rafmacalaba/data-use-mentions-extended huggingface dataset:
to compile macroeconomic statistics and social data reporting and estimation practices. This dimension measures the quality aspect of the data system. Under the assumption that international guidelines provide the benchmark of ideal data systems, adherence to such standards may imply that the quality of data systems meets well-established standards. Countries are evaluated against a set of criteria such as use of an updated national accounts base year, use of the latest balance of payments manual, the external debt reporting status, updated consumer price index, updated industrial production index, updated import/export prices, accounting basis for reporting government financial data, vaccine reporting to WHO (discrepancy between WHO and government estimates), subscription to IMF’s Special Data Dissemination Standard, and enrollment data reporting to the United Nations Educational, Scientific, and Cultural Organization (UNESCO).<sup>6</sup> Each criterion has equal weight.

The periodicity and timeliness dimension measures the availability and periodicity of key socioeconomic indicators, of which nine are Millennium Development Goals (MDG) indicators. This dimension attempts to measure the extent to which data are made accessible to users through transformation of source data into timely statistical outputs. The periodicity of the main indicators considered, each receiving equal weight, includes: (i) Income poverty indicator, (ii) Child malnutrition indicator, (iii) Child mortality indicator, (iv) Immunization indicator, (v) HIV/AIDS indicator, (vi) Maternal health indicator, (vii) Gender equality in education indicator, (viii) Primary completion indicator, (ix) Access to water indicator, (x) GDP growth indicator.

Several studies have used the SCI to evaluate the quality of data systems and investigate its relationship with other macroeconomic variables (Devarajan, 2013; Kubota and Zeufack, 2020). Tables 3 and 4 provide summary statistics for the SCI indicator for both the panel and cross-section data sets, respectively. Tables 5 and 6 present the correlation between the SCI and other variables for both cross-sectional and panel data,

> 6
World Bank’ s  cash  transfers  program  being  implemented  by   UNICEF,  which covers approximately one-quarter of the total population and is aimed at  relatively  poorer  households, demonstrates  the  vast   majority  of  households  can  be  reached  via  phone   (see   (accessed September 2018): http://www.worldbank.org/en/news/press-release/2017/05/19/new-world- bank-support-to-address-food-

> insecurity-in-yemen-aims-to-reach-9-million-yemenis); evidence from different  WFP  surveys  of  food  aid  beneficiaries  suggests  that  the  share  of  food  aid  recipients      that can be reached via mobile phone has remained very high (see (accessed September 2018): http://documents.wfp.org/stellent/groups/internal/documents/projects/wfp278006.pdf);     and     evidence from the WFP mobile phone survey itself suggests that particularly struggling households are well represented in the sample with nearly 40 percent of the sample being displaced and approximately 41 percent receiving food assistance.

19There are only 16 districts of 333 that do not have any respondents in any of the surveys. Alternatively, the vast majority of districts are represented in any single month of the survey. For example, in the March 2019 survey, the survey reached respondents in 264 of the 333 districts in the country- nearly 80 percent of the total. It is important to note that the districts for which there are zero respondents tend to be less populated and in the east of the country. Only 9.2 percent of the country’ s 2017 population resided in the 69 districts for which there are zero respondents in the March 2019 survey; and the districts overwhelmingly came from the governorates of Hadramaut and Al Mahrah, where only 39 and 33 percent of districts in each respective governorate had at least one respondent. Importantly, neither of these governorates is the primary focus of the analysis here.

20For each survey, the 95 percent confidence interval for the average number of mobile phones owned by the household is contained in the 95 percent confidence interval prior to the conflict (based on data from the 2014 Household
- United Nations High Commissioner for Refugee (2019). Uganda country refugee response plan. The integrated response plan for refugees from South Sudan, Burundi and the Democratic Republic of Congo; January 2019-December 2020. Revised in March 2019. Retrieved from <u>https://reliefweb.int/sites/reliefweb.int/files/resources/69674.pdf</u>

- United Nations High Commissioner for Refugees (2020). Global trends: Forced displacement in 2019. 18 June 2020. Available from: https://www.unhcr.org/5ee200e37.pdf

- Verme, P., & Schuettler, K. (2021). The impact of forced displacement on host communities a review of the empirical literature in economics. _Journal of Development Economics_ , 102606.

