rafmacalaba/data-use-mentions-extended huggingface dataset:
developed within the framework of the Women’s Empowerment in Agriculture Index (WEAI), have explored combinations of these approaches. They argue that stylized questions are more suited for activities that tend to follow a fixed schedule, whereas time diaries are more appropriate for activities that are not exceptionally salient nor follow a fixed schedule (e.g. agricultural labor) (Seymour et al., 2017).

# 4.2.1. Keyword questions

The first approach to determine whether a person is employed is a (single) keyword question. This approach is often used in short surveys such as population and housing censuses<sup>12</sup> and in surveys that do not aim to collect detailed labor market data such as the DHS (Fox & Pimhidzai, 2013). The defining characteristic of keyword questions is that they include a single keyword such as activity, work or occupation, and are not preceded or followed by probing and/or screening questions that define the keyword. The risk is that the keyword is not interpreted consistently by respondents, enumerators and data users. The best‐known example of this approach is the DHS questionnaire that includes a different keyword question for men and women. Since 2013 the question for men reads as _‘Have you done any work in the last seven days?’_ The women’s questionnaire includes the questions _‘Aside from your own housework, have you done any work in the last seven days?’_ as well as _‘As you know, some women take up jobs for which they are paid in cash or kind. Others sell things, have a small business or work on the family farm or in the family business. In the last seven days, have you done any of these things or any other work?’._

# 4.2.2. An activity list

The second approach uses an activity list, which consists of a complete list of jobs/activities that are common in the region. Some
tenure than the youngest workers aged 20–24. The DP decomposition produces comparable results, finding a 3.4-year difference. The estimates of the two decompositions diverge further for older workers. For example, the ME approach finds that workers 50–55 have about 10.7 more years of tenure than workers from the youngest group; the DP decomposition reports an 11.7-year difference.

<u>Figure 4 presents the cohort effects on tenure for both estimation methods. The average tenure</u> declines over time for younger age cohorts in both decompositions. The negative gradient of job tenure is more pronounced in panel a, which shows the results of the ME decomposition. The average worker born in 1940, for example, has 3.6 more years of tenure than the average worker born in the 1980s. The DP decomposition shows similar dynamics, with a weaker decline in tenure over cohorts (the difference in tenure between the 1940 and 1980 cohorts is 2.6 years).

<u>Figure 5</u> shows the estimated period effects for both estimation methods. We grouped survey years into five-year intervals to preserve the APC age-period-cohort identity. This grouping results in only five survey periods, making the decomposition of the period effects less informative. Nevertheless, the ME decomposition indicates an increase in average job tenure between 1995 and 2020 by about a year. The DP decomposition produces a small, barely significant change in the time effects.

# **4.1. Subsample decompositions**

We now turn to subsample decomposition to explore the heterogeneity of the period, age, and cohort effects on tenure duration among different groups of workers. We also want to account, to some degree, for potential compositional change in the labor market during the period covered by the EU-LFS. The analysis in this section is based on the ME APC decompositions.

<u>Figure 6 shows the decomposition of the age effect by gender, educational level, region, and type</u> of contract
These distributional predictions are not, however, borne out in the CMMHH data, which shows the highest rate of job losses in the middle wage quintile (35.7 percent), and lower rates of loss at the bottom (9.7 percent) and the top (8.3 percent). Data on the occupational and pay structures within firms is likely needed to better identify the distributional dynamics of employment outcomes both during a crisis and during normal times of workforce adjustment. In developing countries such data are lacking.

## **5.7.2 Georgia**

|_Table 5-25 Jordan: Percentage_<br>**National nominal hourly**|_of PFPS Jobs L_<br>**Wave 1**|_ost, by Wage Q_<br>**Wave 2**|_uintile_<br>CFUWBES||
|---|---|---|---|---|
|<br>**wage quintile**|CFUWBES1<br>Modeled|CFUWBES2<br>Modeled|2<br>Survey<br>Measured|**CMMHH**|
|**Q1 (bottom)**|19.0|30.4|30.1|9.7|
|**Q2**|16.6|26.5|25.5|26.7|
|**Q3**|14.0|22.6|22.6|35.7|
|**Q4**|14.1|21.0|23.5|17.1|
|**Q5 (top) **|13.5|21.4|25.0|8.3|
|**Total**<br> Sources: CFUWBES1, LMPS 20|15.8<br>16, and CMMHH|25.2<br>Jordan 2021.|25
nificant share of the population also reshaped the political landscape and created conditions favorable to the expansion of activity by organized crime groups. The following sections document these parallel processes, and a mediation analysis subsequently quantifies the extent to which the economic effects documented here operate through political and criminal channels.

# **5.1 Additional robustness tests**

**Effects are not mechanically driven by the population decline.** To validate that our main results are not mechanically driven by the population decline, we estimate the effects of forced displacement using annual ENCOVI data to calculate poverty rates and unemployment by state and year between 2017 and 2021.<sup>22</sup> The results point to increments in poverty and lower employment (Table E.13). However, the coefficients are smaller given that real income is extremely low during the period for which microdata exist (2017–2021). In fact, income nationwide declined dramatically and hyperinflation caused a complete generalized loss of purchasing power in this period. In fact, as noted earlier, by 2021, 94 percent of individuals had an income below the poverty line (Figure 2).

**Other specification alternatives.** Importantly, our core results remain consistent across a number of additional robustness tests, including: approximating the municipal variation of imputed outflows with the linear-and-road inverse distances of each municipality to the main entry points in Colombia (Tables E.5 and E.7); using alternative difference-indifference estimators, in line with the latest methods in the literature (Table E.9); employing only the Colombian foreign shares in Venezuela in 1990, instead of total foreigners share, to approximate the variation in foreign settlement share and imputed outflows (Table E.10); and correcting standard errors for clusters at the municipality-year level (Table E.11).

> 22We cannot use data beginning in 2014 due to the low number of cities covered for those initial years.

31
1. _Introduction_

Recent years have seen an increased importance of international trade in goods and financial services. To facilitate such trade, many banking institutions have also become international.<sup>2</sup> Banks expand internationally by establishing foreign subsidiaries and branches or by taking over established foreign banks. The internationalization of the banking sector is facilitated by the liberalization of financial markets worldwide. Developed and developing countries alike now increasingly allow banks to be foreignowned.

Financial liberalization of this kind proceeds on the premise that the gains to domestic market participants from foreign entry outweigh any losses to domestic banking institutions. Several authors have addressed the potential benefits of foreign bank entry for the domestic economy in terms of better resource allocation and higher efficiency (see Levine (1996), Walter and Gray (1983), and Gelb and Sagari (1990)). Levine (1996) specifically mentions that foreign banks may (i) improve the quality and availability of financial services in the domestic financial market by increasing bank competition, and enabling the application of more modern banking skills and technology, (ii) serve to stimulate the development of the underlying bank supervisory and legal framework, and (iii) enhance a country's access to international capital.

As yet, little cross-country systematic evidence exists that these presumed benefits of an internationalization of the banking sector indeed materialize. The literature, however, contains several case studies of financial liberalization episodes. McFadden ( 1994) reviews foreign bank entry in Australia, and finds that this has lead to improved domestic bank operations. Bhattacharya (1993) reports specific cases in Pakistan, Turkey, and Korea, where foreign banks helped to make foreign capital accessible to fund domestic projects. Pigott (1986) describes the policies that have made increased foreign bank activity possible in nine Pacific Basin countries, and he provides some aggregate statistics on the size and scope of foreign banking activities.<sup>3</sup> Using aggregate accounting data, Terrell (1977, Table 20-2) further compares the banking markets
World Bank's South Asia Labor Flagship team for providing the primary datasets used in this paper. We are particularly indebted to Shanthi Nataraj for sharing her wisdom regarding the industrial survey data during the nascent stages of this work. Funding for this project was provided by World Bank and the Multi-Donor Trust Fund for Trade and Development. Our online appendix that contains additional materials noted throughout this study and code for replicating the analysis is available at Stephen O'Connell's website. The views expressed here are those of the authors and not of any institution they may be associated with.

