rafmacalaba/data-use-mentions-extended huggingface dataset:
reading on the Programme for International Student Assessment (PISA) – as an indicator of educational quality (OECD 2016a, 2016b, 2016c).

_Market Efficiency._ To construct a subcomponent index for market efficiency ( _Effi_ ), we classify markets into output, financial, and labor markets. We select the World Bank Doing Business scores as an indicator of output market efficiency, which measure the regulatory environment in terms of ease for firms to start a business, trade across borders, register property, get credit, and the like (World Bank 2017a). We choose the International Monetary Fund (IMF) Financial Development Index as an indicator of financial market efficiency, which measures the level of financial development by including the size and liquidity of financial markets, ease for individuals and firms to access financial services, and the ability of financial institutions to provide services at low costs with sustainable revenues (Svirydzenka 2016). As indicators of labor market efficiency, we construct an composite index, using factor analysis, consisting of minimum wage (% of value added per worker), severance pay for redundancy dismissals (weeks of salary), and the share of women in wage employment in the nonagricultural sector from World Bank databases (World Bank 2017h, 2017q).

_Infrastructure._ For a subcomponent index for infrastructure ( _Infra_ ), we select fixed-telephone and mobile subscriptions (per 100 people) (World Bank 2017c, 2017i); the length of paved roads (km per 100 people) (International Road Federation 2017a, 2017b); electricity production (kw per 100 people) (OECD/IEA 2017); and access to an improved water source and improved sanitation facilities (% of population) (WHO/UNICEF 2017b, 2017a).

_Institutions._ To construct a subcomponent index for institutions ( _Inst_ ), we select the World Bank Worldwide Governance Indicators. These include measures of voice and accountability (citizens’ participation in selecting their government and freedom of expression); control of corruption (the extent to which public power
in mission areas are more successful at achieving their goals. To this end, two empirical tests are conducted, one using data on project ratings and the other using survey data on development outcomes from the Demographic and Health Survey (DHS).

# **3.1 Project Ratings**

Each World Bank project is headed by a team leader who is also responsible for evaluating its success (with respect to the stated goal) upon completion. After the initial evaluation, the World Bank’s Independent Evaluation Group (IEG) performs a second assessment based on available project documentation. Furthermore, the IEG performs an additional in-depth evaluation of approximately 25 percent of the projects, which includes on-site visits and additional analyses (Denizer, Kaufmann, & Kraay, 2013). Each layer of evaluation rates the projects on a six-point scale from “highly satisfactory” to “highly unsatisfactory.” The data contain rating information on 43 percent of the projects included in the grid analysis, thus allowing tests to be run on whether projects implemented in the vicinity of missions display higher ratings. Since rating information is at the project level rather than the location level, here the analysis departs from the grid-level dataset and relies instead on a project-level dataset (recall that each project is implemented across several locations). The baseline specification to be estimated by OLS is where _p_ and _k_ are indices for project and country, respectively.

Rating _pk_ is a binary variable that equals 1 if the rating of project _p_ is “satisfactory” or better and equals 0 otherwise (the most recent available IEG evaluation is used, which means desk reviews in 87 percent of the cases); MissionLocations _pk_ is the project’s fraction of precision 1 and precision 2 locations that are within 25 km of a mission station (this radius implies observational units that roughly correspond to the size of cells in the grid structure). The selection of relevant covariates follows Denizer, Kaufmann, and Kraay (2013). In terms of country-level variables, the controls include growth
2017).<sup>6</sup> Specifically, it pays attention to the role of a reference network, which refers to the group of people whose actions and beliefs individuals care about when they act. Depending on the context and the sphere of life that gender norms refer to, this group can be given by neighborhoods, villages, or people on the street. Hence, as people move from one place to another, they move across reference groups and may knowingly change their behavior to comply with the norms in place in the new setting (Choe et al., 2014).

