rafmacalaba/datause-encoder-data huggingface dataset:
toilets is electronically transferred to the bank accounts of beneficiaries, reducing the chances of corruption.

The project interventions are likely to expand toilet coverage and reduce open defecation in Punjab. This will reduce the fecal contamination of soil and water, which in turn will reduce the possibility of diarrheal and STH infections and have a positive effect on children’s nutritional outcomes. It is important to note, however, that these expected health and nutritional benefits take time to materialize and capture.

So, the expected benefits of the project can be categorized into two groups based on their time horizons. In the short run, we expect an improvement in people’s awareness and practice of hygienic behaviors, an increase in the number of households with toilets, and a reduction in the number of people defecating in the open. In the medium to long run, we expect a decrease in cases of diarrhea and an improvement in nutritional outcomes (that is, a decrease in stunting, wasting, and being underweight) in children younger than five years. In this study, we will explore the short-term impacts of the project.

# 4. Evaluation Design and Methodology

The evaluation used a multiple-arm cluster-randomization design with three treatment arms and one control group to establish causal impacts of the project interventions. The project is delivered at the GP level and the project interventions are aimed at influencing hygiene and sanitation behavior as well as health and nutritional outcomes of the entire community. So, the cluster randomization was done at the GP level. Considering the District Sanitation Committee’s pivotal role in project implementation, the randomization has been stratified at the district level. Of the three treatment arms, treatment arm 1 included GPs that received regular project interventions. In GPs in treatment arm 2, intensive hygiene and sanitation awareness campaigns were carried out in schools (alongside regular project interventions). Treatment arm 3 included GPs where there was an intensive follow-up campaign (in addition to the regular project interventions). Project interventions were withheld in the control GPs. The evaluation used surveys at the household, community, and school levels to collect data on both the project’s beneficiaries and its implementation. Baseline data are from before the start of project’s intervention, and these are compared with midline data, collected after the completion of project interventions, to assess the short-term outcomes of the project. A follow-up survey is expected to be carried out in 2021, toward the end of the project, to assess its medium-term impacts.

## 4.1 Sample Size and Sampling Strategy

As per the original design, there were 50 GPs per arm or group, and 24 households per GP, leading to a total sample size of 200 GPs and 4,800 households. However, there is a distinct possibility that some of the control GPs could have, in fact, received interventions (most likely for political reasons), while 12
7. Optimism on economic prospects and the sustainability of the strong growth performance also emanated from the fact that the volatility of the business cycles in advanced industrial countries had been declining (Figure 2). On the one hand, recessions had a less severe overall impact and were of shorter duration. For example, the 1987 stock market crash in the U.S. did not cause a recession; also, the 1990–91recession was relatively short and shallow. Similarly, the burst of the ―dot-com‖ bubble had a relatively limited effect in the form of a mild recession and a sluggish recovery. On the other hand, expansions lasted longer. This success in stabilizing the business cycles has been referred to as the ―Great Moderation‖, defined as an era of low inflation, high growth and modest recessions.<sup>10</sup>

**Figure 2: Standard Deviation of U.S. Gross National Product Growth**

<!-- Start of picture text --> 10%<br>9%<br>8%<br>7%<br>6%<br>5%<br>4%<br>3%<br>2%<br>1%<br>0%<br><!-- End of picture text --> Sources: Bureau of Economic Analysis; National Bureau of Economic Research, "The American Business Cycle: Continuity and Change," edited by Robert Gordon.

8. The ―Great Moderation‖ was considered to be the result of several developments: for one, business and financial deregulation as well as financial innovation had created a more flexible and adaptable economic system. Financial assets were considered to be less risky than before, giving rise to higher levels of financial intermediation which in turn helped fuel growth as well as greater financial innovation, especially through hedge funds. Volatility of business cycles had also declined because the world experienced abundant liquidity—partly reflecting surplus savings in a number of emerging markets—giving the false sense that stability was due to some structural improvement in the financial system. Also, growing globalization and free trade, partly

> 10 The term “Great Moderation” was coined by James Stock and Mark Watson (2002):  “Has the Business Cycle Changed and why?”

