rafmacalaba/data-use-mentions-extended huggingface dataset:
l 1 w The error component, (yycch) = ββ , represents a community-level random effect that shifts the intercept of the 0cc + ββ xxcch + ηηcc + εεcch wwh h= 1, . . . , NNcc ; cc= 1, . . . , CC (1) regression up or down for each commune, while the household idiosyncratic error within communes cc ) ηη is assumed to be independent across all households in the sample. Both and are assumed to be cch (εε normally distributed as in ) , and ) . cc cch ηη εε cc ηη<sup>2</sup> cch εε<sup>2</sup> In the poverty mapping literature, multilevel models are often called nested-error models. Among several ηη ~ NN(0, σσ εε ~ NN(0, σσ In the poverty mapping literature, multilevel models are often called nested-error models. Among several estimation strategies, Empirical Best (EB) methods are preferred as they provide accuracy and efficiency gains over previous applications, such as Elbers, Lanjouw, and Lanjouw (2003), allow for the inclusion of random location effects and the recovery of location and household-specific idiosyncratic errors (Corral Rodas, Molina, and Nguyen 2021). In the nested-error model (Battese, Harter, and Fuller 1988), welfare (and poverty) are imputed into census data by using the census empirical best approach of Corral Rodas, Molina, and Nguyen (2021).

In the application here, model fitness is maximized by estimating equation 1 independently for each region in Senegal. For each region, the estimation steps detailed in Corral Rodas et al. (2022) are followed, in particular: (1) using the variance inflation factor (VIF) to remove highly collinear variables, (2) estimating a separate regression for each region, (3) dropping high-leverage observations, and (4) avoiding overfitting by limiting the set of right-hand-side variables using a Lasso regression.<sup>9</sup> The model
% indicated that by the time they were 19 years old they had already had a child and the average age when they had their first child was 22.4.

In terms of risk behaviors, 90% of males reported having consumed alcohol, 43% having smoked, and 10% having tried marijuana, which in the case of females occurs for 61%, 8% and 1% of them, respectively. These figures are consistent with those reported in national surveys (INPRF-INSP-Conadic, 2017b, c, a).<sup>12</sup> Table B.2 of Appendix B presents household providers’ main characteristics, as a whole and stratified by the age groups of the youth for whom they were providers. When compared to Table B.1, we observe that providers are on average 30 years older their children and, as expected, the average age is higher for providers of older youth groups, maintaining the same average difference of 30 years.

In terms of the main health indicator, height, we observe that the maximum height of providers is 2.8 cm lower for males, and 3.9 cm lower for females, compared to youth (Table B.1). When considering the relationship between height and weight, it is observed that the average body mass index (BMI) for males and females is in the overweight category, and as observed in the general population based on the national surveys, average BMI is higher for females than for males.

Cognitive and memory tests were performed when collecting data for ENCEL 2017; there is no estimate of these tests for the youth or providers at previous ages. Due to the cognitive deterioration expected with age (Cline _et al_ ., 1989), the providers’ age partly explains this group’s lower cognitive scores relative to the youth’s. While in the cognitive tests no differences are observed by gender, the memory score is higher for males in all cases.

The average years of schooling of providers, 3
</sup>|48,521<br>0.392|38,135<br>0.375|

Standard errors are in parentheses. All models control for firm age, ownership, export status, firm size (employment), proportion of permanent workers, proportion of skilled workers, 55 dummy variables indicating a narrow industry classification, and dummies indicating World Bank regions. All WBT categories are included separately in the model, in addition to the interaction terms. The reference category for climate zone is the bottom quartile in the distribution of WBT which is less than or equal to 23.7<sup>0</sup> _C_ . The minimum WBT in our sample is 14.5<sup>0</sup> C. FE = fixed effect; km = kilometers; OLS = ordinary least squares; WBT = wet-bulb temperature. _∗∗∗ ∗∗ ∗ p <_ 0 _._ 01, _p <_ 0 _._ 05, _p <_ 0 _._ 1

# Income Grouping

A key departure of this study from earlier studies is its use of a globally comparable database of nonagricultural firms across climate zones, regions, and income
37

# Table 2: Top 10 publications according to teachers and citations

|Rank|Teachers‘ ranking in 2004|Ranking based on citations in 2011|
|---|---|---|
|1|Arrow (1963)|Acemoglu et al. (2001)|
|2|Manning et al. (1987)|Arrow (1963)|
|3|Torrance (1986)|Grossman (1972)|
|4|Grossman (1972)|Becker et al. (1994)|
|5|Newhouse (1996)|Rodrik et al. (2004)|
|6|Pauly (1968) (tied 5<sup>th</sup>)|Therneau & Grambsch (2000)|
|7|Buxton et al. (1997) (tied 7<sup>th</sup>)|DiMasi et al. (2003)|
|8|Cutler & Reber (1998) (tied 7<sup>th</sup>)|Angrist et al. (1996)|
|9|McGuire & Pauly (1991) (tied 7<sup>th</sup>)|Dasgupta (1993)|
|10|Harris (1977)|Torrance (1986)|
|10|Labelle et al.(1994) (tied 10<sup>th</sup>)||

Note: The teachers‘ ranking was based on an interview of members of the International Health Economics Association as reported in Culyer (2006). The starting point for the rankings based on citations in 2011 was our database of 33,000 publications in EconLit with a health JEL code. Google Scholar citation data were obtained for as many as possible (80 percent) in June 2011.
cruelty, including rape, gang rape, stripping, insertion of objects into their body, and molestation (Hameed et al., 2002). This paper examines how women’s marriage age and postmarital socioeconomic status evolved in Gujarat after the 2002 riots. Even though several studies have examined the impact of Hindu-Muslim riots on several social, economic and political outcomes of interest, we specifically contribute to the literature by assessing the effect of the riots on women’s marital outcomes.

To examine the effects of the Gujarat riots of 2002 on women’s marital outcomes, we use a retrospective state-year level dataset from the fourth round of the National Family Health Surveys (2015-2016) and a difference-in-differences strategy. Our empirical strategy relies on variation over time in marriages that took place before and after 2002 and the statewise variation in the occurrence of riots. We also use the event study approach to observe differential trends in women’s age at marriage between Gujarat and the other Indian states. The difference-in-differences estimates suggest that age at marriage declined for women 2
||||
|Average Private Credit/GDP (MENA)|43.57||49.25||
|Average Private Credit/GDP (non-MENA)|57.49||54.70||
|Average EXTFIN (MENA)|0.239||0.250||
|Average EXTFIN (non-MENA)|0.285||0.258||
|Average TAN (MENA)|0.382||0.32||
|Average TAN(non-MENA)|0.316||0.30||

_Notes: Estimation results from Equation 2. Panel dimension: country-sector. Average EXTFIN and TAN values for MENA and non-MENA regions are simple averages of trade weighted country values. Source: WB staff calculations, BACI, EDD._ Similar to HRR (2006), a relationship is found between trade specialization and the interplay between property rights and asset tangibility (column 2, Table 4). Sectors with high shares of intangible assets are expected to benefit the most from secure property rights, the exact attribute that the GCI indicator captures.

Significant correlations between governance and asset tangibility level of export sectors are also observed when governance is proxied by the GCI Legal Rights index and World Governance indicators (columns 3-8). Considering the legal framework or governance factors of a country to be endowments, it can thus be expected that in countries with well-developed legal frameworks, trade is specialized in sectors having lower shares of tangible assets. When the legal framework is strong, banks are more likely to enter into contracts and less prone to worry about risks associated with default. The quality of a country’s legal framework influences financial sector development as well as the ease of access to external financing.<sup>20</sup>

> 20 La Porta, Lopez-de-Silanes, Shleifer, and Vishny, 1998; Jensen and Meckling, 1976; Williamson, 1988; Grossman and Hart, 1986; Hart and Moore, 1990; Hart, 1995

17
targets. The difference could stem from bureaucrat capacity, or simply inherent growth potential. Whatever the cause, however, falling behind the target increases the appeal to inflate GDP to reach the target. We thus compare cities that achieve the growth target in the annual _Report on the Work of the Government_ with those that fail. We expect that for the PS truthfully accomplishing the plan in the sense that the predicted true growth surpasses the target, he would be less likely to exaggerate the reported figure.

Our results from the last two columns of Table 5 support the hypothesis that falling behind the target increases performance manipulation. The political cycle effect is observed and pronounced in cities whose true performance failed to reach the target. In contrast, those whose targets have been met truthfully do not exhibit the same pattern in over-reporting GDP figures.

22
Policy Research Working Paper 10722

# **Abstract**

This paper presents distributional national accounts for Honduras over 2003–2019, using survey microdata, administrative tax records, and national account aggregates. It assembles comprehensive data on formal income for high-income individuals, including information on corporate shareholders, which allows corporate profits to be assigned to their owners. The estimates suggest a high and persistent inequality in the country: the top 1 percent highest earners received approximately 30 percent of the total income over the period, placing Honduras among the most unequal countries in the world. Undistributed corporate profits are the overwhelming income source at the very top of the distribution, highlighting its importance in the measurement of income inequality. Finally, using a panel of tax records, the paper also documents that not only is inequality persistent, but the same individuals are often observed at the top, suggesting that the observed inequality has deep roots.

This paper is a product of the Development Impact Group, Development Economics. 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 tscot@worldbank.org. A verified reproducibility package for this paper is available at http://reproducibility. worldbank.org, click **here** for direct access.

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5,555 to 7,438. The number of students in secondary schools increased from under 6.4 million in 1997 to 8.3 million in 2009 (INEP 2003; INEP 2011).<sup>10</sup>

# **3. Data**

The primary data used in this study comes from two sources: the Brazilian school census ( _Censo Escolar_ ) and Brazilian vital statistics data ( _SINASC_ ) from the Ministry of Health. In addition, we use auxiliary data, including population estimates for Brazilian municipalities from the Brazilian Census Bureau, and municipal expenditure data from a variety of sources. Descriptive statistics for the key variables in our analysis are reported in Table S1.1 in the supplementary appendix. As municipal boundaries changed over the period of interest, we base our analysis on 4,884 minimal comparable areas (see Appendix S2 for details). For simplicity, we continue to refer to the unit of observation as municipality.

# _Schooling data_

We use 13 waves of the Brazilian school census, collected annually for the Ministry of Education by the _Anisio Teixeira Institute of Research on Education_ (INEP) which provides administrative data on the universe of schools in Brazil (Glewwe and Kassouf 2012). The school census includes detailed information on the universe of public and private schools in Brazil, such as enrolment by grade, age and sex, information on the number of classes, the physical characteristics of the schools, as well as information on teachers.<sup>11</sup> The school census is available from 1995, but because of inadequate quality of the data, we discard the first two census years. We use the census data to create a dataset on the number of secondary schools, the number of classrooms and the number of students between 1997 and 2009—when the vast majority of the school expansion has

> 10 This increase is mirrored by a steep increase in education expenditure; between 2000 and 2009, Brazil reported the largest increase in education spending as a percentage
economies. They also discovered evidence that this export expansion was associated with sectoral inflows of patent applications and intra-firm trade within US multinational firms.

Based on this small sample, it seems that stronger IPRs, including those implemented via TRIPS, tend to increase both imports and exports among middle-income emerging economies, especially in high-technology and IPRs-sensitive goods. However, this question has rarely been studied in the context of the further elevation of standards embedded in high-protection PTAs. This is the empirical gap we hope to begin filling with this paper.<sup>3</sup> Specifically, employing the World Bank database, we ask whether legally enforceable PTAs with chapters requiring IPRs standards that exceed TRIPS expectations have some additional impact on the trade of member countries, over and above that of TRIPS. We also ask whether these effects vary by countries in different income groups (development levels) and specific clusters of industries that are highly sensitive to intellectual property protection. We pay particular attention to trade in pharmaceuticals, chemicals, and information and communication technologies, for these are the areas in which TRIPS-Plus chapters embody especially rigorous standards.

Our analysis contributes to the literature on the trade effects of PTAs. Whether such agreements increase or decrease trade, couched in terms of trade creation or trade diversion, has long been a subject of theoretical and empirical research (Romalis, 2007; Baier and Bergstrand, 2007). More recent literature suggests that PTAs generally have positive trade effects, controlling for endogeneity of selection into agreements, but the impacts are strongly heterogeneous (Baier and Bergstrand, 2009; Baier et al., 2019).

Note that such studies consider discriminatory reductions in trade barriers between members to be the policy impact of free trade agreements. Thus, they focus on bilateral or within-agreement trade effects, accounting also for trade diversion from outside. When considering IPRs, however, the logic is different, arising from the inherent spillover effects created by national IPR regimes. Specifically, the TRIPS Agreement requires countries to establish and enforce standards that are applied without
in randomutility approaches found in the wider literature on WTP elicitation (e.g. Berry et al., 2020).<sup>18</sup> However, binary choice models do not seem to be commonly used to estimate preferences from survey-based MPL experiments.

For simplicity, let us assume we have MPL data that compares only two options A

> 17In line with the view that full randomization is not desirable, the template does not support a fully random order of choices within MPL. This would require additional coding.

18Recently, (Apesteguia and Ballester, 2018) pointed out that the estimation of time and risk preferences from MPL data with a random-utility model may be affected by the fact that the (cardinal) utility difference between two options may not be monotonic in the risk or time preference parameter. As Conte and Hey (2018) note, this non-monotonicity is a property of the (systematic component of) the utility function; issues may arise here from pooling subjects and implicitly making comparisons across subjects. In our case, the monetary value serves a “normalizing” function. We essentially equate WTP with the (relative) subjective value of each option to the subject, and so the utility difference is, by definition, monotonic in WTP.

