rafmacalaba/data-use-mentions-extended huggingface dataset:
<!-- Start of picture text --> Figure 4: Absolute Incidence of taxes and transfers in Mongolia (2016)<br><!-- End of picture text --> <!-- Start of picture text --> Pension Child Allowance other social transfers Mortgage Subsidies<br>Electricity Subsidies Heating Subsidies Education In‐Kind Health In‐Kind<br>Income Taxes VAT Excise Tax SSC<br>30%<br>20%<br>10%<br>0%<br>‐10%<br>‐20%<br>‐30%<br>‐40%<br>1 2 3 4 5 6 7 8 9 10<br>Source: Authors elaboration using HSES 2016<br>total taxes collected (negative)<br>Percentage of total expenditures in transfers (positive) and<br><!-- End of picture text --> <u>Notes: Absolute incidence refers to share of transfers received (or taxes paid) in each decile as a percentage of the</u> total expenditures (or taxes collected). Horizontal axis stands for deciles of market income (i.e., before tax-andtransfers income).

23 MONGOLIA Distributional impact of taxes and transfers / November 2018
WPS3793

# **CREATING A POVERTY MAP FOR AZERBAIJAN**<sup>**1**</sup>

**Angela Baschieri * Jane Falkingham * Duncan Hornby ** Craig Hutton ****

*** S3RI, University of Southampton**

**** Geodata Institute, University of Southampton**

# World Bank Policy Research Working Paper 3793, December 2005

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

> 1 This research was funded under the TFESSD from the Norwegian and Finnish governments as part of the Azerbaijan Poverty and Environment Mapping work. The work was task managed by Karin Foch (ECSSD). The authors gratefully acknowledge the constructive advice and assistance from Professor Chris Elbers at Vrije University of Amsterdam, from Karin Foch, Irina Klytchnikova (ECSSD), Julian Lampietti (ECSSD), Peter Lanjouw (DERG) and Aleksandra Posarac (ECSHD) and at the World Bank, and from colleagues at Southampton University, particularly Ben Barton at the GeoData Institute. The team is also grateful to the collaboration given by the State Statistical Committee, particularly by Faig Jalilov who prepared the files for the analysis of census data and supervised the enumeration area matching of the settlement map and the census code and by Yashar Pashar who provided numerous insights into the 2002 Azerbaijan Household Budget Survey.
Figure 9: TFP Gains Removing All Distortions <!-- Start of picture text --> Kenya<br>India Portugal<br>Salvador<br>Ethiopia Ghana<br>Peru Colombia<br>Bulgaria Romania Chile Belgium<br>Hungary<br>Latvia<br>SpainItalyFranceFinland<br>6 7 8 9 10 11 12<br>log GDPpc<br>1.6<br>1.5<br>1.4<br>1.3<br>1.2<br>Y−efficient/Y−distorted 1.1<br>1.0<br>0.9<br><!-- End of picture text --> Note: The figure reports the gains in TFP resulting from dismantling _τi_<sup>_E_</sup> and _γi_ in each country and achieving the undistorted allocation. These gains are reported the log of GDP per capita, taken from Penn World Table version 9.0 for 2014.

_Model_ where � _TFPTFP{τ{i_<sup>_E_</sup> 0 _<u>,</u>_<sup>_,γ_</sup> 0 _<u>}</u>_<sup>_i}_</sup> � is the productivity gain from removing � _τi_<sup>_E, γi_</sup> � in _Data_ _<u>TFP</u>_<sup>_USA_</sup> the model, plotted in Figure 9, and � _TFPi_ � denotes the TFP gain between the US and each country in the data.<sup>34</sup> We see from Figure 10 that distortions account for a notable share of the observed TFP gaps in the data. For instance, the combined effect of distortions accounts for more than 40 percent of the gaps in countries with less than half of the US’ TFP. The distortions in our model
bound to the share of hours that may be performed by robots—occupations are classified as replaceable even if only a small proportion of their work can be replaced by robots.

We combined this information with product-level bilateral data on trade and import tariffs. Trade data come from BACI, the World trade database developed by CEPII, building on original data provided by the COMTRADE database of the United Nations Statistical Division. These data contain annual information on bilateral exports and imports at the HS 6-digit product disaggregation for 224 countries. In our final estimation sample we focus on trade between 26 OECD countries for which we have both EU KLEMS and IFR data (Northern countries), and 181 non-OECD (Southern countries). We exclude from our analysis OECD countries for which we do not have either IFR or EU KLEMS data. Annual data on bilateral applied tariffs by country and product (SITC 2-dig., Rev. 4) come from the TRAINS database of the United Nations Conference 15
6 <u>(www.worldpop.org) were all resampled to 1km resolution and included as covariates with thin-</u> plate splines used to model non-linear effects. These covariates were chosen due to their plausible association with poverty and access to handwashing facilities. While other covariates could be used, here the goal of the spatial modeling was to produce predictions of handwashing risk as opposed to examining factors associated with handwashing risk in detail. We also included an additional penalty term in the model to allow covariates that were not related to the outcome to essentially be removed from the model (Marra and Wood, 2011). This model was used to predict handwashing risk at 1km resolution. District level handwashing risk was then estimated by calculating the population weighted mean for all cells within a district.