5
of seasonality specific to each of the 24 coastal provinces. _εcpmy_ represents idiosyncratic standard errors clustered at the province-level.<sup>22</sup> The estimated coefficients of interest in Equations (1) and (2) are _α_ 1 and _β_ 1, which measure the differential changes in fishery earning (Equation (1)) and fishing intensity (Equation (2)) after _Formosa_ , in the central coastal provinces (i.e. the treatment zone) relative to the unaffected provinces.

# **4 Overall Impacts of** **_Formosa_**

In this section, we present the empirical results from estimating the impact of _Formosa_ on the affected fishery communities. We separately investigate the damages caused to fishery earnings and employment, as well as to fishing intensity in the region. Using LFS, we estimate a massive and significant reduction to fishery income. This evidence is corroborated with a clear decline in both fishing prevalence and intensity, as measured by VIIRS satellite data of night-time boat detection. Finally, we probe our findings with a series of validity and falsification tests, from which we observe no “hypothetical” effects of _Formosa_ on the unaffected provinces and/or industries, or before the accident actually took place.

## **4.1 Impact on labor outcomes in saltwater fisheries**

Table 2 presents the DiD estimates for our primary indicator of economic well-being – fishery monthly incomes. We consider two earning measures: (1) monthly income from the primary occupation (columns 1 and 3) and (2) total monthly income from all sources (columns 2 and 4). In all regressions, the treatment group consists of pre-event saltwater fishers located in the affected provinces of Ha Tinh, Quang Binh, Quang Tri, and Hue. As mentioned, we employ simultaneously two control groups in all subsequent regressions. In Panel A, the counterfactuals are pre-event fishers located in the unaffected coastal provinces. To avoid concerns related to potential spillover effects of _Formosa_ to nearby regions, we restrict the sample to only the southern provinces distant from Formosa, i.e. from Phu Yen to Ca Mau (see Figure 1). In Panel B, the counterfactuals are workers located within the _Formosa_ -affected region who were employed in non-affected industries. We purposefully

> 22 In a robustness exercise, we remove all observations in April 2016 in the regressions, since the actual start of _Formosa_ in April remains unclear. Our estimates are robust to the exclusion of April 2016 as a post-treatment month. Results are available upon request.

13
These findings are consistent with the finding presented in the previous section on facility selection, which shows that wealthier women are willing to travel farther to reach high‐level and high‐quality facilities.

# 6. Discussion

A growing body of evidence highlights the critical importance of quality of care for improving health outcomes in low‐ and middle‐income settings. Closing the gap between the health outcomes of the poor and wealthy will require not only increasing access for the poor, but also improving the clinical quality of the care they receive. In their analysis of data from 64 developing countries, Wagstaff, Bredenkamp, and Buisman (2014) find that progress on health service coverage has been considerably more pro‐poor than progress on health status; they hypothesize that the quality of health care is worse for the poor. Our study corroborates this hypothesis, at least for the DRC. In this paper, we demonstrate that socioeconomic differences in the quality of care are indeed substantial. Our analysis employs data collected through household surveys, direct clinical observations, and exit interviews. Although each individual source of data has its limitations in objectively measuring the quality of care, the combination of these data sources provides robust evidence on the existence of a wealth‐quality gradient.

The novel data that link health facilities to households in their catchment area as well as the content of care to price of consultations enables carefully disentangling the various mechanisms underlying the observed wealth‐quality relationship. Although spatial correlation between household wealth and quality of care accounts for more than half of the overall gradient, a statistically significant positive association between wealth and the quality of antenatal care also emerges when we compare women from the same village. This gradient appears to a large extent to be driven by differential sorting or selection into facilities. Empirically, better‐off women are more likely to leave their catchment area to seek care at more distant, higher‐level, or better facilities, where they pay higher prices for the consultations. Both findings imply that equality in quality of health care will not be achieved only through allocating more resources to poorer areas.

