rafmacalaba/datause-encoder-data huggingface dataset:
directions we propose under the current calls for urgent action.

# **7 Potential of frontline public health workers**

Citizens report greater reliance on publicly provided preventive and promotive health services than on curative health services. For example, in response to a question about how often they use government health facilities when someone in the family falls ill, only 12 percent answer "often", while 47 percent answer "rarely" or "never". This is consistent with the findings from the work of Das et al (2016) that people in rural India tend to rely on private providers for curative health care. In contrast, when women in the sub-sample of households who had experienced a recent pregnancy (within the past 5 years) were asked which type of provider gave them ante-natal care, 85 percent responded by indicating a public provider (the ASHA and AWW are the most frequently cited); only 14 percent indicated a private sector provider.

This difference in the extent to which the public sector is used for preventive and promotive rather than curative care is particularly large for poorer and less politically connected citizens. Table 5 shows that respondents who are in positions of political power–elected politicians of local government (the panchayats at the village, block and district levels), members of the state legislative assembly (MLAs) and members of the national parliament (MPs)–are significantly more likely to use government clinics or hospitals for curative care needs. We are unable to control for measures of income and assets because these questions were not asked in the surveys of higher-level politicians owing to sensitivity issues and time constraints in getting these powerful respondents to sit down for a survey. We hypothesize that the estimated influence of political power in accessing curative care in government hospitals may be even higher if we were to be able to control for income, since higher-level politicians would tend to have higher incomes, and higher incomes are associated with greater use of expensive private care facilities.

Among the different frontline workers who could provide maternal and child health/nutrition services–the ASHAs, the AWWs, and the village sub-center ANMs–citizens systematically report much lower reliance on ANMs than on the quasi-volunteer workers (ASHAs and AWWs).

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3

# **IL Methodology and Data**

There is a voluminous literature which looks into the production characteristics of education sector, such as efficiency, scale and scope economies and in the context of developed countries. In most cases, inferences are based on results obtained from the estimation of a cost function (Bee and Dolton, 1985; Butler and Monk, 1985; Kumar, 1983; Scott and Santerre, 1990). An exception focussing on developing countries is a stady by Jimmenez (1986) about primary and secondary education in Latin America which also involved fitting a cost function.

It should be noted that estimations of parametric production, cost or profit functions may not reveal the true characteristics of the relationship **s** tudied for several reasons. First, re .its depend on parametric specification and assumed distribution of the error term. Second, error terms are twosided, meaning that these estimates imply a behavior compared to an average firm. For example, a production function fitted by regression of outputs on inputs will have both positive and negative residuals and what is estimated is _mean_ output not _maximum_ output (Schnidt, 1985). And third, when prices of inputs and outputs are not available or distorted, as is the case with the country we are dealing with, cost or profit function cannot be fitted.

Non-parametric frontier function approach avoids these difficulties. In this study, we apply the non-parametric method of Data Envelopment Analysis (DEA) (Charnes, Cooper and Rhodes, 1978) on the data from Bulgaria to estimate relative efficiency scores in the use of classrooms in Bulgaria's general education (first twelve grades). The efficiency scores are then regressed on a host of probable explanatory variables to examine the factors causing the efficiency differences.

Data Envelopment Analysis has been previously applied on education data by Charnes, Cooper and Rhodes (1978), Bessent _et al._ (1982, 1984) and Ray (1991). These studies use data from the United States. The first three studies include socio-economic fcors in the DEA stage of
<!-- Start of picture text --> 30<br>20<br>10<br>0<br>1 2 3 4 5 6 7 8 9 10<br>Income decile<br>Total energy End-use energy<br>Energy consumption (kgOE/capita/month<br><!-- End of picture text --> Source: BIDS Survey (2004)

**Figure 4: Trend in household’s total and end-use energy by income decile**

As expected, a household’s end-use or useful energy actually is only a fraction of the total energy that the household consumes (Figure 4). For rural Bangladesh roughly only one-seventh of the total energy is converted into useful energy. The gap between total energy and end-use energy also becomes wider as households move from low income to high income status. This is probably because as income grows rural households not only consume more biomass, but also are making a transition from traditional to modern fuels.

