rafmacalaba/data-use-mentions-extended huggingface dataset:
# **4. Conclusion**

LGBTI people are already among the world’s most disadvantaged. Any disproportionate impact of the COVID-19 pandemic on LGBTI people will deepen existing disparities and risk undercutting social advancements in reducing discrimination and exclusion. The findings in this paper suggest that transgender and non-binary people are disproportionately affected by the COVID-19 pandemic compared to cismen. The results show that transgender people expect to lose their jobs, consequently expecting to have reduced consumption and lose their health insurance more than cismen. Furthermore, non-binary people specifically experienced psychological distress at higher rates than cismen during the COVID-19 pandemic.

These findings present some important trends that need to be considered in ongoing COVID-19 recovery efforts. The results call for comprehensive targeted safety net programs and explicit protections from discrimination for gender minorities to ensure an inclusive and resilient recovery. Pre-emptive and multi-level interventions that target the unique needs of LGBTI people, and especially transgender and non-binary people, are essential for post-pandemic economic revival. In addition, recovery policies and programmatic interventions need to consider psychosocial support programs to mitigate any negative mental health impact of the pandemic on individuals.

Finally, this paper serves to showcase the use of survey data collected through mobile apps such as Hornet as they offer valuable and unique information on the lived experiences of marginalized communities that may be difficult to reach otherwise, particularly in crisis situations. Similar surveys should continue to be piloted to further research on disparities and challenges faced by LGBTI people and to inform evidence-based inclusive policies.

28
funded R&D. This has several important advantages. First, it encourages enterprises to start conducting more research. As the innovation survey shows, most Latvian enterprises are not particularly active in this regard. This program can help alter the status quo. Second, it encourages enterprises to find commercial outlets for the governmentfunded research which they conduct. This, in turn, will help to stimulate high tech startups and spin-offs. In the US, the government organizes special seminars to teach firms how to apply for SBIR grants. A similar training program would not only help Latvian enterprises apply for a Latvian SBIR program but it could also be tailored to help them apply for various EU programs as well.

If the government is interested, the World Bank could ask the US National Science Foundation (NSF) to help design this component. (See Annex 8 for further details of the SBIR program.)

**Figure 32 From Academy to Industry**

<!-- Start of picture text --> Reaserch Profit Barrier<br>Profit<br>Enthropy of Knowledge<br><!-- End of picture text -->

**RECOMMENDATION 9.  Establish a fund of funds, similar to Yozma in Israel, Sitra in Finland, or SBIC in the US to help attract venture capital to Latvia.**<sup>52</sup> While

> 52 For details of Sitra’s activities, see <u>http://www.sitra.fi/eng/index.asp?MM=1&DirID=62</u> .  Yozma’s venture capital activities are described in http://www.yozma.com/home/ .  For a general overview of the venture capital industry see, Martin Kenney, Kyonghee Han, and Shoko Tanaka. “Venture Capital Industries in East Asia,” Report prepared for the World Bank, 2003.    Also note that the Netherlands established a matching grant program for seed capital investments in the biotech sector
- 39 -

# **Vil Appendix 2: Data**

Data on financial assets of pension funds, life, and non-life insurance companies for OECD countries come from OECD 1997 and 1998 Institutional Investors Statistical Yearbooks. For non-OECD countries the sources are the following:

- a) data for Chile, were specially assembled by Central Bank of Chile at our request.

- b) data for Thailand was obtained from the Association of Provident Funds and the Annual Report of the Department of Insurance in the Ministry of Commerce.

- c) data for South Africa is published in the Federal Reserve Bank quarterly bulletin.

- d) data for Malaysia is published in the insurance annual report and the EPF annual report by Bank Negara.

- e) data for Singapore is published in the yearbook of statistics by the Departrnent of Statistics.

All other variables come from the World Development Indicators database.

**Stock Market Value Traded** Stocks traded refers to the total value of shares traded during the period. Data are in current local currency.

**Stock Market Capitalization:** Market capitalization (also known as market value) is the share price times the number of shares outstanding. Listed domestic companies refer to the number of domestically incorporated companies listed on the country's stock exchanges at the end of the year. Data are in current local currency.

**Table 12: List of countries**

|AUS|Australia|ISL|Iceland|
|---|---|---|---|
|AUT|Austria|ITA|Italy|
|BEL|Belgium|JPN|Japan|
|CAN|Canada|KOR|Korea, Rep.|
|CHE|Switzerland|NLD|Netherlands|
|CHL|Chile|NOR|Norway|
|DEU|Germany|NZL|New Zealand|
|DNK|Denmark|PRT|Portugal|
|ESP|Spain|SGP|Singapore|
|FIN|Finland|SWE|Sweden|
|GBR|United Kingdom|
01.