1
. The sample mean expenditure per capita in 2000 was 1 _,_ 752 _._ 96$ for rural areas and 3 _,_ 514 _._ 9$ for urban areas, which increased to 2 _,_ 265 _._ 9$ (+29%) and to 4 _,_ 053$ (+15%) respectively in 2007. The bulk of the dependent variables seem to have constant values over the years, with the notable exception of electricity. In rural areas, the proportion of families with electricity increased from 0.35 to 0.70.

The first model tested was the log-linear regression over the split data set. The results (see table [A.1]) are consistent with those presented by Douidich et al. (2016). Illiteracy and a low level of education have a negative impact on expenditure, while a higher number of rooms per capita has a positive impact, all other things being equal.

3Once the structure of questions and answers has been checked, we suggest also performing a graphical analysis of PDF and checking position and variability parameters, see Betti et al. (2018). We do not report this analysis for all the variables since the comparability has already been checked by Douidich et al. (2016) and we use the same set of variables. It is, however, important to underline that since 2015, Morocco has officially administered 12 regions. Previously, there were 16 regions. From that moment the new regions and the oldest ones are not directly comparable. In the interest of future comparability, we decided to use 14 regions, which was also decided by the Moroccan statistics department that unified the regions that had been merged. For more on this point, we recommend the official survey site. The only other variable that needs an explanation is the “low level of education,” with a value of 0 “up to the 1st cycle" and 1 for "over the 2nd cycle.

7
in Other Cities fell by 24 percent. Thus, it seems that public sector employee households in Abidjan were better placed to draw on other sources of income or savings to mitigate the decline in their public sector salaries than public sector employees outside Abidjan.

Tlhe outcome for the informal sector seems to be strongly influenced by the outcome of other segments of the local economy. The big difference between Abidjan and Other Cities is that poverty in the informal sector (i.e. employees in the informal sector or self-employed) in Abidjan showed a big increase, while in Other Cities it declined (table 18). Informal sector households in Other Cities may have benefited from higher derived demand from the rural areas and have more agricultural income. It is hard to draw firm conclusions about self-employed in rural areas, since the sample size of the rural self-employed in 1995 amounts to only 5 percent of the population; poverty declined among these households in West Forest and the Savannah, but increased in East Forest.

**Table 18 Urban Headcount Index of Poverty by Major Socioeconomic Group** _(Poverty Line = 75,000 CFAF per year in 1985 CFAF)_

||_Abi_|_djan_|_Othe_|_r Cities_|
|---|---|---|---|---|
|_Socioeconomic Group_|_1993_|_1995_|_1993_|_1995_|
|Public sector employee|0.002|0.065|0.140|0.274|
|Private sector formal employee|0.049|0.055|0.128|0.188|
|Informal sector|0.058|0.291|0.338|0.278|

21
taking into account data of that year, the contribution in population of the Eastern European nations is of about 100 million inhabitants, which translated into a 28% increase in the EU population whereas in added terms, the increase in GDP was of nearly 7%, emphasizing Poland‘s contribution of 42.7% of that value (Alcalá, 2004: 144).

In terms of rent per capita, the set of the countries of Eastern Europe was placed in 2004 in 4,380 Euros (current exchange rates) and 9,100 (PPP) Euros, respectively, which supposed 20% and 40% of the per capita income in the Europe of the fifteen. By countries the issue was somewhat different: in the case of Rumania the number in PPP was of 24% whereas in Hungary the per capita income was almost a 70% of the EU15. All this put into evidence the retard of these countries, but mainly the effort (with a very high degree of heterogeneity) needed to obtain the much desired real convergence of the EU27.

