rafmacalaba/data-use-mentions-extended huggingface dataset:
052|0.246|
|SecurityIndex|21349|3.683|1.787|17535|3.648|1.755|
|Environmental Index|22196|0.018|0.161|18321|0.02|0.16|
|Financial literacy|22196|0.172|0.377|18321|0.18|0.384|

_Source: World Bank estimates based on EHPM (2019)_

# 5.2. Vulnerability to Poverty: Recent Trends

**This subsection presents estimates of ex-ante vulnerability to poverty over time in the more recent period 2016-2019** . These estimates rely on the household surveys available at the time of this publication. Even though the 2020 data was publicly available, the collection of the 2020 data was affected by the COVID-19 pandemic, potentially affecting the comparability of the income aggregates over time. The statistical office (DIGESTYC) continuously collects the household survey from January to December. Still, in 2020 data was not collected from March to July (the period of strict confinement in which labor incomes probably fell the most); therefore, the entire sample was not covered.

**Our estimates show that the vulnerability rate nearly halved during the period 2016-2019 in El Salvador from a total vulnerability rate of 0.39 in 2016 to 0.24 in 2019, with decreases in both rural and urban areas** . The decrease in vulnerability is 23.8 percentage points in rural areas and 11.1 percentage points in urban areas (see Figure 6). The decline in vulnerability to poverty is mainly related to a parallel decrease in poverty (falling from 31.4 percent in 2016 to 22.3 percent in 2019, when measured in 2011PPPs). Therefore, the share of households close to the poverty line is lower, and a lower share of households switched their poverty status, which then also lowers the rate of households being vulnerable.

14
16

# Footnotes

- 1/ Conditions for product mix upgrading have been analyzed by Falvey (1979) and Rodriguez (1979). Quality upgrading for automobiles and footwear have been shown by Feenstra (1984) and Aw and Roberts (1986).

- 2/ These two allocation criteria are found by Hamilton (1986a) in his survey of export license criteria for clothing exports among ASEAN countries subject to VERs.

- 3/ The analysis with increasing marginal costs is available in appendix form from the authors upon request.

- 4/ McCulloch and Johnson analyze the simpler case of two-tier allocation tchemes for import licenses with a single market demand curve and do &..t have to consider tradeoffs between welfare and efficiency.

- 5/ This quota solution could have been achieved by an export tax to the -

- restricted market at the rate (PR C').

- 6/ More precisely if the unit elasticity point is to the right (left) of the mid-point between H and R, foreign exchange earnings in the nonrestricted market will rise (fall).

- 7/ In his fascinating description of US negotiation of footwear VERs with Korea and Taiwan, Yoffie states that Korean and Taiwanese officials urged footwear producers to increase shipments to the US in early 1976 because they anticipated that a VER would soon have to be negotiated.

- 8/ When export earnings are maximized, the efficiency loss, a. as a portion of rents is given by the expression:

<!-- Start of picture text --> aO(PNR _ - 1) e R " PNR<br>X~ 0\ - 1)<br><!-- End of picture text --> where tan - AHIAC a.

9/ Since 1980, over 300 anti-dumping cases have been initiated by both the EC and the US. The NICs share in the US and EC increased sharply in 1985 reaching 45Z of all cases in both the US and the EC. We thank Patrick Messerlin for providing this information
0.29|0.25|
|**Access to basic services**||||||||||
|Improved water|0.86|0.61|0.87|0.62|0.85|0.66|0.71|0.77|0.93|
|Improved sanitation facility|0.45|0.51|0.52|0.15|0.63|0.13|0.28|0.22|0.83|
|Access to electricity|0.41|0.46|0.93|0.21|0.74|0.10|0.56|0.39|0.99|

Source: International Urban Poverty Database. Note: Real per capita consumption expenditures are deflated using a spatial deflator calculated based on the WorldPop 250m dataset and the DOU method.