- Verwimp, P., & Maystadt, J. F. (2015). _Forced displacement and refugees in Sub-Saharan Africa: An economic inquiry_ . The World Bank.

- Watera, W., Seremba, C., Otim, I., Ojok, D., Mukhone, B., & Hoffman, A. (2017). _Uganda's Refugee Management Approach Within the EAC Policy Framework_ . Konrad-Adenauer-Stiftung.

- Whitaker, B. E. (2002). Refugees in Western Tanzania: The distribution of burdens and benefits among local hosts. _Journal of Refugee Studies_ , _15_ (4), 339-358.

- World Bank. (2019). Informing the Refugee Policy Response in Uganda: Results from the Uganda Refugee and Host Communities 2018 Household Survey.

- World Bank Group. (2016). _Assessment of Uganda's Progressive Approach to Refugee Management_ . World Bank.

- World Health Organization. (2018). Health of refugees and migrants; Practices in addressing the health needs of refugees and migrants. WHO Africa Region.

39
# 1. Vocational Schooling in Israel

Introduction: Since the publication of Foster's now classic paper on the vocational schooling fallacy (Foster, 1966), the appropriate role to be accorded to vocational education within both the schooling and the training systems has been an issue of serious, even intense, debate. The protagonists in this debate have been defined largely along disciplinary lines: educational economists have been in the forefront of those pressing the offensive, while educational policy makers and administrators, particularly in developing countries, have continued to argue, often on the basis of perceived labor market needs, that vocational education should remain a central element in national educational policies.

Meanwhile, available evidence suggests that vocational schooling, round the world, is in retreat. Benavot (1983), on the basis of published UNESCO statistics, has pointed to a world-wide secular decline since the 1950s in the proportion of secondary school pupils attending vocational schools'l/ while a recent survey of World Bank lending for vocationallyspecific education and training has shown a clear and significant shift over the past two decades away from vocational secondary school projects towards various forms of non-formal training (Middleton, 1988). Moreover, a growing case study literature has tended to argue that, in comparison with the 1 These conclusions may need to be modified in the light of a new study near completion and based on more recent UNESCO data than those employed by Benavot. This shows, for more recent years, a tendency for the vocational school enrollment proportion to increase. See Komenan and Ziderman, forthcoming.
distressed banks to estimate the probability of receiving government assistance (versus the probability of resolution of bank distress through a private/market solution) using a multinomial logit model that adjusts for a possible selection bias using the inverse Mills ratio constructed based on the first-stage probit regression estimates for bank distress. Third, we estimate the fiscal expense on bank bailouts using the Tobit model—again adjusting for possible selection bias using the inverse Mills ratio for bank distress. To project future contingent liabilities for 2022-23, the paper combines the estimation results from the three steps with the most up-to-date data from the financial statements of banks.

- _6.1 What factors can predict bank distress that could trigger resolution action?_

We begin by estimating the probability of bank distress using bank-level data. The results are summarized in Table 3. Column 1 presents the results when the CAMEL variables are lagged by one year while Column 2 reports the results when CAMEL variables are computed as averages over the previous two years. The CAMEL control estimates indicate that greater bank capitalization decreases the likelihood of distress. The total number of banks in distress is negatively related with individual bank trouble, mechanically suggesting that once the banking system problems are addressed, on average individual banks are less likely to experience distress. The results on the profitability ratio suggests that sustained profitability over the short (one year) and medium (average over two years) term decreases distress (Table 3). The estimation results highlight the role of timely and credible supervision to mitigate the likelihood of bank distress. Other macroeconomic variables appear to correlate with individual bank distress significantly (at the 5 percent level) only when we consider bank-level determinants lagged one year (Table 3, column 1) but there appears to be a weaker association when in the model specification we include the average value of CAMEL variables over the previous two-years (Table 3, column 2) —even though they may still be relevant for capturing the overall banking systemic risk.

**Table 3: Estimation of the probability of bank entering
hopefully ease the transition to the next expansion.‘‖ This conclusion was based on the view that the degree of uncertainty about the nature of the economic environment in which monetary policy was operating had significantly risen owing to a number of structural economic changes, in particular rising productivity. Consequently, Greenspan advocated an approach to monetary policy that basically viewed the risks of intervention in potential bubbles to significantly outweigh the benefits. This view was based on an extremely optimistic assessment of the American economy and its long-term prospects driven by deep and positive structural change.

