rafmacalaba/data-use-mentions-extended huggingface dataset:
- Claessens, Stijn, and Neeltje Van Horen, N., 2009, ―Being a Foreigner among Domestic Banks: Asset or Liability?‖ Munich Personal RePEc Archive Paper No. 13467, February.

- Clarke, George R. G. 2009. "Beyond Tariffs and Quotas: Why Do African Manufacturers Not Export More?" _Emerging Markets Finance and Trade_ 45(2):44–64.

- Clarke, George R. G. 2011. ―"Are Managers' Perceptions About Constraints Reliable? Evidence From a Natural Experiment in South Africa." _Journal of Globalization and Development_ 2(1):1–28.

- Correa, Paulo, and Mariana Iootty. 2009. "The Impact of the Global Economic Crisis on the Corporate Sector in Europe and Central Asia: Evidence from a Firm-Level Survey." Enterprise Note 9. World Bank, Washington DC.

- Correa, Paulo, and Mariana Iootty. 2010. ―Will the Crisis Affect the Economic Recovery in Eastern European Countries? Evidence from Firm Level Data.‖ World Bank Policy Research working Paper number 5278, World Bank, Washignton DC.

- Corsetti, Giancarlo, Paolo Pesenti, and Nouriel Roubini, 1999. ―What Caused the Asian Currency and Financial Crisis?‖ _Japan and the World Economy,_ 11(3): 305-373.

- Cull, Robert and Maria Soledad Martinez Peria, 2008. ―Crises as Catalysts for Foreign Bank Activity in Emerging Markets.‖ In Justin Robertson, (ed.), _Power and Politics After Financial Crisis: Rethinking Foreign Opportunism in Emerging Markets_ , New York: Palgrave Macmillan, pp 52-81.

- Cull, Robert and Maria Soledad Martinez Peria, forthcoming. ―Foreign Bank Participation in Developing Countries: What Do We Know About the Drivers and Consequences of this Phenomenon?‖ In Thorsten Beck, Stijn Claessens, and Sergio Schmukler (eds.), _Financial Globalization_ .

- Dages, Gerard, Linda Goldberg, and Daniel Kinney. 2000. "Foreign and Domestic Bank Participation in Emerging
considerable variation in education levels, with 49 percent having completed no more than primary education, 43 percent having done some high school education, and only 8 percent with post-high school education. Many owners were reluctant to provide full financial information for several reasons. First, was fear of crime, with 56 percent viewing their neighborhood as unsafe or very unsafe and 10 percent being robbed in the last six months. Indeed, our enumerators were robbed several times. A second reason may be partial informality: 64 percent were registered for taxes, but those registered for taxes were less likely to report sales data. Finally, a third reason is that few owners keep financial records, with only 29 percent saying they record quantities purchased, and only 38 percent saying they record amounts sold. As a consequence, we are missing baseline household income data and profits and sales data for about half the firms in the sample. Of those who do report, mean (median) per-capita monthly household income is US$164 9
patent owners to license their technology in a non-discriminatory way to a variety of interested parties. The pricing mechanisms of ULR contracts are complex and described by Malackowski 2010. The contracts provide potential buyers with a host of important purchasing information relating to the technology offered, the initial target price, and the quantity of contract units offered. Buyers of ULRs must report consumption behavior to IPXI, which acts as the central monitoring and enforcement agency for the marketplace. The administrative responsibilities of IPXI, and the exchange platform facilitating the sale of patent rights commoditized through the ULR contract, reduce inefficiencies in bilateral technology transfer resulting from time, financial costs, redundancy problems and uncertainty of outcomes. ULRs may become an important liquidity alternative to normal equity and thus aid the monetization of patent rights.

Firms in the developing world are in a strong position to use such an exchange platform to monetize their patent portfolios. The exchange permits them to interact with potential licensees that they may never have encountered within their own operating markets. This allows them to efficiently monetize their patents while the independent arbitration of the exchange by IPXI means firms benefit from reduced legal costs, avoid forced cross-licensing, outsourced marketing, auditing and enforcement capacities and regular audits on licensee behavior. Innovating firms in the developing world can rely on the expertise of IPXI and its affiliates and focus their energies on innovation. This distribution of labor improves patent monetization and expands the market for new technologies. While the success of IPXI’s exchange platform cannot be assessed yet because it is still in the process of being established, various exchange models are being introduced all over the world. The experience of other exchanges should serve as a learning experience for these initiatives. While online portals may be currently headquartered in developed economies, there is nothing stopping actors in the developing world from leveraging these digital platforms to their own benefit. The recent founding of the Shanghai Silicon IP Exchange (SSIPEX) in China and the TAEUS patent book project – albeit slightly different from IPXI - suggest that this model is gaining popularity
||||||||||||
|FIRST INTERSTATE|1 600|750|(455)|(200)|1,200|530|670|3.5|33.1|65.6|4.45|4.46|

Nute: Nther ei of those banks had announced a resrve Increas at the time this table was completed, though they did subsequently.

