rafmacalaba/data-use-mentions-extended huggingface dataset:
● Cuttack ● ●●●●● JalandharLahore ●● Ludhiana Kathmandu ● ● Bokaro ● Dhanbad ● Moradabad ● Bareilly ● Aligarh ●● ● ●● ●●●● KanpurKolkataDelhi ● Lucknow ● Gorakhpur ● Patna ● Regionsaa ●● SARSSA<br>● ● ● ● ● ● ● ●● Bhubaneswar ●● Ranchi ● ● JamshedpurDhaka ● ●●● ● Agra ● Asansol ● GhaziabadVaranasi<br>● ● Gwalior Khulna Rajshahi Faridabad<br>−2.5 ● ●● ●<br>● ●<br>●<br>● ● ●<br>●<br>−5.0 ●<br>0 25 50 75 100<br>PM 2.5 in 2015<br>City GVA per capita compared to National GVA, 2006−2015<br><!-- End of picture text --> Dhaka is also struggling with high levels of air pollution, although levels are lower than what we can find in Patna for example. The Clean Air and Sustainable Environmental Project had certainly helped managing

> 20 Published in India Times, <u>https://timesofindia.indiatimes.com/city/patna/patna‐air‐pollution‐worse‐than‐that‐ of‐delhi/articleshow/61664183.cms, accessed on May 4, 2018.</u>

> 21 It is worth noting that, during 2015, productivity had increased approximately 2.5%. However, a similar rate was observed in 2009, although employment was growing at 5.5% at that time.

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the end product to avoid simple yes/no questions that tend to be more susceptible to response bias (cp. Online Appendix S2). For inorganic fertilizers, enumerators used pictures to identify the type of fertilizer used by the farmer and in addition checked the labels on fertilizer bags.<sup>9</sup> For lime, they also inspected the respective bags. In order to verify the use of improved seeds, the survey contained detailed questions on the original source of the seed and for how long it had been reused. If seeds had been reused for more than four seasons, they are not considered improved seeds in the analysis, because improved traits get lost over generations.<sup>10</sup> The endline survey further comprised questions on the participation in ISFM+ extension activities as well as a detailed knowledge test on ISFM technologies. Enumerators first assessed farmers’ awareness by asking them which ISFM components they actively remembered, and in a second step, asked them which practices they recognized when read to them off a list by name.<sup>11</sup> Subsequently, questions on their underlying principles and purpose (‘principles knowledge’) as well as their mode of implementation (‘how-to knowledge’) were posed. The survey combined different types of knowledge questions, including open-ended and multiplechoice questions, to minimize fatigue effects (for details of the knowledge exam, see Online Appendix S3).

For the survey, a team of 34 enumerators was recruited and intensively trained during a tenday training period. Questionnaire contents were carefully translated into the three local languages and pre-tested in several rounds. In addition to the farm household survey, the survey team administered two community level questionnaires to key informants at the Woreda and mws levels, in order to collect data on infrastructure, availability of extension services, rainfall and temperature, as well as other contextual characteristics.

> 9 Even if bags are empty, farmers usually keep them for other purposes, e.g., to sit
, hands and fingers), affect (anxiety and depression), pain and fatigue (e.g. Loeb 2016).

# **Box 1: Washington Group Short Set of Questions on Disability**

The next questions ask about difficulties you may have doing certain activities because of a health problem.

- (a)  Do you have difficulty seeing even if wearing glasses?

- (b)  Do you have difficulty hearing even if using a hearing aid?

- (c)  Do you have difficulty walking or climbing steps?

- (d)  Do you have difficulty remembering or concentrating?

- (e)  Do you have difficulty with self-care such as washing all over or dressing?

- (f) Using your usual language, do you have difficulty communicating, for example understanding or being understood?

For each question, respondents are asked to answer with one of the following options: 1-no difficulty, 2-some difficulty, 3-a lot of difficulty, or 4-unable to do.

For a proxy respondent, each of the six questions starts with “does <person > have difficulty...?” - <u>Source: http://www.washingtongroup disability.com/</u> While the WG recommends that the WGSS be adopted as is, some data sets have included selected questions only, changed the answer scale or the wording of questions. There are thus data sets that have questions somewhat similar to the WGSS. As shown in Table 2.1, 12 data sets under study have the WGSS, while 12 data sets have other functional difficulty questions that fulfill the United Nations principles and guidelines for censuses on disability (United Nations 2017, p. 207) in that they cover at least the four essential domains. The ways in which these 12 6
# **1 Introduction**