81. The Fed Chairman‘s statement that it was not possible to know a priori whether a bubble existed and it was therefore only possible to intervene ex post created the so-called ―Greenspan put‖, essentially a belief among traders that the government would always bail out traders that needed to be rescued after a bubble had burst, but not intervene to stop it from rising.<sup>56</sup> So, effectively the Fed was providing insurance against the possibility of a market crash, a situation referred to as ―meta moral hazard‖ by Miller, Weller and Zhang (2002).

82. Miller et al. cite evidence for such a meta moral hazard from: (i) a small survey of major fund managers and chief economists in London and New York carried out in early 2000 and (ii) a national opinion survey by the Securities Investor Protection Corporation (SIPC) of more than 2,000 individual investors. The former investigated the hypothesis that ―confidence in an everincreasing stock market is due to the belief that monetary policy will be used to support the market and that corrections will elicit reductions in interest rates until the market turns around‖. The result was that respondents believed that the Fed reacted more to a fall of the stock market than to its rise, and all except two believed that this type of reaction was in part responsible for the high valuations on the U.S. market.<sup>57</sup
506|23.92|6.97|35.03|77.97|
|East|12|11|0|1|0.013|13.18|5.84||93.90|
|North|1,629|1,027|328|274|3.402|24.64|6.65|36.21|78.21|
|South|5,297|4,371|580|346|6.863|15.28|7.41|35.88|80.23|
|West|4,493|3,610|486|397|5.347|14.04|4.44|34.56|76.17|
|**Panel B: By or**|**ganizational**|**form**||||||||
|Individual|14,218|13,076|895|247|9.819|8.15|5.50|30.93|65.68|
|FOP|2,647|1,254|720|673|7.669|34.18|9.79|35.17|78.56|
|Legalentity|4,185|939|1,553|1,693|17.643|49.73|15.65|37.75|79.62|

_Source:_ Own computation based on PSG records.

26
Policy Research Working Paper 5957

# **Abstract**

This paper surveys qualitative crisis monitoring data from sites in 17 developing and transition countries to describe crisis impacts and analyze the responses and sources of support used by people to cope. These crises included shocks to export sectors as a result of the global financial crisis, as well as food and fuel price volatility, in the period from 2008 to early 2011. Respondents reported the crisis had resulted in significant hardships in the form of foregone meals, education, and health care, food insecurity, asset losses, stress, and worsening crime and community cohesion. Although the export-oriented formal sector was most exposed to the global economic downturn, the crises impacts were more damaging for informal sector workers, and some of the adverse impacts will be long-lasting and possibly irreversible. There were important gender and age differences in the distribution of impacts and coping responses, some of which diverged from what has been seen in previous crisis coping responses. The more common sources of assistance were family, friends, and community-based and religious organizations; formal social protection and finance were not widely cited as sources of support in most study countries. However, as the crisis deepened, the traditional informal safety nets of the poor became depleted because of the large and long-lasting shocks that ensued, pointing to the need for better formal social protection systems for coping with future shocks.

This paper is a product of the Social Development Department. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at rheltberg@ 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
Policy Research Working Paper 8722

# **Abstract**

The High Frequency South Sudan Survey, implemented by the South Sudan National Bureau of Statistics in collaboration with the World Bank, conducted several waves of representative surveys across seven of the ten former states between 2015 and 2017. These surveys provided a long overdue update to poverty numbers in South Sudan, with the previous national poverty estimates dating as far back as 2009. The escalation and expansion of the civil conflict posed severe challenges to the planning and implementation of fieldwork. The surveys therefore capitalized on several technological and methodological innovations to establish a reliable system of data collection and obtain valid poverty estimates. Focusing on the 2016 urban-rural wave, this paper describes the design and analysis of the survey to arrive at reliable poverty estimates for South Sudan, utilizing the Rapid Consumption Methodology combined with geo-spatial data for inaccessible survey areas.

This paper is a product of the Poverty and Equity Global Practice. 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/research. The authors may be contacted at upape@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 of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
The most recent year for which data is available is 2011, which is used to arrive at the labor share of 0.51 for Bangladesh. The figure below compares the labor share of income of Bangladesh to the mean/median labor shares of lower‐middle income countries obtained from PWT 8.1 for the year 2011. The labor share of the country lies close to the mean/median of the lower‐middle income countries though somewhat lower. In the robustness exercises, I show how alternative values of � affect the results of the analysis.

