rafmacalaba/data-use-mentions-extended huggingface dataset:
they choose.<sup>8</sup> However, the consumer is responsible for higher out-of-pocket payments if the provider is out-of-network. Overseas providers are treated as out-ofnetwork, and insurance coverage abroad typically only applies to medical emergencies. There are also Point of Service (POS) plans which offer consumers the option of obtaining care out-of-network like a PPO plan, except that the in-network portion of the plan is structured exactly like an HMO, with a primary care physician controlling referrals to in-network specialists.

6 US Statute, Title 42, Section 1395Y (a4) of the original Medicare (1965) plan states that “No payment may be made under part A or part B of this sub-chapter for any expenses incurred for items or services which are not provided within the US, except for inpatient hospital services furnished outside the US under the conditions described in section 1395F.” The conditions are that the beneficiary be a US border resident, require hospitalization, and live closer to the foreign hospital than to the US hospital (see, e.g., CMS, 2005).

7 Some HMO plans offered by insurers such as Kaiser, Blue Cross of California, and Highmark are Direct Access or Open Access HMOs that do not have a gatekeeper primary care physician requirement.

8 Interestingly, while PPO premiums are higher than HMO premiums, averaging $10,217 for a PPO plan covering a family of four versus $9,504 under an HMO in 2004, more than half of employees with health insurance coverage chose the former, with only about a quarter enrolling in HMO plans (see, e.g., Kaiser Family Foundation study, 2004).

5
(finance, insurance) with manufacturing. Over 95% of the services in our employment data are local services (housing, local utilities, retail etc.), and these constitute our non‐tradable service sector.

The total value of trade – exports in particular – is relatively small compared to GDP, and notably so for some of the smaller countries in the region (Table 3). There are also large imbalances in terms of the trade levels, with the three Chinese regions and Kazakhstan having trade surpluses, and other countries having deficits (explained through the presence of large remittances and other transfers). Kyrgyzstan’s imports amount to more than 70% of its GDP.

Table 3: Exports and Imports relative to GDP (percent)

||Primary<br>exports|Manufacturing<br>exports|Primary<br>imports|Manufacturing<br>imports|
|---|---|---|---|---|
|China‐3|0|34|5|14|
|Kazakhstan|14|11|2|19|
|Kyrgyzstan|5|12|3|77|
|Pakistan|1|8|3|14|
|Tajikistan|5|7|4|48|
|Turkmenistan|17|2|0|13|
|Uzbekistan|2|9|1|13|

**_Transport:_** Our measure of bilateral trade costs between cells (including access points) is based on travel times from De Soyres et al. (2018), who calculate the travel time between various pairs of cities in Central Asia. They use the current transport infrastructure network to compute shipping times before the BRI, and enrich this with planned projects related to the BRI to compute a post‐BRI matrix of shipping times. They also compute a matrix of shipping times enhanced by additional reductions in border crossing times, resulting in three matrices covering 1,818 cities in 71 countries.
# _4.3.2 Enablers: public intent data_

“Public intent data” refer to data collected for public purposes, regardless of the collection instrument or the entity that manages the data. Traditionally, public intent data are collected by censuses and household surveys, although newer sources of such data have become available and more prominent in recent years, such as data collected through digital identification and facial recognition through public cameras. Issues measured under the dimension of public intent data include: the existence of open data laws, the interoperability of government data exchange platforms, the existence of a data classification policy and its mandatory use for government data, the existence of access to information (ATI) legislation and related exceptions, and, finally, the adoption by governments of an open licensing regime.

Country performance on the abovementioned aspects vary significantly, except on ATI legislation (figure 8), which has been adopted by 70 percent of the countries surveyed, while about half the countries include exceptions regulating ATI rights.<sup>19</sup> ATI legislation provides citizens a legal instrument to obtain public sector disclosure. Access and circulation of information held by public actors is a cornerstone for freedom of information and expression. This is one of the SDGs as it increases accountability and transparency of government action.<sup>20</sup>

**Figure 8. Percentage of countries with good regulatory practices to facilitate the use of public intent data (by country income)**

<!-- Start of picture text --> High income Upper middle income Lower middle income Low income<br>Semantic interoperability mandated for<br>government entities<br>100%<br>Adoption of open licensing regime by 80%<br>60% Existence of Open Data Law<br>governments<br>40%<br>20%<br>0%<br>Existence of exceptions to the ATI right Existence of data classification policy<br>Existence of Access to Information (ATI
We supplement these two follow-up surveys with several other data sources. We used administrative data on program take-up and activities uploaded by firms for describing adoption and compliance in Section 2. Monitors also conducted two visits with all insourcing and outsourcing firms to verify the presence of hired workers or contracted professionals, and also to collect data on these specialists and their activities (used in Section 2.4). A survey of business service providers was used to compare the characteristics of providers in the GEM project to other providers in the marketplace. Finally, in October 2019, we used independent raters to score firms on the quantity and quality of their social media presence (described in Section 5).