The differences between total and useful energy are further demonstrated in Figures 5 and 6. In the distribution of the total energy, biomass constitutes an overwhelmingly large share of energy use and this pattern is consistent for all households (Figure 5). As household income grows, the amount of total biomass energy per capita used by households increases consistently especially after 20
(iii) _Accountability_ , which measures the extent to which the actors of the sector, whether consumers, operators, financiers (including donors), regulators, Ministry bureaucrats or politicians, can be held responsible for their obligations. This is largely linked to the information flows between actors since it is through misuse or lack of transparency of this information that the potential for abuses leading to underperformance in costs, quality or price can take place.

(iv) _Fiscal efficiency,_ which measures the extent to which governments are able to collect adequate revenue when they commit to direct subsidies. These are quite common in the sector as a way of ensuring that the limited ability of consumers to pay for services does not lead to the exclusion of the poorest, or as a way to reduce the financial risk that operators are expected to take on when investing in a project.

The detailed evidence collected over the years by various studies of the sector taking different perspectives shows that the particularly large number of failures in WSS contractual arrangements between public and private players, as well as across government levels within countries or across government agencies and ministries, can be correlated with a poor appreciation of at least one of these four sources of institutional weaknesses ( Estache and Wren-Lewis (2010) provide a survey of the empirical evidence).

The empirical indicator that has enjoyed the highest visibility of the risks linked to institutional standardization is the rate of contract renegotiation. This is a reasonably credible indicator of the time inconsistency of the contract, which tends to be bad for reforms demanding long term commitments by governments (e.g. to fair rates of return or to the payment of subsidies if these are part of the contractual promises) and in particular for investment. Between 1990 and 2010, according to Guasch et al. (2015), over 90% of the water Public Private Partnership (PPP) deals, supported by a largely standardized contractual and regulatory packaging, have been renegotiated. The most interesting observation is that the usual outcome of renegotiation has been a redesign of contracts and regulation to better match the various risk drivers linked to a wide range of institutional weaknesses that have only been recognized during the renegotiation process. For instance, the widely popular price caps, built in the original designs of the 1990s, have been replaced by de facto cost-plus regulation to reassure investors, since it guarantees a minimum return.<sup>7</sup> Similarly, investment subsidies have now

> 7 The shift to a cost-plus regime has sometimes been explicit but more often the result of the identification of a growing number of costs items for which an automatic cost pass-through in prices or subsidies was allowed. These are now known as hybrid regulatory models. When over 50% of costs are passed through, they are close to cost-plus regimes.

4
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||period for the Lower house of the country and 0 otherwise._Source:_<br>Inter-Parliamentary Union (IPU) and website searches|
|---|---|
|GovExp|General government expenditure (% of GDP)._Source_: International<br>Monetary Fund, World Economic Outlook Database, October 2017.|
|Mortality|Mortality rate, adult, female (per 1000 female adults)._Source:_WDI,<br>World Bank|
|PopGrowth|Population growth (annual %)._Source:_WDI, World Bank|
|Inflation|Inflation, GDP deflator (annual %)_Source:_WDI, World Bank|
|_Regions_||
|East Asia and Pacific (EAP)|Dummy indicating a country in East Asia or Pacific region._Source:_WDI,<br>World Bank|
|Europe and Central Asia (ECA)|Dummy indicating a country in Europe or Central Asia region._Source:_<br>WDI, World Bank|
|OECD high income|Dummy indicating a country in OECD high income group._Source:_WDI,<br>World Bank|
|Latin America and Caribbean (LAC)|Dummy indicating a country in Latin America or Caribbean region.<br>_Source:_WDI, World Bank|
|Middle East and North Africa||
|(MENA)|Dummy indicating a country in Middle East or North Africa region.<br>_Source:_WDI, World Bank|
|South Asia (SA)|Dummy indicating a country in South Asia region._Source:_WDI, World<br>Bank|
|Sub-Saharan Africa (SSA)|Dummy indicating a country in Sub-Saharan Africa region._Source:_<br>WDI, World Bank|

# **3. Findings**

We begin by controlling for cross-country differences in income levels using GDP per capita, a proxy for political change, and year and country fixed-effects. We find that richer countries have less incidence of poverty, and that countries that spend more on government services as a share of their GDP also display lower poverty headcount. Government expenditure on health and education is also negatively correlated with the poverty headcount. These results are consistent with the previous literature. When we include health and education expenditures separately, education expenditure is negatively correlated with the poverty headcount and this correlation is always statistically significant. Health expenditure appears with a negative sign but is only sometimes statistically significant (not shown).

