rafmacalaba/data-use-mentions-extended huggingface dataset:
GVC participation of a country-sector ( _gvcil_ ) is measured as the import content of exports (as percent of a sector’s exports) for the 28 exporting countries for the year 2015 (latest available). The measure is based on data from the OECD International Input-Output tables and computed following the approach by Borin and Mancini (2019). While the GVC participation measure varies across exporting countries, it is only available at a more aggregate sector level covering 15 TiVA sectors.

To capture the importance of imported inputs for production, we rely on import data from UN Comtrade for 2017 and compute a sector’s share of parts and components (as percent of total imports) in partner countries ( _gvc partnerjl_ ). Parts and components<sup>19</sup> at the HS6-digit product level are determined based on the UN Broad Economic Category (BEC) classification and then further aggregated to the TiVA sector level in order to be consistent with the backward GVC participation measure.<sup>20</sup> We interact the GVC measures with the shock measure in the exporting and partner country to reflect a shock’s transmission through the GVC channel. The upstream shock variable ( _upstream shockilt_ ) is computed based on IPI growth and data from the OECD International Input-Output tables to compute weights.<sup>21</sup> To control for global sector-time trends we use industrial production growth data from UNIDO INDSTAT which are available at the 2-digit ISIC level and cover 60 countries representing more than 90 percent of world GDP and 95 percent of manufacturing value added. Our measure _global outputmt_ is based on manufacturing value added in constant 2015 USD. The global <mark>average is based on the relative contribution of a country (weight) to the world’s total manufacturing value-added. The correlation matrix between independent variables is shown in Appendix 2, while the summary statistics are reported in Appendix 3.</mark>

# **3. Regression results**

Before assessing the heterogeneous impact that Covid-19-induced shocks could
. We rst analyze the case where brokers can obtain complete information on this risk. Then, their business is simply to acquire land from a customary owner and to attempt to establish statutory rights on the plot. If successful, they have to pay a conversion fee (which may cover various expenses ranging from land surveying fees to registration in the cadaster). We then contrast this with the case where brokers are unable to obtain information on the risk of a formalization failure. This is typically caused by the inherent diculty of inspecting and uncovering all dierent stakes in the ownership of a land plot. We show that brokers then face an additional problem of adverse selection as customary owners may choose to oer the riskiest plots for sale. The information asymmetry causes a land market failure, as transactions fail to take place at some specic distance from the city center.

The paper also provides a framework for an empirical analysis of land tenure conversions in Sub-Saharan African cities. It exploits a unique survey of land plots in Bamako, Mali, that were transacted between 2009 and 2012 and unbuilt at the time of 2In Mali, coxers are land brokers who facilitate transactions between customary owners and buyers. According to Durand-Lasserve et al. (2015), they maintain a network of informers in peri-urban villages to identify land that can be transacted. They negotiate with village authorities on behalf of buyers and are therefore key players in the conversion of customary agricultural land into residential land. They know how to circumvent regular procedures and deal with the administration to make sales and land tenure conversion eective. They can be found alongside roads, near plots for sale.

3
Figure 1: Weighted actual and forecast GDP growth, firm-level data <!-- Start of picture text --> 2006 2010 2014 2018<br>30<br>20<br>10<br>percentage points<br>0<br>-10<br><!-- End of picture text --> Notes: Figure depicts means and ranges of weighted actual GDP growth (in gray) and forecast GDP growth (in black) at the firm-level, using the estimation sample. Means are displayed in lines, while ranges are shown in bars.

27
a benchmarking tool to measure the regulatory environment for the digital economy. The objective is to encourage competition among countries as they move toward more efficient, more transparent, and easier-to-implement regulations for the thriving digital economy. In 2018 the Digital Business Indicators project collected information on the existence and quality of the regulatory environment in broadband connectivity, digital payment, data privacy and security, as well as logistics, in 21 pilot countries (see list of countries in annex A). Data were collected through standard questionnaires sent to experts in the private sector, public sector ministries, and authorities, as well as law firms in each country.

This study presents findings from the Digital Business Indicators initiative, and it extends the discussion to a wider range of regulatory issues associated with digital businesses. It first probes the characteristics of digital platform firms, as well as their impacts on traditional firms. It then zeroes in on a few key regulatory and policy areas, including competition, taxation, data privacy, and infrastructure. Data from the World Bank’s Digital Business Indicators project are used to analyze data privacy and infrastructure issues. When empirical data are missing in areas such as competition and taxation, this study takes stock of the ongoing policy discussions. It aims to advocate a research agenda that will develop the best regulatory and policy practices for governments seeking to promote the digital economy.

