rafmacalaba/data-use-mentions-extended huggingface dataset:
<!-- Start of picture text --> Figure 4. Quality-adjusted Education Benefits (JOD million) Figure 5 Quality-adjusted Health Benefits (JOD million) by<br>by Market Income Decile Market Income Decile<br>140 700<br>120 600<br>100 500<br>80 400<br>60 300<br>40 200<br>20 100<br>0 0<br>Household per capita market income decile Household per capita market income decile<br>Net benefits Quality-adjusted benefits Net benefits Quality-adjusted benefits<br>Note: Households are grouped into per capita market Note: Households are grouped into per capita market income<br>income deciles. Net benefits are those estimated in the deciles. Net benefits are those estimated in the baseline<br>baseline scenario. Quality-adjusted benefits are adjusted scenario. Quality-adjusted benefits are adjusted according to<br>according to learning outcomes in the S-HCI by decile. under-five stunting in the S-HCI by decile.<br><!-- End of picture text -->

# Impact on measured inequality and poverty

In cash and non-cash terms, Jordan’s fiscal policy appears modestly progressive; the poorest households receive more benefits than they pay while other households pay more into the system at a rate which slowly increases as they get richer. How does this impact inequality, as commonly measured by the Gini Index, and what is the effect on poverty?

Jordan’s inequality (Gini) is measured in the HEIS at 35.1 points based on market income—before the fiscal system affects households—and at 29.3 points based on final income—after accounting for all fiscal policy (Figure 6.).<sup>50</sup> This indicates that overall fiscal policy reduces inequality in Jordan by 5.8 points. The largest fall is observed between consumable and final income, which is when in-kind transfers (health and education) are included. In purely cash terms, inequality falls
range. To guard against this possibility, we control for the square of the number of required documents ( _Documents_<sup>2</sup> ).

A number of studies have shown that small countries tend to trade more than the large countries and that the same holds for rich compared with poor countries. One might then speculate that the reason why income and population matter for the strength of the documentstime cost relationship is because income and population are picking up the effect of trade openness. To check for this possibility, we control for trade (exports plus imports) to GDP ratio (log values of the average of trade to GDP ratio taken over 2001-2005) interacted with the number of required documents ( _Documents*_ Trade to GDP ratio).<sup>4</sup> The argument in the previous paragraph can be extended to another variable: the quality of the overall business climate. For example, higher income countries are likely to be less regulated (less burdensome business climate). Hence, the differential effect of the number of required documents on the time cost across rich and poor countries could potentially be the differential effect across less and more regulated economies if regulation and required documents to trade are compliments for the time cost. To guard against this possibility, we control for _Documents*Business Climate_ , where _Business Climate_ equals the log of the average value over 2001-2005 of the overall score of economic freedom as measured by the Index of Economic Freedom, Heritage Foundation.

Another factor that is known to be correlated with income level and the business regulations is corruption. Typically, corruption falls with higher income levels and increases with various aspects of more stringent regulation (such as, the number of documents required to

> 4 We also experimented with using an overall (weighted) tariff rate, average values over 2001 to 2005 and taken from World Development Indicators, World Bank. However, our main results did not change much on adding the tariff measure interacted with _Documents_ to any of the specifications discussed in the
. These included the requirement that both the organizations, as well as the main team of interviewers, supervisors, and managers, had ample experience on collecting firmlevel data in their respective country and follow similar procedures for implementing the survey.

The questionnaire was implemented at the establishment level. In the sample, 86% of our observations refer to single establishment firms. In the case of multi-establishment firms, the questionnaire was applied to the specific unit of production that was randomly selected.

The protocol for the implementation of the survey required that the survey should be

> 56For example, Holbrook, Green and Krosnick (2003) use data from three experiments in the US and show that telephone respondents are less likely to cooperate and more likely to present themselves in socially desirable ways. Jackle, Roberts and Lynn (2006) show in a designed experiment that evaluate the differences between the two modes of data collection show also that telephone respondents are more likely to give socially desirable responses, which in our context is likely to result in an upward bias of technology use.

56
We would like to point out that while our main focus is on micro-level data as mentioned above, we check our main results using macro or country-level data on a measure of the quality of tax administration which is the time it takes to prepare, file and pay three major types of taxes and contributions – corporate income tax, value added or sales tax and labor taxes, including payroll taxes and social contributions. The data for the variable come from the World Bank’s Doing Business project.

The plan of the remaining sections is as follows. In section 2 we describe the data and the empirical methodology. Estimation results for the linear specification using the ordinary least squares, ordered logit and the instrumental variables estimation method are provided in Section 3. Results for the non-linear specification are provided in Section 4. Regression results using macro-level data are provided in Section 5. The concluding section summarizes the main results and suggests scope for future work.

