rafmacalaba/data-use-mentions-extended huggingface dataset:
Disease Control’s AIDS hotline in one year came not as a result of a million dollar public awareness campaign or through news and documentary broadcasts, but rather in response to a beloved soap opera character dealing with his HIV positive diagnosis.<sup>2</sup> This paper contributes to the literature by carefully analyzing the impact of financial education messages delivered through a popular South African television soap opera, “Scandal!” In partnership with the production company of Scandal, the soap storyline features one of the main characters borrowing excessively through hire-purchase, gambling, and falling into a debt trap; and eventually seeking help to find her way out and manage her debt responsibly. The storyline plays out over a two month period, and the study evaluates the effectiveness of these messages through two intermediate surveys and one final follow-up survey conducted four months later. Further, three qualitative focus groups provide insight into the mechanisms behind measured impacts.

The methodological challenge associated with such an evaluation is non-trivial. Critically, it is impossible to externally restrict viewership since the soap opera is nationally televised with no variation in TV signal strength, at least in urban areas where this study focuses. Even an encouragement design methodology is limited in scope as we can only encourage a set of individuals to view Scandal, but in no way can we prevent others (particularly those in the control group) from doing the same.

To overcome this constraint, we employ a symmetric encouragement design in this study. Specifically, while a randomly selected treatment group is encouraged through financial incentives to view Scandal, another set of individuals – the control group – is similarly encouraged through identical financial incentives to view a comparable soap opera (“Muvhango”) that overlaps with Scandal in television primetime. Hence, we are able to create an artificial separation between treatment and control groups, which enables us to identify the treatment effects of financial literacy delivered through Scandal.

> 2 See also Chong and Ferrara (2009) and Kenny (2009) for similar findings.

3
records, and the farm performance survey. Section four presents the results from regressions exploring the impacts of title on self-assessed land rights, land values, investment, and productivity. Section five concludes by discussing implications for policy and future research.

# **2. Background and conceptual framework**

A large literature shows LSLBI can provide benefits for local populations if their land rights are respected while also highlighting that policies and the institutional arrangements to implement them affect volume and impact of such investment and that geo-referenced inventories are needed to assess quantity and impact of such investment. Low levels of agricultural productivity and large amounts of potentially suitable land have long led Zambia to adopt policies, including a dualistic land tenure regime, to encourage large farm growth. While this is estimated to have led to an agriculture sector dominated by (domestic) large farms, neither the extent and nature of large farms nor the effect of such policies on their productivity is known.

# **2.1 Lessons from large land-based investment**

While early contributions highlighted the scope for “pioneer investors” to support discovery of agroecological suitability and establishment of technology and market linkages (Collier & Venables 2012), the extent to which large land acquisition by capital intensive large farms can support Africa’s structural transformation has long been subject to debate (Deininger & Byerlee 2011; Collier & Dercon 2014; Cotula 2014).<sup>8</sup> A key motivation for providing title to large farms is the hope that doing so will provide them with the means to access credit to complement their better access to product markets and management thereby catalyzing structural transformation. However, with few exceptions (Muyanga & Jayne 2019), evidence on large farms’ productivity or its determinants is lacking, making research on this issue a priority.

Several studies explore long-term effects of foreign cash crop plantations using discontinuity designs. They often find negative and persistent effects on human capital as in South America (Dell 2010) or Puerto Rico (Bobonis & Morrow 2014) due
Food Security and Nutritional Diversity**

Five years after the asset transfer, the intervention continues to have a significant impact on consumption among treatment households. Our consumption proxy is 16% (p-value = 0.015) larger in the treatment group than in the control group (Table 2).<sup>19,20</sup> The intervention also increases an index of food security for treatment households by 0.09 SD (p-value = 0.115), compared to control, however, this impact is not statistically significant. It is worth putting these results into context. Due to food price increases, food consumption in constant terms decreased by 27% in the control group between midline (July–October 2018) and endline (January–June 2021) (Figure IV), while total consumption decreased by 8% during the same period (not shown). Therefore, these impacts occur while households in both treatment and control groups are experiencing decreases in food and overall consumption, as well as in food security.

While we observe higher consumption together with small but statistically insignificant improvements in our measures of food security, we find that the intervention improved the nutritional quality of the food consumed by treatment households, consistent with the literature (Subramanian & Deaton, 1996; Strauss

> & Thomas, 1995; Subramanian & Deaton, 1996).<sup>21</sup> As Table 2 shows, per-capita consumption for UP

> 19Our proxy includes 29 items with the greatest explanatory power (75% and 59% of the variation in total consumption at baseline and midline for the UP and non-UP households, respectively).

