rafmacalaba/data-use-mentions-extended huggingface dataset:
Unfortunately, there are important concerns about the coverage and accuracy of earnings data. Fewer countries collect earnings data than employment data, and some countries only collect earnings data for salaried workers. The profits of self-employed workers are notoriously difficult to measure accurately, and inaccurate measures of inflation can also introduce additional noise into earnings data.<sup>16</sup>

# **3.2 Methodology**

_Workers are divided into 16 cells, based on their gender, age, education and location of residence._ Only workers between age 15 and 64 are included in the sample. Age is broken into youth (age 15-24) and adults (age of 25-64), and education is grouped into the least educated (those that completed elementary or junior high) and more educated (secondary level and above). Average indicators are taken for each cell, country, and survey, weighted according to their sample weights. With the exception of education groups in the European countries, the dataset is defined consistently for all 17 countries.<sup>17</sup> _Labor market activity and type of job indicators are considered both as a ratio of the population and of the labor force._ Indicators of interest include the labor market activities over population (employment, unemployment, nonparticipation ratios), sector and status over labor force (share of each sector and status among labor force), and earnings and hours information for workers (earnings, wages, and hours). First we look at trends in employment, unemployment, and non-participation rates as a share of the population. Population trends may be relevant for policies, such as universal transfers, that are delivered outside the labor market. To better understand changes among potential workers and to inform the design of labor market programs, we then examine labor market outcomes for the active labor force. The focus is on shifts in sectors, employment status, and unemployment. Finally, in countries where the data are available, we report changes in average earnings, wages
Table A.4: Attributes of raw data

|**Countries**|133|
|---|---|
|**Firstyear**|1875, Switzerland*|
|**Variablesprimary**|168|
|**Variables cleaned**|76|
|**Policies directly in**|4|
|**headings/PICs**||
|**Policies ingroups, nested once**|66|
|**Policies ingroups, nested twice**|6|

_Source: ESMAP RISE dataset and authors’ elaboration based on dataset described in this paper._ 51
|2%|2%|3%|2%|3%|3%|4%|
|Lazio|10%|12%|11%|9%|8%|10%|9%|6%|
|Abruzzo|2%|2%|2%|2%|2%|2%|2%|3%|
|Molise|0%|0%|0%|0%|1%|0%|1%|2%|
|Campania|6%|6%|7%|7%|13%|7%|7%|4%|
|Puglia|4%|5%|6%|7%|9%|6%|6%|4%|
|Basilicata|1%|1%|1%|1%|1%|1%|1%|2%|
|Calabria|2%|3%|3%|2%|4%|3%|3%|3%|
|Sicilia|5%|6%|7%|9%|10%|7%|7%|2%|
|Sardegna|2%|2%|2%|3%|3%|3%|2%|1%|

Table 1: The Table shows for each Italian region (rows) data of Households’ income shares (DF estimation). These shares represent the income source for households across the regions. The Italian regions are listed from North regions to South and islands (Sicilia and Sardegna)

- SSC employer from ISTAT data 2016. The total social security contributions by employers are equal to €176.5 billion;

- Taxes on commodities, composed of other net taxes on products from national SAM, are redistributed across regions using the demand for the respective commodity as a share. We took data from the national SAM 2016, which report
et al (2005), the authors of the World Bank study “ _Natural Disaster Hotspots: A Global Risk Analysis_ ”, the cumulative precipitation anomaly index is taken. This is the deviation in precipitation from a long‐term mean or median for a specific period of time, usually expressed as the proportion of the long term mean or median. It is straightforward to calculate and does not require other meteorological input (such as temperature data) and thus also no additional spatial interpolation. It is also flexible. It does not impose a distributional structure on the rainfall data, like the widely used Standardized Precipitation Index (SPI) (McKee et al., 1993). Furthermore, unlike the rainfall decile index, which ranks the historically observed rainfall in each location and considers rainfall episodes in the lowest decile(s) as droughts, the cumulative precipitation anomaly index also allows the likelihood of a drought in a particular area to vary across space. The latter is important to explore potential adaptation to frequent drought exposure, as will be seen later on.

