rafmacalaba/datause-encoder-data huggingface dataset:
chosen so that the opening statement by the SPs would be consistent with multiple underlying illnesses, but further questioning should have led to an unambiguous (correct) diagnosis. This allows us to measure provider quality through adherence to an essential checklist of questions and examinations that would allow them to accurately make a diagnosis and provide a correct treatment. We also chose these cases since they represented conditions with high or growing incidence in India and other middle- and low-income countries and minimized risk to SPs that could arise from unsafe invasive examinations, such as a blood test with an unsterilized needle.

We also picked cases where the role of suitable medical advice was important because real patients would be unlikely to be able to categorize them as “life threatening” or “potentially non-harmful” and triage themselves into clinics or hospitals. For instance, the SP with unstable angina complains of chest pain which, even in countries with advanced health systems, is often mistaken by patients as arising from heartburn, exertion or muscle strain.<sup>13</sup> Similarly, wheezing and shortness of breath in asthma may arise from short-term allergies to environmental contaminants. Finally, for any child with diarrhea, a key contribution of a health care provider is to assess whether the symptoms reflect a bacterial or viral infection (and thus whether the patient requires antibiotics) and the degree of dehydration - each of which may be difficult for parents to assess.

# **3.2 Healthcare Provider Sampling and Summary Statistics**

Our study first uses the census of healthcare providers described earlier to construct a near representative sample of public and private healthcare providers in rural MP in three of the five sampled districts. While our SPs were recruited from the districts in our sample, they were never residents of the villages where they presented themselves to health providers. Since providers in rural areas might know their patients, the SPs had to justify their presence in the area by mentioning, for example, work-related travel or visits to relatives. For such excuses to be plausible, our final sample dropped villages that could not be accessed by paved roads and comprised of a total of 46 villages across three districts. While these sampled villages have more providers on average than the entire representative set of villages, there is no difference in the composition of providers across the frame and sample (Table 1).

Since SPs visited clinics to obtain primary care, we excluded community health workers, midwives, and providers that only made home visits. We sampled providers in all public clinics (up to two providers per clinic) and a maximum of six private providers in each market for a total of 247 providers in 235 clinics, and SPs completed interactions with 224

> 13The REACT study in the United States found that many chest pain patients delayed calling 911 because they confused their symptoms with heartburn (Faxon and Lenfant, 2001).

10
Tatyana Bogomolova, Gregorio Impavido, Montserrat Pallares-Miralles

**Figure 4: On average teacher wages slightly increase with age for both men and women**

<!-- Start of picture text --> 8,000<br>7,000<br>6,000<br>5,000<br>4,000<br>3,000<br>2,000<br>1,000<br>-<br>17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60<br>Age<br>Male Female<br>UGS (000')<br><!-- End of picture text -->

**Notes:** * Age and wage distribution for teachers (2003/04). **Source** : MOFPED.

# **_III.C  Information on the stock of retirees_**

The total number of beneficiaries in all categories is 15,813 and 11,567 for civil servants and teachers respectively. As previously mentioned, the individual records of the stock of beneficiaries did not specify who old-age pensioners were or who survivors were. An additional sample was used to separate pensioners by benefit category. The sample data were not segregated by gender and the age indicated in the records related to recipients of survivorship benefit referred to the age of the deceased employee/old age pensioner (not the survivor her/himself). All pensioners 45 years of age were assumed to be survivors. For pensioners older than 45 years, the share of survivors in each age cohort – derived from the sample – was assumed to be the same for men and women.

The number of survivors was estimated to be 2,292 among civil servants and 505 among teachers. Table 7 summarizes the estimated numbers of the stock of old age pensioners, their average age and pension for the base year of 2003/04. The number of active teachers is twice as large as the number of civil servants. However, the number of teacher retirees is somewhat smaller. This is due to the fact that the teachers sub-scheme is significantly younger following a recently introduced expansion in hiring policy. Teacher retirees are also on average slightly older than government retirees, and receive lower pensions due to their lower average wages.

- 32 -
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- David Bounie, Abel Franc ̧ois, and Patrick Waelbroeck. Debit Card and Demand for Cash. _Journal of Banking & Finance_ , 73:55–66, 2016. doi: 10.1016/j.jbankfin.2016.0. URL `https://ideas. repec.org/a/eee/jbfina/v73y2016icp55-66.html` .

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- David Bounie, Youssouf Camara, and John Galbraith. Consumers’ Mobility, Expenditure and Online- Offline Substitution Response to COVID-19: Evidence from French Transaction Data.