# The changing business landscape

In 1937 Ronald Coase established a clear boundary between firms and markets in his influential article “The Nature of the Firm.” According to Coase, firms exist because of inefficiencies in the marketplace.<sup>4</sup> Where the costs of transaction and coordination between market players are high, large hierarchies in the form of firms predominate, and they manage to achieve economies of scale in production and distribution internally. The emergence of large industrial corporations that conduct the full range of production activities in-house demonstrates the validity of Coase’s theory. For example, in early 1900s U.S. Steel Corporation controlled all stages
in the area, while in a low malaria area immunity does not exist; and (3) the infection in a low-malaria area is likely to be more severe due to the lack of exposure to the disease. Therefore, I focus on the part of Senegal discussed earlier that is at a pre-elimination stage. Within this area, I focus on ve of the lowest malaria districts where data are disaggregated at the health post level and available for every health post in these districts. Malaria data are not available at this high spatial resolution for any of the other low malaria districts. The data cover 117 health posts. The appendix provides a map of the ve health districts, which I subdivide into areas based on the location of the health posts and cell phone towers. Health posts in close proximity were grouped together forming 36 health post catchment areas.

I use incidence data based on data collected from each health post on all new cases in the reporting month.<sup>12</sup> The use of incidence data is one thing that separates this paper from some of the previous work that relies on endemicity data. The endemicity data are gathered from parasite rate surveys in which a random subsample of the population is tested for malaria parasites. When the malaria prevalence is very low, the likelihood of having a positive case becomes very small. Therefore, when focusing on a low-malaria setting to understand impact of mobility, incidence is a more reliable measure (Alegana et al. 2013, J. M. Cohen et al. 2013).

PNLP's work has led to a system that provides high quality data on malaria incidence across the country. In Senegal, if an individual feels sick, usually experiencing a fever, chills and fatigue, she will go to the closest health post where she will be tested using a rapid diagnostic test (RDT) due to her symptoms. If she tests positive, she will be provided with medication for free to treat the disease. Therefore, all incidence data used in
# **7. Concluding remarks**

Within the growing literature on fiscal federalism, a rigorous understanding of the impact on welfare of transfers to subnational governments is an important research question. The present paper contributes to this body of work by identifying the causal effects of a fiscal transfer fund on local welfare. It makes use of a social infrastructure fund in Mexico as a case study to illustrate a larger problem that has implications at the global level, that is, how to raise the effectiveness of transfers to local governments to achieve higher-quality spending and, ultimately, improve social outcomes.

Existing systems vary in scope and arrangements. They include systems in resource-rich countries with fiscal rules for sharing or not sharing natural resource revenues among producing and nonproducing regions and systems that rely on transfer agreements in countries with no tax revenues from natural resources. In the context of these arrangements, it is critical to develop an agenda to assess the effectiveness of the resource allocations, and to push for revenue decentralization, which, in many developing countries, remains weak (Gadenne and Singhal 2014). Local governments that do not face the political cost of higher revenue collection may come across perverse incentives to overspend, leading to vertical fiscal imbalances. Meanwhile, adequate data and formulas to distribute funds can create incentives to invest efficiently. They can help in evaluating the effectiveness of transfers, such as earmarked funds dedicated to specific programs, to close coverage gaps, create appropriate incentives in design, and boost the quality of social spending.

This paper takes advantage of a novel data set to assess the effects on welfare of federal earmarked transfers in Mexico. The results show that the fund earmarked for social investment known as FAIS had a modest, but positive and statistically significant effect on average household income between 2005 and 2014. It also had a positive effect on several nonmonetary measures of well-being, such as access to services (electricity, sewerage, drinking water), the quality of the dwelling (floor materials, access to toilets), education, and health
stimulating activities with any caregiver in the previous three days). A Z-score of 0 would indicate that a child in this sample has a similar developmental status to that of a child in the CREDI reference sample who is the same age. As demonstrated by Figure 1, the average child in this sample has a developmental status almost 2 standard deviations (1.72) below the mean, indicating much lower levels of child development in this sample compared to the global population. Distributions varied by various characteristics of interest, such as maternal education, living in a rural area and refugee status (Figures 2-4).

# **Figure 1**

_Sample Distribution Compared to Global Distribution (n=1397)_

# **Figure 2**

_Sample Distribution for Children with Mothers with Less than a Primary Education Compared to Global Distribution (n=824)_ 13
is well suited to studying how leadership changes affect bureaucratic behavior and service delivery: bureaucrats operate under strong top-down and bottom-up pressures, since their tenure is highly contingent on local leadership and, as frontline providers, they are in regular contact with citizens.