When we zoom into specific facilities, we find a within‐facility wealth‐quality relationship. This relationship appears to be partially explained by the fees many facilities charge separately for laboratory tests and drugs. We find a statistically significant quality‐price relationship even when including facility fixed effects in the regressions. It could be that poorer women choose to receive a more limited package of services, or that providers do not offer poor women services for which they would have to pay extra 16
**Table 6 Fitted output per worker in Russia for a worker with average home country HCI, 2011 US$ at PPP**

|Country of Migrant<br>Worker|Output per worker in<br>home country (2011<br>US dollars, PPP)|Output per worker in<br>Russia<br>(2011<br>US<br>dollars, PPP)|Difference between<br>output per worker in<br>Russia<br>and<br>home<br>country (2011 US<br>dollars)|
|---|---|---|---|
|Armenia|22,915|43,249|20,334|
|Georgia|22,522|44,497|21,975|
|Kyrgyz Republic|11,142|43,494|32,352|
|Tajikistan|13,786|42,034|28,248|

Sources: Output per worker, Penn World Tables; Fitted output in Russia, authors’ calculations The output per migrant worker is between double and three times more in Russia than it would be in the home country of the migrant worker. Most of the difference arises from the much higher capital stock per worker in Russia than in the migrant sending countries. Also note that the output per worker of migrants from each of the four sending countries is fairly similar. This is because the difference between the highest HCI (Georgia) and the lowest HCI (Tajikistan) of these four is only 15 percent and, given the coefficient of 0.4 on the log of HCI in the regression, this translates into a difference in output per worker of only 6 percent holding capital per worker constant. One might argue that, because capital per worker is the main determinant of output per worker, it does not matter how much human capital migrant workers have as long as they migrate to a country with a much larger capital stock per worker than their home country. But that ignores the fact that the human and physical capital are complements: a larger capital stock per worker will usually comprise more technologically sophisticated capital and this will require workers with more human capital to operate it.

We can infer two conclusions from the data in table 6. The first is that, as long as there are very large differences between what a worker, given his or her education and skills, can earn at home and abroad, powerful incentives for large-scale labor migration will continue. Secondly, given the magnitude of these differentials, especially in the Kyrgyz Republic and Tajikistan, it is unlikely that marginal gains to returns to labor in the domestic economy will have much impact in terms of reducing incentives for workers to migrate.

# **4. Aggregate Expenditure and the Structure of the Economy**

This section examines what happened to aggregate final expenditure and the structure of the economy in the remittance receiving FSU countries of CASC. We would expect that an increase in remittances as a share of GDP would be accompanied with an expansion of total expenditure, relative to output, and a shift in the structure of the economy towards the production of nontraded goods. Table 7 provides data on total expenditure alongside services value added, as a 8
# IX. **References**

Ashenfelter, Orley and R. Layard (1986), ed. _Handbook of Labor Economics, Vol. I_ (Elsiver Science Publishers).

Becker, Gary (1991). _A Treatise on the Family (Enlarged Edition)_ (Harvard University Press: Massachusetts).

Chant, Sylvia (1991) _Women and Survival in Mexican Cities: Perspectives on Gender, Labor Markets and Low Income Households._ Cunningham, Wendy and William Maloney (1998) _Heterogeneity among Mexico's Micro-Enterprises An Application of Factor and Cluster Analysis,_ Policy Research Working Paper 1999 (Washington, DC: The World Bank).

Davila, Enrique (1997) "Mexico: The Evolution and Reform of the Labor Market" in _Labor Markets in Latin America: Combining Social Protection with Market Flexibility_ Sebastian Edwards and Nora Lustig, ed., (Brookings Institute: Washington, DC), 292327.

Fleck, Susan (1983) _The Political Economy of Intrahousehold Resource Allocation: A Non-Cooperative Sequential Move Game_ (unpublished).

Gruber, Jonathan and Julie Cullen (1996) "Spousal Labor Supply as Insurance: Does Unemployment Insurance Crowd-out the Added Worker Effect?" NBER Working Paper #5608.

Haddad, Hoddinott, and Alderman (1997) _Intrahousehold Resource Allocation in Developing Countries_ (Johns Hopkins University Press: Baltimore).

Heckman, James and Thomas MaCurdy (1980) "A Life Cycle Model of Female Labour Supply" _Review of Economic Studies_ 48(47), 47-74.