13 By taking log transformations, negative predictions are avoided and estimation issues related to the skewness of the rainfall data are mitigated.

14 A similar degree of precision was registered in a series of modified specifications. Using a polynomial regression of the IEW and IDW indices reduces the root mean square error by 0.01 (from 0.764 in the current specification). Similarly, application of the interpolation on the log or squared root transformed values reduces the RMSE only by 0.03. Inclusion of time varying month dummies yields virtually no improvement, while inclusion of regional dummies reduces the RMSE by 0.05.

15 The administrative regions of Vietnam are presented in Figure 0.

16 Other disciplinary conceptualizations of drought include hydrological, agricultural and socio‐economic drought, each accounting for the effect of rainfall deficits on their respective domain of interest. Hydrological droughts relate to shortages of water in river systems which can be due to meteorological droughts in subsets of the river basins but
They also included an allowance for extreme sea levels which influences initial dike heights, and roughly doubled global costs compared to Dronkers et al. (1990) (see Table 1).

To set the stage, we analyzed possible determinants of unit costs of sea dikes with a country-level cross-sectional data set from the DIVA database. The total sample contains 248 observations. We removed 47 observations without low-lying land below 10 meters A.D., as these do not have sea dikes. Furthermore, eight outliers with very high asset densities (e.g. Monaco, Gibraltar, Bahrain) were excluded from the econometric analysis.

A least squares regression analysis was performed to investigate how experts appear to have evaluated the importance of local differences in determinants of unit costs, as revealed
basic needs (CBN) approach in 1995-96 are Takas 593 and 492 in site 1, 529 and 484 in site 2, 592 and 499 in site 3, and 591 and 499 for national rural households. Comparison of HES sample with site specific poverty incidence based on CBN gives a mixed picture with some sites in some rounds having higher poverty rates compared to national rural average and vice versa. Similar to monthly per capita expenditure, poverty incidence varies substantially across rounds. Based on CBN, the highest poverty incidence in all sites are observed in round 2, while based on DCI, the poverty peaks in round 3. As mentioned, round 2 contains the major lean season, while round 3 the minor one.

**Spouses’ characteristics - age, education, and assets at marriage** : On average, husbands are about 8 years older than their wives. To focus on bargaining between husbands and wives, following Quisumbing and Maluccio (2003), I restrict the sample to monogamous households<sup>15</sup> with husband and wife present and with no change in marital status (i.e., divorce, separation, re-marriage, death, etc.) during the survey period. The resulting sample selection bias (if any) would lead to a conservative estimate of bargaining effects as households in which the disagreement between the spouses are the strongest would be more likely to split and are thus absent in this sub-sample.

The marriage module of the survey asked the heads and their wives the assets they owned at the time of their wedding. These assets included land, cattle, housing, food items, and durable (jewelery, watch, clothes, and household utensils). The reported values of these assets at the time of marriage were converted in 1996 taka using national consumer price index. Bangladeshi wives had far less assets at the time of their marriage than their husbands primarily because their value of landholding, housing, and cattle were much less than those of their husbands (see Table
central in the context of graduation decisions, however, as all candidates for graduation have relatively high incomes already. What matters instead is their “capacity to _sustain_ a long term development program” [emphasis added] as reflected in part by “the extent of progress in establishing key institutions for economic and social development” (Shihata 2000: 496).

A more cautious approach toward graduation is thus warranted for countries where this sustainability is in question – that is, where the country has a higher likelihood of falling back below the income threshold. Relevant institutional indicators then are those associated with lower volatility in income levels and growth rates (Mobarak 2005; Quinn and Woolley 2001; Rodrik 1999).

Rodrik (1999) emphasizes “institutions of conflict management” that he argues are particularly important following adverse shocks that often trigger distributional conflicts. Institutions of conflict management are those that “adjudicate distributional contests within a framework of rules and accepted procedures,” including “an independent and effective judiciary” and “an honest and non-corrupt bureaucracy.” A stronger rule of law restricts the potential scope of redistribution, reducing the incentive and ability of social groups to make “opportunistic grabs” in countries with latent social conflicts. As empirical proxies, Rodrik uses the ICRG indicators described above, as well as indicators of civil liberties and political freedoms produced by Freedom House, arguing that: Democratic institutions—political parties, elected representatives, free speech, and the like—can be viewed as the ultimate institutions of conflict management, in that they allow for differences among social groups to be resolved in a predictable, inclusive, and participatory manner (p. 395).

Quinn and Woolley (2001) provide strong empirical evidence that democracies experience much less volatility in income growth than non-democracies, although average income growth is similar in the two groups.<sup>4</sup> Their explanation is somewhat different from Rodrik’s. They argue that voters are risk-averse, and show that voters reward incumbent governments only modestly for growth, but
accurately. We then used the latter module as our data source to measure the main outcomes. We discuss this process in more detail in Section 3.

_Stage 3: Selection of households and respondents._ The experiment was conducted in two regions within the Departments of San Salvador and Usulután. We selected these regions in order to achieve high variation in the types of activities reported. Region 1, which is located in the Department of San Salvador, includes households located close to the Metropolitan Area of San Salvador, the main economic activities of which are commerce, construction, manufacturing, and sugar cane production. Region 2 is situated in the Department of Usulután, where the main economic activities include coffee production, fishing, and commerce. Using the 2007 Salvadoran Population Census (i.e., the most recent census available), we identified 276 enumeration areas (EAs): 114 in Region 1, and 162 in Region 2. Each of these EAs had at least 30 households and was classified as either rural or peri-urban. From the 276 EAs, we randomly selected 48 that were evenly distributed across the rural and peri-urban areas and then conducted a full household listing for each EA. We then randomly selected 21 households within each EA for a total of 1,008 households to constitute our study sample. Within each household, we randomly chose a minimum of two and up to a maximum of four working-age household members between the ages of 15 to 64 years, which yielded a total of 2,480 working-age individuals. Since our main hypothesis consists of the differential impacts of these survey methods by age and sex, we stratified the selection of the working age household members by these two variables, and we defined youth as individuals between the ages of 15 to 24 years.

_Stage 4: Random assignment of households to experimental groups._ We conducted a randomization at the EA-level to assign the 1,008 households with equal probability to one of the following three groups (Figure 1):

1. _LOA Module group
||-0.211|-0.0438|-|-|
||[+125.00%]|[+204.50%]|-|-|

Note: This table shows the event-study estimates of heterogeneous effects across sector and firm’s operating size. Disaggregated sectors (Panel A) include manufacturing & construction; wholesale & retails; transportation; and accommodation, food & entertainment. Firm’s operating size is broken down by revenue quartiles. The coefficients are estimated following Equation 1. Data on household business suspension and closure filings are obtained from the Household Business Tax Census. Data on individual work hours and income are obtained from the Vietnamese Labor Force Surveys. Monthly income is detrended from pre-COVID linear trend and residualized from individual observables including age, gender, educational level, and occupation level. Square brackets show the equivalent of estimated coefficients in percentage changes from pre-COVID means. Standard errors are clustered at the commune level and are presented in parentheses. *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1.

19
|STIC|Product|Export growth|2010|
|---|---|---|---|
|Rev. 3|description|2005-10(%)|RCA|
|p05799|Dried fruit not elsewhere specified,mixtures|342|500|
|p05451|Onions/shallot,fresh/chilled|474|156|
|p05776|Walnuts,fresh/dried|208|55|
|p68422|Aluminum/alloywire|3607|32|
|p68412|Aluminum alloys,unwrought|223|30|
|p05752|Grapes dried(raisins)|90|29|
|p22212|Groundnuts shelled|79|24|
|p05423|Dried beans not elsewhere specified|210|12|
|p05793|Stone fruit not elsewhere specified,fresh|388|8|
|p59312|Prepared explosives not elsewhere specified|211|7|

Source: Tajikistan Customs Committee data, COMTRADE data and author calculations.

To close the discussion on Tajikistan’s export potential, we can look at the resource endowment of the country. Tajikistan has 3.3 million hectares of pastures land, suggesting that livestock may be a sector for potential diversification if complementary measures for fodder conservation, animal health and hygiene are appropriately taken (World Bank 2007a). Given its mountainous landscape, Tajikistan may

> 5 The RCA of country i in product j in year t is defined as: ~~,~~ where Eijt is country i export of

> product j in year t, Eit is country i total export in year t, Ejt is world export of product j, and Et is world total export in year t. If RCAijt>1, country I is said to have a revealed comparative advantage in product j in year t.

> 6 Cai and Leung (2008) calculates the variation of the RCA as follows: , with , and .

8
electricity subsidies to customers during the pandemic while Rwanda did not. Thus, data from these countries will provide comprehensive evidence of the effect of the pandemic and associated policy measures on households and firms in the context of developing economies. Specifically, we seek to address two key questions: first, how did the pandemic affect electricity consumption by households and firms in the developing world? Second, to what extent did pandemic relief measures such as electricity subsidies matter for mediating the impact of the pandemic on households?

Causal identification of the impact of COVID on outcomes is beset with several challenges. The main challenge relates to the universal nature of the pandemic and the wide reach of the lockdowns (SAH) in many countries. This limits the ability of researchers to

> 1https://data.worldbank.org/indicator/EG.ELC.ACCS.ZS?locations=GH-RW

1
barriers between the signing countries. Consequently, one would expect that GVCs are particularly active among countries that have signed regional trade agreements. Indeed, GVC activity is particularly intense among EU and ASEAN members, but it should be noted that other regional trade agreements, such as Mercosur, appear to have been much less successful in generating GVC participation among its members.

Trade costs not only affect the overall GVC participation of countries, but they might have a significant effect in the positioning of countries in GVCs. In sequential (or snake-like) GVCs, trade costs compound along the value chain and have a higher incidence on downstream stages than on upstream stages. As Antràs and de Gortari (2019) demonstrate, this leads remote countries to specialize in upstream stages, and more central countries to specialize in more downstream stages. An implication of this fact is that we might expect the effect of trade costs to be more significant for backward GVC participation indices than for forward GVC participation indices.

Empirical work in international trade also emphasizes the role of market size in shaping bilateral trade flows. Larger economies are expected to export more (since they produce more), and they are also expected to import more (since their income is larger). An often-underappreciated aspect of the gravity model of trade, the most successful empirical model of bilateral trade flows, is that it provides a straightforward explanation for why the ratio of trade to output tends to be smaller 10
15 Useful results can be obtained initially with relatively aggregated Census level inputs, but the same modeling engine is able to accept the most disaggregated customer location data that can be provided. Other inputs representing the costs of best international practice in specific areas can also be derived from current values used in the HCPM since these are driven by technology rather than local conditions. At a later time, these inputs can be customized to fit local conditions as required.

But, what is the usefulness for regulation of cost proxy models like the HCPM? Several questions arise in this context: What is the least information a regulator should have at hand if he is to trust the results given by the model? What is there to be gained if better data is available? What can the regulator do with certain qualities of information? Precision will normally pay, so it is likely to be convenient to make some investment in data collection and elaboration.

We mentioned that the HCPM had been designed with the expectation that it would ultimately be used with a source of geocoded data (i.e. geocoded customer location data or Census block level data). But does lack of geocoded locations imply that the model cannot be applied? The answer to the question is no (with some qualifications). If a map of the study area were available, a grid could be placed on top of it, and blocks could be constructed, where each would be given a location in the grid. In this most primitive case _(least information case),_ we assume that only the total number of residential and business lines for each wire center, locations of the wire centers, and a fairly detailed country or regional map are available. We assume that a user is capable of manually "gridding" the map, creating a matrix in which areas that appear from the map to be populated are given the value '1' and areas which appear not to be populated are given the value '0'. Each populated mesh in the grid
traceable payments, including credit cards, debit cards, cash receipts in B2C transactions, e‐invoices in B2B transactions, financial income information, property transaction information, and other third‐party information provided by public and private institutions. NTS now make use of TIS to verify taxpayers’ tax returns and to analyze risk assessments and tax audits. NTS, using TIS, also provides improved taxpayer services by providing prefilled tax return forms and other tax payment guide services.

Second, ensuring that the tax rebate process is easy and guarantees assured return of the rebate are important success factors. The incentives given to end‐consumers to encourage electronic payments are relatively small, so if the application process for the tax rebate is inconvenient or cumbersome, or if rebate payments are unreliable, people would be discouraged from using the system. While Korea’s VAT compensation for receipts, introduced in 1977, failed due to its inconvenience and unreliable cash compensation, TIETP was successful because of its convenience, which was enabled by making electronic data processing and application processes 41
Thus the power of difference-in-differences estimation is the same with a single baseline and follow-up and _n=100_ , as it is with two pre-treatment rounds and two post-treatment rounds and _n=50_ . Intuitively, with difference-in-differences, every observation counts equally in calculating the pre-treatment and post-treatment means which form the basis of estimation.

This result of course depends on the assumption of equal correlation being a reasonable one. So this implication is likely to make sense when choosing between one or two follow-up surveys, or even between one and five follow-up surveys, but should not be taken to the extreme of saying we should expect the same power from _T=100_ and _n=2_ as we would from _T=2_ and _n=100_ .

**_Implication 9:_** With ANCOVA estimation, when the autocorrelation is high it is better to do a larger cross-section and fewer survey rounds, whereas when the autocorrelation is low, it is better to do relatively more survey rounds and a smaller cross-section. Holding nT fixed, with a single baseline: (i) the optimal value of _r_ holding _nT_ fixed is ; (ii) two follow-up surveys will offer more power than a single follow-up survey for ρ<0.5; (iii) three follow-up surveys will offer more power than one or two follow-up surveys for ρ<1/6.

_Proof:_ Set _m=1_ and _nT=K_ in (11), and then take the derivative with respect to _r_ to show (i). Compare the variances with r=1, 2, and 3, to show (ii) and (iii).

Therefore when the total sample size is fixed at _K_ , power will typically be greater using a baseline and 2 post-treatment surveys with a cross-sectional sample of K/3 than a single baseline and follow-up for many types of economic data. But it will be rare in practice for more than two post-treatment surveys to be optimal with a fixed total sample size. However, the standard practice of a single
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> 9 GDP data come from INEGI (National Accounts).

> 10 The _Índice de Rezago Social_ is calculated by CONEVAL based on the Population and Housing Census.

> 11 The data on the incidence of crimes come from the National Survey on Victimization and Perception of Public Safety (ENVIPE).

> 12 The data on perceived levels of public sector corruption at the state level comes from the National Survey on Governmental Quality and Impact (ENCIG).

21
on water for irrigation.<sup>3</sup> Therefore, Tunisia represents an important case study for assessing the severe impacts of drought on the labor market in a country that, like many others, is increasingly destined to face the impacts of a changing climate. Future scenarios project rising temperatures, decreasing precipitation, increasing evapotranspiration and decreasing availability of water resources with detrimental effects on agricultural productivity (Abdelmalek and Nouiri, 2020; Verner et al., 2018).

# **3. Data**

> 1 INS statistics at https://www.ins.tn/enquetes/caracteristiques-des-agents-de-la-fonction-publique-et-leurs-salaires-2010-2021

> 2 The survey is available at: <u>https://www.eib.org/en/press/all/2022-561-84-of-tunisians-say-climate-change-is-already-affecting-their-everydaylife#:~:text=The%20survey%20results%20confirm%20that,such%20as%20floods%20and%20hurricanes.</u>

> 3 <u>https://www.reuters.com/world/africa/tunisia-introduces-water-quota-system-2023-03-31/</u>

5