Our analysis relies on data from a large survey that we conducted in 2022 with village heads, bureaucrats, and citizens in 852 villages spanning 17 provinces across Indonesia. We designed this survey to collect rich data on bureaucrats’ characteristics and citizens’ attitudes, and to understand how the policy priorities of village officials align with the preferences of citizens. We also use detailed administrative records on village-level public goods provision. Together, these data sources allow us to study what citizens want from their village government, what bureaucrats know about these preferences, and how they act upon them. To our knowledge, this paper is among the first to study bureaucratic performance from the dual perspective of bureaucrats and the citizens they serve.

Using this dataset, we employ a regression discontinuity design (RDD) leveraging variation from close village elections where the incumbent narrowly won or lost. Incumbency plays a central role in shaping electoral competition in this context since village elections are non-partisan by law. Across the 852 villages we surveyed, 512 conducted an election featuring an incumbent between 2015 and 2022. Incumbents won a slight majority (52%) of these elections, allowing us to identify the effects of turnovers on village- and individual-level outcomes. We also use variation from the staggered timing of village elections inherited from Indonesia’s democratic transition (Martinez-Bravo et al., 2017). Supporting our 1
shareholder: the most common legal forms of corporatized SOEs are standard corporate forms such as Limited Liability, Joint Stock Company, among others. An SOE is non-corporatized if it is classified as a state company according to law, and this legal status is not a standard corporate form (i.e., no shareholder structure). A methodology was introduced to perform an analysis of the legal forms to be included in the final database (see Annex 2).

Finally, our database includes those firms that can generate profits and are engaged in market activities. The capacity to generate financial gains and profits implies that SOEs can participate in the market like any private actor that improves efficiency or adjusts prices to compete. This does not mean that only firms reporting profits are included in the Global BOS database, but rather that firms must have the capacity to generate revenues through the provision of goods and services. In this manner, a company is considered as an SOE if it provides a good or service which should be traded at economically significant prices. Based on this criterion, we exclude firms that offer goods or services which are often provided for free, such as firms in health or education services.

The second criteria of the BOS database is a novel algorithm tracing state participation in the corporate sector beyond directly owned firms. The ORBIS ownership information (known as the “links vintage files”) only provides the connection for pairs of companies. In other words, the raw ORBIS files do not directly connect firms in such a way that for company C, we can identify company A as its indirect owner and connect all relationships as in A (y%) -> B (x%) -> C.<sup>17</sup> To address this issue and the lack of an SOE identifying variable in the ORBIS database, we developed an algorithm that retrieves the ownership structure of firms linked to the state using available information on shareholders and direct shareholding percentages.<sup>18</sup>
owners regarding select problems faced by the enterprise. Our study exploits these qualitative questions to analyze how problems faced by enterprises affects enterprise performance, conditional on key enterprise parameters such as capital and labor.

# **2.3 Consumer Pyramids**

The last NSS employment-unemployment survey was conducted in 2011-12. In this regard, we use the four rounds of the NSS surveys between 1999 and 2011 to gauge the historical predictors of rural non-farm employment, and then use data from 2015 from the Consumer

> 1 The corresponding survey rounds are 55, 61, 66 and 68. The NSS conducts similar surveys in the intervening years but the sample sizes at the level of districts are too small to conduct any robust analysis. The surveys for each round begin on July 1, and continue to June 30 of the subsequent year.

8
for the highlands regions. Work on updating baselines will be conducted during 2016, with a view to obtaining updated baselines for all regions in Ethiopia.

# IV.3 Complementarities between the LEAP and LIAS tools

The LEAP and LIAS tools complement each other in enabling a successful drought response. In particular, the two tools have a different focus, with the LEAP tool focused mainly on the impacts of a drought shock as measured by WRSI on HRD numbers, and the LIAS tool focused on assessing the implications of a range of variables – including market access and prices – on livelihood strategies. Each tool sheds light on the question of food security within Ethiopia from a different angle, with the LEAP tool providing a dynamic, macro-level assessment of drought risk, and the LIAS tool providing a detailed bottom-up view. It has therefore been proposed that LEAP and LIAS data should be integrated to a greater extent. For instance, LIAS data can be used within LEAP, as follows<sup>50</sup> :

- (i) To check planting dates and the length of crop cycles within LEAP;

- (ii) To determine where certain crops are grown and to adjust LEAP accordingly;

- (iii) To identify the areas where drought is likely to have the most severe impacts on livelihoods based on LIAS data on households’ dependence on self-grown crops for food;

- (iv) To support the development of a LEAP pastoral index based on LIAS data for pastoral areas.

> 50 Hoefsloot et al. 2013.

16
based solely on data spanning the 1990s may miss important links between tariffs and wages. Here, we fill this gap by pursuing a historical investigation of these episodes of reforms.

