rafmacalaba/data-use-mentions-extended huggingface dataset:
G.; Marzucchi, A.; Vona F. (2016): Do green jobs differ from nongreen jobs in terms of skills and human capital? In: Research Policy, 45(5), 1046- 1060.

- Dierdorff, E.; Norton, J.; Drewes, D. W.; Kroustalis, C.; Rivkin, D.; and Lewis, P. (2009) Greening of the World of Work: Implications for O*NET® -SOC and New and Emerging Occupations. The National Center for O*NET Development.

- Dierdorff, E.; Norton, J.; Gregory, C.; Rivkin, D.; and Lewis, P. (2011) Greening of the World of Work: Revisiting Occupational Consequences. The National Center for O*NET Development.

- Elliott, R.; Kuai, W.; Maddison, D.; Ozgen, C. (2021) Eco-Innovation and Employment: A Task-Based Analysis. IZA Discussion Papers No. 14028

Eurostat (2009). The environmental goods and services sector. doi 10.2785/31117

- Granata, J.; Posadas, J.; Testaverde, M. (2021) Indonesia’s Online Vacancy Outlook: from online job postings to labor market intelligence 2020. World Bank.

- Granata, J.; Moroz, H. (2022) Identifying Skills Needs in Vietnam: The Survey of Detailed Skills. World Bank.

- Gregg, C.; Strietska-Ilina, O.; Büdke, C. (2015) Anticipating skill needs for green jobs: a practical guide. Skills and Employability Branch Employment Policy Department. ILO. Geneva.

35
(2015) highlight numerous ways in which the insured took advantage of the NHIS, such as frequent and unnecessary visits to health facilities, impersonation, or even feigning sickness to collect drugs for non-insured persons.

# **3 Data and Research Design**

## **3.1 Data**

To analyze the effects of NHIS implementation on risk coping mechanisms with a focus on child labor impacts, we use household data from the fifth round of the Ghana Living Standards Survey (GLSS), collected from October 2005 to September 2006. The fifth round of the GLSS interviewed 37,128 individuals in 8,687 households. We define a child as aged 5 to 17 years and limit the sample to those households composed by at least one adult and one child (30,060 individuals in 7,982 households), i.e., households with at least one potential child laborer.

Because the timing of implementation of the NHIS is non-random,<sup>7</sup> our empirical strategy relies on within district variation as opposed to cross-district variation. Correctly identifying geographic information is therefore central to our analysis. The finest within-district level reported in the survey is the enumeration area (EA), which roughly corresponds to villages (in rural areas) and neighborhoods (in urban areas). EAs within the same district were surveyed at different times, with no systematic order. Importantly, the date of the survey of each EA is orthogonal to key defining characteristics, such as population, economy, infrastructure, provision of education, and health care facilities.<sup>8</sup> This orthogonality is key for the identification of the treatment effect of insurance, as we will explain below.

We link the survey data to information on the exact implementation date of the NHIS at the district level. We collected these data from several sources, ranging from district level NHIS web-pages to newspaper articles and phone calls to district level NHIS authorities.<sup>9</sup> During
health-related intentions into health outcomes. In consequence, these potentially-critical variables are generally excluded from statistical assessments of relationships between DHS-recorded variables and health outcomes .

In South Asia, many empirical studies based on the DHS and local sampling exercises have found that health outcomes are improved when parents (usually mothers) are better-educated, wealthier and more mature. Supporting evidence for wasting can be found in Vollmer et al. (2017), Harding et al. (2018), Martorell and Young (2012), Black et al. (2018), IFPRI (2014), Frongillo et al. (1997) and Fernandez et al. (2002). Similar results for maternal anemia can be found in Dutta and Sengupta (2017), Mangla (2016), Gogoi et al. (2016), Chowdhury et al. (2015), Mithra et al. (2014), Arlappa et al. (2014), Singh and Chaudhary (2015), and Tayade et al. (2018).