# **3.2 Measurement of Main Outcomes**

Appendix 4 details the construction of our main outcome measures: (i) Business Practices; and (ii) Firm Growth.<sup>8</sup> <u>Business Practices.</u> A particular focus of the follow-up surveys was detailed measurement of business practices. We measured 41 different business practices, representing both traditional activities (in finance/accounting, marketing/sales, operations/HR) and also more novel activities (in digital marketing). A concern in collecting such data through surveys, especially after skillbuilding interventions, is the possibility of experimenter demand effects whereby entrepreneurs may say they are using particular practices because they think it is the desirable answer. Our surveys took several precautions to mitigate this possibility. First, the survey was conducted by an independent survey company (Kantar TNS RMS) and not framed as measuring the impacts of the GEM project. Firms were told the purpose was to “help better understand the growth process of enterprises in priority sectors, the challenges your business faces, and your use of different market services and government programs”. Second, enumerators were trained to probe each answer and only record the firm doing the practice if they could provide specific examples or evidence. For example, when asking whether the firm conducted
Table 1 presents oil prices under various scenarios and corresponding percentage changes from the current (i.e., 2009) price level. For example, a 50% increase in oil price from the baseline in 2020 refers to a 147% increase as compared to the 2009 level.

**<u>Table 1: Oil prices and percentage changes from the current (i.e., 2009) price level</u>**

|Year|Baseline|Scenario||
|---|---|---|---|
||25%|50%|100%|
||US$/barrel(2008 price)|||
|2009|56|||
|2010|67|||
|2015|87<br>109|130|174|
|2020|93<br>116|140|186|
||% Changefrom 2009level|||
|2009|0|||
|2010|19|||
|2015|54<br>92|131|208|
|2020|65<br>106|147|230|

Source: EIA (2009) and IEA (2009) for baseline data for period 2009-2015.

# **3.1 Impacts on biofuel production and penetration in transportation fuel mix**

Table 2 presents the production of biofuels in monetary value in the baseline and the percentage increase from the baseline under various scenarios for oil price increase. As can be seen from the table, global biofuel production in 2020 would be more than double than that in year 2009. Middle/low income countries are found responsible for a larger share the output in 2020 than high income countries. It is interesting to note that production of biofuels is highly sensitive to oil price. For example, a 25% increase in oil price from the baseline in 2020 (i.e., a 107% increase from the 2009 level), would cause a 20.
Policy Research Working Paper 10881

# **Abstract**

Current investment trends in emerging market and developing economies are not enough to meet the needs of their growing populations and will fall short of achieving the Sustainable Development Goals related to human and physical capital development. Public investment can play a critical role in addressing this shortfall, especially if it can crowd-in private investment. Using theory and panel data for 109 developing countries from 1980–2019, this paper investigates whether public investment crowds in or crowds out private investment. The paper also explores how the relationship changes across different groups of countries and under different institutional settings. The analysis uses changes in predicted disbursements on loans from official creditors to developing country governments as an instrument for changes in public investment. The findings show that public investment is a complement to private investment, raising the marginal productivity of the latter. As a result, an extra dollar of public investment raises private investment by 1.6 dollars. The findings also reveal stronger evidence of crowding-in of private investment in low-income countries and Sub-Saharan Africa, where investment needs are greatest. Finally, the findings are embedded in a model with imperfect capital markets, which shows that public investment can be used as an effective vehicle to address underinvestment issues induced by capital market distortions.

This paper is a product of the Macroeconomics, Trade and Investment 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/prwp. The authors may be contacted at jfrancois1@worldbank.org, mkonte@ifc.org, or fruch@worldbank.org. A verified reproducibility package for this paper is available at http://reproducibility.worldbank.org, click **here** for direct access.

<!-- Start of picture text --> TRANSPARENT<br>ANALYSIS<br>G
in the positive trend of SP injections in the control group. The risk of information spillover becomes more pertinent towards the final period of our analysis, as control units were closer in time to receiving the intervention themselves.

