rafmacalaba/datause-encoder-data huggingface dataset:
The third column of Table 2 additionally controls for the log number of qualitative articles. The SPI overall scores are still statistically significant at the 5% level, as is country population. Column 4 examines the relationship with one of the pillars of the SPI, data sources, which covers the availability of recent censuses, surveys, academic data, and geospatial data. The data sources index from the SPI is also correlated with data use in academia, conditional on log GDP, population, and the number of qualitative papers. Similar regressions using the other pillars of the SPI, such as data services and data infrastructure are not associated with the number of articles using data in a similar regression, suggesting that it is the availability of particular data sources that is helpful in boosting academic data use.

_Table 2. Relationships between Number of Papers Using Data and Statistical Performance_

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
|(Intercept)|-12.41***|-10.66***|-3.96***|-3.57**|
||(0.82)|(0.95)|(1.14)|(1.17)|
|Log GDP per capita|0.58***|0.36***|0.12+|0.10|
||(0.05)|(0.07)|(0.07)|(0.08)|
|Log Population|0.70***|0.63***|0.29***|0.29***|
||(0.03)|(0.04)|(0.05)|(0.05)|
|SPI Overall Score||0.02***|0.01*||
|||(0.01)|(0.01)||
|Log Qualitative Papers|||0.64***|0.65***|
||||(0.08)|(0.08)|
|SPI Data Sources Score||||0.01*<br>(0.00)|
|Observations|168|168|168|168|
|R2|0.751|0.774|0.852|0.852|
|R2 Adj.|0.748|0.770|0.849|0.849|
|AIC|414.8|400.1|331.1|330.7|
|BIC|424.2|412.6|346.8|346.3|
|RMSE<br>_Note:_GDP, population and S|0.82<br>PI data are retr|0.78<br>ieved from th|0.63<br>e World Ba|0.63<br>nk's World|

_Note:_ GDP, population and SPI data are retrieved from the World Bank's World Development Indicators. Regressions include all papers using data from 20172019. Standard errors are robust to heteroskedasticity. ***=0.001 level, **=0.01 level, *=0.05 level, +=0.1 level.

Using more detailed data from the SPI makes it possible to assess how the availability of specific data sources relates to academic output. Figure 6 shows the linear regression coefficient for the availability of each of the ten data sources considered by the SPI, conditional on log GDP per capita, log population, and log of qualitative papers. The ten data sources include: population census, agriculture census, business/establishment census, household consumption/income survey, agriculture survey, labor force survey, health survey, business/establishment survey, civil registration and vital statistics system (CRVS), and geospatial data at the Admin 1 (usually province/state) level.

14
<mark>Effectiveness of the intervention was evaluated using an RCT. Following the baseline survey, recruited participants were randomized into intervention (n=118) and control (n=117) groups by an independent researcher. The intervention group received cash grants plus the 5 weekly face‐ to‐face group sessions of the PM+E training intervention, while the control group received cash</mark> grants only.

# 5.4 Descriptive Statistics at Baseline

<mark>Majority of the participants (95 percent) were male and married (90 percent), with around 11.3 years of education on average. Average household income was PKR 101,291 (US$ 725), and average number of dependents was 10. Fewer than half of the entrepreneurs (40 percent) received funding from ERKF during the first round of ERKF cash grants (1 year before the intervention), while the remaining received grants during the second round (6 months before the intervention). The largest proportion of firms owned by these entrepreneurs (36 percent) belonged to the service sector, followed by manufacturing, retailing, etc. Most firms (87 percent) were microenterprises (that is, having full‐time employees of ≤ 20). Overall, the sample selected</mark> was representative of the larger population of ERKF grantees.

<mark>Tables 1‐3 below show the demographic, business, and psychological characteristics of participants across the treatment and control groups at baseline. Demographic characteristics of participants across the treatment and control groups were well balanced at baseline. Psychological indicators at baseline suggest that 1 in 3 to 4 entrepreneurs were experiencing mild to severe symptoms of depression or anxiety at baseline (i.e. PHQ‐ADS score of 10 or higher). These were balanced at baseline. Participants in the treatment group appear to have marginally higher well‐being scores at baseline, with the difference statistically significant at the 10% level.</mark> Table 1: Demographic Characteristics of Participants

|||Control|Tre|atment|t‐test|
|---|---|---|---|---|---|
|Variable|N|Mean/SE|N|Mean/SE|p‐value|
|Male|117|95.7%|118|94.1%|0.566|
|||[0.019]||[0.022]||
|Age (years)|116|42.9<br>[0.987]|118|42.2<br>[0.992]|0.604|
|Married|117|90.6%<br>[0.027]|118|88.1%<br>[0.030]|0.542|
|Education (years)|117|11.6<br>[0.329]|117|11.0<br>[0.418]|0.298|
|No. of dependents|109|10.5<br>[0.642]|113|9.5<br>[0.882]|0.372|
|Household income (PKR)|101|109,485<br>[12,880]|102|93,176<br>[9712]|0.312|
|ERKF Round 1|117|41%<br>[0.046]|118|38.1%<br>[0.045]|0.6522|

_Note:_ Standard errors in brackets. The values displayed for the t‐tests are the p‐values of difference across the groups. ***, **, and * indicate significance at the 1, 5, and 10 percent levels, respectively.