# _1.2 Respiratory illness_

To generate continuous maps of respiratory illness, we calculated the prevalence of respiratory illness symptoms at any time in the two weeks preceding the survey at each DHS cluster, available for individuals younger than age 5 years (Croft, Marshall and Allen, 2020). The prevalence of respiratory illness symptoms was then modeled using a binomial GAM with handwashing risk, distance to road, population density and poverty as covariates in addition to a spatial bivariate smooth. The ward level poverty estimates were rasterized to be on the same 1km resolution grid as all other covariates and included as an additional covariate. This model was then used to predict prevalence of respiratory illness at 1km resolution. District level prevalence of respiratory illness was then estimated by calculating the population weighted mean for all cells within a district.

# _1.3 Comorbidities and factors for the probability of severe COVID-19_

In addition to respiratory illness, we generated estimates of the prevalence of several additional comorbidities and probability factors for severe COVID-19 at the district level. Individual probability factors that are included at this stage are based on existing literature and presently are HIV prevalence (without Viral Load Suppression), anemia prevalence, and obesity prevalence, in addition to respiratory illness
they used grids that were constructed based on “bottom-up” methods from geo-coded address locations and population register data. By contrast, for the remaining EU countries they used a population disaggregation grid created by the European Commission’s Joint Research Center (JRC) based on administrative area population and CORINE land cover data. Finally, they used LandScan data for French overseas regions, as well as Madeira and Açores in Portugal (see Dijkstra and Poelman, 2014, pp 7-8 for more details).

> 29 Although _WorldPop_ data sets are available for more countries, Deuskar and Stewart limit themselves to countries for which the data have been derived using “random forest” modeling methods.  These methods are thought to be superior to earlier methods that were used to generate the population grids for other countries.

> 30 See <u>http://web.ornl.gov/sci/landscan/landscan_documentation.shtml for more information.</u>

10
point is that of double counting. The diets that individuals consume do not necessarily have only one dietary risk factor, and hence these individuals are at higher risk for more than one NCD. Adding the risks across multiple trials for individual NCDs is therefore likely to overestimate dietary risks of NCDs in aggregate.

It may be possible to reduce the double-counting on the side of dietary factors by using a more parsimonious indicator of dietary quality, such as the GDRS-protect and GDRS-risk scores (for cross-country data), or the two GDQS sub-scores (for national data). We propose to try this approach.

This does not solve the problem of multiple NCDs, however. Although deaths from NCDs list a primary cause of death, individuals suffering from (and being treated for) NCDs may have multiple conditions, but the individual should only be counted once when calculating treatment costs and lost productivity costs. The pragmatic approach suggested here is to focus on two of the top two conditions in terms of cause of death globally, namely cardiovascular disease and diabetes. Cancer could be included in future, as ongoing prospective cohort studies provide more information on the dietary risks for a broader range of cancers. This may yield an overly conservative estimate of the impact of unhealthy diets on NCDs, but the underlying rule on such economic calculations is always to err on the side of conservatism in such estimates.

# 6. Preliminary Test of the Methodology Using Cross-Country Data

Some preliminary regressions were undertaken using cross-country data, while recognizing that analysis using data for individuals and households within one country would be preferable (discussed in the section immediately following this one). This section discusses results of using cross-country data, benefiting from the recent availability of data on several diet quality measures across over 50 LMIC. Data definitions are given in Table 5. Stata 17 ((https://stata.com) was used for the analysis, and the dataset created using data from public databases is available through the World Bank Microdata Library (https://dimewiki.worldbank.
and Kozicki (2005), Kiley (2015), Lewis and Vazquez-Grande (2017), Brand _et al_ . (2018), and Beyer and Wieland (2019).

> 4 Examples include Holston _et al_ . (2017), Del Negro _et al_ . (2017), Christensen and Rudebusch (2017), and Krustev (2019).

> 5 Examples include Mendes (2014), Fujita and Fujiwara (2016), Belke and Klose (2017), Hledik and Vlcek (2018), and Beyer and Wieland (2019).