The study’s main limitation is related to data constraints and the restricted time horizon available for the analysis. First, the inability to distinguish zero values from missing information in our data implies that our analyses suffer from measurement error in the dependent variable, which yields inflated standard errors. Second, we are unable to ascertain whether women initiating SP receive timely renewals, i.e., maintaining uninterrupted contraceptive protection, since we cannot track them over time with aggregated health facility data. Third, we do not have information on women’s demographics in our data. Consequently, we cannot 16
# **1. Introduction**

Schools throughout the world closed in response to COVID-19 beginning in 2020. In some cases, they quickly reopened in 2021, but in some countries, they remained closed longer (Patrinos 2023). Globally, schools were closed for an average of 5.5 months (22 weeks) since the onset of the pandemic, equivalent to two-thirds of an academic year, when localized school closures are considered (UNESCO 2023a). The duration varies by region, from just one month in Oceania, to 2.5 months (10 weeks) in Europe, to as many as 5 months (20 weeks) in Latin America and the Caribbean. Early on, the school closures were expected to contribute to what was already described as a learning crisis (Angrist et al. 2021; World Bank 2017).

Country studies show large losses (Alasino et al. 2024; Betthäuser et al. 2023; Carlana and La Ferrara 2023; Donnelly and Patrinos 2021; Engzell et al. 2021; Hammerstein et al. 2021; Jack and Oster 2023; Jack et al 2022; Maldonado and De Witte 2022; Zierer 2021). On average, school closures induced by COVID-19 led to a learning loss of 0.17 of a standard deviation – that is, at least one-third of a year’s worth of learning (Patrinos et al. 2023). Distance learning during the school closures does not seem to have helped very much (Haelermans et al. 2022; Singh et al. 2022); only the duration of school closures led to variations. Most studies observe increases in inequality where certain demographics of students experienced learning losses that were more significant than others. These learning losses could translate to earnings losses and could cost this generation of students trillions of dollars (Psacharopoulos et al. 2021).

Also, global studies – that is, studies using data from international assessments where students in many countries take the same tests and under the same conditions, thus, making them
# Magnitude and Distribution of Electricity and Water Subsidies for Households in Addis Ababa, Ethiopia<sup>1</sup>

## **Introduction**

In Addis Ababa, Ethiopia, increasing block tariff (IBT) structures have been used to calculate households’ monthly bills for both electricity and water services.<sup>2</sup> These IBT structures have two principal objectives. The first is to ensure the fair, equitable, and affordable provision of these utility services; the second is to use the higher prices in the IBT’s upper “blocks” to promote energy and water conservation. Our paper focuses on the first objective and analyzes the incidence of electricity and water subsidies delivered under these two IBTs to 366 households—with private connections to the electricity grid and to piped network water—for the exclusive use of their household members.

Our analysis is restricted to this 366-household subsample, which is derived from a large and representative household survey of Addis Ababa that includes 987 observations, because we have data for the subsample households—which have private electricity and water connections—from their monthly electricity and water bills; these data include the quantities of electricity and water used as well as the households’ socioeconomic status. We are thus able to calculate the magnitude of both the electricity and water subsidies that the 366 households received in 2015, and we can also examine the distribution of electricity and water subsidies by wealth groups within the subsample.

1 The authors express great thanks to Alemu Mekonnen, Tensay Meles, Abebe Damte Beyene, and Samuel Abera for their key contributions during the data collection fieldwork, to Gunnar Kohlin, Peter Martinson, and Mike Toman for their advice on the research design and survey instrument, and to Richard Spencer for useful comments on a draft of the paper. The authors also acknowledge with gratitude financial support for the research from the World Bank’s Knowledge for Change Trust Fund.

> 2 <mark>The electricity IBT was in force until November 2018, while the water
**–** **<u>Table 2: Area with summer and winter crops or fallowed, 2019 23 (hectares, millions)</u>**

|<br>**Agric. season **|<br>**Total **|<br>**Winter crop**|**Summer crop**|
|---|---|---|---|
|2019|27.31|9.42|17.89|
|2020|25.76|7.51|18.26|
|2021|26.69|9.45|17.23|
|2022|25.43|8.38|17.06|
|2023|24.88|6.76|18.12|
|Average 2019–21|26.59|8.79|17.79|
|2022 – avg. 2019–21|-1.15|-0.42|-0.74|
|2023–avg. 2019–21|-1.71|-2.04|0.33|

_Source:_ Computations based on data from publicly available crop maps (www.cropmaps-ua.com).

19
. Conditional on these assumptions, the results do suggest that at least some of the factors associated with upward tilting lifetime incomes and lower risk are associated with reduced savings rates. Perhaps most puzzling is the apparent irrelevance of the sector of employment for savings decisions, despite the likely future contraction of the public relative to the private sector. The muted support is consistent with prior findings for developing market economies [Gupta (1987), Campbell and Deaton (1989), and Schmidt-Hebbel, Webb and Corsetti (1992), inter alia] which, following quite different methodologies, find at most muted support for smoothing.

