rafmacalaba/datause-encoder-data huggingface dataset:
# **Table 3:  Determinants of road maintenance expenditures Coastal region municipalities in Bangladesh, 2007-2013**

**All variables except** **_Pucca_ Share in logs**

## **Dependent variable:  Road maintenance expenditure**

||**Rob**|**ust**|**G**|**LS**|**Fixed E**|**ffects**|
|---|---|---|---|---|---|---|
||**(1)**|**(2)**|**(3)**|**(4)**|**(5)**|**(6)**|
|**_Pucca_ Share**|**-2.796**|**-2.801**|**-2.796**|**-2.801**|||
||**(1.79)**|**(1.71)**|**(1.75)**|**(1.67)**|||
|**Groundwater Salinity**|**1.859**|**1.862**|**1.859**|**1.862**|**10.014**|**9.617**|
|**x****_Pucca_ Share**|**(2.81)****|**(2.43)***|**(2.85)***|**(2.30)***|**(2.09)***|**(2.30)***|
|**Road Network Length**|**-0.205**|**-0.203**|**-0.205**|**-0.203**|||
||**(0.59)**|**(0.63)**|**(0.53)**|**(0.58)**|||
|**Local Revenue**|**0.741**<br>**(2.21)***||**0.741**<br>**(1.92)**||**0.049**<br>**(0.08)**||
|**Development Income**|**0.735**||**0.735**||**0.228**||
||**(2.21)***||**(1.88)**||**(0.54)**||
|**Local Revenue +**||**0.738**||**0.738**||**0.159**|
|**Development Income**||**(4.69)****||**(4.41)****||**(0.84)**|
|**Constant**|**-9.416**|**-9.428**|**-9.416**|**-9.428**|**2.728**|**2.278**|
||**(2.56)***|**(2.52)***|**(2.46)***|**(2.43)***|**(0.46)**|**(0.43)**|
|**Observations**|**41**|**41**|**41**|**41**|**41**|**41**|
|**R-squared**|**0.66**|**0.66**|**0.66**|**0.66**|**0.40**|**0.40**|
|**Number of municipalities**|||||**20**|**20**|

**t statistics in parentheses**

*** significant at 5%; ** significant at 1%**

16
implemented the fewest reforms, with 49 and 25, respectively. Despite having no UB reforms and the fewest ALMP reforms, SAR implemented the highest number of social assistance programs (Gentilini et al. 2022). These initiatives constituted 78 percent of SAR's and low-income countries' social protection and labor market policies.

Overall, most of UB reforms during the Covid-19 pandemic were implemented by high income countries (at 62 percent), while upper middle-income countries accounted for 26 percent and lower middle-income countries for 11 percent of these reforms. Low-income countries had no UB reforms. A larger proportion of low and lower middle-income economies implemented ALMP reforms during this period, with 8 percent and 17 percent, respectively, compared to 47 percent in high-income countries and 27 percent in upper middle-income countries.

# **3.4. Correlations among UB, ALMP, and labor market outcomes**

This section presents simple correlations between UB and ALMP indicators and labor market outcomes based on the novel data collected in 2019 and 2020, without controlling for other indicators. As seen from Table 2, the unemployment rate is significantly associated with only two ALMP, namely training and internship programs, the former with a negative and the latter with a positive association. The employment rate, on the other hand, is associated significantly and negatively with four indicators of UB and ALMP: availability of UB scheme, length of minimum contribution period for UB, and two training incentives (subsidy and reimbursement of training costs). The employment rate in agriculture and the selfemployment rates have a significant and negative correlation with the majority of UB and ALMP indicators, while employment rates in industry and services have a positive association. The only exception is that the employment rate in services is negatively related to the length of the minimum contribution period for UB.

These findings imply that, ceteris paribus, countries with UB and ALMP tend to have lower agricultural employment and self-employment rates and higher employment rates in services and industry. Although having a UB scheme is positively associated with both log and growth of labor productivity, a longer UB period is negatively associated with the latter. Moreover, among the ALMP indicators, four have a significant and positive relationship with labor productivity growth: counseling services, support for geographical mobility, internship programs, and training incentives. The log of labor productivity is significantly associated with most indicators of UB and ALMP, and all of these associations are positive.

