rafmacalaba/data-use-mentions-extended huggingface dataset:
service**|0.02%|.|0.01%|.|0.15%|7.58%|7.75%|
|**State-owned**<br>**enterprise**|0.01%|0.01%|0.01%|0.02%|0.13%|2.57%|2.74%|
|**Domestic private**<br>**firm**|0.32%|0.05%|0.13%|.|1.40%|6.50%|8.42%|
|**Foreign-owned**<br>**private firm**|.|.|.|.|0.07%|3.37%|3.44%|
|**Total**|2.50%|45.31%|17.17%|0.02%|14.53%|20.48%|100.00%|

**Source: World Bank staff calculations based on 2013 labor force survey.**

**Notes: Working people 15 and over. Data are for 2013. State-owned enterprises include cooperatives.**

As Vietnam’s transition continues and market forces play an increasingly dominant role, labor markets can become more important places of economic opportunities for working people. But these new opportunities will be accompanied by new risks as well as by new expectations from citizens about how their government can help to mitigate risks. As a result, managing and mitigating risks will become an ever more important element of the social contract. Combined with other forms of social protection, appropriately designed and implemented labor market policies – labor market regulations, interventions, and institutions – have the potential to help people better grasp and take advantage of economic opportunities in a risky world. More specifically, labor market policies have the potential to help lower
simple processes to break down siloes and reduce ambiguities that may give rise to bureaucratic discretion.

Finally, our findings suggest new directions for future research on the relationship between FDI and government policy levers. While this paper provides suggestive evidence regarding sources of heterogeneity in foreign investors’ policy experiences and preferences, it is insufficient to draw causal conclusions. More robust research leveraging more granular administrative data sets of FDI would thus be valuable for expanding our understanding of such heterogeneity. As such data sets are rare and more common in high-income countries, efforts to collect and publish granular FDI data (i.e., comprehensive data on MNE affiliate activities in a country) are vital. Finally, as the implications of COVID-19 become clearer and new data are released, future research to understand whether investor preferences have changed post-pandemic will also be critical.

22
divide adolescent pregnant women in two groups, depending on their latent status: those who, after becoming pregnant, choose to give birth (latent status _B*_ ), and those who would choose to abort (latent status _A*_ ). Equation (1) will identify the effect of adolescent childbearing only if:

- (i) The sample is limited to women of latent status _B*_ , who after becoming pregnant choose to give birth. Consequently, they would have only two outcomes: live birth or miscarriage.

- (ii) Miscarriages are exogenous, or there is nothing in the error term  that is simultaneously correlated with the identifier for live birth _X_ and the outcome of interest _Y_ .

In order to ensure (i), it is necessary to exclude from the sample of women who experienced pregnancy as adolescents those who either aborted or would have aborted, had they not miscarried. Do ENADID data allow for this? At first sight the data present two problems that may hinder the seemingly simple process.

First, abortions are grossly underreported in ENADID. Table 2 shows that the number of abortions per thousand women reported in ENADID is 82 times lower than a low estimate based on hospitalization data and surveys of health professionals: 0.34 vs. 28 (Juarez et al., 2006). This is not surprising, considering that in 2006 abortion was illegal throughout the country (it became decriminalized in Mexico City in 2007). However, underreporting of abortions will not bias estimates in (1), as long as women _do not report_ pregnancies that were terminated in abortions (as opposed to reporting them as miscarriages). Provided that women do not report abortions as miscarriages, the coefficient  in equation (1) will be unbiased regardless of the extent of underreporting. A data analysis in the subsequent section will show that reporting abortions as miscarriages is highly unlikely.

The second issue is that some women who reported miscarriages may have latent status _A*_ , but miscarried before aborting
# **5. Conclusion**

The objective of this paper is to analyze the patterns of UB and ALMP indicators across different income groups and regions and investigate the interlinkages between labor market outcomes and UB and ALMP, drawing on novel UB and ALMP data collected from 191 economies in 2019–2020. The paper also aims to assess the trends of global labor market reforms implemented during the Covid-19 pandemic utilizing the World Bank’s comprehensive inventory of these reforms.

