rafmacalaba/data-use-mentions-extended huggingface dataset:
parameters (Anderson and van Wincoop 2003). Feenstra (2004) and Redding and Venables (2004) showed that policy relevant parameter estimates can be obtained by replacing national variables with dummies in cross-sectional analysis, leaving only the bilateral variables, although Anderson (2011) expressed some concerns about this approach. Because this fixed-effects (FE) approach is the simplest solution to the problem it has become enormously popular and is examined to ensure that the parameters for Monte Carlo analysis represent such structural gravity models. 2 Where heteroscedasticity is allowed for, the variance of the residuals is modelled as = ii where _x_ is the predicted log of trade and the exponent term ensures the variance is always σσ eepositive (see Cameron and Trivedi 2009, p155). Consistent with standard practice, estimates<sup>(aa+bbxx)</sup> based on the OLS residuals were used for Feasible GLS and Weighted Tobit estimators to see how well these simple approaches perform and to allow comparison with the EK-H estimator.

PPML was considered because of its widely perceived ability to deal with the bias problems associated with both zeros and nonlinearity/heteroscedasticity, and the tentative support for its performance provided by Martin and Pham (2020, p11) when predicted trade is concentrated near zero. The Tobit model is designed to deal with limited-dependent variable bias, and Weighted Tobit attempts to deal with both limited-dependent variable bias and impacts of heteroscedasticity on this model. The EK-H model was included because it specifically deals with both heteroscedasticity and limited-dependent variable bias.

Several models used in earlier work were not examined. The Gamma Pseudo-Maximum Likelihood model was excluded because it did not perform well in Head and Mayer’s simulations (2014, p181). NLS was excluded because of concerns about bias due to limiteddependent variables, heteroscedasticity and nonlinearity; and evidence against normality of 12
(“long-run” estimates); (2) static estimates obtained using annual data with various specifications for the lag operators; and (3) dynamic estimates, also using annual data.

_“Long-run” estimates._ An attractive feature of (1) is that it is consistent with the fact that much of the effects of the independent variables upon per capita agriculture GDP are likely to be embodied through processes that may take considerably more than one year to have an effect. Working with several year averages instead of annual data might help in elucidating what can be considered long-run effects. A drawback of the approach is that one loses degrees of freedom by reducing the number of observations. Alternatively, we used 3 or 5 year simple averages.<sup>22</sup> In general the absolute values of the coefficients tend to be higher when 5-year averages are used, but their signs and degree of significance change very little.

Table 2 provides the Random Effects (RE) and Fixed Effects (FE) estimators of the per capita agricultural GDP regressions using 5-year simple averages as units of observation. The most important message emerging from all these estimates (as well as from the several alternative specifications used that we do not report here) is that while government expenditures have a positive and highly significant effect on agriculture per capita income, the structure or composition of such expenditures is quantitatively much more important and also of great statistical significance. In fact, the results show that increasing the share of (non-social) subsidies keeping the total public expenditures constant has a large negative impact on agricultural per capita GDP. According to the estimates, a reallocation of just 10% of the subsidy expenditures to supplying public goods instead may cause an increase in per capita agriculture income of about 2.3%. And this is obtained _without_ increasing the total government expenditures.<sup>23</sup> By contrast, increasing government expenditures without altering their composition is much less effective in raising per capita agriculture incomes: A 10
test theory, we create an inter-temporal comparison using a linking function derived based on Togo, which participated in all rounds of PASEC. However, given that PASEC did not conduct intertemporal scaling calibration directly, intertemporal comparisons for PASEC should be analyzed with this caveat in mind.

_LLECE_ **.** The Latin American Laboratory for Assessment of the Quality of Education (LLECE) was formed in 1994 and is coordinated by the UNESCO Regional Bureau for Education in Latin America and the Caribbean. Assessments conducted by the LLECE focus on achievement in reading and mathematics in primary school. The first round was conducted in 1998 across grades 3 and 4 in 13 countries. These countries include: Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Honduras, Mexico, Paraguay, Peru and Venezuela. The second round of the LLECE survey was initiated in 2006 in the same countries as LLECE I. In round two, called the Second Regional Comparative and Explanatory Study (SERCE), pupils were tested in grade 3 and grade 6. The Third Regional Comparative and Explanatory Study (TERCE), was done in 2013 across grades 3 and 6 and included 15 Latin American and Caribbean countries. We only include SERCE and TERCE data in this database, since these assessments are most similar and cover comparable grades.

