what business models they have adopted, what governance framework they have, and what challenges they face. It also examines the countercyclical role played by development banks during the recent financial crisis. This survey is based on new data that have been collected from 90 national development banks in 61 countries.

This paper is a product of the Financial Systems Practice, Financial and Private Sector Development Vice Presidency. 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 jdelunamartinez@worldbank.org or cvicente@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
# **Figure 3**

Argentina versus Chile: 10-year Difference in Social Indicators <mark>Panel A. Changes in Unemployment Rate</mark> <mark>Panel B. Distribution for Unemployment Rate</mark> <!-- Start of picture text --> 20 0.45<br>15 0.40<br>10 0.35<br>0.30<br>5<br>0.25<br>0<br>0.20<br>-5<br>0.15<br>-10<br>0.10<br>-15 0.05<br>-20 0.00<br>Argentina Chile Standarized 10-year Difference in Unemployment Rate<br>Argentina Chile<br> Panel C. Changes in Monetary Poverty Panel D. Distribution for Monetary Poverty<br>40 0.45<br>30 0.40<br>20 0.35<br>0.30<br>10<br>0.25<br>0<br>0.20<br>-10<br>0.15<br>-20 0.10<br>-30 0.05<br>-40 0.00<br>Argentina Chile Standarized 10-year Difference in Monetary Poverty<br>Argentina Chile<br> Panel E. Changes in 1/HDI Panel F. Distribution for 1/HDI<br>0.5 0.45<br>0.4 0.40<br>0.3 0.35<br>0.2<br>0.30<br>0.1<br>0.25<br>0<br>0.20<br>-0.1<br>0.15<br>-0.2<br>0.10<br>-0.3<br>0.05<br>-0.4<br>-0.5 0.00<br>Standarized 10-year Difference in 1/HDI<br>Argentina Chile Argentina Chile<br>Density<br>(percentage points)<br>Absolute Change in Unemployment Rate<br>-6.0 -5.5 -4.9 -4.4 -3.9 -3.4 -2.8 -2.3 -1.8 -1.2 -0.7 -0.2 0.3 0.9 1.4 1.9 2.5 3.0 3.5 4.0 4.6 5.1 5.6 6.1 6.7<br>Density<br>(percentage points)<br>Absolute Change in Monetary Poverty Rate<br>-18.7 -17.2 -15.6 -14.1 -12.5 -11.0 -9.5 -7.9 -6.4 -4.8 -3.3 -1.8 -0.2 1.3 2.9 4.4 5.9 7.5 9.0 10.6 12.1 13.6 15.2 16.7<br>Density<br>Absolute Change in 1/HDI<br>-10.0 -9.3 -8.5 -7.7 -7.0 -6.2 -5.5 -4.7 -3.9 -3.2 -2.4 -1.6 -0.9 -0.1 0.6 1.4 2.2 2.9 3.7 4.5 5.2 6.0 6.7 7.5 8.3 9.0 9.8<br><!-- End of picture text --> Notes: Poverty line of 5.50 dollars per person a day (2011 PPP). For panels B, D, and F, we fitted a standard normal distribution taking the first two moments (mean and standard deviation) of the 10-year differences in each social indicator. Sources: Authors’ estimations based on SEDLAC (CEDLAS and World Bank), Human Development Report Office (United Nations), and WEO (October 2018).

19
OIC countries need to develop a regulatory and supervisory framework that supports wide financial inclusion based on sound risk management and with sufficient consumer protections. During this process, governments and regulators need to take the lead in supporting improvements in access to finance, especially through _Shariah_ -compliant financial tools, displaying the _Leadership_ called for in the G20 Principles (See Box 4). Financial inclusion, especially Islamic financial inclusion, should be considered as a goal alongside prudential regulation and financial system stability. The CGAP and World Bank Financial Access survey (2010) of financial regulators worldwide found that regions that include financial access in their strategies and mandate their financial regulators to carry such agendas are also the countries that reform the most. Regulators with a financial inclusion strategy are more likely to have more financial inclusion topics under their purview and more resources and staff dedicated to working on these matters.<sup>32</sup>

**Practical measures that can be taken by regulators** (as has been the case in Indonesia and Pakistan) include: licensing Islamic banks, supporting centers for training and certification on Islamic financial operations to staff and managers of financial service providers, and developing guidelines setting out requirements for licensing and appointment of _Shariah_ advisers to rule on _Shariah_ compliance. The political climate for Islamic finance also affects investor and lender decisions about whether to offer _Shariah_ -compliant products, and acts as an incentive or disincentive to its growth.