Investments in early childhood are a critical determinant of later life outcomes, and stimulating activities — for example, shared reading and infant-directed speech — are an important way that older family members invest in young children (Knudsen, Heckman, Cameron, and Shonkoff 2006, Grantham-McGregor _et al_ . 2007, Almond and Currie 2011, Walker _et al_ . 2011, Aizer and Cunha 2012). Underinvestment in early childhood is an acute problem in low- and middle-income countries (LMICs), where an estimated 43 percent of children are at risk of failing to meet their developmental potential because of inadequate nutrition and cognitive stimulation (Black _et al_ . 2017). A growing interdisciplinary literature examines the causes and consequences of parental investments in young children in LMICs, seeking to identify interventions that can change parenting practices to improve developmental outcomes in children and increase incomes in adulthood (cf. Gertler _et al_ . 2014, Black _et al_ . 2017, Andrew _et al_ . 2018). However, parents are not the only caregivers in most societies — in many low-income contexts, much of that work is done by older siblings, particularly sisters (Weisner _et al_ . 1977, Lancy 2015). Though this pattern is well-documented in the anthropology literature, older siblings’ role in childrearing is often ignored in academic and policy discussions of investments in early childhood.<sup>1</sup> We model older siblings’ contributions to the human capital accumulation of young chil-

> 1Though older siblings are known to play an important role in caring for young children in LMIC contexts, standard approaches to quantitative measurement frequently ignore both the investments older children make in their younger siblings and the impacts that early childhood interventions (including those that seek to change childrearing practices) might have on sibling caregivers. For example, the standard format of the Family Care Indicators, one of the most widely used measures of early childhood stimulation, does not record stimulating activities carried out by household members under 15 years old (Hamadani _et al_
social-level determinants of subjective well-being. Both papers categorize the determinants roughly in income, personal characteristics, attitudes and beliefs, work conditions and macro environment.

**There is agreement in the literature that the correlation between income and subjective well-being is at most weak, leaving room for other factors to explain the perceptions of well-being.** For instance, Dolan et al. (2008) notice that results in the literature generally suggest positive but diminishing returns to income. Zaidi et al. (2009) using the 2006 LiTS obtain a positive correlation between income and satisfaction, though Cojocaru and Diagne (2013) find only a weak correlation between objective welfare and the household relative income position using the the 2010 LiTS. Clark and Oswald (1994) in the UK, and Frey and Stutzer (2000) in Switzerland find at most a low correlation between income and subjective-well-being.

**Income inequality can affect negatively the perceptions of well-being when is associated with an unfair process and unequal distribution of opportunities.** Using data for Europe and U.S. states, Alesina et al. (2004) obtains that even after controlling by income a higher national-level inequality is associated with more negative perceptions of well-being. However, it may also be the case that for countries with higher economic mobility inequality communicates opportunities, and hence higher inequality may signal a higher reward to effort, and have a positive effect on well-being (Dolan et al. 2008). The 2006 World Development Report highlights that income inequality influenced people’s happiness – regardless of absolute income levels- linked to perceptions of “unfair processes and unequal distribution of opportunities” in society (World Bank 2005, p.82). Finally, Abras (2012) obtain that circumstances determined by the lottery of birth (e.g. gender, parental status and politics), affect the perceptions of well-being when they play a role in determining income by means of facilitating positions or contracts.

**Perceptions of fairness are also correlated with higher levels of reported self-satisfaction
>102</sup> Since unit costs of production are not available for cinnamon and cloves, we use their (national) FOB export prices instead.

# **A.E Fertilizer Use and Subsidies**

To compute chemical fertilizer use in the production of various agricultural crops, we use data provided by Sri Lanka’s NFS. Fertilizer requirements for 2022, displayed in Appendix Table A2, are reported as MT of fertilizer required per ha of cultivated land for each of 23 crops. As explained in Section IV.C, this fertilizer intensity metric is used in our main analysis to build a firm-level fertil102Due to our model’s perfect competition assumption, a crop’s unit cost of production equals its (farm-gate) producer price, which justifies using the former (which is available in the Economic and Social Statistics report) as a proxy for the latter. For tea and rice, unit costs are reported for the whole island, but for maize, onions, and potatoes they are reported for individual districts. We use data from Puttlam for onions and from Badulla for maize and potatoes, as these districts are major producers of their respective crops.
outcome variables on export practices, and assumed a Gaussian prior with mean equal to this product, and standard deviation derived from the standard error in the cross-sectional estimation and the assumed standard deviation on the impact on export practices. Full details and the registered priors are contained in the study’s registration in the AEA registry.

## **3.6 Weakly Informative "Default" priors**

For comparison purposes we also generate Bayesian results using highly diffuse or "weakly informative" priors, which are now the default standard for Bayesian analysts in cases where specific outside information is lacking (e.g. Meager (2019), Lemoine (2019), Thorlund et al. (2013), Chung et al. (2012)). These priors perform mild regularization on the estimation procedure, and we follow the literature above in using diffuse Normal priors centered around zero for coefficient parameters, and using diffuse half-Normal or halfCauchy priors on variance parameters. In theory, the impact on the estimation from these priors should be quite minimal. This enables us to see how much of any difference in results is coming from the Bayesian impact evaluation techniques alone, versus through the specific additional information contained in our elicited priors.

