rafmacalaba/data-use-mentions-extended huggingface dataset:
modules and arrange it for better reading. An example is the cross-reference between which arms and interventions, which would be most intuitively displayed as a table. Ideally, users can also save searches or selected studies (see above) and visualize various metadata fields for this set (e.g. show the share of entries with a specific value for CV fields). Front-end users should also have access to the same longform/help information as back-end users to facilitate interpretation of the data.

The most important usability features for a catalog are the search and filter options available. Boolean operators AND, OR, and NOT improve filtering within CVs or across fields, e.g. they could allow users to find all studies outside of a specific country, or studies that cover specifically early childhood and primary education. Mathematical operators ( _>_ , _≤_ , etc.) on dates and numerical entries can for example help find studies within certain time periods, or of a certain sample size. A WYSIWYG mask for constructing a search within and across fields helps first-time users, while a free-text entry field supporting advanced search functions makes the exact criteria applied replicable for other users, e.g. for meta-analysis purposes.

Just as with the metadata schema itself, standardization and free access are paramount for fostering the reuse of RCT data and promoting equitable access. We therefore encourage catalog implementers to make user access free and to use open-source programming to allow other catalog owners to adopt useful features.

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# **Trade and Female Labor Participation:**

# **Stylized Facts Using a Global Dataset**<sup>**1**</sup>

**Nadia Rocha**<sup>**2**</sup> **and Deborah Winkler**<sup>**3**</sup>

**Key words:** Trade, GVC, women, female labor force participation, labor share, wage gap **JEL codes:** F1, F2, F6

> 1 This paper was prepared as background work for World Bank‐World Trade Organization joint report “Trade and Gender Equality: Empowering Women in the Global Economy”. The authors thank Ana Fernandes, Caroline Freund, Claire Hollweg and other participants of the “Trade and Gender Authors’ Workshop” at the World Bank on March 7, 2019 for helpful suggestions. We also thank the participants of the “Conference on Trade and Gender” at the World Trade Organization on December 6‐7, 2018 for their comments. We are grateful to <mark>Maryla Maliszewska, Israel Osorio‐Rodarte and Huanjun Zhang f</mark> or sharing sectoral sex‐ disaggregated wage and employment data. We acknowledge financial support from the Trade Umbrella Trust Fund. The findings of this paper are those of the authors and do not necessarily represent the views of the World Bank, or its member countries.

> 2 Senior Economist, Macroeconomics, Trade and Investment Global Practice, The World Bank, Washington, DC 20433. Email: nrocha@worldbank.org.

> 3 Senior Consultant, Macroeconomics, Trade and Investment Global Practice, The World Bank, Washington, DC 20433. Email: dwinkler2@worldbank.org.
The results of our empirical analysis show that the types of discriminatory practices captured by the survey data are related to women’s labor market outcomes. Firms that have restrictions in place on the types of tasks that female employees can carry out are less likely to have a female top manager and employ fewer women. The negative relationship between job restrictions and female employment is particularly strong in the manufacturing sector. While our results do not provide any evidence that allowing women to work night shifts is related to women in managerial positions, we do find that allowing women to work nights is associated with higher levels of female employment. Once again, this relationship is particularly strong for firms operating in the manufacturing and construction sectors. The final relationship that we uncover in the data is that firms offering maternity leave entitlements are more likely to have hired a married woman. In this case, it is particularly difficult to determine in which direction the causality may run – it may be that firms that report that women are entitled to take maternity leave are those firms that already have married women employed.

