rafmacalaba/data-use-mentions-extended huggingface dataset:
16 Chile during the 19809. Finally, an interesting observation derived from our estimates is that the proportion of women affected by the MW is lower than that of men. One interpretation for this is that women affected by the MW withdraw themselves from the labor force and work in the informal sector and in other productive activities which are not totally taken into account by labor force surveys. Moreover, it has been observed that the average women participating in the labor force has an above-the-average human capital, and it is likely that on the average the pi portion of women covered by the MW is in fact less than that for men.

The estimates presented in Table 4 have been based on the total predicted wage computed with the OLS estimates of [81. As discussed above, this method underestimates the actual coverage of the MW. In order to analyze a more accurate computation, we should compute the change in the cumulative wage function with regard to changes in the MW for a given human capital level. The computed density function (DF), which corresponds to the change in coverage with increases in the MW, are presented in Table 5 for the years 1980 and 1985, and for some specific experience and schooling years.

As shown in Table 5, the proportion of young individuals affected by an increase in the MW appears extremely high (between 40 percent and 50 percent). In the case of the older, more experienced group, the potential coverage decreases substantially between 1980 and 1985, suggesting this group is more affected by elements related to a contractionary global economic situation. In general, however, one may conclude that, in considering the potential coverage seen for both 1980 and 1985, the relative change in MWs is more binding for the young than for the older group. This is consistent with the relatively larger expansion of unemployment among the young between those years, at the same time that the prevailing MW is more binding in terms of real levels (Figure 1).18
level of the treatment variable).<sup>10</sup> Callaway and Sant’Anna 2021 warn about potential biases in staggered DID in the presence of dynamic treatment effects. These challenges result from the two-way fixed effect (TWFE) estimator making “forbidden comparisons” between treated firms and those previously treated (as well as those not yet treated). Past treated units may not have a parallel trend to the current treated group, because of dynamic treatment effects. These biases can be large when there is a large proportion of treated units, which is fortunately not the case in our context - fewer than 1% of treated firms in our sample (see Table 1). Callaway and Sant’Anna 2021 present an event study estimator that compares each cohort of firms entering the entity list, against those firms that are never treated and not yet treated cohorts as a control group.

To explore possible mechanisms, we examine how treatment effects differ across groups of firms (e.g., those with existing US collaborations), introducing a triple difference. Unfortunately Callaway and Sant’Anna 2021 cannot estimate triple (or continuous) treatment effects, and therefore we retain the two-way fixed effects model as our baseline and verify the robustness to employing the Callaway and Sant’Anna 2021 estimator.

The identifying assumption of our DID analysis is that the patent activity in both the treatment and control groups follows the same trend before sanctioned firms are added to the Entity List. Figure 4 shows that the sanctioned and unsanctioned firms exhibited parallel trends before the sanctioned firms were added to the Entity List (using the Callaway and Sant’Anna 2021 estimator). Kahn-Lang and Lang 2020 argue that tests of parallel trends may be under-powered and suggest verifying also differences in pre-treatment levels between the treatment and control groups. In Table A.2 we are unable to reject balance in the level of (pre-treatment) patent outcomes and (pre-treatment) covariates.

Figure 4 shows a slightly negative effect of U.S. sanctions on sanctioned
In fieldwork, a sufficient number of households must be assigned each optional module to obtain a reliable total consumption estimate. In wave 2 of the SHFS, this was ensured by interviewing 12 households per EA allowing for the ideal partition of three items per optional module.

# Consumption estimation

Household consumption was then estimated using the core module, the assigned optional module, and estimates for the remaining optional modules where K<sup>∗</sup> ∶��1, ... , k<sup>∗</sup> �1, k<sup>∗</sup> �1, ... , M� denotes the set of non‐assigned optional modules. Consumption of non‐assigned optional modules was estimated using multiple imputation techniques taking into account the variation absorbed in the residual term (Pape and Mistiaen, 2018). Multiple imputation was implemented using multivariate normal regression based on an EM‐akin algorithm to iteratively estimate model parameters and missing data.<sup>9</sup> The standard errors capture the error distribution of the multiple imputation process. The underlying model is a welfare model relating consumption to key household characteristics thus explaining 71 percent of variation in food consumption and 64 percent in nonfood consumption. The model parameters were household size, share of children in household, share of seniors in household; household head gender, employment, and education; dwelling type, dwelling drinking water access, dwelling floor, and dwelling ownership status; household experience of hunger; receipt of remittances; population type (urban, rural, IDP, nomadic) and a region‐ population type interaction, as well as each household’s core consumption quartile.<sup>10</sup> Pape and Mistiaen (2018) demonstrate that the Rapid Consumption Methodology yields reliable estimates of poverty using an ex‐post assessment with household budget data from Hargeisa and mimicking the Rapid Consumption methodology by masking consumption of items that were not administered to households.<sup>11</sup
data available from household consumption surveys to measure the welfare implications of various types of digital technologies, that is, mobile phone access, fixed broadband Internet, and mobile broadband Internet.

The analysis applies a robust methodology that can be used to assess the impact of mobile and fixed broadband Internet across Sub-Saharan Africa as more data on coverage and connectivity become available. In addition, the results contribute an important perspective to the policy discussion on the degree to which digital infrastructure can serve as a welfare- and resilience-enhancing mechanism. By demonstrating that broadband coverage can improve consumer welfare and reduce poverty, the paper supplies evidence on the positive spillovers of connectivity. This empirical evidence can be useful to policy makers in addressing public investment gaps across various sectors of infrastructure.

The rest of the paper is structured as follows. Section 2 describes the data sources, while section 3 presents the estimation strategy. Section 4 discusses the results, and section 5 concludes.

> http://www.africabandwidthmaps.com/. Internet traffic in countries runs first through national backbone or fiber-optic networks, which are then connected to end users through last-mile infrastructure, such as fiber cables, copper cables, wireless transmission, or cellphone towers. 2G, 3G, and 4G mobile coverage maps have been obtained from three major telephone communication providers—Orange (or the local subsidiary Sonatel), Senegal Expresso, and Tigo—and Mobile Coverage Maps (database), Collins Bartholomew, HarperCollins Publishers, Glasgow, https://www.collinsbartholomew.com/mobile-coverage-maps/.

> 4 Bahia et al. (2020) are a notable exception. They explicitly test the impact of 3G and 4G technologies on consumption and poverty using data on Nigeria.

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industry, they also herald a world that is shifting from person-to-person interactions and paper transactions toward fully digital, remote access transactions. Moreover, the same technological advances that enable new, more efficient ways of doing business are also responsible for a constant increase in reported vulnerabilities. Given these twin developments, it is critical to implement the most robust security measures, policies, and procedures possible.

As system risks are inherent in every network system, proper risk mitigation is integral to maximizing the safety and soundness of U.S. TreasuryDirect. Among the strengths of the new TreasuryDirect system is the use of the Pay.Gov database that relies on several information databases to verify customer identification. However, this might be harder to replicate in emerging markets due to lack of reliable informational databases in most of these countries.

The TreasuryDirect’s network system relies on five key security mechanisms: firewalls, intrusion detection systems (IDS), password authentication, Secure socket layer (SSL), and the annual GAO e-security audits. It is important to understand the strengths and weaknesses of each of these mechanisms.

Glaessner, Nevin and Kellermann (2002) developed a risk management framework for understanding the trade-offs and risks inherent in electronic security infrastructures. A main conclusion is that the efforts to mitigate e-security risks should not be overly reliant on any single security mechanism. Instead, layered security systems should be used.

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contexts. Our heterogeneity analysis suggests that the ability to respond to government restrictions varies, which enables economic activity despite mobility restrictions. The nature of government containment policies could also vary, and different types or intensity of policies could produce qualitatively different aggregate responses. Second, the main results reported in nighttime light intensity cannot be directly converted to GDP, and we can at best report a range of estimates based on past studies. Using elasticities from a cross-country study accounting for a country’s level of development (Hu and Yao 2019) suggests that Red zone districts had between 12.4 and 18.6 percent lower GDP than Green zone districts in May and on average between 8.9 and 13.4 percent lower GDP from May to July. However, the elasticity of nighttime lights to GDP might have changed during the COVID-19 pandemic and, moreover, may not be equal across districts. Third, we do not develop a comprehensive model of epidemics and pandemics, associated containment policies and the corresponding economic response. Absent such a model, policy counterfactuals such as more targeted containment or subsidies for private initiatives are difficult to estimate.

Nonetheless, our work accounts for the role of government containment policies, which has been much debated around the world for the COVID-19 pandemic, on aggregate economic outcomes. We hope that the results will guide future research and policy analysis.

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Policy Research Working Paper 10426

# **Abstract**

Measuring poverty entails making interpersonal welfare comparisons, that should account for differences in prices faced by households, both over time and across space. This paper investigates the impact of seemingly minor differences in the practical implementation of price adjustments, by developing an analytical framework that is consistent with standard consumer theory and mindful of the data limitations faced by practitioners. The main result is at odds with common sense: even when multiple price indexes are available, say a food and a nonfood Consumer Price Index, it turns out that using a single price index, the total Consumer Price Index, to adjust the consumption aggregate is recommended. The practice of adjusting the components of the consumption aggregate separately, using matching deflators—food expenditure with the food index and nonfood expenditure with the nonfood index—can lead to a systematic bias in the welfare measure, and consequently in poverty and inequality measures. The direction of the bias can be easily predicted based on the price level and household consumption patterns. On the interplay between spatial and temporal deflation, the findings show that temporal deflation should be carried out before implementing adjustments to spatial cost-of-living differences. The paper illustrates these findings using the Islamic Republic of Iran’s 2019 Household Income and Expenditure survey: the bias in the headcount poverty rate due to incorrect deflation is substantive (5–10 percent for estimates at the national level, 15–20 percent in urban and rural areas, and more than 30 percent for district-level headcount rates). Higher-order Foster-Greer-Thorbecke poverty measures are even more affected.

This paper is a product of the Poverty and Equity Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at sredaelli@worldbank.org.

_The Policy Research Working Paper Series disseminates the
set of expectations. The paper concludes that the proposed framework provides a robust and low-cost approach to maintain reliable projections and scenario analyses that can be interpreted within the context of available economic outlooks, contributing to the capacity to monitor global food insecurity trends.

The model is based on historical associations between the prevalence of severe food insecurity and covariates that capture economic and structural drivers of food insecurity. All the data can be obtained from official public sources, and outlooks are available for the key predictors. The model was validated using holdout data that explicitly tested the model’s ability to forecast new data from

> 29One could argue that in order to be more accurate, the model should also include data on aid or supportive measures. However, since the modeling effort is itself motivated by a desire to trigger action, any resulting forecasts themselves should not bake in the assumed effect of assumed protective measures not yet taken. In a related early-warning early-action effort, Andr ́ee et al. (2020) provide more discussion on isolating the impacts of humanitarian action from forecast risk signals.

> 30A secondary challenge is that governments notoriously push back on governance indicators and no official data are widely available across countries. Since the objective of this paper is to produce outlooks that could help with resource allocation, the overall preference would be to reach sufficient accuracy using official or measured data that cannot be disputed alone.
the Functioning of the European Union that applies to EU member states, the WTO Agreement on Government Procurement (GPA) and recent vintage preferential trade agreements (PTAs) – embody not only generally accepted good PP practices but require that foreign firms be treated the same as national bidders. The main thrust of such agreements is to open procurement markets to foreign competition.

As do all trade agreements, national procurement regulations and international agreements that discipline PP practices include exceptions that allow governments to respond rapidly to emergencies in ways that may be inconsistent with the rules that apply in normal times. This might take the form of direct contracting for supplies from producers without going through the processes that normally would be used (Baxter and Casady, 2020). At the time of writing it is not yet possible to investigate the extent and effectiveness of emergency procurement measures taken by different jurisdictions.<sup>7</sup> Instead, we examine the relationship between precrisis attributes of public procurement regimes as reflected in indicators compiled by the World Bank and the trade policy behavior of countries in the first seven months of the COVID-19 pandemic. Most trade policy activism was observed in the initial months of the pandemic, reflecting the feasibility of applying trade policy instruments very rapidly. Similarly, trade measures can also be removed rapidly—and in principle should be to abide by WTO rules. Global excess demand for protective equipment and COVID-19 medical supplies was met with a massive supply response, attenuating the rationale for using trade policy instruments for an extended period.

> 6 The basic features of good administrative practice in public procurement are summarized in UNCITRAL (2014) and World Bank (2017).

> 7 Comprehensive and comparable information on whether and how governments diverged from normal practices in procuring supplies does not exist. Cocciolo et al. (2020) and OECD (2020a) discuss procurement challenges and experiences during the first seven months of the COVID-19 pandemic.