This investigation reveals new insights on the patterns of UB and ALMP and their linkages with labor market outcomes in low-income, upper-middle-income and high-income economies, especially given the gap in the literature in developing countries. Also, different from past studies, the econometric analysis in this paper incorporates a wide range of UB and ALMP indicators, as well as many categories of labor market outcomes, and controls for the interlinkages between per capita income and UB and ALMP indicators. Finally, unlike most studies that use micro level data, this analysis employs aggregate-level indicators to assess the overall association between UB and ALMP and labor market outcomes.<sup>22</sup> The key findings of the descriptive statistical analyses can be summarized as follows:

- Among the 191 countries, 47.6 percent have UB schemes and 85.3 percent have ALMP.

- Across ALMP, public employment services (PES) are most prevalent (employed in 81.7 percent of countries), followed by national skills funds (52.9 percent) and government incentives offered for training (53.9 percent).

- The use of ALMP vis-à-vis UB increases substantially, as income level decreases,

- On average, employees need to contribute at least 11.6 months to become eligible for UB, and the average maximum UB period is 37.3 weeks.

- Among the six eligibility conditions for UB covered by the data, all of which are also ALMP, periodic reporting on active job search, participation in a training program, and registration with PES are most commonly used.
I have the estimates of p and p (and the estimates of and ) from the above steps, I employ equation (5) to recover final consumption shares VV<sup>�</sup> NN<sup>�</sup> p . BBpp MMpp **Labor market wedges (** p **):** Data on value-added shares CC<sup>�</sup> p and employment shares p allows expressing sector 's labor productivity relative to any arbitrary sector . As agriculture is almost always TT VV<sup>�</sup> LL the sector with the lowest value-added per worker, I measure productivity in industry and services ii jj relative to agriculture and set . Specifically, the wedge applicable to sector in period equals the ratio of its value-added per worker aappaa to agricultural labor productivity iippaa . ττ = 0 ∀ pp, tt ττ ii **Labor share of income** ) **and sectoral linkages** iippaa ) **:** I obtain the labor share of value-added aappaa tt ww ww at the sectoral level from the Global Trade Analysis Project (GTAP) database (pp pp Center for Global (BB (MM Trade Analysis, 2015). The GTAP data are available for three overlapping years over which I perform the quantitative analysis using the time-series on employment, consumption, and trade shares. I estimate the labor share of value-added for each of the three years, the average of which serves as the benchmark labor share for the entire period under analysis.

10
# **1   Introduction**

The advent of the Industrial Revolution was a defining moment in the economic history of the world. It ignited a period of Great Divergence in which the industrializing nations broke away from the rest (Clark, 2014). For the most part, this divergence that started centuries ago still defines the fault lines between the rich and the poor economies. It is not so surprising then that industrial expansion is a key component of many growth policies.<sup>1</sup> At the same time, deindustrialization remains a robust feature of economic development (Clark, 1957; Kuznets, 1957; Herrendorf _et al._ , 2014), especially when considering the sector's employment share instead of its output contribution (Rodrik, 2016). Moreover, there is emerging evidence that the onset of deindustrialization has been _premature_ in recent decades (Rodrik, 2016; Felipe _et al._ , 2019). The peak industrial share in the developing economies is lower relative to the early industrializers and materializes at a lower income per capita.

A growing literature is trying to uncover the underlying factors that drive deindustrialization. More crucially, it seeks to quantify the growth implications of deindustrialization and identify policies that can arrest the industry's slide. However, the country-level studies only cover a handful of economies. This analysis requires quality long-term sectoral data, which are not available for many countries. Small and low-income economies are particularly under-represented. Using learnings from other cases to devise policies is of limited use if factors driving deindustrialization vary across countries.