Source: Saraf, 2019; World Bank Group, 2018 13
<!-- Start of picture text -->
[o)<br>+<br>iS<br>a Om<br>nO =<br>55<br>72°<br>oes<br>raow<br>os<br>c<D) no<br>~8&°<br>FS<br>TC<br>Cc<br>><br>oO<br>1 a 2. 3 4 5<br>Quintiles of difference in share of riders who are male<br>(public - reserved space)<br>[EN 11 Low-level users Es 2<br>ME 13 High-level users<br><!-- End of picture text -->
- ii. Air: lead in environment comes from industrial emissions, smelters and refineries

- iii. Dust and soil: dust and soils can be significant sources of lead exposure, especially for young children. Lead in soil can come from the air or from erosion of lead bearing rocks and may be carried indoors as dust.

- iv. Water: lead can enter the water supply from lead solder in the plumbing or lead pipes in the house.

- v. Paint: most indoor and outdoor paints contain substantial amounts of lead. Most paint companies in large cities have eliminated lead from their products, although lead in paints might still be prevalent in rural areas.

- vi. Inexpensive, horizontal PVC mini blinds.

- vii. Leaded crystal is widely used for serving beverages. When the crystal comes in contact with the beverages, especially acidic beverages such as port, wine and fruit juices, some lead dissolves into the liquid.

- viii. Lead fumes are released when waste oil, colored newsprint, battery casings or wood covered with lead paint are burned.

Thus, while India has been phasing out lead in gasoline since 2001 there are a number of other sources that are not still controlled. Therefore it will be quite some time until the lead phase-out policy brings significant results. Roy et al (2009) in a special study about lead phase out report that measured lead blood levels are still high in the Indian population.

Some of the studies of BLL in India date back to 2003 and the average BLL do not reflect the recent phase-out program of lead in gasoline. While there is great uncertainty about how much BLL will decline due to the on-going lead phase-out program, international experience indicates that a program over a five-year period could lead to a 40 percent reduction in BLL under a complete phase out.

As there is great uncertainty about current BLL in the urban population as a whole (and the rural population), it is necessary to undertake new studies of BLL in children and adults to provide a more accurate estimate of health effects and their costs taking into account the gradual lead phase-out in India.

# **IV    Water Supply, Sanitation and Hygiene**

The main health impacts of unclean water and poor hygiene are diarrheal diseases, typhoid and paratyphoid. In addition there are costs in the form of averting expenditures to reduce health risk. Diarrheal and related illness contributes the dominating share of the health cost. We consider these in turn.

# **_4.1 Diarrheal Diseases, Typhoid and Paratyphoid_**

WHO has proposed a rigorous methodology<sup>11</sup> that links the access to improved water supply, safe sanitation, and hygiene to diarrheal illnesses (mortality and morbidity of children under 5) and other population morbidity based on an extended meta-analysis of peer reviewed

> 11 Fewtrell, L. and J. Colford Jr. (2004).

15
The reporting of the self-employed who are working in a fixed location outside their homes is much less sensitive to the reference period. They did not report working significantly more often and did not report working more days and hours when they were interviewed three times a week instead of once a week. They did report working fewer days and hours conditional on reporting any work, but the difference with self-employed workers who were working from their homes is not statistically significant. Put simply, it seems that the sensitivity of the self-employed to survey mode is driven by those working at home or in mobile places of employment.

In the appendix we explore heterogeneity among the wage employed, dividing them into formal and informal workers. While appendix table D4 indicates that differences in the impact of survey mode and the reference period across these groups are generally not statistically significant, the point estimates suggest a similar pattern as in the results comparing self-employed with and without a fixed place of employment outside their home: there is some evidence that informal wage workers reported more employment than formal ones when the reference period was shortened.

# **7. Conclusion**

A randomized survey experiment was conducted in urban Ghana to assess the impact of reference period and survey modality on reported labor market statistics. Interviewing people over the phone instead of in person reduced the reported incidence of employment by 8 percent, the number of days worked by 0.6 and the number of hours by 7, on average. These results mask marked heterogeneity in reporting across different types of jobs. Phone effects are concentrated among the self-employed who work from home or have a mobile place of employment. They are insignificant for the wage employed and for the self-employed who work outside of their homes in a permanent structure.

Shortening the reference period from one week to two days (by means of two separate 24hour recall questions) also has different impacts on the wage workers versus the self-employed; survey participants who reported their labor market activity three times a week reported significantly more self-employment spells than those reporting only once a week, but they did not report more wage employment. These effects are particularly pronounced among self-employed 17
gons were finely drawn to circumscribe built-up areas and are highly accurate for the time period of interest. Throughout our analysis we assign a pixel’s value to a Palestinian location if the pixel’s centroid lies within 500 meters of the location’s polygon. This “generous” assignment rule allows for potential geolocation errors in both ArcGIS’ under-the-hood projection of NTL data from WGS-1984 coordinates to UTM-36N, and for shifting error in the NTL data themselves (Tuttle et al., 2013).<sup>15</sup> Summing up the DNs of all assigned pixels per location, we find that the brightest three towns in 2006 were Hebron (3577 counts), Nablus (2309), and Ramallah (1830).

Potential truncation of DMSP-NTL imagery can arise because of topcoding. Based on 1970s technology, DMSP satellites were only equipped to record up to 6 bits of information per pixel, rendering DNs of 0 to 63. Moreover, the gain setting was typically quite high in order to detect faint light sources. When the satellite viewed bright urban sources, it often topcoded (maxed out at 63). The overwhelming majority of West Bank Palestinian locations were too dim to suffer from this problem, but few neighborhoods in the greater Jerusalem area (Bethlehem, Ramallah) are topcoded for most years. As a result, we cannot tell for most of these locations if they grew brighter or dimmer; they report 63 for most or all of their pixels. As described below, we perform robustness checks to guard against the influence of these topcoded locations on our results. Most importantly, parallel to the topcoded DMSP-NTL series, NOAA also generated a ‘radiance-calibrated’ series for select years, including 2006 and 2010. The radiance-calibrated (RADCAL) series was constructed from a lower average gain setting, avoiding topcoding at the cost of introducing bottom-coding. We show that our main results survive when we use these non-topcoded data. The right-hand-side map of Figure 10 shows the RADCAL image captured by the F16 satellite for 2006, which illustrates that the bottom-coded setting does not pick up light emissions from dimly lit areas.

Another potential concern is that OLS sensors on DMSP satellites deteriorate over years in orbit, and that their average gain settings vary from year to year and satellite to satellite. As a result, the images of the West Bank in any two given years are not directly comparable. To facilitate interpretation of our graphs, however, we applied intercalibration parameters to make the data as comparable over time as possible. For topcoded imagery, we applied the parameters recommended in Wu et al. (2013). For non-topcoded imagery, we applied the parameters recommended in Hsu et al. (2015). In our regressions, we rely on year effects and locality fixed effects, as well as the use

> 15In a robustness check that we do not present to conserve space but is available upon request we experimented with using a more conservative assignment rule, where a pixel’s value is assigned to a location only if its centroid lies inside the polygon. The results obtained using this alternative assignment rule are very similar to the ones presented in the main text.

23
size, work experience, monthly earnings, and so on. The fixed effects vector _τ_ usually includes randomization strata fixed effects, and, for the Nairobi microfranchising specifications, also survey enumerator and survey month fixed effects.

We estimate equation (2) separately for the outcomes of self-employment and migration. The parameter _β ITT_ provides the causal impact of the entrepreneurship proEach of these was chosen for inclusion on the basis of gram. programs having a significant impact at some point in time on self-employment, and so we expect to see significant impacts for this outcome. When we consider migration as an outcome, we are then estimating the causal impact of programs intended to increase self-employment on migration. We also provide migration-self-employment elasticities, which are the ratio of the impact on migration to the impact on self-employment. This is estimated via 2SLS regressions, in which migration is the main outcome and self-employment is instrumented with treatment status. We do not interpret this as necessarily giving the causal impact of self-employment on migration, since some of the programs considered could influence migration even without affecting self-employment (e.g. grants to the business could be instead spent on funding migration), which would violate the exclusion restriction for instrumental variables. Moreover, these programs could influence migration in different directions for different people, potentially violating the monotonicity assumption needed for IV to identify a local average treatment effect of self-employment.