The analysis focuses on behaviors or actions and attitudes or empirical expectations (Alesina et al., 2013).<sup>7</sup> These two components are measured and analyzed separately, rather than combined in an index. Following previous studies, survey clusters are used as a proxy for reference networks (Storey & Kaggwa, 2009; Uthman et al., 2011; Vyas & Heise, 2016). The prevalence of behaviors and attitudes at the reference network level is inferred by aggregating (non-self) reported values across individuals in the same cluster, as it is reasonable to think that people residing in the same cluster might have direct contact with each other. This approach is consistent with the feminist literature which has theorized gender norms as having blurry boundaries, rather than focusing on a particular group with similar demographic characteristics (Oakley, 2015). Also, following gender norms theory, which focuses on the alignment between the norm and personal attitudes, the analysis in this paper assumes that gender norms become less (more) traditional when both attitudes and behaviors become less (more) rigid.

The analysis examines 17 items (10 attitudes and 7 behaviors) classified into five domains. _Reproductive health,_ is measured using one indicator for attitudes and one indicator for behaviors, as shown in Table 1. The question on attitudes refers to women’s approval of contraception to prevent pregnancy. The proxy for behavior
sobre a Propriedade Territorial Rural. Notes: the bars represent the distribution of payments within each quintile.

**Figure 8. Concentration of taxes (% of fiscal interventions)**

<!-- Start of picture text --> 100<br>90<br>80<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>1 2 3 4 5<br>Quintiles of per capita market income plus pensions<br>Indirect Taxes Direct Tax IPTU/ITR Direct Taxes MIPP<br>Concentration shares (% )<br><!-- End of picture text --> Source: authors’ estimations based on surveys PNAD-C, POF, and PNS, and administrative data from the Ministry of Finance, Ministry of Health, and Government Open Data Portal. Notes: IPTU stands for Imposto sobre a Propriedade Territorial Urbana, while ITR stands for Imposto sobre a Propriedade Territorial Rural. Notes: The bars represent the share of each tax paid by a given quintile.

25
product dummy reflects whether the variety has been first exported by that country after 2000, and not at any point in 1990-1999 before our sample period.<sup>25</sup> Then we run a horse race with new product and initial quality interactions.

> 24 Product complexity is measured using Levchenko (2007) with 1997 IO tables for US NAICS 1997 corresponded to data. We use the negative of the HHI, so that higher complexity measures a wider variety of inputs.  We divide the HHI by 1,000 for legibility of the coefficients.  We demean product complexity interactions so the so non-interacted terms reflect the effect of robots at the mean complexity.

> 25 Broadly similar results are obtained using alternative years such as products introduced since 2005 or 2010.

28
New Zealand). A reduction in visa processing time would be likely to facilitate Mode 4 trade, also by making the process more certain and predictable. In addition, longer visa durations for services suppliers would be a significant aspect of any TFiS agenda on MNP. Ideally, the duration of a visa should match the time needed by the service supplier to deliver the service.

## **Table 6 Attributes of business visa applications: summary statistics (2017)**

|**Attribute**|**Sample avg.**|**Min**|**Max**|
|---|---|---|---|
|Cost to obtain a business visa (USD)|84|7 (JPN)|297 (COL)|
|Duration of visa for crew (no. of months allowed)|5|0 (COL)|23 (IND)|
|No. of documents needed to obtain a business visa|9|2 (GBR)|16 (FRA)|
|Range of visa processing time (days)|13|1 (JPN)|32 (CAN)|

Source: Singhal (2019) based on OECD STRI; Finally, it is interesting to note that there is little, if any, statistical correlation between the various attributes of business visa applications. For instance, it would be expected that countries with more restrictive policies towards MNP to require more documents to apply for a business visa or to allow for smaller visa durations. Moreover, even the visa processing times and the duration of visa for CSSs, ISSs and ICTs are negatively correlated, which suggests that even if it may take longer for a country to issue a business visa, that may not result in longer stays in that country for service professionals.

Singh (2019) concludes that moving towards multiple-entry visas for service providers in all sectors, providing opportunities for e-visas/visas on arrival and/or exempting visas for
family. In fact, alll the wife-abusers whom we had in-depth interviews with justified their behavior with "instrumental" explanations, as a means to extract transfers or control resources.

The interviews that we conducted revealed that there was a close link between much of the abuse by the groom's family and the demand for transfers from the bride's family. We will illustrate this link with a brief outline of the case of Sannamma and Raju, a young couple who had been married for about two years. Their parents arranged the marriage vhen Sannamma was 17 and Raju was about 24, and the wedding was celebrated about six months later. Sanamma's parents are relatively rich with about 10 acres of irrigated land, while Raju's were considerably _5_ According the 1991 Indian Census, in this region of India the divorce rate is estimated at 0.3 per cent.

6 The term "dowry" has been used in a number of different ways in the literature. We will employ it to mean a groom-price, a payment in cash and/or kind directly made from a bride's family to a groom's. We will call the reverse transaction a brideprice.

7 This ratio excludes those bride-households that received brideprices, since this community, like many others in the sub-continent, has undergone a transition from paying brideprice to dowry. When brideprice families are included the average dowry is about double the size of annual incomes. These ratios are very similar to those in the frequently analyzed ICRISAT survey which was conducted in two neighboring states (Rao, 1993).

_5_
were destroyed in the agriculture sector over the last decades and the service sector did not generate enough jobs to absorb those displaced workers.

During the last decade, transition economies have also experienced a large worker and job reallocation due to the significant destruction of jobs in privatized companies and in the agriculture and over-staffed industrial sector. Hence we might expect high start-up costs to prevent firm entry and therefore increase unemployment.

Administrative burdens on firm creation refer to issues such as the number of procedures to register a business, the time and cost to undertake those procedures and the minimum capital requirements. However, as one can see in Box 1, other “unofficial burdens” such as informal payments or bribes required to get business licenses, can have also a large impact on the administrative entry barriers for new businesses.

# **Box 1: What the official data on entry barriers do not show: the case of Romania**

Measurement matters. Different ways of measuring the same concept can yield different conclusions. The case of the start-up costs in Romania is a good example of that.

According to _objective_ data from the World Bank, opening a business is easy in Romania: no more than 6 procedures are required to start a business, one can go through the process in less than a month (37 days in average in Europe) and the cost of the process and minimum capital requirements are among the lowest in the ECA countries.

However, when one looks at similar indicators of start-up costs based on _subjective_ opinions, in this case of managers of large corporations, the situation is quite different. According to the evaluation given to the sentence “Starting a new business is generally easy” by the Global Competitiveness Report, Romania is one of the countries where starting a business is most difficult (figure 2.1).

The differences between the _objective_ and _subjective_ indicators could lie on the existence of wide-spread corruption in Romania, which is not included in any of the objective measures of start-up costs compiled by the World Bank. Indeed
27|22,976|15,486|5,064|
|2011|18,293|24,991|0.25|20,059|19,979|6,048|
|2012|19,147|24,015|0.23|14,397|18,657|6,534|
|2013|20,258|26,440|0.22|18,825|23,572|8,263|
|2014|21,594|27,655|0.23|23,102|26,729|8,871|
|2015|24,935|43,335|0.22|37,766|34,424|11,884|
|2016|27,146|52,673|0.20|45,407|40,541|16,371|
|2017|29,648|56,270|0.21|43,822|48,091|19,476|
|2018|32,183|45,868|0.24|32,242|41,520|11,299|
|2019|33,704|56,362|0.24|46,312|47,958|17,347|

_Note:_ This table presents information on corporate profits from tax records. Number of corporations refers to the number of firms filing CIT each year. Aggregate profits is the sum of taxable profits (in billion Lempiras) from all CIT filers. Share with negative profits is the percentage of filers declaring negative income. Profits net of dividends is the total amount of profits minus total amount of distributed dividends. Profits matched to individuals refers to the amount of profits net of dividends that can be attributed to some shareholders using the shareholder database - this number can be larger than column (4) since profits can be negative. Finally, ”profits matched to individuals with valid ID
<!-- Start of picture text --> Figure 16. Share of Services Exports in Total Exports, 2011<br>A. B.<br><!-- End of picture text --> <!-- Start of picture text --> 80 80<br>60 60<br>40 40<br>20 20<br>0 0<br>UMC EuropeUMC LAC UMC AsiaHigh Income Russia China Brazil India SAfricaTurkey<br>Gross Direct Total Gross Direct Total<br>Percentage Percentage<br><!-- End of picture text --> _Source_ : World Bank Trade Value Added Database and Francois et al., 2013.

_Note_ : Gross = Gross Exports, Direct = Direct value‐added exports; Total = Direct value‐added and forward linkages exports, UMC = Upper Middle‐income Countries, 40
_Choosing the minimum daily caloric requirement for the food poverty line._ There is no recent estimate of daily caloric requirement for the Brazilian population. The Food and Agriculture Organization of the United Nations (FAO) estimated minimum dietary energy requirements for the Brazilian population in 2000-2002 and 2006-2008 at 1,840 and 1,860 kcal per person per day, respectively (FAO, 2011). Average dietary energy requirements were estimated at 2,340 (2000-2002) and 2,360 kcal per person per day (2006-2008) (FAO, 2011). In the absence of estimates of the energy requirements of a population of interest, the World Health Organization (WHO) recommends using a mean daily per capita intake of 2,100 kcal for a developing country profile (Table 1). This is the threshold we will be using to estimate the food poverty line for Brazil.

**Table 1. Potential minimum individual calorie requirements for Brazil**

|_Minimum individual_<br>_calorie requirement_<br>_(kcal/day)_|_Source_|
|---|---|
|1,840|FAO minimum dietary energy requirement (MDER) for Brazil 2000-2002|
|1,860|FAO MDER for Brazil 2006-2008|
||WHO (2000) recommends this mean daily per capita intake (for a|
|2,100|developing country profile) if energy and protein requirements of the<br>population are unknown.|
|2,300|World Bank (2007)|
|2,340|FAO average dietary energy requirement (ADER) for Brazil 2000-2002|
|2,360|FAO ADER for Brazil 2006-2008|

_Source:_ Own compilation.

_Estimating the cost per calorie._ To estimate the cost per calorie, we use information on food purchases (expenditures and quantity consumed) by food item from POF. POF collects information on food purchases for consumption at home as well as food consumed away from home (FAFH). Food purchases for consumption at home
program can be sustained over time.|

The IHfRA data collection team used electronic tablets and transmitted data to a cloud-based server, allowing the research team to conduct quality control measures in real-time, checking for consistency and errors. Additionally, IHfRA randomly selected 15% of villages for a second round of interviews, by different interviewers, with a shorter questionnaire, to check consistency across key variables. Separately, children from two households per village had their height and weight re-measured by an IHfRA supervisor, as a quality check.

# Outcomes

Primary outcomes were caregiver-reported diarrhea in the last seven days among all children who were under 5 years old at the time of the survey, length-for-age Z score for a randomly selected child in each household, and a WASH governance index. If the household had one child between age 2 and 5, we measured the length and weight of that child. If the household had more than one child between age 2 and 5, we randomly selected one child. If the household had no children between ages 2 and 5, but one or more children between ages 0 and 2, we measured
805***|0.883***|0.776***|0.721***|0.710***|
||(0.193)|(0.195)|(0.270)|(0.276)|(0.251)|(0.249)|
|_R_<sup>2</sup>|0.848|0.848|0.848|0.855|0.857|0.857|
|Controls|||||||
|Age|No|Yes|Yes|Yes|Yes|Yes|
|Firm size|No|No|Yes|Yes|Yes|Yes|
|Share of white-collar workers|No|No|No|Yes|Yes|Yes|
|Capital/worker|No|No|No|Yes|Yes|Yes|
|Exports/sales|No|No|No|No|Yes|Yes|
|FDI share|No|No|No|No|Yes|Yes|
|Time efects|No|No|No|No|No|Yes|
|Observations|1402|1402|1402|1402|1402|1402|

Robust standard errors in parentheses

* Significant at the 1% level, **Significant at the 5% level, *** Significant at the 1% level All specifications include firm’s fixed effects.

Source: Authors’ calculations using data from ENTIC, INEGI 17
their values to ones observed in 2019. Because, in general, both the rule of law and the control of corruption can have a negative value, in each year we transform them using a max-min technique (by using the ensemble of all countries with available data).

