rafmacalaba/datause-encoder-data huggingface dataset:
Wara, Michael (2008), Measuring the Clean Development Mechanism’s Performance and Potential. _UCLA Law Review_ , 55, 1759-1803.

WBGU (2003), Climate Projection Strategies for the 21<sup>st</sup> Century: Kyoto and Beyond. Berlin: German Advisory Council on Climate Change.

Wheeler, David and Mody, Ashoka (1992), International Investment Location Decisions: The Case of US Firms. _Journal of International Economics_ , 33, 57-76.

World Bank (2006a), Investment Framework for Clean Energy and Development. Washington DC: The World Bank.

World Bank (2006b), Where is the Wealth of Nations? Measuring Capital for the 21<sup>st</sup> Century. Washington DC: The World Bank World Bank (2009), World Development Report 2010: Development and Climate Change. Washington DC: The World Bank.

Yang, Dean (2008), Coping With Disaster: The Impact of Hurricanes on International Financial Flows, 1970-2002. _The B.E. Journal of Economic Analysis and Policy_ , 8, article 13.

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Xu, B. (2000), Multinational Enterprises, Technology Diffusion, and Host Country Productivity Growth. _Journal of Development Economics_ , 62, 47 7-493.

35
<!-- Start of picture text --> Social gaps Rank correlation Cutoff values<br>Social Sustainability Index by cutoff and scenario<br>Second-order stochastic dominance Metrics coefficient k = 33% k = 50% k = 75%<br>Spearman 0.96*** 0.96*** 0.95***<br>H<br>Kendall tau-b 0.87*** 0.86*** 0.84***<br>Spearman 0.98*** 0.95*** 0.64***<br>A<br>Kendall tau-b 0.93*** 0.82*** 0.52***<br>Spearman 0.97*** 0.97*** 0.95***<br>M0<br>Kendall tau-b 0.89*** 0.9*** 0.84***<br>0 20 40 60 80 100<br> Cutoff k (relative scale) ***p<0.01, **p<0.05, *p<0.1<br>Baseline Alternative<br>South Africa<br>C10.1. FOSD: Counting Vector C10.2. Dominance Analysis<br>Counting vector CCDF by scenario Difference between counting vector CDF curves<br>First-order stochastic dominance (α=0)<br>0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1<br>Counting vector (relative scale) Counting vector (relative scale)<br>Baseline Alternative Confidence interval (95 %) Estimated difference<br>C10.3. SOSD: Social Sustainability Index C10.4. Rank correlations<br>Social gaps Rank correlation Cutoff values<br>Social Sustainability Index by cutoff and scenario<br>Second-order stochastic dominance Metrics coefficient k = 33% k = 50% k = 75%<br>Spearman 0.92*** 0.97*** 0.95***<br>H<br>Kendall tau-b 0.78*** 0.89*** 0.83***<br>Spearman 0.93*** 0.92*** 0.9***<br>A<br>Kendall tau-b 0.83*** 0.78*** 0.72***<br>Spearman 0.98*** 0.93*** 0.95***<br>M0<br>Kendall tau-b 0.94*** 0.83*** 0.83***<br>0 20 40 60 80 100<br> Cutoff k (relative scale) ***p<0.01, **p<0.05, *p<0.1<br>Baseline Alternative<br>.4<br>.3<br>.2<br>.1<br>Social Sustainability Index<br>0<br>.2<br>1<br>.8<br>.1<br>.6<br>CCDF<br>.4 Difference<br>0<br>.2<br>0 -.1<br>.4<br>.3<br>.2<br>.1<br>Social Sustainability Index<br>0<br><!-- End of picture text --> _C11. Change in the indicators included for each dimension, one indicator removed at a time. Baseline scenario: All indicators included. Alternative scenario: Perception of safety indicator removed (weights within the Social Cohesion dimension were scaled from 6.25% to 8.33% so all weights add up to 1)._ Peru C11.1. FOSD: Counting Vector C11.2. Dominance Analysis 59
- 60 -

carrled out as between fuels if the data were available. In **essence** this **is** the same approach as the power system analysie of Plnto and Besant-Jones. In his econometric study of manufacturing lndustry ln Mexico, Sterner uses the translog cost function to a time series of cross sections for various industrles. Not only were the partial price elasticities of substltutlon calculated but also those between energy and other lnputs. Sterner compares his elastlcitles wlth others for developing countries and finds that **his** own prlce elastlcitLes (at mean shares) are similar to those for industrialized countries but show a bigger difference against the values obtained by a varlety of methods for developing countries. The absence of a standardized approach means that few general lessons can be drawn. More research, using Sterner's methodology on other developing countrles is still needed.