89
estimates and other welfare indicators for Kazakhstan rely on the 2017 round of the HBS, conducted by the Statistics Agency of the Republic of Kazakhstan. For household consumption and expenditure, the survey is usually considered nationally representative, representative at the oblast (region) level, and separately representative for rural and urban areas. The survey uses a stratified sample design with strata corresponding to 14 regions + 2 large cities crossed by their urban and rural areas (except for Almaty and Astana cities, which are entirely urban). A complete consumption module is gathered in the HBS, covering both food and non-food items. Information on household composition, income, employment, and related topics is also collected. All data for the HBS in Kazakhstan are collected in person, except for consumption, which is collected using a diary-type instrument. The survey is continuous, and representative quarterly within the year for most welfare indicators.

18
- Henderson, Vernon and Hyoung Gun Wang, “Urbanization and City Growth: The Role of Institutions,” _Regional Science and Urban Economics_ , 37(3), (2007): 283-313.

- Henderson, Vernon and Hyoung Gun Wang, “Aspects of Rural-Urban Transformation of Countries,” _Journal of Economic Geography_ , 5(1), (2005): 23-42.

- Himanshu, “Recent Trends in Poverty and Inequality: Some Preliminary Results,” _Economic and Political Weekly_ , 42(6), (2007): 497-508.

- Kathuria, Vinish, Seethamma Natarajan, Rajesh Raj and Kunal Sen, “Organized versus Unorganized Manufacturing Performance in India in the Post-Reform Period,” MPRA Working Paper 20317 (2010).

- Knoben, Joris, “The Geographic Distance of Relocation Search: An Extended Resource-Based Perspective”, _Economic Geography_ , 87(4), (2011): 371-392.

- Knoben, Joris, Leon Oerlemans, and Roel Rutten, “The Effects of Spatial Mobility on the Performance of Firms”, _Economic Geography_ , 87(2), (2008): 157-183.

- Kundu, Amitabh, “Method in Madness: Urban Data from 2011 Census,” _Economic and Political Weekly_ , 46(40), (2011a): 13-16.

- Kundu, Amitabh, “Politics and Economics of Urban Growth,” _Economic and Political Weekly_ , 42(20), (2011b): 10-12.

- Kundu, Amitabh, “Exclusionary Urbanization in Asia: A Macro Overview,” _Economic and Political Weekly_ , 44(48), (2009): 48-59.

- Kundu, Amitabh, “Trends and Pattern of Urbanization and Their Economic Implications,” India Infrastructure Report (2006).

- Kundu, Amitabh, Basanta Pradhan and A. Surmanium, “Dichotomy of Continuum: Analysis of Impact of Urban Centres on Their Periphery,” _Economic and Political Weekly_ , 37(50), (2002): 5039-5046.

- Lall, Somik, “Infrastructure and Regional
paper was 6 months before these trade reforms and that the effect presented in the graphical periodic coefficients shows that response was mostly after this period, we test the effect of these trade policies on FDI. This is also in line with the literature on complementary institutional reforms in addition to FDI reforms to the extent that these regulatory changes improved the trade regime or were perceived to do so.

We use the same methodology, with the reform period adjusted to November 2021 instead of May 2021, and focus on the all the manufacturing sectors, and the fully liberalized non-commodity sectors.

We find that realized FDI in all manufacturing sectors increased by 103.2 percent following these trade reforms (Table 7). In fully liberalized non-commodity sectors, realized FDI also increased by 21.2 percent after the trade reforms compared to the period before the trade reforms. Figure 7 shows the period-by-period coefficients.

While the caveat should be noted that the post-trade reform period is even shorter than that for the investment reform, this may signal the importance of complementary trade reforms and that the shift between the levels of liberalization is still important. Some of the trade reforms were being implemented after they were enacted, which may have had mixed effects. Crucially, this analysis does not distinguish which of these (many) trade regulatory changes may have been the key to this response as that is beyond the scope of this analysis.

