rafmacalaba/data-use-mentions-extended huggingface dataset:
|beverages,<br>tobacco,<br>wood, paper<br>(HS 11, 15-24,<br>44-48)|||||||||
|---|---|---|---|---|---|---|---|---|
|Chemicals,|42172|0.58|394995|2.27|20.32|11.49|0.08|0.20|
|plastics,<br>rubber<br>(HS 28-36,<br>38-40)|||||||||
|Machinery,<br>electronics,<br>transportation<br>equipment<br>(HS 84-89)|61309|0.85|227942|1.31|11.37|14.10|0.04|0.06|

Source: Authors’ calculations based on data from Comtrade.

Top Pakistan’s exports products are the ones in which the country has a revealed comparative advantage (RCA)<sup>6</sup> , like textiles, apparel, leather, footwear, agriculture products, meat and dairy and seafood. For rising products such as mineral, metals and machineries and electrics, the country has no comparative advantage in relation to the rest of the world. The export growth of these products is reflected though in increasing values of RCA. In section 3.3 there is a further analysis relating sectors and revealed comparative advantage.

# 2.2 **Diversification**

Diversifying exports across markets and products is important because it reduces the vulnerability of the country’s export portfolio to partner-specific shocks and to extreme volatility in export prices. The recent crisis has highlighted the critical importance of diversification in reducing the risks of volatility in global demand. Evidence suggests it is not natural resource dependence per se that increases risk, but rather the concentration of
1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015<br><!-- End of picture text --> Source: Constructed from UNHCR population data <u>(http://popstats.unhcr.org/en/time_series). Note:</u> 2015 data are mid‐year and lower than end of year data.

> 5 http://www.unhcr.org/en‐us/figures‐at‐a‐glance.html.

3
14 to “benefits” appears to have dwindled over time, possibly because by 2017 households were denied the chance to avail themselves of both HUS and “benefits,” and were required to choose between them.

Table 3 compares the HUS amounts documented in the HBS for various types of households with official administrative data, suggesting that the figures in the HBS are generally in line with the official statistics. Table 4 displays the shares of the sample (or of specific segments of the sample) that receive the HUS—for natural gas and/or for other utilities—in each year. Table 4 broadly confirms the evidence in table 2, but also shows that users of natural gas are more likely to receive the HUS than the other households, and that up of two-thirds of the households that use natural gas for space heating report receiving the HUS.

Were the households that received the HUS poor? Table 5 shows that after 2014 HUS recipients were by no means limited to the poorest people, although the shares of HUS recipients are higher in the first three quintiles of the distribution of income. In 2017 and 2018, one-third of the households in the top income quintile received the HUS. Table 6 presents another striking piece of information. While in 2014 almost half of the HUS disbursements went to the households in the first quintile of the distribution of income, in 2016 and 2017 the HUS was handed out almost evenly to all income quintiles. This tendency was somewhat moderated in 2018 and 2019, when the wealthiest 20% of the households received only about 12% of HUS.

# _3.D. Natural Gas Usage_

In the remainder of this paper, attention is restricted to those households in the HBS that use natural gas (about three-quarters of the full HBS sample), and more specifically to those that use piped natural gas for space heating (48% of the full HBS sample). Fully 80% of the latter use
the population do not want title in some 11% of villages, a share is that more than two-thirds (68%) in the West and almost that level (65%) in the South. Use of sampled households’ GPS coordinates allows us to map this. Figure 1 shows the location of villages where more than a given share of the sample population wants to acquire title (panel A) or with willingness to pay above a certain level (panel B). While it is not surprising to find most demand and willingness to pay concentrated along the line of rail, there is considerable variation over space.

