rafmacalaba/data-use-mentions-extended huggingface dataset:
the tax law applicable to direct taxes and social security contributions, see annex II , in Nuñez et, al. (2019).

> 35 The only exception is victimization transfers, the value of which was taken directly from the survey having been unable to clarify what kind of subsidy it is.

> 36 For detail on the procedure, see annex II, in Nuñez et, al. (2019).

> 37 BEPS: Periodic economic benefits [BEPS], is a voluntary savings program for the elderly for those who do not have the resources to obtain a pension (income up to a monthly minimum wage). The value of the subsidy is 20% of the total saved once the person reaches retirement age (57 years for women and 62 years for men). “Ser Pilo Paga” is a National Government scholarship program that subsidizes higher education for poor students (according to the SISBEN score) and have obtained a good score on the Saber 11 State standardized tests. The program benefited 40,000 students.

> 38 More detailed information is found in Annex III in Nuñez et, al. (2019).

19
IMF 2019). Thus, the BaU does not consider the contraction in GDP due to the COVID-19 pandemic. While for most countries the GDP per capita growth rates are quite stable in the long run, some quickly aging economies or those with slowing population growth rates are expected to experience lower GDP growth rates after 2030. Also, higher income is associated with an increased share of services in household demand and since productivity growth in services is usually lower than in manufacturing, some economies experience slower GDP per capita growth rates due to slower productivity growth.<sup>9</sup> The baseline also targets population growth following the latest UN population projections (UN 2020), as well as the GIDD projections, available by broad age group (we use the 15-64 age cohort for labor force), gender, and education (primary, secondary and tertiary). Growth of skilled labor is equated with the growth of specific education categories. For low- and lower-middle income countries, skilled workers are equated with secondary and tertiary levels. For upper-middle and high-income countries, skilled workers are equated with tertiary levels only.

We simulated different scenarios that reflect the depth of the RCEP agreement. The first scenario simulates the expected tariff reduction among RCEP members as scheduled in the agreement.<sup>10</sup> A second scenario also includes non-tariff measure reductions among goods and services. We follow Petri and Plummer’s (2020) assumptions and simulate a 35 percentage reduction of ad valorem equivalents of non-tariff measures on agricultural goods, a 25 percentage reduction on manufacturing goods, and a 25 percentage on services among RCEP members countries, and a 10 percentage of non-tariff measures applied by RCEP members to imports from countries outside RCEP, as it is assumed that some of the reforms carried out in the agreement are applied on a non-preferential basis. Third, we also assume that the Rules of Origin (ROO) regime in RCEP reduces trade costs among its members by 1% over the period of implementation (2022-2035). The
|(0.0448)||(0.0240)*|(0.0298)*|(0.0389)||(0.0130)|(0.0132)|(0.0225)|
|IDN exports per worker *||||-0.0777||||-0.0881||||0.0336|
|Share of hhlds with computer||||(0.111)||||(0.0902)||||(0.0507)|
|Observations|165|165|165|165|165|165|165|165|165|165|165|165|
|R-squared|0.960|0.966|0.963|0.965|0.972|0.975|0.973|0.975|0.966|0.968|0.967|0.966|

Source: Authors’ calculations based on Sakernas 2005-2010 and 2011-2015, Susenas 2005-2010, 2015-2016 Philippines STEP survey, and 2011-2015, and UN Comtrade database 2005-2010.

Notes: IV regressions. IV: Global demand for foreign products excluding Indonesian products. Indonesian exports per worker in thousands of USD at 2010 prices and global demand for foreign products in millions of USD at 2010 prices. ICT variable at the province level is the share of households with computer. Province controls include the age structure of the population, share of urban population, real GDP per capita, minimum wage level, gender and educational composition of employment. All models control for province, year fixed effects, and linear province time trends. Robust standard errors between parentheses clustered by province. ***, **, and * indicate significance at 1%, 5%, and 10% confidence levels, respectively.

46
# **1. Introduction**

Forced displacement causes abrupt changes in living conditions. Immediately after displacement, forcibly displaced people are often in a highly vulnerable situation due to the loss of assets, the disruption of family structures, the loss of support networks, and their limited access to labor markets and services. These changes occur within existing structures of gender inequality, and while men, women and children are all likely to be adversely affected, these changes may have different consequences for women and girls. However, we might also expect that the impacts of displacement may be mitigated over time as displaced people establish new homes and networks, find work, and integrate into their new communities. Empirical research on income poverty rates among displaced populations is growing, yet the impact of gender inequality on poverty among displaced populations is rarely discussed, nor is much known about the dynamics of poverty in situations of displacement, largely because of lack of data. This study seeks to fill this gap.