# _C. The Early Grade Reading Assessment (EGRA)_

> 12 The following is a list of participating countries in chronological order: Djibouti (1994), Congo (1994), Mali (1995), Central African Republic (1995), Senegal (1996), Burkina Faso (1996), Cameroon (1996), Côte d'Ivoire (1996), Madagascar (1997), Guinea (2000), Togo (2001), Mali (2001), Niger (2001), Chad (2004), Mauritania (2004), Guinea (2004), Benin (2005), Cameroon (2005), Madagascar (2006), Mauritius (2006),
-9-

Originally it was intended to include India in the present study, but the complete Indian manufacturing census was not available to us in time. India is interesting because it is the country whose authorities seem most dissatisfied with the ICP results for 1975 which they think exaggerate India's real product. Futhermore, an earlier "industry of origin" study mentioned in table 1.2 (Maddison, 1970) showed a substantially lower real product in India than the ICP. Preliminary results of a separate India/USA comparison ar'z now available (Van Ark, 1987), and a complete study will fellow.

Given the much higher number of industrial products compared to those in agriculture (13,000 opposed to 150), it was; not easy to find a reasonably representative minimum sample for all the major manufacturing branches. Table 1.4 shows that we succeedpd in this respect for Brazil and Mexico for most branches, where our total sample covered 33 and 39 percent of total value added respectively. For the USA our sample was rather small for food products and electrical machinery, but our overall sample coverage was close to 20 percent.

Chapter II deals with tl. problem of reconciling the industrial census waterial with the national accounts. Chapter III presents PPPs and binary output comparisons for a sample of 17 industries for Brazil/USA and Mexico/USA both in national and US units. Chapter IV is a binary comparison of Brazil and Mexico using a more refined definition of value added. There were considerable problems in matching different data sources, making coverage adjustments for non-measurable items, defining the boundaries of manufacturing in a comparable way, and testing the validity of price and quantity indicators used to blow up sample results to cover branches as a whole. These methodological issues are covered in Chapters III and IV as they arise and the particular problems of matching and quality are treated in Chapters V and VI. Chapter VII deals with labour productivity. Chapter VIII presents our main findings and recommendations in summary form.
Policy Research Working Paper 10231

# **Abstract**

Extreme values are common in survey data and represent a recurring threat to the reliability of both poverty and inequality estimates. The adoption of a consistent criterion for outlier detection is useful in many practical applications, particularly when international and intertemporal comparisons are involved. This paper discusses a simple, univariate detection procedure to flag outliers in the distribution of any variable of interest. It presents outdetect, a Stata command that implements the procedure and provides useful diagnostic tools. The output of outdetect compares statistics—with focus on inequality and poverty measures—obtained before and after the exclusion of outliers. Finally, the paper carries out an extensive sensitivity exercise, where the same outlier detection method is applied consistently to per capita expenditure across more than 30 household budget surveys. The results are clear-cut and provide a sense of the influence of extreme values on poverty and inequality estimates.

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 gvecchi@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 names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
these estimates, I then interpolate the SEBJ as: θθ≈1/4 θθ

> 33 Recall the SEBJ is defined as the number of employers plus non-agricultural employees, as fraction of total employment.

> 34 Downloaded from https://ilostat.ilo.org/data/browse-by-subject/ on 20 February 2020 (with ICSE-93 option).

> 35 Note that I must use ICSE-93 rather than “Aggregate status in employment”, as the latter is missing data on employers.

36 The reason for this is that the SEBJ data are based on total employment, whereas the employment-to-population ratios are based on the 15-64 age group.

> 37 I thank Michael Weber for providing these data (accessed on 25th February 2020). In cases where multiple JOIN surveys are available for the same year, I use the one with the largest total employment.

> 38 The ILO series used here is “Employment distribution by status in employment (by sex) (%) – Annual”, downloaded from <u>https://www.ilo.org/shinyapps/bulkexplorer7/ on 22nd January 2020.</u>

39 ILO data set “Share of agriculture in total employment (%)- Annual” (latest period), accessed 22nd January 2020 from https://www.ilo.org/shinyapps/bulkexplorer7/ 40 More specifically, I trim the top 5% of More specifically, I trim the top 5% of � outliers in each case, and estimate using OLS without a constant. The estimates of 0.53 and 0.30 are rounded to 1⁄2 and 1⁄4 respectively. AANNEE 13

> 40 More specifically, I trim the top 5% of  More specifically, I trim the top 5% of � outliers in each case, and estimate using OLS without a constant. The estimates of 0.53 and 0.30 are rounded to 1⁄2 and 1⁄4 respectively.