In addition, consumer protection is also increasingly important as access increases, so that new customers, and existing customers with access to new services, can take well informed decisions about how best to manage and use Islamic financial services. In some countries, customers stay away from Shariah-compliant services because of lack of education about authenticity and credibility of products. Consumer protection can help remove such perceptions and can lead to enhanced inclusion. Therefore, it is essential that consumer laws and regulations are developed and put in place: i) to protect against unfair or deceptive practices ii) to improve transparency through disclosure and plain language requirements for products and pricing, in a way that allows consumers to easily access to _Shariah_ -compliant products and services, and iii) to establish a low cost, efficient, and fair mechanism for resolving customer complaints and disputes.

> 32 (Pearce 2010)

43
use associations as a tool to gather information about alternative service providers in presence of uncertainty. It may also indicate that some individuals – the more educated and the ones who are members of associations – tend to have a greater ‘disinclination’ to accept bribery and therefore are more likely to decide not to seek a service in presence of corruption<sup>15</sup> . These findings are robust to the introduction of regional control dummies, as shown in Table 6.3, and to agency dummies (not reported).

The household’s decision of not seeking a service in a public agency when needed may however depend on the nature of the service sought, and more specifically on whether there exists an alternative, private provider for the same service. Thus, the determinants of the discouragement effect will depend on whether state agencies can act as monopoly provider for the public service or not. To check this hypothesis, we divide the 13 public agencies depending on whether they are monopoly providers of a service or not. On the one hand, National Bank, National Tax Administration, local revenue services, local Water Companies, the local motor vehicle administration, the immigration office, public registry, National Police, the National Registry for Identification Cards are classified as monopoly providers. On the other hand, public notary, public schools, public hospitals and Social Security are classified as non-monopoly providers, since there are private providers for these services.

We next define the following dependent variables: MONOPOLY_DISC=1 if a household is discouraged to use a service in at least one institution that has the monopoly to provide the service, and equal zero otherwise.

NON-MONOPOLY_DISC =1 if a household is discouraged to use a service in at least one institution that do NOT have the monopoly to provide the service, and equal zero otherwise.

The regression results can be found in Table 6.4. The variables female, age, number of dishonest institutions and knowledge to report a corrupt act now only matter for discouraged in monopoly-institutions but not for discouraged in non-monopoly-institutions. Member of an association is significant for both monopoly and non-monopoly institutions. When we include in the regression the regional dummies (columns 9 and 10) the coefficients are significant. Thus, governance features matter more when users interact with agencies that have a monopoly of the service they provide than with agencies for which users have alternatives.

<Table 6.4 around here>

# **7. EXPLORING THE SUPPLY SIDE OF SERVICE DELIVERY: PUBLIC AGENCY LEVEL ANALYSIS**

As we have emphasized throughout this paper, access to publicly provided services is a function of the quality of governance in a country. The previous section has focused on the demand side of service delivery trying to link bad governance to the individual decision of not to seek a public service. The evidence suggests that while individual characteristics may affect this decision, governance also increases the probability that an individual user will be

> 15 We thank John Helliwell for suggesting the latter interpretation of this result.

14
**Table 2 – Individual Panel Short-Term Models**

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
|VARIABLES|Urban,FE|Urban,RE|Rural,FE|Rural,RE|
|gdp_real_index|-0.0268**|-<br>0.00869***|-0.0342***|0.00453**|
||(0.0124)|(0.00213)|(0.00976)|(0.00177)|
|Age|0.820***|0.560***|0.469***|0.315***|
||(0.0960)<br>-|(0.00933)<br>-|(0.0731)<br>-|(0.00588)<br>-|
|age squared|0.00834***|0.00742***|0.00182***|0.00362***|
||(0.000892)|(0.000118)|(0.000591)|(6.62e-05)|
|Married|-1.499***|-5.696***|-1.882***|-2.784***|
||(0.423)|(0.158)|(0.371)|(0.0901)|
|ageXmarried|0.0229**|0.0551***|0.0344***|0.0619***|
||(0.0104)|(0.00367)|(0.00791)|(0.00211)|
|head of household|0.843|0.645***|0.578|0.109**|
||(0.722)|(0.0628)|(0.388)|(0.0525)|
|primary education|0.126|0.268***|0.0440|-0.694***|
||(0.0907)|(0.0480)|(0.0942)|(0.0586)|
|secondary education|-1.845***|-4.525***|-2.403***|-3.942***|
||(0.279)|(0.121)|(0.858)|(0.327)|
|ageXsecondary education|0.0541***|0.154***|0.0768**|0.116***|
||(0.00839)|(0.00358)|(0.0317)|(0.0122)|
|tertiary education|1.296***|4.324***|1.707**|3.252***|
||(0.166)|(0.0855)|(0.846)|(0.343)|
|vocational education|2.083***|5.617***|2.189***|2.336***|
||(0.140)|(0.0710)|(0.510)|(0.255)|
|household head has general education|-0.0585|-0.185***|0.167|-0.576***|
||(0.0847)|(0.0431)|(0.117)|(0.0631)|
|spouse is active|0.723***|1.132***|0.428***|1.157***|
||(0.127)|(0.0861)|(0.0569)|(0.0380)|
|household has children under six y.o.|0.124|-0.253***|0.0918|0.209***|
||(0.113)|(0.0432)|(0.0840)|(0.0310)|
|household has children in age 7-17 out of school and<br>|||||
|work|0.355***|0.680***|0.0682|0.433***|
||(0.0819)|(0.0529)|(0.0463)|(0.0277)|
|household has more than 1/3 of other females inactive|-1.106***|-0.505***|-1.506***|-1.880***|
||(0.0816)|(0.0460)|(0.0628)|(0.0430)|
|number of over 60 y.o. inactive|-0.942***|-0.354***|-1.341***|-1.254***|
||(0.0735)|(0.0315)|(0.0443)|(0.0271)|
|Constant||-10.74***||-6.919***|
|||(0.308)||(0.242)|
|Observations|19,262|205,564|31,298|140,154|
|Number of indcode|9,631|102,782|15,649|70,077|
|Source LFSs 2007-2011. Conditional logit fixed effect:|dependent variab|le: FLP (1: in t|he labor force;|0: otherwise).|
|Standard errors in parentheses (*** p<0.01, ** p<0.05, *|p<0.1).||||