Table 7: Event study results of the response of Realized FDI to trade policy changes in November 2021

|ATET|ATET|ATET|
|---|---|---|
|All Manufacturing Sectors (1vs0)<br>1.032***<br>(0.0796)|||
|100 % (1vs0) Liberalized Non-Commodity Sectors|0.212***<br>(0.0282)||
|Non-Fully Liberalized Non-Commodity Sectors (1vs0)||-0.197***<br>(0.0275)|
|Observations
11 times their current income. Using these three measures, we also see that respondents would be less inclined to migrate for jobs that they are overqualified for, unless they receive a substantial earnings premium.

In a context marked by economic and political upheaval, economic and political stability can drastically alter migration intentions. Our survey experiment shows that while political stabilization, understood as a cessation of violent conflict and reaching a political settlement, would reduce migration intentions, economic stabilization alone may not have any such effect. This finding has critical policy implications as it shows the limits of relying on plausible economic improvements to stem talent outflows without addressing political instability and conflict in the country. If political instability continues or worsens, one can expect a gradual exodus of highskilled individuals out of the country. This in turn could have pernicious implications for the functioning and productivity of key sectors and occupations that rely on high-skilled workers. A disproportionate exit of skilled workers could also harm economy-wide productivity in the long run. Any efforts to stymie such movements by authorities can only aggravate migrants’ vulnerabilities; as long as the underlying intent to migrate remains strong, individuals may be compelled to rely on irregular and risky channels.

While this paper has used cross-sectional data to study migration intentions and their interaction with stabilization prospects, there is little robust causal evidence on actual migration flows in response to stabilization in complex settings. Future research could potentially build on some of the methods developed in this paper and use panel data to study high-skilled migration flows from settings characterized by multiple sources of instability. A more detailed analysis of individual characteristics that drive migration responses to stabilization efforts would also deepen some of the initial insights offered in this paper.

18
<mark>Note: Each point represents the combination of employment to population ratio as (comparative data, Internet survey data). Average relative deviation is the average of relative values of absolute deviation of the Internet survey from the comparative data. Specifically, we calculate the average of abs(Onlinecomparative)/comparative.</mark> <mark>Data on other labor market indicators were collected by the survey, including the formal versus informal nature of employment, and type of employment. Respondents are classified to be working formally if they have a written contract, if they have any form of social insurance, and if they get annual paid or sick leave. Those who do not satisfy any of these three conditions are deemed to be working informally. The respondents are classified as self-employed if they own a business or business operated by the household or a family farm. They are instead classified as an employee if they work as an employee for another house, or another company, or as an apprentice, trainee, etc. The questions related to formality and self-employment are asked only to those who responded that they are</mark> _<mark>currently</mark>_ <mark>employed at work, and not to those employed but not</mark> _<mark>currently</mark>_ <mark>at work. Therefore, the survey sample size for these questions is lower than for the previous graph.</mark> <mark>The comparative data for formal and self-employment are available for fewer countries and fewer time periods. Figure 5.3 and figure 5.4 present a scatter plot of the formal share between online surveys and the comparative data, and a scatter plot of the self-employment share between online surveys and the comparative data, respectively. For the propensity score adjusted online estimates of formal employment, the deviations from the comparative data range from 12.7 percent to 55.04 precent, with an average of 39.1 percent. Without weight
# **1.1 Related Literature**

Our work connects to several strands of literature. First, we contribute to the literature on firms’ strategies to minimize tax payments. While tax evasion (Slemrod, 2019) and tax avoidance via profit shifting (e.g. see Tørsløv et al. 2022, Bilicka 2019, Beer et al. 2020) received most attention, we document another channel: the use of tax expenditures. The limited evidence we have thus far points to their importance: Klemm (2010) details the types of tax expenditures and argues that they are frequent in low-income countries. Garcia-Bernardo et al. (2022) show that only a moderate share of the fall in ETRs worldwide in recent years is attributable to profit shifting, with the remainder due to domestic tax policy changes, including tax expenditures. Better understanding firms’ use of tax expenditures matters for tax revenue and for economic activity.<sup>5</sup> We are the first to document the extent to which tax expenditures reduce firms’ ETRs in a diverse set of countries.