13
region. This variation limits the possibility of comparing the studies either across time or across geographical regions. Each of these countries needs to consider adopting a more consistent use of indicators and stronger prioritization of UNGASS indicators in their respective research agendas. It is important to establish guidelines and standards for the definition of operational variables in order: (i) to strengthen the evidence related to HIV and other STIs; (ii) to guide the research; and (iii) to guarantee the dissemination and use of data when planning the response to the spread of the HIV epidemic.

# **Conclusions about the use and usefulness of the tool**

- The absence of simple tools for assessing the quality of existing HIV data has motivated the development of this checklist tool.

- The experience of implementing this tool in Latin America proved to be easy and feasible.  The tool permitted a group of users to assess more than 300 research

38
Policy Research Working Paper 10430

# **Abstract**

This paper estimates the effect of voice and accountability, which captures transparent electoral processes, free media, and freedom of expression, on access to sanitation services in developing countries. The core argument is that voice and accountability increases the visibility of sanitation as a public good and raises awareness of its benefits; hence, increasing its supply and demand. The analysis utilizes data from 73 developing countries and an instrumental variable approach to identify the causal effect of voice and accountability on access to, and use of, sanitation. The paper also employs a novel _instrument-free_ _estimator_ as both an alternative estimator for the analysis and an empirical strategy to formally assess the validity of the instrument in a just-identified model—a previously untestable just-identifying exclusion restriction. The paper finds robust evidence that voice and accountability increase access to sanitation and help close the persistent rural- _urban inequality_ in access to sanitation. The results suggest that key tenets of democracy such a freedom of speech, free media, and power of electoral incentives are not a luxury of the rich—they are relevant to the world’s poor as they can shape the demand and distribution of sanitation services.

This paper is a product of the Macroeconomics, Trade and Investment 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 jfrancois1@worldbank.org_and ckouame 1@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 names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are
the sample has domestic violence legislation while the remaining 69 percent does not. The variable shows substantial variation over time for the countries under study. For example, at the beginning of our time period, 1990, only one country had domestic violence legislation compared with 51 at the end of the study period, 2012. This is indicated in table 1 where we present the number of countries with domestic violence legislation in our sample. As a robustness check, we take into account lagged effects of the explanatory variable by reporting results with one year lagged values of the domestic violence legislation variable.

In our baseline model, the panel specification allows us to control for all time invariant country features as well as the annual global shock to the dependent variable. In order to further raise our confidence against this problem, we control for a number of additional factors (see section 2 for motivations for the controls). Another layer of defense is provided by the use of the IV estimation method (discussed in detail in section 5).

A formal definition of the various controls is as follows. The overall income level is a broad proxy measure for a number of factors that could affect the health, longevity and hence mortality rate of men and women. Whether such factors affect women more than men is a moot point. However, there is some evidence to suggest that growth and development may benefit the relatively less privileged sections of society more, which happen to be women as far as the mortality rate is concerned. For example, the growth literature documents catching up by the relatively poor countries (convergence) while the literature on access to finance suggests that smaller and less financially connected firms benefit more from overall financial development than larger and better connected firms (see for example, Beck et al. 2005). We filter out such factors from affecting our results by controlling for (log of) real GDP per capita (constant USD, 2005). The data source is WDI. We complement this with the control for the annual growth
These countries in Latin America provide an interesting case for understanding women’s lower access to land because inheritance laws do not preclude the inheritance of land by girls and women. Nonetheless, although legal restrictions may be the same, individuals’ preferences for how to allocate their estates may perpetuate gender imbalances. Deere and Léon (2003) present data from a review of wills in Mexico and show that partners are selected to inherit land 38.5 percent of the time; daughters, 8.8 percent of the time; and sons, 38.8 percent of the time. Sons and partners are the predominant choice, with daughters a very distant third. Deere and Léon argue that a number of factors suggest improvements in the likelihood that women will inherit land (for example, joint titling, discussed below), but this pattern of inheritance indicates worsening inequality in women’s access to land across generations, all else equal, given that women choose their daughters as sole heirs only 19 percent of the time (compared to 5 percent for men).<sup>12</sup> Women are also less likely to acquire land from the state, which mostly takes the form of land redistribution programs. Deere and Léon (2001, table 3.2) show that the fraction of beneficiaries of 13 Latin American land reform programs who were women was approximately 11–12 percent. The main reason for this situation is likely to be the institutional arrangement of these programs: they target household heads (which have previously been identified solely identified as male) and sometimes restrict households to one beneficiary, making men much more likely to benefit. However, this situation can be rectified with policy reform. For example, Deere and Léon (2003) document that in Colombia, the share of female beneficiaries from agrarian reform increased from 11 to 45 percent after joint titling for land parcels was mandated and enforced. Finally, the market is 11
as in the base scenario (no behavioural impacts). 64 Potential savings are estimated by applying the percentage change in the ‘survey’-budget, before and after the reform, to the administrative budget. Additional bill recovery from non-paying households in the top 40 percent of the distribution would yield extra revenues of approximately JOD 17 million. Full bill-recovery from all households would increase revenues by JOD 60 million in total. These estimates are based on self-reported zero-bill households in HEIS and may differ from administrative data.

