rafmacalaba/data-use-mentions-extended huggingface dataset:
MALI’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE and 2001 but fell by 0.5 percent of population per year between 2001 and 2006, during which the use of wells and boreholes increased by 2.4 percent of population per year.

**Table 8.  Expansion of safest water and sanitation technologies**

|a.Water|Population g<br>(per y|aining access<br>ear, %)|b. Sanitation|Population<br>(per|gaining access<br>year, %)|
|---|---|---|---|---|---|
||1996–2001|2001–2006||1996–2001|2001–2006|
|Piped water|0.79|0.55|Flush toilets|1.04|–0.57|
|Standposts|2.05|–0.51|Improved latrines|1.36|2.28|
|Wells/boreholes|–1.20|2.34|Traditional latrines|0.50|0.25|
|Surface water|0.24|–0.05|Open defecation|–1.18|0.32|

Source: WHO–Joint Monitoring Programme 2010, from Demographic and Health Surveys for 1987,1996, 2001 and 2006 Between late 1900s and early 2000s, the patterns from providing access to sanitation modalities have shifted from flush toilets to improved latrines. Population gaining access to flush toilets increased by 1 percent per year between 1996–2001 while during 2001–06 fell by –0.6 percent. During the same periods, the percentage of the population gaining access to improved latrines each year increased by 60 percent from 1.4 to 2.2 percent (table 8b). Although population using open defecation decreased at a 1.2 percent per year during 1996–01, for 2001–06 every year 0.3 percent
entire section D covering manufacturing (twodigit codes 15 through 37), section F covering construction (code 45), section G covering wholesale and retail trade as well as repair of motor vehicles, motorcycles and personal and household goods (codes 50 through 52), section H covering hotels and restaurants (code 55), and section I covering transport, storage and communications (codes 60 through 64). Formal registration usually refers to registration with tax agencies or in general firm registries. The universe includes partially privately owned firms and excludes fully state-owned firms. The sources of the sampling frames for these WBES were: for Argentina – Dun & Bradstreet 2016, for Bolivia – Economic Census, updated by Encuestas y Estudios consulting group 2016, for Ecuador – Superintendencia de Compañías Valores y Seguros del Ecuador 2016, for Paraguay – Directorio General de Empresas y Establecimientos 2015, for Peru – the combination of Top 10mil 2011, Registro Mype Callao 2010, Registro Mype 2012 and SUNAT (Hacienda) 2011, and for Uruguay – Instituto Nacional de Estadística 2015.

> 43 Full details of the methodology can be found at http://www.enterprisesurveys.org/methodology. Stratified random sampling was used, with strata based on firm size, geographical location, and economic sector. The data includes sampling weights. All results are obtained using these weights and thus refer to the entire population of pertinent establishments in the six countries. 44 Hadfield and Bozovic (2016) have argued in the context of innovation-oriented interactions that legal contracts are valuable in planning transactions, even if the parties have no intention of using the contract in a formal legal setting. In this case, respondents would not identify the use of such a contract with the effectiveness of the legal system, but rather with first- or second-party mechanisms (i.e., trust and mutual interest).

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(3):424–43

- Chen Y, Whalley A. 2012. Green Infrastructure: The Effects of Urban Rail Transit on Air Quality. _Am. Econ. J. Econ. Policy_ . 4(1):58–97

- Chin A, Smith P. 1997. Automobile Ownership and Government Policy: The Economics of Singapore’s Vehicle Quota Scheme. _Transp. Res. Part Policy Pract._ 31(2):129–40

- Chugh R, Cropper M, Narain U. 2011. The Cost of Fuel Economy in the Indian Passenger Vehicle Market. _Energy Policy_ . 39(11):7174–83

- Coffin, D., Horowitz, J., Nesmith, D., & Semanik, M. 2016. Existing Barriers to Trade in Used Vehicles. United States International Trade Commission.

- Cohen P, Hahn R, Hall J, Levitt S, Metcalfe R. 2016. Using Big Data to Estimate Consumer Surplus: The Case of Uber. _NBER Work. Pap._ w22627

- Collier, P., Glaeser, E., Venables, A., Manwaring, P., and Blake, M. (2019). _Urban Mobility:_

- _policy decisions for connecting the city_ . IGC Cities that Work Policy Brief.

