rafmacalaba/data-use-mentions-extended huggingface dataset:
9

**Control variables** . We also include a set of control variables that are commonly used in poverty equations: overall income per capita ( _GDP per capita_ ) to control for economic development, a measure of human capital level ( _Education_ ); a variable of financial deepening ( _Private credit/GDP_ ); growth of the consumer price index ( _Inflation_ ) to control for the macroeconomic environment; and an indicator of institutional quality ( _Law and order_ ) drawn from the International Country Risk Guide (ICRG) database which measures the strength and impartiality of the legal system, and the popular observance of the law.

Data sources are provided in Appendix 3.

# **C- Methodology**

The poverty regression presented above poses several challenges for estimation. The first is the presence of unobserved period- and country-specific effects. The second challenge is that most explanatory variables could be jointly endogenous with poverty, so we need to control for the biases resulting from simultaneous or reverse causation. For this purpose, we estimate the coefficients of our model by using the System Generalized Method-ofMoment (GMM) estimator developed by Blundell and Bond (1998). The estimator combines two sets of equations. The first set includes first-differenced equations where the right-hand-side variables are instrumented by the levels of the series lagged one period or more. The second set consists of the equations in levels with the right-hand side variables being instrumented by lagged first or higher-order differences.

The consistency of the GMM estimators depends on whether lagged values of the explanatory variables are valid instruments in the poverty regression. We examine this issue by considering the Hansen test of over-identifying restrictions. The no rejection of the null hypothesis implies that instrumental variables are not correlated with the residual and are satisfying the orthogonality conditions required. A serial correlation test is also carried out and demonstrates that the errors exhibit no second-order serial correlation.

# **D- Results**

A look at the plots in Appendix 4 which compare the trade-poverty relationship in the top country group and the bottom country group
limitations. For instance, the GoE, ACCRA and Oxfam are jointly developing a tool to estimate need based on _woreda_ risk profiles. Moreover, the NDRMC is working on the development of a multi-sector early warning system based on _woreda_ risk profiles, thereby further enhancing its existing early warning framework. In addition, the existing LEAP tool is being refined to include market data, to incorporate information to predict need in the pastoral regions of Afar, Somali and Borena, and to predict needs associated with flood risks. Similarly, LIAS baselines for the highlands regions are being updated in the course of 2016, to reinitiate the collection of LIAS data; with updated baselines and continued investment in the tool, it would be possible to reinitiate the use of LIAS data as part of seasonal needs assessments. These extensions and improvements will further strengthen Ethiopia’s early warning systems. Moreover, as more and better data become available with time, the predictive accuracy of the LEAP and LIAS tools will be improved further. The LEAP and LIAS tools in combination with hotspots and IPC assessments could be used jointly to trigger early action, where different sources of data could be triangulated to enhance accuracy.

Ethiopia’s current drought response mechanisms are centered on the use of PSNP contingency budgets and the HRD appeals process. The integration between the PSNP’s FCB and HRD Appeal process could be enhanced further by combining fast, early action based on early warning data with a slower response through the HRD process. In particular, approximate early warning-based no-regrets triggers could be used as a mechanism to effectively address needs associated with high-frequency, low-intensity drought events. Early warning data collected during the beginning of a rainy season (for instance, in August / September for the _meher_ season and in April / May for the _belg_ season) could be used to trigger early action, thereby preventing some of the worst impacts of a drought. By contrast, the HRD process could 25
system (greater credit to GDP ratio), in countries with higher education attainment, lower percentage of working age population, and greater adoption of mobile phone technology. Highly significant is also the association of stronger public governance with smaller trade-offs and possibly higher synergies between the inclusion of firms and financial stability. Also the inclusion of individuals correlates more positively with stability in countries that show sustained financial deepening (higher through-the-cycle growth of credit), higher education attainment (secondary enrollment rates), and greater informality—similar to the aggregate results. In contrast to the aggregate results and the results for firms, greater share of domestic private ownership in firms significantly mitigates the trade-off between inclusion and stability. However, greater foreign ownership amplifies the trade-off between the inclusion of individuals and stability. In addition to financial openness, fiscal freedom and investment freedom that proved important also on aggregate, financial sector liberalization (financial freedom) increases the trade-off between the inclusion of individuals and stability.

The multivariate conditioning on country characteristics (reported in Table 6) provides results that are broadly consistent with the univariate conditioning but the estimation sample is more representative of developing countries.<sup>24</sup> Financial openness can introduce or increase the trade-off between advancing

> 22 To support our conjecture, Annex 5 provides estimates of the difference between the risk-taking appetite between self-employed in the formal and informal sectors using the Life in Transition Survey II for countries with available data. We thank Hernan Winkler for providing us with the estimates.

> 23 This is the ‘fiscal freedom’ indicator in the Heritage Foundation’s Index of Economic Freedom.

> 24 Note that this exercise is done on a much smaller sample than the univariate conditioning. We see it as delivering complementary inference on the country characteristics influencing the covariance between inclusion and stability, rather than a superior source of inference.  To partially address the influence of the different sample sizes, we run two regressions constraining the sample size to 99 observations (Table 6, Column 1, 3 and 5) and 144
want to spend on these services, and the higher the income the higher is the willingess to have fast, broad-coverage and more expensive mobile and internet services. However, contrary to electricity or transport, once basic requirements of telecommunication are meet, these services provide luxury entertainment that is very responsive to income changes.

In our data set transport reflects mainly the household’s owning of vehicles (e.g. cars, motorbikes, bicicles) rather than expenditure on train, bus or airplane tickets. Therefore, it is likely that our results capture the income elasticity of passing from lower-quality, cheap vehicles to modern, fully equiped, powerful ones. A typical means of tranport in Vietnam is small motorbikes or scooters which are flexible and easier to use in cities with heavy traffic. However, the development of motorways is inducing also an increase in registered passenger cars, which increased by 437.5% between 2008 and 2019, while the number of registered motorcycles increased by 145.5% (ASEAN data).

> 4 There is a modest degree of self-production of food among the poorer households, which might explain the relatively low level of food expenditure.

17
# **3.** **<u>Data</u>**

We draw on several data sources. First, we use self-reported data (on household and business characteristics) collected by credit officers at the time of the loan application. Second, we use administrative data with loan characteristics and client repayment histories for all study loans. The data cover 100% of clients from loan disbursement until three months past loan maturity (and 99.3% until 12 months past maturity), with loan maturity accounting for extensions due to passes. The data span 49 months from when the first loans were disbursed until 30 months after the last set of loans were disbursed.

Third, the lender conducted client satisfaction phone surveys on a subsample of study clients. The lender’s staff called both standard and flexible loan clients to assess client attitudes towards their loan product, their level of knowledge about the product’s features, and the reasons for pass use among clients who had used them. Respondents were chosen randomly from the pool of clients every month over 18 months, stratifying each month by credit officer and loan type.<sup>5</sup> In total, 575 phone surveys were completed for 457 different clients, representing 18% of all clients in the study sample. Phone surveys were made on average six months after loan disbursement.

Lastly, we conducted an in-person follow-up survey. This survey was brief (median survey duration was 34 minutes) and took place at clients’ businesses or homes around ten months (sd=2 months) after the loan disbursement. Since loans were disbursed over time, the survey was conducted on a rolling basis to ensure comparable duration post loan disbursement. Respondents were asked about loan repayment behavior and a set of business and household outcomes. We achieved a response rate of only 69%, we fail to reject a difference in levels across experimental arms (69% response rate for both treatment and control groups) and we fail to reject compositional
percent aspired to it; 21 percent expected their children to do so while 40 percent aspired to it (Garcia, Harker, and Cuartas 2019). Similarly, when asked about educational options they were aware of and felt academically able to follow, French junior-high-school students reported that they felt able to follow only a subset of options of the ones they were aware of (Guyon and Huillery 2021). In El Salvador, Mexico, and Uruguay, a housing program for slum-dwellers had a positive impact on participants’ aspirations but not their expectations, and their expectations were found to be unrelated to the evolution of their housing aspirations over time (Galiani, Gertler, and Undurraga 2021).

