rafmacalaba/data-use-mentions-extended huggingface dataset:
measuring reported attitudes and awareness appears to be much easier than changing or measuring violence-related behaviors.

# **_Mass media campaigns to increase awareness of women’s rights_**

Organizations (mostly NGOs) around the world have used mass-media campaigns to raise awareness of gender-based violence, promote nonviolent behavior and encourage women and men to be more supportive of their friends and family members who experience violence. These campaigns have included international campaigns (such as the 16 Days of Activism Against Gender Violence Campaign), national campaigns (such as the annual campaigns conducted by the Nicaraguan Network of Women Against Violence), and local campaigns conducted within individual communities. These campaigns often appear to successfully raise awareness and increase knowledge. For example, national surveys suggest that-at least partly due to the annual campaigns--women in Nicaragua are increasingly aware of their rights. A Demographic and Health Survey (DHS) found that more than two thirds of women believed that violence against women was never justified and that they should be able to refuse sex with their partner for any reason. While it is difficult to sort out the contribution of multiple initiatives on changes in awareness and attitudes, the DHS found that one quarter of the women surveyed were able to repeat one or more messages from the annual campaigns (Ellsberg, Liljestrand, and Winkvist, 1997; Rosales, 1999; Herrera, 2001). Once again, however, researchers have not yet been able to measure the impact of these initiatives on the levels of violence against women. Moreover, experiences from other fields suggest that while these types of mass media campaigns play an important role in awarenessraising, strategies such as ‘edutainment’ are more likely to change behaviors over time (CDC, 2004).

# **_Multi-sectoral initiatives to reduce violence against women throughout the community_**

Association Najdeh, an NGO in Lebanon, operates 26 service centers for Palestinian refugees that offer vocational training, literacy, preschools, and income generation programs. In 1999, they launched a domestic violence initiative using action research,
including the APR and APY, and a list of all fees. These laws also establish that institutions regulated by the SFC must provide their clients clear and timely financial information allowing them to be adequately aware about their rights and obligations with the regulated financial institutions, and enough information for them to be able to compare costs among products. Particularly, Law 1748 of 2014 mandates that financial institutions inform their clients in addition to the interest rate paid or received by them, the Unified Total Value for all items, actually paid or received by the client in all their products and in advance to the conclusion of the contract, but this law is not currently enforced.

Additionally, Law 1328 and Law 1480 established that financial institutions must provide financial education to their clients. Decree 457 of 2014 which was drafted by the Inter-Sectorial Commission for Economic and Financial Education, in charge of designing and implementing the National Strategy for Economic and Financial Education, states that consumer protection is one of the main objectives.

One issue hindering the effectiveness of financial disclosure is the low level of financial capabilities among Colombians. According to the PISA 2012 results, Colombia occupied the last position (out of 17 countries) on financial literacy. This low level of financial capabilities may impact financial decisions. People unaware of the consequences of their financial behavior are more prone to making bad decisions. In fact, a 2012 World Bank study found that just one-third of those surveyed could calculate a simple interest rate, and that 69 percent of the surveyed population stated they were never taught how to manage their money. A survey conducted by the CAF in 2014 showed that only 12% of the people surveyed managed the concept of compounded interest rates, only 36% mentioned to have a financial plan for their lifetime, and 67% reported to have had economic difficulties in the near past. Similarly, in a survey conducted by Banca de las Oportunidades and the Financial Superintendence of Colombia in 2015, only 62% of the people surveyed mentioned they knew the different costs associated to their
1||
|∆_σ × κσ_||||0.750***<br>(0.022)||1||
|Growth Component|||||1.081***<br>(0.007)||1|
|Distribution Component|||||0.882***<br>(0.015)||1|
|Constant|0.103|0.156*|0.203***|0.165***|0.0129|0|0|
||(0.087)|(0.083)|(0.075)|(0.036)|(0.024)|||
|E[_dH_]|-0.826|-0.794|-0.794|-0.794|-0.794|-0.794|-0.794|
|E[∆ ̄_y_]|4.499|4.430|4.430|4.430|4.430|4.430|4.430|
|E[∆_σ_]||-0.0626|-0.0626|-0.0626|-0.0626|-0.0626|-0.0626|
|Observations|1310|1307|1307|1307|1307|1307|1307|
|R-squared|0.425|0.463|0.584|0.893|0.951|0.876|0.942|