> 20Further details on the consumption proxy are in Online Appendix Text 2. Comparison of control means and impacts across all main outcomes and their proxies for the midline and endline samples can be found in Table A11 of the Online Appendix.

> 21The food security index incorporates indicators related to the _extensive_ margin, i.e., whether the household experienced

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.1<br>.8<br>0<br>.6<br>CCDF<br>.4 Difference<br>-.1<br>.2<br>0 -.2<br>.4<br>.3<br>.2<br>.1<br>Social Sustainability Index<br>0<br><!-- End of picture text --> _C4. Change in the indicators included for each dimension, one indicator removed at a time. Baseline scenario: All indicators included. Alternative scenario: Medical attention indicator removed (weights within the Social Inclusion dimension were scaled from 6.25% to 8.33% so all weights add up to 1)._

# Peru

# C4.1. FOSD: Counting Vector

# C4.2. Dominance Analysis

<!-- Start of picture text --> Counting vector CCDF by scenario Difference between counting vector CDF curves<br>First-order stochastic dominance (α=0)<br>0 .2 .4 .6 .8 0 .2 .4 .6 .8 1<br>Counting vector (relative scale) Counting vector (relative scale)<br>Baseline Alternative Confidence interval (95 %) Estimated difference<br>.1<br>1<br>.8 .05<br>.6<br>0<br>CCDF<br>.4 Difference<br>.2 -.05<br>0<br>-.1<br><!-- End of picture text --> C4.3. SOSD: Social Sustainability Index C4.4. Rank correlations 50
or supplier links that involve at least one agribusiness company. We identify this latter based on their primary NAICS 6-digit code, including relevant industries from the agriculture,

> 6In financial reporting, a 10-Q is a company’s quarterly report, containing unaudited financial statements, while the 10-K is an extensive annual report with audited financials, executive details, and structure. An 8-K is filed by firms to swiftly update shareholders on unscheduled, important events like management shifts, investigations, deals, closures, layoffs, or bankruptcy, often leading to multiple filings within a quarter for prompt communication. U.S. listed firms must for instance detail any customer that accounts for more than 10% of its revenue (Gofman and Wu, 2022), with some firms voluntarily disclosing additional customers (Huang et al., 2023).

> 7Note that we already observe many records of Latin American source companies in 2014, suggesting a backward updating of relationship for Latin American firms.

> 8The parent or ultimate parent will be identical to the company itself for self-owned firms.

8
DITC/TAB/2017/2.

- Dhingra, Swati, Rebecca Freeman, and Hanwei Huang (2021), “The impact of non-tariff barriers on trade and welfare.” 17.

- Dür, Andreas, Leonardo Baccini, and Manfred Elsig (2014), “The Design of International Trade Agreements: Introducing a New Dataset.” _Review of International Organizations_ 93, 353– 375.

- Ederington, Josh and Michele Ruta (2016), “Nontariff Measures and the World Trading System.” _Handbook of Commercial Policy 1b_ . Ed. by Kyle Bagwell and Robert W. Staiger. 1st ed. Vol. 1A. Elsevier B.V., 211–277. url: http://dx.doi.org/10.1016/bs.hescop.2016.04. 010.

- Egger, Peter H. and Mario Larch (2008), “Interdependent Preferential Trade Agreement Memberships: An Empirical Analysis.” _Journal of International Economics_ 762, 384–399. url: http://dx.doi.org/10.1016/j.jinteco.2008.08.003.

- Egger, Peter H., Mario Larch, and Yoto V. Yotov (2022), “Gravity Estimations with Interval Data: Revisiting the Impact of Free Trade Agreements.” _Economica_ 89353, 44–61.

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abundance; fragility, conflict, and violence; and income.<sup>2</sup> We also examine whether the sensitivity of capital flows to global vis-à-vis domestic factors has changed in the post-crisis period. The capital flows data are gross capital inflows, which capture not only the real channels, but also the financial channels of transmission of shocks. Consequently, gross inflows would identify the different channels (real vs. nominal variables) because net and gross inflows have significantly diverged since the mid-1990s (i.e. net flows, a mirror of the current account, are more reactive to real shocks, while gross flows are influenced by both nominal and real variables).