18
- 57 -

# ANNEX 4. Review of Pricing and Cost Recovery in SARS:

# HEALTH SECTOR

# **A.** THE POLICY

# A.1 Interpretation of Efficiency Prii

1. OHS 2.25 suggests a limited scope for applying marginal cost pricing principles to public health services. Both because of the difficulty of measuring true economic costs and because of distributional objectives, in practice health care has generally been provided free and financed out of general taxation.

2. Very recently, however, arguments have been set forth for a dramatic change in health financing policies by borrowing countries, with 1 the emphasis on users bearing a larger share of health care costs. The proposed pricing reforms are tailored within the context of different types of health services, and are sumarized **as** follows: preventive services which are not patient-related (e.g., disease control programs, sanitation, education on health and hygiene) should be provided at zero, or even negative, cost to users since these services have strong "public good" attributes. Patient-related preventive services (e.g., i_ unization, maternal and child health care, visits by village health promoters), on the other hand, should not be provided free of charge. User charges for these services aro feasible; but they should be below marginal cost because of externalities and users' lack of information. (Inmunization is a good example.) These issues justify the provision of such services at subsidized costs to users in order to encourage demnd.

3. For curative care (e.g., sale of medicine, outpatient and inpatient care), efficiency pricing should be applied as a benchmark, and any departures from it should be explicitly justified. Curative services typically account for at least 70 percent of a country's annual health expenditures, and the underlying issues on externalities and users' knowledge are less vague on this side. Increased recovery of costs fron users can be implemented in combination with risk-sharing arrangements such as insurance schems; increased privatization in the supply and finance of certain health services; and structuring public subsidies to the health sector to strengthen incentives for cost control.

1/ This section draws heavily from SWP No. 721, Paying for Health Services in Developini Countries: An Overview, by David de Ferranti.
# **Sources and References**

IOSCO Emerging Markets Committee. 2011. “Development of Corporate Bond Markets in the Emerging Markets.” November. Madrid.

Kelly-Dynega, Noreen, and Sarah Lightdale. 2012. “District Court Ruling Paves the Way for More ‘Negligent Securities Fraud’ Enforcement Actions under Sections 17(a)(2) and (3) of the Securities Act.” Client Alert, July. Latham & Watkins, New York.

McKinsey Global Institute. January 2013. “Infrastructure Productivity: How to Save $1 Trillion a Year.” McKinsey & Company, Washington, DC.

Vizcarrondo, Paul, Jr. 2011. “Liabilities under the Federal Securities Laws.” September. Wachtell, Lipton, Rosen, and Katz, New York.

Surveys and interviews with the International Capital Market Association (ICMA), as well as the European Commission website and relevant laws and regulations, for information related to the European Union.

Websites and relevant laws and regulations of, as well as detailed surveys and interviews with the following securities regulators and self-regulatory organizations:

|Brazil|Comissão de Valores Mobiliários, ANBIMA|
|---|---|
|Chile|Superintendencia de Valores y Seguros|
|India|Securities and Exchange Board of India|
|Israel|Israel Securities Authority|
|Malaysia|Securities Commission|
|Thailand|Securities and Exchange Commission|
|United States|Securities and Exchange Commission|

72
However, it is probable that as soon as the low income countries reach higher Internet penetration, language will start to matter as indicated by the results for upper middle income.

**<u>Table 7:</u> Impact of sharing the same language on the diffusion process**

||<br>Low and Lower Middle Income|<br>Upper Middle and High Income|<br>All|
|---|---|---|---|
||[1]|[2]|[3]|
|Log real GDP per capita|0.904|0.671|0.282|
||[0.827]|[0.685]|[0.539]|
|Log real cost|-0.065|-0.02|0.005|
||[0.084]|[0.074]|[0.048]|
|Log lines per capita|0.258|-0.303|0.166|
||[0.293]|[0.307]|[0.245]|
|Log computers per capita|0.228|-0.204|0.107|
||[0.210]|[0.234]|[0.162]|
|Lag Internet users|0.539***|0.719***|0.622***|
||[0.049]|[0.082]|[0.047]|
|Lagged language network|0.08|0.239***|0.237***|
||[0.161]|[0.075]|[0.056]|
|Constant|0.11|-0.019|-0.004|
||[0.073]|[0.050]|[0.045]|
|Method of estimation|IV|IV|IV|
|Fixed effects|Yes|Yes|Yes|
|Number Observations|358|380|738|

Notes: The dependent variable is the log of Internet users per capita. For each country _i_ , the lagged language network is the logarithm of the total users in other countries (other than _i_ ) with the same official language, per capita. The robust standard errors are in brackets.