# **3.3 Tenure characteristics at the parcel level**

Parcel level data allow to distinguish between residential and agricultural parcels and statutory vs. customary tenure systems as illustrated in table 4. Estimates on population mean using the 3,787 residential parcels in our sample (panel A) suggest that, 43% can be transferred by bequest and 38% by sale, a share that is much higher for parcels located on state (with 65% able to bequeath and 68% to sell) than on customary land (34% and 25% with bequest and sale rights).<sup>20</sup> With rights to 73% of residential parcels documented in some way (41% and 22% with complete or partial title and 11% with a form of informal document), documentation is concentrated on state land; in fact, only 2.2% of residential parcels on customary land have an incomplete title and about 13% have an informal document. Owners want to acquire title for about half (46%) of

> 19 To implement this, a contingent valuation approach was adopted with starting values of ZMK 50, ZMK 500, and ZMK 5,000 and subsequent questions narrowing amounts (e.g., for the ZMK 50 starting value, the sequence is ZMK 3,000, ZMK 100, ZMK 2,500, ZMK 200,
)) as well as that made for similar employer-employee databases for other countries (e.g., Fr ́ıas et al. (2022) for Mexico).

> 8The firm’s exporting status is based on matching RAIS to the customs data as described below.

9Our selection of a random sample of workers is done for computational reasons and it follows the approach of Dix-Carneiro & Kovak (2019) for RAIS data and of Autor et al. (2014) for US social security data.

7
between year t and year t+1. (5) _ENTREj_ represents the interaction _Entrejt_ x _Postt_ where _Entrejt_ : (1= Student _s_ attends a school _j_ in year _t_ that was treated) and _Postt_ : (1 = year of the intervention; 0 = year before the intervention). (6) _Interaction j_ in column (i) is given by the variable _Risk sjt_ (Probability of dropout for student _s_ that attends school _j_ in year _t_ estimated in the Early Warning System); in column (ii) by _Large school sjt_ : (1=Large school: size in 2017 > median), and in column (iii) by _Man sjt_ : (1=Man). (7) All specifications include the corresponding _Postt_ , _Entrejt_ and _Interaction j_ dummies. (8) Student characteristics used as control: age dummies, gender and risk (probability of dropout estimated in the Early Warning System).

# - <u>Scalability and cost benefit analysis</u>

As the size of the RCT suggests, the program was designed to be implemented at scale by relying on existing MINEDUC staff, including trainers, teachers, and school principals, and at a very low cost per student benefited by the program (roughly USD 2 dollars). The training and overall implementation of the program was chiefly in the hands of MINEDUC, with minor support from the World Bank. Expanding ENTRE to additional grades would reduce the costs per student by approximately 76%, given that the training and materials for principals (which represent roughly half of the budget for an average school) are a “fixed cost” for the school, there are many multiplegrade schools and the number of teachers per student is substantially larger in the sixth grade than in the first five years of primary education.

The cost-benefit analysis was conducted using the J-PAL tool and following its cost guidelines.<sup>17</sup> As previously mentioned, the intervention is low-cost, with a total cost per student of USD
health (whether an individual was ill in the last month, and for how many days in the last month they were unable to perform their normal daily activities due to illness), reported ability to perform ordinary activities (doing vigorous activity, walking uphill, bending over or stooping, walking more than 1 km, walking more than 100 meters, or using a bath or toilet), anthropometrics (height, weight, middle upper-arm circumference, and z-scores for height-for-age, weight-for-age, weight-for-height, and body mass index-for-age), and—for those ill in the last month—the location where medical care was sought (no treatment sought, public dispensary, public hospital, public health center, private pharmacy, traditional healer, private dispensary/ hospital/ clinic, or mission dispensary/ hospital).<sup>9</sup> Among those seeking treatment, we further gathered data on health care financing methods (free treatment, loans, cash or assets, or health insurance). We also collected household-level data on expenditure on formal insurance<sup>10</sup> and—at endline—whether the household participates in the CHF.