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NUE of 13. Harou et al. (2017) also use the MTPF data from the late 1990s to estimate fertilizer profitability in Malawi. The authors find that bundles of fertilizer distributed under FISP (100 kilograms) are almost always profitable on average in Malawi, and profitability of fertilizer is robust to tripling of fertilizer prices, and to a 50% decrease in maize price and to drought. The objective of our paper is to build on the previous literature using the most recent data in Malawi from a nationally representative sample of panel households, along 5
practitioners. This conclusion becomes even more forceful when taken together with the comparison of the time required for GPS compared to CR measurement, with our data showing GPS to lead CR by several orders of magnitude.

This strong message in support of the adoption of GPS in survey fieldwork, is, however, mediated by a number of considerations regarding outstanding challenges with GPS measurement. One that emerges from the analysis is that while the GPS measurement error is almost universally small in magnitude (only 5 percent of observations recording a discrepancy with CR of more than 0.09 acre), in relative terms a discrepancy of plus or minus 10 percent is not uncommon. However, as illustrated, the CR method is not immune to measurement error thus some of the problematic cases could be attributable to noise in the CR data. Considering that GPS measures in large scale surveys are often plagued by a missingness rate in the range of 15-30 percent, which suggests that a large scale dataset of GPS plot measurements could be plagued by as much as 50 percent problem cases. Complementing data collection with information that can aid in identifying those problem cases, as well as enforcing sound field implementation protocols, can significantly reduce both bias and missingness in GPS measures.

Despite the evidence that subjective measurements can be riddled with problems, farmer self-reported estimates of area should still be included in household surveys, but not as the primary measurement method. Objective measurements come with their own challenges, including time and equipment requirements, questions of accuracy at small-plot levels, and feasibility of full plot sample measurement. Subjective measurements have negligible fieldwork costs, and, more importantly, they can serve as a baseline for imputation where objective measurements may be missing (Kilic et al. 2013). Therefore, we recommend GPS measurement (where feasible) complemented by farmer self-reported estimated area (for all plots).

An ancillary story emerging from the data concerns self-reported data. While confirming all the known issues with measurement error in self-reported land data, the analysis presented here provides at least one
.

> 9 `https://blogs.worldbank.org/opendata/new-world-bank-country-classifications-income-level-2022-2023`

> 10Some economies, such as Malta, Réunion, Taiwan, and Hong Kong, do not have their income information recorded in the World Bank income data. As a result, they are excluded from the regression analysis that involves income level. However, they are included in the regression analysis when income level is not a factor.

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of _c_ can be obtained as follows: _c_ = (345880 _/_ 200) _/_ (475150 _/_ 3200) _≈_ 12.

We have also collected similar budgetary information for several household surveys through personal communications. We then computed _c_ in a similar manner. Table 3 summarizes all the estimates of _c_ we have obtained using the budgetary information we obtained from personal communications. Based on this table, we choose to use the following values of the cost ratio: _c ∈{_ 4 _,_ 16 _,_ 64 _}_ .

Note that the cost calculations are based on average cost. Because the actual cost function for a survey depends on the logistical arrangement and is in general not exactly equal to eq. (16), the marginal and average costs are likely to differ. For example, we would not need to incur additional training cost to just add one more household to the sample. However, if we scale up the survey significantly, it is likely that we need to increase most of the cost components, such as the costs of personnel, travel, and materials. Therefore, the calculations of _c_ provided in Table 3 should be taken as approximations.

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. While these more modest associations are not illustrated in table 2, the simulations that are shown demonstrate that the selectivity mortality would only have a large impact on observed anthropometrics if there were very large differences in anthropometrics between the children who died and those who survived. Current research on the association between mortality and malnutrition does not substantiate such large differences.

# **_Simulations Based on a Proportional Hazard Model_**

The simulations discussed in the previous section were based on imputations of a few categories of height-for-age data to the children in the sample who had died. It is more realistic to assume that children‘s anthropometrics and survival depend on their individual characteristics, prenatal conditions, health of the mother, and those of their household (Wolpin 1997). To approximate this, children who died were matched with children who survived past the age of 36 months using the estimated survival hazard as a matching score. The anthropometric scores of children who survived were then imputed

> **7** Boerma et al (1992) demonstrate that the differences in malnutrition between the children who died after the measurement and who survived a specified time period in longitudinal studies in Indian states of Tamil Nadu and Punjab were relatively small: height-for-age z-scores of 60 percent of dead children were lower than -2 SD from the mean compared to 50 percent among survivors.

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