* , **, and *** indicate significance at the 10, 5, and 1 percent levels respectively. The regression uses countries with GDP per capita growth in the interval [-4.9 , 9.2 percent] and controls for country fixed effects.

# **6. Conclusions**

This paper provides a detailed empirical study of the process of adoption and diffusion of the Internet in a large sample of countries for the period 1990-2004. In the first part of the paper we show that this process is well characterized by an S-shape pattern. This is true if we use the world aggregate or if we consider different groups of countries based on their income. The slope of this pattern is positively related to the level of development of each group of countries although, due to the nature of the curve, with time less developed countries adopt Internet faster than more developed ones.

The second part of the paper explores the main determinants of Internet diffusion and finds that national network effects (measured as the lag of the number of users in a given country) are a crucial determinant of the spread of Internet. This network effect is stronger in more developed countries than in developing ones, implying that both groups are facing different stages of Internet adoption. We explored potential differences in this process across time and we found that low and lower middle income countries are following the path made by the upper middle and high income countries.

22
**Table 2: Australia Fund Type Asset Mix and Performance**

|**Proportion of Assets %**|**Corporate**|**Industry**|**Public Sector**|**Retail**|**Total**|
|---|---|---|---|---|---|
|Australian Shares|30|29|22|26|26|
|International Shares|28|25|27|22|25|
|Listed Property|1|1|4|4|2|
|Unlisted Property|7|10|6|2|7|
|Australian Fixed Income|14|6|7|15|9|
|International Fixed Income|6|5|7|7|6|
|Cash|6|6|9|14|8|
|Other Assets|8|19|18|9|16|
|Total|100|100|100|100|100|
|**Rate of Return(2004-2013)**|**6.5%**|**6.7%**|**7%**|**4.9%**|**6%**|
|**Volatility**|**9**|**9.5**|**9.7**|**9.4**|**9.5**|

Source: APRA Initial evidence from a forthcoming paper<sup>22</sup> suggests that higher switching levels between providers in selected Latin American systems are correlated with higher levels of short-term investments. The analysis also shows that changes in regulation (such as making switching more difficult) can have a positive effect on portfolio turnover and construction.

**Table 3: Correlation between calendar-year returns and transfers**

||**Across Fund**<br>**Providers**|**With Fund**<br>**Providers***|
|---|---|---|
|LAC|||
|Chile|-0.46|-0.41|
|Colombia|0.15|0.04|
|Costa Rica|-0.23||
|Mexico|-0.41|0.71|
|Peru|0.18|-0.10|
|EEC|||
|Estonia|-0.28|-0.14|
|Romania|-0.03||

Source: Fuentes, Morales and Stewart (forthcoming) 22 See Fuentes, Moralez and Stewart (forthcoming).

10
outside the context of a healthcare visit. Most of this expenditure is likely to be direct purchases from a pharmacy. Because NHIS does not cover the costs of medicines and supplies acquired outside the context of a consultation, we think it unlikely that NHIS covers the OOP expenditure reported as such.<sup>20</sup>

# **4 Estimating the Distribution of Income Net of OOP Healthcare Expenditures**

There are several options for identifying NHIS members.<sup>21</sup> We use only those who were able to show a valid NHIS card to the GLSS 2016/17 interviewer. This produces an estimated 9.3 million beneficiaries, compared to 10.8 million registered beneficiaries in 2016 and 12.2 million in 2017 based on program administrative data obtained from the government.

To generate treatment and control groups, we use coarsened exact matching (Blackwell 2009). We match NHIS members and nonmembers on region and area of residence (urban versus rural), the log of household consumption per adult equivalent, and several individual-level characteristics that increase the likelihood of NHIS membership because they reduce or eliminate the annual registration and membership fees: those aged 70 years old or older; a child under 18 years; a woman who is currently pregnant, has been pregnant in the past year, or currently has an infant under 3 months old; a contributor to SSNIT; or a recipient of a SSNIT pension.