Overall, the results show that discriminatory behavior by firms and the presence of a discriminatory environment may prevent women from participating in the formal economy and advancing their careers This has some important implications for economic development. Findings from other contexts have shown that female labor supply is related to economic growth. For example, in the United States, research has shown that without the increase in female labor force participation that occurred between 1890 and 1980, income per capita could have been as much as 14 percent below its actual level (Goldin, 1986). Furthermore, Klasen and Lamanna (2009) find that gender gaps in education and employment considerably reduce economic growth, and Cavalcanti and Tavares (2016) suggest that gender discrimination impacts output through two channels – it decreases women’s participation in economic activity, which has a direct impact on output, and it is associated with higher levels of fertility and lower levels of investment in human capital, which have long-run
” Working Paper, IRIS Center, University of Maryland, College Park MD

- Baland, Jean Marie and Jean-Philippe Platteau, 1999. The Ambiguous Impact of Inequality on Local Resource Management.” _World Development_ 27(5): 773-88

- Bardhan, Pranab, 2002. “Decentralization of Governance and Development.” _Journal of Economic Perspectives_ 16(4): 185-205.

- Bardhan, Pranab, and Dilip Mookherjee, 2000. “Capture and Governance at Local and National Levels.” _American Economic Review_ , 90(2): 135-39

- Beck, Thorsten, George Clarke, Alberto Groff, Philip Keefer and Patrick Walsh, 2001. “New Tools in Comparative Political Economy: The Database of Political Institutions,” _World Bank Economic Review_ 15(1): 165-76

- Besley, Timothy, Rohini Pande, Lupin Rahman, and Vijayendra Rao, 2004. “The Politics of Public Good Provision: Evidence from Indian Local Governments.” _Journal of the European Economic Association_ , April-May 2004

- Bird, Richard M. 2003. _Subnational Revenues: Realities and Prospects,_ reading for course on Intergovernmental Fiscal Relations & Local Financial Management _,_

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The rest of the paper is organized as follows. Section 2 presents a number of stylized facts on UK‐EU trade agreements and trade relations. The empirical analysis of the impact of trade agreements on UK trade with the EU and other partners is in section 3. The future scenario analysis is presented in Section 4. Concluding remarks follow.

# 2. Trade agreements and UK‐EU trade

This section presents some key stylized facts on UK‐EU trade relations. The first subsection looks at the trade policy regime, while the second one focuses on trade flows.

## a. Trade agreements

Part of the current public debate on trade policy presents trade agreements merely as institutions aimed at lowering tariffs among member countries and thus sees the trade effects of undoing trade agreements as the result of changes in preferential market access in goods. Modern trade policy institutions are, however, more complex than this. How have trade agreements evolved? How does the EU compare to other agreements?

A new database by the World Bank (Hofmann et al., 2016) reviews 279 PTAs, offering new insights on the changing nature of trade agreements. The approach followed by Hofmann et al. (2016) for the identification of provisions and their legal enforceability follows closely the seminal paper by Horn et al. (2010) and the World Trade Report 2011 (WTO, 2011). Horn et al. (2010) identify 52 policy areas included in PTAs signed by the EU and US. They consider a policy area to be legally enforceable if the language is sufficiently precise, implying clear legal obligations, and if the area is not excluded from dispute settlement procedures under the PTA. Using this approach, WTO (2011) constructed a data set mapping the same set of provisions for 100 PTAs in force in 2011 signed by mostly developed countries that contribute to more than 90 percent of world trade. In an effort to include a larger number of developing countries, Hofmann et al. (2016) updated the WTO data set and
|31.9|55.8|100%|

Source: authors' calculation-b-ased on data in table 5.

Increased government spending on primary education contributes between 12 and 20 percent of the increase (see column 7), reflecting the expansion of overall government budgets and increased allocation to education as a whole. The former factor becomes

> 29 Note that the product of these ratios, 1.43 (=1.21 x 1.18) is the same as the product of the ratios on the left hand side of the equation.

> 30 The first row relates to the data for the two countries at the bottom of the per capita income scale-$200 and $400 respectively-that were already examined in detail above; they are included here for completeness.
In the case of utilities expenditures, the situation is reversed. Population groups with a low vulnerability to poverty cut the consumption of utility services the most. Residents of Minsk, well‐paid employees with high education, and households without children spend more on utilities than the population on average, so they have more room for optimizing the use of utility services. They are also better off, on average, and can afford investments in energy, heating and water saving technologies. Residents of rural areas and small cities also registered a significant reduction in utilities expenditures, which could be due to their greater ability to adjust consumption of utilities in individual houses, relative to apartment blocks in large cities. Households with two or more children were among those who adjusted their consumption of utility services to a smaller extent than the average household (Figure 25).