Overall, the results indicate that higher shares of employment in firms with more than 5 employees compared to microenterprises are significantly associated with movements out of lower tier informal self-employment. In particular, the growth of small firms – with size between six and 20 employees –is positively correlated with shifts from informal lower tier selfemployment to upper-tier- but also lower-tier informal wage employment. Unpacking the correlation by country income group we find that increasing shares of the workforce in small firms (with 6 to 20 employees) lead to shifts to formal wage employment in UMICs and HICs, though the coefficient - albeit positive - is not significant in LMICs and LICs. In LMICs and UMICs the increasing incidence of medium firms (with 21-50 employees) is positively associated with shifts from formal wage work to informal upper tier wage employment.

We also see marginally significant increases in unemployment as larger firms become more common (and significant increases without heteroskedasticity corrections (Table A19). The changing industrial sector thus seems to be correlated with increases in unemployment, which 30
estimates. Specifically, for each aggregate indicator and year, we examine whether the equally weighted alternative estimate falls inside or outside of the 90 percent confidence interval around the baseline WGI estimate. In 2023, the share of countries for which the equally weighted alternative estimate is significantly different from the baseline WGI estimate is below 5 percent for four of the six aggregate WGI measures. For two of the aggregate indicators, the share is somewhat higher: 24 percent for Political Stability and Absence of Violence/Terrorism, and 17 percent for Rule of Law. A similar pattern can be seen averaging across all 25 years in the WGI dataset. For four of the six aggregate indicators, the share of significant differences between the baseline and equally weighted alternative is 3 percent or less, while for Political Stability and Absence of Violence/Terrorism and for Rule of Law, the proportions are slightly higher at 16 and 11 percent respectively.

In summary, the baseline WGI estimates by design assign greater weight to data sources that are more correlated with each other. Conditional on the identifying assumptions of the UCM, this makes sense – data sources that are more correlated have more favorable signal-to-noise ratios and should therefore receive greater weight. It is, however, possible that some of the observed correlation between data sources reflects correlated perceptions errors. In this case, the default WGI methodology would assign “too much” weight to data sources that make these correlated errors. However, the fact that the baseline WGI estimates are not very different from a simple equally weighted alternative suggests that this concern is not very significant.

Of course, the equally weighted version of the WGI discussed in this subsection is just one of infinitely-many possible weighting schemes, and different weighting schemes will naturally lead to different results. For the convenience of WGI users interested in exploring alternative weighting schemes, the WGI website contains a consolidated dataset containing all six aggregate WGI indicators together with all the data from the individual data sources on which the aggregate indicators are based. This dataset can readily be used to
the transition of the economy following a (trade) policy shock and to use those simulations to assess the dynamic distributional impacts of trade reforms. The model relies on the interplay between labor demand and labor supply in a rational expectations equilibrium. The demand side is simple because labor demand is just the value of the marginal product of labor for firms that do not face any costs of adjusting either labor or capital (see Bet, Brambilla, and Porto, 2011). Labor supply to different sectors is derived from workers’ intertemporal optimization decision. In a given period, a worker produces in a sector and earns the equilibrium wage in that sector. At the end of each period, each worker has the opportunity to switch sectors, but at a cost. These costs have a common component to all workers and an idiosyncratic component that varies for each worker over time. The common costs and the parameters of the distribution of idiosyncratic costs can be estimated with panel data. To do this, the authors derive an Euler equation that represents the equilibrium condition for the workers. This equilibrium condition essentially links gross flows of workers across sectors (from sector i to sector j and also from sector j to sector i) with future intersectoral wage differentials. The Euler equation can easily be implemented as a linear regression.

The interpretation of the labor mobility costs in these papers is, in principle, broad. It is possible to argue that these costs include retraining and relocation costs as well as psychological or other nonpecuniary costs of moving (such as tedium in the current job). In addition, the parameters that characterize the labor mobility costs are identified with the correlation of job flows and wage differentials across sectors. This means that, in the data, labor market imperfections and other features of the economy (not modeled) that affect job flows, for instance, will affect the estimate of the labor mobility costs. In consequence, these costs are in some sense “reduced-form” labor mobility costs. I will explore some of their
%. The number of licenses is not fixed, but allocated at the discretion of the regulator. The highest level of protection in the financial sector is associated to insurance services under mode 3 (STRI=41.67). Entry is allowed only through subsidiary and acquisition. If the local firm is private, the foreign ownership limit is 80%. Subsidiaries must form joint ventures with local partners and meet minimum capital requirements. One member of the Board of Directors must be Indonesian.