Heckman, James and Thomas MaCurdy (1982) "Corrigendum on A Life Cycle Model of Female Labour Supply" _Review of Economic Studies_ 49(49), 659-660.

Khandker, Shahidur (1988) "Determinants of Women's Time Allocation in Rural Bangladesh" _Economic Development and Cultural Change_ 37(1), 111-126.

Lundberg, Shelly (1985) "The Added Worker Effect" _Journal of Labor Economics_ 3(1), 11-39.

Lustig, Nora (1992) _The Remaking of an Economy_ (Brookings Institute: Washington, DC).

Maloney, Tim (1991) "Unobserved Variables and the Elusive Added Worker Effect" _Economica_ 58(230), 173-187.

47
# **4.1 Data**

## **– 4.1.1 CPS US**

Our data for the United States come from the March supplement to the Current Population Surveys (CPS) for 1995 and 2007.<sup>9</sup> The dataset provides the distribution of labor earnings in the US in 1995 and 2007 for full-time workers of both genders. We use the following variables for our analysis. _Y_ denotes real hourly labor earnings (sum of annual pretax wages, salaries, tips, and bonuses, divided by the number of hours worked annually). The vector **_X_** consists of three covariates of _Y_ , namely: (i) the worker’s age in years; (ii) a gender dummy; and (iii) a categorical variable for the highest educational level attained (“high school”, “some college” or “college”).

We restrict the sample to individuals aged 16 to 65 that reported a positive value for real hourly earnings in the previous year. Individuals with missing values for any of the four variables in _Y_ and **_X_** were excluded from the sample. After applying these filters, we trimmed the sample by dropping the top and bottom 0.5% of the distribution of hourly wages in each year, to eliminate outliers. Hourly wages are in US dollars of March 2007. The Consumer Price Index was used to inflate 1995 incomes: nominal values in 1995 were multiplied by 1.36 to be expressed in 2007 dollars. The final sample contains a total of 165,245 observations. Summary statistics are presented in Table 1.

– Table 1: Summary Statistics US

||Mean|S.D.|Min.|Max.|Observations|
|---|---|---|---|---|---|
|CPS 1995||||||
|Hourly Work Earnings|16.730|11.402|1.047|74.162|69,494|
|Age|37.039|12.090|16|65|69,494|
|Male|0.527||||69,494|
|High School|0.333||||69,494|
|College Incomplete|0.295||||69,494|
|College|0.243||||69,494|
|CPS 2007||||||
|Hourly Work Earnings|19.626|16.748|1.202|168.280|95,751|
|Age|39.284|12.807|16|65|95,751|
|Male|0.525||||95,751|
|High School|0.305||||95,751|
|College Incomplete|0.291||||95,751|
|College|0.297||||95,751|

> 9http://www.census.gov/programs-surveys/cps.html

24
are partly due to the creation of a second pillar, and because the actuarial imbalances of the system were already being addressed by the reform.

**Table 1: Revenues, Expenditures and Balance of the PAYG, 1991-99 (in % of GDP)**

||1991|1995|1996|1997|1998|1999|
|---|---|---|---|---|---|---|
|**Contribution Revenues**|**11.0**|8.9|8.4|8.3|8.2|7.8|
|Pension Fund||7.5|7.1|7.0|7.0|6.8|
|Health Fund (disability)||1.2|1.1|1.1|1.0|1.0|
|**Pension Expenditures**|10.5|9.1|8.5|8.3|8.7|8.8|
|Old age||6.8|6.3|6.2|6.4|6.4|
|Survivor||1.1|1.0|1.0|1.1|1.1|
|Disability||1.2|1.1|1.1|1.2|1.3|
|PAYG Balance|0.5|-0.2|-0.1|0.0|_-0.5_|-1.0|
|Revenue loss to second pillar|||||0.3|0.6|
|Pure PAYG Balance<br>**Table 2: Base of Pay**|_0.5_<br>**roll Tax (%**|-0.2<br>**of GDP) a**|-0.1<br>**nd Contribu**|0.0<br>**tion Rates**|-0.2<br>**(%), 1991**|-0.4<br>**-98**|
||1991|1995|1996|1997|1998|1999|
|**Covered Wage Bill/GDP**|30.9|23.6|22.2|22.4|22.1|22.3|
|**Total Contribution Rate**|34.5|34.5|34.5|34.0|34.0|33.0|
|Pension Fund|30.5|30.5|_30.5_|30.0|31.0|30.0|
|Health Fund (notional)|4.0|4.0|4.0|4.0|3.0|3.0|