Table 2 reports the results from our matching exercise. L1 is a measure of distance between NHIS members and nonmembers, bounded by 0 (perfect match) and 1. The ex-ante data show that the two groups are well-matched except with respect to region of residence and the log of household consumption per adult equivalent. After matching, some imbalance with respect to consumption remains, but it is considerably less than in the ex-ante comparison. Overall, the criteria used for the match generate 141 strata, 95 of which are successfully matched. Only 313 individual records out of 58,844 respondents could not be matched and are excluded from the analysis.

> 20 Indeed, the distribution of the values reported for “medicines and medical supplies” purchased outside the context of a healthcare visit are almost identical for members and nonmembers.

> 21 Questions 1, 3, and 6 in Section 3B of the GLSS 2016/17 questionnaire.

11
ways. First, when respondents under Clinic condition decided whether to attend the health clinic, they were informed that they would not need to utilize any services at the clinic. Second, we eliminated a concern about uncertainty of the vaccine supply as a source of distrust of health services, as discussed above. Third, at the clinic, respondents interacted with health staff only after they agreed to receive the vaccine; thus, respondents did not need to interact with health staff at the clinic if they did not wish to. At the same time, this attempt to minimize the influence of the psychic costs of clinic attendance might have led to underestimated psychic costs of vaccination because the difference in conditionality, either clinic visit or vaccination, might have been nuanced, as discussed below.

> 29Northern Nigeria suffers from higher maternal and child mortality and lower utilization of health services than Southern Nigeria. The under-5 child mortality rate is 260 per 1000 in northeast states while it is 103 in southwest states (UNICEF, 2013). The percentage of women receiving two or more injections against tetanus during their last pregnancy was 58.8 percent in Adamawa state, while southern states achieve about 75 to 80 percent (DHS, 2013). Although the state government has been providing free antenatal care services including tetanus toxoid vaccination to pregnant women, the vaccination rate remains low.

> 30Among the 11 wards in Jada, we focused on all 9 rural wards, each of which has 1 to 5 public health clinics. We selected the main health clinic from each ward, with an exception of one large ward, where we selected 2 clinics.

31 Catchment areas are defined by the primary healthcare development agency that is responsible for national immunization campaigns. None of the catchment areas of the 10 clinics in the sample overlap each other.

> 32Our survey team visited households to find out if they had any eligible women.

> 33This study examines psychic costs among women of childbearing age. Focusing only on pregnant women was practically infeasible because it would have required a much greater number of villages to be covered. Furthermore, targeting non-pregnant women of childbearing age in the study is as important as targeting pregnant women to protect newborn babies in the long run, because the immunity of tetanus toxoid vaccines lasts for several years.

> 34We employed this simple selection procedure to minimize a potential threat that interviewers might pick a respondent based on their convenience and/or preference in practice, though we acknowledge that this procedure might have been less ideal than simple randomization.

> 35Since we did not conduct a household census in the village, it is likely that we did not reach some households with an eligible woman. At the same time, because the survey team spent more time in larger villages, the number of eligible women in the sample should be positively correlated with the total number of eligible women in the population across villages.

36The voucher indicated the respondent’s name, her unique ID assigned in the project, date of the intervention, 24
Optimizing the staff mix could be facilitated by moving from an input-based hospital payment method to an output-based one. The fixed annual budget allocations of the input-based systems mean that health care managers have neither the autonomy and flexibility nor the incentives to hire and fire workers so as to optimize the staff mix.

# _<u>D2.4. Excess medical capacity in the hospital sector</u>_

The share of health expenditure devoted to the hospital sector in the Western Balkans is high, but the sector is marked by low productivity. This takes a number of forms.