Other studies have suggested that culture-based preferences can also play a significant role. For example, associations between child gender, birth order and wasting have been explored by Harding et al. (2018), Hill and Upchurch (1995), and Pillai and Ortiz-Rodriguez (2015). In a study of child feeding practices, Dasgupta et al. (2018) find a perverse “education bias”: Cultural preferences seem to dictate a negative association between maternal education and the share of fish among animal protein sources, even though fish is both less expensive and nutritionally superior.

With these studies as background, we specify regression models for child wasting and maternal anemia in equations (1) and (2) below. All regression variables are based on identical measures in the DHS surveys for India and Bangladesh. We posit that child wasting probability is a function of mother’s education,<sup>3</sup> household wealth, mother’s age, child birth order and child birth month.<
- Hanson, G. H. (2006). Illegal migration from Mexico to the United States. _Journal of Economic Literature_ , _44_ (4), 869–924.

- Kemnitz, A., & Mayr, K. (2012). Return migration and illegal immigration control. _Norface Migration Discussion Paper No. 2012-40_ .

- Kossoudji, S. A., & Cobb-Clark, D. A. (2002). Coming out of the shadows: Learning about legal status and wages from the legalized population. _Journal of Labor Economics_ , _20_ (3), 598–628.

- Krafft, C., Assaad, R., & Rahman, K. W. (2019). Introducing the Egypt Labor Market Panel Survey 2018. _Economic Research Forum Working Paper No. 1360_ .

- Lacuesta, A. (2010). A revision of the self-selection of migrants using returning migrant’s earnings. _Annals of Economics and Statistics/Annales d’Economie_<sup>_ ́_</sup> _et de Statistique_ , 235–259.

- Lavy, V. (1984). The economic embargo of Egypt by Arab states: Myth and reality. _Middle East Journal_ , _38_ (3), 419–432.

- Mann, J. (2012). King Faisal and the challenge of Nasser’s revolutionary ideology. _Middle Eastern Studies_ , _48_ (5), 749–764.

- Massey, D. S., Pren, K. A., & Durand, J. (2016). Why border enforcement backfired. _American Journal of Sociology_ , _121_ (5), 1557–1600.

- Massey, D. S., & Singer, A. (1995). New estimates of undocumented Mexican migration and the probability of apprehension. _Demography_ , _32_ (2), 203–213.

- OAMDI. (2016). Labor Market Panel Surveys (LMPS). Retrieved from `http:// www.erfdataportal.com
I POLICY RESEARCH WORKING PAPER 2198

# Summary findings

There have been extensive theoretical studies of firms' responses to environmental regulations and enforcement but few empirical analyses of firms' expendirures on pollution abatement in response to different reguilations and enforcement strategies.

Wang and Chen empirically analyze the pollution abatement efforts of Chinese industrial firms under a system combining pollution charges and abatement subsidies.

Using data on China's top industrial polluters and on regional development in China, they find that the combination of charges and subsidies used in China has provided effective incentives for the most heavily polluting industrial firms to abate pollution.

Chinese industries operate under a unique pollution control system, a rnarket-based instrument combining emissions charges and abatement subsidies. This combination of clharges and subsidies has given firms incentive to invest in wastewater treatment facilities. The pollution levy, although low, has significantly improved investments in abatement.

Wang and Chen found that the more pollution a firm generates, the more likely it is to invest in pollution abatement.

This study was only of top polluters, which are closely monitored by environmental agencies, so the results may not be valid for other sources of industrial pollution.

- - This paper a product of Infrastructure and Environment, Development Research Group is part of a larger effort in the group to identify appropriate policies for environmental regulation in developing countries. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Hua Wang, room MC2626, telephone 202-473-3255, fax 202-522-3230, Internet address hwangl@worldbank.org. Policy Research Working Papers are also posted on the Web at http://www. worldbank.org/html/dec/Publications/Workpapers/home.html. October 1999. (28 pages)

_The Policy Research Working Paper Series disse7ninates 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 filly polished. The papers
RePEc rankings for the under 60 economists, and a larger impact for the over 60 economists.