- Currie J, Neidell M. 2005. Air Pollution and Infant Health: What Can We Learn from California’s Recent Experience? _Q. J. Econ._ 120(3):1003–30

- Currie J, Walker R. 2011. Traffic Congestion and Infant Health: Evidence from E-ZPass. _Am. Econ. J. Appl. Econ._ 3(1):65–90

- Daniel JI, Bekka K. 2000. The Environmental Impact of Highway Congestion Pricing. _J. Urban Econ._ 47(2):180–215

- Davis LW. 2008. The Effect of Driving Restrictions on Air Quality in Mexico City. _J. Polit. Econ._ 116
1991-92|193.8|91||||||
|1992-93|238.8|113|1993|310|16.7|5.4|87|
|1993-94|258.3|122||||||
|1994-95|209.0|99|1995|374|16.1|4.3|84|

# Accelerating increase in poverty, 1988-1993

As the economic recession deepened between 1988 and 1993, poverty in CMte d'Ivoire more than doubled. The increase was particularly strong in Abidjan, where poverty increased tenfold. With the large increase in poverty in Abidjan and to a lesser extent in Other Cities, the contribution of urban areas to the headcount index of poverty increased by more than 60 percent between 1988 and 1993 9 The poverty results for 1985-1988 presented in this paper take account of the reweighting scheme proposed by Demery and Grootaert (1993).

10
were put on a reserve list in case some applicants would drop out of the experiment before the implementation starts. A baseline survey with all 1,300 firms was conducted in November/December 2018. This survey was implemented with Innovations for Poverty Action (IPA). The sample size was chosen based on power considerations and budget constraints. Power is discussed in more detail in Section 4.

**Phase 5 - Randomization of selected applicants into treatment arms through a public lottery.** In April and May 2019, with technical support from the World Bank, MEBF ran public lotteries in each participating

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> These differentials are based on mean log wages of the two groups rather than mean wages.<sup><u>b</u></sup> Differential in (geometric) mean predicted wages of males and females, using earning function estimated over pooled sample without ethnic dummy; known also as explained pay gap.<sup>c</sup> Sector of economic activity is controlled for. _Sources:_ Calculations based on LFS data.

# **Local unemployment and wages**

One of the commonly used methods of measuring labor market flexibility is to estimate so called wage curve: the responsiveness of wages to regional unemployment rates at job locations (see Blanchflower and Osvald (1994). This methodology involves calculating the relationship between wages and unemployment levels, referred to as elasticity. This calculation measures the responsiveness of wages due

> 13  Only hired employees are considered in this analysis.

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# **1. Introduction**

Agricultural labor accounts for the largest share of child labor worldwide (60 percent). In SubSaharan Africa, the setting of this study, smallholder farming is the only source of income and employment for most households and accounts for 85 percent of child labor (ILO 2017). Yet, measurement of farm labor is a challenging topic due to its inherent seasonality, variable and irregular work schedules, multiple plots, intercropping, and varying saliences of individuals’ work activities (Arthi et al. 2018), and the gender division of farm labor (Beegle et al. 2017), as culturally defined roles determine the capacity of men and women to allocate labor time across economic activities (Palacios-Lopez et al. 2017). While the measurement of child labor is essential to our understanding of the main factors that drive children to work and the development of sound policy, research on data quality and data collection methods is an overlooked topic in development economics (Beegle et al. 2012).

In this study, we implement three randomized survey design interventions over the agricultural coffee calendar in rural Ethiopia to address whether response by proxy rather than selfreport has effects on the measurement of child labor statistics within and across seasons. Specifically, our experimental survey design intervention consists of the random manipulation of the survey respondent in the application of the same survey instrument to 1200 Fairtrade coffee households in three different seasons of the coffee production calendar: the _Meher_ season (main rainy season), the _Belg_ season (short rainy season) and the harvest season.

Over the past years, the increasing availability of multi-topic household surveys in agricultural settings has highlighted systematic challenges concerning the link between agricultural information that is commonly captured during a single visit to the household and the measurement of farm labor that is variable and irregular due to the salience of seasonal work activities (Arthi et al. 2018; Gaddis et al. 2019). One dimension of this measurement problem is 2
corporate output recovery. As in other cross-country micro studies, we are restricted to examining the micro data for public firms since detailed balance sheet data on private firms across countries is unavailable. However, we were able to obtain operating revenue on a sample of private firms (156 firms with nonmissing data over 10 years) in Argentina from the ORBIS database.<sup>15</sup> In Figure 3D, we examine

> 12 It may be noted that our micro level analysis is focused only on the corporate sector (largely manufacturing firms) while the GDP numbers reflect other sectors of the economy and not just the corporate sector.

> 13 Figure 3B does not include Russia and Turkey because the firm-level data do not allow us to go back six years before the crisis.

> 14 A description of the construction of national income statistics from the International Financial Statistics reveals that sales from commercial income statements are adjusted for changes in output inventories and work in progress to measure production. The components of inventory are not well populated in the Bloomberg database and so we use other approximations of production.

> 15We used the 2009 version of ORBIS data which goes back ten years to 1999. Hence we are unable to replicate the private firm analysis for the other 3S countries since the crises periods are before 1999.

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premium gained by greater levels of education of girls who postponed childbirth.<sup>13</sup> Since wages are not reported separately for adolescent mothers and non-mothers, we use the average adult female expected wage as an earnings proxy for a girl who postponed childbirth and the average female youth expected wage as an earnings proxy for adolescent mothers. Then the difference between average female wage and the average teenage mother wage is a proxy for the ―cost‖ of early childbearing to lifetime economic productivity:<sup>14</sup> where _I_ is forgone annual earnings; _wF_ is mean annual adult female wage; _EmpF_ is adult female employment rate; _wYf_ is mean annual youth female wage and _EmpYf_ is youth female employment rate.

The above costs correspond to the average costs of early pregnancy for one girl in one year. To measure the total cohort cost per year, we multiply the average cost with the number of adolescent births in the observation year ( _Yf_ ). Assuming these girls will stop working when they are age 60 and these young mothers are age 15—the International Labor Organization’s standard age for the beginning of a work life—when they enter the labor market, we multiply the annual cost of the cohort by the years that the cohort will be working, which is 45 (retirement age minus age of first working). Finally, as above, we state the total country costs as a share of current year GDP.

Several sources of data are used. The wage data are those that were derived for the estimates of early school leaving, reported in section a, above. The World Bank’s HNPStats was used for incidence of adolescent childbirth, and the World Bank’s WDI database was used for GDP values.

While the observed wage gap between teen mothers and other girls persists throughout life, this may be more a factor of differences in innate ability rather than a

> 13 Ideally, we would have replicated the age earnings profiles discussed above in the ―education‖
contact information was recorded incorrectly at the time of the third round of BEEPS. Further, the classification treats firms that have shut down temporarily the same as firms that have closed permanently. Finally, some firms that were still operating but were not interviewed might have filed for insolvency or bankruptcy—although as shown in Table 2 this might not be a major concern given that only 26 of 1696 operating firms that were interviewed were in bankruptcy or liquidation. Despite these minor limitations, this is the most reasonable breakdown possible given the available information. The firms that we identify as no longer operating almost certainly struggled more during the early phase of the crisis than others.

The dependent variable in the survival analysis is a dummy indicating that the firm was not operating or was in the process of closing down at the time of the second survey—either because the firm had closed permanently, had filed for bankruptcy or insolvency, or had been temporarily shut down. This was the case for 296 of 2,501 firms interviewed in these countries during the third round of BEEPS (see Table 2).

# **IV. Estimation**

As noted, we use the data from BEEPS and the FCS to look at the effect of the crisis on different firms in the region focusing on firm and country characteristics. The first part of the analysis focuses on whether firms were still operating in mid-2009 using data from the FCS. We refer to this analysis as the ̳survival analysis.‘ The second exploits variation over time in firms‘ reported financial constraints for a balanced panel of respondents to the 2002, 2005, and 2008-2009 BEEPS. We refer to this as the analysis of financial constraints.

For both analyses, the basic regression is: In the survival analysis, Y is a dummy variable that takes the value 1 if the firm was not operating at the time of the FCS survey—but was operating at the time of the earlier BEEPS survey. Because the survival analysis is cross-sectional—we only have information on whether a
three assessments. In addition, UNEB administered an additional Mathematics test (“Math independent”), which the research team adapted from TIMSS, an international test,<sup>9</sup> through discussions with psychometricians in Uganda. The independent test was included to detect real gains in achievement using an alternative to the official test (NAPE), which may be subject to “teaching to the test”. NAPE data were collected in 2011 for 1,230 students from 48 treatment schools and 1,126 from 45 control schools, and in 2012 for 1,268 students from 48 treatment schools and 990 from 45 control schools.

# b. Empirical Strategy

The research team performed the phase-in lottery in December 2010. Treatment is defined as formal notification that the private school is a part of the PPP program. All treatment schools received this notification of acceptance into the PPP program in February 2011 and none of the control schools did. In this respect, compliance to randomized design was close to 100%.

However, actual transfer of resources under the PPP program was slower and compliance was less than perfect. Consequently, we are estimating two models: an intent-to-treat model, ITT (based on the lottery assignment) and an instrumental variable (IV) design that uses actual program implementation, as reported by the schools.

The ITT model is based on two main specifications. In the first model, the outcome variable _Y_ of student (grade and gender) _i_ in school _s_ at time _t,_ is regressed against a dummy variable indicating random assignment to treatment ( _T_ , 1=treatment; 0=control).