_Figure 25: Real change in utilities consumption during crisis (2014‐2017) for major socio‐economic groups depending on initial level of food consumption, %_ <!-- Start of picture text --> 2 expenditure on utilities per capita in 2014, in BYN in prices of 2014<br>0 hh_3more_kids<br>10 15 20 25 30 35<br>-2<br>-4<br>hh_single_parent<br>-6<br>-8<br>hh_2kids<br>child<br>-10 nonemployed<br>minsk<br>-12 average<br>large_cities<br>other_edu retiree<br>-14 hh_1child working_age employed hh_no_kids<br>-16 rural sec_specialized_edu<br>small_cities<br>-18 partly_employed high_edu<br>-20<br><!-- End of picture text --> Source: Authors’ estimates based on HSS data.

Among the relatively well‐off population groups, another line of expenditures that underwent adjustments during the crisis was communication services, as well as culture, sports and recreation services, as in these households the consumption of
This paper proceeds as follows. Section II reviews the early literature that examined the impact of tax policy on FDI from a global perspective using investors' surveys and time-series econometric analysis. Section III explores which tax instruments have the greatest impact on FDI and what kind of foreign investors is likely to be most responsive to changes in tax policy since these two areas have retained the attention of many researchers over the past 15 years. Section IV focuses on three issues that have emerged with globalization: the interconnection between the home and host countries taxation and its subsequent impact on FDI; tax competition versus harmonization across countries and states, and the costs associated with tax incentive schemes. The last section concludes with a few remarks and ideas for future research.

# **1I. Early Literature: The Aggregate Approach**

Tax policies are obviously capable of affecting the volume and location of FDI, since all other considerations equal, higher tax rates reduce after-tax returns. Of course, all other considerations are seldom equal. Countries do not only differ in their tax policies, but also in their commercial and regulatory policies, market size, natural endowments, and human capital. All these factors influence the desirability of an investment location.

Based on this perception, the early literature attempted to determine if tax policy was one of the key factors in the decision-making process of multinational companies. Two basic approaches were and continue to be developed: (A) selective surveys of international investors, and (B) time-series econometric analysis. The majority of earlier studies focused on the aggregate FDI data by lumping together firms of all types and paid little attention to differences across sectors and industries as well as between regions and countries. Below is presented a brief summary of the major findings.

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# **7. Conclusion**

The consequences that come with hosting refugees are driven by several factors which encompass the refugee policy in the hosting country, the sheer number of refugees being hosted, the duration of stay of the refugees and the coping strategies which the hosts employ given the refugee shocks, among others. Sub-Saharan Africa (SSA) has to cope with a large and rising number of refugees who live for protracted durations in their host countries. Therefore, understanding the consequences of hosting refugees in SSA has increasingly gained attention in the literature. Several studies have highlighted a net economic benefit. In this study, we contribute to the literature by exploring the potential channels of refugee influence on household welfare and the possible coping strategies employed by the refugee hosting households.

Our study centers on Uganda which has a unique refugee policy. The country hosts the most refugees in SSA and is the third largest refugee hosting nation globally. We use panel data to determine the effect of refugee presence on household welfare based on consumption per adult equivalent between 2009 and 2012. The refugees originate from various source countries. We concentrate our analysis at the enumeration area/cluster level and use a constructed refugee index which weights the number of refugees in the closest refugee settlements by the inversed distance from those settlements to the clusters. This is intended to capture the relative importance of proximity to the refugee settlement rather than the usual classification of refugee hosting districts versus non-refugee hosting districts. We employ a shift-share instrumental variable, which is based on the distance of to the closest border crossing points for each source country, in order to limit endogeneity concerns.