# **4 Methods and Empirical Strategy**

## **4.1 Empirical specification**

We carried out follow-up surveys in 2011 and in 2012 to capture both short-term (1.5 years) and medium-term (2.5 years) impacts of the program. Given random assignment to treatment, we recover causal intent-to-treat estimates from the following empirical specification: where _i_ indexes individuals and _t_ indexes the survey round. _hit_ is a health-related outcome, _αi_ are individual fixed effects, _Ti_ =1 in a village assigned to treatment and zero otherwise, 2011 _t_ =1 at the time of the midline survey (July–September 2011) and zero otherwise, and

> 9Data on protective footwear were only collected for children aged 0–18, data on anthropometrics for children aged 0–5, and data on ordinary activities for those aged 60 and over
In 2020, the world was affected by the COVID-19 pandemic. To stop the spread of the virus in France, the government imposed a first containment from mid-March to mid-May. In addition, in mid-May 2020, the French banks increased the limit for contactless payment in order to reduce physical contact and promote social distancing. Again, after a significant increase in the contamination of individuals by coronavirus in October 2020, the French government decided to impose a second containment. I use these three staggered shocks to study the resilience of merchants using contactless payment technology and their effects on merchant sales and substitutions between means of payment. For comparability purposes, I focus the analysis on offline merchants who accept contactless payments since 2019:01 (the treatment group) and those who still do not accept

> 8These datas set are a representative sample of CB transactions and were made available by CB. I exploit the card payments data in accordance with the EU General Data Protection Regulation, in application of Article 89. I use the abbreviation ‘CB’ to indicate the source of the card payments.

> 9The SIRENE database is available on the following link: https://www.data.gouv.fr/en/datasets/base-sirene-desentreprises-et-de-leurs-etablissements-siren-siret/

10
from 1960 to 2020, compiled by the World Bank and the United National Department of Economic and Social Affairs (UNDESA, 2020, World Bank, 2022). A comprehensive dataset on all BLAs for the same period comes from Chilton and Posner (2018), Peters (2019 _a_ ) and Chilton and Woda (2022). We merge the two sets of databases by converting the BLA database into country-pair _×_ decade format for analysis. For each of the BLAs, we designate the country with a lower income per-capita as the _origin_ country and the other as the _destination_ country.

> 1The enforcement of BLAs is often measured through reports from international agencies such as the International Labor Organization, labor inspection data from national governments, monitoring of complaints from migrant workers and worker welfare organizations, or academic research studying the impact of BLAs in specific corridors (United Nations (2022)). However, factors such as lack of data, limited monitoring capacity of national governments, under-reporting of issues by migrant workers, and difficulties in cross-border mechanisms of enforcement can make monitoring effective implementation of BLAs challenging (Chilton and Woda, 2022, United Nations, 2022).

3
57.2|4.6|55.6|2.6|57.6|<br>4.3|55.9|2.0|58.2|
|Monoparental|1.1|6.8|0.5|7.5|0.6|6.3|0.4|7.6|0.7|6.3|0.4|7.6|0.6|6.4|0.3|8.4|
|Female|1.0|84.1|0.5|89.5|0.5|79.8|0.3|80.8|0.5|79.8|0.3|78.7|<br>0.5|79.7|0.3|78.6|
|Lactating and pregnant women|3.9|3.9|34.6|0.8|23.3|<br>3.1|39.9|<br>1.7|47.3|<br>3.1|39.7|<br>1.7|45.9|<br>2.8|40.4|<br>1.2|
|_Community characteristics (from DHS 2000)*_|||||||||||||||||
|Primary school|||||||||||||||||
|With|71.1|89.7|19.4|96.2|51.7|87.4|20.1|80.1|50.7|87.2|18.7|81.3|44.4|86.1|12.1|80.3|
|Without|8.2
(possibly) Nepal as well. Bangladesh has higher levels than typical, whereas Afghanistan and. Pakistan look unexceptional.

The data on the prevalence of bribes line up with those on corruption, with a high prevalence of firms making bribe payments in Bangladesh even for such a poor country and a low prevalence in Nepal. The low cost of constraint reported in the richer SAR countries of Sri Lanka and Bhutan is reflected in a low prevalence of bribes for countries at this level of GDP per capita.