- **Depreciation Rate:** ���. ��� **.** The annual depreciation rate of capital stock is sourced from the PWT 8.1. The PWT 8.1 classifies capital stock into six different categories with each category having a different rate of depreciation. A somewhat lower depreciation rate for Bangladesh is rooted in the fact that the country has larger share of capital stock in assets that depreciate slowly relative to assets that have a much higher rate of depreciation such as computers, software etc. The aggregate depreciation rate for the country is likely to inch upward as the capital mix shifts towards assets that have a higher depreciation rate. The robustness exercises discuss the sensitivity of the findings to the choice of higher depreciation rates.

- ��

- **Initial capital‐to‐output ratio:** ��. ��. The initial capital‐to‐output ratio is calculated ��

- using the capital stock and GDP data from the PWT 8.1. The most recent year for which data is available from the PWT 8.1 is 2011 which is used to calculate the specified value of capital‐to‐output ratio. The figure below compares the capital‐to‐output ratio of the country with some of its neighbors. The capital‐to‐output ratio of the country is lower compared to China driven by the fact that China has made massive investments in capital stock over the last
MFA quota is endogenous to the export flows, i.e. it was more likely to be imposed when a country-product had experienced significant export growth to the US.

> 40 Online Appendix D presents the results from a robustness check, where we estimate the impact of tariff preferences granted by the US under different schemes using the data on US tariffs at country-product level for the period 1997-2017 instead of treatment indicators. The results indicate that on average US tariff preferences do not significantly increase export growth at the countryproduct level. However, when the effect is allowed to differ for African and non-African countries, US tariff preferences significantly increase export growth for African countries. When the effect is further allowed to differ across product groups, the results show that US tariff preferences have a significant positive impact on apparel export growth as well as manufacturing export growth from African countries. We view these results as consistent with those based on our triple-differences specification. 41 We also re-estimate Eq. (1) allowing the AGOA apparel term to have a different coefficient for each African country. Online Appendix D shows cross-country heterogeneity in the impact of AGOA on apparel. The countries with the largest significant positive impacts of AGOA on apparel exports to the US are Kenya, Madagascar, Eswatini, Ethiopia, and Lesotho. In contrast, South Africa, Senegal, Nigeria, and Côte d’Ivoire exhibit a negative impact of AGOA on their apparel exports to the US.

27
registered outside of the village.

# **_2.3 Characteristics of e-households and non-e-households in Taobao Villages_**

E-commerce participation is not random. E-households and non-e-households differ in many dimensions. Table 2 shows the descriptive statistics for these two household types in the Taobao Villages. Comparing the characteristics of household heads, e-households are significantly younger than non-e-households with an average difference of about 10 years. E-household heads are better educated than those of the non-e-households. Specifically, non-e-household heads are about 12 percent more likely to have completed primary or junior high school education compared to e- household heads, but 6 percent, 10 percent, and 3 percent less likely to complete senior high school, college, and university education, respectively. E-household heads are healthier and less likely to be unable to work due to sickness. E-households are 16 percent less likely to be locally registered than non-e-households, but 13 percent more likely to come from another province. This observation confirms the finding on the village level illustrated in Table 1 that people tend to migrate to Taobao Villages to engage in e-commerce. E-household heads are 9 percent more likely to have working experience in urban areas and 31 percent more likely to have self-employed experiences than non-ehousehold heads. Among those who have urban experiences, e-household heads are 20 percent more likely to have learned about e-commerce than non-e-household heads. Measured by a constructed risk preference index,<sup>9</sup> e-household heads are significantly less risk-averse than non-e-households.

In terms of household characteristics, e-households have slightly more members than none-households and have younger age composition. Land ownership of the two household types is not significantly different, potentially because agricultural land is not essential capital for e- commerce business.

> 9 Risk preference of the household head is constructed from the answers to hypothetical survey questions that ask people to choose between receiving an amount of cash for certainty versus playing a game with uncertainty. The seven survey questions are formulated as follows: “Would you like to receive X yuan for certainty or receiving 2,000
/mark>

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