rafmacalaba/data-use-mentions-extended huggingface dataset:
industrial composition in Georgia. For example, education, health, and culture are mainly statefinanced whereas manufacturing, trade, and finance are privately-financed. Therefore, industrybased analysis can shed further light on the findings of the public/private sector analysis. When the index is defined in terms of 13 industrial categories, as expected, we obtain a higher value, indicating that 47.47 percent of workers have to be moved in order to achieve gender balance in employment.

Next, we consider the Duncan index of occupational segregation. As we move from the least detailed breakdown (4 skill categories) to the most detailed (299 four-digit categories), the Duncan index rises from 0.3463 to 0.7033. The latter index is the closest to the commonly reported index out of the three occupation-based indices in Table 2. It reveals the degree of occupational segregation much higher than what is observed in industrialized countries. For example, the recent estimates of the Duncan index for the US based on the three-digit 1990 Census occupational classifications indicate the value of about 0.50 in 2011 (Hegewisch and Hartmann, 2014).

During the 2004 – 2007 expansion the degree of industrial and occupational segregation increased (Figure 3). After 2009 however, a downward trend is discernable in the index calculated using all, but the most detailed, categories (Figure 3). This would indicate a decrease in the degree of industrial and occupational segregation. With that said, these changes are not large, which is not unusual. For example, Anker (1998) reports that between 1973 and 1990, the Duncan index in the Netherlands decreased from 0.671 to 0.588 when measured in threedigit SIC categories. On the other hand, in Japan between 1970 and 1990 it hardly changed, if anything increasing from 0.526 to 0.529. In the United States, after declining from about 0.70 to 0.50 between 1970 and mid-1990s, the index stalled at about 0.50 in 2011 (Hegewisch and
**Table 10: Characteristics of importers identified as risky — suits**

|Tax<br>identification<br>number|Declared value (US$)|Unit value (US$)|Taxes (duties and VAT) paid<br>per unit imported (US$)|
|---|---|---|---|
|0000000016|43,120|0.64|0.28|
|0000000017|12,083|0.78|0.34|
|0000000018|6,126|0.58|0.26|
|0000000019|5,754|0.56|0.25|
|0000000020|5,629|1.84|0.81|
|0000000021|2,735|0.76|0.33|
|0000000022|2,112|2.31|1.01|
|0000000023|1,917|0.64|0.28|
|0000000024|1,565|0.59|0.25|
|0000000025|1,506|0.72|0.32|

# **VI. First Lessons and Customs Reforms**

To supplement the risk analysis based on compliance, this study has identified some risky import operations and some risky economic operators. Although we are not yet able to determine what extent we have effectively identified non-compliant operators, we are already in a position to present certain findings: First, by reducing information asymmetry, mirror analysis seems to be a powerful intelligence and investigative tool. While gap indicators aim to provide an estimate of tax losses, ratio indicators aim to identify the type of fraud.

Second, combining mirror analysis with an analysis of declaration patterns is useful to identify and target some high-risk economic operators.

Third, in order to assess the compliance of a declaration, investigators should use all sources of available information, whether internal or external.<sup>38</sup
Two obvious barriers to integration of Venezuelan refugees and migrants in Brazil, that we could not control for in our estimation due to data limitations, are language barriers and xenophobia. The official language of Brazil is Portuguese, while the mother tongue of Venezuelans is Spanish. Consequently, language barrier may partially explain not only the downgrading in grades and occupations, but also lower enrollment rate in _Cadastro Unico_<sup>_ ́_</sup> . Hostility toward refugees and migrants is another barrier. Brazil ranks 50<sup>_th_</sup> in the migrant acceptance index (Esipova et al., 2017), published by Gallup Poll, below many of the other Latin American host countries, so it is likely that xenophobia against Venezuelans may hinder their integration. However, our data does not provide any information on that. The results of the Venezuelans not being sufficiently rewarded for their human capital provides some evidence of discrimination, but it may also point to productivity loss due to other factors like being fluent in Portuguese that we did not control for in the estimation. However, the results point out that occupational downgrading is higher among Venezuelans suggesting di↵erential treatment. Figure 14 shows that the wage gaps between the observed Venezuelan wage and their predicted wage if they are rewarded equally for their endowments as Brazilians and controlling for selection to waged employment are substantial specially at the fundamental<sup>31</sup> and the high school level.

Our results suggest certain policy implications that may accelerate inclusion of Venezuelan refugees and migrants and their children in Brazil. These policy implications include:

- Facilitation of the process of credential and skill verification and validation - This will subdue downgrading in both schools and the formal labor market.

- Strengthen voluntary relocation to areas within Brazil that have more job opportunities - The federal government, along with UNHCR and other civil society have been implementing a program like this since 2018.

- Provision of language training may help children to enroll in school at the grade, commensurate with their age
Figure A2: Main employment treatment effects relative to control <!-- Start of picture text --> Work vs. Control<br>Psychosocial wellbeing<br>Psychosocial index | |<br>Phq−9 | |<br>Cohen Stress Scale | |<br>Life satisfaction | |<br>Sociability | |<br>Self worth | |<br>Locus of control | |<br>Stability | |<br>Health<br>Days healthy | |<br>Preferences<br>Risk tolerance | |<br>Time preference | |<br>Cognitive performance<br>Cognitive index | |<br>Math score | |<br>Digit span | |<br>Gender<br>Household power index | |<br>Work rights index | |<br>Consumption<br>Savings | |<br>Loan repayment | |<br>Necessary goods | |<br>Luxury goods | |<br>−0.4 −0.2 0.0 0.2 0.4 0.6 0.8<br><!-- End of picture text -->

**Notes:** This figure plots the point estimates and 95% confidence intervals for each outcome in the work treatment group relative to the control group. All outcomes are standardized. The scales for PHQ-9 and the Cohen Stress Scale are scaled such that positive values represent better outcomes.

58
Beyond the small fraction of salaried workers with access to social security benefits, the profile of labor informality in Senegal is completed with the presence of a long network of family businesses among self-employed and employers that are beyond the control of the tax authorities. As Table 7 shows, the percentage of these non-agricultural enterprises with a formal accounting system is around a 2.8% – of which only a quarter transmits to the Tax Authority – 97.3% do not have a fiscal identification number and 96.4% are not even registered at the Commercial Register. Tax compliance among these family businesses is almost null, since only 0.5% have their workers registered at Social Security. However, these small firms do not complain about an excess of regulation and taxes as a main obstacle for their business. Even among formal firms, less than a quarter consider that taxes and regulations are a problem for the exercise of their activity. This evidence is consistent with data from larger firms, with at least 5 employees, since 26.5% (30.2%) of these firms consider tax administration (tax rates) as a major or severe obstacle to their growth and operations (World Bank Enterprise Survey 2014). The problem reported by these firms does not seem to be the burden of taxes but the unfair competition from informal firms as the leading constraint for formal businesses.<sup>10</sup> Whether this informality is chosen or involuntary is a key aspect to understand what are the most suitable policies to solve this problem, a matter that will be dealt with in the next section.

# **4. Involuntary informality in Senegal**

## **_Model to estimate involuntary informality_**

To estimate the size of involuntary informality and its underlying drivers, the analysis follows the approach in Alcaraz et al. (2015). In this model, there are two sectors in the labor market: formal and informal. The model abstracts from the participation decision and therefore individuals only
>Bank Level Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .|51|
|||7.1.3<br>Estimated Bank-Level PDs and LGDs<br>. . . . . . . . . . . . . . . . . .|53|
|||7.1.4<br>Credit Risk Exposures, Loan Concentration and Residual Maturity .|53|
||7.2|Results of the Stress Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .|56|
|||7.2.1<br>Aggregate Results for the Banking System. . . . . . . . . . . . . . . .|56|
|||7.2.2<br>Bank Level Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . .|60|
|||7.2.3<br>Sensitivity of Outcome Indicators to Changes in Calibrated Parameters|63|
|||<br>7.2.4<br>Application of the Approach When No Bank-by-Bank Supervisory<br>Data are Available. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .|64|
|**8**|**Con**|**clusion**|**67**|
|**Re**|**fere**|**nces**|**69**|

