rafmacalaba/data-use-mentions-extended huggingface dataset:
The article employs a unique data source from Jordan, the 2010 Jordan Labor Market Panel Survey (JLMPS 2010), which includes information on parents’ schooling for every adult in the sample, along with the 2010 School Census produced by the Jordanian Ministry of Education (Hashemite Kingdom of Jordan, 2010). The school census provides the subdistrict, type, and date of establishment of every school in Jordan, allowing us to measure the local supply of each type of schools in each subdistrict in every year (under the presumption that there were no significant school closures or changes in type over time, which is likely the case). The exposure of an individual in the JLMPS 2010 sample to the supply of public schooling is then determined by the number of sex-appropriate basic (or secondary) public schools (per 1,000 individuals) that were available to them in their subdistrict of birth at the time they were of age to enroll in that school level (six years of age for basic and 15 years for secondary). The richness of the data set makes it the first in the Middle East to allow such a study.

The empirical analysis employs a standard difference-in-differences approach to disentangle the impact of the expansion of local public schooling on the correlation between a child’s educational attainment and that of his/her parents. In particular, the analysis exploits the variation in the supply of public schools across cohorts and subdistricts of birth and allows the effect of this variable to vary by parents’ schooling, where both subdistrict-of-birth and year-ofbirth fixed effects are controlled for. The empirical strategy is similar to that used in Duflo (2001), who looked at the impact of increased school supply on educational attainment. Parents’ schooling is added here as an additional regressor along with its interaction with the local supply 4
Figure 3: Means 50 and 95 Percent Confidence Intervals of the Sample Distributions of the Labor Payment Changes by Sector from Armenian-EUFTA—30,000 simulations.

<!-- Start of picture text --> 25<br> 20<br> 15<br> 10<br> 5<br> 0<br>-5<br>fence e ipelinesp retail trade and repair rying r a<br> d d u<br>n i n m a n<br>Other social and personal services Electricity, gas and water supply ucatio d E Manufacturing lic ad b PuTransport via railwaysnsport viTra olesale a h W Telecommunications Health and social work Cnstructiono ing and qMi n nkingBaInurance s Air transport<br><!-- End of picture text --> Note: The boxes are limited vertically by the 25% and 75% quartiles. The bars in the box are the means. The vertical lines extend to the 2.5% and 97.5% percentiles.

67
the countries (23 out of 59) with harmonized HFPS data have survey rounds conducted within the Round 1 and Round 2 windows.<sup>28</sup> To focus on the patterns associated with economic recovery, we restrict our attention to 20 countries where policy stringency declined between Round 1 and Round 2.<sup>29</sup> For the average country in our sample, policy restrictiveness — measured by the Oxford Stringency index — fell from 77 to 68 between rounds 1 and 2, where higher values indicate greater stringency.<sup>30</sup> Our findings are thus reflective of countries covered by HFPS where policies became more favorable toward economic activity between May and September 2020, and do not reflect what happened during subsequent months that included a second wave of the pandemic in some countries.

Since we are focusing on changes in three outcome variables that were the focus of the analysis of the initial impacts of COVID-19 – income loss, employment, and food security – over time, and disaggregating by several sociodemographic characteristics, the sample of countries varies because of differences in coverage of variables across surveys and quality of data. Our total sample of countries includes two countries in the World Bank’s Europe and Central Asia region, two in East Asia and Pacific, eight in Latin America and the Caribbean, and eight in Sub-Saharan Africa. Of these, seven are low-income countries, seven are lowermiddle-income, and six are either upper-middle-income or high-income countries. Eight countries fall under the World Bank’s IBRD lending classification and 12 under the IDA category (including those

> 27 Note that LICs account for most of the lower end of the global income distribution.

> 28 Survey waves were fielded at different times in each country. Therefore, these rounds do not necessarily correspond to waves 1 and 2 for all countries but can also correspond to waves 1 and 3.

