rafmacalaba/data-use-mentions-extended huggingface dataset:
of forced migrants, the PEP became a benchmark for a development-based approach to the current predicament.

Regularization (or legalization) programs give migrants legal residence and thus access to the rights and services enjoyed by citizens, including the right to work. These programs, which grant temporal benefits but typically exclude voting rights, have been implemented in the United States, Europe, Latin America, and LMICs in response to a sharp increase in irregular migration. Despite their prevalence, these programs are highly controversial. Critics claim they encourage irregular migration, lead to job displacement and unemployment for natives, increase crime, and burden social welfare and public finances. Yet, prior research has demonstrated negligible effects on employment opportunities for natives and shown reductions in migrants’ crime rates (Bahar et al. 2021; Pinotti 2017; Baker 2015). Furthermore, from a theoretical perspective, regularization programs may produce positive effects for both migrants and host societies. The right to work means migrants may rely less on social welfare and be more likely to pay taxes, more productive by working in occupations more closely related to their skills, and more inclined to invest in their children’s human capital. Research on long-term migration has established positive effects on host countries and shown that these effects are or faster if are to eco- larger migrants permitted integrate nomically (Abramitzky and Boustan 2022).

The features of PEP facilitate causal identification of its effects. First, the program was introduced decisions or ex-ante behavioral re- unexpectedly, thereby isolating anticipatory Unknown to both and for the sponses. migrants government officials, ex-post eligibility program was based solely on prior registration in a nationwide census of irregular forced migrants, the _Registro Administrativo de Migrantes Venezolanos_ (RAMV for its Spanish acronym), that was administered between April and June of 2018. According to the government officials who designed RAMV, the census was implemented to count the number of irregular Venezuelan forced migrants in Colombia and was not intended to precede or lead to a regularization program. However, in August 2018, Colombia
informal firms, which is due to their ambiguous legal status, lack of proper accounts, and the lack of credit-rating procedures relevant to informal firms. Because of the small absolute size of the loans required by informal firms, it should be feasible to support alternative procedures for the provision of credit.

Third, putting the emphasis on exports requires significant improvements in the investment climate. With poor infrastructure and a weak regulatory system, Africa is at a disadvantage in this context, and reforms are urgently needed. Not all reforms may be required at once, however, and focusing growth efforts on a specific sector or location can save money. There is clear-cut evidence that sound economic policies make a difference. In Madagascar, for instance, the creation of an efficient export processing zone led to a very rapid expansion in the textiles and garment sector, and in Mauritius the investment climate played a major part in transforming the economy in less than 20 years. In some cases, access to firm-level panel data has made it possible to measure the effects of macro policies on different types of firms with greater precision than what has been possible with aggregate data. Gauthier, Soloaga and Tybout (2002) provide a case study of the Cameroonian experience, see Box 2.

The basic point is that Africa must try to take advantage of the existing opportunities, and take action where the problems are most acute. We know that African manufacturing firms have the potential to perform well. We mentioned in the introduction that one of the most striking results that have come out of the work on the firm data is that there is large variation in performance within sectors and countries. In recent years, while most firms may have experienced limited success, some have performed very well. These tend to be exporters. To enable more firms to achieve similar levels of performance, the adoption of new technology and orientation towards new markets must feature as key components of African industrial policy. Policies that provide incentives and means to firms to adopt a scientific strategy are likely to
Transparency itself is also significant at the .05 level, and each 0.5-point improvement on its 1-6 scale is associated with an increase of 4 percentage points in use of country PFM systems.

Equation 2.4 adds a dummy variable for 12 “fragile states” (listed in OECD, 2011a: 104). In 2007 the OECD-DAC adopted a set of “Fragile States Principles” reflecting a view that they had different problems requiring special treatment in comparison with better-performing aid recipients. One of the 10 principles calls for “a focus on state building as the central objective,” suggesting that use of country PFM systems may be higher in fragile states than otherwise expected, based on income, size, etc. On the other hand, donors might rely less on country systems in fragile states, if these countries are perceived to involve extra risks to donors, beyond the risks measured by PFM Quality and Civil Liberties. Results in equation 2.4 suggest that the latter effect dominates. Use of country PFM systems is 10 percentage points lower on average in fragile states, other things equal, and this effect is significant at the .05 level. Controlling for the fragile states dummy, coefficients for PFM Quality and Civil Liberties are somewhat smaller than in the baseline specification of equation 1.3, but they remain significant at the .01 level.