> 9 <mark>The Trends in International Mathematics and Science Study (TIMSS) is a series of international assessments of the mathematics and science knowledge of students around the world. For this research, we used a balanced selection of openly available questions from Grade 4 TIMSS Mathematics tests across specified learning domains.</mark>

6
Over the three years, some household members split from the 2007 original households and became an independent family head (for marriage or other reasons). In our sample, household division occurred in 204 original households (9% of our sample). We use the 2007-survey original household as the unit for analysis to avoid bias that may arise from household splits. For instance, a new household head, who split from his original household, might share and cultivate farm lands with his parents though the land is still owned by his parents (vice versa). By aggregating original and split households in 2010, we minimize the split bias<sup>9</sup> .

The 2007 survey was designed to overlap with villages in the 1994/95 PATANAS survey conducted by ICASEPS to build household panel data. The 1994/95 PATANAS survey focused on agricultural production activities in 48 villages chosen from different agro-climatic zones in seven provinces. In 2007, we visited those villages to expand the scope of research as a general household survey under the IMDG survey. In the 2007 round, therefore, we added 51 new villages in the same seven provinces<sup>10</sup> .

In the revisited villages in 2007, we re-sampled 20 households per village from the 1994/95 sample and followed the split households. In the new villages, we sampled 24 households from two main hamlets in each village. Since one of the 48 villages in the 1994/95 PATANAS was 9 It is possible that the 2007-08 food price crisis affected household split decisions, which will potentially cause an additional bias if we omit split households or do not aggregate original and split households. In this paper, we only report the results using the aggregated households. However, even when we use only households which did not experience split (excluding 204 split households), our empirical results remain the same.

10 These new villages were selected with the following criteria. First we chose the same districts where PATANAS villages are located. We list villages
allocation of public offices to key elites (van de Walle 2012: 113).<sup>3</sup> In such settings, a cabinet position forms the top echelon of elite offices and can be seen as the ultimate gift, “bringing with it patronage opportunities as well as significant perks and status-enhancing privileges” (van de Walle, 2001: 103; see also Kroeger 2018, LeVan and Assenov 2016).

Elite clientelism in the form of prebendalism is closely linked to grand corruption, which channels benefits other than the official salary to a political office holder. In an earlier empirical analysis, Mills (2012) uses data for 42 African countries over the period 1985-2010 and finds that cabinet size is associated with higher levels of grand corruption. One reason is that horizontal accountability – whereby members of a country’s legislature hold the executive branch to account – is a likely victim of prebendalism. The handing out of cabinet positions to members of parliament based on loyalty acts as a disincentive for them to exercise effective oversight. For instance, Ghana’s former President John Kufuor picked about three-quarters of his cabinet ministers from among parliamentarians, who in order to be considered had to be loyal rather than scrutinize the executive (Lindberg 2010).<sup>4</sup> Elite clientelism can be contained by programmatic political parties, which appeal to voters on the basis of specific policies that are grounded in an ideological program (Keefer 2013: 7). Programmatic parties are able to solve collective action problems and make credible commitments to deliver public goods, which requires mechanisms to discipline and sanction party leaders and members whose actions are not conducive to delivering promised policies. In contrast, clientelist politicians prefer discretion and weak oversight of the implementation of policies, so that they can extract personal benefits and channel resources to their supporters (Cruz and Keefer 2015). This implies that the potential for cabinet size to be associated with poor governance and corruption is especially likely in settings where programmatic political parties are weak or absent
the bilateral nature of the DIOC (and DIOC ~~-E~~ ) data is a very unique and valuable feature. Otherwise we could not obtain emigration numbers from the censuses of individual destination countries as they only give information on people who are present at the time, not of those who have left the country.

Table 1 presents age distribution by migration status across OECD countries and the age distribution of emigrants from these countries for the year 2010. The first set of columns refer to nativ ~~e-~~ born individuals, followed by a set of columns pertaining to immigrants. Two key observations emerge from Table 1: (i) immigrants and emigrants are generally younger than natives; and (ii) the age distribution of immigrants and na ~~-~~ tives differ across all countries. We see that in countries such as Japan, Italy, Germany and Greece, the 65+ years old comprise over a quarter of the population above age 25. In almost all countries, they account for no less than 15 percent of the population. In comparison, migrants are younger in most of these countries. A close inspection of Ta ~~-~~ ble 1 reveals that the shares of natives between the ages of 45 and 64 also exceed the

> “Censuses often focus on the resident population, whether they are regular or irregular. ®The DIOC database allows identifying the originxeducationxage dimension, or the originxagexstatus dimension. For each country of destination, we extract the labor market status of young and old workers from the second and compute the ol ~~d-~~ t ~~o-~~ young ratios of participation and employment rates. We then use these ratios to characterize the labor market status of workers by origin, education and age.

14