# _Political instability_

Among the SAR countries in which the role of political instability was included in the survey, there is a very clear downward income-constraint locus. The richer country Bhutan registers a very low cost of this constraint (in the cross-country comparison), which contrasts with the higher than typical costs reported in Nepal, Afghanistan and Bangladesh. Pakistan is also on the high side for countries at its level of GDP per capita.

# _Access to Land_

There is an interesting degree of variation in the evaluation of problems related to access to land among the SAR countries (Figure 4). Across countries in the world, the constraint slopes downward as income per capita rises. Among the SAR countries, four have predicted values above the regression line and four, below. There are richer and poorer countries in each group. In the “high” group are Bangladesh, Afghanistan, Pakistan and the Maldives. The exceptional problems of the Maldives are highlighted in the chart. Afghanistan and Bangladesh (and Pakistan in the 2007 survey) also look unusual relative to other poor countries in the extent of access to land problems. The contrast with Nepal is very clear. In India and Sri Lanka access to land appears to be less problematic as compared with countries at a similar level of development.

# _Water_

Problems with the availability of water (Figure 5) tend to be high in the SAR countries as compared with countries at similar levels of development (the exception is the Maldives). The problems in Pakistan are especially notable.

33
, if the entrepreneur had not even started reading the handbook, the facilitator would elicit their priorities among the practices and start introducing the chapter corresponding to the most relevant practice. Each shop visit lasted approximately 30 minutes. At the end of the first visit, the shop owner was asked to establish goals for the implementation of a practice covered during the visit and for the study of selected material. A second visit was scheduled two weeks after the first and at the convenience of the shop owner. This second visit followed the same protocol as the first with the difference that the starting point was determined by the work left from the first session and the entrepreneur’s priorities elicited during that visit.

There are several features that make these sessions unique. First, the assistance was provided on-site rather than in an outside venue, which allowed shop owners to tend to their business matters with only minor interruption. Second, the assistance sessions involved direct one-to-one interaction on topic areas that were elicited prior to each session. As a result, although the sessions were only 30 minutes each, they were intense in engagement and content. Finally, the sessions were led by trained facilitators who themselves came from similar backgrounds as the shop owners. Hence, the social distance between the assistance providers and receivers was quite small.

Appendix Table A1 uses data recorded by the facilitators to summarize several key features of these assistance sessions. First, on a descending scale of 1-5 (1=most interested; 5=least interested), shop owners on average expressed the most interest in learning about marketing practices, though the table shows considerable heterogeneity in interest across all practice areas of the handbook. Second, up to 47.5% of shop owners had already started reading a chapter and over 50% had tried to implement a suggested practice. Finally, up to 42.5% had encountered a problem in implementation, 10
.1|

Source: Jordan Labor Market Panel Survey (LMPS) 2016 and Georgia Labor Force Survey (GLFS) 2019. Notes: GLFS 2019 does not distinguish between owner-operation of or unpaid family work on an on-farm versus an off-farm business Since GLFS 2019 does not include questions on regular/irregular workers, only temporary/permanent classification is reported in the table. For Georgia, permanent workers are defined as those reporting that they are permanent workers. For Jordan, permanent workers are defined as individuals who either report they are permanent workers or who work full-time as regular employees.

overwhelmingly regular or permanent, and temporary work represented a very small share of private sector jobs (Table 3-2).

Informal employment constituted an important component of jobs in both countries. Beyond selfemployment and employment by the family, much of which may be informal, informal wage employment represented 31.3 percent of jobs in Jordan and 13.1 percent of them in Georgia (Table 3-2).

3.3 Response to the Pandemic

# **3.3.1 Jordan**

Beginning on March 21 of 2020, the Government of Jordan put in place rigorous measures to contain the spread of COVID-19, including the closure of businesses and work stoppages for all but essential economic activities, as well as non-essential movement restrictions. In an effort to stem job losses, Defense Order #6 (DF6), also issued in the spring of 2020, prohibited layoffs by registered private firms, unless they were “frozen” or permanently closed. Because many workers still experienced significant wage reductions and others suffered from the cessation of their employers’ operations, Jordan also launched subsidy schemes—the most important of which started in January of 2021. According to the CFUWBES data, despite DF6, even firms 10
male and female car and motorcycle users and implemented regression analysis to estimate the importance of various personal and trip attributes (including gender) in determining the odds of switching to private modes only since the start of the pandemic. Specifically, the analysis applies a logistic regression model with the dependent variable being a binary yes/no of whether the person is a new user of private motorized modes as compared to the pre-pandemic period.