This evidence is thus consistent with the view that blogging helps build prestige and recognition in the profession, with bloggers being more likely to be admired or respected than other academics of similar (or in many cases better) publication records. This is of course only a correlation, and there are several caveats to consider. First, to the extent that blogging serves to increase the RePEc ratings by increasing downloads (as seen in the previous section) and citations, the observed correlation will be a lower bound on the causal impact of blogging.<sup>14</sup> However, if bloggers are also more likely to be engaged in other activities of a public intellectual, such as media appearances, writing books etc., and if these don‟t all arise directly as a result of blogging, the estimates will conflate the impact of blogging with the impacts of these other activities, thereby overstating the impact of blogs. Nevertheless, given the large magnitude of the coefficient observed, it does not seem likely that all of the observed impact of blogging just reflects omitted variables, and therefore we view this evidence as strongly suggesting that blogging increases the influence, respect, or public image of the blogger.

# **4. Survey Data from Development Economists**

In order to explore in more detail how potential readers use blogs, in February 2011 we conducted surveys of several potential readership groups for blogs about development economics issues. Development economics is a useful case to examine for several reasons. First, it is a field in which a mixture of academic and less academic potential audiences can be identified, which may be

> 14 Mixon and Upadhyaya (2010) show that among bloggers, there is a positive correlation between the readership levels of the blog and the academic citation levels of the bloggers, although it is not clear whether this reflects a causal relationship in either direction.

13
expenditure in their model is determined by a wide range of regressors, including the existing stock of infrastructure, population density, the urbanization rate, the urban-rural balance, the labor force participation rate, per capita GDP, the internal and external balances, size of the foreign sector, terms of trade shifts, debt obligations, the level of institutional development, level and mix of foreign funding, and the degree of antipoverty commitment on the part of government.

In our approach, we broadly follow the Fay (2001) and Faye and Yepes (2003) specification, taking into account recent work of Estache (2005) and the World Bank (2005a) that includes estimates of investment needs in the entire Sub-Saharan African region. The methodological innovation is the use of a panel of 52 low- and middleincome countries employing dynamic heterogeneous panel estimation methods in order to arrive at robust estimates of “demand” for infrastructure in electricity and telephony as a first step towards forecasting investment needs in South Africa.

# **The Econometric Approach to Estimating Demand for Infrastructure**

# **_The general approach_**

We adopted a three-stage, general econometric approach in estimating the demand for electricity and telephony, and for projecting the dollar investment needs in electricity and telephony for South Africa through 2010.

In the _first stage_ of the research, we perform a panel data analysis on 52 countries for the period 1980-2002 from the World Bank World Development Indicators database to estimate two separate demand equations, for electricity and total telephone lines (fixed and cellular). The estimator employed in this context distinguishes between long-run equilibrium and short-run dynamics, and allows for panel group (country) heterogeneity in the dynamics of adjustment to long run equilibrium. In doing so, we avoid the danger of bias and inconsistency in estimation under the assumption of group homogeneity. The result is a set of more accurate parameter estimates, underlying the remainder of the forecasting exercise.

Then, in the _second stage_ , we use the estimated demand equations to project the electricity and telephone demand
0.69|0.56|0.7|
|Price of an inter-Africa call per mi|nute|US $||0.42|1.16|0.94|1.06|0.99|

_Source:_ Adapted from Minges and others 2009 using data from the Central Bureau of Statistics, Sudatel, Zain, and World Bank ICT At-aGlance.

_Source:_ Data for landline subscribers is for 2005 taken from the Central Bureau of Statistics, South Sudan; Mobile phone subscriptions based on World Bank staff estimates for 2011; _Note:_ Landline and mobile subscriber data are based on information from Sudan; the others are based on Sudan aggregates. These are representative of Sudan because until recently South Sudan did not have access to adequate ICT services. Most of the ICT connectivity existed only in Sudan.

Analysis of 2006 data for all parts of Sudan suggests that almost 98 percent of the population could access mobile telephony on a commercially viable basis (figure 26). This result is based on the assumption that 4 percent of local income in each area could be captured as revenue for voice telephony

> 7 Global system for mobile communications.