> 6 Examples include Hamilton _et al._ (2016), Fiorentini _et al._ (2018), and Schmelzing (2020).

> 7 The only exceptions are Klose (2020) and Wynne and Zhang (2018), who estimate equilibrium rates for the BRIC countries with the Laubach-Williams model. This is only possible because these countries have good quarterly data, which is not the case for most other EMDEs.

3
SAS;<br> green = LAC; black = SSA or MENA.<br>For Myanmar, Sri Lanka, Panama, Peru and Thailand 2015 tariff data are used.<br>Average STRI 2016 used for 23 EU member states.<br>70<br>60<br>50<br>40<br>STRI 2016<br>30<br>20<br><!-- End of picture text --> Across services sectors, distribution and telecommunications are on average the most open (Figure 5). The generally lower level of restrictiveness in telecommunications (both fixed and mobile telephony) reflects the continuous liberalization and regulatory reform of the sector across economies since the 1990s. Within distribution, not surprisingly, wholesale distribution is less restricted than retail distribution, where regulation in some economies has tended to protect smaller retailers from competition (Figure 6).

Financial and transport services are on average more restricted. Commercial banking and insurance services – sectors where there has been gradual liberalization over the last two decades – now constitute the midfield within the sectors covered by the STPD. In transport, the supply of rail and air transportation services are the most restricted (average scores above 50), reflecting in rail transport the difficulties in introducing competition, and in air transport the persistence of policies protecting domestic suppliers from competition. Maritime and road freight transport present the lowest average scores in transport.<sup>15</sup> The maritime transport is fairly open, reflecting in particular the openness in international shipping services. Road transport has traditionally been heavily

> 15 Maritime covers maritime freight transport and auxiliary services (agency, freight forwarding, cargo handling, storage and warehousing).

14
|Services,<br>Agriculture|Mining, forestry, industrial production, services|4.5|
|TR9 - Dogu Karadeniz|Agriculture|Agriculture(specializedproducts: tea and hazelnuts),forestry|2.6|
|TRA - Kuzey Dogu Anadolu|Agriculture|Husbandry, forestry, less-industrialized agriculture,<br>industrialization through increased construction|2.2|
|TRB - Orta Dogu Anadolu|Agriculture|Husbandry, lower skill agriculture, light manufacturing,<br>industrialization through increased construction|3.8|
|TRC - Guney Dogu Anadolu|Services|Developing industrialization (textiles and manufacturing) ,<br>industrialized agriculture,services|8.1|

_Source_ : Turkish Statistical Institute data compiled form Household Labour Force Statistics (publication), Household Labour Force Data Base (internet)

> 18 Does not include all activities. Regional specializations within the country

50
origin and destination, has global coverage: 175 source countries, 200 destination countries, and observations matched with 53 ISIC Rev. 4 industries at the 2-digit level of aggregation. Historical extracts of the database span the years 2003 to 2022.

**Mergers and Acquisitions (M&A).** Mergers and acquisitions (M&A) refers to the consolidation of companies or assets through various types of financial transactions, without the generation of new productive capacity. Cross-border M&A observations - referring to the purchase by a foreign entity of assets that corresponds to more than 10 percent of the total assets of a target company - are sourced from the _Thomson Reuters_ commercially available _Refinitiv_ database. Observations are at the project level, and include, for each investment project, the same information as _fDi Markets_ without the estimation of jobs created. The dataset has global coverage spanning the years 2003 to 2022.

A limitation of both data sets is that observations refer to announcements of future rather than current investment flows, which may take time to materialize. Therefore, they differ from official FDI data in Balance of Payments (IMF) and government records 3
15 overall average of 0.2916 for all employees legally entitled to severance payments. Similar to the IFLS (2007), both proportions suggests a high degree of non-compliance.

The results of the analysis highlight two important findings about the compliance of employers with the severance pay regulations. First, employees who are more vulnerable are more affected by non-compliance. Second, while _de jure_ severance costs may be high for covered wage-and-salary workers, firms frequently do not actually pay the legally entitled amount to eligible employees. The required payments may not be delivered when the payment is due, however, if a firm enters bankruptcy because other creditors may have higher priority claims to the assets of the firm. If the rate of noncompliance due to bankruptcy is high, then an employer-based severance program would be ineffective in providing income security to wage-and-salary employees. A sound company, on the other hand, may face above-average costs when the volume of severance payments is high.