Table 16. Services Trade Restrictions Indexes of East Asia and the Pacific and the European Union

||Overall|Financial|Telecomm.|Retail|Transportation|Professional|
|---|---|---|---|---|---|---|
|Indonesia|50|23.4|25|50|66.4|76|
|Malaysia|46.1|44.6|25|25|55.4|73|
|China|36.6|34.8|50|25|19.3|66|
|Europe|26.1|4.2|0|25|37.1|54|
|Japan|23.4|1.9|25|25|15.6|56|
|Korea Rep.|23|2.3|50|0|20.8|66|
|Not|e: Europe in|clude 20 coun|tries for which t|here is da|ta. Source: The World|Bank.|

Source: World Bank’s Services Trade Restrictions Database (2012).

Malaysia is the second most restrictive destination considered in this note according to trade policy barriers in services. As in the case of Indonesia, constrains are mainly observed in the professional and transportation sectors. Contrary to the Indonesian case, trade policy barriers in the financial sector are not minor. In the case of professional services,
by Friday, I went to the doctor. The doctor gave me antibiotics, which I took until Wednesday, and now I am fine._ ‖ Yet, among households in poor localities and slums, the underlying models of disease and treatment-seeking seemed to be different. People appeared to be sick all the time and going to a doctor seemed less like an ―exceptional‖ event than a common fact of life, well-integrated into a household‘s daily routine. Illness narratives among poor households we interviewed were fractured and temporally confusing.<sup>3</sup> The chaos inherent in preliminary interviews with poor households--including numerous doctor visits, uncertainty about when the disease was diagnosed, whether it was ―cured,‖ and uncertainty about current health status—is very different from what standard health surveys lead us to believe. The health rounds of India‘s National Sample Survey, for instance, allow for a fairly well-developed narrative in which people fall sick with a variety of

> 2 This is a collaborative study between the authors, anthropologists based at Johns Hopkins University, and the Institute of SocioEconomic Research on Development and Democracy (ISERDD) in Delhi.

> 3 In one case, an interviewer speaks with a woman from a poor household about the diagnosis and treatment of her tuberculosis. The interview winds back and forth; the path of treatment is never clear, and the respondent keeps contradicting the temporal sequence of events.  She cannot give clear answers about what treatment was sought when and what the results from these treatments were. Eventually, it emerges that her tuberculosis was discovered in a hospital when she went for an ante-natal checkup (although we remain unsure, since a little later she tells the interviewer that a private doctor asked for a chest X-ray 6 months before the hospital visit) and that she was then put on a treatment regime. It later emerges that her baby died because, on the advice of her neighbors, she did not breastfeed the child, believing that it would transmit TB to
, to use Deaton‘s terminology, is more prevalent in the sample than is selection.

Similarly, a paper by Gorgens et al. (2007) finds evidence that extremely high mortality rates during the 1959-196 famine in China impacts trends in adult height in rural areas, but the affect of the estimated selection is relatively small. At the same time, no significant mortality bias was found for urban population in China. Bozzoli, Deaton and Quintana-Domeque (2009) also demonstrate that the selection could have a significant positive impact on adult height at very high mortality rates<sup>2</sup> . A recent paper by Moradi (2010) estimates the size of the selection affect of survival in Gambia and finds it to be too small to account for the tall adult heights observed in Sub-Saharan Africa.

> **2** The paper presents several specifications of the regression of adult height on pre-adult mortality rates and mortality rates squared. The coefficients on the linear mortality rates are negative and those on quadratic mortality rates are positive and significant. The estimated inflection rate after which higher pre-adult mortality rates have a positive effect on adult height varies by specification, but for all specifications this rate is outside of the data range (i.e. at or above pre-adult 250 deaths per 1000).

3
(related to the risk of non-compliance with customs regulations ranging from 1 to 9) and valuation advice in case it was issued.

- **Container weight measurement data** We obtained from the company in charge of managing Toamasina’s container terminal - Madagascar International Container Terminal Services Limited (MICTSL) - data on the weight of containers that arrive in Toamasina as measured by weighing at a scale upon arrival for the period 2015-2017. This port authority weight data is merged to the customs data at the declaration level, for declarations whose goods fill completely one or more containers. For declarations that share containers with other declarations this information is missing. These port authority weight data provide a useful benchmark for verifying whether the weight registered by the broker is correct.

- **UN COMTRADE data** We rely on an international trade data source UN COMTRADE to obtain export flows - values and quantities (weight) - at the country-HS 6-digit-year level for all of Madagascar’s trading partners in 2015-2018. We use this mirror data for flows imported by Madagascar

- 14This data was obtained from the customs administration’s internal control systems and merged to the transaction data.