Several of the banks stated that their developing country reserves were 25 peri*nt of developing country exposure, but this was accomplished by adding back the "Allocated Transfer Risk" to reserves. Our table does not aod back this rioserve and thus the ratios are slightly lower.

Bank Aerica Indicated that It. reserve was for 25 percent of Its S10 billion developing country **exposure,** but that ratio Is achieved only after adding back about **5600** million of "Allocated Transfer Risk" reserves and prior charg-oftfs of developing country loans.

The non-performing loan totals are for year-end 1986 and thus do not include tilie Brazilian loans placed on nonaccrual status In the first quarter. The adjusted equity to assets ratios assume that the holding companies pay the sam dividends In 1967 as In 1986 and that asset totals at yeoar-nd 1987 aro the sas as at year-end 1966.

Adjustmnts have been made In the data for Chemical to reflect the acquisition of Texas Comerce In May 1967.

Source: International Bank Credit Analysis Group (ISCA), London.
Tertiary Primary or less Secondary Tertiary Primary or less Secondary Tertiary Primary or less Secondary Tertiary Primary or less Secondary Tertiary Primary or less Secondary Tertiary Primary or less Secondary Tertiary Primary or less Secondary Tertiary Primary or less Secondary Tertiary Primary or less Secondary Tertiary<br><!-- End of picture text --> _Source:_ Estimates based on multiple labor force and household surveys (see annex table A1). _Note:_ The sample includes 35 countries with information on all dimensions and education levels. The figure shows JQMs by industry, disaggregated by education level, for the wage employed only.

There is substantial variation in job quality within each education group across industry sectors (see figure 6). As expected, low-productivity sectors, such as agriculture, construction, and commerce, exhibit relatively lower job quality among those with tertiary education relative to the results in high-productivity sectors, such as mining, utilities, and financial and business services. The public administration JQM scores are highest among workers with tertiary education as well as among other education groups. Among the JQM dimensions, income typically exhibits the highest score across all industries and education groups (except for public administration, in which stability has the highest score). The JQM dimensions can vary widely among low-skill sectors, such as agriculture and commerce. For example, income and working conditions dominate the JQM in agriculture, while income and stability are the strongest dimensions in commerce.

Regarding gender disparities within industries, the results show significant differences in three sectors: construction, transport and communications, and other services (figure 7). In construction and in transport and communications, women have an average JQM that is 27 percent and 21 percent higher than the average JQM among men, respectively. On average, only 1 percent to 2 percent of women wage 20
that Denmark is more effective in equalizing opportunities than the United States. These kinds of findings can presumably be expanded in future work.

The book makes its most important contributions on its central terrain of measurement. Even if no researcher disputes that studying different concepts of inequality clearly requires reliable data on inequality, the measurement of inequality and socio-economic mobility is inherently challenging – so much so that the ideal data is rarely available, which makes it hard to piece together reliable trends and patterns in inequality and mobility across time, space, and groups. MDMIW documents impressive improvements in the measurement of income inequality, wealth inequality (which is even harder to measure) and socio-economic mobility that make creative use of new (and big) data sources. Even so, it is clear that tracking changes over time remains an enormous challenge, especially when trying to discern trends across the full spectrum of country experience. In the World Bank’s most recent Poverty and Shared Prosperity Report (World Bank 2022), for example, data across two time periods on ‘shared prosperity’ – the rate of growth of the bottom 40% of a country’s income distribution – is only available for a total of 91 economies,<sup>6</sup> and of these, only four are low-income and 21 are lower-middle-income; put most starkly, though approximately 650 million people live in the world’s poorest economies, there is change-in-inequality data (itself of variable quality) on only 13 million of them (see World Bank 2020: 64-65). In short, despite ‘promoting shared prosperity’ being one of the World Bank’s “twin goals” (the other being the eradication of extreme poverty), at the global level progress has been slow in terms of collecting and curating widespread data on changes in inequality (and for the moment is likely to remain so, since at least two datasets, separated by a time span of 5-10 years, are required to determine any such change). In this sense,
(4) are also consistent with Hur, Raj, and Riyanto’s (2006) study, which examines both sector level external finance dependence and asset tangibility.

The summary statistics in Table 3 (lower section) shows that sector-level dependencies and private credit to GDP ratios between the MENA and non-MENA country groups are similar using either the BACI or the EDD data. Non-MENA export sectors are more dependent on external finance and have lower shares of tangible assets compared with MENA export sectors. The private credit to GDP ratio is also higher in non-MENA countries, highlighting their higher levels of financial sector development in those countries.

