rafmacalaba/data-use-mentions-extended huggingface dataset:
still relevant for other policy purposes though, as further explained in the next subsection.

# **B. Measurement approaches and their suitability for skills policy**

This section describes the four approaches introduced above, looking into what they measure, the challenges of each of them during data collection or the application of the methodology, especially in developing countries, and how each of them contributes to informing skills policy, which is the reason for developing this paper. It also presents international examples of how they have been applied, with more details for the task approach since it is found to be the most suitable for informing skills policy.

## The output approach

The **output approach** estimates the number of workers employed in firms producing environmentally friendly goods and services. These firms are likely to operate in the environmental goods and services sectors (EGSS). The OECD and Eurostat have laid out the foundation for data collection and analysis of the EGSS.<sup>12</sup> Identifying green jobs or occupations through this approach could be quite straightforward: when the firm produces only green outputs in the EGSS, all employees are considered to be performing

> 9 What the ILO (2021) understands as ‘Basic skills necessary for adapting oneself to related environmental regulation and requirements to curb climate change.'

> 10 For this paper, from section 3 onwards, green jobs will be those with green tasks.

> 11 Greening of the economy means the production of greener outputs (products and services) and the use of greener technologies.

12 See OECD and Eurostat (1999), and Eurostat (2009). The OECD and Eurostat have been pioneers and have developed a handbook to determine environmentally friendly goods and services. The handbook has guided the efforts of other institutions and the development of survey instruments like the Green Goods and Services Survey of the BLS.

7
# **3.2 The Construction of a Core-Periphery Typology**

This section describes the construction of a typology that we use to interpret changes in nighttime light emissions, so that we may estimate changes in economic activity within and across urban agglomerations. Our objective is to use a methodology that is easily interpretable and able to delineate urban agglomerations and their respective peripheries.

A traditional core-periphery model used by economists (e.g., Krugman (1991)) assumes a monocentric urban core and a surrounding periphery. However, urban agglomerations are often polycentric (e.g., Kloosterman and Musterd (2001)) with a given agglomeration able to benefit from the sizes of nearby agglomerations (e.g., Burger et al. (2015)). Further, the use of existing district boundaries to delineate urban areas suffers from two additional problems. First, as Fotheringham and Wong (1991) have shown, the modifiable areal unit problem makes statistical analysis of areal data dependent on the particular boundaries used. Second, urban boundaries are not consistent with administrative boundaries.

To our knowledge there is no standard method that is used to construct polycentric agglomerations. We employ the following two steps that combine the GHSL data and a clustering methodology to delineate urban agglomerations that are polycentric. First, starting with the individual raster pixels identified as being high-density (i.e., urban) by the GHSL for 2000, we construct a distance matrix, where the distance is computed using the cosine formula (to account for the Earth’s curvature). While the GHSL data is available every 5 years, we use the same typology for the entire 2000-2019 period, so that our results may be more easily interpreted.

Second, we employ hierarchical clustering methodology (Friedman, Hastie, and Tibshirani (2001)) to group the grid cells into urban agglomerations. The single linkage method we employ involves starting with every grid cell being marked as being in its own cluster. It then proceeds sequentially to combine clusters and stops
in 2003 (Table 2.2). The level of attained education of the work force is rapidly increasing (Figure 2.2). The male and female workers that completed lower secondary education increased by 62.2 and 83.6 percent, respectively, during 1995-2003. The workers that had completed upper secondary education expanded by 118.5 and 75.3 percent for male and female workers, respectively, although the level is still very low. Only 2.6 and 3.1 percent male and female workers have completed secondary school.

**<u>Figure 2.2:  Education Attainment of Rural Labor Force</u>**

<!-- Start of picture text --> 60.0<br>1995 Male 1995 Female<br>50.0<br>2003 Male 2003 Female<br>40.0<br>30.0<br>20.0<br>10.0<br>0.0<br>No Complete Eduation Primary Complete Lower Sec. Complete Upper Sec. Complete Higher Education Technical<br>Source: Calculations based on ENE surveys.<br><!-- End of picture text --> 8
group of LDCs may reveal that, despite our best efforts, measurement error is partly driving the negative correlation between private and public saving rates. This is a likely possibility given that private saving was derived as the difference between national and public saving - -any error in public saving would translate mechanically in an error of the opposite sign in private saving. If we assume the estimated public saving coefficient for the OECD sample as mostly free from measurement error, then we find a larger effect of public saving on national saving than reported above. A permanent increase in public saving of 4% of GNDI would lead to an increase in national saving of 3.6% of GNDI in the short run and 2.6% of GNDI in the long run. Interestingly, for both the industrial and developing country subsamples, Wald tests allow clear rejection of full long-run Ricardian offsetting, with p- values below 1 percent.