> 29 Countries are Argentina Burkina Faso, Colombia, Costa Rica, Dominican Republic, Ethiopia, Guatemala, Honduras, Kenya,
<!-- Start of picture text --> Ghana Algeria<br>0 2 4 6 8 10 0 2 4 6 8 10<br>Tax Morale Tax Morale<br>Morocco Nigeria<br>0 2 4 6 8 10 0 2 4 6 8 10<br>Tax Morale Tax Morale<br>.8<br>.4<br>.6 .3<br>.4 .2<br>Density Density<br>.2 .1<br>0 0<br>.8 .6<br>.6<br>.4<br>.4<br>Density Density<br>.2<br>.2<br>0 0<br><!-- End of picture text --> Figure 1: Tax morale by country <!-- Start of picture text --> Morocco<br>Ghana<br>Morocco<br>Ghana<br>Nigeria<br>Nigeria<br>Algeria Algeria<br>2.3 2.4 2.5 2.6 2.7 2.5 2.6 2.7 2.8 2.9 3<br>Trust in public institutions Trust in the neigbourhood<br>(a) trust in public institutions (b) Trust in the neighbourhood<br>10 9.5<br>9<br>9<br>8.5<br>Tax Morale Tax Morale 8<br>8<br>7.5<br>7 7<br><!-- End of picture text --> Figure 2: Tax morale and trust 16
# **II. The Customs Administration in Madagascar: Context**

Customs plays a very important role in revenue collection in Madagascar. The size of the customs administration is limited in terms of the number of customs officers (in comparison to other countries with similar characteristics). Customs controls are still largely ineffective.

In 2014, imports accounted for 31 percent of GDP (US$3.29 billion).<sup>8</sup> Accounting for 22 percent of imports, the European Union is the biggest supplier of non-oil goods (cf. Table 11, appendix A). Due to large tax rates, taxes on petroleum products are the main source of revenues collected by customs (26 percent).

# **<u>A. The Importance of Revenues Collected by Customs</u>**

As for many other African countries, revenues collected at the border from trade remain significant in Madagascar (see _i.e.,_ Keen (2003), Zake (2011), Montagnat-Rentier and Parent (2012)). Customs collected 45 percent of total tax revenues in 2014 (see Figure 1). Due to the decline in tariff protection and the rise of indirect taxation, value-added tax now represents 72 percent of revenues collected by customs (see Figure 2). As duties on petroleum products account for 30 percent of revenues collected at the border, revenues from customs are consequently heavily dependent on oil prices.

A comparison of the data on revenue collected by Madagascar customs with that of other African countries (especially low-income countries), yields the following results (see Table 1):

- There is potential to improve the level of effective taxation.

- The customs administration of Madagascar is plagued by a lack of human resources, with around 15 percent lower resources than the administrations of countries in a similar category. This explains why the level of revenues collected by each customs officer is higher than the median.

**Table 1: International Comparison with Madagascar Customs**

|
have the data on non-performing loans, or the data on reclassified receivables), while we do have enough data to shed some light on the reasons for decline in trade credit after the crisis.

# **IV.2. Heterogeneous firm responses**

In this section, we study firms ́ trade credit policy as a function of their relative financial health. The supply-driven reason for decline in trade credit provision after the crisis would be caused by the unwillingness (or inability) of suppliers to provide credit to their customers. In this case, we would expect that those firms in more difficult financial position would be the most likely to cut the supply of credit to their customers. The supply-driven reason for reduction in trade credit provided to firms’ customers would imply that such a reduction is relatively higher for firms with weaker pre-crisis financial conditions. This argument forms our main identification strategy.

# **IV.2.1. Short-term debt.**

As suggested earlier, firms that enter the crisis with a high proportion of shortterm debt are likely to be particularly disadvantaged by the credit crunch, because of the higher costs of short-term debt and difficulties in rolling it over. Even though the contemporaneous short-term debt to assets ratio is likely to be endogenous, we initially run the regressions using this figure, because it allows us to observe the effect of shortterm debt in the pre-crisis period. We estimate model (2) and present results in Table 3, Panel A.

The coefficient on _Stdtoa_ shows the effect of short-term debt on firms ́ pre-crisis trade credit provision: We find that firms with higher percent of short-term debt provide more credit to their customers during non-crisis times. To get a sense on the order of 15
# **The Exceptional Persistence of India’s Unorganized Sector**

Ejaz Ghani, William R. Kerr and Stephen D. O’Connell

**Keywords:** Informal, structural transformation, transition, entrepreneurship, employment, agglomeration, urbanization, development, poverty, India.