**Growth probabilities data:** For the retrospective analysis and parameter estimation we also need to provide PPI with an initial estimate for the growth probabilities. In our dataset, we have 3 data on the poverty indicators of Ethiopia for 3 survey periods (2011, 2016, and 2019). This is a relatively short time-series which might make it difficult to estimate the initial value for the growth probabilities. While we have this in mind, we also acknowledge that most of the countries in our dataset have always shown improvement in the indicator's value. Since the changes in the indicator values are relatively homogeneous, this allows us to take the easiest approach for calculating the growth probabilities. That is, we estimate the growth probabilities by calculating how many times an indicator improved from one period to another, and divide that amount by the number times that the indicator changed. To reduce potential noise, we set the values for each indicator that did not exhibit improvement to 0.1, and for the indicators that always showed improvement to 0.9.

41
interest rates can—and should—still diverge to reflect domestic economic conditions, but this divergence will be around a larger, shared global component.

Finally, this increased global component in monetary policy does not necessarily imply that central banks will be responding more to global supply shocks (including oil and other commodity shocks). Instead, global shocks will likely continue to be predominantly demand shocks—as occurred during the 2020-24 rate cycle. Correctly identifying the components of global shocks that are demand versus supply is important as this decomposition could imply different monetary policy responses—with supply shocks generally requiring a more muted response (albeit subject to the characteristics of the shock and state of the economy, as discussed in Bandera et al., 2023). It is possible that overestimating the supply component of the post-2021 global shocks resulted in a slower-than-optimal response to the post-pandemic inflation. Granted, identifying global supply and demand shocks in real time is challenging, especially during periods of heightened macroeconomic volatility. Improving our ability to accurately identify these global demand and supply shocks will be increasingly crucial, however, as international factors are likely to continue to play an outsized role in the determinants of interest rates and inflation.

# References

Afrouzi, H., M. Halac, K. Rogoff, and P. Yarad. 2023. “Monetary Policy Without Commitment.” NBER working paper 31207.

Adrian, T., and Estrella, A., (2008), “Monetary Tightening Cycles and the Predictability of Economic Activity”, Economics Letters, Vol. 99, No. 2, pp. 260-64.

Antolín-Díaz, J., and Rubio-Ramírez, J. F., (2018), "Narrative Sign Restrictions for SVARs", American Economic Review, Vol. 108, No. 10, pp. 2802-29.

Aruoba, S. B., and Drechsel, T., (2024), “The Long and Variable Lags of Monetary Policy: Evidence from Disaggregated Price Indices”. Unpublished mimeo, University of Maryland.
illustrates how this can be used to monitor compliance with environmental regulations. Making land use information public allows to use land use at parcel to determine eligibility for public credit programs (Assunção _et al._ 2020), certification of private sector supply chains (Carlson _et al._ 2018; zu Ermgassen _et al._ 2020), or reductions in the cost of measures to enhance resilience such as index based crop insurance (Masiza _et al._ 2022). Data on parcel boundaries together with satellite imagery on historical land use or yield proxies also offers opportunities to allow unbanked farmers to establish a history of creditworthiness.

Finally, connectivity can foster decentralization by combining central data maintenance with access to and use of authentic information by public and private bodies. By reducing cost of accessing information on registered primary or secondary rights (including encumbrances) and allowing its sharing (subject to right holders’ consent where required by data privacy regulation) in real time with stakeholders in private or public sector. By indicating, for example, interest in certain transactions (e.g., leasing land or obtaining credit at some price), this can reduce transaction cost and increase competition in and thickness of land and financial markets, expanding the set of possible contracts and contracting partners.

Together with the ability to reference land use outcomes that are objectively verifiable via remote sensing at high levels of granularity, connectivity provides opportunities to expand the contracting space in ways that may allow to better insure against risk or reduce the potential for moral hazard. Reliable data on parcel boundaries and land rights could allow to bundle cash rent with crop insurance as alternative to sharecropping. The scope to easily register encumbrances or monitor cultivation activity at parcel level in real time can aid reputation development and potentially support an array of contract farming arrangements. Building on private operators’ experience in documenting use rights for supply chain management or certification and adding interoperability with public records could allow to document rights in ways that can mature over time and reduce rural factor market imperfections in ways that