36
and discouraged assembler-supplier linkages. This set of problems in turn reflects government policies and institutions, which have themselves been a function of broader political pressures. _Market Fragmentation, , Inter-Firm Linkages, and Parts Firm Capacities_ Auto assembly in Indonesia exhibits a combination of foreign influence, corporate concentration and brand / market fragmentation. Japanese brands dominate the market, with Toyota, Mitsubishi and Suzuki accounting for roughly three quarters of the total market (Toyota accounted for 28% of all car sales in 2003). Until recently, the assembly of various brands came under the purview of a small number of Indonesian business groups, of which three (Astra, Indomobil, and Krama Yudha) controlled "brand holder sole agents" accounting for 90% of vehicles assembled (SICCI 2002: 6). These brand holders were selected for their political influence rather than their manufacturing capacities, and prior to 1999, they were authorized by the government to import, produce, sell, or export cars. Brand holders were also allowed to procure licenses for the production of major components. As a result, Indonesian components production is dominated by Japanese-affiliated firms operating within particular brand holders. According to Japanese data, 76 of the country's 158 component producers were Japanese affiliates.<sup>9</sup> In the late 1990s, the largest brand holder, Astra, accounted for 23 of the 158 component firms and 15 of the Japanese joint ventures. Astra is the only brand holder to have procured _all_ functional components internally, but other groups have followed this pattern of vertical integration with regard to component production (“Post crisis condition of automotive component industry," 2002).

Two features of this arrangement discouraged the growth of parts manufacturing capacity. The first involves market fragmentation and weak scale economies. Major brand holders controlled multiple brands and assembly operations, with one group assembling BMW and Daihatsu, another producing Mercedes and Hyundai. There was, moreover, "little apparent

> 9 Unless noted, data on the structure of components producers is drawn from Ito 2003: 9

56
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# **Assessing the Longer Term Impact of Community-Driven Development Programs: Evidence from a Field Experiment in the Democratic Republic of Congo***

Eric Mvukiyehe (World Bank Research Department) Peter van der Windt (New York University – Abu Dhabi)

**Keywords** : Community Driven Development, Service delivery, Social cohesion, Economic development, Field experiment, Congo.

# **JEL codes:** C93, D02, P48

* We thank Marie-France Guimond, Macartan Humphreys, Ann Laudati, Guillaume Labrecque, Helen Poulsen, Dana Olds, Daniel Rogger, Sarah Furrer and Maarten Voors. We thank our 94 enumerators, Alain Manda, Félix Toshibangu, Fils Likuta, Justin Kalombo, Christian Kalombo, Eustache Kuliumbwa, Summer Lindsey, Patrick Milabyo and the late Jean Paul Zibika for in-country work. Thanks to Han Il Chang, Laura Moreno and Nausheen Khan for research assistance. We acknowledge financial support from DFID, the World Bank and NYU Abu Dhabi. This study has been pre-registered at: http://egap.org/registration/1773 (deviations can be found in Appendix H). IRB approval from Wageningen University. Computational reproducibility verified by DIME Analytics.
Victor Lavy and Analia Schlosser. Mechanisms and Impacts of Gender Peer Effects at School. _American Economic Journal: Applied Economics_ , 3(2):1–33, April 2011. URL https: //ideas.repec.org/a/aea/aejapp/v3y2011i2p1-33.html.