**JEL Classification:** J16, L10, L26, L60, L80, M13, O10, R00, R10, R12

**Sector Board:** Economic Policy (EPOL)

_Author institutions and contact details:_ <u>Ghani: World Bank, Eghani@worldbank.org; Kerr: Harvard University, Bank of Finland, and NBER, wkerr@hbs.edu; O’Connell: World Bank</u> and CUNY Graduate Center, <u>soconnell@gc.cuny.edu.</u> _Acknowledgments_ : A first draft of this paper was circulated in November 2011. We thank Swaminathan Aiyar, Ahmad Ahsan, Mehtabul Azam, Henry K Bagazonzy, Kaushik Basu, Steven Brakman, Louise Fox, Arti Grover, Himanshu, Lakshmi Iyer, Henry Jewell, Emmanuel Jimenez, Ravi Kanbur, Vinish Kathuria, Tarun Khanna, Homi Kharas, Luke Simon Jordan, Kalpana Kocchar, Amitabh Kundu, Peter Lanjouw, Pratap Bhanu Mehta, Pradeep Mitra, Rakesh Mohan, Truman Packard, Onno Ruhl, Gunjan Sharma, Arvind Virmani, and Hyoung Gun Wang for helpful comments on this work. We are responsible for any errors. We thank the 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. Funding for this project was provided by World Bank and Multi-Donor Trade Trust Fund. The views expressed here are those of the authors and not of any institution they may be associated with. The research in this paper was conducted while Kerr was a Special Sworn Status researcher of the US Census Bureau at the Boston Census Research Data Center (BRDC).
introduced such innovations before. Firms that had a website in 2019 were 55% more likely to start or increase business activity online than firms that did not have a website.

Fig. 11. Firms’ responses during the COVID-19 crisis by firm characteristics <!-- Start of picture text --> Start/increase online business activity<br>40%<br>30%<br>20%<br>10%<br>0%<br>GVC Innovator High productivity Foreign licensed Website Well managed<br>technology<br>no yes<br>Start/increase remote work<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br>GVC Innovator High productivity Foreign licensed Website Well managed<br>technology<br>no yes<br><!-- End of picture text --> _Source:_ the authors’ calculations based on COVID-19 Follow-up Enterprise Surveys.

More productive firms were also adapting better during the pandemic. They were less likely to close down both permanently and temporarily; they also suffered smaller sales and employment losses. Furthermore, more productive firms were more likely to start or increase business online and more likely to start or increase remote work. For example, high productivity firms (top 10 percentile of the productivity distribution) were 55% more likely to increase online business activity and were more than three times are likely to introduce remote work compared to low productivity firms in the bottom decile.

Firms with links abroad – through foreign ownership, trade or use of foreign technology – were on average more likely to adapt, in particular they were more likely to introduce remote working arrangements.<sup>15</sup> Firms that were majority foreign owned were 11% more likely to start or increase remote work during the pandemic than domestic firms. Trading has a similar effect to foreign ownership: global value chain participants (firms who
year is divided by the June CPI in each province for observations in semester 1 and the December CPI in each province for observations in semester 2.<sup>14</sup> One notable aspect of the province-specific CPIs is that they are all equal to 100 in the base year (2012=100). This allows tracking of differences in the evolution of the cost of living across provinces over time but does not allow for identification of the difference in the cost of living across provinces in the base year.<sup>15</sup> The poverty line (z) used in this paper is determined using the level of PCE in 2003 corresponding to the official poverty rate of 24.9% in 2003.<sup>16</sup>

**Shock Measure** :  A wind model based on Boose et al. (2004) for the Philippines is employed to estimate local wind speeds at any particular locality where a tropical typhoon directly passes over or nearby.<sup>17</sup>

An additional distinguishing feature of this study is the fact that it uses the Philippines Standard Geographic Codes (PSGC) of the barangays (smallest administrative units) or residence of the households sampled by the FIES. Access to the PSGC of barangays, allows the wind model to be more granular in the sense that estimates of the wind speed associated with any given typhoon can be derived for the geographic location of each barangay. This provides a much better estimate of the wind speed experienced by any given household during a typhoon and thus the basis for a more realistic assessment of the impact of wind speed on household consumption. Anttila-Hughes and Hsiang (2013), did not have access to the barangay-level codes, and thus had to estimate windspeeds at the province level. This, in turn, implies that all households in each of the 81 provinces were assigned the same wind speed irrespective of a household’s distance from the typhoon’s path.