The effect of inadequate health care, proxied by adult female mortality, on the poverty headcount is positive and statistically significant (Table 2). Population growth affects negatively the poverty headcount and this association is statistically significant, as in previous studies. The effect of political change is insignificant, while inflation is marginally significant (at the 10% level), with a negative sign.

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43 conceptualization through extrapolation of visible changes. In institutional structure as in technology, there may be dividends for latecomers. Developing countries need not recapitulate the concentration of production in large, hierarchically structured organizations. If larger numbers of smaller units does constitute the preferred destination for modern economic organization, perhaps developing countries can take a substantial short cut in getting there.

The difficulty here, of course, lies in the diagnosis of the character and direction of the "wave" -- assuming there is such a wave. A wide range of considerations are arguably at work in producing the trend described, even after excluding those that seek to explain the statistical evidence on SMEs as an artifact of some more fundamental change."<sup>5</sup> Prominent among the candidates that have the most far-reaching implications are two products of the micro-electronic revolution, low-cost communications and flexible capital equipment. The former makes complex coordination economically feasible even across large distances, thus reducing the coordination advantages that large establishments derive from geographical concentration of activity. The latter reduces the cost advantages of

**15** Among the "artifactual" explanations are the following: (i) shifts in the sectoral composition of output in favor of sectors where SMEs play a larger role, especially the rise of the service sector; (ii) counter-cyclical behavior of the SME employment share, coupled with a comparatively high incidence of "bad economic times" in the advanced countries since the mid70s; (iii) cost advantages for small firms because they present an inconvenient target for union organizers and government enforcement of labor standards.
population worsened dramatically following the economic crisis of the 1990s; however although consumption levels recovered by 2000, mental health did not (Friedman and Thomas, 2007). Additionally, as shown earlier, in all countries, poor physical health as measured through self-reported health status is strongly correlated with worse mental health.

# <u>5.3 Implications for further research on mental health and development</u>

Effective public health policy requires an understanding of the mechanisms that determine poor mental health and, in turn, the implications of poor mental health for the individual and his/her family. The descriptive analysis here provides suggestive evidence for what some of these mechanisms may be and therefore a _potential_ role for public health interventions.

The lack of any relationship between conventional economic welfare measures and mental health outcomes across a diverse sample of developing countries suggests that poverty, _per se_ , is not a strong determinant of poor mental health. A straightforward equity rationale for public investments in mental health is undermined by the higher relative prevalence among the poor of other health problems such as tuberculosis and malaria as well as continuing financing gaps for these illnesses. The lack of a relationship between consumption poverty and mental health is certainly not, however, supportive of arguments that suggest no scope for public interventions towards improving mental health.

Country studies on India, Indonesia and Tonga suggest that _changes_ in life-circumstances brought on by positive or negative events have relatively long-lasting implications for mental health. In addition, two of the strongest factors associated with poor mental health are poor physical health and widowhood. These findings are also consistent with studies that report worsened mental health outcomes in populations that have suffered conflict or disasters (United Nations High Commissioner for Refugees (UNHCR), 2005; Lopes Cardozo et al., 2004). The Indian and Indonesian studies suggest that the trauma from adverse events may persist long after the recovery of more traditional measures of welfare and there may very well be real individual and household costs to this persistence. Possible impacts of mental health on labor force participation and health-seeking behavior have already been discussed. Additional examples of such costs along the health dimension include: lower adherence to dietary recommendations and medication regimes among diabetics with depressive symptoms compared to diabetics without (Ciechanowski et al., 2000); high co-morbidity rates for smoking and psychiatric disorders, with smoking twice as common among the mentally ill compared to the mentally healthy population (Lasser et al., 2000); and an association between maternal mental health and child welfare in two South African studies, with maternal depression significantly increasing the odds that a child will experience growth faltering (Harpham et al.,

