rafmacalaba/data-use-mentions-extended huggingface dataset:
Peninsula Economic Corridor; (5) the China‐Pakistan Economic Corridor; and (6) the Bangladesh‐China‐India‐Myanmar Economic Corridor.

> 3 There is no official list of countries in the Belt and Road Initiative. For this study, we focused on a list of 71 economies (Annex 1). Countries in the list should be interpreted as economies that are geographically located along the Belt and Road as proposed by China.

2
distribution by economic sector and occupations. Finally, we compare the characteristics of vulnerable (bottom 40 percent) and non-vulnerable (top 60 percent) workers within each employment type to better understand the profile of poorer workers. Due to sample size, we can only use the GMD to parametrically explore characteristics of unpaid, informal wage, and low-educated self-employed, with a much lighter touch on high-educated self-employed. We complement these findings with an analysis of the IES that allows us to understand more about the characteristics of low- and high-educated self-employed and informal employers.

# **5.1 Distribution of Demographic Characteristics by Employment Type**

Women’s informal sector participation is higher than their share of the workforce in urban SSA, and they dominate the non-wage informal sectors. Women are 47 percent of the entire workforce while they represent 51.5 percent of the informal sector (using the lower-bound definition) (Figure 7). Within the informal sector, women are disproportionally represented in two types of jobs: they are 58.1 percent of unpaid workers and 59.9 percent of LE-SE. By contrast, women are less than 40 percent of informal (35.2 percent) and formal (38.2 percent) wage employees. These aggregate trends are reflected across countries.<sup>48</sup> Married women especially cluster in unpaid and LE-SE. The conditional estimates confirm that women and dependent spouses are more likely to be unpaid or LE-SE than are men and household heads.<sup>49</sup> As most spouses in the sample are female, it is not surprising that female spouses follow this same pattern (Table 2).

The urban informal sector mainly employs prime-age workers. Those aged 25-55 years are 73.3 percent of the workforce and 66.9 percent of informal sector workers (Figure 7). LE-SE and informal wage employees – the two largest employment types – are mainly prime-aged adults. This age pattern appears in most countries. However, a closer look reveals more
between pre-reform trade and current trade, after controlling for size and distance, must be largely a result of historical linkages and not the result of unobservables such as comparative advantage and tastes.

# 3.1 The Data

We examine trade among 9 regions in Russia and 14 former republics of the Soviet Union before and after disintegration. The trade data are from the Russian State Statistical Committee and the World Bank and include bilateral trade flows among regions and republics, in U.S. dollars. Income figures are from the World Bank and are also in U.S. dollars. Distance is taken from the Russian Ministry of Transport tables as the shortest road distance in kilometers between regional and/or republican centers. Unweighted average ad-valorem tariff rates are published by the EBRD. Population figures are from the World Bank. (See the Appendix for a detailed description of the data and a map of the region.) There are two weaknesses in the data. First, because of central planning, the pre-reform trade values are not market values. Since we are comparing across regions and republics all of which are within the same country and subject to the same prices, they are nevertheless valuable estimates of relative trade between partners. The second problem is the presence of barter trade, which became quite common in the FSU in the reform period. Barter trade is recorded in the dataset, however the prices at which it is recorded are likely to be biased downwards in order to avoid taxes and tariffs. Again since we are comparing trade within the FSU, this is less of a problem because barter trade is likely to be as prevalent among regions as between regions and republics (see Appendix). Therefore, although the magnitudes of trade are likely to be distorted, there is no reason to think that relative trade among parties within the FSU is systematically biased. If we included non FSU countries in the study, these problems would distort relative trade as well.

6
|**Table 4: Heterogeneous Impact on For**<br>_Dependent variables:_|**malizatio**<br>(1)|**n by Basel**<br>(2)|**ine Char**<br>(3)<br>**For**|**acteristic**<br>(4)<br>**malized: G**|**s**<br>(5)<br>**UFE data**|(6)|(7)|(8)|
|---|---|---|---|---|---|---|---|---|
|||Operates<br>in||Doesn't<br>look like|<br>Index of<br>business|Does not<br>have|One visit<br>or fewer|Female<br>owner<br>|
||Female|Dantokpa||formal|size below|<br>secondary|<br>from tax|(sample|
|_Variable for heterogeneous analysis:_|owner|market|Trader|species|median|education|inspectors|restricted<sup>α</sup>)|
|_Impact in group [...] for heterogeneous variab_|_le=0_||||||||
|Group1|0.130***|0.102***|0.142***|0.119**|0.077**|0.150***|0.123**|0.175***|
||(0.035)|(0.026)|(0.033)|(0.054)|(0.032)|(
in 1997, countries did not join immediately. Among the BAFTA and CEFTA countries, the system could be considered mainly in place as of 2002.<sup>3</sup> Since this paper focuses on the impact of RoOs and RoCs on sourcing decision, we exploit the introduction of the PECS and investigate changes in imports among a group of the EU FTA’s peripheral partners, BAFTA and CEFTA (also called Spokes), between 1995 and 2002. To provide preliminary evidence of the effect of PECS on trade relationships, in Figure 1 we plot the evolution of imports to Spoke countries before and after the introduction of PECS.<sup>4</sup> The vertical axis measures changes in imports to each Spoke country from RoW (non-participating countries). Notice that we exclude imports from Spokes themselves and from the EU15. The horizontal axis measures changes in imports to each Spoke country from