_Note:_ *,**,*** denote significance at the 1,5, and 10 percent level, respectively. Standard errors presented in parentheses. Dependent variable: percentage point change in the headcount poverty rate in country _i_ from year _t − n_ to _t_ , where the headcount poverty rate is calculated as the percent of the population under the $
7 power parities (PPPs), and the process of constructing expenditure totals and subtotals is guided by the UN’s Classification of Individual Consumption According to Purpose (COICOP) classification system. In both exercises, the various components of consumption – including out-of-pocket health expenditures – are also distributed along with the consumption aggregate. Often, the original microdata (or parts of the microdata) are also made available to authorized users (typically World Bank staff), which allows for validation, where possible, of different methods to estimate out-of-pocket health expenditures, which can then be related to a standardized consumption aggregate.

Some country-specific surveys can appear in multiple (harmonized) multi-country collections. France’s HBS, for example, has been harmonized by both Eurostat and the LIS. Peru’s ENAHO survey has been harmonized by both the LIS and the World Bank’s SHES exercise. Romania’s HBS has been harmonized by Eurostat and the World Bank’s Europe and Central Asia harmonized collection (ECAPOV). These multiple adaptations provide additional opportunities for data-validation but also highlight the potential for obtaining different results depending on which adaptation one uses.

The studies to date summarized in Table 2 have mostly used standalone surveys. The exceptions are the studies by Wagstaff et al. (2018b; 2018c) – they use standalone surveys and surveys from several collections. Often, the authors sifted through alternative estimates (e.g. of catastrophic expenditures) for a particular country and year, using external checks to choose between them.

# <u>Measuring out-of-pocket spending</u>

Household surveys vary in how (and indeed whether) they inquire about out-ofpocket health expenditures. This poses challenges for comparisons across countries, and over time within the same country.

First, not all surveys are clear whether the spending reported is gross or net of any reimbursement by a health insurer, and even when it is clear, the amount reimbursed may not be known at the time of the survey, making it impossible to correct for overreporting. Second
<!-- Start of picture text --> MHHH-FHHH gaps in size of land operated (cond_) vs. GDP per capita<br>t aBGR<br>GTM<br>_a APA<br>c<br>S<br>zm= APAK -<br>fa a<br># “a0GHA | ee<br>= a<br>au pea<br>o ae<br>= oR BOL<br>30 “MW — — 4JaTKEN <&VNM ALB<br>=<br>a<br>oo<br>=a<br>o<br>«IDM<br>6.5 Tv 75 8 8.5 g<br>log of GDP per capita (PPP, constant USS 2005)<br>Source: RIGA data.<br><!-- End of picture text -->
experienced a slight rise. The clear implication from changes in these two ratios is that cash use is falling in Europe.

An alternative way to illustrate the reduction in cash use is to compare the value of cash holdings per person (in constant U.S. dollars) with the number of non-cash transactions per peison. Across countries, a high number of non-cash transactions per person is associated with a low stock of cash per person (comparing Column 8 with 6 in Table 1). The estimated relationship across 14 developed countries annually over 1987-93 suggests that a 6.8% rise in non-cash transactions is associated with a 100% reduction in cash holdings (Humphrey, Pulley, and Vesala, 1996).