As a further test, we compare cross-section estimations between LFS and HBS data for the only year when these two surveys have been both administered. Results are shown in Table 3. As can 15
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35
**be** uignlfIcanto,n for small agricultural **based** economies.? This should not be a surprise. In a developing economy, tax collections will generally be significant in modern manufacturing relative to traditional sectors, and business Income taxes will generally be greater than personal taxes.0 Thus, to the extent that foreign investment is concentrated in the modern sector, the proportion of business related Income taxes paid by foreign investors should be significant.

Finally, countries are aware of the potential effect that interjuriedictional variation in taxation has on both domestic and international investment within each country. Tax sparing provisions have become more common in tax treaties between the capital exporters and importers.' The effect of such provisions is to preserve the tax incentives for foreign Investors which would be nullified in other circumstances. In addition, countries are increasir.gly aware of what has been labelled "tax induced capital flight", where tax incentives or low levels of taxation create an incentive for domestic nationals in one country to Invest in another.'<sup>0</sup> The recent controversy about the effect of US tax rules on "capital **flight"** from Latin America Is one example of this phenomenon." Under US tax rules non-residents are not subject to US tax on Interest from deposits held In US banks." Latin American countries, many of which use the source principal (see below), claim that this exemption has induced firms and individuals to 7. This statement is based on a sample of income tax returns collected as part of the Malawi tax reform effort.

8. This is true for a variety of reasons including the adoption of modern bookkeeping techniques in the modern sector, the relative ease of tracing transactions, the low level of personal income and the relative small number of taxpayers in the modern sector.

9. Tax sparing is a method where the home country of a foreign investors allows a credi for taxes computed without incentives. This allows the foreign country to provide effective incentives for foreign investments. In effect, the home country allows a credit for foreign taxes which are never paid. The United States is an exception to this trend since the United States does not allow tax sparing provisions in any of its treaties.

10. H. David Rosenbloom has suggested to me that "capital flight" is largely a pejorative term void of any meaningful content. What one country sees as "flight" is seen as increased investment in another. Whether such outcomes are the result of an efficiently operating market and or a cost may be one of perspective.

11. See McLure (1987) for further development and analysis. Also see Karzon(1983) for a detailed development of international tax evasion.

12. Under prior US law such income was defined to be non-US source. In 1986, such income was defined to be US source but was then explicitly exempted from taxation.

**-3-**
21 <!-- Start of picture text --> RCEP, Tariffs imposed RCEP, NTBs imposed<br>China<br>Southeast Asia<br>India<br>Laos<br>Cambodia<br>Indonesia<br>Philippines<br>Korea<br>Thailand<br>Vietnam<br>Singapore<br>New Zealand<br>Malaysia<br>Japan 2015 2030<br>Brunei Darussalam<br>Australia<br>0 2 4 6 8 10 0 5 10 15 20<br><!-- End of picture text --> Source: Authors’ estimates

**Figure 14. Trade barriers imposed by FTAAP countries before and after trade liberalization to imports from member states, trade weighted averages in %**

<!-- Start of picture text --> FTAAP, Tariffs imposed FTAAP, NTBs imposed<br>Russion Federation<br>China<br>Indonesia<br>Philippines<br>Korea<br>Thailand<br>USA<br>Vietnam<br>Singapore<br>New Zealand<br>Malaysia<br>Japan<br>Brunei Darussalam<br>Australia<br>Peru<br>Mexico<br>2015 2030<br>Chile<br>Canada<br>0 2 4 6 8 10 0 5 10 15 20<br><!-- End of picture text --> Source: Authors’ estimates