> 2For further information see http://rtais.wto.org/UI/PublicMaintainRTAHome.aspx.

> 3The system was based on the EEA agreement (1994) between the EU, the EFTA countries, the CEEC (Central Eastern European Countries) and the Baltic States. Table 12 in Appendix A provides further details about the preferential agreements providing for diagonal cumulation of origin between the EU and the Spoke countries. The system was then widened to Slovenia and to industrial products originating in Turkey (1999). The system was also enlarged to the Faroe Islands in 2005 and later to the countries of the Mediterranean and Balkan region.

> 4Our analysis considers imports of BAFTA and CEFTA countries. Notice that Bulgaria, the Slovak Republic, and Slovenia are dropped from our analysis due to absence of tariff data in the period under consideration. Section (3.2) provides additional details about trade and tariff data used.

6
The descriptive statistics of the main LFS outcome variables are presented in Table A.1, Panel B. All statistics are presented as the means of the pre-COVID-19 period (i.e., all months in 2018 and 2019). On average, an HB individual worked for over 47 hours per week, earning approximately 5.8 million VND per month (approximately 250 USD). While average workload is mostly homogeneous across industries and firm sizes, average monthly income varies, between 5.3 million VND in the accommodation, food services, and entertainment sector (lowest) to over 7.2 million VND in transportation.

## **2.4 Face-to-Face Index**

The Face-to-Face Index measure (F2F) measures the importance and intensity of F2F interactions with other people for more than 900 occupations based on 4-digit International Standard of Industrial Classification (ISIC) codes (Avdiu and Nayyar, 2020). The measure utilizes the Occupational Information Network (O*Net) database for the United States, which provides scores on the importance of four work activities: (1) establishing and maintaining personal relationships; (2) assisting and caring for others; (3) performing for or working directly with the public; and (4) selling to or influencing others.<sup>17</sup> Table A.2 provides illustrative examples of F2F index scores and their closest 4-digit industry matches that appear in our data. Generally, manufacturing and wholesaling activities receive smaller F2F scores relative to accommodation or retails, reflecting the lower face-to-face intensity required to conduct business.

We calculate a commune-level baseline F2F measure by taking the average 2019 F2F index of all household businesses in a commune. Figure A.1 provides a visualization of the geographical distribution of the F2F measure. Visually, there is significant variation in the intensity distribution of the index, or equivalently, significant geographical variation in business lockdown exposure.<sup>18</sup>

# **3 Estimation Strategy**

To identify the impact of
242)|(0.274)|(0.205)|(0.223)|(0.383)|(0.309)|
|N|322|322|322|322|322|322|
|R-sq|0.517|0.541|0.492|0.508|0.367|0.458|
|adj. R-sq|0.481|0.508|0.466|0.482|0.336|0.431|
|Sector fixed effects|Y|Y|Y|Y|N|N|
|Province fixed effects|Y|Y|N|N|Y|Y|

Notes: Standard errors in parentheses. + p<.1 ++ p<.05 +++ p<.01. Source: Sri Lanka Census of Industry, 2004. WBES.

37
Policy Research Working Paper 9088

# **Abstract**

This study explores the potential and the limits of medium-resolution satellite data as a proxy for economic activity at small geographic units. Using a commune-level dataset from Vietnam, it compares the performance of commonly used nightlight data and higher resolution Landsat imagery which measures daytime light reflection. The analysis suggests that Landsat outperforms nighttime lights at predicting enterprise counts, employment, and expenditure in simple regression models. A parsimonious combination of the first two moments of the Landsat spectral bands can explain a reasonable share of the variation in economic activity in the cross-section. There is however poor prediction power of either satellite measure for changes over time.