Recently, new developments ln functional form specifLcation have appeared and these are especially valuable sinethey offer comparisons between model forms and between studles. Considine 119891 developed a logistic fuel share model, as explained in section 3, whlch has the advantage of imposing global concavity (although at the possible price of abandoning global symmetry). Its other distinctive feature La the stabilLty of the elasticities with respect to fuel price changes. The translog function yields very different elasticities at different fuel shares (which is revealed by Griffin and Pindyck's results where the single model is evaluated at indlvidual country shares). Hence lf fuel prices change strongly then so will the elasticities at those prices. Considine defines a subsector "stationary fuel consumption" which is mainly the industrial sector less those subsectors where fuels are feedstocks (petrochemicals, plastLcs, steel). The data is from the U.S. for the period 1970 to 1985 and thus allows for some of the effects of the two oil shocks on fuel choice. The partial price elasticities for both the translog and logistic functional forms are calculated both at the mean shares for the period and for five year intervals. The effects of regulation are also incorporated in both models. Tables 4.7 and 4.8 give the own and cross price elastlcities for the 2 models for 1970 and 1985 prices.
|**Table2.3TheIMECAIndicatorSys**|**temforPM1**|**0 andOzon**|**e**|||
|---|---|---|---|---|---|
|_IMECApoints_|_100_|_200_|_300_|_400_|_500_|
|PMl0 [ig/m <sup>3 </sup>(dailyaverage)|150|350|420|500|600|
|Ozoneppm(daily1-hr.maximum)|0.110|0.232|0.355|0.477|0.600|
|_Source:_INE(April2000)athttp:///w|ww.ine.gob.m|x/dggia/ind|icatores.|||

Figure 2.2 shows the trend in the IMECA points between 1990 and 1999 for ozone and between 1995 and 1999 for PM1 O. Table 2.4 shows the number of days per year satisfying air quality standards.

**Figure 2.2 Daily Average Trends in the ZMVM for Ozone and PM10**

Ozone, daily average 1-hour maximum <!-- Start of picture text --> 400<br>350<br>300 - - _ _ _ _ _ _ _ _ _ _ - _ _<br>100 164. 1180 1652 173.2 169. -4 - 15.1 9<br>0<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999<br>-Maximum * Average -Minimum AQS <= 100 IMECA units<br>PM10, daily average<br>250<br>200 4_ __-_<br>E100Xf L -- 100.3 *98.6 - 102.8 1<br>50 l_l____ _. _<br>0<br>1995 1996 1997 1998 1999<br>-Maximum * Average -Minimum AQS <= 100 IMECA units<br><!-- End of picture text --> _Source: SMA (1999)._ _5_
of the unskilled wage range was insufficient for all but small families. It is worth noting that the lowest proportion of the poor associated witb very low wages (insufficient for three children) was found in those towns where there were fewest poor. As we discussed above, the specialized industries in these towns appears to have pushed wages up above the poverty line.

Widow headed housebolds, the old and the sick made up a far smaller proportion of the poor than of the extreme poor, that is of paupers. A table of poverty rates by ages constructed by Rowntree (1901, p.443) for York shows the same increase in old age as we saw for the pauper cycle in Figure 7, although not as dramatic. As with pauper rates, there was a bulge in poverty rates before age 15 with approximately 27% of working class children living in poverty. But whereas before we saw that most child pauperism was explained by single earner families, most child poverty occurred in large families where the chief earner was low paid.

The difference in the composition of the poor relative to that of paupers is explained by Rowntree's poverty line being drawn at a much higher level than some official line below which people became paupers on relief. The poor as defined by Rowntree's poverty line included 16% of the people surveyed, while total pauper rates in ZnglanA and Wales at this time were at 2.2%.