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|<br>|Public procurement<br>TRIMS measures|<br>Approximation of<br>legislation|<br>Political dialogue<br><br>Public administration|
|---|---|---|---|
||GATS|<br>Audiovisual|<br>Regional cooperation|
||TRIPS|<br>Civil protection|<br>Research and technology|
|||<br>Innovation policies|<br>SMEs|
|||<br>Cultural cooperation|<br>Social Matters|
|||<br>Economic policy dialogue|<br>Statistics|
|||<br>Education and training|<br>Taxation|
|||<br>Energy|<br>Terrorism|
||||<br>Visa and asylum|

The relationship among EU members is the deepest when we use as a measure of depth the number of legally enforceable provisions. The EC Treaty and the EU enlargements encompass 44 legally enforceable provisions. They include all WTO+ provisions and a large number of WTO‐X areas. In addition, the EU is a member of 36 trade agreements with third countries. Some of these PTAs are also very deep. This is the case for the agreements with Moldova, Ukraine and the European Economic Area (EEA), an agreement that includes the EU and all EFTA members except Switzerland. These PTAs respectively include 44, 43 and 36 legally enforceable provisions. All the other PTAs signed by the EU are shallower. Table 2 lists all the provisions in the data set and identifies those included in the EU and the number/share of EU agreements with third countries that include these provisions.

_Table 2:_ Provisions in the EU agreement and number and share of EU’s PTAs with third countries including each provision

||EU28|EU‐3rd Countri|es PTAs|
|---|---|---|---|
|Provision|Legally<br>enforceable|Number|Share|
|Tariffs on manufacturing<br>goods|Yes|35|100%|
|Tariffs on agricultural goods|Yes|35|100%|
|Anti‐dumping|Yes|34|97%|
|Customs|Yes|33|94%|
|Export taxes|Yes|32|91%|
|Countervailing measures|Yes|29|83%|
|Competition policy|Yes|28|80%|
|State aid|Yes|26|74%|
|TRIPS|Yes|23|66%|
|IPR|Yes|22|63%|
|STE|Yes|21|60%|
|Movement of capital|Yes|19|54%|
|Public procurement|Yes|14|40%|
|TBT|Yes|10|29%|
|GATS|Yes|10|29%|

7
activities and challenges during disasters have aggravated the sociological (Whittle 2010) and epidemiological effects and increased psychological and physical distress (Reacher 2004).

Other post-flood effects, for example increased levels of poverty and famine, can be cited from the Pakistan 2010 event, as indicated in a report by UNESCO on the flood’s impact on the Millennium Development Goals which demonstrated that 5 million people were affected by undernourishment, and that severe damage of crops has led to higher food prices which caused lower food security for the affected people and increases in poverty. Other indirect effects, like closure of schools and damage to educational buildings, also have a long term effect after flood events, which lengthen the duration of the activity of resettlement and restoration to normal life.

Another post-flood impact which directly or indirectly affects already suffering people is the burden of debt for restoration of the economy. According to the country’s economic survey 2009-10, about 34% of Pakistan’s GDP is being used for debt reduction after the 2010 flood. This puts extra pressure on people and reduces their financial ability to cope with the changed situation, making them in turn more vulnerable.

# **1.8 Summary**

**The foregoing analysis of the trends in flood impacts across the world concludes that**

**there is evidence that the impact of flooding is increasing globally** . Trends in number of events, numbers affected by those events and financial, economic and insured damages have all risen over the period since 1950. Immediate loss of life from flooding seems to be increasing more slowly or even decreasing over time which can be attributed to successful warning, evacuation and emergency actions, as well as increased investment in flood defenses.

The need to mitigate the devastation caused by flood events across the world is justified by the cost in human life, massive damages and impact on the lives of millions of people annually. As recent events in Pakistan, Australia and Brazil show, floods can occur in widespread locations and can sometimes overwhelm even the best prepared countries and cities. The perception that these events are increasingly frequent and costly and might continue to worsen in a changing climate has led to calls to act urgently to prevent further catastrophes.

Urban areas which are at risk from flooding have particularly been hard hit by this increase. Indeed as urban populations represent an increasing proportion of world populations, urban floods account for an increasing percentage of the total flood impact. Reported data does not allow us to summarize urban flooding as a global distinct entity but many of the most devastating recent events affected major urban centers and the specific problems of urban floods have been identified.

As will be shown in Section 2, projections of future flood trends vary widely but there is a consensus that flood impacts will continue to rise well into the future (Stern 2006; UNEP 2007).

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