Our findings confirm that trade reforms, ceteris paribus, have i) decreased wages and ii) increased wage inequality in Argentina. After controlling for individual worker characteristics, survey effects, industry effects, and time-varying skill premium effects (like labor regulation and unionization or school quality) we find a strong positive association

> 2The work by Attanasio, Goldberg, and Pavcnik (2004) and Golberg and Pavcnik (2005a) is similar to ours in that it exploits data from the eighties and the nineties. There is a major difference, though. Whereas their study involves one trade reform, we study two episodes of trade liberalization separated by a reversal to protection.

3
openness, and hence safeguards the democratic legitimacy of independent central banks (Geraats 2002b). It is essential to have openness as a part of public governance (Stiglitz 1999).

This paper focuses on economic transparency defined as availability of and access to economic information and statistical data (Geraats 2002b). Transparency of statistical data relates to open access data and information accountability. There is a healthy literature on the relationship between data transparency and macroeconomic and financial factors, especially sovereign bond spreads and institutional quality.

Clare and Courtenay (2001) find that transparency increases predictability of monetary policy. Glennerster and Shin (2008) examine whether greater transparency (measured by IMF binary transparency data) reduces the cost of borrowing in sovereign bond markets. They find that there are diminishing marginal benefits of transparency when a country has smaller and less liquid debt markets. Alfaro and Kanczuk (2019), on the other hand, examine how undisclosed debt affects debt sustainability by modeling international investors’ behavior with and without debt transparency. They find that disclosure of nontraditional debt (their proxy of debt transparency) increases welfare for the borrowing countries and reduces debt sustainability. Horn, Reinhart and Trebesch (2019) build a new data set for China’s total loans and grants to 152 countries and find that the lack disclosure in debt data leads to mispricing sovereign bonds and associated default risks.<sup>2</sup> On a related literature, Gelos and Wei (2002) investigate the impact of transparency on the behavior of international investment funds and explore whether a developing country’s opacity explains mutual funds’ investment position. Their findings suggest that international investors prefer more transparent markets to invest while the degree of herding among funds is greater in opaque markets. Tebaldi et al. (2018) examine the determinants of sovereign bond spreads for emerging markets from 1994 to 2014 and they conclude that the main determinants are GDP growth, real effective exchange rates and political liberalization. Presbitero et al. (2016) examine drivers of sovereign bond issuances in
and attitudinal variables are controlled for, although this improvement in the R<sup>2</sup> is much below that reported by Ravallion and Lokshin (2002) for Russia.

Other behavioral explanations, including differences in views on what constitutes poverty and wealth in a given country, or misreporting, with the reluctance to admit to poverty (wealth) by the poor (rich), can also be at play. We discuss in section 4 the possibility of frame of reference biases.

# **3.2. Satisfaction with life**

As described in section 2, two measures of overall life satisfaction are available in the LiTS. We discuss differences between the two measures in section 4, as an example of the role of framing in subjective welfare assessments. Averaged over the entire region, 53 percent of the adult population reported to be satisfied with life in 2010. This measure ranges from less than 20 percent in Romania and Hungary to 89 percent in Sweden. The share of the adult population satisfied with life is considerably lower in Eastern Europe and Central Asia than in Western European countries. With the exception of Italy, in all of these countries (Germany, France, Sweden, UK), more than 70 percent of the adult population are satisfied with life (only 50 percent in Italy). Using the alternative life satisfaction scale that ranges from 1 (completely dissatisfied) to 10 (completely satisfied), the mean level of life satisfaction in the region is 5.9 out of 10, which is broadly consistent with the 5-step Likert scale.

There is considerable evidence of a positive association between average life satisfaction and country income at any given point in time (Deaton, 2008). In Figure 3, we look at whether a similar gradient can be observed in the LiTS data for the two life satisfaction measures that are available.

9
Policies Met the “Timely, Targeted, and Temporary” Principle? _Essays in Economic and Business History_ , 35(2).

- Taymaz, E. 2010. The effectiveness of crisis measures: The case of motor vehicles industry. In Crisis and Turkey: Impact analysis of crisis response, ed. Ü. Efendioğlu, 41–72. Ankara: ILO.

- Tomer, J.W. K., & Fishbane, L. (2020). An infrastructure stimulus plan for the COVID-19 recession July 2020.

- UNEP. (2009). Global green new deal: An Update for the G20 Pittsburgh Summit. _New Solutions: a journal of environmental and occupational health policy_ : NS (Vol. 19).

- U.S. Bureau of Labor Statistics. (2021). “Labor Force Statistics from the Current Population Survey– Household Data Not Seasonally Adjusted: A-31. Unemployed persons by industry, class of worker, and sex,” January 8, 2021, https://www.bls.gov/web/empsit/cpseea31.htm

36