2
is more one that highlights the general importance of ensuring that markets are contestable and entry barriers are removed – which is much more likely to be the case if reforms are implemented on a nondiscriminatory basis.

# **5 Models of Services Liberalization**

## **5.1 Pioneering work**

Early CGE models of multilateral liberalization focused on trade in goods, motivated by the Tokyo Round of multilateral trade negotiations (Deardorff and Stern, 1981, 1982; Whalley, 1982). These pioneering efforts treated services as nontradables. One of the first attempts to move beyond trade in goods and consider services was an application of the Deardorff and Stern Michigan model to assess the possible impact of the Uruguay Round as it related to services. Building on early barrier estimates by Hoekman (1996), Brown, Deardorff and Stern (1996) and Brown et al. (1996) revised the Michigan model to allow for services trade. Confronting problems now well known (and outlined above), but less appreciated at the time, extending the model required the Michigan team to estimate services trade flows from the swiss-cheese of aggregated and bilateral trade data (conceptually a data cube, but full of holes). In a procedure similar to the one followed in future extensions of the GTAP database, Brown et al. (1996) used a RAS-type routine to estimate the full bilateral trade matrix. Given Hoekman’s assessment that the Uruguay Round did not actually yield any actual liberalization, the analysis of Brown et al. is more of an estimate of what might be accomplished in future rounds. In this context, they model reductions in tariff equivalents of policies restricting trade in services, and conclude that future services liberalization had the potential to yield gains comparable to past accomplishments under the GATT in goods, measured in terms of GDP and trade volumes. More recent estimates suggest that the tariff equivalents grounded in earlier counts of the number of nontariff barriers (NTBs), like those from Hoekman, overstate actual price impacts of barriers to
|3,001|21,161|0.54|0.05|120|32.2|
|ALL ABOVE PRODUCTS|417,213|4,344,658|1.49|3.06|118|41.0|

The higher the index the higher the capital intensity of the production process. Industries with a index value of 100 would have a labor/capital intensity that was average for all manufacturing activity. For information on how the index is derived see Lary (1968) or World Bank (1992).

Source: Derived from United Nations Comtrade Statistics.
ownership of a transaction account. It is the usage of such accounts and other financial services which is more critical. Sri Lanka has made noteworthy advancements in terms of basic financial inclusion metrics. For example, the number of adults with accounts at formal financial institutions stands at 74 percent, ahead of the regional average in South Asia of 68 percent (Global Findex 2017). However, usage of transaction accounts has room to improve, with 26 percent of adults having

> 9 Formal financial services are regulated by the financial sector regulators (Central Bank of Sri Lanka covering banking, finance and leasing companies, Insurance Regulatory Commission of Sri Lanka covering insurance, and Securities and Exchange Commission of Sri Lanka covering capital markets ).

> 10 Annual Report CBSL 2018.

> 11 World Development Indicators, 2015.

7
per kilometer squared compared to the Sub‐Saharan Africa average of 35.<sup>37</sup> Because an accurate high‐resolution map of population density is not available for South Sudan, the spatial distribution of settlements was used as a proxy for population density in order to calculate weights with which to weight poverty estimates.