**_4_** _European data reflects the total U.S. dollar value of coin and currency (1993 exchange rate) for 11 countries divided by the total dollar value of Ml or GDP. It is equivalent to a weighted (not a simple) average of individual country ratios. Since cash balances can be held for prudential or speculative purposes (hoarding), in addition to pure transaction purposes, observed levels of cash holdings only approximate the level of cash use. Cross-country evidence sugges_ **_t_** _s hat hoarding is especially important in Switzerland, the Netherlands, and Germany but not important in Denmark, Finland, France, Norway, or the U.K. (Boeschoten, 1991 and 1992). As seen in Table 1, countries where hoarding is though_ **_t_** _o be important also have relatively large cash/MI and cash/GDP ratios distorting, somewhat, the implied differences incash use across countries._

**_6_** _The results for Germany and the U.S. must be taken with caution since it has been estimated that perhaps 35% of_ the _value of German currency and 60% of U.S. currency is held outside the_ country _(Boeschoten,_ 1992; _Porter and Judson, 1995). Only if these
# Table A.3: Election and District Characteristics (DLHS samples)

||N|Mean|S.D.|
|---|---|---|---|
|**Panel A: Election data**||||
|Share of constituencies won by women in a district (F)|245|0.05|0.09|
|Share of male-female close elections won by women in a district (FC)|245|0.01|0.04|
|Share of close male-female elections in a district|245|0.02|0.06|
|Whether the district had at least one seat won by a woman|245|0.33|0.47|
|Whether the district had at least one male-female election|245|0.56|0.50|
|Whether the district had at least one male-female close election|245|0.16|0.36|
|Whether the district had at least one male-female close election won by a woman|245|0.07|0.25|
|**Panel B: Census data**||||
|Fraction of female population|245|0.49|0.02|
|Fraction of urban population|245|0.33|0.21|
|Fraction of SC/ST population|245|0.34|0.25|
|Female literacy rate|245|0.63|0.11|
|Male literacy rate|245|0.74|0.08|
|**Panel C: Village data (DLHS)**||||
|Any sub-center|7,721|0.55|0.50|
|Any primary health center|7,721|0.23|0.42|
|Any block primary health center|7,722|0.06|0.24|
|
had not repartnered. During 2011–16, the period covered in the panel used in this analysis, Brazilian gross domestic product (GDP) shifted from a growth rate of around 6 percent to a contraction rate of 4 percent partially as a consequence of the global economic slowdown.<sup>2</sup> However, women’s earnings did not fall as much as men’s earnings over the period, and the gender wage gap thus narrowed. Additionally, the ratio of the female labor participation rate and the male rate rose from 68 percent to 71 percent.<sup>3</sup> In 2013, the rate of female homicides in Brazil was 4.8 deaths per 100,000 women, the fifth highest rate in the world at the time (Waiselfisz 2015). However, the rates of nonfatal violence are not quite as shocking. In a representative survey among women ages 15–69 in the state capitals of Brazil, the 12-month prevalence of any type of minor physical IPV was 21.5 percent and of severe physical IPV, 12.9 percent; rates were higher among younger women (Reichenheim et al. 2006). In comparison with other national statistics, these rates are about average. Prevalence was far greater than the mean estimates in North America (2 percent), moderately greater than those in Europe (8 percent) and Sub-Saharan Africa (9 percent), and close to the levels reported in Asia and Oceania (12 percent). Yet, the rates are well below the mean reported in North Africa and the Middle East (33 percent). The overall prevalence of IPV was also lower in Brazil than the average in Latin America of 21 percent, but closer to the rates in Mexico (15 percent) and Uruguay (10 percent) (Reichenheim et al. 2011).

Comprehensive legislation in Brazil addresses domestic violence. The most publicized piece of such legislation is Law 11.340, which was adopted in 2006 and is known as
- D. Using LASSO instead of XGboost for the geospatial and census model

This exercise provides a useful opportunity to compare predictions across two different machine learning approaches: Extreme Gradient Boosting, and post-LASSO, which uses LASSO-selected variables in an OLS regression model. The main difference between these two approaches is that the former, as applied here, is a tree-based classification method that uses sequential random forests to predict the dependent variable. Extreme gradient boosting can therefore accommodate highly non-linear relationships. In contrast, post-lasso imposes a linear functional form. An open question in this context is how much this linearity assumption affects the accuracy of the predictions.