Equation 3.1 adds the percentage of aid for each donor-recipient pair that is in the form of direct budget support (DBS), as reported in the PDMS. Budget support (which comprises 12.5% of aid on average in our sample) uses country PFM systems, by definition. When this variable is included, the regression in effect is testing for relationships between the regressors and use of PFM systems for project aid and other non-DBS aid. Coefficients for PFM Quality and Civil Liberties are again somewhat smaller in 3.1 than in 1.3, but they remain highly significant.

Results for PFM Quality are potentially weaker for donors other than the World
Our statistical procedure extracts appropriate time trends from real interest rates even with short samples and high volatility. Equilibrium interest rate estimates from the seminal Laubach-Williams model (Laubach and Williams 2003) are very imprecise even for advanced economies. This is both due to a weak relationship between the output gap and the real interest rate gap and due to a weak relationship between inflation and the output gap. If these relationships are very weak, their model is unobservable and the equilibrium interest rate cannot be uniquely identified (Hamilton _et al._ 2016, Fiorentini _et al._ 2018). Those cases are already common for advanced economies, but the identification challenges are even more severe for EMDEs. First, many of them report only annual data, which makes it even harder to find a strong relationship between these variables and, second, EMDEs are more likely to have structural breaks in their data. Fiorentini _et al_ . (2018) show that if the interest rate gap is assumed to be stationary, the Laubach-Williams model can identify the equilibrium interest rate even when the relationships between the output gap, the interest rate gap, and inflation are weak. They also show that from this assumption it follows directly that the equilibrium real interest rate can be estimated with a univariate local level specification model that decomposes the ex-ante real interest rate into its permanent and transitory component. Instead of ARCH, we use a stochastic volatility model to allow for time-varying variance of the interest rate gap and estimate it with Bayesian methods, which is more suitable for EMDEs.

Our study contributes, first and foremost, to the large literature on estimating equilibrium interest rates. The equilibrium rate of interest is a theoretical concept and cannot be observed. The most prominent methodology to estimate it, based on a semi-structural model of Laubach and Williams (2003), provides only very imprecise estimates and even minor modifications of the model or the estimation strategy can result in very different estimates of equilibrium interest rates.<sup>3</sup> In addition, it is not
the potential benefits of formalization verbally described, and advisors helped firms with the paperwork as needed. The second treatment aimed to enhance the benefits of formalization by also offering business training and support opening a business bank account if they formalized. The third treatment built on the second by offering tax mediation services, with the goal of providing protection and assurance against fear of the tax administration. A supplementary treatment provided information in the form of leaflets and a verbal explanation to see whether information alone had an impact.

We use administrative data on formalization coupled with two rounds of follow-up surveys to measure the impact of these treatments. Only 2 percent of the control group formalized over a 3
- <mark>Hale, T., Angrist, N., Goldszmidt, R., Kira, B., Petherick, A., Phillips, T., Cameron-Blake E., Hallas, L. M., and Tatlow, H. (2021). A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker).</mark> _<mark>N</mark> ature Human Behaviour_ , _5_ <mark>(4), 529-538.</mark>

- Henderson, J. V., Storeygard, A., and Weil, D. N. (2012). Measuring economic growth from outer space. _American Economic Review_ , _102_ (2), 994-1028.

- IMF (2020a). _World Economic Outlook: The Great Lockdown_ , April 2020. Washington, D.C.: International Monetary Fund.

- IMF (2020b). _World Economic Outlook: A Crisis Like No Other. An Uncertain Recovery._ June 2020. Washington, D.C.: International Monetary Fund.