This paper is a product of the Knowledge and Strategy Team, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at heilmann@usc.edu.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
high school graduate compares the expected payoff of two choices—going to college, or joining the labor force as a high school graduate. The enrollment decision is a discrete choice problem, where the payoff associated to each option is the sum of three components. The first component is the expected value of going to college, _V_<sup>_coll_</sup> ( _t_ = 1 _, h_ 0 = 0 _, θ, y_ ) or of entering the labor force as a high school graduate, _V_<sup>_hs_</sup> . The second component is a type-specific preference for college enrollment, _ξj_ = _ξ_<sup> ̃</sup> ( _θj, yj_ ), which captures type-related unobserved factors (i.e., parental education) that affect enrollment. We normalize the unobserved preference for joining the labor force as a high school graduate to zero for all types. The third component is an idiosyncratic choice-specific shock for each individual, _ε_<sup>_hs_</sup> and _ε_<sup>_coll_</sup> , corresponding to working as a high school graduate or enrolling in college, respectively. Thus, all individuals face the same _V_<sup>_hs_</sup> and individuals of a given type face the same _V_<sup>_coll_</sup> and _ξj_ , yet individuals within and across types differ in their idiosyncratic shocks. We assume that

> 9This is in keeping with the Colombian context, where tuition is fixed regardless of the number of classes taken.

> 10We do not model student’s decision to work during college because our administrative data does not record this information. Further, data from Colombia’s National Survey of Time Use ( _ENUT_ ) reveals that high-income college students are more likely to work during college than their lower-income counterparts, suggesting that the primary motivation to work is not necessarily to pay for college (details available upon request). For a model of student workers, see Garriga and Keightley (
TFiS and attempts to provide a policy-relevant definition of the concept. It does so by discussing TFiS theoretically and by taking the concept of TFiS to trade data in order to analyze how the various aspects of TFiS form an important costs factor for trading services. Only in this way can a more focused discussion take place on developing the potentially useful idea of facilitating trade in services within the global trading community and to determine on which measures to focus when practically applying a policy-relevant agenda. The paper is organized as follows. The next session sets out a discussion on the concept of TFiS by setting out what it actually contains. Section 3 provides an empirical analysis of the potential determinants of TFiS as per the discussion in the preceding section, while Section 4 places the outcomes in broader context. The last section concludes.

# **2. Conceptualizing TFiS: What is it?**<sup>**2**</sup>

Broadly, measures that fall within the area of trade facilitation in services relate to notions such as “ **transparency** ”, “ **regulatory practices** ”, “ **regulatory cooperation** ”, “ **regulatory coherence** ”, and “ **good**

> 2 A first attempt to conceptualize TFiS and to determine what measures fall under the concept of TFiS, with members of the epistemic community on trade in services, was made during a conference in March 2017. This conference was held by the World Bank in collaboration with the Government of India. This section draws on some of background materials and discussions presented during this event.

3
.3|
|Income total, %|0.0|-0.1|-0.2|-0.4|
|Absolute poverty rate of the formalized, p.p.|0.0|5.1|4.1|3.2|
|<br>Absolute poverty rate, p.p.|0.0|0.1|0.2|0.2|
|Gini index, p.p.|0.0|0.0|0.0|0.1|
|Total budget balance, %ofGDP|0.0|0.2|0.4|1.0|

Source: Authors’ calculations using RUSMOD for 2017 policy year and 2016 RLMS-HSE data.

Formalization is costly for workers if the economic incidence of direct taxes falls on them. Figure 8 illustrates the outcomes of reform 1 for different types of socio-demographic groupings. In case of random formalization of 50 percent of informal workers, the transition to formality is costly for the workers in most cases. There are no losses for workers under scenario A, because SIC is assumed to have no incidence of workers, so changes in it do not affect their take-home pay. In scenario B, where workers are responsible for paying all additional SIC and PIT due to formalization, their new gross and net earnings decrease substantially. The additional social benefits cannot compensate the higher taxes, which is why the net effect is negative and especially so in the middle of the income distribution. Scenario C represents the intermediate case, where workers bear a part of tax burden (PIT, but not SIC), which yields a lower negative effect. The negative effects of scenario B are similar 22
Another major issue is the fact that countries are more likely to adopt and encourage effective regulatory agencies the more that they have a positive attitude to the separation of powers, the commercialization of economic activities and to private investment and market economics in general. Hence, one should not assume that independent regulators are exogenous. In all areas of the world, countries will select whether they want to go down the route of commercialisation and independent regulation. Early adopters in particular are likely to be heavily self-selecting.

This endogeneity problem is well-known in the ICB effectiveness literature<sup>38</sup> . It has surfaced in the regulatory effectiveness literature. Two recent examples are in Gual and Trillas (2002) and Guasch, Laffont and Straub op cit<sup>39</sup> .