Figure 2 below presents the total number
examined gender wage gaps in Vietnam between 1993 and 2009, Ganguli and Terrell (2005) used data from Ukraine to examine the earnings differentials between men and women during the 1986 to 2003 period, and Badel and Peña (2010) used survey data from 2006 to estimate gender wage differences in Colombia. All of these studies find that women’s earnings are significantly lower than those of men, men earning up to 30 percent more than women in these countries. The authors note that education and experience account for a small proportion of the estimated wage gap, and that the bulk of the gap is attributed to differential returns to education and skills for men and women. Three of these studies use quantile regression-based decomposition methods, allowing researchers to examine wage differentials at different points of the wage distribution. In the case of Colombia, Badel and Peña (2010) found that women at the top and bottom of the wage distribution are those primarily affected by differences in returns to endowments or skills. For Ukraine, the gaps are widest at the top end of the wage distribution, while the opposite is true in Vietnam, where the wage gaps decrease as one moves along the distribution from bottom to top.

A limited set of studies on gender wage discrimination examines the contribution of cognitive and noncognitive skills in explaining the gender wage gap (Fortin, 2008; Mueller and Plug, 2006; Nordman, Sarr, and Sharma, 2014; Nyhus and Pons, 2012; Sakellariou, 2012; and Semykina and Linz, 2007). Most of these studies are based on data from OECD countries. To our knowledge, Nordman, Sarr, and Sharma (2014) present the only available evidence for developing countries. They used matched employer-employee data from Bangladesh to examine discrimination in male-female wages, and found that, when controlling for educational attainment, the mean wage gap is about 8 percent. The mean wage gap reduces marginally when cognitive and noncognitive skills are added to the model. Examining the wage gaps at different points of the wage distribution
# **Non-technical Summary**

This paper studies the link between export product variety and country productivity, based on data of 34 developed and developing countries, from 1982 to 1997. Export product variety is measured by the share of US imports on the set of goods exported by each sampled country relative to the world. It is a theoretically sound index which is consistent with within-country GDP maximization as well as cross-country comparison. Country productivity is constructed based on relative endowments and product variety. Increases in output product variety improve country productivity as the new mix of output may better utilize resources of the economy and improve allocative efficiency. Such effects depend on the elasticity of substitution in production between the different varieties. The more different the varieties are in terms of production, the more efficient it is to use the endowments of the economy when a new variety is available, which leads to productivity gains. In addition, as suggested in the literature, export product variety depends on trade costs, such as tariffs, distance and transport costs. Such trade cost variables are used as instruments to help us identify the effects of export variety on country productivity. Empirical evidence supports our hypothesis. Overall, while export variety accounts for only 2% of cross-country productivity differences, it explains 13% of within-country productivity growth. A 10% increase in the export variety of all industries leads to a 1.3% increase in country productivity, while a 10 percentage point increase in tariffs facing an exporting country leads to a 2% fall in country productivity.
birthday or household enumeration method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

# _Data Preparation_

Data weighting is used to ensure a nationally representative sample for each economy. Final weights consist of the base sampling weight, which corrects for the unequal probability of selection based on household size, and the poststratification weight, which corrects for sampling and nonresponse error. Poststratification weights use economy‐level population statistics on gender and age and, where reliable data are available, education or socioeconomic status.

Additional information about the Global Findex data, including the complete database, can be found at <u>http://www.worldbank.org/globalfindex.</u> Additional information about the methodology used in the Gallup World Poll can be found at <u>http://www.gallup.com/178667/gallup‐world‐poll‐work.aspx.</u> 32
multilateral development agencies to make a difference. It is hopeful that this opportunity will not be lost, provided that investment climate and governance continue to improve, and capacity for regulation and supervision continue to enhance.