This paper addresses this gap by conducting a country-level analysis of six Central American economies in the last two decades. I piece together data from several sources and harmonize them at the sector level. The raw data require cleaning, and I make several adjustments to ensure quality before using them in analysis. Though value-added shares are indeed a part of the examination, the study concentrates on the dynamics of sectoral employment shares. Two facts guide this choice. First,
_<mark>140</mark>_ <mark>, 102991.</mark>

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- Global Data Barometer (2022). _First Edition Report – Global Data Barometer_ . ILDA. DOI: <u>https://doi.org/10.5281/zenodo.6488349.</u>

- Hanson, J. K., & Sigman, R. (2021). Leviathan’s latent dimensions: Measuring state capacity for comparative political research. _Journal of Politics_ , _83_ (4), 1495–1510.

- <mark>Hartmann, D., Guevara, M. R., Jara-Figueroa, C., Aristarán, M., & Hidalgo, C. A. (2017). Linking economic complexity, institutions, and income inequality.</mark> _<mark>World development</mark>_ <mark>,</mark> _<mark>93</mark>_ <mark>, 75-93.</mark>

- Henderson, J. V., Storeygard, A., & Weil, D. N. (2012). Measuring economic growth from outer space. _American Economic Review_ , _102_ (2), 994–1028.

- Hodelin, R. S. (2022). Statistical disclosure and economic growth: What is the nexus? _World Development_ , _160_ , 106036.

- Hu, Y., & Yao, J. (2022). Illuminating economic growth. _Journal of Econometrics_ , _228_ (2), 359– 378.

-
The profiles of the three types of informal urban enterprises are rather similar, in terms of owner characteristics, sector, and motivation for informality, with most differences emerging in earnings, business practices, and access to financial tools. Informal enterprises are primarily led by prime-aged men and women (gender balanced) with a secondary education or less. Seventy percent of firms are younger than five years, reflecting challenges in firm survival, though firms with paid employees are a little older and report higher earnings, suggesting that firm growth is possible. Most firms are in the retail sector, which is also a disproportionately productive sector. These firms use few modern financial tools and practice poor business practices. Half do not see the value of formalizing, do not have information on how to formalize, or do not want to pay the taxes associated with formalization. More productive firms are led by prime-aged adults, are young, and are in the retail sector. HE-SE enterprises have the highest productivity while profits are highest among employers.

Urban variables were weakly correlated with job type. A minority of urban firms express a need for urban public services (electricity, water). Among those who need these services, HE-SE and employers have high access while LE-SE do not, even when controlling for firm productivity level. All express a need for, and access to cell phones, with sufficient cell tower across urban areas. More crowded neighborhoods are home to informal business owners while less poor neighborhoods house more structured work arrangements.

The findings of this study are suggestive due to data limitations. Although the study covers a wide range of African countries across the continent, the GMD only include data for 26 of 48 countries in Sub-Saharan Africa, equivalent to 61 percent of the region’s population. The IES only includes three countries for which we have recent data. The worker and firm data are not strictly comparable due to differences in the number of countries included in the analysis, the national versus main cities representativeness, and the informality focus of the firm
, 36 documents used various kinds of cross-sectional designs (90%). Among these, 20 documents used KAP surveys (50%); 10 used serological surveys with or without supplementing KAP surveys (25%); and six included crosssectional survey studies about other issues (15%). Of the remaining four documents (10%), there was one experimental design study, one quality-control study for laboratories, one census, and one case series study. In **Bolivia** , 24 documents (96%) used cross-sectional design or survey design with different variations. Among these, 16 documents used KAP surveys (64%); seven used HIV serological surveys with or without supplementing KAP surveys (28%); and one was a syphilis serological survey (4%). The remaining document used a longitudinal design, made up by a cohort of people living with HIV (4%).

In Figure 8 below, cross-sectional studies or surveys and their variations appear in different shades of blue.

22
) _External Trade of the Republic of Moldova 2001-2010_ , Statistical Yearbook.