Support for the view that the paupers represent the poorest of the poor can be found in Rowntree's own investigation of York in 1899. Rowntree divided the households into classes. The composition of the poorest class (those with a household incone eauivalent to less than 18s a week for a family with two adults and two to four children) looked much like the composition of pauperism. That is, 47% of its sembers were in widow or single parent headed 51
The aggregate consumption variable in the EMNV98 is described by Sobrado (2001) as a measure of wellbeing with a “unique set of desirable characteristics”. One advantage cited is that consumption information has proven to be more reliable than income data which are subject to error due to concerns about privacy and difficulties in measuring informal earnings. However, the problem is that neither of these variables takes account of heterogeneity in hours of market and domestic work that, as the following rankings by pcc indicate, is strongly evident in the data. Pcc may therefore fail to provide a reliable measure on which to base living standard comparisons, if domestic work is productive.

Table 5 presents a quintile ranking of individual records for which time use data are available. Column 1 lists the mean pcc in cordobas per annum (pa) in each quintile. Column 2 presents the data means for market hours of work pa for the full sample and

**Table 5     Quintile ranking of individual records by pcc pa**

||All<br>|All|Female|Child 6-14|
|---|---|---|---|---|
|Quintile|Pcc C$ pa|Market hrs|Market hrs|Market hrs|
||1|2|3|4|
|1|1465|637|275|250|
|2|2664|710|386|215|
|3|4100|758|433|210|
|4|6038|839|595|178|
|5|16306|976|770|135|
|Overall|6976|806|531|112|

column 3, for female hours only.<sup>55</sup> The final column shows the average hours worked by children aged 6-14 years. From the quintile means in columns 2 and 3 it is clear that the rise in average hours with pcc is largely a result of an increase in female hours across the ranking. Children work longer on average in the lower quintiles but this does not offset the effect of longer hours by women in the upper quintiles. If these profiles of hours could be reliably interpreted to reflect choices in response to rising earning opportunities, with households in each quintile making similar choices, pcc could then be expected to be strongly correlated with living standards. The increase in female hours with pcc

> 55  Hours of work per annum are calculated from the information available on hours worked in the last week, month and year, and hours work per day, in the LSMS.

55
challenges and represents a priority area for the fruitful sharing of experiences and policies across recipient countries. Cross country research in this area is still at a nascent stage as relevant data only recently became available for a few recipient countries. Lack of consistency and completeness of the available information has also precluded any rigorous econometric work in this area. Although, some studies on the policy implications and the management of private capital flows in developing countries are beginning to appear in the profession, this remains a very fertile area for further research.

There has also been a change in the destination of these foreign financing flows to developing countries in the 1990s. The overall composition of aggregate resource flows to developing countries by income group has now become a function of access to international capital markets. On the whole, the middle-income countries enjoy market access. Among low-income countries, China and India have recently raised substantial resources from the international capital markets, while the smaller low-income countries continue to depend on official sources of financing.

**Figure 4**

**Eighty four percent of official concessional loans and grants goes to the poorest 20 percent**

<!-- Start of picture text --> C 100<br>8c 0<br>60<br>o ~~~~~~~~~~Distribution of official concessional loans and grants, 1993<br>-Distribution of official concessional loans and grants, 1987<br>< 40<br>20<br>20<br>0 20 100<br>Share of developing countly GNP (percent)<br><!-- End of picture text -->

**Abo, S.oCd by GNP** pe .pits, theX-.i. **repre.ad, the .h-re ofd elopjoig-oerhy NP. .t.ltinogf.t hap-ot** -ounuy. All **-ouncrie.** rpo.nig tl **.. ubh th** DRS **sin-** 1987 **re** incudeda **So-u World Bank Deblor** Repotiog **Syalnn** (ODA). ed **national a-uoml.** (oNP pe Capi.a .ing **th. B.a All.** mehod).