# 4.4 Alternative definitions of the public sector

Table 6 presents full-sample system-GMM estimation results using the four . alternative definitions of the public sector introduced earlier. Up to now we have focused on the public sector definition that includes the general government and, when available, public enterprises; furthermore, the related saving and income data have been adjusted to account for the inflationary erosion of privately-held public liabilities. The results of this core regression, discussed above, are reproduced in Table 6, column 4, under the heading of “PA.” The other columns make use instead of the three alternative public- (and private-) sector saving measures introduced earlier corresponding to, respectively, unadjusted central
VG group but were not beneficiaries. These three strata, i.e., GL, RF, and ENB, within which the group investment, training, and household cash transfer experiments were conducted, are the focus of this paper.

Within this sample, we conducted a number of surveys.<sup>11</sup> First, we conducted a comprehensive three-wave household survey. The survey included data on consumption, income and revenue, savings and borrowing, revenue, food security, productive assets, livestock, housing quality, food security, health, and education. We also tracked the progress of the groups, using a detailed enterprise survey. This not only collected a standard battery of business practices, as well as asset and profit/loss data for the groups, but it attempted to conduct the mapping of group activities back to the individual level – tracking contributions of time, inputs, and money to the group from each member as well as the rate of profit-taking by members from the group enterprise. For the enterprise survey we have an additional ‘rapid resurvey,’ conducted roughly six months after disbursement of TASAF funds to the Early treatment group, intended to capture outcomes immediately after disbursement.<sup>12</sup> As this study began in 2008 with data collection ending in 2012, it pre-dated the standard use of trial registration and pre-analysis plans. Thus, we use two seminal papers in the literature – Banerjee et al. (2015) and Haushofer and Shapiro (2016) – to guide our grouping and selection of primary and secondary outcomes. Our primary outcomes include consumption (food, non-food, and total, measured as real USD monthly per capita adult equivalents – adjusted for differences in price levels across districts and over time), housing quality, livestock, and productive assets. For

> 11 All survey instruments and enumerator manuals for the survey can be found at https://sites.google.com/site/decrgberkozler/datasets.

> 12 An important issue
spillovers from one country’s tax system to real investment elsewhere.<sup>7</sup> Against that backdrop, the core purpose of this paper is to make further progress on what thus remains, somewhat surprisingly, one of the least-understood aspects of international tax arrangements: the impact on real investment. The results then enable us to address a key but somewhat neglected aspect of the prospective impact of the global minimum tax: its effects on real investment, both by country and in aggregate.

The fundamental problems associated with the use of FDI data are overcome here by using a newly-constructed dataset on Foreign Affiliate Investment (FAI). These data explicitly record the acquisition of tangible assets (new and old) by foreign affiliates in each host country,<sup>8</sup> and see through conduit flows to identify the country of the ultimate parent. Consequently, neither of the main shortcomings of FDI data applies. Estimation can explore the effects on host-parent bilateral FAI flows of tax systems in the host country, parent country and other potential host countries. Our dataset covers inward investment from 187 parent countries into affiliates in 32 (advanced) host countries from 2003-2016, along with detail on a range of activity variables. The rich information in this dataset helps disentangle the effect of taxes from unobserved, confounding factors on inward foreign investment. The limitation of these data to tangible assets is a significant one, given the increasing importance of intangibles in multinational activity; but there can be little doubt as to the importance and salience of tangible investment for the formation of tax and other policies.

Armed with these data, the conceptual challenge is then to elucidate the precise channels by which taxation might affect inward FAI. Candidates explored in previous work, sometimes somewhat haphazardly, include statutory tax rates, average effective tax rates (along the lines of Devereux and Griffith (2003)) and marginal effective tax rates of the kind developed in closed economy contexts (classically, as in King and Fullerton (1984))<
FACTIVA for each country and each month. A measure of normalized article counts is then constructed by taking the ratio between the number of articles mentioning “street protests” and the total number of articles for each country-month pair multiplied by 100. Formally, for country _i_ in month _t_ the intensity of media chatter around protests is as follows: The news-based protest data provide us with a balanced panel for 207 countries from January 1, 2000 to December 19, 2019 (see Panel B of Appendix Table A1 for the list of countries). The coverage is more comprehensive than for ACLED and allows us to exploit time and space variation. Panel B of Appendix Figure A1 presents the histogram of the entire distribution of newsbased protests. In 33.4 percent of country-month pairs (16,568 of 49,678), there is zero news about protest (Appendix Table A2 for summary statistics). The distribution is also skewed toward zero, which supports the use of the Zero-Inflated Poisson estimator.