65 Some households with higher incomes nonetheless are large households and are thus relatively poor (in per capita terms), so lowering the tariffs for the highest consumption blocks reduces poverty by a small amount.
from the National Nutrition Survey 2013. Nutrients. 2018;10(11):1730. Published 2018 Nov 11. doi: https://10.3390/nu10111730

> 34 Derek Headey, Kalle Hirvonen, John Hoddinott, Animal Sourced Foods and Child Stunting, American Journal of Agricultural Economics, Volume 100, Issue 5, October 2018, Pages 1302– 1319, https://doi.org/10.1093/ajae/aay053

> 35 World Bank. 2018. Making growth work for the poor: a poverty assessment for the Philippines (English). Washington, D.C.: World Bank Group. http://documents.worldbank.org/curated/en/273631527594735491/Making-growth-work-for-the- <u>poor-a-poverty-assessment-for-the-Philippines</u>

> 36 Minimum dietary diversity (MDD) is defined as the percent of children 6-23 months of age who receive foods from 4 or more food groups during the previous day. Seven food groups are considered: (1) grains, roots and tubers, (2) legumes and nuts, (3) dairy products (milk, yogurt, cheese), (4) flesh foods (meat, fish, poultry, and liver/organ meats), (5) eggs, (6) vitamin-A rich fruits and vegetables, (7) other fruits and vegetables. A minimum acceptable diet (MAD) defined as children 6–23 months of age who receive a minimum acceptable diet (apart from breast milk). This indicator is comprised of two fractions: (1) The proportion of breastfed children 6-12 months of age who had at least the minimum dietary diversity and the minimum meal frequency during the previous day and (2) The proportion of nonbreastfed children 6-23 months of age who received at least 2 milk feedings and had at least the minimum dietary diversity not including milk feeds and the minimum meal frequency during the previous day.

> 37 Chawanpaiboon S, Vogel JP[1], Moller AB, Lumbiganon P, Petzold M
controlling for the population-weighted _distance_ (ln) between the host country _i_ and country of origin _o;_ whether the origin and host country share a _common language_ , _common border_ , or _colonial history_ . Data on these bilateral variables were obtained from the gravity data set developed by Head, Mayer and Ries (2010).

We estimate a two-stage Heckman model to simultaneously examine investment at the extensive margin - i.e. whether to invest - and the intensive margin - i.e. how much to invest. The first stage analyzing the extensive margin consists of a probit model, where the dependent variable is 1 if a MNE invested in a host country in year _t_ and 0 otherwise. The second stage, examining the intensive margin, consists of an OLS-model estimating the amount of greenfield FDI (transformed using the inverse sine-transformation) for those firms that decided to invest. To avoid multicollinearity resulting from limited nonlinearity in the functional form, we use the colonial history dummy as our exclusion restriction. However, our results are also robust to using different exclusion restrictions.

Table 6 presents the results from the two-stage Heckman model. Column 1 shows the results for the regression of the intensive margin, where the dependent variable is the amount of greenfield FDI flows given that an MNE invests in a country. At the average geographic diversification level, a nationwide conflict has a significant negative effect on total FDI flows, whereas a localized conflict does not significantly affect greenfield FDI flows (Column 1). This is consistent with our hypotheses and main results. However, in the equation for the extensive margin there is no significant main effect of BRD, irrespective of the type of conflict. Hence, political conflict affects greenfield FDI flows through a decrease in the size of investment projects, whilst there is no evidence that conflict affects the probability that an MNE invests in a country. The diversification moderator is not statistically significant for the intensive margin, but it is positive and significant at the 10% level for the extensive margin (Column 2)