7
To test the structural hypotheses that local rainfall variability affects welfare through occupational choices we estimate the IV equations (4) and (5) for non-flood prone Upazilas. Table 5 shows the second stage coefficients of equation (5) for three measures of occupational focus: (1) the head and at least one member of the household are self employed, (2) the head and at least one member of the household are self employed in the same sector, and (3) the head and at least one member of the household are self employed in agriculture. As before the dependent variable is log of per capita monthly consumption.

**Table 5: Effects of occupational focus on household welfare in non-flood prone Upazilas**

|VARIABLES|(1)<br>OLS|(2)<br>IV|(3)<br>OLS|(4)<br>IV|(5)<br>OLS|(6)<br>IV|
|---|---|---|---|---|---|---|
|Both self employed|**0.102*****|**1.160***|||||
||(2.844)|(1.876)|||||
|Both self employed in the same sector|||**0.109*****|**1.530****|||
||||(3.817)|(2.422)|||
|Both self employed in agriculture|||||**0.122*****|**1.414*****|
||||||(3.692)|(2.917)|
|Observations|591|591|1,425|1,425|1,425|1,425|
|Endogeneity Test χ<sup>2</sup>(1)||**6.087****||**9.409*****||**9.199*****|
|Anderson-Rubin weak Instrument Test χ<sup>2</sup>(1)||**7.75*****||**11.64*****||**11.64*****|

Robust t-statistics in parentheses based on PSU level clusters, *** p<0.01, ** p<0.05, * p<0.1 . Full estimation results are in annex Table A10 We find that occupational focus within household increase welfare. In all cases the OLS estimates (columns 1, 3, and 5) are smaller than the IV estimates (columns 2, 4, and 6). This is consistent with our earlier results and the hypothesis that the OLS estimates capture both the direct positive effect of occupational focus as well as the indirect negative effects of local rainfall variability on consumption. The null that the occupational focus variables are exogenous is rejected for all the 3 measures of occupational focus at 5 percent level of significance or better. The Anderson-Rubin Wald test for weak instruments rejects the null at 1 percent level or better for all three measures of occupational focus. Thus, the IV estimations confirm our hypothesis that the household adaptation to higher local rainfall variability by occupational diversification comes at a cost of welfare loss.

The estimates of the consumption models with the interactions terms between local rainfall variability and access to credit, safety-net, and market (equation 6) are in Table 6. The results are not qualitatively different from the estimations of the occupational equation (2) for households focused on self employed agriculture. Columns (1),(2), and (3) show the consumption estimates models with interactions between rainfall variability and access to credit, safety-net and market for households in non-flood prone Upazilas.

18
2008), before reversing its trend by easing back to 48% in subsequent years (Eurostat 2019). A more granular analysis by region shows that among HICs, North America experienced the largest increase in domestic government spending on health (Figure 2) between 2000-2003 and 2012-2016, possibly as a result of the spike in spending induced by the Affordable Care Act. In the same time period, the Sub-Saharan Africa and South Asia regions have seen either no or very modest increase in their health spending (Table 5).

**Figure 1:** Domestic government health expenditure as a percent of GDP, by income group

<!-- Start of picture text --> 2000 2004 2008 2012 2016<br>High income Upper middle income<br>Lower middle income Low income<br>6<br>5<br>4<br>3<br>2<br>Domestic gov health expenditure (% of GDP) 1<br><!-- End of picture text --> 10
– revenue (Currie, Lin and Meng, 2014). This structure where medical staff are salaried but still have an incentive to generate revenue to sustain the – clinic exists in many other settings across the developing world, including private, mission, and NGO-run medical facilities.

CSComs are one of the most important sources of care in Mali: according to the 2012-2013 Demographic and Health Survey, 47 percent of mothers in Bamako who sought care for a child under five with fever or cough took the child to a CSCom. The quality of care across CSComs varies and is typically poorest in rural areas. Our study was conducted in the capital city of Bamako and a nearby suburb, where clinics offer a higher standard of care and are usually headed by a trained medical doctor (as compared to a national average of roughly one third (PMI, 2016)). All clinics in our sample have at least one salaried physician on staff, and in over 90 percent of clinics that have a pharmacy, there is a physician present when the pharmacy is open (see Appendix Table B1).