# _Impacts of self-employment assistance programs on self-employment and migration_

The impacts of each program on self-employment and migration are shown in table 3. Table 4 instead considers whether these also affected the likelihood of programs being employed at all (whether in self-employment or other paid work), and this relationship with migration. Both tables are divided into two parts. Part 1 presents results from studies for which we could not distinguish between short-distance versus medium/long-distance migration, while part 2 provides evidence from studies that allowed us to isolate respondents moving further away from baseline location.<sup>16</sup> The first randomized experiment we consider for the subset of studies that include short-distance migration is the Uganda Youth Opportunities Program (YOP) (Blattman et al., 2014, 2019). Groups of 10 to 40 people submitted proposals on how they would use a grant worth $7,500 on average ($400 per person) to learn and start an independent skilled trade. Applicant groups were screened by government offi16The different degree with which each study attempted to track movers for follow-up interviews is partly reflected in the large heterogeneity of attrition rates. Online appendix table A.6 briefly summarizes attrition rates for each study included in our analysis.

13
communications, financial, insurance, and business services, and in electricity and water with the strongest effect being that of financial, insurance, and business services. Our simulation exercise consists of generating 1000 random time-varying FDI penetration ratios for the four services, recomputing our services FDI linkage variable using those random ratios, and estimating the specification in column 5 of Table 1 1000 times, as in Keller (1998).<sup>33</sup> The average coefficient on the services FDI linkage obtained from this simulation exercise is positive but smaller than our estimates in Table 1 and it is insignificant suggesting that our estimated effect of services FDI on productivity growth of Chilean plants is not driven only by the stronger usage of services by some plants.

# **7. Heterogeneity in the Effect of Services FDI**

Our main findings concern the average impact of services FDI on plant productivity growth across all manufacturing industries. However, the evidence in Panel B of Table 4 suggests that the strength of that impact may differ across industries. We focus on one particular dimension of heterogeneity: the degree of product differentiation in the industry. One can argue that differentiated product industries are characterized by stronger product complexity (Berkowitz et al., 2006).<sup>34</sup> As such, it is likely that services needs are greater for differentiated product industries (Fink et al., 2002). Thus, productivity growth of plants in industries producing differentiated products may benefit more from services FDI. To test this hypothesis, we use the differentiated product

> 33 We draw random time-varying FDI penetration ratios for each of the four services sectors from a uniform distribution whose support ranges from 0 to the maximum FDI penetration ratio observed in our sample using the pseudo random number generator of the GAUSS software.

> 34 The authors argue that differentiated products have many characteristics that are difficult to stipulate in a contract, thus trade in such products benefits more from good dispute resolution and enforcement institutions.

28
-5-

market. To the Gulf states these were essentially offshore companies that were subject to few regulations or reporting requirements. When the market peaked in 1982 the equity base had reached $4.1 billion, half of which had been issued in the first six months of the year.

Following the expiration of the ban, 37 KSCCs capitalized at $2 billion A/ started up, and thess too began trading on the parallel market despite regulations that prohibited founders from selling shares before a three-year period of profitability. To skirt the law, letters of sale, rather than actual shares, were given to the buyer. Depending on how many times the shares were sold, buyers would accumulate sequential letters that wculd trace the sale back to the founder. The government accelerated the process during the boom years by reducing the maximum subscription amount to encourage small investors to establish firms, and in this way, spread the benefits of the stock market boom. New issues between 1979-82 in all markets totaled close to KD 2.2 billion, an increase in outstanding stocks of 373 percent. In 1982 the equity of the Gulf companies alone exceeded that of the listed Kuwaiti companies. The equity base of the entire parallel market (including KSCCs) was more than twice that of the Kuwaiti market . ._ _The Flrst Market Break._ In late 1976 the first major market break occurred; the annual ir.dex fell 18.7 percent, from 235.2 to 191.8, and volume dropped 66 percent. The government intervened to avert a crisis by suspending the establishment of new shareholding companies and increases in the capital of existing companies. The rationale was that the pace of new equity issues was affecting domestic liquidity and had contributed to precipitating the crisis. The government stepped in to support the market by purchasing shares at a floor price. From December 1977 to April 1978, the government bought about KD 150 million in shares. The Central Bank of Kuwait (CBK) intervened to address possible repercussions to the banking system by effectively setting up a purchasing facility for any bad debt as a result of bank lending to share dealers or against security of shares. The facility, however, was not used by any bank. The market recovered toward the end of 1978 and both markets remained steady until 1981, when strong bull market effectively started. The Kuwaiti share index moved from 331 in the first quarter of 1981 to 523 in the second quarter of 1982 (see figures 1 and 2). The Gulf index moved from 120 to 235 from September 1981 to March 1982 (see figures 3 and 4).

i/ Ibid.

2/ See Statistical Appendix 8 and 9.