Statistics Moldova(2011) National accounts data. Available at: <u>http://www.statistica.md/index.php?l=en</u> Walewski, Mateusz, Mayu Sandu, Georgeta Mincu, Eugene Hristev, and Beata Matysiewicz (2008) _The effects of migration and remittances in rural Moldova and a Poland’s case study of migration management_ . CASE - Centre for Social and Economic Research. Warsaw.

World Bank (2009) _Moldova: Policy Notes for the Government_ . May 2009.

World Bank (2011) _Moldova Country Economic Memorandum: After the Global Crisis: Promoting Competitiveness and Shared Growth_ , Report No. 55195-MD, April 4. Poverty Reduction and Economic Management Unit, Europe and Central Asia Region.

World Bank (2012) World Development Indicators. October 1. Available at: - <u>http://data.worldbank.org/data catalog</u> 38
percentage-point increase associated with each additional year of education. Firstly, we employ the difference-in-difference method (DiD) to estimate: where _Yi,t_ are the returns to schooling for country i at time t; _Schooling,t_ is the average years of schooling for the population in the country i and time t; _Posti,t_ equals 1 if time t is post-transition (starting with the 1995 observation that represents the 5-year average from the year 1995 to 1999) irrespective of whether it is a transition or a non-transition country, 0 otherwise; _Transition,t_ equals 1 if the country is a transition country, 0 otherwise; _DiD,t_ is the interaction term between _Transition,t_ and _Posti,t_ that captures the average treatment effect of the transition; _ε_ is the error term. No employment variable was included because there is no consistent and comparable employment data available before the transition. The available ILO labor data for most transition countries starts in 1994 (https://ilostat.ilo.org/data/#).

Since the fall of the Soviet Union implied deep political and economic transformations for most of the post-socialist countries, we include two variables to account for these changes: the polity index and trade as a percentage of GDP: where _DiD,t_ is the interaction term between _Transition,t_ and _Posti,t_ ; _Polityi,t_ is the polity index for country i at time t ; and _Tradei,t_ is the share that trade represents of GDP for country i at time t (see Table 1).

6
it wrong not to pay taxes?) and positive views about whether individuals are punished for not paying fees and taxes.

In Table 1 we present correlations across the summary indexes from the household survey on government performance in different areas. All the measures are broadly positively correlated: positive responses or evaluations in one dimension are usually accompanied by positive evaluations in similar dimensions. It is also clear, however, that these measures are not perfectly correlated, i.e., they likely capture different dimensions of citizens’ interaction with the state.

> 15Weights for each component are equal to the sum of row-entries in the inverse covariance matrix. That means the index underweights components highly correlated with other components and over-weights those with "new" information–i.e., those with a low correlation with other components.

16
# **APPENDIX – Definitions**

# **A1. Bank Variables**

The source of all these variables is the BANKSCOPE data base. The time series of the variables at the country level are obtained by taking bank-level averages in each country.

**Net interest Margin** (in percent of total assets): The net interest income as a percentage of total assets. The higher the ratio the cheaper the funding or the higher the margin the bank is obtaining. It is an indicator of the operational performance.

**Non-interest income** (in percent of total assets): It is the ratio of other operating income to total assets. It is an indicator of the operational performance. It indicates to what extent fees and other income represent a greater percentage of earnings of banks. The higher this ratio is the better.

**Pre-tax operation income** (in percent of total assets): The ratio of profit before tax to total assets.

**Overhead Costs** (in percent of total assets): It is a measure of efficiency. It is an indicator of the quality of operations.

**Loan Loss Provision** (in percent of total assets): Loan loss provision in percent of total assets. It is an indicator of asset quality. Ideally this ratio should be low.

**Equity** (in percent of total assets): As equity is a cushion against asset malfunction, this ratio measures the amount of protection afforded to the bank by the equity they invested in it. The higher this ratio the more protected is the bank.

**Non-interest assets** (in percent of total assets): The ratio of non-interest earning assets to total assets.

**Customer and short term funds** (in percent of total assets): This is the ratio of deposits to total assets. It indicates liquidity of banks.