Second, the literature on tax evasion and avoidance shows that tax minimization strategies strongly vary with firms size: tax evasion rates decrease with firm size (Best et al., 2022; Basri et al., 2019; Bachas et al., 2019), while tax avoidance increases (Gumpert et al., 2016; Davies et al., 2018). Yet, the relationship between tax expenditures and firm size has not been systematically investigated before. We do this with granular data and along the entire (formal) firm-size distribution, uncovering an important non-linearity in the ETR-firm-size relationship.

Third, our work relates to a literature at the intersection of economics and accounting that examines the ETR-firm-size relationship (see Jansk ́y (2022) for a survey and Table A.1 for a summary). These papers differ in their methods (data and ETR definition) and results. We make progress by using tax administrative data for
Lastly, the impact is larger for mothers of six-year-old children who are self-employed. These results are not surprising, as entrepreneurs might themselves be especially affected by a lack of childcare possibilities, and drop out of leading businesses or entrepreneurial activities.

In sum, these findings indicate that women who faced more impediments to labor market opportunities previously to the reform, for example in the form of less infrastructure in rural areas, the lower possibility to combine work with childcare responsibilities in the case of entrepreneurial activities, or due to a greater security network in form of other incomegenerating individuals in the household, experience greater effects of the reform.

# **5.3 DDD Effects**

An omitted variable that affects the employment of mothers of six-year-old children differently than the employment of mothers of three- to four-year-old children could bias our estimates from difference-in-difference regressions. Adding a third difference might generate more reliable results (Angrist and Pischke 2009).

We add a third difference by differentiating between mothers of children who indeed participated in preparatory classes and preprimary childcare, and those who did not. This approach allows us to control for any factors that might impact mothers of six-year-old children differently than those of younger children. At the same time, it allows us to control for unobservable factors that could drive the employment of mothers who send their children to public childcare and early childhood education facilities and those who do not tend to take advantage of these services. One important shortfall of our triple difference estimation is the fact that preparatory classes are compulsory while all forms of early childhood education and childcare that target children younger than six years old are voluntary.

To identify these groups, we leverage data from the European Union Statistics on Income and Living Conditions (EU-SILC) from 2010-2020. In contrast to the EU-LFS, the EU-SILC, which collects data on living conditions and income in the European Union, contains infor17
This paper employs a cross-country study to estimate _tax capacity_ from a sample of 110 developing and developed countries during 1994-2009 and the two sub-periods of 1994-2001 and 2002-09. In this study, we extend the empirical methodology applied by Tanzi and Davoodi (1997), and Bird, Vazquez, and Torgler (2004). The estimation results are used as benchmarks to compare taxable capacity and tax effort in different countries. _Taxable capacity_ refers to the predicted tax-to-GDP ratio that can be estimated with regression analyses, taking into account a country’s specific macroeconomic, demographic, and institutional features. _Tax effort_ is defined as an index of the ratio between the share of the actual tax collection in GDP and the taxable capacity. The concepts of taxable capacity and tax effort are also extended to measure total fiscal revenue capacity and revenue effort.

Calculating tax effort and actual tax collection benchmarks allows us to rank countries into four different groups: (i) low tax collection, low tax effort; (ii) high tax collection, high tax effort; (iii) low tax collection, high tax effort; and (iv) high tax collection, low tax effort. This classification is based on the global average of tax collection and a tax effort index of 1, corresponding to the case when tax collection is exactly the same as estimated taxable capacity.