Inpatient admission rates are low with the result that available resources, such as hospitals, beds and staff, are under-utilized. Annual inpatient admission rates range from 8.7 per 100 people Albania to 12 per 100 people in Serbia, compared to 17 in Croatia, 18 in Slovenia, 17 in the EU and 21 in the EU-12. Bed occupancy rates in acute care hospitals for those countries for which data are available (i.e. Serbia, Montenegro and Macedonia) are between 5 and 10 percentage points lower than the EU average of 76%. Moreover, the fact that the patients who are admitted seem to have longer-than-average stays in hospital, between 9.5 and 11 days, compared to an average of 8 days in EU 10 and 9.25 days in EU as a whole, means that bed occupancy rates are higher than they would have been were patients being discharged or moved to outpatient care as soon as they could be. Only in Albania is the average length of stay (ALOS) very short, about 6.4 days. Comparison with data from earlier years suggests that the ALOS has been rapidly decreasing, though: between 2000 and 2005, the ALOS fell by at least one day in all the countries of the Western Balkans.

With the exception of Montenegro, the number of outpatient contacts per person per year is low compared to EU countries. In Albania, the average person utilizes outpatient care only about 1.5 times per year. This number is higher in Bosnia and Herzegovina (3.3) and in the FYR of Macedonia, but well below the EU and Montenegro average of around 7.

|**Table 6 Inpatient an**|**d outpatient health care utili**<br>|**zation, 20**<br>|**05 (unless noted ot**<br>|**herwise)**<br>|
|---|---|---|---|---|
||**Bed occupancy rates**<br>**(acute care hospitals)**|**ALOS**<br>**(days)**|**Inpatient**<br>**admissions,**<br>**per 100 people**|**Outpatient contacts,**<br>**per person per year**|
|Albania|-|6.4|8.7|1.5|
|Bosnia and|-|9.6|8.2|3.3|
|Herzegovina|||||
|Serbia|69%*|10.6|12.0|-|
|Montenegro|69.7%*|9.8*|10.7|6.9|
|Macedonia, FYR|55.5%|11.1|9.9|4.3|
|Kosovo|-|-|-|-|
|Croatia|88.1%|10.3|16.6|6.9|
|Slovenia|70.1%|7.1|17.6|7.2|
|EU|75.9%|9.3*|18.1*|6.8*|
|EU-15|-|9.6**|17.5**|-|
|EU-12|74%|8.03|20.8|7.9|

Source: WHO HFA-DB, 2007, except for Serbia and Montenegro (World Bank estimates) Note: Data are for 2005, unless denoted by an * for 2004 or a ** for 2003 With the exception of Macedonia, all countries have between 1 and 2 hospitals per 100,000 people compared to an average of 3 hospitals in the EU. Also, compared to the EU average of 585 beds per 100,000 population, the number of beds in the hospital sectors of the Western Balkans is 27
virtue.<sup>4</sup>

# **4 Existing Evidence on Community-Driven Development**

A growing empirical literature has arisen to evaluate the impacts of CDD programs on social capital. The central finding has been that the impact of these programs on social capital is mixed at best. Wong (2012) offers an in-depth review of 14 such programs. She concludes that while these programs do improve local public service delivery, they seem to have no impact on local social capital development. Similarly Mansuri and Rao (2013), in their extensive book-length study of participatory development programs, point to the difficulty that these programs have had in overcoming local collective action problems to increase citizen participation.

The most rigorous study to date, (Casey, Glennerster and Miguel, 2012), evaluates a World Bank program in Sierra Leone. It is an important study for at least three reasons. First, like ours it is a randomized control study. Second, the researchers used innovative behavioral measures of social cohesion they called “structured community activities.” Third, they archived a pre-analysis plan (PAP) that specified precisely which measures they would use to test their hypotheses, thereby making “cherry picking” of results impossible.<sup>5</sup> They

> 4Voors et al. (2012) also use lab-in-the-field techniques to show that preferences became more pro-social as a result of exposure to civil war violence.

> 5The nature of our involvement in the evaluation of the social impacts of the CDF did not allow us to develop and file a PAP. We were brought in quite late in the life cycle of the program and were charged only with devising and implementing better measures of the social capital (compared to standard survey measures) and using those measures to evaluate the social capital impacts of the program. Therefore while we did not have the opportunity to file a PAP, we are protected against the charge of cherry picking by the strict focus of our study on social capital as measured by our lab-in-the-field activities and networks survey.

14