8
Policy Research Working Paper 6425

# **Abstract**

This paper tests whether structural or firm-specific characteristics contributed more to (labor) productivity growth in the European Union between 2003 and 2008. It combines the Amadeus firm-level data on productivity and firm characteristics with country-level data describing regulatory environments from the World Bank’s Doing Business surveys, foreign direct investment data from Eurostat, infrastructure quality assessments from the Global Competitiveness Report, and credit availability from the World Development Indicators. It finds that among the 12 newest members of the European Union, country characteristics are most important for firm productivity growth, particularly the stock of inward foreign direct investment and the availability of credit. By contrast, among the more developed 15 elder European Union member countries, firm-level characteristics, such as industry, size, and international affiliation, are most important for growth. The quality of the regulatory environment, measured by Doing Business indicators, is importantly correlated with productivity growth in all cases. This finding suggests that European Union nations can realize significant benefits from improving regulations and encouraging inward and outward foreign direct investment.

This paper is a product of the Finance and Private Sector Development Department, Europe and Central Asia Region. 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 author may be contacted at adallolio@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
977)|1,304<br>(626)|
|Fraction of total applications denied ( % out of total received)|13<br>(5)|5<br>(1)|17<br>(11)|

Source: Calculations based on the 2011–12 Bank Regulation and Supervision Survey, which reflects values as of 2010. Values in parentheses refer to the 2007 Bank Regulation and Supervision Survey, which captures data as of 2005. ADV: advanced economies, EMDEs: emerging and developing economies (Table 1 provides the complete list of countries).

25
these specific variables from these specific surveys had been used in the literature (i.e., whether as an outcome or as explanatory variables, or as indicative of social norms). We were able to detect that for a given topic, data were used as indicative of a presence of social norms when the indicators referred to were closer to beliefs or opinions (for example, acceptance of wife-beating, intensity of preference for sons), and as an outcome when reporting occurrence or frequency of a behavior (for example, incidence of IPV, fertility). We found many indicators being used both to refer to dimensions of women’s empowerment or agency and to social norms. We then proceeded to sort indicators from the closest proxy of a possible social norm (i.e., beliefs and normative explanations for behaviors), to the ones that reported individual-level outcomes that appear to be the most independent from a possible gender norm. We then identified which indicators were available across countries and survey rounds. The final classification of indicators labels them as either ‘gender norm-influenced outcomes’ or ‘gender-normative attitudes’. Most of the first set of variables come from the DHS data, while the latter is mainly from the WVS data.

Since our primary gender outcome of interest is employment status, that variable is included, followed by education (years of education), which impacts gender outcomes across multiple domains. Next, we look at key hypothesized determinants of labor force participation around marriage and children (age of marriage and age at first birth). The next set of variables relate to intrahousehold power and negotiationagency (role in household decision-making), IPV (incidence and acceptance), age and education gap with spouse, difference between desired fertility and realized fertility, time between marriage and age at first birth, and son preference. The literature has identified these variables as strongly influenced by social norms. Clearly, some variables have a more direct link with social norms, such as the age of marriage and IPV, while
12

# 4. New 1997 Household Budget Survey

In 1996 the author published a study analyzing the distributional impact of the Egyptian food subsidy system.'<sup>8</sup> This study used expenditure data from the 1990/91 Household and Income Expenditure Survey (HIES), which was a large, nationallyrepresentative survey conducted by the Egyptian Central Agency for Public Mobilization and Statistics (CAPMAS).1<sup>9</sup> One of the main problems with this 1990/91 HIES survey was that it did not collect expenditure data on different kinds of subsidized and nonsubsidized foods. For example, the 1990/91 survey did not collect data on the level of expenditures on subsidized bread (like baladi bread) as opposed to nonsubsidized bread (like fino bread). This made it difficult to pinpoint the distributional effects of subsidized foods on different income groups in the Egyptian population.

To remedy this data deficiency, in 1997 the International Food Policy Research Institute (IFPRI), together with the Egyptian Ministry of Agriculture and the Egyptian Ministry of Trade and Supply, carried out a new household survey. This new survey -- the Egypt Integrated Household Survey (EIHS) -- was designed to collect detailed expenditure data on all of the main subsidized and non-subsidized foods in Egypt. The survey was a single-round, nationally-representative survey that included about 2,500 urban and rural households from 20 different governorates. The sample frame used for selecting households was supplied by CAPMAS from its 1990/91 HIES survey.<sup>20</sup> The balance of this paper uses data from the 1997 LFPRI survey to evaluate the distributional impact of Egyptian food subsidies. To do this, several key calculations are made. First, per capita total expenditure is calculated from the IFPRI survey data for each household.<sup>2 1</sup> The measure of total expenditure used is quite comprehensive, and includes: