rafmacalaba/data-use-mentions-extended huggingface dataset:
data are available, they can enable tracking of individuals between locales and (with sufficiently-precise coordinates and timestamps) identification of co-locations that are close enough for transmission to occur. Mass testing in each locale can produce relatively precise estimates of infection rates. If cell phone data and testing are fully mobilized, the five unknown elements of the composite gravity parameter are reduced to one for statistical estimation: the likelihood of infection per interaction. Even if testing data are not available, the statistical problem is reduced to finding a composite measure for the likelihood of infection. The need for a distance measure is eliminated, since travel and interactions are observed directly.

By implication, gravity-type studies of Covid-19 transmission in networks of places can be supplanted by models that use aggregative cell phone data when the following conditions hold: (1) Travelers carry cell phones with high probability; (2) access to the full set of time-and-locationstamped cell phone data for the entire network is free and open; and (3) local technical resources can accommodate the programming and computational demands imposed by very large-scale analysis of cell phone data. No setting currently meets these conditions, to our knowledge, but more limited Covid-19 studies are appearing within geographic domains bounded by the researchers’ access to cell phone data (e.g. Pullano et al. (2020) for transmission within France; Jia et al. (2020) for transmission from Wuhan, China).

Having reviewed the available options, we return to our motivating conditions: An optimal modeling approach must be _implementable immediately_ ; in any network of places where Covid19 infection data are available; scalable for entities of arbitrary size; solely reliant on free, publiclyavailable data; rigorously grounded in proven methodologies; and, far from least, _capable of_

> 1 For a detailed review of applications in epidemiology, see Truscott and Ferguson (2012).

4
is from perfect democracy. Democracy can be used to assess the strength of the transition (World Bank 2002).

The polity index database contains information for most of the countries and years included in the study. This database has no information on Iceland at all and misses information for Bosnia and Herzegovina, Cyprus, Czechia, Hungary, Kosovo, Montenegro, Serbia, and the Slovak Republic for only one year in most cases. As in the case of returns to education, we use the 5-year average of the polity index to make it congruent with our schooling data.

It is important to note that we identified in the polity database those countries that emerged from countries that disintegrated during our period of study and assigned to them the polity rate of their origin country before their formal constitution as an independent state. The countries that dissolved during the period of study are the Soviet Union, Yugoslavia, and Czechoslovakia, giving way to the constitution of 24 independent states included in our sample. These countries are shown in Annex 3. Using this strategy, we were able to identify 231 data points included in the analysis.

To include trade openness in our analysis, we analyze trade as a percentage of GDP to account for the influence of trade on economic growth, which in turn can lead to labor market changes that affect wages (Calderon and Cantu 2019; Kapsos 2005; Majid 2004). This quantifies trade as the sum of exports and imports of goods and services measured as a share of GDP. To ensure data comparability, this trade information was obtained from the World Bank, which has been collecting information on this topic since 1960. Again, this was included in the database of analysis using its 5-year average, which provided information for 214 data points.

Using our unbalanced panel data of 48 countries in Europe and Central Asia (28 transition and 20 non-transition) we estimate the determinants of returns to schooling, which are defined as the 5
Greenspan Alan, _Testimony before the Subcommittee on Telecommunications and Finance of the Committee on Energy and Commerce,_ U. S. House of Representatives (25 May 1994).

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_ISDA_ memorandum, "Response to the BIS Market Risk Proposal" (2 August 1995). Jackson Patricia, "Risk Measurement and Capital Requirements for Banks", _Bank of_ _England Quarterly Bulletin_ (May 1995).

- _J P. Morgan,_ "RiskMetrics - Technical Document" and "RiskMetricsTM/RD: A regulatory dataset" (26 May 1995).

- _J: P. Morgan,_ "Response to the Basle Committee Proposal on the Supervisory Treatment of Market Risks" (2 August 1995).

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- Kupiec Paul and O'Brien James, "Recent Developments in Bank Capital Regulation of Market Risks", _FEDS Working Paper 95-51_ (December 1995).

- Merton Robert, "Financial Innovation and the Management and Regulation of Financial Institutions", _NBER Working Paper_ 5096 (April 1995).

- Price Waterhouse, _The Regulation of Market Risk: The Impact of the European Community's Capital Adequacy Directive and the Basle Proposals_ (1994).

- _Risk_ magazine (various issues and Special Supplements).

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- Weston Stephanie and Gray Brian, "The Supervisory Treatment of Banks' Market Risk", _Reserve Bank of Australia Research Discussion Paper_ 9408 (December 1994).
proportionate changes.<sup>2</sup> So it may well

> 1 A useful compilation of studies using panel data can be found in the August 2000 special issue of the _Journal of Development Studies_ ; see the introduction by Baulch and Hoddinott (2000).  The churning also stems in part from time-varying measurement errors, though plausible covariates have been evident in the studies that tested for this (see, for example, Jalan and Ravallion, 2000).

> 2 For further discussion see Amiel and Cowell (1999), Atkinson and Brandolini (2004) and Ravallion (2004).

3
# **<mark>Referencias Bibliográficas</mark>**

1. ONUSIDA/09.36S. 2009. “Situación de la epidemia de sida, diciembre de 2009”. <u>http://data.unaids.org/pub/Report/2009/jc1700_epi_update_2009_es.pdf</u>

2. UNAIDS/WHO. 2002. “Initiating Second Generation HIV Surveillance System: Practical Guidelines. UNAIDS/WHO Working Group on Global HIV/AIDS and STI Surveillance”. - <u>http://data.unaids.org/Publications/IRC pub02/jc742 initiatingsgs_en.pdf</u> 3. UNAIDS/WHO. 2004. “Second Generation Surveillance for HIV: The Next Decade”. - <u>http://data.unaids.org/publications/irc pub01/jc370 2ndgeneration_en.pdf</u> 4. Rodríguez-García R, World Bank Group. 2007. “Planning and Managing for HIV/AIDS Results. A Handbook”. <u>http://siteresources.worldbank.org/INTHIVAIDS/Resources/375798 1103037153392/Results_Handbook_31Oct2007.pdf</u> 5. Atkins D, Best D, Briss PA, et al. 2004. "Grading quality of evidence and strength of recommendations". BMJ 328 (7454): 1490 6. World Health Organization. 2009. “HIV Triangulation Resource Guide”. <u>http://data.unaids.org/pub/Manual/2009/20090915_hiv_triangulation_resource_guid e_en.pdf</u> 7. Downs S, Black N. 1998. “The feasibility of creating a checklist for the assessment of the methodological quality both of randomized and non-randomised studies of health care interventions”. J Epidemiol Community Health 1998; 52; 377-384.

8. World Health Organization. 1999. “Sexually Transmitted Infections Prevalence Study Methodology. Guidelines for the implementation of STI prevalence surveys”. <u>http://www.wpro.who.
Iizumi, T. and Wagai, R. (2019) ‘Leveraging drought risk reduction for sustainable food, soil and climate via soil organic carbon sequestration’, _Scientific Reports_ , 9(1), p. 19744. doi:10.1038/s41598-019-55835-y.

Imran, M., Zurita ‐ Milla, R. and Stein, A. (2013) ‘Modeling Crop Yield in West ‐ African Rainfed Agriculture Using Global and Local Spatial Regression’, _Agronomy Journal_ , 105(4), pp. 1177– 1188. doi:10.2134/agronj2012.0370.

van Ittersum, M.K. _et al._ (2013) ‘Yield gap analysis with local to global relevance—A review’, _Field Crops Research_ , 143, pp. 4–17. doi:10.1016/j.fcr.2012.09.009.

Jain, M. _et al._ (2016) ‘Mapping Smallholder Wheat Yields and Sowing Dates Using MicroSatellite Data’, _Remote Sensing_ , 8(10), p. 860. doi:10.3390/rs8100860.

Jensen, N.D., Barrett, C.B. and Mude, A.G. (2016) ‘Index Insurance Quality and Basis Risk: Evidence from Northern Kenya’, _American Journal of Agricultural Economics_ , 98(5), pp. 1450– 1469. doi:10.1093/ajae/aaw046.

Jensen, N.D., Mude, A.G. and Barrett, C.B. (2018) ‘How basis risk and spatiotemporal adverse selection influence demand for index insurance: Evidence from northern Kenya’, _Food Policy_ , 74, pp. 172–198. doi:10.1016/j.foodpol.2018.01.002.

Karlan, D. _et al._ (2014) ‘Agricultural Decisions after Relaxing Credit and Risk Constraints*’, _The Quarterly Journal of Economics_ , 129(2), pp. 597–
37 Bangladeshi surveys in 1983 and 1985 asked pill users the brand name(s) of their oral contraceptive. This survey found that pill use increased for all brands from government, CSH and commercial sources. The proportion using both CSH and commercial pills increased while the proportion using government pills decreased. Vhile it is difficult to ascertain vhat would have happened to the volume of commercial sales in the absence of the socially marketing effort, this suggests that they vere at least not hindered by the CSH program and may have been helped by it.

Contraceptive social marketing in countries xn which contraceptive prevalence is high and where the commercial sector plays a more important role may have less of an overall impact on contraceptive prevalence because of substitution avay from government and commercial sources. Further, there is some evi4ence that vhen higher income groups are targeted, as they were in Colombia, there may be greater substitution avay from commercial products (Binnendijk, 1985).

In Sri Lanka, the Preethi condom vas launched as a socially marketed product in 1973. A survey of Preethi users one year and one half after the advent of the program suggested that 65 percent vere new contraceptors. The remaining 35 percent was divided among those who had used oral contraceptives, IUDs, traditional method and other condom brands (Davis and Louis, 1977). An estimated four percent had switched to the Preethi brand from another condom brand.

Evidence from the Dominican Republic suggests that commercial sales can decline substantially after a socially marketed product is introduced. The SOMARC project together vith the Dominican Republic government chose to market Hicrogynon, a Schering Ag brand of oral contraceptives as the social marketing product. The commercial price of Microgynon was cut in half and it was promoted through local advertising channels. After the launch of Microgynon as the social

**fl.tfp:Paily** Plamning **Papr 'dOwle)**
range of countries for a range of values obtained from the literature for the three key parameters �q; �I and �.

# 3 Data description

Assessing the national wage e¤ects of immigration to and emigration from diverse set countries across the globe requires country-level international migration and labor force data by skill level. The detailed description of the migration data is in the Data Appendix. Here we describe brie‡y the main sources and features of the migration and labor force data used.

## 3.1 International migration data

The relevant migration ‡ows to be used in our exercise are immigration and emigration ‡ows (namely gross ‡ows of immigrants and emigrants net of returnees and re-migrants). They capture the change in actual supply of migrants in a country.

There are several sources for migration ‡ows by receiving country (e.g. OECD International Migration database, UN migration statistics) but those only include gross in‡ow of people in a country and they almost never correct for migrants who leave or go back to their country of origin. Moreover they never record undocumented migrants and they often

> 5The externality is expressed in terms of the ratio between labor composite. Such a ratio, however, is almost identical to the share of workers with high schooling in the labor force.

8
during the Republic of Yemen’s conflict (e.g., Tandon and Vishwanath 2020; Tandon and Vishwanath 2021; Favari et al. 2021; etc.). These estimates suggest that well-being was likely not trending leading up to displacement, and the estimates are not picking up some of these changes as opposed to the immediate impacts of forced displacement.

And second, our results are consistent with displacement in fact being forced, as opposed to households being pulled towards better economic opportunities. Average violence was surging leading up to displacement in our data, and a wide variety of other evidence further suggests that violence was a pivotal factor in displacement during this time period (e.g., TFPM 2016; OCHA 2018; D’Souza et al. 2022; etc.); and among households that would be most likely to migrate due to economic conditions (e.g., those with the worst pre-displacement food access), the results show an identical and dramatic initial drop in food access as opposed to an improvement in food access that might have occurred had these households migrated towards better economic opportunities.

Our results contribute to the literature describing the consequences of forced displacement. First, this is the first analysis we are aware of that is able to arguably identify the impact of forced displacement on food access using data immediately before and after households become displaced.<sup>4</sup> Having pre-displacement data collected from households that would later become forcibly displaced allows us to demonstrate that households are not likely migrating due to sharp changes in economic factors, and further allows us to more precisely estimate the immediate impacts of displacement than comparing post-displaced outcomes of the forcibly displaced to host populations.

Second, these results demonstrate that households are surprisingly resilient to displacement in the Republic of Yemen in a critical welfare dimension. In part, this is likely due to a well-targeted increase in humanitarian assistance, which further offers support to a growing body of literature demonstrating that social protection schemes that reach world. These indicators are
. Sub-Saharan Africa Transport Policy Program (SSATP).

- ———. 2007b. Republic of Benin Transport Assessment Note for Roads, Airports and Port Sectors. Africa, Transport Sector (AFTTR) Report 40178-BJ. Washington, DC. June.

- ———. 2007c. Memorandum Economique du Benin: Mission d’évaluation du secteur portuaire. Cotonou, October 31–November 4, 2007. Aide Mémoire.

- ———. 2010. Project Appraisal Document. First Phase of the Abidjan-Lagos Trade and Transport Facilitation Program. February 25, 2010. Transport Sector. Country Department AFCRI. Africa Region. Report 49368-AFR.

World Health Organization. 2009. Global Status Report on Road Safety: Time for Action. Geneva.

World Road Statistics. 2007. Data 2000–2005. International Road Federation. 2007.

47
movement of natural persons. A pre‐commitment approach will allow such pre‐ conditions to be put in place and ensure that there is an agreed timetable to open markets to greater competition. Explicitly recognizing that services liberalization cannot – and should not be – divorced from services regulation will do much to help harness the potential that trade agreements have to expand services trade and investment.

# **References**

- Abbott, K. and D. Snidal, (2000). “Hard and Soft Law in International Governance,” _International Organization_ 53(3): 421–56.

- Adlung, R. and M. Molinuevo (2008). “Bilateralism in Services Trade: Is there Fire behind the (BIT‐) Smoke?,” _Journal of International Economic Law_ 11(2): 365‐409.

- Adlung, R. and P. Morrison (2010). “Less than the GATS: ‘Negative Preferences’ in Regional Services Agreements,” _Journal of International Economic Law_ 13(4): 1103‐43.

- Adlung, R. and M. Roy (2005). “Turning Hills into Mountains? Current Commitments under the General Agreement on Trade in Services and Prospects for Change,” _Journal of World Trade,_ 39: 1161‐94.

- Arnold, J., B. Javorcik and A. Mattoo (2007). “The productivity effects of services liberalization: Evidence from the Czech Republic,” World Bank Policy Research Working Paper 4109.

- Arnold, J., A. Mattoo and G **.** Narciso (2008). “Services Inputs and Firm Productivity in Sub‐Saharan Africa: Evidence from Firm‐Level Data _<u>," Journal of African Economies</u>_ <u>, 17(4): 578‐99.</u>

- Arnold, J., B. Javorcik, M. Lipscomb, and A. Mattoo (2010), “Services Reform
and public sector management and institutions. Individual policy scores are collected from the World Bank through surveys of its staff. For each policy, a score between 1 and 6 is provided, with higher scores indicating higher degrees of policy and institutional effectiveness, making the CPIA actually more a matter of resilience than of fragility. These scores are averaged at both the cluster and country level to provide an overall CPIA score falling between 1 and 6, with an unweighted average score of 3.2 or less generally seen as the threshold of state fragility. However, in our analysis, we treat state fragility as a continuum rather than a binary concept. We, therefore, refer to state fragility more broadly as countries with lower CPIA score without using the 3.2 cutoff point.

CPIA scores are available since 1977 for World Bank client countries though only those for low-income IDA-eligible countries are published. However, in our sample we focus on the period 1998-2019 to ensure comparability of CPIA scores to account for several changes occurred to the methodology over the years (see Gonzalez and Nishiuchi, 2018, for an overview). For the sample, we concentrate on countries without too many missing values for the CPIA. This means we leave out from the sample a number of World Bank client countries that have high-income status. As these countries would typically have high CPIA values, there would be little to explain from the covariates.

As a robustness check later in the paper, we also perform part of the analyses with another measure of fragility, namely the Fund for Peace’s Fragile States Index (FSI). This index consists of five groups of indicators measuring state cohesion, economic conditions, political legitimacy and public service provision, social conditions, and external intervention. The FSI is only available from 2006 onwards. We therefore do not use it in our baseline analysis, which spans a longer timeframe. The FSI also covers more countries than the CPIA in the sense that the latter has missing values for a fair number of developed OECD countries
starts to export and following entry into export markets, the value of exports as a proportion of sales) and on output and inputs is drawn from the Prowess database. Prowess is a corporate database that contains normalized data built on a sound understanding of disclosures of over 20,000 companies in India. The database provides financial statements, ratio analysis, fund flows, product profiles, returns and risks on the stock market etc. The Centre for Monitoring the Indian Economy (CMIE), which collects data from 1989 onwards, assembles the Prowess database. The database contains information on 23,168 firms 12
# **3. Econometric Methods**

The econometric analysis of contingent valuation data depends on the chosen formulation of the question. The choice between closed-ended questions or "payment cards" depends on several factors. Because of its specific nature closed-ended questionnaires "eat up" a lot of data. Since the identification of an effect rests on the random amounts offered to different individuals, one needs a large sample to achieve statistically significant effects. For similar reasons, the results are more likely to be misleading when a single closed-ended question approach is applied to a small sample.<sup>21</sup> When an open ended question is used, the result is usually analyzed by regressing the contingent valuation on a set of explanatory variables using OLS. We will use this approach as a benchmark. To analyze the answers from closed-ended questions, researchers initially used to run a simple logit or probit model where the explanatory variable was the offer, or the log of the offer. However Cameron and James (1987) show that there is an important difference between the traditional logit/probit model and the dichotomous choice generated by a closed-ended questionnaire. In particular, while in the traditional logit (probit), the β′ _s_ and the σ cannot be identified separately, this is possible in the statistical model generated by the closed-ended contingent valuation model. The reason is the following. Imagine that we ask individuals to report their willingness to pay an amount of taxes _T_ in order to enjoy a new national park. If they accept to pay that amount then _I_ = 1. Otherwise _I_ = 0 . Then where *<sup>_T_</sup> _i_<sup>is the unobserved upper limit of the willingness-to-pay of individual i. The</sup> willingness to pay is function of some variables which we can group under _xi_ .

where _ui_ follows a normal distribution. By the usual reasoning in probit models then

> 21 Cameron and Huppert  use a simulation to generate single closed-ended responses from a "payment card
Policy Research Working Paper 5966

# **Abstract**

Swaziland and Lesotho have the highest HIV prevalence in the world. They also share another distinct feature: during the last century, they sent a large numbers of migrant workers to South African mines. This paper examines whether participation in mining in a bordering country affects HIV infection rate. A job in the mines means leaving for long periods away from their families and living in an area with an active sex industry. This creates potential incentives for multiple, concurrent partnerships. Using Demographic and Health Surveys, the analysis shows that migrant miners ages 30-44 are 15 percentage points more likely to be HIV positive, and women whose partner is a migrant miner are 8 percentage points more likely to become infected. The study also shows that miners are less likely to abstain or use condoms, and female partners of miners are more likely to engage in extramarital sex. The authors interpret these results as suggesting that miners’ migration into South Africa has increased the spread of HIV/ AIDS in their countries of origin. Consistent with this interpretation, the association between HIV infection and being a miner or a miner’s wife are not statistically significant in Zimbabwe, a country where the mining industry is local and does not involve migrating to South Africa.

This paper is a product of the Human Development and Public Services Team, Development Research Group. 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 authors may be contacted at l.corno@ucl.ac.uk and ddewalque@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