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46
|Gulf of Gabes Marine and Coastal Resources Protection Project|TaoufiqBennouna|
|---|---|
|Gulf of Gabes Marine and Coastal Resources Protection Project|TaoufiqBennouna|
|Gulf of Gabes Marine and Coastal Resources Protection Project|TaoufiqBennouna|
|Gulf of Gabes Marine and Coastal Resources Protection Project|TaoufiqBennouna|
|Gulf of Gabes Marine and Coastal Resources Protection Project|TaoufiqBennouna|
|Gulf of Gabes Marine and Coastal Resources Protection Project|TaoufiqBennouna|
|RURAL FINANCIAL SERVICES PROJECT|Christopher Paul Jackson|
|RURAL FINANCIAL SERVICES PROJECT|Christopher Paul Jackson|
|RURAL FINANCIAL SERVICES PROJECT|Christopher Paul Jackson|
|RURAL FINANCIAL SERVICES PROJECT|Christopher Paul Jackson|
|RURAL FINANCIAL SERVICES PROJECT|Christopher Paul Jackson|
|RURAL FINANCIAL SERVICES PROJECT|Christopher Paul Jackson|
|RURAL FINANCIAL SERVICES PROJECT|Christopher Paul Jackson|
|RURAL FINANCIAL SERVICES PROJECT|Christopher Paul Jackson|
|RURAL FINANCIAL SERVICES PROJECT|Christopher Paul Jackson|
|RURAL FINANCIAL SERVICES PROJECT|Christopher Paul Jackson|
|RURAL FINANCIAL SERVICES PROJECT|Christopher Paul Jackson|
|Kosovo Post-Conflict Fund Budget Support(Social)|Saumya Mitra|
|Kosovo Post-Conflict Fund Budget Support(Social)|Saumya Mitra|
|Economic Assistance Project|Saumya Mitra|
|Economic Assistance Project|Saumya Mitra|
|Pilot FisheryDevelopment Project|John W. Fraser Stewart|
|Pilot FisheryDevelopment Project|John W. Fraser Stewart|
|Pilot FisheryDevelopment Project|John W. Fraser Stewart|
|Pilot FisheryDevelopment Project|John W. Fraser Stewart|
|Pilot FisheryDevelopment Project|John W. Fraser Stewart|
|Pilot FisheryDevelopment Project|John W. Fraser Stewart|
|Pilot FisheryDevelopment Project|John W. Fraser Stewart|
|Pilot FisheryDevelopment Project|John W. Fraser Stewart|
|Pilot FisheryDevelopment Project|John W. Fraser Stewart|
|Pilot FisheryDevelopment Project|John W. Fraser Stewart|
|LGU Urban Water and Sanitation Project APL2|Christopher Casuga Ancheta|
|LGU Urban Water and Sanitation Project APL2|Christopher Casuga Ancheta|
|LGU Urban Water and Sanitation Project APL2|Christopher Casuga Ancheta|
|LGU Urban Water and Sanitation Project APL2|Christopher Casuga Ancheta|
|LGU Urban Water and Sanitation Project APL2|Christopher Casuga Ancheta|
|LGU Urban Water and Sanitation Project APL2|Christopher Casuga Ancheta|
|LGU Urban Water and Sanitation Project APL2|Christopher Casuga Ancheta|
|LGU Urban Water and Sanitation Project APL2|Christopher Casuga Ancheta|
|LGU Urban Water and Sanitation Project APL2|Christopher Casuga Ancheta|
|LGU Urban Water and Sanitation Project APL2|Christopher Casuga Ancheta|
|StrengtheningCivil SocietyInvolvement in Assessingthe National|EcChukwudi H. Okafor|
|StrengtheningCivil SocietyInvolvement in Assessingthe National|EcChukwudi H. Okafor|
|StrengtheningCivil SocietyInvolvement in Assessingthe National|EcChukwudi H. Okafor|
|Economic and Public Sector Reform Credit Project|Frederick Kilby|
|Economic and Public Sector Reform Credit Project|Frederick Kilby|
|Economic and Public Sector Reform Credit Project|Frederick Kilby|
# **Ill. New Waves of Liberalization in the Mid 1980s and the Early 1990s-Trend Acceleration in Speed of Trade Integration?**

The 1991 inaugural issue of the World Bank's _Global Economic Prospects and the Developing Countries (GEP91)_ stated that:" All through the period 1950-90, intemational trade grew faster than output. The rapid growth of world trade in the 1950s and 1960s was due partly to a recovery from the stagnation of the interwar years. It was spurred by buoyant growth in industrial countries, reduced barriers to trade, low world inflation, modest real rates of interest, and expanding real resource transfers to developing countries. But many of these trends were reversed in the 1970s and 1980s. The growth of international trade slowed markedly and the gap with world output growth narrowed... Progressive liberalization of trade policies between 1947 and 1974 helped. Average tariffs in industrial countries fell from about 40 percent to 3 percent... The forces for trade liberalization have weakened since the mid 1970s, when industrial countries began to establish new barriers to trade. By 1986, almost 16 percent of OECD imports were covered by nontariff barriers... The protectionis **t** rend in developing countries has been similar. Analysis of a sample of 82 developing countries in 1987 revealed that 28 percent of all imports were subject to nontariff barriers...

Looking back, however, there was a marked acceleration in world integration through trade again in the mid 1980s, as is highly visible in Chart 12. Measured by a ratio of trade to output, this meant a reversal in the trend in trade integration for OECD, which had been slowed by the macroeconomic instabilities and heightened nontariff barriers in 1970s and early 1980s. For LMIC as a whole, a rising trend in trade integration was a rather new phenomenon. In fact, out of the 16 percent rise in LMICs' trade integration ratio (trade/GDP) in the past three decades or so, a 15 percent surge was observed only after the mid 1980s. A series of reform and liberalization efforts enabled LMIC to vigorously take part in the world market. Emerging LMIC markets, a decline in commodity prices, a surge in foreign investment activities after the Plaza accord, and a series of bilateral and regional trade arrangements such as an expansion of the EU and the US-Canada free trade agreement, put OECD economies back on an accelerated integration path.