The evolution of the measure is presented in Figure 2 in monthly frequency (Panel A). We also illustrate the evolution of the measure for countries in the Middle East and North Africa (Panel B). Both panels show a clear uptick in the chatter about protests around the Arab Spring in 2011 and the second wave of protests that started in 2019. The uptick in Panel A around 2003 reflects global protests against the war in Iraq.

4
_15_ 44.

44. Many developing countries have active solar water heating industries. Solar water heaters for residential and small commercial installations are manufactured locally in Israel and Jordan where as many as 1 in 5 homes use solar water heating. The SWH industries in Morocco, Tunisia, Egypt, Senegal, and Zimbabwe fabricate as well as import some collector components. Both India and Nepal have sound SWH industries supplying residential and commercial systems. Australia, Israel, France, USA, and Japan are major exporters of SWH technology and large dorr.estic markets exist in both Australia and the USA.

<!-- Start of picture text --> Industrial Sector SWH Application<br>IRR: Kenya Brewery Fuel Oil Retrofit<br>SWYH Internal Rate of Return<br>40%<br>30%<br>20%-<br>1 0 % o%<br>0% I 10 15 20 I ._ * 25 30 * 35 . 40 _ 45<br>Fuel Oil Economic Cost ($/bbl)<br>Source: See Annex<br><!-- End of picture text --> Figure 6 Solar Hot Water Fuel Oil Boiler Retrofit 45. Industrial applications of solar water heating in developing countries are limited to a few large pilot plants in the Middle-East and a few other countries. The brief analysis below, based on an ESMAP study of the potential for solar water heating in Kenya, illustrates that low oil prices can severely curtail the economic advantages of industrial SWH.

46. An ESMAP SWH study for Kenya, originally assessed at 1985 fuel prices, was recently reevaluated at borde.. prices of August, 1986.16/ The border price of fuel oil fell from US$ 16.75 to US$ 11.25/bbl over this period. Because all of the industrial SWH installations originally

> 16/ Joint UNDP/World Bank ESMAP Solar Water Heating Study, Kenya, December 1986. Assumptions and results of **this
Policy Research Working Paper 7937

# **Abstract**

This paper uses loan-level data from 124 countries over 1995–2015 to examine the transmission of monetary policy through the cross-border syndicated loan market. The results show that the expansion of monetary policy increases cross-border credit supply especially to weaker firms. However, greater foreign bank presence in the borrower country appears to reduce the potentially destabilizing impact of lower policy interest rates on cross-border lending, as it attenuates increases in loan volume and maturity while magnifying increases in collateralization and covenant use. The mitigating effect of foreign banking presence in the borrowing country on the transmission of monetary policy is robust to controlling for borrower-country economic and financial development, and a range of borrower and lender country policies and institutions, including the strength of bank regulation and supervision, exchange rate flexibility, and restrictions on capital flows. The findings qualify the characterization of international banks as sources of credit instability, and suggest that foreign bank entry can improve the stability of cross-border credit in the face of international monetary policy shocks.

This paper is a product of the Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at Ademirguckunt@ worldbank.org; balint.horvath@bristol.ac.uk; H.P.Huizinga@uvt.nl.

_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
aggregate decomposition would remain valid as long as overlapping support and ignorability assumptions are tenable.

In exploring the existence and extent of the gender gap in a multivariate framework, the validity of findings largely depend on the plausibility of ignorability and zero conditional mean assumptions, i.e. the extent to which the identification strategy addresses possible unobservable household-/plot-level heterogeneity that jointly determines plot agricultural productivity and observable covariates, including whether a plot is managed by a female. While the most rigorous studies on the gender gap recognize the need for an instrumental variable strategy to deal with potentially endogenous observables, recovering instrumental variables that predict endogenous covariates without directly influencing the outcome is often not possible. A subset of the studies that are reviewed in Section 2 and that feature plot-level analyses have attempted to address the potential bias by controlling for direct measures of plot soil quality and household-crop fixed effects. With panel data, time fixed effects have also been included in the specifications.

Furthermore, to deal with the possibility that the male and female plots might be physically systematically different from each other along the dimensions that are finer than the observable variations in soil physical infrastructure and quality, an alternative identification strategy has been to rely on a spatial fixed effects estimator that allows for local neighborhood effect in unobserved land quality that could be correlated with the gender of plot manager and the other regressors. The spatial fixed effects are differenced out by modeling the difference between the plot-level outcome and the average of the outcome across plots from other households within a critical distance as a function of a vector of plot-/household-level variables that are differenced from their matched plot-/household-level neighborhood averages (see Goldstein and Udry (2008) for an example of this).