> <sup>35</sup>
# **I. Introduction**

The set of decisions made in the transition to adulthood -- including when to exit school, when to marry, and when to seek employment -- are critical with respect to a young person’s well-being over the life course. These life events are, in turn, related to moves to new dwellings and new communities. Consequently, migration is common in adolescence and young adulthood, often more so than for older adults. Yet empirical studies of migration tend to focus on adults, and not specifically adolescents and young adults. It is a topic sometimes omitted from major studies on transitions to adulthood or only touched upon in a limited fashion often due to data limitations, such as the Panel on Transitions to Adulthood in Developing Countries (2005). Equally important, work on migration tends to emphasize international migration which for many developing countries captures only a small fraction of migration. Migration for many is not only within-country, but may be fairly local.

The objective of this paper is to investigate the relationship between household characteristics, major life-cycle decisions, and migration among adolescents and young adults in contemporary Malawi. Our research questions are twofold. First, what are the socio-economic and demographic determinants of migration, and how are these conditioned by gender? Second, how does school attendance, first marriage, and employment-seeking relate to migration patterns? In a departure from many migration studies in Sub-Saharan Africa, we emphasize moves that are the most common and therefore the most relevant: within-country and often local moves to neighboring communities.

To investigate these questions, we draw on two data sources. We examine descriptive patterns from cross-sectional national household survey data. For further analysis, we take advantage of panel data collected from a survey designed specifically to explore socioeconomic 2
# 4. Application: Estimation of the Basic House Price

This section demonstrates how the large volumes of property price data collected for select EMDEs can be used beyond descriptive statistics. To do so, we introduce the notion of the _Basic House Price (BHP)_ , the price of a standard house that is defined identically across all markets. By fixing the type of house to be the constant, _BHP_ aims to provide a data point on price that is independent of the distribution of type/quality of housing that varies widely across markets. The _BHP_ is a key concept that allows for the comparison across and within EMDEs, assessing critical drivers of price and performance of housing markets at the lower end of the price spectrum.

We apply a machine learning technique, Random Forest (RF), to estimate the _BHP_ from the collected web scaped data. Compared to Ordinary Least Squared (OLS) regression, Random Forest has consistently been found to perform better and provide more accurate price predictions (cf. Section 2.3). While the results are presented for five countries as way of application in the next section, the methodology introduced can be rolled out for all emerging economies.

## 4.1 Defining a Basic House

Housing costs reflect the value of the land, the price of the house, the age, condition, and location of the property, as well as the local market. Also, private property prices depend on macroeconomic as well as demographic conditions including migration, urbanization rates, population growth, income growth, a country’s housing finance system including current interest rates and the availability of mortgage lending for all segments of the population. Other aspects relevant to house prices include challenges on the supply side such as a restrictive regulatory environment with lengthy permit granting processes, a shortage of labor and low mobility, as well as high construction costs.

In estimating the _Basic House Price_ , we focus on formal housing built by private developers, through public-private partnerships between developers and governments, or by private individuals
# **Conclusion**

**The SDS makes several contributions** . First, the SDS provides a comprehensive but also in-depth portrait of skill, task, and educational requirements for a set of detailed occupations in Vietnam. The SDS is among the first surveys to collect this information at the detailed occupational level in a developing country setting. The collection of information about detailed skills means that these skills can be flexibly grouped into different categories (for example, socioemotional skills, digital skills, routine skills, interpersonal skills) as needed. The use of a consistent scale anchored to the time spent using or performing a skill or task yields a measure of skill and task importance that is easily interpreted. The SDS approach also has some advantages over collection of skill and task data via online job vacancy data, which has become common in recent years. In developing country contexts, online vacancy data tends to be biased towards higher-skilled digital-intensive occupations and jobs at firms that use the internet (CSC 2019; World Bank 2021). The SDS avoids this bias by selecting the occupations of interest, including low-skilled jobs, first and using a sampling frame based on Vietnam’s Labor Force Survey. Finally, the information generated can be easily compiled into profiles that can be shared with labor market stakeholders in order to inform career and workplace decisions.