Despite the heterogeneity of economic structures and composition of flows across Sub-Saharan African countries, the empirical analysis provides some major directions for African economic development. These results suggest effective priorities and focus on sustainable development in the region. What policy recommendations would result from the regression analysis for the region? It is important to diversify the economic and export structure to mitigate the output effects of volatility in oil and commodity prices, develop domestic financial markets that provide domestic financial instruments to attract investors, and implement policies that enhance the business environment and create investment opportunities for foreign and domestic investors. According to the empirical evidence, financial openness would attract all types of capital inflows; therefore, a priority should be to develop the domestic financial markets in Sub-Saharan Africa. FDI and foreign aid are the main sources of financing in some countries in the region —especially where public sector participation in the economy is larger than private sector business activity. Therefore, policies that improve the business environment for domestic private sector firms will foster sustained foreign financing in productive activities.

Our main empirical results suggest that the behavior of capital flows across Sub-Saharan African countries is unique: differences in the economic structure of countries vis-à-vis industrial countries may help explain the different transmission channels on the impact of external factors on gross capital inflows. On the other hand, both pull and push factors help explain gross
Using the approach based on the risk of falling into poverty, as proposed by Lopez-Calva & Ortiz-Juarez (2014), is conceptually more accurate in defining the lower bound of the middle class for country-specific analysis. Interestingly, it has been found that despite using an alternative approach, this paper’s results align closely with their findings, which is a valuable contribution to the discussion on middle-class thresholds. Moreover, while the risk-based approach is highly relevant and useful for defining the lower end of the middle class, it does not address the upper end of the spectrum. The proposed methodology in this paper simultaneously tackles the lower and upper bounds of the middle class, using a consistent methodological approach. Doing so provides a comprehensive and nuanced understanding of the middle class in Latin America, which can be of great value to policy makers and researchers alike.

Despite offering valuable insights into the socioeconomic structure of the region, this methodology has certain limitations that should be acknowledged. First, the synthetic panel construction using labor market surveys is subject to potential biases and measurement errors inherent in self-reported income data. These biases may impact the accuracy of the estimated bounds for the middle class. Additionally, the synthetic panel data may not capture the full extent of income mobility based on cross-sectional surveys rather than longitudinal data. Second, this approach does not explicitly account for factors such as social protection systems, access to quality education and health care, or other non-income dimensions contributing to an individual's vulnerability or resilience to falling into poverty. As a result, the proposed methodology may not fully capture the complex dynamics that define the middle class in Latin America. It may overlook essential aspects related to social inclusion, economic security, and quality of life. Lastly, this method may need to comprehensively understand the heterogeneity within the middle class. This group is diverse, encompassing households with varying levels of vulnerability. This approach may not adequately capture these nuances, which are essential for designing effective policies to foster inclusive growth.

While the present approach offers a
countries, representing 85% of the global population and 92% of global total GDP (PPP) in 2015.

In figure 1, we plot the average cell-level precipitation between 1990 and 2014 against the level of GDP per capita observed in 2014 (y-axis), and cell-level temperature against GDP per capita in 2014. A local weighted scatterplot smoothing (LOWESS) represents the non-parametric correlation between weather variables and GDP across cells. Precipitation and GDP per capita follows an inverted U-shape. Up to a level of 500mL to 700mL of precipitation, an additional drop of rainfall is correlated with a higher level of GDP per capita. The relationship then turns negative (Fig 1-A). Above -20oC, temperature and GDP are negatively correlated (Fig 1- B).

In Figure 1 C-D, we collapse weather data to the country level. Following DJO and BHM, we weight each cell by its total population. Observe that the inverted U-shape correlation between population-weighted precipitation and GDP per capita at the cell level is lost at the country level in Figure 1-C. After an initial decrease in GDP 4
survey, typically admitting to sensitive acts at a lower rate than did the respondents not so identified, the possibly candid group.

In this paper we describe the results of implementing this same method for identifying reticent respondents in the Nigeria Enterprise Survey, and we document the extent to which reticence matters in this context. We identify 13.1 percent of respondents as reticent with a very high probability. These reticent respondents answer sensitive questions elsewhere in the questionnaire differently from possibly candid respondents. These differences are most pronounced when sensitive questions are asked in a very direct way referring to the respondent’s own business. For sensitive questions that are worded in a way that implies personal wrongdoing on the part of the respondent, we find that reticent respondents admit to sensitive acts at a significantly lower rate than possibly candid respondents.

The rest of this paper proceeds as follows. In Section 2 we give a detailed description of the coin-toss procedure and document the prevalence of reticence based on estimates derived from this procedure. In Section 3, we examine how the characteristics of reticent respondents are different from those of other respondents. In Section 4 we document how these reticent respondents differ in their responses to other sensitive questions in the survey and show that reticent respondents are less likely to implicate themselves in sensitive acts. In Section 5, we examine whether reticence matters for regional rankings of corruption. Section 6 draws together the lessons from this paper.