# **3. Data**

## _Data set_

We use a large cross-sectional survey that is representative of students in public, secular, middle schools on the Indonesian islands of Java and Sumatera, which are home to 70 percent of the Indonesian population. The survey, collected in February-March 2018, covers 55,964 8<sup>th</sup> grade students studying in 2,095 public schools.<sup>3</sup> The data was collected as the baseline of an impact evaluation of a pilot intervention aimed at improving students’ aspirations, mindsets, socioemotional skills, studying practices, and learning outcomes (Johnson et al. 2020).

## _Measures of outcomes and correlates_

**Schooling outcomes** . We measure two current schooling outcomes: absenteeism and grades. Absenteeism (the opposite of school attendance) is the number of missed days of school in the month preceding the survey, which is self-reported by the students. Students who did not miss any day—51 percent of the sample—are marked with a zero. Eighty percent of students who missed at least one day report they missed school because of sickness. Students who mention other factors for missing schools, such as family’s demands, school and weather factors, and issues related to their behaviors, miss more days
Hyde, J. S. (2005). The gender similarities hypothesis. _American Psychologist_ , 60(6):581.

Hyde, J. S. and Mertz, J. E. (2009). Gender, culture, and mathematics performance. _Proceedings of the National Academy of Sciences_ , 106(22):8801–8807.

Jensen, A. R. (1999). The g Factor: The Science of Mental Ability. _Psycoloquy_ , 10(04):36– 2443.

Karkee, V. and Niall, O. (2023). African youth face challenges in the transition from school to work. Technical report, ILO.

Laajaj, R. and Macours, K. (2021). Measuring skills in developing countries. _Journal of Human Resources_ , 56(4):1254–1295.

Laajaj, R., Macours, K., Pinzon Hernandez, D. A., Arias, O., Gosling, S. D., Potter, J., Rubio-Codina, M., and Vakis, R. (2019). Challenges to capture the big five personality traits in non-WEIRD populations. _Science Advances_ , 5(7):eaaw5226.

Lundeberg, M. A., Fox, P. W., and Pun ́ccoha ́r, J. (1994). Highly confident but wrong: Gender differences and similarities in confidence judgments. _Journal of Educational Psychology_ , 86(1):114.

Napolitano, C., Molina, D. C., Johnson, H. C., Oswald, F., Hernandez, D. A. P., Tiwari, A., De Martino, S., and Trzesniewski, K. (2021). Are growth mindset, mastery orientation, and grit promising for promoting achievement in the Global South? Psychometric evaluations among Indonesian adolescents.

Niederle, M. and Vesterlund, L. (2007). Do women shy away from competition? do men compete
positive imports of capital goods in year _t_ . Output tariff(s)(t-1) are MFN applied tariffs from WITS-WB dataset at the 3 digit industry level and input and capital goods tariffs are constructed separately using these output tariffs and India 1993 inputoutput matrix. Importer inputs is a dummy equal to one if the firm imports intermediate goods. Herfindahl index measures the concentration of sales of the industry. Capital intensity is measured by capital stock over sales of the firm. The Prowess dataset reports the year of creation of the firm that allows to construct the age of the firm. Heteroskedasticity-robust standards errors are reported in parentheses. Errors are corrected for clustering at the 3-digit industry level.<sup>_∗∗∗_</sup> ,<sup>_∗∗_</sup> , and<sup>_∗_</sup> indicate significance at the 1, 5 and 10 percent levels respectively.

_The heterogeneous effects of input tariff cuts_ 33
the survey questionnaires could render the latter variable incomparable over time. For example, 14 percent of total household consumption was comprised of items that were found in 2015 only. Furthermore, comparing household consumption between 1994 and 2015, 12 percent of total household consumption in 1994 is accounted for by consumption items that are more disaggregated than 2015; the corresponding figure for 2015 compared with 1994 is 11 percent. Still, when we re-plot Figure 1 using household consumption per capita, estimation results shown in Figure 1.1 (Appendix 1) indicate similar patterns.