17
Policy Research Working Paper 11045

# **Abstract**

The publication of nearly 600,000 new species occurrence maps using Global Biodiversity Information Facility data provides an opportunity to reassess international species protection with broader representation for plants, invertebrates, and other species. This development aligns with the global 30x30 initiative, where 188 governments have committed to expanding terrestrial and marine protection to cover 30 percent of the planet by 2030. This study leverages Global Biodiversity Information Facility occurrence maps to identify new opportunities for species protection in 10 countries in Latin America (Brazil, Costa Rica, and Ecuador), Africa (Cameroon, South Africa, and Madagascar), and the Asia-Pacific region (Papua New Guinea, the Philippines, India, and China). By focusing on individual countries, the paper emphasizes the importance of local conservation stewardship. Both terrestrial and marine cases are analyzed, with particular attention to endemic species.

Unlike previous efforts, this approach assigns equal weight to all vertebrates, invertebrates, plants, and other species mapped in the database. A spatially efficient algorithm identifies priority localities for establishing new protected areas to safeguard unprotected species. The findings reveal that initial conditions, such as existing protection levels and the spatial clustering of unprotected species, greatly influence outcomes. Unprotected species are shown to be spatially clustered in some countries but not in others, and the representation of different taxa among unprotected species is found to vary significantly across countries. Some countries can achieve full protection within the 30 percent territorial limit, while others may need to exceed it. However, in all cases, spatial clustering enables significant protection gains through modest expansions of protected areas, demonstrating a path forward for enhancing biodiversity conservation within global commitments.

This paper is a product of the Development Research Group and the Development Data Group, Development Economics and the Environment Global Department. 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
distribution arising from this design is: the percent of survey participants filling out a diary being: For example, in a recall survey _p_ ( _y_<sup>_∗_</sup> ) = 0 at all values _y_<sup>_∗_</sup> . We are interested in the effects of the collection mode on functionals of the distribution of usual consumption _FY ∗_ [ _y_<sup>_∗_</sup> ]. Possible choices for these functionals are quantiles, share below the poverty line, and the Gini coefficient. The difference: represents the distance between the true statistic, _ν_ ( _FY ∗_ [ _y_<sup>_∗_</sup> ]), and the same statistic that would be computed under the assignment design described above, _ν_ ( _FY_ [ _y_ ]). In this section, we find the configuration of weights _p_ ( _y_<sup>_∗_</sup> ) that minimizes the distance in (8) at any given choice for the value of _p_ (the algorithm used to obtain the solution is described in the Appendix). In an effort to contain the computational burden, we use _FY d|Y ∗_ [ _y|y_<sup>_∗_</sup> ], _FY r|Y ∗_ [ _y|y_<sup>_∗_</sup> ] and _FY ∗_ [ _y_<sup>_∗_</sup> ] as if they were _known_ quantities and discard the additional variability arising from estimation errors.

Distributions retrieved from a recall survey are closer to the underlying distribution of usual consumption than in a diary survey. This can be seen in Panel A of Figure 9, where the statistic _ν_ represents the Kullback-Leibler distance (KLD) from the consumption distribution and _ν_ ( _FY ∗_ [ _y_<sup>_∗_</sup> ]) = 0. The continuous line here shows the value
# **III. Estimation**

We study the extent to which the time to move goods from the factory to the ship influences the volume of exports. Longer time delays act as a tax on exports, especially on high-value goods, since they are effectively depreciating during the delay. In addition, the exporter must expend capital on the exporting process and storage/transport of the goods during the delay. Finally, long time delays are likely to be associated with more uncertainty about delivery times, which would further depress exports.<sup>12</sup> For comparison purposes, we begin by estimating an augmented gravity equation that takes the remoteness of a country into account. The intuition is that more remote countries are likely to trade more with their actual trading partners because they have fewer alternatives. For example, Australia is likely to trade more with New Zealand than Austria is with Portugal—even though their other bilateral characteristics are similar—as the latter have more source countries to choose among.

Since this impact is likely to be correlated with our explanatory variables of interest, there is a potential omitted variable bias. Indeed, Anderson and Wincoop (2003) show that the failure to control for what they call the “multilateral resistance” is a major reason that McCallum (2000) found a large border effect in bilateral trade between Canadian provinces and U.S. states. In our case, countries that have more opportunities for export may have higher returns to enhanced local trade facilitation, and invest more in time efficient means. In addition, countries in market centers are more likely to

> 12 The Doing Business data contain information on the maximum time for exporting.  To control for uncertainty, we added maximum-time and also maximum-time-less-average-time variables to the regression equation.  The coefficients on these variables were not significant when either was included along with the average time variable (which remained robust) and coefficients were very similar to those reported here when they were included without the average time variable. The correlation between maximum time
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