The analysis provides guidance for countries with various levels of tax collection and tax effort. The authors argue that taxation is always a critical dimension of fiscal policy for all countries, while countries at various stages of development and with different initial levels of tax collection and effort should rely on different strategies for tax reforms. Our analysis focuses on tax performance and provides broad directions for reforms in developing countries.

Section II provides an overview of the worldwide trend in tax revenue collection across incomegroups and geographic regions, using the tax-to-GDP ratio as a measure of tax collection. Section III highlights alternative measures of the tax performance of countries and extends the existing literature to the empirical estimation of a country’s taxable
Women in much of the Arab World are very lightly concentrated in industry.<sup>8</sup> In oil exporting countries (OECs) of the Gulf, they are mostly concentrated in services<sup>9</sup> and in oil importing countries (OICs), such as in Morocco and Egypt, they are additionally concentrated in agriculture (UNDP 2021). Female participation in industry is generally below 15% throughout the region with the exception of Tunisia (33%) and Algeria (25%). With just 7% of total female participation in industry, Egypt occupies the bottom position compared to its OICs counterparts. In fact, quite comparable to the average for the group of OECs.

With such limited participation in industry and in turn manufacturing in Egypt, it is expected that the effect of COVID-19 on women employment be limited. Our firm-level representative sample data show that overall, there has been a decrease in manufacturing employment in response to COVID-19 for both men and women. The reported decline has been however quite small and accounts for less than 5% of original weighted employment prior to COVID (Table 1; column 3). This decline is equivalent to just 10353 jobs in our sample when we use weights.<sup>10</sup> In terms of percentage change this decline hit men harder (-5% compared to -3.6% for women; columns 6 and 9). Female participation within manufacturing is just 18.2% and has slightly increased to 18.4% post COVID, indicating that women are heavily underrepresented in manufacturing and that’s probably the reason why men are hit harder in this male dominated sector of the economy.

**-** **<u>Table 1: Employment pre and post COVID and labor market participation by gender</u>**

|Total|Total||Male|Male|% change|Female|Female|% change|F share in|F share in
*|47.28||11.0|
|Price of a 3-minute call to the United<br>States|**2.0**|**0.9**|1.44||2.0|
|Price of inter-Africa calls, average|**0.6**|n.a.|0.57||n.a.|

Source: Minges and others 2009, derived from AICD national database downloadable from http://www.infrastructureafrica.org/aicd/tools/data. — = data not available. n.a. = not applicable. Côte d’Ivoire is connected to the SAT3 submarine cable, which provides good connectivity to the internet. International bandwidth has improved markedly in recent years. Yet the national 27
We make five observations based on these results. First, export growth enters in the majority of estimations as positive and significant. This is interesting in that it suggests that a discovery-promotion strategy may have much in common with an export-promotion strategy, if one believes that the penetration of a foreign market is itself a discovery (and if not, including this variable is a necessary correction for the fact that we are using export data rather than domestic production data). This finding could contradict the argument that trade liberalization implies more potential imitators and therefore lower appropriability ( _q_ ), it is harmful for discovery. To the extent that liberalization increases export activity, our data suggest that it may have a positive relationship with discovery.

The second observation concerns the absorptive capacity variables. Using the 4-digit data, they enter as negative and jointly significant. In addition, the journals measure enters as negative and individually significant with the 6-digit data, although not jointly significant when tested with the patent data. This negative relationship is quite surprising, considering that absorptive capacity was expected to have a positive effect on a country’s ability to discover new products, although it might also affect the ease of imitation, thereby reducing discoveries.

The third observation, consistent with the results of the absorptive capacity variables, relates to the barriers to entry variable in the 6-digit data, which enters as positive and significant. That is, higher barriers to entry are associated with an increase in discovery activity. Given that more procedures in the process of starting a new business increases the costs of a first mover, we would expect that in absence of market failures this variable should have a negative relationship with discovery activity. This result, combined with that relating to absorptive 34