> 12 The downward sloping trend of the Gini coefficient is consistent with the findings in other studies that use earlier data from the RLMS, including Gorodnichenko _et al._ (2010) and Denisova (2012). We also restrict our analysis to 1994, when the RLMS was first implemented. See Milanovich (1998) for a study that analyzes data from Russia for earlier periods.

15
reverting error, attenuation is not guaranteed. If the ‘shrinkage’ of the variance in the first term in the denominator due to multiplying by λ<sup>2</sup> (for 0<λ<1) exceeds the effect of adding the variance of the random noise term ( σ _v_ 2 ), the response coefficient is overstated rather than understated. Also, the variance of the error-ridden variable is less than that of the true variable, contrary to what is possible with the reliability ratio interpretation.

Knowing if the coefficient on the proxy for permanent income is either attenuated or exaggerated seems important for many of the policy conclusions that economists may draw from regressions where surveyed household consumption is a key explanatory variable. Moreover, when economists attempt to deal with possible attenuation by using instrumental variables for household consumption (e.g., Alderman et al, 2006) they are using an estimator that is inconsistent when measurement errors are correlated with true values (Black _et al._ 2000). Once again, knowing more about the nature of measurement error in household consumption data may help improve modeling practice and interpretation of empirical results.

# **III. The Survey Experiment and Evidence from Village Averages**

The designs of the eight alternative consumption modules are described in Table 1. They differ by method of data capture (diary versus recall), by respondent (individual versus household reporting), by recall period (7 day, 14 day and usual month), and by number of items in the recall list. The designs were strategically selected to reflect the most common consumption modules used in multi-topic living standards surveys in developing countries (which typically seek less commodity detail than do household budget surveys). Design variation was restricted to foods and frequently purchased non-foods, but assignment to different modules also affects reports on infrequently purchased items, which were covered by a set of annual recall questions common to all households. Beegle et al (2012) ascribe this impact on the infrequent items as due to either
Policy Research Working Paper Series

|T,tle|Author|Date|Contact<br>**for**paper|
|---|---|---|---|
|WPS1760 Credibility of Rules and Economic<br>Growth: Evidence from a Worldwide<br>Survey of the Private Sector|Aymo Brunetti<br>Gregory Kisunko<br>Beatrice Weder|April 1997|M. Geller<br>31393|
|WPS1761 Bending the Rules: Discretionary<br>Pollution Control in China|Susmita Dasgupta<br>Mainul Huq<br>David Wheeler|May 1997|E. de Castro<br>89121|
|WPS1762 Strategies for Pricing Publicly<br>Provided Health Sertvices|Paul J. Gertler<br>Jeffrey S. Hammer|May 1997|C. Bernardo<br>31148|
|WPS1763 China and the Multilateral Investment<br>Guarantee Agency|Yushu Feng|May 1997|E. Beers<br>36175|
|WPS1764 A Reversal of Fortune for Korean<br>Women: Explaining 1983's Upward<br>Turn in Relative Earnings|Yaba vab der Neykeb<br>Rodgers|May 1997|D. Ballantyne<br>87198|
|WPS1765 Explaining Agricultural and Agrarian<br>Policies in Developing Countries|Hans P. Binswanger<br>Klaus Deininger|May 1997|D. Housden<br>36637|
|WPS1766 New Systems for Old Age Security:<br>Theory, Practice, and Empirical<br>Evidence|Estelle James|May 1997|S. Khan<br>33651|
|WPS1 767 Pension Reform: Is There a Tradeoff<br>between Efficiency and Equity?|Estelle James|May 1997|S. Khan<br>33651|
|WPS1768 Is There a Quantity-Quality Tradeoff<br>as Enrollments Increase? Evidence<br>from Tamil Nadu, India|P. Duraisamy<br>Estelle James<br>Julia Lane<br
0.05|0.00|2126|
|Compassion|3.75|3.67|-0.07|0.00|2126|
|Self-Sacrifce|4.05|4.14|0.08|0.00|2126|
|PSM Index|-0.01|0.02|0.04|0.43|2126|
|_Panel D: Cognitive and risk profle measures_||||||
|Altruism - percentage shared|0.29|0.32|0.04|0.00|2125|
|Choose dominated risk option|0.10|0.13|0.03|0.04|2126|
|Risk-aversion (1-5)|3.72|3.91|0.19|0.01|1869|
|Cognitive ability - Number of digits remembered|5.52|5.25|-0.28|0.00|2126|