# **2. Data and methodology**

Our main data source is the survey of over 11,000 firms in 30 countries in Eastern Europe and Central Asia conducted by the World Bank in 2008 (Business Environment and Enterprise Performance Survey (BEEPS, 2009), Enterprise Surveys). The countries covered by the survey include Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, FYR Macedonia, Georgia, Hungary, Kazakhstan, Kosovo, Kyrgyz Republic, Latvia, Lithuania, Moldova, Mongolia, Montenegro, Poland, Romania, Russia, Serbia, Slovak Republic, Slovenia, Tajikistan, Turkey, Ukraine and Uzbekistan. The survey is designed to be representative of the non-agricultural private economy at the country level and contains a mixture of manufacturing and service firms, small and large firms and young and old firms.

6
...rm models, including Helpman et al. (2008) and Baldwin and Harrigan (2011). Relative to this strand of work, a key distinguishing feature of our empirical analysis is the ability to link information on emigration stocks with detailed data on ...rm-level export outcomes and other ...rm characteristics. In doing so, we also contribute to a rich literature on the e¤ects of social networks on aggregate trade ‡ows (Gould, 1994; Rauch, 1999; Rauch, 2001; Rauch and Trindade, 2002; Melitz, 2008; Guiso et al, 2009).

The remainder of the paper is organized as follows. Section 2 outlines a multi-country heterogeneous-...rm trade model, and uses it to discuss the speci...c channels whereby migrant networks may impact on ...rms’bilateral exports. Section 3 provides historical background and discusses the timing and drivers of Portuguese emigration ‡ows. Section 4 describes the data employed, before section 5 presents preliminary evidence based on country-level data. Section 6 examines the e¤ect of networks on export participation and intensity at the level of the ...rm, emphasizing the role of ...rm age and location in shaping

> 3 Importantly, Crozet and Koenig (2010) also use ...rm-level data to estimate key parameters of the model of Chaney (2008), but in doing so restrict the focus to the e¤ect of geographic distance on trade.

> 4 An important caveat, however, is that the measure of familiarity employed by Anderson (2007) exhibits high colinearity with geographic distance.

3
industry and firm level data to explore the positive impact of finance on growth. More recently, Oliver, Levine and Warusawitharana (2014) find that external finance supports productivity growth in their sample of European countries.

However, a number of recent papers revisit the finance-growth relationship and find more nuanced effects. This paper builds on this newer literature on productivity and finance that examines the possible negative relationship between productivity and/ or growth and finance in very large financial systems. Gazdar and Cherif (2015) find that finance is more likely to support growth in MENA countries in good institutional contexts. Demetriades and Law (2006) find that financial development has larger effects on GDP per capita when the financial system is imbedded within a sound institutional framework. Barajas et al (2013) find that the beneficial effect of financial deepening on growth varies across countries; lower income countries benefit less because their regulatory and supervisory systems are less developed. Aizenman, Yinjarak and Park (2015) find a nonlinear effect of finance and growth and an uneven effect across sectors; they compare East Asia and Latin America, concluding that both the quantity and quality of finance matter. When the financial system channels resources to productive sectors of the real economy, then growth in finance and real output are positively correlated. Arcand et al (2012) find that there is a threshold beyond which finance does not have a positive impact on growth. Shen and Lee (2005) show that stock market development has a positive effect on growth but banking development does not; they find that the conditioning variables of financial liberalization, high income level and good shareholder protection mitigate the negative effects of banking development on growth. Cecchetti and Kharroubi (2012, 2015) find that the impact of finance on growth is nonlinear (very large financial sectors can have a negative relationship with growth) and that a fast growing financial sector has a negative impact on aggregate productivity growth. In their theoretical model, this is because low productivity (and high collateral) projects are more likely to be
given the low levels of employment and the high measurement errors produced by the crosswalks.<sup>40</sup> For example, Elliot et al. (2021) applies the O*NET classification and Vona et al. (2019) methodology to study how eco-innovations impact employment in the Netherlands, finding that there is no impact on overall employment but that they increase green jobs. However, the share of green jobs is significantly higher than that in the U.S., bringing into question the quality of the crosswalk to measure green employment.<sup>41</sup> Section four of this paper reports the same issue when applying O*NET classification to estimate green employment in Indonesia.

A second modality of the task content approach consists of applying text analysis to occupational manuals with task descriptions. Janser (2019) applied text mining to the German occupational database to calculate the level of "greenness" of occupations. The dictionary included 153 green terms and was applied to a database with occupational requirements at the 8-digit level, containing 14,546 words, to identify green tasks for each occupation. Following Consoli et al. (2016), Janser created a greenness index, which is the share of green requirements (tasks) in the occupation. Janser shows that there was a greening of jobs between 2011 and 2016 in Germany, with slight wage increases, and that the greenness of occupations and employment growth are positively correlated.