One of the most commonly-treated illnesses in CSComs is malaria. Despite recent progress, malaria is the second largest cause of mortality in Mali, accounting for roughly 14 percent of all deaths and 19 percent of deaths among children under five (IHME, 2018). Although the parasite is endemic in all parts of the country except the sparsely populated northern desert, rates of transmission are substantially lower in urban areas. For example, in 2015 the estimated prevalence of the parasite in children under five in Bamako was six percent, as compared to 36 percent nationwide (PNLP et al., 2016).

Malaria infections are classified as either “simple/uncomplicated” or “severe”. Simple malaria is not life threatening if treated promptly, and is characterized by non-specific, flu-like symptoms including fever, chills, and headache. If left untreated, simple malaria can progress to severe malaria. In this stage of the disease, patients often suffer convulsions and experience life-threatening complications, including loss of consciousness/coma, respiratory failure, renal failure, and severe anemia (Trampuz et al., 2003). Patients with severe malaria require prompt, aggressive treatment to avoid death and should be hospitalized until their symptoms stabilize.

Mali’s national malaria policy requires that suspected malaria cases be confirmed via a positive microscopy or rapid diagnostic test (RDT) before dispensing treatment (Minist`ere de la Sant ́e, 2013).<sup>8</sup> RDTs are meant to be

> 8This recommendation was first made in the five-year strategic plan for 2007-2011.

8
Policy Research Working Paper 5442

# **Abstract**

Although Kenya’s financial system is by far the largest and most developed in East Africa and its stability has improved significantly over the past years, many challenges remain. This paper assesses the stability, efficiency, and outreach of Kenya’s banking system, using aggregate, bank-level, and survey data. Banks’ asset quality and liquidity positions have improved, making the system more resistant to shocks, and interest rate spreads have declined, in part due to reduction in the overhead costs of foreign banks. Outreach remains limited, but has improved in recent years, driven by mobile payments services in the domestic remittance market. Fostering a level regulatory playing field for all deposit-taking institutions is a key remaining challenge. Specifically, an effective but not overly burdensome framework for regulation and supervision of microfinance institutions and cooperatives is a priority. Maintaining an openness to new, and non-bank, providers of financial services, which has enabled the success of mobile payments, could also further outreach.

This paper—a product of the Finance and Private Sector Development Team, Development Research Group—is part of a larger effort in the department to study the efficiency and outreach of African financial sectors. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at rcull@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
the GDP of rich countries to the terms of trade faced by LIC and to the international interest rate. This ordering permits the international interest rate to react contemporaneously to the state of the global economy, but imposes that the feedback from the international interest rate to global output operates only with a lag. As pointed out by Ahmed (2003), this assumption is standard in studies of U.S. monetary policy that use quarterly or monthly data, but may be overly strong when using annual data as in our case. Placing terms-of-trade below the GDP of rich countries assumes that changes in the demand for commodities resulting from changes in the state of the international economy translate into changes in the relative price of these products contemporaneously, but changes in commodity prices affect rich countries’ output only with a lag. This assumption is also common in VAR studies of U.S. monetary policy that control for the price puzzle by including indexes of commodity prices (see, for example, Christiano et al., 1998, and references therein). The ordering of the terms-of-trade index and the international interest rate also follows the typical ordering of commodity price indexes and interest rates in these studies. Nevertheless, in the robustness section we will also determine the impact on the results of assuming several alternative orderings among these variables. For the case of aid, we also impose a block triangular structure in the matrix of contemporaneous relations between the _y_ variables, _A_<sup>0</sup> 22<sup>, which</sup> assumes that output responds contemporaneously to changes in aid, but aid flows to a country respond to changes in its economic conditions only after a year. Given the usual delays in the process of aid allocation (see Odedokun, 2003), we believe that this is a sensible assumption.

The identification assumptions described above translate into the following structure for the matrices of structural coefficients: where _m_ is the number of variables included in _y_ excluding _AID_ , and the size of the different sub-matrices conform with the dimension of the vectors that they multiply, as indicated by the dimensions in subscript.

Several aspects of the model deserve further discussion. The vector _yit_ is assumed to be trend stationary. There is a longstanding debate in macroeconomics about whether macroeconomic 12