_l Global Economic Prospects and the Developing Countries 1991, p. 9._ 19
policy of “slum declaration.” Similar policies are implemented under the name of “slum notification” in other parts of India, as well. This formalization of land tenure differs from common titling programs that provide full property title; slum declaration only guarantees the occupancy of slum residents and their entitlement to basic services. Even in formalized or “declared” slums, people have no legal basis in other bundles of property rights, such as the right to develop, inherit, sell, lease, or mortgage their houses. This characteristic of slum declaration offers a researcher an opportunity to examine whether the legal assurance of occupancy rights, rather than the provision of a full bundle of property rights, can benefit slum dwellers.

For the empirical investigation, this paper assesses the slum residents’ willingness to pay for the benefits of slum declaration. Applying a generalized spatial two-stage least square (GSTSLS) model developed by Kelejian and Prucha (1999) and Kelejian and Prucha (2010), this paper develops a spatial hedonic model to identify and estimate the premium captured in housing rent in the informal housing market. Accounting for spatial autocorrelation and heterogeneity, as well as a host of housing, slum, and locational characteristics, the model makes it possible to reveal the tenure security premium associated with slum declaration status. Based on the identification strategy proposed by Bajari and Benkard (2005) and Bajari and Kahn (2005), this paper then explores the heterogeneity of the estimated marginal willingness to pay (MWTP) depending on household characteristics.

This paper draws on rare datasets that help to adequately take into account the legal, social, political, and geographical factors that are deeply embedded in the local contexts. The primary data source is a household survey conducted by the author in 2013. The surveys were collected from 562 slum households that represent the slum households in the entire city of Pune. This paper also retrieves slum-level information from the _Pune Slum Atlas_ , prepared by the Maharashtra Social Housing and Action League, or MASHAL (MASHAL, 2011), and combines it with the household survey data. The dataset, constructed in this way, contains information about detailed housing, households, and slum and locational characteristics.

The series of analyses performed in this paper clarify that even in the presence of other legal and non-legal factors, slum residents highly evaluate the benefits from slum declaration as to what improves their tenure security. The hedonic analysis reveals that slum declaration status is associated with approximately 19% of the average housing rent in Pune’s slums. The estimation result is robust against a bias stemming from spatial effects and selectivity in survey responses. The calculated MWTP is 600 Indian rupees, which is equivalent to approximately 6% of the average monthly expenditure of slum households in Pune. This is a strong premium, considering that a majority of slum residents enjoy _de facto_ tenure security to some degree, as demonstrated by their fairly long average duration in their current 3
<!-- Start of picture text --> Figure 4: Routine & Non-Routine Employment<br>(A) Effective Employment (B) Importance of Non-Routine Labor<br>Routine (Effective Units)<br>Routine (Raw CPS)<br>Non−Routine (Effective Units) Raw (CPS)<br>Non−Routine (Raw CPS) Effective Units<br>1970 1980 1990 2000 2010 1970 1980 1990 2000 2010<br>Year Year<br>140<br>150<br>120<br>100<br>100<br>Employment (Mio.)<br>50 NR/R Employment (%)<br>80<br>60<br>0<br><!-- End of picture text --> _Notes:_ Panel A plots employment levels in routine and non-routine jobs as reflected in the CPS. The graph plots both the raw CPS numbers as well as our imputed “effective” units based on equations (4) and (5). Panel B illustrates the relative importance of non-routine jobs.

frictionless world, an “effective unit” of labor needs to be paid a fixed wage _wt_ and therefore, the ratio of non-routine to routine labor in effective units is given by where _er,t_ and _enr,t_ are effective units of labor embodied in routine and non-routine workers, respectively. Panel B of Figure 4 illustrates the time path of this ratio, revealing that non-routine labor inputs have increased relative to routine labor inputs, both in terms of raw labor and in terms of effective units of labor.

For our calibration exercise, it will be useful to construct the time paths of routine and nonroutine labor in effective units, as well as a sequence of real wages per effective unit of labor. We obtain an estimate for _wt_ directly from regression model (1). To do so, we normalize _Xit_ such that _Xit_ = 0 corresponds to our “reference worker”: a 19-year-old, white, male, full-time, routine, manufacturing worker with a high school degree, who works 50-52 weeks per year. This allows us ˆ to interpret our estimated constant in regression (1) as the baseline wage, that is _wt_ = _β_<sup>ˆ</sup> 0 _,t_ . Figure 5 illustrates the resulting baseline real wage series and we note that our estimates are in line with a vast literature in labor economics that finds stagnating real wages for the “middle class” starting 11