**Tax rate:** It is the ratio of taxes paid to profit before
and religious minorities, indigenous peoples often are among the poorest in society and face institutionalized discrimination at different levels of power, forcing them into economic marginalization and financial insecurity. For this reason, the study also covers indigenous populations and includes a question on the laws regulating communal land rights.<sup>6</sup> _Sexual minorities_ refers to people who are lesbian, gay, bisexual, transgender, or intersex. Lesbian women are women who are attracted to women, and gay men are men who are attracted to other men. Bisexuals are attracted to both men and women. As for _transgender_ , the United Nations defines the term as follows:

[A]n umbrella term used to describe a wide range of identities—including transsexual people, crossdressers (sometimes referred to as “transvestites”), people who identify as third gender, and others whose appearance and characteristics are perceived as gender atypical. Transwomen identify as women but were classified as males when they were born. Transmen identify as men but were classified female when they were born. (Free and Equal Initiative n.d.) Further, an _intersex person_ is someone born with sexual anatomy, reproductive organs, and/or chromosome patterns that do not fit the typical definition of male or female. This may be apparent at birth or become so later in life. An intersex person may be identified as male or female or as neither. Intersex status is not about sexual orientation or gender identity: intersex people experience the same range of sexual orientations and gender identities as non-intersex people. (Free and Equal Initiative, n.d.) International law in the field of LGBTI rights is still in its infancy, and the World Bank Group has only recently acknowledged the economic fragility of those populations (SOGI Task Force 2015) and the effect that exclusion of sexual minorities can have on the economic growth of a country (Kim 2014). As highlighted in a World Bank report on LGBTI communities around the world, data on LGBTI people are scarce
where _Bit_ denotes the entire set of words in the call of firm _i_ at time _t_ , and **1**<sup>**_DEM_**</sup> ( _·_ ) is an indicator function which takes value 1 if the input word is in the “demand” word list, and 0 otherwise. _C_<sup>_r_</sup> ( _b_ ) denotes the set of words in the _r_ -terms range of word _b_ (before and after), and the function _S_ ( _c_ ) is defined as follows: in which _S_<sup>+</sup> and _S_<sup>_−_</sup> represent the lists of positive and negative tone words, respectively. Finally, demand uncertainty on a given call is measured by aggregating uncertainty scores around each discussion of “demand”. The score is computed by the frequency _r_ of uncertainty-related words within the -words range of mentions, divided by the total number of words on a given call. More specifically, the uncertainty score of a given call is calculated as follows: where, **1**<sup>**_UNC_**</sup> ( _·_ ) denotes an indicator function which takes value 1 if the input word is in the words related to uncertainty, 0 otherwise. We set _r_ to 10.

The positive, negative, and uncertainty keywords are identified using the Loughran and McDonald (2011) sentiment word lists. These word lists contain finance related sentiment text which allows us to correctly identify the most relevant words in the earnings call reports.

The same method is used to calculate sentiment and uncertainty scores around supply 6
# **“United We Stand Divided We Fall” Maternal Social Participation and Children’s Nutritional Status in Peru**<sup>**1**</sup>

## Marta Favara<sup>2</sup>

The World Bank and University of Essex

**Key words:** Social capital, Child development, Peru, Young Lives. **JEL Codes** : I12, D1. **Sector Board** : POV

> 1 I would like to thank Prof. Cheti Nicoletti and Dr. Mark Bryan for the extensive discussion and comments and the participants at ISER seminars, at Sirpig workshop 2013 (The World Bank) and at IAFFE conference for their helpful suggestions on an earlier version. All mistakes are the authors’ only responsibility. This paper is a chapter of my PhD thesis at the University of Essex (UK) and it will be partially used for the Regional Study on Chronic Poverty in LAC (LCSPP).

2 Marta Favara (mfavara@worldbank.org) is a PhD candidate at University of Essex (UK), IZA Research Affiliate and ET Consultant at the World Bank (LCSPP). She wrote this paper as part of her PhD thesis at the University of Essex (UK). The paper will be partially used for the ongoing Regional Study on Chronic Poverty in LAC (LCSPP).