The results when using post-LASSO to generate the geospatial predictions based on the partial registry – the second step of the partial registry procedure -- are displayed in Figure 8. These are applied to predictions from the baseline census model, which uses data from all districts but predicts the average welfare of the bottom half of households. Overall, the post-LASSO model performs slightly better in terms of rank correlation, while extreme gradient boosting performs a bit better when looking at AUC and R-squared. Thus, in this context, whether one uses postLASSO or extreme gradient boosting in the second stage of the partial registry method makes little difference. However, the estimation method for the benchmark welfare seems to affect the results considerably. When the geospatial models are trained using a benchmark welfare that was predicted using LASSO, the metrics for the partial registry methods decrease significantly: rank correlations go from 0.75 to 0.27, AUC from 0.89 to 0.66 and R-squared from 0.57 to 0.08. This could indicate potential measurement errors in the census that affects the performance of LASSO models since they are more sensitive to outliers.

**Figure 8.** Partial registry predictions using LASSO vs. XGBoost

<!-- Start of picture text -->
1.00<br>0.89<br> 0.90 0.85<br> 0.80 0
service provision in separate models due to high correlations among the various indicators.<sup>11</sup> Figure 7 illustrates the effect of donor and non-state actor service provision on citizens’ willingness to defer to the tax department. With one exception, analyses point to a positive relationship between donor and non-state actor service provision and the willingness to defer to the tax department. Respondents who believe that traditional actors are responsible for collecting taxes are less likely to be willing to accept the authority of the tax department than respondents who believe that the government is responsible for collecting taxes.

I expected respondents who believe that non-state actors, rather than the state, are responsible for collecting taxes to be less likely to be willing to defer to the tax department. The results suggest that this is the case. A belief that traditional leaders instead of the central or local government are responsible for collecting taxes corresponds to a percentage point increase of 5.8 that one will be unwilling to defer to the tax department.

I argue that non-state actor and donor service provision is likely to undermine the fiscal contract between a state and citizens by providing citizens with essential goods and services that they believe the state has an obligation to provide. The analysis of the Afrobarometer data does not yield support for this hypothesis. Instead, I find a positive relationship between donor and non-state service provision and deference to the tax department. In other words, citizens who believe that donors and non-state actors are helping their country by delivering essential goods and services are more likely to be willing to defer to the tax department. This positive relationship is consistent across all of my measures of donor and non-state actor service provision.<sup>12</sup> Of the indicators of donor and non-state actor service provision, the measure of service provision by the UN has the largest relative effect on the acceptance of the tax department’s right to make people pay taxes. A belief that the UN is doing a lot, rather than a little, to help one
their social contract with the government. The analysis was conducted in an equivalent way to Equation (1) above, i.e., by conducting pooled (across treatments and countries) OLS regressions with country fixed effects, but with an interaction between respondents’ priors and the treatment. A dummy variable for each of the respondents’ priors is created ( _PRIOR_ ) that takes on the value of 1 if a respondent has a particular prior (e.g., trusts government) and a value of 0 otherwise (e.g., does not trust government) (see Table 5). This can be expressed formally as follows: where _i_ denotes individuals, _j_ denotes countries, _π_ 1 captures the average difference between respondents without a prior in any treatment group ( _T_ ) and the control group about the outcome of interest ( _Y_ ), _π_ 2 captures the average difference in the outcome of interest ( _Y_ ) between respondents in the control group with and without a given prior ( _PRIOR_ ), and _π_ 3 captures the interaction between the treatment variable ( _T_ ) and the prior variable ( _PRIOR_ ) for the outcome of interest ( _Y_ ). Further, _Xi_ is a vector of variables that controls for potential imbalances in background characteristics (age, sex, location, income, education level, perceived relative income, actual income, energy consumption, trust in government, belief in government capacity, knowledge of subsidies) between treatment and control groups; _θj_ captures country fixed effects; _εij_ is the model error term (clustered at the country level); and _β_ 0 is the intercept.

# **4 Descriptive findings**

This section presents descriptive findings from the cross-country survey about respondents’ knowledge of and beliefs about energy subsidies and support for energy subsidy reform.