**Still, the SDS has some weaknesses** . The SDS requires outlays on administering a survey, and initial data collection covered only 30 of the hundreds of occupations in Vietnam at single point in time.

**Ensuring the sustainability of occupational profiling efforts will require ongoing investment** . To be useful to students, employers, training institutions, policy makers, and other labor market stakeholders, labor market information must be both comprehensive and updated. This means that the SDS would need to be expanded to eventually cover all occupations in Vietnam. Plans would also need to be made to periodically review occupations already covered by the SDS. These efforts would require investment in survey administration
grade; ADU randomly selects which specific test papers are offered in a given school. The SLQAT is transported in sealed envelopes and opened only in the presence of the school administrator and teachers. At that time, both the PEF inspection team and the school learn which grades are selected for the SLQAT. Test invigilation is coordinated by the ADU member assigned to the PEF inspection team. The completed tests are transported back to PEF headquarters and graded by ADU. The school passes the SLQAT if at least 67% of tested students score 33% or higher.

Figure 2 presents the numbers of schools which passed each step of the program entry process. Out of the 1,070 and 1,430 schools that had submitted properly filled-in applications and were inspected in phases 3 and 4, respectively, 799 (75%) and 872 (61%) schools were offered the SLQAT. Of the schools that were offered the SLQAT, 514 (64%) and 431 (49%) schools achieved the minimum pass rate and became eligible for the program.<sup>14</sup> In terms of program take-up, PEF reports that 482 (94%) and 425 (98%) of the schools that passed the SLQAT in phases 3 and 4 respectively signed the formal program participation agreement.

_Continuing benefit eligibility rules_ : The program participation agreement stipulates several conditions for maintaining benefit eligibility. The conditions that are stringently applied by PEF are (1) schooling is offered to students without charging them any fees (and displaying the freeschooling status prominently on a PEF-issued signboard outside the school gate) and (2) participation of the program school in the QAT and that at least 67% of the tested students score 40% or higher on the QAT. A one-time violation of these conditions typically results in a warning and the capping of enrollment figures for the subsidy payment until the next QAT round. A second violation results in the permanent disqualification of the school with immediate

> 14 Our own tallies based on the SLQAT data
Round-tripping became an important practice for Russia’s economy as well. According to Kheyfets (2010, 15), between 70% and 90% of Russian companies formally belong to companies registered in offshore zones. A high correlation of inward and outward investment flows between Russia and such financial hubs as Cyprus and the British Virgin Islands became a distinctive feature of FDI in Russia (UNCTAD 2013, 65). A surprising emergence of the island of Cyprus as the major source of FDI into Russia as well as the central destination for Russia’s outward FDIs is driven by the phenomenon of round-tripping. Cyprus ranked first among the biggest sources of FDI coming to Russia before 2013, and by 2016, the trends returned to pre-crisis levels (i.e., prior to the 2014 sanction regime). As of August 2019, Cyprus is also the most popular jurisdiction to register businesses of Russian origin. According to Russian economic consulting firm _Credinform_ , over 53% of Russian companies with offshores are controlled through Cyprus.<sup>9</sup> Other offshores such as the Seychelles and British Virgin Islands account for 14% and 11%, respectively.<sup>10</sup> Cyprus is an important offshore not only for Russia. Rabab’ah et al. (2016) conducted a social network analysis relying on the data from the Panama papers and focusing on the Middle East region network. This analysis revealed the United Arab Emirates and Cyprus as the central nodes with the highest degree of connections to other nodes in the network, implying a significant role played by these jurisdictions in financial flows going through the Middle East region.

Other resource-endowed post-Soviet countries such as Kazakhstan show similar patterns of roundtripping investment flows. A study of inward FDI by Dyker (2015, 121) reveals that since 2005 onethird of Kazakhstan’s inward FDI originates in the Netherlands. The author suggests that many Kazakh oil and gas companies, both private and state-owned, round-trip their investments through the Netherlands. A study of round-tripping by