Our results indicate that the presence of refugees causes significant welfare benefits especially for households living closer to refugee settlements. However, it is the rural households, initially involved in subsistence agriculture who benefited from the refugee presence. Uganda is a case in point here. It contrasts with previous studies pointing to households with access to human and physical capital as those most likely to adapt to the refugee shock and respond
No.1, pages 51‐86 Barone, G. and F. Cingano (2011) “Services Regulation and Growth: Evidence from OECD Countries”, Economic Journal, Vol. 121. No. 555, pages 931‐957.

Basu, S., L. Pascali, F. Schiantarelli and L. Serven (2006) “Productivity, Welfare and Reallocation: Theory and Firm‐level Evidence”, NBER Working Paper Series No. 15579, Cambridge MA: NBER.

Beverelli, C., M. Fiorini and B. Hoekman (2015) “Services Trade Restrictiveness and Manufacturing Productivity: The Role of Institutions”, CEPR Discussion Paper No. 10834, London: CEPR.

Borchert, I., B. Gootiiz and A. Mattoo (2012) “Policy Barriers to International Trade in Services: Evidence from a New Database”, Policy Research Working Paper Series No. 6109, Washington DC: World Bank.

Bourlès, R., G. Cette, J. Lopez, J. Mairesse and N. Nicoletti (2013) “Do Product Market Regulations in Upstream Sectors Curb Productivity Growth? Panel Data Evidence for OECD Countries”, _The Review of Economics and Statistics_ , Vol. 95, No. 5, pages 1750‐1768.

Cummins, J. and M. Rubio‐Misas (2006) “Deregulation, Consolidation and Efficiency: Evidence from the Spanish Insurance Industry”, _Journal of Money, Credit and Banking_ , Vol. 38, No. 2, pages 323‐355.

Duggan, V., S. Rahardja and G. Varela (2013) “Services Reform and Manufacturing Productivity: Evidence from Indonesia”, Policy Research Working Paper Series No. 6349, Washington DC: World Bank.

Eschenbach, E. and B. Hoekman (2006) “Services Policy Reform and Economic Growth in Transition Economies”, _Review of World Economics_ , Vol. 142, No. 4, pages 746‐764.

Fernandes, A. and C. Paunov (
place (l), suggesting the notation px,l,t. Because we lack specific information about this vector, we use a triplet of dummies (x, l, t) to proxy the missing input prices.<sup>9</sup> Separate from differences in costs and expectations explained by start-dates of the projects, the duration of the projects may also matter. Booth (1991) points out that projects can exhibit ‘economies of time’, such that projects with longer duration are associated with lower cost per unit costs. On the other hand, CDM projects with longer duration are likely riskier than the projects of same size and type with shorter duration. In order to take account of such time relationships, project duration (in years) is also used as a continuous explanatory variable.

In the methodology outlined above, we use electricity prices to account for expected revenue from electricity sales when calculating abatement costs. Still, because the electricity pricing regimes are sometimes complex and subject to direct and indirect subsidies, using average reported prices to disentangle abatement and power revenue streams can introduce its own set of problems and errors. To account for this, we include estimates based on an alternative approach; we calculate the present value of the total project cost without adjustment and, to account for this omission, include the volume of the generated power as a state variable in the cost function. This also allows for the fact that there may be joint-production effects that the baseline methodologies ignore. In this case, Cin equations (7) and (8) represents the present value of the project costs and the vector of control variables _q_ includes electricity output.