Another trait to consider is the characteristic of its productive structure: in the countries of the enlargement, more than 20% of the population was occupied in the agricultural sector whereas in the EU15 that percentile was of 4.8%. Among the countries one can highlight are Romania (40%), Bulgaria (28%) and Poland (26%). As far as foreign trade is concerned, the entailment of the 12 countries with the EU15 (exports and imports) approximately reached 60% of its trade balance whereas for the EU15 that value remains below 2.5% (Alcalá, 2004).

> 3 Randomization, was not possible either since the treatment group was not randomly selected.

> 4 Ravallion, M. (1999: ―The Mystery of the Vanishing Benefits: Ms. Speedy Analyst's Introduction to Evaluation‖. Policy Research Working Paper 2153, World Bank, Development Economics Research Group, Washington, D.
# **5.2 Results by type of visa provisions**

In Table 5 we show the effect of specific migration-related provisions in RTAs.<sup>26</sup> Visa provisions having legal enforceability _via_ a dedicated dispute settlement mechanism (column 1), and those easing of administrative procedures for migration (column 4) are the most effective in boosting bilateral migration. In particular, the inclusion of a dispute settlement mechanism in visa provision as well as provisions aimed at reducing the administrative burden for migration increase the bilateral stock of migrants by 11.8%. Provisions _calling_ for the free movement of persons have a significant effect but smaller in magnitude (i.e. 7.2%).

## – Table 5 about here –

The bilateral stock of migrants may also be affected by the presence of Job Posting related provisions. Under the General Agreement on Trade in Services (GATS), posting is defined as one of the four ways to supply services across borders. Simply put, it allows workers to perform a task (i.e. service) in a foreign country establishment while staying formally employed in its firm’s country of origin. In our case, Posting provisions refers to clauses in RTAs that facilitate the entry of professionals and/or investors among the member countries of an RTA. While we have a provision in our Visa-and-Asylum database that concerns the international mobility of investors, additional Job Posting related provisions may be found in other chapters of an RTA. Indeed, the database on the Investment chapter of Deep Trade Agreements contains a provision dealing with the movement of professionals within the boundary of a multi-national enterprise, which fits even better with the very definition of Job Posting.

In Table 6 we estimate the effect of job posting related provisions on bilateral migration. Namely, in columns (1) and (2) we show the effect of provisions within the Investment chapter of RTAs that aim at easing the movement of business persons (column 1) and professionals (column 2
than SP. Indeed, SP is not even mentioned in the classic policy package for developing countries that emerged in the 1990s, often referred to as the “Washington Consensus,” following Williamson (1990). Williamson identifies health and education as “proper objects of government expenditure,” but says nothing about SP. The more explicitly poverty-

> 2 Following World Bank usage, SP refers to public programs for “social assistance” (in the form of cash or in-kind benefits often targeted to poor families), “social insurance” (mainly unemployment benefits and pensions), and “active labor market programs” (such as job training schemes). On the history of thought on the role of SP see <u>Ravallion (2016a, Part 1).</u>

> 3 See, for example, Kristov et al. (1992), Lindert (1994), <u>Peracchi (1998), Cornelisse and Goudswaard (2002), Auteri and Costantini (2004), Shelton (2007), Brückner et al (2012), and Clemente et al. (2012). The finding that</u> public spending as a whole tends to rise as a share of GDP as GDP rises is sometimes referred to as Wagner’s Law. 4 Figure 1 uses the most recent pre-pandemic data on total SP spending for each country. We consider the pandemic period separately. We also consider the effect of dropping spending on pensions; the pattern in Figure 1 is very similar in this case (Addendum).

> 5 As estimated by a nonparametric regression function in Figure 1. Our use of the term “Engel curve” borrows from the more familiar usage in the context of modeling consumer demands. We are not the first to use the term in the context of public spending, which appears to be Bird (1971). Figure 1 and other SP Engel curves in this paper are nonlinear (and non-parametric) generalizations of the longstanding Working-Leser specification for such Engel curves
conclusion.