29
the only data we use are the CHIRPS Rainfall dataset (Funk et al. (2015)).

Our algorithm involves the following steps. First, we calculate the average and standard deviations of total rainfall (in mm) for every 10-day period or decad in a given month in any given province (i.e. decad x month x province).<sup>18</sup> Second, we calculate the standardized anomalies for every decad x month x province x year. Third, we exclude all decads that are not in the growing season. Fourth, we define a dry spell of length _n_ for a given decad, as having below average rainfall in that decad, as well as the _n −_ 1 preceding decads. In addition, at least half the decads in a dry spell are required to receive less than

> 16Expert, on the ground opinion (e.g. http://fews.net/southern-africa/mozambique) is broadly consistent with these observations (scroll down to look at the seasonal calendars for South-Central and Northern Mozambique).

> 17See, for example, http://fews.net/east-africa/tanzania.

> 18The length of the last decad in a month adjusts so that it just covers the month. Consequently, decads may be compared across years.

9
were somehow inferior. Moreoever, the housing market allows poorer households to find housing more in keeping with their ability and willingness to pay for it.

Many renters in Russia have chosen not to privatize their apartments, influenced largely by the sense of "occupation rights" inherited from the former Soviet Union. Many Russians have little incentive to privatize their housing, but data from Moscow and two smaller cities indicate that market ideas about searching for housing are beginning to penetrate the Russian public's mentality.

This paper - a product of the Poverty Reduction and Economic Management Sector Unit, Europe and Central Asia - is part of a larger effort in the region to study housing reforms in Russia. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Sandra Graig, room H12-095, telephone 202-473-3160, fax 202-477-0288, Internet address sgraig@worldbank.org. March 1998. (42 pages) _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 represen_ **_t_** _he view of the World Bank, its Executive Directors, or the countries they represent._ Produced by the Policy Research Dissemination Center
Figure 4. Initial Poverty Levels (2006) and Poverty Reduction (2006-2013) <!-- Start of picture text --> TRA2<br>TRB1<br>TRA1<br>TR10<br>TR41<br>TR42<br>TRB2<br>TR90<br>TR51 TR72<br>TR52 TR71<br>TR33 TR81<br>TR21 TR82<br>TR32<br>TR31 TR22<br>TR63 TRC3 TRC2<br>TR83<br>TR62<br>TR61<br>TRC1<br>2 2.5 3 3.5 4<br>Log initial poverty rate ($5/day PPP)<br> Low Initial Poverty High Initial Poverty<br>5<br>0<br>-5<br>-10<br> Declining Poverty Increasing Poverty Annualized growth in the poverty rate 2006-2013 ($5/day PPP)<br><!-- End of picture text --> _Notes_ : Initial poverty rates are in 2006. Poverty line is $5/day PPP per capita, OLS imputed income poverty, spatially deflated. _Source_ : LFS, SILC 2006-2013; authors’ calculations.

# **<u>Poverty Gap</u>**

Fluctuations in Turkey’s poverty rate explain only a portion of the entire poverty story as the headcount rate shows only the number of people living under a certain amount of income or consumption level. Supporting this headcount rate with the poverty gap index is valuable for obtaining a more complete picture of poverty in Turkey. The poverty gap measures the depth of poverty by taking into account the distance between the poverty line and the observed level of income/consumption of the poor. As the poverty gap increases, people under the poverty line have to increase their income/consumption at proportionally higher rate in order to escape poverty.

The relationship between moderate poverty rate and poverty gap is analogous to the previously explained trend between moderate and extreme
to countries in LAC. Second, the paper will allow for the testing of the robustness of results to different institutional fragmentation and institutional coordination measures. Third, it will allow for an assessment of whether existing metropolitan coordination measures are effective in helping to produce better economic outcomes. Finally, contrary to existing literature, most of the analysis will be supported by spatial data that are readily available at the global scale and for developing countries. This will allow the paper to contribute to the development of a methodology that can be easily replicated for other regions of the world.