# **3 Data Description**

Available information about CDM projects sent to the CDM Executive Board (EB) for consideration through December 2010 is obtained from the CDM/JI Pipeline Analysis and Database of the United Nations Environment Programme (UNEP) Risoe Center. The dataset includes information about individual CDM project, including the project name, type, registration
in the SILC is to compare the reliability of aggregate income in the SILC against the National Accounts figure of the Central Statistical Office. The study on the micro-macro gap between the EU-SILC data and national accounts shows that coverage of the household disposable income reported in Romania was the lowest in the European Union. The estimated total sum of EU-SILC disposable income was 33% (+/10%) of national accounts' gross household sector disposable income before any modifications. This share was higher than 50% in all remaining countries; it was higher than 75% in many countries. The coverage of wages and salaries in Romania in 2014 equaled 65% and was also the lowest in the European Union. It was nearly 90% or even above 100% in most countries. This situation might be explained by the high number of subsistence farmers and self-employed, but also due to incentives to set up a microenterprise and pay 3% on turnover (below the threshold of EUR 1 million per year and without the obligation to have a full-time employee until 2023) rather than have a labor contract to cover a tax wedge of 43% of gross income. The micro-macro gap at the EU level is caused mainly by measurement errors and conceptual differences (Törmälehto, 2019).

**The outcomes of this comparison are presented in Table 2.** The total compensation of employees in national accounts equals €87.0 billion. The estimate based on the EU-SILC data, which does not include social security contributions paid by the employer, is approximately €75.8 billion. The estimate based on the tax data, which does not include self-employed and social security contributions paid by the employer, is €67.0 billion. Although these estimates are not fully comparable, differences are probably small enough to be explained by varying data coverage.

**Following the literature, we assume that employees report their total income in survey data, including envelope payments and income earned in the informal economy** . The higher value of aggregate compensation
outcomes between the children in the treatment group and their matched counterparts in the control group.<sup>26</sup> The results, indicate little overall effect of the ICDS program on nutritional outcomes (Table 4). We find that the only significant effect of the program was a positive effect on boys’ stunting in the data from the 1992 survey, but not in 1998. For girls, the effect was not significant. We disaggregated the results to see whether there are significant effects at regional levels, but found none except a significant _negative_ impact in the poor Northern states, and in the Northeastern states. There, children living in an ICDS village had a higher probability of being underweight in the 1998 survey.

Other studies also find little evidence of program impact on child nutritional status. A national study (NIPCCD 1992) found the prevalence of underweight children to be somewhat lower where the program was in place, but given the sample sizes of the control and treatment groups these differences are not statistically significant. Using the 1992 NFHS data, Deolalikar (2004) found that the presence of an ICDS center is associated with a 5 percent reduction in the probability of being underweight for boys, but not for girls. Our results from the same survey are in line with this (Table 4). Using data from a sub-group of states, Bredenkamp (2004) found that the presence of a center has no significant effect.

Our results on program impact are not conclusive, because of the absence of panel data on children (or villages) participating in the program. Our method is an improvement on previous studies, because we tried to control for various observed factors that could bias the estimates of the effects of the ICDS programs. However, with cross-sectional data some unobservable household or village characteristics correlated with the program placement and program outcome could introduce bias into the estimates of project impact.<sup>27</sup> If, for example, the program were placed in a village because a food
/sup> , _IL_<sup>_progB_</sup> , _IL_<sup>_progC_</sup> ) for the sample of European countries. Recall that _P_<sup>0</sup> stands for the percentage of poor individuals in the population (Headcount index) and _P_<sup>1</sup> is the poverty gap index.

_IL_<sup>_prop_</sup> can be interpreted as the average tax rate to be levied on non-poor individuals to collect enough revenue to rise all poor individuals to the poverty line. For Romania we see that the index is greater than 1 (3.62). It means that, to defeat poverty, the income of non-poor individuals should almost quadruplicate. Estonia and Hungaria have the same proportion of poor individuals and almost the same poverty gap index. Note however that in Estonia it is sufficient a proportional tax rate of 5 _._ 5% levied on the non-poor to solve poverty, while in Hungaria the tax rate should be fixed at 8 _._ 8%.

_IL_<sup>_flatA_</sup> is the flat tax _f_ to be levied on all non-poor individuals who can bear this cost without crossing the poverty line. For Romania no flat-tax can be collected without having non-poor individuals crossing the poverty line.

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