# **7. Conclusions**

The purpose of this paper is to investigate the relationship between the efficiency of domestic banks and foreign bank entry, and also to study possible role of the order of financial liberalization in this process. We focus on the banking sector of 30 countries for the period of 1995-2002. The BANKSCOPE database is our main data source.

The first issue that we investigate is how foreign bank openness differs from one country to another and whether foreign bank entry is related to the level of economic development. We also try to examine whether changes in the foreign bank share are significant determinant of domestic banks’ performance indicators such as the net interest margin, non-interest income, profits, overhead costs, and loan loss reserves. Finally, we check how these results change when countries are grouped according to the sequence of their financial liberalization. Throughout our analyses, we control for other bank variables and macroeconomic indicators.

The descriptive statistics indicate that there is no specific relationship between the level of economic development and openness to foreign banks. When the foreign bank share is investigated at the country level, it can be seen that this share changes a lot among countries. When countries are grouped according to their sequence of financial liberalization such as domestic financial markets first, stock market first, or capital account first, it is observed that domestic banks’ net interest margin, non-interest income, overhead costs, and loan loss reserve get the lowest values in the countries liberalized their stock market first. This indicates that competition is well-established in these countries. The highest values of non-interest income, overhead costs, and loan loss reserves are in the Asian and Latin American countries which liberalized their domestic financial markets first. Despite differences in the performance indicators among the groups, the foreign bank share does not change a lot. But
=45.

- Eswaran, M. and A. Kotwal, 1990, “Implications of Credit Constraints for Risk Behaviour in Less Developed Economies”, _Oxford Economic Papers,_ 42‐2: pp. 473‐82.

GLOBE Task Team (Hastings, David A., Paula K. Dunbar, Gerald M. Elphingstone, Mark Bootz, Hiroshi Murakami, Hiroshi Maruyama, Hiroshi Masaharu, Peter Holland, John Payne, Nevin A. Bryant, Thomas L. Logan, J.‐P. Muller, Gunter Schreier, and John S. MacDonald), eds., 1999. _The Global Land One‐kilometer Base Elevation (GLOBE) Digital Elevation Model_ , Version 1.0. National Oceanic and Atmospheric Administration, National Geophysical Data Center, 325 Broadway, Boulder, Colorado 80303, U.S.A. Available from http://www.ngdc.noaa.gov/mgg/topo/globe.html.

- Hallegate, Stephane, and Patrice, Dumas, 2009, Can Natural Disasters Have Positive Consequences? Investigating the Role of Embodied Technical Change, _Ecological Economics_ , 68: 777‐786.

- Hasegawa, M., 2010, Risk Coping Measures against Different Types of Shocks: Empirical Evidence from Vietnam Household Living Standard Survey, _OSIPP Discussion Paper_ 10E006, Osaka School of International Public Policy, Osaka University.

- Helders, Stefan.  2005. _World Gazetteer Database_ .  Downloaded June 7, 2007 from http://world‐ gazetteer.com/.

- Jayachandran, S., 2006, Selling Labor Low: Wage Responses to Productivity Shocks in Developing Countries, _Journal of Political Economy_ , 114‐3: 538‐575.

- Just, Richard E, and Rulon D, Pope, 1979, Production Function Estimation and Related Risk Considerations, _American Journal of Agricultural Economics_ 61‐May:276‐284.
Percent|
|2010 Cohort (n=1372)|||||
|Assigned to Treatment (n=1040)|671|64.52%|369|35.48%|
|Assigned to Control (n=332)|86|25.90%|246|74.10%|
|2011 Cohort (n=1415)|||||
|Assigned to Treatment (n=1110)|826|74.41%|284|25.59%|
|Assigned to Control (n=305)|110|36.07%|195|63.93%|
|2012 Cohort (n=1306)|||||
|Assigned to Treatment (n=889)|597|67.15%|292|32.85%|
|Assigned to Control (n=417)|127|30.46%|290|69.54%|

Notes: There are four individuals from the 2011 cohort and five individuals from 2010 whose status in the EF database is unknown. For these individuals, we rely on the respondent’s self‐report of whether they took an EF training in the past year for the ATT results. The table only includes those individuals who were surveyed for the first follow‐up.

29