# _The Future of the PA YG System in the Absence of Reform_

Along with the rest of Europe, Hungary will experience rapid population aging in the next few decades, a development that will submit the pension system to great pressures. The impact of these adverse demographic trends in the absence of reforms was assessed through the use of an actuarial model developed during the reform.<sup>5</sup> The base year used for the actuarial projections is 1997-the year preceding the implementation of the reform. The main economic and demographic assumptions used in the actuarial projections are shown in Table 3.

**Table 3: Main Economic and Demographic Assumptions for Pension Simulations, 1997-2070**

<!-- Start of picture text --> 1998 1999 2000-2030 2000-2070<br>Economic Assumptions<br>Real GDP Growth 5.0 4.1 3.0 2.7<br>Real Wage Growth 3.5 3.5 3.0 3.0<br>Inflation Rate 14.3 10.0 3.4 3.0<br>Unemployment Rate 9.0 8.0 7.0 7.0<br>Demographic Assumptions<br>Population Growth -0.3 -0.3 -0.2 -0.3<br>Employment Growth 1.4 1.1 0.0 -0.3<br>Life Expectancy (Men) 65.1 65.0 71.8 76.4<br>Life Expectancy (women) 74.6 74.8 79.3 84.5<br><!-- End of picture text --> Note: Actual figures for 1998 and 1999. GDP growth is derived from wage growth. The labor share is assumed to remain constant. Life expectancy is years at birth, based on current mortality.

4Palacios and Rocha (1998) provide a more detailed analysis of the performance of pension revenues and expenditures during the 1990s.

The actuarial model was developed by Patrick Wiese.

4
19 When these countries attracted more FDI inflows, national saving, domestic investment, and the rate of economic growth all declined; hence FDI appears to have been immiserizing.

In contrast, the role of FDI in the Pacific Basin developing market economies has been benign. In these economies, FDI financial flows have not been close substitutes for other types of foreign capital flows. The insignificant effect of the current account financing requirement on FDI does indeed appear to indicate that FDI is autonomous rather than accommodating; it is matched by increased capital formation that is just as productive as domestically financed investment.

# **5** Incentive-Disincentive Packages **for** Foreign Direct Investment and Other Domestic Distortions

So far, the analysis has detected differential effects of FDI on rates of economic growth in two distinct groups of developing countries. Hence, this section analyzes this differential effect in more detail. As the World Bank (1991, p. 95) points out: " ... direct foreign investment in an economy with highly distorted policies is likely to generate net losses for the host country instead of welfare gains." Indeed, the theory of immiserizing growth might well apply most forcefully in the case of FDI simply because FDI that produces negative value added at world prices can be accompanied by the removal of resources in the form of repatriated profits.

This section presents a framework for examining the effects of distortions, including distortions created by the incentive-disincentive package, in the economy on the efficiency of FDI. It also suggests the possibility of some interaction between the incentive-disincentive package and other distortions in the economy on the efficiency of FDI. The empirical illustration, however, focuses solely on distortions in finance and trade, leaving empirical investigation of the incentive-disincentive package and interaction between the size of such package and other distortions on FDI efficiency for another study.

Venkataraman Balasubramanyam (1984, pp. 732-733) concludes that incentives for FDI are generally offered to offset " ... a complex web of controls and regulations." Saul Lizondo (1991, p. 79) also notes: "Incentives are seldom granted without conditions; instead, they are usually subject to the compliance of requirements that constitute disincentives to foreign direct investment." One might therefore consider sets of incentive-disincentive packages of varying sizes and complexity that all attract exactly the same quantity of FD!. In a neoclassical world, any package which maintains the quantity of **FDI** by offsetting constraints such as local content requirements or ownership limitations with incentives such as tax holidays