The methodology had to employ a novel process to generate estimates of settlements given the absence of more recent and up to date population data since the 2008 Census. This process was based on a wide variety of data sources and variables associated with population density, leveraging varied sources of data such as open source data from Open Street Maps on residential areas, roads, health facilities, schools, data from the Global Urban Footprint project, as well as data form the survey itself. The map of settled areas in South Sudan was built by processing and regrouping the data sets (Table 9 in Appendix E). The map of settled areas was created as a binary map (1=settled, 0=not settled) at 100m resolution. While drawing the map, the data sets were manually checked against Google Satellite imagery for the presence of settlements. One advantage of this system of estimation for settlements is that each component can be updated independently as new data become available or the situation within the country

> 37 World Development Indicators.

17
decline following the blockade. However, the results here demonstrate that in some dimensions there was a stronger impact in IPC 4 regions than in the rest of the country. Although the change in food access was very similar in IPC 4 regions and the rest of the country (columns 1 and 2), access to other basic services and the share of households with overlapping deprivations all increased by more in IPC 4 regions.<sup>41</sup> Together, these results demonstrate it could be possible that households in IPC 4 regions might have been impacted more than the rest of the country by all the different shocks that occurred during 2017.

# **7. Conclusion and Policy Implications**

We found that there was a large increase in the share of households receiving food assistance amongst the mobile phone-using population following the 2017 IPC announcement in Yemen. Furthermore, there was a small average increase in food access following the increase in the share receiving food assistance, but much of the improvement was delayed and the immediate improvement was small. We further explore potential reasons for why the improvement in food access was not stronger and more immediate.

There are two primary policy implications based on these results. First, although the results suggest that the humanitarian community is well positioned to effectively support households in the event of new conflict-related shocks, the results also suggest the potential need for more frequent updates to targeting strategies.<sup>42</sup> And second, more systematic measurement of important dimensions of well-being aside from food security can potentially help with better targeting of assistance in Yemen and future crises.

Another policy issue highlighted by this analysis is the potential need for more transparency in the measures that are pivotal in the IPC classification. As demonstrated by the summary statistics, there was little difference between much of the country based on food access measures in the survey used here. More transparency of the data used and the ways in which the evidence was used to converge to an IPC classification could be helpful in interpreting
from visually observable hierarchies. In a real-world scenario, such hierarchies would be identified by experts in road construction and regional accessibility; the priority here was to illustrate our process and its accommodation of such hierarchies. The accessibility improvement modeling process was then run for these sequences as well. The notion of such tiers that form part of the sequences identification process is illustrated in Figure 5 for a number of connecting roads ranked into three tiers. For narrative simplicity, in the remainder of this paper all potential additions to a candidate layout are referred to as a road sequence – whether a standalone road or a combination of roads.

# 3.3. Geospatial cost-time analyses

A recently released geospatial model of Nepal representing distances in units of time offers a scalable, replicable solution to the problem of modeling travel in Karnali (Banick and Kawasoe, 2019).<sup>2</sup> The model calculates the minimum travel time to cross every 30 m<sup>2</sup> of Nepal’s two dimensional surface based on the underlying terrain, landcover, altitude, roads, and road conditions; an accompanying monsoon model adjusts these factors and resulting travel times for monsoon conditions. The two dimensional output is packaged into a 30 m<sup>2</sup> gridded (“raster”) friction surface that can be used to calculate accessibility to various services from any place on the grid. These accessibility rasters can be aggregated into descriptive statistics at almost any useful level of analysis – administrative areas, catchments for specific markets or hospitals, or catchments for individual roads.