This second modality also has some methodological limitations. First, the country of interest needs to have an occupational manual that includes task statements as part of the occupational description. The more narrowly defined the occupations are and the more precisely defined the task statements are, the

> 38 Alatas, Granata and Posadas (2020), Apella & Rovner (2021) for Indonesia and Uruguay respectively.  Granata and Moroz (2022) describe Viet Nam’s efforts to replicate and adjust select modules of O*NET to Viet Nam, but do not attempt to compare it with
Where _i_ indexes schools, _X_ includes baseline socioeconomic characteristics, _FSSP_ is a binary variable that takes the value 1 for a stipend-eligible school and 0 otherwise. measures the net impact of the stipend program.

Therefore, the school-level analysis measures whether the increase in enrollment experienced by a cohort when they first joined the program (the short-term impact) is continued through successive grades relative to the trend observed for the comparison cohort. A sustained increase in net enrollment could be due to increased transition across grades (the push effect), reduction in drop-out rates, and/or influx of new entrants (including both rejoiners and those who switch schools). Yet, the school-level approach cannot distinguish these channels of impacts since the school censuses do not provide information to measure them separately. However, preprogram and post-program data from household surveys indicate that female rejoining (new entrants) and grade repetition at the middle school level is very low.<sup>19</sup> This suggests that net changes in female enrollment (if they happen) are largely driven by the combined effects of the program on both transition and dropout rates.

# **_Household-level Analysis_**

The units of observation used for this analysis consist of girls expected to be exposed to the program for at least one year between 2003-04 and 2007-08. Although the household survey data used for this analysis provide rich information on a wide variety of indicators, they do not contain explicit information on the treatment status and length of exposure of girls to the FSSP.

Therefore, some steps were taken to select the girls who fall within an age range and are likely to have been exposed to the program for at least one year. The motivation for constructing synthetic cohorts based on age and grade criteria, as opposed to only an age based criterion, was to arrive at a cohort that is more reflective of actual participants<sup>20</sup> Annex B explains more fully

> 19 Both rejoiners and repeaters constituted around 0.5 percent of total enrollment in middle
Since 2014, the data show increases in the participation rate (Figure 1), which is known to be countercyclical, and employment-to-population ratios. The data also show a clear deterioration of the quality of employment. This can be seen in terms of a falling rate of _adequate_ employment among the working-age population (Figure 2, top), and the sharp increase in informality (bottom). Last, the data also shows a reduction in monthly earnings since 2015 (Figure 3, top) and stagnating hourly wages in 2015-2017 followed by a sharp reduction in 2017-2019 (bottom).

# **4.2 Mobile Phone Records:** **_Telefonica Ecuador_**

The main challenge to carry out the analysis was the need to obtain information on the size and geographic distribution of the Venezuelan immigrants in Ecuador. Prior to our study the existing information regarding the size of the Venezuelan population in Ecuador was mainly based on official records of net migration flows on a monthly basis. These data have two important limitations. First, what is being measured are the entries and exits, not the actual count of people. More importantly, the net migration estimates miss the foreign population that enters the country without registration at an official point of entry. Furthermore, no data were available at the time on the magnitude of unregistered entry.<sup>14</sup> The knowledge of the geographic distribution of the Venezuelan migrant population was also severely limited. Characterizing this distribution is complicated by the high geographic mobility of this population and the lack of baseline information in the traditional datasets, such as the Population Census.

Our approach to address these challenges has been to rely on mobile phone records. More specifically, we contacted the two main cell phone providers in the country to request their collaboration. However, only _Telefonica Ecuador_ had the technical capabilities to implement the data collection we proposed. In addition, this company was the only one with a large presence in the Venezuelan mobile phone market and, thus, could be expected to
a good condition. For tenants, we simply ask how they would rate their relationship with the property owner from 1 (very poor) to 10 (excellent).

_Perception of service quality_ : Tenant / Property owner agrees or strongly agrees that they are satisfied with utility services, the utility services improve people’s lives and provides clear communication, the government is trying to improve their lives, and (reverse coded) the government is not interested in helping the community.

_Perception of service fairness_ : Tenant / Property owner agrees or strongly agrees that the utility enforcement mechanisms are fair and bills are accurate and fair.

_Activism_ : Whether the compound has a committee, tenants have reached out to community leaders, participated in community meetings, or are members of community committees.

_Psychological well-being_ : We include a set of standardized measures to capture different dimensions of psychological well-being among tenants, including Cohen’s four-item stress scale (Cohen et al., 1983), depression (Center for Epidemiologic Studies Depression (CES-D) seven-point scale (Radloff, 1977)), optimism (Rosenberg optimism questionnaire (Rosenberg, 1965)), and the World Value Survey (WVS) measures of happiness, trust and life satisfaction. The psychological well-being index in turn is a standardized weighted average of these sub-indices.