_Note:_ This table compares average characteristics of politicians and bureaucrats. Column (1) reports the average characteristic for all politicians, while column (2) does the same for bureaucrats. Details about the construction of variables are presented in the Annex. Column (3) presents the difference between politicians’ and bureaucrats’ means. Column (4) presents the p-value of a test with null hypothesis of equal means. Column (5) reports the number of observations with non-missing values in each test.

44
50, 100, and 200 year events, under current and future climate conditions.

There is a significant amount of uncertainty with regards to how much sea level will rise. For that reason we model three future climate scenarios per return period: a low, medium, and high scenario (Table 1), using estimates from the IPCC (IPCC 2014; IPCC 2007). For the fluvial and pluvial hazards, future climate scenarios were not explicitly simulated owing to the complexity and considerable uncertainties that arise (Smith et al. 2014).<sup>1</sup> Although robust modeling of the magnitude of future extreme rainfall is not yet possible, heavy rainfall is expected to increase in a warmer climate, owing to the increased water holding capacity of the atmosphere. Therefore instead of a direct modeling approach, future climate scenarios were inferred by taking flood hazard maps derived under current climate conditions for different return periods, and using

> 1 These uncertainties largely arise from climate models; global climate models (GCMs) struggle to represent the physical processes that produce extreme rainfall. Indeed even in higher resolution regional climate models (RCMs), heavy rainfall events are poorly represented. As a result the modelled rainfall data must be ‘corrected’, in order to render it realistic. The fact that the underlying models themselves cannot represent flood driving rainfall means that there is little confidence in the projections that they produce. Moreover, at the national scale there is very little river gauge data available in Vietnam. Therefore rainfall‐runoff models, required to transform rainfall projections into river discharge values, would be largely un‐calibrated. This adds an additional source of significant modeling uncertainty to the model cascade. The combination of poorly represented extreme rainfall in climate models, coupled with uncalibrated rainfall‐runoff models, would largely render any projections of future flood risk impractical, owing to the significant uncertainties that arise.

4
**Colombia.** ( _Financial Institution Guarantee Fund, Banking Law 117 of 1985_ ) The deposit insurance scheme of Colombia was established in 1985. The scheme is government legislated and administered and membership to the system is mandatory. Deposits in foreign currencies are excluded, whereas inter-bank deposits are not. The coverage is per depositor per institution up to 20 million Colombian pesos with a 25% co-insurance. The general premium rate is currently 0.5% on all deposits which will go down to 0.3% after January 2007.

_Source_ : IADI Survey: Colombia (2002).

**Croatia.** ( _State Agency for Deposit Insurance and Bank_ Rehabilitation) The deposit insurance scheme of Croatia was established in 1997. Even though the system is privately administered, some decisions must be approved by the central bank. Inter-bank deposits are not covered. The scheme extends coverage to deposits in foreign currencies, except to foreign currency deposits placed prior to 1993, which were covered by a government bond issue. The fund may borrow form the central bank. _Sources_ : Garcia (1999), Kyei (1995).

**Cyprus.** ( _Deposit Protection Scheme, Central Bank of Cyprus_ ) The deposit protection scheme of Cyprus came into effect on September 1<sup>st</sup> , 2000. It is jointly administered by the Central Bank and Management Committee. Membership is mandatory for the scheme and it covers all deposits except entities or persons against which criminal proceedings have been instigated or which a confiscation order has been made. The coverage limit is 90% of the Cyprus pound equivalent of EUR 20,000 per depositor per institution. _Source_ : IADI Survey: Cyprus (2003).

**Czech Republic.** ( _Deposit Insurance Fund, Act No 156, 1994_ ) The Deposit Insurance Fund of the Czech Republic was established in December 1994. It is government legislated and privately administered. The insurance is granted for savings and checking accounts as well as certificates of deposit and foreign currency