**Finally, where relevant, the analysis highlights results based on the most recent public household travel survey** for the Buenos Aires metropolitan region (ENMODO 2018), whose official results were published by the government in 2022.

# **3. MAIN FINDINGS**

**The first key finding of the analysis is that women in AMBA tend to travel less, even though their trips may be organized into more complex trip chains with multiple trip purposes and stops** . According to the CDR-based analysis, in 2021, men in AMBA made about 19.3 million trips per day, compared to 18.8 million trips by women. However, while the total number of trips by men versus women was higher in the younger age groups (up to 44 years of age), among the older age groups the number of trips made by women was higher, especially in the >64 age group where women were estimated to make 2.1 million daily trips compared to 1.7 million among men (Figure 1). Of course, the _total_ trips may not represent the gender specificity of travel patterns perfectly given that the number of men and women traveling differs in the first place – especially in the older age group the number of women in AMBA significantly exceeds
and Practices, edited by C. Monga and J. Y. Lin. Oxford, U.K.: Oxford University Press.

Steinwender, C., and P. Shu. 2018. “The Impact of Trade Liberalization on Firm Productivity and Innovation.” NBER Working Paper 24715, National Bureau of Economic Research, Cambridge, MA.

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UNCTAD (United Nations Conference on Trade and Development). 2021a. World Investment Report 2021. Investing in Sustainable Recovery. New York: United Nations.

UNCTAD (United Nations Conference on Trade and Development). 2021b. Technology and Innovation Report 2021. Catching Technological Waves Innovation with Equity. New York: United Nations.

UNCTAD (United Nations Conference on Trade and Development). 2021c. Reaping the Potential Benefits of the African Continental Free Trade Area for Inclusive Growth. New York: United Nations.

UNCTAD (United Nations Conference on Trade and Development). 2022. Investment Trends Monitor. Issue 40. Geneva: United Nations Conference on Trade and Development.

UNESCO (The United Nations Educational, Scientific and Cultural Organization). 2019. “Combining Data on Out-of-school Children, Completion and Learning to Offer a More Comprehensive View on SDG 4.” Information Paper 61, UNESCO Institute for Statistics, Montreal, Canada.

UNESCO and UNICEF (United Nations Educational, Scientific and Cultural Organization; United Nations International Children’s Emergency Fund). 2021. Situation Analysis on the Effects of and Responses to COVID-19 on the Education Sector in South Asia. Sub-regional Report. October.

UNESCO, UNICEF, and World Bank (United Nations Educational, Scientific
share of total profits can be distributed to shareholders with a valid domestic identification number, as we document in column (6) – in 2019, only L14 billion in profits can be assigned to individuals with a national ID, out of L40 billion assigned to some shareholder. The main reason for that discrepancy (which can be massive in some years like 2018) is that some of the most profitable corporations in the country are owned by foreign shareholders, many of them corporations themselves. This is income that is not flowing to national taxpayers that can be linked to our other datasets compiling income from other sources, and therefore is not included in our study.

Finally, we highlight that these aggregate of assigned corporate profits refer to the entire dataset of taxpayers in Honduras, only a small share of which is actually used when we combine our tax records with household In as docu- survey. every year, mented in Table C2, the total amount of corporate profits in the final microdata is much larger than the aggregate in Table B1, since individuals being assigned large losses are as a rule not at the top of the distribution, so by construction we end up

> 1In some years the amount of profits assigned to individuals is larger than the total profits. This can happen since profits are often negative – being unable to distribute negative profits from a firm, everything else equal, will increase the total amount of assigned profit in comparison with total profits.

50