# **4 Data and Methods for Estimating Treatment Effects**

## **4.1 Data and Main Outcomes**

Our primary hypothesis is that the program will lead more firms to export, diversity the range of products exported and destinations exported to, and improve the export performance of participating firms. Our primary outcomes of interest are therefore export outcomes. We use annual data on exports from 2010 to 2020 provided by the National Directorate of Taxes and Customs (DIAN) and supplied to us by the Colombian National Planning Department (DNP). 135 of the 200 firms exported at least once during these 11 years. These data provide export values at the 6-digit product and destination country level for each firm. For example, perfumes and cosmetics exported by a firm to Ecuador in 2018,
for the particular skills of less educated and less able villagers in other committees and roles. This may also result in a sense among participants that potential benefits of participation do not warrant the time and energy required to participate. Thirdly, the ways in which groups (their leaders, and constituent individuals) interact with each other and define, defend, and reconstruct their identity—or, more accurately, particular forms of identity in response to particular circumstances—ultimately shapes the power of groups.<sup>71</sup> For example, norms of decisionmaking in KDP forums may militate against women, the poor, and individuals from certain cultural traditions. Where these individuals are not encouraged to participate, the (il)logic of their membership in a particular identity group may preclude quick involvement in a novel associational setting. Such problems are well known to facilitators of participatory processes in developing and industrialized nations alike.

Thus another key question is whether—in addition to providing inclusive decision-making forums—such participatory collaborative processes can help generate such points of strength for coalitions of marginalized groups to develop countervailing power, and if so, how? Does KDP in fact empower villagers in this way? We argue that KDP can over time, but the initial stage of this brand of empowerment may be neither flashy nor definitive in their observable implications. Our case studies do suggest that typically KDP forums catalyzed formal associational interactions and sustained deliberation between diverse groups of women and the poor who may otherwise have found no reason to interact with one another. Key informant surveys from wellfunctioning KDP districts reveal that villagers find its deliberative forums more democratic than most other forums in their villages.<sup>72</sup> In addition to these findings, a good indicator of empowerment is whether or not KDP provides forums for the management of the conflict it necessarily introduces to villages and neighborhoods. By this measure, it does exceptionally well. In none of our case studies did we find evidence that conflicts caused by KDP forums (for example,
Traditional neoclassical economics suggests possible explanations such as a lack of relevant information or large countervailing costs. In turn, policy makers and researchers have often focused on the health system, user fees, or information, in seeking to remove external obstacles and encourage healthy behaviors. But, while effective, these actions alone have been insufficient to address the full complexity of health behavior change and habit formation. Relative ignorance or limited knowledge on these issues might once have been widespread and undoubtedly still exist among certain population groups. However, in most countries, the majority of adults are now aware of the health risks of, for example, tobacco and alcohol use (i.e., WHO Global Adult and Youth Tobacco Surveys). Hence, lack of knowledge is unlikely to be a driving explanation of unhealthy behaviors. Similarly, although for some people in some situations the actual cost of a behavior change (e.g., giving up smoking) might be high enough that the ‘rational’ decision is not to do so, this is not the case across all such behaviors, nor for most people. A modest reduction in unhealthy behaviors such as high calorie consumption, or a modest increase in healthy behaviors such as walking more, generally has both a low cost and often also some direct near-term benefits such as improved energy and sleep, entirely independent of long-term health outcomes. Hence this is again unlikely to be a driving explanation, and indeed many people report that they wish they acted differently in these respects (Faries M. D. 2016), strongly suggesting that they are not in fact optimizing their utility according to the traditional framework.

Policy efforts towards behavioral and psychological obstacles that influence unhealthy lifestyles and habit formation are needed. Unlike many other causes of morbidity and mortality, NCDs are typically delayed - in the sense that negative outcomes occur years or even decades after the precipitating behaviors- and are often only weakly linked to identifiable individual moments in time. Why would I then change my behavior today for something that might
December-February, monsoon takes the value 1 for June-September, and autumn takes the value 1 for October-November, and 0 otherwise.

Access to credit is identified with the loan indicator variable that takes the value 1 if the household had taken any loans in the last 12 months from family, friends, micro-finance institutions, banks, or other sources. The safety net indicator variable takes the value 1 if at least one member of the household benefited from one of the safety net programs (See Table A2 in annex tables) and 0 otherwise.