We lack, in our case, plot-level measures of soil quality, and the nature of farm organization as captured in the IHS3 data does not allow us to feature household fixed effects as a central piece of our empirical strategy. The average number of plots cultivated by Malawian farming households is 1.76,
3

# INTRODUCTION

The central purpose of this paper is to present a systematic review of the wealth of sociological information pertaining to housing in Russia and the development of a housing market there that has been collected by means of surveys over the last several years and that is largely unknown outside of Russia. The author has been personally involved in much of the research whose results are presented here. A particularly important contribution to research in this area was made by the World Bank's Enterprise Housing Divestiture Project, which was managed by Dennis Whittle, Mari Kuraishi and Lev Freinkman, to whom particular thanks must go for stimulating discussions and organizational support.' The analysis presented in the paper focuses on the process of housing privatization and the development of the housing market in Russia through 1996. This new market, still in the process of formation, has emerged from the privatization of the existing housing stock, from sales of newly constructed apartments 2 and from the reduction of housing subsidies. The findings presented here are based mainly on the results of household surveys conducted in 1992-1996 in Russian cities, and generally reflect developments in different types of urban settlements throughout Russia.<sup>3</sup> The survey data also allow for analysis of the demand for housing and household mobility in Russia.

A brief overview of the problems of housing sector reform in post-Soviet Russia will serve as the backdrop to the detailed examination of the household survey results that constitutes the bulk of this analysis.

In the early 1990s, the Govemnment of Russia was preoccupied with the tasks associated with macroeconomic stabilization and consequently, until recently, housing issues were not a real policy priority. To the obvious extent that housing is a basic need of the entire population, the political sensitivity of reform of the housing sector has been tremendous and has resulted in widespread resistance to the implementation of housing reforms. Budget subsidies to the housing sector still consitute almost _25%_ of local fiscal expenditure, or three-quarters of the cost of the provision of the housing and associated services. Regional
Note: The sign + denotes that the difference between the average tariff faced by men and by women is significant (based on a t-test).

# **5.2.4 Formal vs informal workers**

The household surveys reporting the principal economic activity during the reference week also identified the type of enterprise individuals were employed in. From this information, each enterprise was classified as belonging either to the formal or to the informal sector. The survey's definition of the informal sector is an enterprise employing less than 10 workers. Unfortunately, only 54% of respondents reported the number of employees in the enterprise in which they worked. Nonetheless, workers in informal sector enterprises face an average 9.8% tariff, which is significantly higher than the 7.2% for enterprises classified as in the formal sector.

# **5.3 Globalization did not narrow the bias against the poor**

While global tariffs fell from 1996 to 2012, the tariffs facing the poor, workers in rural areas and women remained higher than those facing the rich, workers in urban areas and men, respectively (Table 5). In fact, the reduction in tariffs was slower for workers in rural areas and for women, while the tariff gap between the highest and lowest income decile remained unchanged over the 16-year period.

Table 5: Average Tariff Reduction between 1996 and 2012 (change in percentage points)

|Decile 1(lowest 10%)|2.6|
|---|---|
|Decile 10(highest 10%)|2.5|
|Rural|2.4|
|Urban|3.3|
|Women|2.5|
|Men|2.7|

13
. Panel A shows that on average, 31% of eligibles in treated villages are registered ELA club members. Panel B then reports statistics from the endline survey. There is widespread knowledge of ELA clubs: 89% of girls in treated villages have heard of them, as have 27% of girls in control villages. Participation rates are more than double membership rates: 71% of girls in treated villages have _ever_ participated in an ELA club meeting or activity. This is only 4% of girls in control villages, so there are very limited spillovers in participation to control locations. In short, there is high demand among young women for access to ELA clubs.

Conditional on ever participating: (i) 82% of young women have participated in life skills (77%

> 28The key exam school stages are as follows. The Basic Education Certificate Examination (BECE), taken at age 15, is required for admission into senior secondary school. The West African Senior School Certificate Examinations (WASSCE), taken at age 18, is required for university/college admissions. The reported magnitude of time allocations across the age distribution are plausible: the youngest girls report spending around 60 hrs/wk on all forms of learning except ELA (formal schooling, other vocational training, church-based schools). Work hours rise to just over 35 hrs/wk for older women in our sample. At each age, respondents report on average spending at least 40 hrs/wk engaged in household chores.

17