Applying the friction surface to services of interest allowed us to specify the precise accessibility gains associated with each planned road or sequence of roads in Karnali province. We measured the increase in accessibility associated with specific proposed roads by generating a friction surface for every proposed road incorporating its projected travel time improvements, then using said model to calculate accessibility to selected nearby services. Comparing these to similar measures from a reference data set based on the existing
Similarly, the number of sample households increased from 3,000 in 2012 to 4,991 in 2016 and 5,311 in 2019. Despite the gradual expansion of the sample, about 74 percent of the households (9,769 observations) were re-interviewed in at least two survey rounds. The sample households were selected following a three-stage sampling procedure. First, the districts were stratified into ACCs defined by the ATA, and five sample districts were randomly selected from each ACC. Second, two _kebeles_ were randomly selected from each district to be part of the surveys. Finally, in the third stage, 15 farm households were randomly selected from each sample _kebele_ based on household lists maintained by local administrations. In addition, about 20 percent of the sample was selected from neighboring 8
lime supplements for better soil management (Smale and Theriault, 2018). Blanket recommendations and subsidy programs that heavily focus on nitrogen without careful attention to soil or agronomic conditions can thus fail to address the relevant limiting factors for plant growth specific to local contexts (Smale and Theriault, 2018).<sup>10</sup> Yet, despite the ubiquity of fertilizer subsidies as an agricultural policy tool and the magnitude of resources devoted to them, little is known about their long-term impacts, or the externalities and waste imposed due to their ineffective use (Gautam et al., 2022). Lopsided subsidies for fertilizers which substantially lower the prices of nitrogen relative to other nutrients can promote inefficient and ineffective use. Such excess use and inefficiencies in application means that not all of the nitrogen that is applied on fields gets absorbed by crops. This is because there is a limit to how much a plant can produce based on nitrogen alone.<sup>11</sup> Due to the unique chemistry of the nitrogen cycle, the remaining excess of reactive nitrogen then gets lost to the surrounding environment in its multiple chemical forms—as nitrites and nitrates polluting the waterways; as anhydrous ammonia or nitrogen oxide negatively impacting air quality; and as nitrous oxide, exacerbating climate change and stratospheric ozone depletion (Kanter 2018).<sup>12</sup> Using disaggregated grid cell-level datasets on nitrogen fertilizer, yields and water quality, combined with administrative data on subsidies from 1995-2013 covering about 150 countries, the paper highlights these unintended but significant long-term costs of fertilizer subsidies. In doing so, the results focus on how ineffective application of nitrogen fertilizer can hurt agricultural productivity as well as impair freshwater resources.

The rest of the paper is organized as follows. Section 2 describes the data and empirical strategy used in this analysis. Section 3 presents the main results demonstrating the impact of nitrogen fertilizer on agricultural productivity, and pollution in the waterways along with the overall impact of subsidies. Finally, Section 4 concludes with policy
0.06|0.02|0.01|0.00|0.03|0.12|0.01|0.12|
|_Pr_(_P_)|0.21|0.15|0.01|0.20|0.05|0.19|0.13|0.25|
|_Pr_(_C_)|0.24|0.22|0.00|0.05|0.59|0.30|0.24|0.32|

_Notes:_ All figures are sample means. Log irrigated area, log( _I_ ), and choice probabilities, _Pr_ ( _j_ ), are simulated by drawing multiple values of _ε_ for each borewell and then averaging optimal choices. Column (7) reports mean predictions when each borewell in the E. Godavari sample is assigned well-flow state probabilites ( _πki_ ) drawn at random from the Anantapur sample. Column (8) is the same as column (7) except that the E. Godavari sample is _also_ assigned pipe widths ( _Ri_ ) drawn at random from the Anantapur sample.

6 shows that the model also reproduces, more or less faithfully, the bivariate relationship between area irrigated (relative to borewell plot area) and the coefficient of variation of groundwater supply.

Comparing the remainder of columns (1) and (2) of Table 7 shows that the model is quite successful at predicting choices of transfer arrangements ( _L_ , _C_ , and _P_ ), but far less so when it comes to unconstrained self-cultivation ( _U_ ) versus autarky ( _A_ ). While the latter result may not seem encouraging, it must be emphasized that our model is _extremely_ parsimonious. Moreover, as alluded to earlier, we are not only estimating choice probabilities. Indeed, it is remarkable that our likelihood, which recruits parameters such as _c_ ̄, _λ_ , and _α_ to fit the mean (and variance) of irrigated area without the benefit of any free constant