# **5. Conclusion**

There are few instances of radical economic change comparable to the transition of eastern Europe from plan to market, providing a valuable opportunity to study economic behavior in the presence of first order changes in circumstances. Using three matching surveys for Bulgaria, Hungary and Poland, we explored the savings responses of household to the transition experience.
measure firms’ AI adoption and subsequent effects. Miric, Jia, and Huang (2023) and Webb (2019) used patent data as a proxy for AI adoption. Zolas, Kroff, Brynjolfsson, et al. (2021) and McElheran, Li, Brynjolfsson, et al. (2024) used the US Annual Business Survey data to track AI use among businesses. Even though AI development and use has been ongoing for decades, AI usage among US businesses remains very low and highly uneven. Fewer than 6% of firms used any of the AIrelated technologies, and adoption is heavily tilted towards very large businesses, businesses owned by more educated and younger owners, and in superstar cities. Bonney, Breaux, Buffington, et

> 1Digitally tradable services include, for example, information and communication technology and business process outsourcing, finance and insurance, professional services, and research activities.

5
implementation mandate. In order to better characterize the issuance of subsidy at different policy phases, we make an assumption on consumers’ expectation for policy availability contingent on existing local subsidy programs: if a province or a city had subsidy program in the previous time period, consumers would anticipate the continuation of the subsidy issuance (could

> 25The official documents for 2013-2015 and 2016-2020 both stated that the subsidies should target consumers directly, and consumers are eligible to pay the post-subsidy price. In the policy document for 2013-2015, the government issues quarterly advance payment to manufacturers and conducts final settlement annually. In the policy document for 2016-2020, both the advance payment and settlement are conducted annually. Sources: `http://www.gov.cn/zwgk/2013-09/17/content_2490108.htm` and `http://fgk.mof.gov.cn/law/ getOneLawInfoAction.do?law_id=83837`

> 26The MIIT publishes the announcement on subsidy settlement by region-firm-vehicle model and shows the number of applications versus application approval. Approval rate is calculated using the data provided in the policy document appendix. The 2018 settlement was published in November 2019. Source: `http: //www.miit.gov.cn/n1146295/n7281310/c7548610/content.html`

> 27Nevertheless, since local subsidy issuance is not uniformly administered as central subsidy, more delays in settlement are observed in practice. Source: `http://www.nengyuanjie.net/article/25080.html`

14
within the fi rm, Share of high educated workers is the share of workers with at least the secondary education, Share of females is the share of females in total workforce, Share workers with training is the share of workers that participated in training offered by the fi rm in the past year, Share public ownership (foreign) is the share of the fi rm’s capital owned by public (foreign) owners, Tax evasion is the share of the fi rm’s total sales that the manager reports as not being reported for tax purposes, Bribes for government contracts is the share of a total

> 46This investment climate survey project has evolved over time within the World Bank. Previous similar projects included the Regional Program on Enterprise Development that has been collecting fi rm-level data in Sub-Saharan Africa countries for a decade and the World Business Environment Survey.

26
their health, there could be a tendency for them to become more adherent. Therefore, we cannot conclude definitely as to the impact of the crisis on adherence between these two years, as we do not have a good counterfactual, that is, we do not know how adherence would have evolved without the crisis.

# **5. Is there an impact of the food crisis on the frequency of visits to the health facility?**

As mentioned in the introduction, cost of transportation to get a prescription refill at a health facility is a strong barrier to adherence. Essential expenditures such as food, schooling and health are competing inside the household budget. An economic crisis, by reducing income and increasing food prices can shift the equilibrium in the household allocation of resources and reduce expenditures devoted to health. In addition to the food crisis, a sharp increase in fuel prices potentially increased even more the cost of transportation for patients. In this context, another way to look at the impact of a food crisis on adherence to treatment and on the livelihoods of people living with HIV/AIDS is to consider the change in the frequency of visits to the health facility. The frequency of visits can also be understood as a proxy for good adherence to treatment.

The biomedical data, which collected health related information on 498 HIV positive patients of the survey, allows us to calculate the number of weeks between two visits, with one to six observations for each patient (data on the last seven visits). For the analysis we keep only those observations that are in the proper timeframe, that is, between the two waves of the survey. The time between two visits in itself is not a sufficient indicator of regularity because the visit protocol varies across health facilities. Therefore, the outcome studied is the standardized deviation from the mean frequency of visits in the health facility of the considered observation. A positive number means that the patient visited the facility less often than average. We merged the biomedical records with the living standards