If MENA countries were to have similar levels of financial sector development as the rest of the world, we would expect MENA’s exports to reflect greater specialization in sectors more dependent on external finance and more intangible assets, a point worth noting since these sectors tend to have higher value-added.

Next, we examine results of the regression incorporating both country-level financial sector development and governance indicators. Table 4 presents results when financial sector development is proxied by the private credit to GDP ratio, and various governance proxies. The dependent variable is the share of exports by sector. Comparative advantages from a sector’s external finance dependence are naturally best linked with financial sector development. Asset tangibility is related to liquidity, contracts, and ownership, and more related to legal and governance factors. This specification is most similar to Hur, Raj, and Riyanto’s study (HRR, 2006).

16
Overall, the analysis highlighted the critical need for additional information on national health surveys. A systematic review of the data available in the current national health surveys in relation to the specific components of the three clusters of underlying causes of malnutrition considered as important by the nutritional scientific community reveals that these surveys contain information on only a small fraction of the ideal measures of food security, child care and environment and health. The collection of information on these additional variables currently missing from these surveys will enable a more robust understanding of the extent to which children have access to adequate care or adequate food security or environment and health. Panel data of young children between the ages of 6 and 18 months would also further our understanding of the relative contribution of the various components of the three pillars, and how access to different components of the three pillars at different ages of a child affects nutritional outcomes. In the sample of countries covered in this report it is found that the most complete information is collected on the components of environment and health, while there is much less robust information collected on the components of child care and food security. As pointed out by Barrett (2010) in his article on measuring food security, recognition that **“measurement drives diagnosis and response”** is critical for setting a renewed and higher standard in the effort to reduce child malnutrition worldwide.

Using all the information available, albeit incomplete, the analysis revealed that progress towards improved access to adequate food security and to adequate environment and health has been quite limited. It appears that access to adequate environment and health remains the greatest challenge relative to the other two pillars of food security and care. Access to improved sanitation both in the household and in the community as a whole were the lowest of all the other components of environment and health. In the countries covered in this report access to adequate environment and health in general is not surpassing 10% of the population of children. Access to adequate care has improved in some countries by more than 10
Policy Research Working Paper 11066

# **Abstract**

Fiscal rules have been shown to support fiscal discipline by improving government budget balances and restraining the growth of debt. However, questions remain about what enhances their effectiveness and how certain conditions help to build the credibility needed for their survival and success. Using data from 108 countries between 1984 and 2012, this paper studies the dynamic effects of fiscal rule adoption. It shows that although fiscal rules generally improve the primary balance, their effects depend on the time horizon under consideration and the context of adoption. In advanced economies and countries with strong political institutions, the effects strengthen over time. Conversely, in emerging markets and developing economies—especially those with weaker institutions—their impact tends to fade as time passes. The findings highlight the critical role of economic conditions and consensus building at the time of adoption. Specifically, fiscal rules introduced in times of economic hardship or under highly concentrated political power are often less effective in the medium term.

This paper is a product of the Prospects Group, Development Economics. 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://www.worldbank.org/prwp. The authors may be contacted at antonio.fatas.@insead.edu; bgootjes@worldbank.org; jmawejje@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 its affiliated organizations, or those
7 primary cooking fuel. By contrast, there is a handful of publications examining exclusive users of LPG. Mani et al. (2020) used panel data to examine shifting household fuel use patterns for cooking three years apart in 2015 and 2018. Of the exclusive users of LPG in 2015, one-third had ceased to be exclusive users by 2018, with 10 percent having become minority users. More encouragingly, 46 percent of primary users and 23 percent of minority users in 2015 had become exclusive users by 2018 and the total number of exclusive users had doubled during the intervening years. Thoday et al. (2018) examined the impact of Indonesia’s kerosene-to-LPG conversion subsidy program on abandonment of wood use. Williams et al. (2000) used stove monitors to see if removing all financial barriers to regular use of LPG would see households cook exclusively with LPG in Puno, Peru, and found that fewer than half of the participating households in the study seemed to have done so. Asante et al. (2018) carried out the first systematic evaluation of the Rural LPG Promotion Program in Ghana and did not find exclusive users even in the initial stage of evaluation. After 18 months, only 8 percent of the study participants were still using LPG. In terms of national statistics being made available, Peru’s Instituto Nacional de Estadística e Informática (INEI, National Institute of Statistics and Informatics) published a breakdown of exclusive and nonexclusive users of LPG, natural gas, and electricity by the poverty status every year between 2007 and 2017 (INEI 2018).