The access to market index measures how easily people can reach markets; it is the sum of the population of the markets in the vicinity of a location inversely weighted by the travel time along the transportation network to these markets (Blankespoor and Yoshida, 2010). The index was calculated with the negative exponential potential accessibility model for 202 markets with populations ranging from approximately 15,000 to 6,500,000 (Dhaka) and aggregated at the Upazila level. The access to market index is a continuous variable that takes values between 0 and 1. **Map 2** shows the access to market index for various Upazilas in Bangladesh. The construction of local rainfall variability, and historically flood prone areas are described in detail below.

We control for other factors such as household age-group composition with three variables, number of females in the household ten years or older, number of males in the household ten years or older, and number of dependents. We include the number of household members between 10 and 65 engaged in agriculture in some of the specifications. Household level education is measured by the share of literates in the household (See Table A1 for a complete list of variables and their descriptive statistics).

We use a household wealth proxy with land ownership and livestock indicator variables. Land ownership takes the value 1 if the household owns more than the average land in the survey and 0 otherwise. The average land is the mean of land owned by the households that own land.
. Using a data set comprising 169 countries and covering the period from 1991 to 2013, the paper finds that structural change has played a critical role in enhancing economic performance since the early 2000s, even if it remains comparatively less important than within‐sector productivity improvements. The widespread reallocation of labor from agriculture to the services sectors has been the key driver of structural change. The paper also finds robust evidence that the pace of structural change is significantly shaped by human and physical capital.

4
# _3.3 Estimation Approach_

We use two core sets of analyses to estimate the impacts of warrantage. First, we set out to quantify the effects of receiving access to warrantage. Second, we estimated the spillover impacts of warrantage by examining impacts on non-treated households by comparing non-participant households in low and high exposure villages.

To begin, we quantified the effects of warrantage among households that expressed interest in participating. To do so, we estimated the following model: h1 1T T T h h0 + γ h0 (1) vv hvv YY = αα + ββ TT + δδYY + ZZ + uu where _h_ indexes households and _v_ indexes villages. The sample was restricted to all lottery participants. T T T h is a binary indicator equal to one if the household won the lottery and thus received access to warrantage. TT _Yh1_ is the outcome measure as measured during the endline survey. _Yh0_ is the baseline value of the outcome measure, included whenever available. Continuous variables are presented in FCFA, winsorized at the 99<sup>th</sup> percentile.<sup>7</sup> _Xh0_ is a vector of household controls, all measured at baseline, including indicator variables for whether the household head is married or is a polygamist, as well as the number of total spouses, household size, the value of warrantage crops, amount of land owned, and an indicator variable for whether the household head was familiar with warrantage.<sup>8</sup> Due to village-level lotteries, we include village fixed effects, denoted by . We clustered standard errors by village to account for within-village correlation of vv unobserved variables. Here, ZZ 1 measures the impact of receiving access to warrantage among ββ

> 7 Results are qualitatively similar when using alternative specifications, such as using log transformations of continuous variables.

> 8 Note that all results are qualitatively similar when we exclude covariates from the analysis.

13
supervisory power (borrower) in column 4, indicating that international banks avoid foreign subsidiary usage in case of greater official supervisory power in borrower countries. The foreign subsidiary and borrower country subsidiary shares vary positively with Monitoring (borrower) in regressions 4 and 5, as better financial market monitoring institutions in borrower countries appear to make borrower country subsidiary usage more attractive. In addition, the foreign subsidiary share is positively and significantly related to Creditor rights (borrower), and negatively and significantly to Time to enforce contracts (borrower). Overall, regression 4 provides evidence that foreign subsidiary usage is positively related to the quality of institutions in borrower countries as related to financial market monitoring, creditor rights, and the time to enforce contracts, while foreign subsidiary usage is negatively related to borrower country supervisory, power consistent with regulatory arbitrage.

Bank regulation potentially is endogenous to absolute and relative loan volumes. Borrowing countries experiencing large syndicated loan provision by local subsidiaries of international banks, could, for instance, increase the quality of regulation to discourage such credit provision. To mitigate potential endogeneity, we next re-estimate regressions 4-6 of Table 4 using instrumental variables (IVs), taking Capital regulation (borrower), Overall activity restrictions (borrower), Official supervisory power (borrower), and Monitoring (borrower) to be potentially endogenous. Following Houston et al. (2012, p. 1879), we employ instrumental variables that have been advanced in the literature as possible determinants of regulation. First, we use the time-varying means of the regulatory variables (excluding the pertinent country) to reflect possible ‘regulatory contagion’ (see DemirgucKunt and Detragiache, 2002).<sup>20</sup> Second, we use a dummy variable indicating that the central bank supervises banks for prudential purposes (from the World Bank regulation

> 20 <mark>Specifically, in case of a borrower-country regulatory variable, we instrument it by the mean of this variable for all borrower countries excluding the pertinent borrower country. In the regressions with bilateral data,