Understanding the impact of gender inequality on poverty rates among displaced populations is important as displacement changes social structures and access to opportunities in ways that differ for women and men. For example, during displacement, household composition changes due to separation, conflict-related mortality, or widowhood. This shock often results in the formation of new female-headed households. Evidence for Sub-Saharan Africa shows that female-headed households that have previously been highly dependent on male income – notably widow-headed households – are particularly prone to poverty, although other types of female-headed households may not be more likely to be poor than male-headed households (Brown & Van der Walle, 2020). For this reason, while it is important to analyze differences in poverty risk between households with female and male heads, it is also important to understand how different routes to female headship, and the changes in the household composition more broadly, impact poverty risks and expenditure levels.

This paper explores level and distributional changes in expenditure among Syrian refugee households in Jordan between 2013 and 2018 using a gender lens. By the end
**Figure 12. Distribution of Urban Informal Firms by Firm Type**

<!-- Start of picture text --> Mozambique 78 2 21<br>Zambia 58 6 35<br>Zimbabwe 48 15 36<br>Avg. (Firm weighting) 72 4 25<br>Avg. (Equal-country weighting) 61 8 31<br>Low-educated Self-employed High-educated Self-employed Employer<br><!-- End of picture text --> Source: Own elaboration based on IES.

We consider two sets of variables to characterize urban informal firm types. The characteristics of the firms we measure are firm age, sector of activity, whether they operate outside household premises, the value of sales in the last month, the number of workers and productivity levels. We consider a set of variables related to financing: access to financial services and financial behavior including having a bank account, using banks or microfinance institutions for day-to-day operations, whether the accounts of the business are mixed with household expenses, and whether they use mobile money. We also separate “less vulnerable firms,” defined as those with productivity measures in the top 10 percent of the sample distribution, and “more vulnerable firms” to better understand the characteristics that are unique to higher productivity firms. We select the 10 percent cut-off following the informal firm heterogeneity analysis in the literature.<sup>56</sup> The productivity variable is calculated as the value of profits (sales minus total costs) per worker.

# **6.1 Distribution of Firm-Related Characteristics, by Informal Firm Type**

A minority of informal firms manage to survive and grow. Less than 3 percent of firms are more than 20 years old, with 43.3 percent being start-ups (up to one year) and nearly 30 percent in existence for 2 to 5 years (Figure 13). This reflects high entry (and probably exit) rates of informal firms. When comparing different firm types, we find that HE-SE are younger
and Mogstad, M. (2016). Field of Study, Earnings, and Self-Selection. _The Quarterly Journal of Economics_ , 131(3):1057–1111.

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# 3. Introduction of Tax Incentives for Electronically Traceable Payments (TIETP)

After the mandatory use of CRs proved to be a failure, tax authorities in Korea decided to develop other policy and administrative options to prevent underreporting. In the late 1980s, they began to focus on electronic payments, such as credit card payments, that enabled tax authorities to follow the retail sectors’ audit trails. In 1984, to encourage use of credit cards in retail service sectors, the Ministry of Finance introduced regulations<sup>16</sup> requiring large‐scale businesses (above W 10 billion in sales) to submit detailed lists of tax‐deductible business entertainment expenses to the NTS, with the exception of expenses paid using credit cards. In 1986, the NTS first requested credit card companies to submit taxpayers’ credit card transaction data, which was allowed under the Credit Card Business Law when requested by tax authorities for purposes of tax inquiries or investigations. The NTS thereafter began to use credit card transaction information to verify retail businesses’ tax returns (Jang 1997, 178). The effects of this approach were limited, however, since significant numbers of transactions were still paid with cash.

From the mid‐1990s, when personal income taxation in Korea shifted from use of government assessments to voluntary reporting using tax returns, cash transactions without receipts and underreporting became much more serious challenges to the Korean tax authorities. NTS would receive taxpayers’ voluntary tax returns without assessment if it did not have clear counterevidence to taxpayers’ assertions. NTS could no longer enforce income taxation on the basis of its own income‐to‐sales ratio criteria, as before. Korean tax authorities attempted to fill the gap between taxpayers’ voluntary reporting (underreporting) and NTS’s deficient tax information and evidence.

Against this backdrop, in 1994, the Ministry of Finance introduced a tax incentive for credit card use—0.5 percent of credit card sales credited to VAT payable for retail sellers dealing mainly in goods or services to consumers<
# **Table 2: Baseline Regressions**

The regressions below are estimated using country fixed effects and robust standard errors clustered at the country-year level. The dependent variable _Access to finance_ is a dummy variable that indicates whether the firm has access to a loan, overdraft, or a line of credit. The _Lerner index_ is a measure of competition (higher values imply lower levels of competition). The _Herfindahl index (HI)_ and _Concentration 3_ are measures of concentration. _Log firm size_ is the logarithm of the firm’s number of permanent employees. _Log firm age_ is the logarithm of the firm’s age in years. _Government-owned_ and _Foreign-owned_ are dummy variables that equal one if the firm has government or foreign ownership, respectively. _Exporter_ is a dummy variable that indicates if the firm is an exporting firm. _Manufacturing_ is a dummy variable that takes value 1 if the firm is in the manufacturing industry. _Financial development is_ measured as domestic credit to the private sector as a fraction of GDP. The _inflation rate_ is measured as the growth rate of the GDP deflator (annual). Results in column (b) are weighted by the inverse of the standard deviation of the Lerner Index. *** p<0.01, ** p<0.05, * p<0.1

|||Acc<br>|ess to finance<br>||
|---|---|---|---|---|
|Variables|(a)|(b)|(c)|(d)|
|Lerner index|-0.615**|-0.749**|||
||[0.269]|[0.335]|||
|Concentration 3|||-0.129<br>[0.142]||
|Herfindahl index||||-0.033<br>[0.148]|
acceptable to invade private property or engage in antidemocratic behavior (See Table D.26).

_Spillovers in non-guerrilla areas during territorial control and in the post-war period_ — We also rule out that effects stem from counter-insurgency in nearby control areas during the period of guerrilla control. It’s possible that nearby control areas benefited from the lack of development or the agricultural focus in guerrilla areas. In this case, effects would be concentrated close to the boundary or just in the rd sample. First, evidence from the doughnut-hole analysis shows this is not so: effects are robust to excluding observations close to the boundary. Second, if we increase the sample beyond the bandwidth to 17 km, we see homogeneous effects on development.<sup>37</sup>

> 36We checked for this possibility by digitizing the number of commercial establishments 2 km around the boundary of past guerrilla presence using Google Maps. We could not distinguish any significant differences between treated and control areas in the number of commercial establishments. The estimates are available upon request.

> 37One potential concern (as with many rd designs) is that we observe cross-sectional differences today in development. Due to the lack of panel data, we cannot disentangle how much the effects originate in improvements in the control group and deterioration in former guerrilla areas over time versus just improvements in the control group and no changes in former guerrilla areas. Hence, we analyze heterogeneous effects based on distance to a main road, dis-

43
0.871|0.878|(0.886)|0.846|0.824|(0.791)|0.895|0.928|(0.501)|
|Never married|0.335|0.295|(0.536)|0.330|0.258|(0.451)|0.340|0.329|(0.902)|
|Access to mobile phone|0.983|0.986|(0.856)|0.981|0.977|(0.903)|0.984|0.994|(0.518)|
|Access to internet(Wi-Fi)|0.185|0.156|(0.581)|0.168|0.125|(0.556)|0.202|0.186|(0.828)|
|Observations|2,480|2,212||1,210|804||1,270|1,408||

_Notes:_ This table compares the average characteristics of the individuals in our sample and individuals in El Salvador. The 2022 Household and Multipurpose Survey (EHPM) provided the data for individuals in El Salvador that we compared to data that we measured similarly in our survey. Columns (1) to (3) compare the two full samples and Columns (4) to (9) compare the samples by the Departments of San Salvador and Usulután. We restricted the EHPM sample to working-age household members (aged 15 to 64 years) in rural areas.

46
the world (Adamopoulos, 2018). Second, the transport program we study includes both large economic corridor upgrades aimed at connecting cities, as well as smaller-scale rural road improvements. This allows us to examine differential patterns of effects according to the type of transport investment, as reflected in the second part of our analysis.

The large number of roads upgraded and localities connected over the program period allow us to study the impact of the program as a whole, and of the different types of investments separately. The overall objectives of the program were to support the rehabilitation, improvement, and construction of roads with access to ports (particularly important given that Ethiopia is landlocked), roads that link to major economic centers and resources, and roads connecting areas with potential for commercial agriculture (Ethiopian Roads Authority, 2015a).

> In this paper, we ask whether road upgrades promote growth in local economic activity and produce changes in land use, particularly urban land and cropland. We use three empirical approaches: (1) a

> 1Number extracted from the World Bank projects database, accessible here `https://projects.worldbank.org/en/ projects-operations/projects-list?sectorcode_exact=TI`

2
and services. For Finland, the high turnover in manufacturing is likely the result of major restructuring, which took place in the aftermath of the deep recession of the early 1990s. The lower turnover rate in the French service sector compared with that in manufacturing is likely to depend on the existence of a size threshold in the French data, which tends to be more binding in the service sector than in manufacturing. As an indication, the French data also suggest a higher average size of firms in the service sector than in manufacturing, in contrast with all other countries.

19
5 While the original INDSTAT 2 database includes 23 manufacturing industries, exclude the “manufacture of recycling” industry due to insufficient observations.

6 The average and standard deviation of the change in the tariff rate in our sample are -0.4 and 3.6 percentage points, respectively. Tariff changes range from -52.0 to 41.0 percentage points.

- 7 Table 2 tabulates the underlying regression results.

8 Employment increases by about 0.5 percent but the effect is not statistically significant.

9 This result is consistent with evidence in Jaumotte, Lall and Papageorgiou (2013) who find that trade openness is associated with lower income inequality. While more work is needed to understand the distributional effects of tariffs, we believe that the increase in unemployment is a potentially important channel. Another possibility is that rent-seeking means that protectionism benefits more the rich than the poor.

10 All the results are robust when the real trade balance is deflated by trend real output (instead of real output).

- 11 See Appendix S3 for some examples of major tariff increases in our sample.

27
of parents, number of family members living in the same household, the availability of household assets as well as gender, age, geographic location and GPA of the applicant, among others.

Second, to measure students’ ability at baseline, we use the information from the censusbased ENLACE 9th grade, measuring math and language achievement levels. From 2007 to 2013, ENLACE was administered to all students in 3rd to 9th grades and those finishing 12th grade. The test had no consequences either on graduation or on student’s GPA. The score of ENLACE is normalized to have a mean of 500 and a standard deviation of 100.

Using the CURP we were able to merge the baseline application format with the micro data from ENLACE 9th grade which was taken by applicants in May 2009. For ease of exposition and interpretation, when presenting the results, we renormalize the ENLACE results to a mean of zero and a standard deviation of 1. Table 2 shows the baseline characteristics, distinguishing between students in the treatment and the control groups. In the top panel we report the socioeconomic characteristics measured through the baseline format completed by all applicants, in the bottom panel the administrative information on 9th grade test scores. Overall, the characteristics of the treatment and control groups are well balanced in line with the randomized design of the evaluation.

Outcome variables are measured through ENLACE 12th grade administered in May 2012 to all students finishing EMS. Additionally, our evaluation sample was also merged with ENLACE 12th grade of 2013 to identify students that graduated from high school but that had a lag of one year. The participation of students in our sample, who entered EMS in August 2009, in ENLACE 12th grade of 2012 or 2013 is used as a proxy for upper secondary graduation.<sup>9</sup> The same end-of-secondary-school test is also used to measure the impact of PROBEMS scholarship on math and Spanish test scores.

> 9In what follows, when we refer to ENLACE 12th grade, which includes the information from the tests administered in
is usually achieved through a measure of bilateral asymmetry that quantifies the magnitude (and direction) of the observed discrepancy. Many such measures have been proposed to assess the quality of the UN Comtrade database (Carrère & Grigoriou, 2015, Chen et al., 2022; Farhad et al., 2023). These measures have proven especially useful in understanding general patterns in trade reporting, pinpointing uncertain and problematic data, and relating country-specific and bilateral characteristics to misreporting. However, special attention must be paid to both structural and non-structural causes of discrepancies in the measure’s construction and interpretation.

7