- <mark>Ju, M. J., Oh, J., and Choi, Y. H. (2021). Changes in air pollution levels after COVID-19 outbreak in Korea.</mark> _<mark>S</mark> cience of the Total Environment_ , _750_ <mark>, 141521.</mark>

- <mark>Khamis, M., Prinz, D., Newhouse, D., Palacios-Lopez, A., Pape, U., & Weber, M. (2021). The Early Labor Market Impacts of COVID-19 in Developing Countries. Jobs Working Paper No. 58. World Bank, Washington, DC.</mark>

- <mark>Kim, K. (2022). The North Korean economy seen by satellite: Estimates of national performance, regional gaps based on nighttime light.</mark> _<mark>J</mark
, in Dallas, available federal evaluation resources dropped by 65% between 1978 and 1983 (Webster, 1987, p.37). The impact of these reductions has fallen mainly on local evaluations of process and curricula.

At the same time, data on student achievement at the school level are enabling researchers to choose successful schools for deeper inquiry into the factors of school effectiveness (Cohn and Rossmiller, 1987).

The current focus of on minimum standards, achievement testing, and monitoring is not without controversy. Many educators and evaluators are concerned that intense public and media interest in comparisons of test scores across schools, districts and student ethnic and racial groups distorts the meaning of test data. It is argued that achievement tests provide narrow measures of the broad goals and achievements of schools, and that short-term political pressures on schools are accompanied by little in the way of positive resources. Reduced resources for process evaluation make it more difficult for education managers to develop information-based strategies to overcome school deficiencies. One evaluator notes that his state provides no funding for remedial programs for the schools that do not meet standards.
): From Table 2 in the text.

Column (3): Incidence per thousand in overall population from Table 1 of Ghana Health Assessment Team (1981).

Column (4): Appendix A of Grosse et al (1979). Column (5): Aggregates of the _ssx_ age-sex categories used in Appendices A and C of Grosse et al (1979).

Column (6): Calculated from the last two columns of Appendix C of Grows. et al (1979) by the formula (CFNRX-CFRX)/CFRX, where CFNRX is the case fataiicty rate without treatment, CFRX is the case fatality rate with treatment by a VHW.

Column (7): Derived from the incidence rates by age-sex group in Appendix A of Grosse et al by choosing a value in the mi4dle of the range of incidence races given in that source.
**Table 2: Evolution of the labor force module in household surveys, 1992/93 - 2009/10**

|Question<br>type|SURV<br>IHS 1|EY<br>992/93|UNHS|1999/00<sup>~~14~~</sup>|UNHS|2002/03|UNHS|2005/06|ÙNHS|2009/10|
|---|---|---|---|---|---|---|---|---|---|---|
||Yes<br>/no|Type|Yes/<br>no|Type|Yes/<br>no|Type|Yes/<br>no|Type|Yes/<br>no|Type|
|Employment<br>screening<br>questions?<br>Inactivity<br>measured<br>separately?|<br>No|_Activity status_<br>_responses also_<br>_include inactivity_<br>_variables_|No|Labor module is<br>restricted to 3<br>questions on<br>activity status<br>_Activity status_<br>_responses also_<br>_include inactivity_<br>_variables_|Partial|“During<br>the last 7<br>days did<br>[NAME]<br>engage in<br>a family<br>enterprise<br>or in any<br>kind of<br>work for<br>pay or for<br>profit?]|Yes<br>– 7<br>day<br>recall|Detailed –<br>separate<br>questions for<br>wage, family<br>farming, HE<br>_12 month_<br>_recall has no_<br>_separate_<br>_screening;
27 The checks variable, intended to reflect the number of independent veto players in a country, simultaneously captures some of the other institutional influences that have been the subject of scrutiny. For example, a closed list has the effect of reducing the number of veto players (by increasing control of party leaders over party members in the legislature); at the same time, the literature predicts that the introduction of a closed list should reduce incentives of individual candidates to appeal to special interests. Similarly, the effect of low voting thresholds in proportional representation systems is predicted to be the emergence of more smaller parties appealing to narrower constituencies. This should lead to governing coalitions with more parties, and therefore more veto players. The checks measure therefore allows the net effect of these countervailing institutional influences to be assessed.

The proximity of elections is the final institutional characteristic of countries examined below. A variable tracking the number of years to the next election, legislative or presidential, counting from the first year of the crisis, has been created from information in the DPI.

A key challenge in the analysis of special interest influence is often that special interests line up on both sides of policy debates. When this occurs, analysis of the institutional determinants of special interest influence must take into account the constituencies and supporters of different government veto players. In the case of banking crises, though, the need to do this is diminished by the fact that special interests tend to line up on the same side of regulatory issues. Government policies that permit imprudent banking tend to benefit narrow interests — recipients of sweetheart loans, bank owners and managers - at the expense one for each legislative chamber, and one ifthe fist government party is closer in political orientation (left, right or center} to the first opposition party than to the party of the president. If the legislature is closed list (voters must vote for parties and cannot register candidate preferences) and the president’s party has a majority in parliament, the legislature is not counted as a
8 postneonatal mortality across malaria zones reflects this phenomenon.<sup>6</sup> Table 2 shows neonatal, postneonatal, and infant mortality rates by characteristics, pooling data from 2003 and 2008. Neonatal mortality rates are statistically identical across malaria risk zones (approximately 36 per 1000 live births), while postneonatal mortality is lowest in low malaria risk zones (16 per 1000), slightly higher in intermediate malaria risk zones (20 per 1000), and three times as high in high malaria risk zones (62 per 1000).

ITN ownership rates have increased across Kenya, and the postneonatal survival gains have been chiefly in the high malaria risk areas, particularly rural Nyanza province but also urban Nyanza province as well as both urban and rural Western province. Figure 2 shows a scatter plot by province and urban/rural classification of postneonatal mortality rates vs. ITN ownership using the 2003 and 2008 DHS data. Figure 3 shows a similar plot for neonatal mortality. The geography of shifts over time that have taken place in neonatal mortality show no obvious correlation with malaria patterns.

It is important to recognize that the ITN measure used throughout this paper is _household ownership_ of at least one ITN at the time of the DHS survey. This differs from actual _usage_ of ITNs by individual children. Because information on ITN usage by deceased children is not available, it is not possible to use DHS data to examine the association between ITN usage and mortality. We thus take ITN ownership by the household is used as a proxy for ITN usage. ITN usage by children is highly correlated with the household‘s ownership of at least on net. In the sample, 82 percent of living children in households with at least one ITN slept under an ITN the night before the interview.

Table 2 summarizes comparisons of neonatal, postneonatal, and infant mortality rates by basic characteristics. As noted, postneonatal mortality is greater in high malaria risk zone and is significantly lower in households that own at least one ITN. This difference is significant both
example, with longer recall periods as well as seasonality of different activities among this population.

Looking at gender differences, the last two columns of Table 2 show that women are significantly more likely than men under both survey approaches to work in crop agriculture over the last 12 months — particularly in own-use production as opposed to market activity — and less likely to work in wage employment and _ganyu_ . Weekly hours, on the other hand, tend to be greater for men across both farm and off-farm activities.<sup>14</sup> While men are significantly more likely to report management of a non-farm enterprise than women under the business-as-usual approach, this difference disappears in the individual-interview approach. Figure 1 looks at gender differences across samples by age, finding that the individual-interview approach in the IHPS tends to raise reported wage employment and NFE management for nearly all men across the age distribution, but for women the largest increases in these activities are focused on younger age groups (around 30 years of age; for NFE management there is an additional increase among older women (55+) in the IHPS as well). For women, lower time constraints outside of their child-rearing years may be one reason for these trends. Generally, Table 2 shows that men’s participation across different

> 14 Within crop work, hours spent separately in market activity versus own-use production were not collected (and also would be very difficult to collect).

9
<!-- Start of picture text --> E. Government revenue, by population size,<br>2011-23<br>Percent of GDP<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>Micro states Other small states<br><!-- End of picture text -->

**F. Volatility of government revenue, 2000-23**

<!-- Start of picture text --> Standard deviation<br>10<br>8<br>6<br>4<br>2<br>0<br>exporters importers<br>Small states Small states: Commodity Small states: Commodity EMDEs excl. small states<br><!-- End of picture text --> _Sources_ : GFS (database); WEO (database); World Bank.

_Note_ : EAP = East Asia and Pacific; EMDEs = emerging market and developing economies; LAC = Latin America and the Caribbean.

A. Panel shows average revenue to GDP ratios in 32 small states and 110 other EMDEs.

B. Bars show the average revenue to GDP ratios for the period 2011-22. Small states include 34 economies, and EMDEs excluding small states include 97 economies.

C.-E. Bars show the average revenue to GDP ratios for the period 2011-23.

C. EAP small states include 13 economies, LAC small states include 11 economies, and other small states include 11 economies.

D. Small states commodity exporters include 13 economies, small states commodity importers include 22 economies, and tourism-reliant small states include 22 economies.

E. Micro states have a population of less than 200,000. Micro states include 14 economies, and other small states include 21 economies.

F. Standard deviation of annual change in revenue to GDP ratios in 35 small states and 113 other EMDEs for the period 2000-23. Small states commodity exporters include 13 economies, and
and the distribution of poverty across regions. In this paper, we provide a conceptual and quantitative understanding of the two non-standard features inherent in the official poverty lines of Egypt. We study which of these two non-standard features has the largest impact on poverty figures. We also investigate how Egypt’s poverty methodology compares with more standard methodologies, both in terms of identifying disadvantaged households and in terms of poverty comparisons over space and time.

We start by studying the poverty trend over the period 2015 – 2017/18. Over the period, the fraction of poor individuals has increased due to a negative shock to consumption. However, we show that the use of a comparable poverty line leads to an increase in poverty rate over the period about twice as large as that documented by the official poverty lines. Indeed, the poverty increase over the period can be

> 2 See Decerf (2022) for a recent survey of absolute and relative poverty measurement.

2
_Table 14: Share of the national population affected by droughts according to EM-DAT and LSMS-ISA data_

|Country|Year|Percent of the<br>population affected<br>by drought using<br>LSMS-ISA data|Percent of the<br>population affected<br>by drought using EM-<br>DAT data|
|---|---|---|---|
||2011 - 2012|7.88 %<br>[5.73 % ; 10.04 %]|6.20 %|
|Ethiopia|2013 - 2014|11.45 %<br>[ 8.83 % ; 14.07 % ]<br>|_missing_|
||2015 - 2016|32.50 %<br>[ 27.33 % ; 37.67 % ]|9.68 %|
||2018 - 2019|14.30 %<br>[ 10.88 % ; 17.72 % ]|_missing_|
||2009 - 2010|23.82 %<br>[ 20.44 % ; 27.20 % ]|_missing_|
|Malawi|2012 - 2013|8.98 %<br>[ 6.98 % ; 10.98 % ]|_missing_|
||2015 - 2016|25.51 %<br>[ 19.25 % ; 31.78 % ]|_missing_|
||2018 - 2019|7.66 %<br>[ 5.06 % ; 10.26 % ]|_missing_|
|Mali|2014|15.89 %<br>[13.35 % ; 18.43 %]|_missing_|
||2017|24.53 %<br>[ 21.54 % ; 27.53 % ]|_missing_|
|Niger|2011|56.14 %<br>[ 48.77 % ; 63.50 % ]|17
# **Table B1 – Perceived economic well-being explained by income, wealth, and usufruct conditions, 1991 and 2004-2016**

||**Mod**<br>|**el 1**<br>|**Mod**<br>|**el 2**<br>|
|---|---|---|---|---|
|**Variable**|**Parameter**|**p-value**|**Parameter**|**p-value**|
|**Income**|0.6138|<.0001|0.6150|<.0001|
|**Wealth**|0.0564|<.0001|-|-|
|**Adjusted wealth ***|-|-|0.0563|<.0001|
|**Usufructuary**|0.1549|<.0001|-0.0279|0.2978|
|**Bare owner**|-0.0043|0.9421|0.0624|0.2860|

Model = Cumulative probit regression.

Dependent variable = Subjective economic well-being: “Is your household’s income sufficient to see you through to the end of the month? 1 with great difficulty – 2 with difficulty - 3 with some difficulty – 4 - fairly easily – 5 easily – 6 very easily.

Sample size = 55,435 observations in 1991 and from 2004 to 2016.

Further variables included in the model: Year, Number of components (linear and squared), Geographical Area, Municipality size (inhabitants), Gender, Age, Education, and Civil status of the adult with the higher income.

* Adjusted estimates based on H1 assumption (i.e. usufructuary age = respondent age + 25; see the text).

Source: Our elaboration on SHIW data.