# **2. Identifying Reticent Respondents Using the Coin-Toss Question**

The coin-toss methodology presents survey participants with a series of ten sensitive questions, which are listed in Table 1. As indicated above, respondents privately toss a coin before answering each question and are instructed to answer 'yes' if the coin comes up heads. If the coin comes up tails, they are instructed to answer the sensitive question truthfully. The series of ten random response questions includes three that ask about less sensitive acts. In the process of identifying reticent respondents, answers to 4
hypertension, stroke etc). (The questions on functional ability were only asked of pensioners in 2000, although all adults were asked these questions in 2002.) We use both objective and subjective measures of economic welfare. The RLMS includes a wide range of socioeconomic characteristics including consumption expenditures and incomes (which included imputed values for consumption and income in kind). Our main objective welfare indicator is total household expenditure normalized by date and region-specific poverty lines, interpreted as cost-of-living deflators. We use established poverty lines for Russia. We also use data on incomes which have the advantage that they are individual-specific.

However, we recognize that these widely used income-based metrics give an incomplete picture of economic welfare, as discussed in section 2. We follow a strand of the literature in economics that has employed subjective assessments of economic welfare as extra identifying information.<sup>12</sup> The RLMS includes the following question on self-assessed (economic) welfare ( _SAW_ ) asked of each adult: _“Please imagine a 9-step ladder where on the bottom, the first step, stand the poorest people, and on the highest step, the ninth, stand the rich. On which step are you today?”_ Being individual-specific, the answers to this question arguably give more complete information about the underlying economic welfare of that individual; _SAW_ will naturally reflect both household resources and individual command over those resources. However, we must also recognize that answers to this question are likely to be influenced by many factors that one might not want to include in a measure of economic welfare; personality traits, for example, can influence subjective welfare but not be deemed relevant to assessing whether a person is “poor” or not. We thus use the predicted values of _SAW_ based on relevant covariates as the preferred welfare metric (section 2). The data on _SAW_ establish the weights on various multiple objective dimensions of economic wellbeing.

> 12 Kapteyn (1994) provides an overview of this approach and antecedents in the literature.

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half indicate being unemployed. Around 60% of the respondents identify with socially and economically disadvantaged castes (OBC, SC/Dalit and ST), which prior studies suggest exhibit a lower awareness regarding malaria prevention (Singh et al., 2020). Household size ranges between 6 and 7 members. One of every eight households is home to a pregnant woman. Three-quarters of participants reside within 60 minutes (by walk) of a medical center, and a similar proportion has a mosquito net at home.

In terms of outcomes, 2% of respondents report a household member having experienced malaria in the past two weeks (and 20% within the last five years). About 70% of those with a bed net at home report having used it the previous night, with about 70% of household members sleeping under it. Combining these numbers with the average bed net ownership in the sample (75%) suggests that just over 50% of individuals are regularly protected from mosquito bites at night. Relatedly, approximately one-third of the participants express some level of concern about getting malaria in the following month.

As expected, our online sample exhibits a higher socioeconomic status compared to the general population. This is highlighted by population-level statistics from the 2019-2021 India Demographic

> 32The normalized difference is the difference between the two means divided by the square root of the sum of the variances of the two variables.

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Figure 3.20 Probability of going to museums, films, exhibitions, or sports events during the past year

|Family economic condition-well off (student response)<br>Mother's education sr. sec|||||||
|---|---|---|---|---|---|---|
|Student performance ranking - high (self assessment)|||||||
|school is in city<br>Student standardized test score|||||||
|-0.100|-0.050|0.000<br>0.050|0.100|0.150|0.200|0.250|

_Source_ : Authors’ calculation based on the CEPS.

# **Curriculum reforms for the academic track**

There have been continued curriculum reforms in China, and one of the primary goals of the reform in recent years is to emphasize holistic development of students (普普普普 ), shifting away from the exam orientation. The Eighth Curriculum Reform is one of the most ambitious reforms. The reform covered the entire basic education system including preschool, compulsory education (primary school and middle school), and high school. The high school part of the reform was enacted in 2004. It was first formally implemented in four provinces (Shandong, Hainan, Guangdong, and Ningxia) in China. Other provinces and municipal cities joined the reform in succession in the following eight years until 2012.

There are six specific implementation goals of the reform as stated in the MOE’s “Basic Education Curriculum Reform Outline” (MOE 2001).

- (a) Change the existing curriculum, which puts too much emphasis on imparting knowledge to students, to a new curriculum to emphasize helping students form positive and active attitudes toward learning.

- (b) Reduce the number of subjects and form a more balanced and comprehensive curriculum. Adjust the curriculum to satisfy