In addition to the indices, we measure rent and rental income, migration and general socioeconomic measures of property owners and tenants to explore possible effects on rent and associated gentrification. We report the results from the indices in the main paper and include the results of all sub-indicators in the appendix Tables A1 and A2.

# **8 Results**

## **8.1 Baseline Balance**

We present descriptive statistics and baseline comparisons between treatment and control groups for our primary outcome measures using the administrative payment data on 6 August 2018 and 28 October 2018 to coincide with the download dates for the data sets used for the randomized assignment of the engagement and enforcement interventions respectively. Appendix Table A3 presents comparisons for each group and
20 7. The poor in a typical Bangladesh village are often involved in various small scale business activities. These comprise the supply of various transport and domestic services and petty trading activities, such as collecting natural fuels and selling prepared beverages.

8. One may be able to avoid these problems in future work with access to unit record data.

9. The following Engel curve was calibrated to 1973-74 data (from BBS, 1980, Table 4.11) for 11 expenditure groups (the top two were excluded to give more precise estimates for lower income groups)s

- S - .33 + .14lnE - .015(lnE)2 R<sup>2</sup> . .90 (5.5) (6.0) (6.7)

where S = share of total food expenditure devoted to foodgrains, E - mean monthly expenditure on all foods, and absolute t-ratios are given in parentheses. Mean food expenditures by income group for 1978-79 were deflated to 1973-74 prices for use in the above formula.
on empowerment of female host-community members are missing in the literature. We add to these studies by looking at the presence of IDPs as a mechanism through which the spatial spillover of conflict potentially operates.

# **2.2 Violence and Forced Displacement in Nigeria**

According to the Global Terrorism Index 2020, Nigeria was the country third most affected by terrorism, after Afghanistan and Iraq. Nigeria accounts for almost half of all deaths caused by organized violence in Africa (Pettersson and Öberg, 2020). Together Boko Haram and Fulani extremists account for almost 80 percent of terror attacks and roughly 90 percent of terror victims in Nigeria.

Nigeria is the seventh country in the world ranked by number of people who are internally displaced, with 2.73 million in 2020 (IDMC, 2021). Most of the displacement is due to violent conflict, in particular the Boko Haram insurgence. The Islamist group was founded in 2002 to counter Western education and democracy. Its Hausa name translates to “Western education is forbidden.” The group’s focus on forbidding Western education is unique among jihadist groups. The group has been responsible for much of the surge in terrorist activity in Nigeria and for thousands of attacks and deaths in the Chad Basin region. Since 2011, Boko Haram activity has led to over 20,000 terrorism-related deaths and 37,500 combat-related deaths. To date, Boko Haram is the deadliest terrorist group in Sub-Saharan Africa and the fourth-deadliest group worldwide (IEP, 2020).<sup>5</sup> Attempts of the Nigerian government to neutralize the group started in 2012, after which the conflict escalated quickly and peaked in 2014–15. In 2014, the group kidnapped almost 300 schoolgirls from the town of Chibok, more than 100 of whom were still missing as of 2020 (Strochlic, 2020). In the same year, the group was responsible for the first attack on the capital of Abuja, targeting a bus park where more than 70 people were killed. After 2014, the
# 4.2.2.- Services to airlines

Service directly provided to airlines also has to be taken into account in order to reach a complete quality assessment. Although BAA is not subject to quality standards, some airlines have already requested the Monopolies and Mergers Commission to establish standards regarding the availability of key operational equipment such as baggage belts, jetties, stands, moving walkways and lifts.

In spite of a lack of quality regulation, BAA makes direct measurements of its service delivery by recording objective data on the availability of critical equipment. Table 4.5 shows the 24 hour availability data for passenger-sensitive equipment from April 1995 to March 1996. Other performance indicators developed by BAA are: number of faults per unit (as a measure of the effectiveness of preventive maintenance), and time to site and time to repair (as measures of reactive maintenance). A target of repairing 95% of faults within four hours was set. Table 4.6. shows average fault repair time for passenger sensitive equipment. Other aspects considered are: percentage of passengers boarding /disembarking via jetty, coach or steps (see Table 4.7), planned and unplanned stand outage (in terms of hours per month) and maximum baggage handling delivery times (see Table 4.8).

**Table 4.5. Percentage availability of critical equipment at selected BAA airports. April 1995 to March 1996**

||97.8|99.2|99.0|99.1|98.9|
|---|---|---|---|---|---|
||98.8|99.5|99.3|n.a.|99.3|
||98.4|99.4|98.7|98.5|99.3|
|.~|98.6|99.5|99.4|99.7|99.8