# **4.  Conclusions**

The current impasse in reforming severance regulations reflects objections from both employers and employees. While recent negotiations have either collapsed or ended in a stalemate, renewed efforts are needed to find a workable compromise between the interests of employers and those of employee representatives. In addition, the reform options need to consider the voice of vulnerable workers who have been excluded from the debate. While it is not possible to assess the degree of hardship wage-and-salary workers face following a job separation, it is possible to infer that workers experience two significant disadvantages. First, severance payments are received by only a minority of eligible employees. Second, the severance payments to recipients are only a fraction of the legally-entitled amounts. Approximately one-third of legally-eligible employees actually receive severance pay after a job separation. On average, the ratio of the severance pay received to the legally-entitled amount is below 40 percent. The product of these two ratios yields a wage-loss protection share of between 10 to 14 percent of eligible severed workers’ monthly wages.

Indonesia lacks an administrative structure to pool the risk
Average input tari¤<br>Tari¤s im p osed at hom e on im p orts of interm ediate inputs used are constructed by ...rst keeping tari¤ data<br>and im p ort data only for HS 6-digit products classi...ed as interm ediates according to the UN BEC<br>classi...cation. The sim ple average of tari¤s is taken and im p orts are sum m ed at the EO RA sector level.<br>Im p orts are sum m ed across countries of origin to obtain im p ort weights which are used to com pute an<br>auxiliary m easure of tari¤s on im p orts of BEC interm ediates at the rep orting country-EO RA sector-year level.<br>Then, based on the US Input-O utput table for 2005 from W IO D which was aggregated to the eight EO RA<br>m anufacturing sectors, we construct for each sector the share of its total interm ediate inputs that originates<br>in each of the eight EO RA sectors. Finally, we combine these I-O table weights with the auxiliary tari¤s on<br>im p orts of BEC interm ediates to construct a weighted-average tari¤ on interm ediate inputs at the rep orting<br>country-EO RA sector-year level.<br>Average m arket access tari¤<br>Tari¤s im p osed in destination m arkets on exp orts of the sector are constructed by ...rst taking the sim ple<br>average of tari¤s and sum m ing exp orts at the EO RA sector level. Then, exp orts are sum m ed across<br>destination m arkets to com pute exp ort weights at the rep orting country-EO RA sector-year level which<br>allows us to construct a weighted-average of the tari¤s the destination m arkets im p ose.<br>FD I pro jects<br>Sum of announced green.
significant in the first stage regression. Our two alternative indicators of initial political structure, Communist Share and Initial Executive Constraints, enter both significantly at the 1% level and with the expected sign (columns 2 and 3).

Using alternative indicators of institution building confirms our finding. In columns 4 and 5, we use the change in institutional development as dependent variables. Specifically, we compute the difference between the Rule of Law and Control of Corruption indicators constructed by KKM for 1996 and the respective ICRG indicators for the first year of transition. This has the disadvantage that we have to take the same value for all FSU countries and for all Yugoslav republics.<sup>19</sup> Using these indicators of institutional change confirms our findings. Executive Constraints enters positively and significantly in both OLS and IV and the specification tests confirm our econometric model. Finally, in column 6, we use the institutional reform indicator, constructed by EBRD for 1996. Using the institutional reform rather than the institutional development indicator confirms our results.

The Table 4 results show that even when controlling for other potential determinants of institutional development, Executive Constraints 1992 enters positively and significantly at the one percent level. Controlling for strong links to the political and economic past, as measured by an FSU dummy and the trade share with CMEA partners, does not alter the results (columns 1 and 2).<sup>20</sup> Ethnic fractionalization or being landlocked does not seem to have an impact on institution building (columns 3 and 4). Easterly and Levine (1997) show that ethnic fractionalization fosters rent-seeking and might not be conducive to the building of strong market institutions. Bloom and Sachs (1998) show that landlocked economies experience lower growth

> 19 ICRG data are not available for all countries in our sample for 1996 so that we still have to rely on KKM for the end-point of this variable of institution building.

24
Policy Research Working Paper 7878

# **Abstract**

Gender-based wage discrimination is a highly researched area of labor economics. However, most studies on this topic have focused on schooling and paid limited attention to the mechanisms through which cognitive and noncognitive skills influence wages. This paper uses data from adults in seven low- and middle-income countries that participated in the STEP Skills Measurement Survey to conduct a comparative analysis of gender wage gaps. The paper uses schooling and skills measures, including reading proficiency and complexity of on-the-job computer tasks to proxy cognitive skills, and personality and behavioral measures to proxy for noncognitive skills in wage decompositions. The analysis finds that years of school explain most of the gender wage gap. The findings also suggest that cognitive and noncognitive skills affect men’s and women’s earnings in different ways, and that the effects of these skills vary across the wage distribution and between countries.

This paper is a product of the Education Global Practice Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at Ntognatta@ worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team