This study adds to this limited literature by focusing on LPG as a cooking fuel and abandonment of polluting fuels following adoption of LPG. The study uses national household expenditure surveys in Sub-Saharan Africa to gain a better understanding of patterns of household energy use for cooking with a view to refining government support to household use of LPG. In contrast to the Multiple Indicator Cluster Surveys (Kojima 2021c) or Demographic and Health Surveys,<sup>6</sup>
Thus, our key covariate is transformed into deaths per thousand population. We then calculated, across countries and years, the tertiles of conflict (low, medium, and high conflict as compared to none).<sup>14</sup> Tertiles are preferred to continuous measures of conflict, since outliers in continuous measures can be problematic. Previous studies that combine DHS data with conflict-intensity data have also looked at tertiles (Kelly, 2017; Kelly, Colantuoni, Robinson, & Decker, 2018, 2019). However, the population normalization is a new approach undertaken in this paper in order to account for the widely varying populations across countries and different locations within them.

Our main specification uses this contemporaneous<sup>15</sup> tertiles of conflict (compared to none) model. As sensitivity analyses, we also estimate a number of other models. One is a tertiles of conflict with the contemporaneous conflict and four years of lagged tertiles. The different demographic, economic, and social channels for the impact of conflict on child marriage may act with some lag. For example, the economic destruction wreaked by conflict may impact local economies for a number of years after conflict subsides. There may also be rebound patterns as conflict subsides. As a further sensitivity analysis in terms of tertiles, we also estimate a model with contemporaneous tertiles of conflict (compared to none) where the tertiles are countryspecific rather than global. Conflict intensity may be experienced relatively subjectively within a country and the intensity of conflict varies substantially across countries. In an additional sensitivity analysis, we estimate a model with non-normalized contemporaneous tertiles of conflict, that is, we do not divide by the population. The absolute (rather than relative) number of fatalities may be more salient.

Lastly, we estimate a model that measures the number of years with conflict out of the contemporaneous year and the preceding four years,<sup>16</sup> similar to our lagged tertiles model. The years of conflict covariate is categorized into none
‐1.5 ‐1 ‐0.5 0 0.5 1 1.5<br>3 3.5 4 4.5 5 5.5 6<br>Log‐difference of Economic Policy Uncertainty (EPU)<br>Log of Economic Policy Uncertainty (EPU) index index<br>0.4 0.4<br>0.3 y = ‐0.0729x + 0.3948 0.3 y = ‐0.0208x + 0.058<br>R2 = 0.0876 R2 = 0.0044<br>0.2 0.2<br>0.1 0.1<br>0<br>0<br>‐0.1<br>‐0.1<br>‐0.2<br>‐0.2<br>‐0.3<br>‐0.3<br>‐0.4<br>‐0.4<br>‐0.5<br>‐0.5 ‐1.5 ‐1 ‐0.5 0 0.5 1 1.5<br>3 3.5 4 4.5 5 5.5 6 Log‐difference of Economic Policy Uncertainty (EPU)<br>Log of Economic Policy Uncertainty (EPU) index index<br>Source: International Monetary Fund World Economic Outlook, www.PolicyUncertainty.com (Baker et al. 2016), and<br>authors’ calculations.<br>)‐difference<br>g<br>(log‐difference) (lo<br>Goods and services import volume Goods and services import volume<br>)‐difference<br>g<br>(loort volume<br>p<br>Goods im<br>Goods import volume (log‐difference)<br><!-- End of picture text --> The sources used for
the second survey question applied to measure employment (During the past week, did you perform or help carry out any work, with relatives or individuals, without pay? (Except household work)”), a discrepancy could also be noted among those who initially responded no, but later reported engaging in economic activities without pay such as helping their partners perform agriculture related activities (watering, collecting and cleaning the production), performing volunteer work in their communities, or engaging in production activities related to sustaining the home (such as collection of firewood and livestock/poultry rearing for own consumption).

In contrast, men more consistently and unequivocally responded ‘yes’ to the household survey question on economic activity with payment in cash or in kind despite largely working in agricultural selfemployment. In fact, the only male interviewee to clearly respond ‘no’ was a 72-year old man, who stopped working because of age.

15 Q1: "During the past week, did you dedicate an hour or more to any work or activity with payment in cash or in kind, or did you get any income? (Except housework)"; Q 2: “During the past week, did you perform or help carry out any work, with relatives or individuals, without pay? (Except housework)”.

13
Basic Indicator or the Standardized Approach. The inclusion of an explicit operational-risk, capital charge should not in theory imply a significant increase in required supervisory resources, as supervisors should be assessing operational risk anyway. However, as the BCP compliance data above makes clear in practice

> 35 There has been much detailed work on the identification, measurement and management of particular aspects of operational risk that may then feed into the AMA approach.  For example the World Bank has been working on E-Finance and associated operational risks including security risks – see Glaessner et al (2002) for example.

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