Gual and Trillas discuss the impact of 37 telecom regulators and they instrument the degree of independence of the regulator which is measured by an index, following the ICB effectiveness literature. The degree of regulatory independence is estimated

> 37 See Fink, Matthoo & Rathindran op cit, Appendix 4, pp 32-3 for a good discussion of some of these issues in the context of telecom regulation.

> 38 See, for instance, the survey of ICB empirical studies in Berger, de Haan and Eijffinger (2000).  We will discuss this and related issues in Section 2.5 below.

> 39 See also Gutierrez (2003) which has a detailed investigation of endogeneity issues in telecom regulation.  He finds little or no change in  his estimates from allowing for endogeneity.

29
9 In the IFLS (2007) survey data, approximately 35 percent of all labor market participants work in the formal sector. These wage-and-salary employees are potentially covered by the severance regulations. Of those individuals in covered employment who are employed by a firm falling under the auspices of the regulations, not all meet the requirements. Furthermore, of those who do meet the necessary coverage requirements, not all are eligible to receive severance pay.<sup>9</sup> Of government and private sector employees working in covered employment, only 14.8 percent state that they are entitled to severance pay as one of the set of benefits offered by their employer. Based on this low percentage, it seems that many formal sector employees lack a clear understanding of severance pay eligibility.

In both surveys, women in covered employment are less likely than men to be eligible for severance pay in the event of a job separation.<sup>10</sup> As Table 2 shows, eligibility for severance pay increases strongly with age, but there are no noticeable differences in eligibility by level of education. While there is variation in eligibility for severance pay across industries, there is no apparent pattern. There is, however, a strong systematic relationship between eligibility for severance pay and tenure: eligibility increases strongly with tenure. For firms of different sizes, the eligibility proportion steadily increases with firm size.

There are two noticeable differences, however, between the surveys. The first difference is the likelihood of eligibility for severance across firm ownership status. In the IFLS (2007), wage and salary workers employed by state-owned enterprises are more likely to be eligible for severance than employees working in a government agency. On the other hand, the likelihood of eligibility for severance is similar across firm-ownership status in Sakernas (2008). Second, neither survey shows a consistently positive association between eligibility and the level of wages across the full range of wage rates.

3.3 _Compliance with current severance pay regulations_

> 9 Question TK25A3 of
. A city consists of "contiguous grid cells with a density of at least 1,500 inhabitants per km<sup>2</sup> of permanent land or with a built-up surface share on permanent land greater than 0.5 and has at least 50,000 inhabitants in the cluster with smoothed boundaries" (Florczyk et al., 2019).

The GHS-BUILT is derived from satellite imagery to measure the built-up area. The data set is constructed of a series of built-up layers across four different periods (i.e., 1975, 1990, 2000, and 2014). Each year of the data set is based on different collections of Landsat satellite imagery. A total of 33,202 scenes were captured to produce the multi-temporal layers of built-up (Florczyk et al. 2019). The GHS-BUILT uses a 30m spatial resolution, which is higher resolution compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Type (MCD12Q1) and Global Land Cover (Globcover) that are available at 500m and 300m, respectively. Coarser resolution imagery may lead to the omission of small built-up areas (as in low income countries) and poor accuracy at the urban fringe.

The advantages of this data set are twofold. First, it uses a common definition of urban center across the world which is crucial for global level comparison. Although there has been a wide discussion in the literature on how to properly define cities, no definite consensus has been reached. Some studies have used a pre-defined pixel grid as a cookie-cutter and applied that to define each city (Mahtta et al., 2019) while others have used the cities' administrative boundaries or commuting zones (Roberts et al. 2017). Second, it defines the urban extent that corresponds to the most recent available data (2015). Having

> 11 Council on Tall Buildings and the Urban Habitat (CTBUH).

3
# _5.2 Economic Outcome Descriptives_

Three outcome variables are used to study the economic impact of the INDH on households: income, consumption, and the total value of assets (wealth) of households. These are also presented in log terms. The outcomes are shown by round and INDH in Table 3. It is important to note that the areas treated with the INDH intervention had a higher poverty rate according to the poverty map estimates. Consequently, it is likely that in the absence of any intervention, the treatment areas would be worse off and so there may be offsetting effects. The regressions will control for the poverty rate and thus this should be addressed in other analyses. For almost all the economic outcome variables used in this study for the 2008 round, no statistically significant difference has been recorded. This may be due to the offsetting effect of the program against a higher poverty rate in treatment areas. Beginning with the 2011 wave, significant differences are apparent with better economic outcomes in treatment communes. When the outcomes achieved by 2013 are compared, the differences between communes targeted for INDH Phase I and those not targeted are significant, except for mean per capita expenditure. It is also notable that there are mixed trends over time across the different outcome variables.

11