# **2. The presumptive tax on small and microenterprises: The Ethiopia context**

Businesses in Ethiopia are classified into three groups for tax administration purposes, namely Category A, B, and C taxpayers. This paper’s focus is on Category C taxpayers, which are unincorporated small and microenterprises, with an annual turnover of less than 500,000 birr (approximately USD 9,040<sup>3</sup> ) (Harris and Seid 2021).<sup>4</sup> Category C taxpayers pay the presumptive tax, which is calculated using the gross annual turnover, and are not required to keep a book of accounts (Proclamation No. 410/2017).<sup>5</sup> The presumptive tax rates differ by activity and revenue, consisting of lump sum tax liabilities for 99 business sectors with 19 turnover bands (with a total of 1,881 activity-bands) (see Council of Ministers Regulation No. 410/2017

> 3 1 USD=55.31 Ethiopian birr (exchange rate on October 6, 2023).

> 4 In contrast, Category A taxpayers are all incorporated businesses (regardless of turnover) and unincorporated businesses with a turnover of more than 1 million birr. Category B taxpayers are unincorporated businesses with a turnover between 500,000 and 1 million birr (Harris and Seid 2021, Mascagni and Molla 2018).

> 5 There is also an indicator system for operating public buses, freight transport, and flour mills (Council of Ministers Regulation No. 410/2017).

4
female proxy respondents over which this sub-group analysis is executed. For land size, on the other hand, we find statistically significant heterogeneous impacts of 4.5 percentage points per additional hectare of land.

Finally, we address the potential concern that self/proxy discrepancies in child labor may be affected by Fairtrade cooperative certification. It is important to highlight that Fairtrade does not ban children’s engagement in the household farm but aims to regulate it by allowing children to work in family farms as long it is outside school hours and free of risky activities. We investigated self/proxy discrepancies of child labor reporting due to variations in proxy respondents’ knowledge of Fairtrade standards related to labor, environmental regulations, and Fairtrade pricing. Based on this information we computed a knowledge index using principal component analysis.<sup>18</sup> Unreported results show that the coefficient associate with the interaction between the survey treatment indicator and the knowledge index is negative, negligible, and not statistically significantly different from zero. These findings show that knowledge of Fairtrade standards does not have a positive and systematic differential effect on the self/proxy reporting of child labor statistics.

# **5. Costs and Statistical Power Implications**

Results presented in section 4 have implications for survey costs and statistical power. One way to address this trade-off is to ask how many household surveys would be needed to detect meaningful impacts for a hypothetical randomized intervention that targets child labor as the outcome of interest and relate that finding to survey cost considerations. To implement that exercise, we use self- and proxy-reported pooled tabulates of child labor for girls as the baseline 22
# **Appendix B.  Numerical implementation**

153. In this section we present the numerical implementation of the portfolio selection model presented in the previous section. The implementation consists of three stages:

- characterization of the dynamics of the variables of interest (asset returns, contributions to an individual account, minimum wage, etc.)

- estimation/calibration of the parameters involved

- calculating the optimal portfolio for the expected trajectory

## **a.** **<u>The dynamics of quantities of interest</u>**

154. The following specific dynamics were considered from the base of available assets:<sup>49</sup> where is the price of a bond index with duration _,_ , , for with as the _constant_ risk reward associated to the risk factor . In this case, corresponds to the interest rate risk factor, while _{ }_ represents independent risk factors linked to the remaining available assets. For their part, , for . The correlation between assets and , with , coming from .

155. Note that the dynamics considered imply risk reward, volatilities and constant correlations over time, a modeling alternative that is mainly due to the short data series available, which make non-linearity models less reliable in asset dynamics, like mean reversion, or changes of regimen.

## **b.** **<u>Estimation and calibration of parameters</u>**

156. In the calibration process diverse market indices were considered in order to allow a reduction in the dimensionality of the problem and greater stability in the solution.<sup>50</sup> At the domestic level, the asset indices COLCAP and IGBC were considered, as well as the fixed income index IDXTES drawn up by Reveiz and León (2008). Additionally, state bond indices were constructed from the interest rate curves

> **49** The dynamics in question correspond with the Cholesky decomposition of an asset base with correlated shocks, and