rafmacalaba/datause-encoder-data huggingface dataset:
Within this category of research questions, greater attention also needs to be given to better understanding the development possibilities in fragile and conflict-affected states. Depending on the definition used, between 500 million and 1 billion people live in states seriously affected by conflict or fragile governance. In contrast to most of the remaining developing world, these have seen little progress in terms of development outcomes and are becoming an increasingly serious part of the global development problem. The 2011 _World Development Report_ addresses this question by examining the relationships among peacebuilding, state-building and development. The Report also explores how to build confidence and state legitimacy, through inter-related actions on security, economic development, governance, and the provision of justice. However, sustained research will be needed to improve our understanding of alternative approaches to this problem, as well as the associated challenge of reconciling local identity and governance concerns with an increasingly globalized development process.

Another important sub-theme concerns how to better utilize and protect various aspects of the global commons in a growing and rapidly urbanizing world. While globalization has been a potent force for development, the crisis has also exposed the fragility of growth to policy failures and spillover effects among nations in relation to natural resources and the environment. Economic growth also places increasing pressure on common resources. Given demographic imbalances between countries, and the threat of larger-scale environmental disruptions in the future, migration also looms as a growing issue. How should global arrangements be reformed to ensure that these challenges are widely seen as important and legitimate, and that international responses provide a robust and supportive framework for sustainable development? Ensuring markets and financial flows is critical but we must also look beyond these.

How can developing countries better mitigate and adapt to the longer-term effects of climate change, and how can the prospects for rapid economic progress without unmanageable climate change be enhanced? Widespread instances of water scarcity, depletion of fisheries, deforestation, and loss of biodiversity pose similarly serious challenges, even in the nearer-term. With rapid urbanization expected to continue, moreover, what urban development initiatives are most important in terms of infrastructure expansion, increased energy efficiency, and improved resilience?

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# **Table VIII:** Program impacts on height-for-age z-scores (children of beneficiaries: **baseline schoolgirls** )

|**Panel A: Born During Program**|**Raw Effect**<br>Gender|+ Maternal<br>Selection<br>weights|+ Paternal<br>Selection<br>Controls|+ Child Age|**Direct Effect**<br>+ Mother<br>Age|
|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|
|=1 if Conditional Schoolgirl|0.155|-0.050|-0.054|0.023|0.124|
||(0.162)|(0.192)|(0.186)|(0.177)|(0.155)|
|=1 if Unconditional Schoolgirl|0.953**|0.525**|0.549*|0.666**|0.523*|
||(0.476)|(0.221)|(0.306)|(0.315)|(0.299)|
|p-value UCT vs. CCT|0.091|0.022|0.028|0.024|0.115|
|p-value Treatment|0.123|0.040|0.089|0.072|0.218|
|Sample Size|315|315|315|315|315|
|**Panel B: Born Within 9 Months of Program E**|**nded**|||||
|=1 if Conditional Schoolgirl|0.251|0.156|0.235|0.125|0.086|
||(0.279)|(0.263)|(0.240)|(0.175)|(0.194)|
|=1 if Unconditional Schoolgirl|0.177|0.163|0.109|-0.431**|-0.434**|
||(0.514)|(0.315)|(0.336)|(0.183)|(0.193)|
|p-value UCT vs. CCT|0.887|0.984|0.725|0.013|0.028|
|p-value Treatment|0.663|0.787|0.619|0.028|0.047|
|Sample Size|214|211|211|211|211|
|**Panel C: Born More than 9 Months After Pro**|**gram Ended**|||||
|=1 if Conditional Schoolgirl|-0.011|0.497|0.149|0.264|0.257|
||(0.187)|(0.445)|(0.199)|(0.196)|(0.179)|
|=1 if Unconditional Schoolgirl|-0.351**|-0.651***|-0.336|-0.102|-0.123|
||(0.174)|(0.242)|(0.212)|(0.168)|(0.183)|
|p-value UCT vs. CCT|0.115|0.006|0.025|0.068|0.078|
|p-value Treatment|0.114|0.002|0.075|0.184|0.186|
|Sample Size|507|506|506|506|506|
|<br>Control Structure:||||||
|Maternal selection controls + propensity weight||X|X|X|X|
|Father selection controls|||X|X|X|
|Cubic in child age in months||||X|X|
|Maternal age in years, age interactions|||||X|

_Notes:_ Regressions are OLS models with robust standard errors clustered at the EA level. All regressions are weighted to make them representative of the target population in the study EAs. The height-for-age z-score is calculated using the 2006 WHO child growth standards. Specification (1) controls for the gender of the child. Specification (2) adds selection weights and controls directly for maternal baseline characteristics ( stratum indicators, household asset index, highest grade attended, and an indicator for never had sex). Specification (3) adds controls for paternal attributes (highest education level, religion, ethnicity, main activity, and likely HIV status). Specification (4) adds a linear, quadratic, and cubic in child age. Specification (5) adds maternal age and maternal age interacted with the other baseline covariates. We restrict the sample to respondents who were surveyed during the latest household survey conducted two years after the program (Round 4). Parameter estimates statistically different than zero at 99% (***), 95% (**), and 90% (*) confidence.

49
a considerably higher incidence of 74.1%. The chosen solution only uses an average of 3.9 questions per household, allowing 94.6% of the population to be sampled to achieve an incidence of 78.3%. Further average length reductions yield little benefit in terms of respondent numbers, and decrease accuracy so much that the overall effect on incidence is negative.

This case study suggests that TrESt has significant potential for raising incidence in a suitable setting. The case study relies on limited information and should be interpreted as a stylized example rather than as a fully calibrated use case. Nevertheless, it provides an illustration of the relationship between targeting survey coverage and household-level accuracy, and that it can be beneficial for desired policy outcomes to prioritize the former over the latter. Another caveat is that the low travel time between households in the urban setting under consideration here is a key environmental factor that promotes a close link between questionnaire length and incidence. Whether similar benefits would accrue where population density is lower could be assessed with enumeration meta-data for rural and peri-urban localities. Even when the number of questions is similar, the simulation suggests that the TrESt approach has a considerable advantage over a standard PMT, likely due to a more efficient orientation of survey resources to households with more uncertain eligibility status, and due to the greater predictive power of the non-linear, national-level machine learning model.

# **6 Discussion**

We proposed a selection of practically feasible methods that expose a tradeoff between accuracy and survey length, all based on variable sequences that order questions in order of predictive power. One simply truncates questionnaires to a certain length for all surveyed households, another deploys prediction intervals to generate a household-level early stopping criterion. For the most effective variable sequence – generated by stepwise selection – both approaches produce remarkably similar results in a simulation of a 40% programme coverage simulation with data from Indonesia, despite relying on different mechanisms. Compared with a policy baseline PMT that requires 22.8 questions to achieve an EER of 26.44%, truncation only needs 14 questions for a similar EER, and the early stopping method requires 18. A combined method that leverages their respective advantages achieves a superior length-accuracy trade-off at any point, and requires a mere 8.9 questions for an equivalent EER.

The methods presented here provide policymakers a choice on cost versus accuracy to suit their context and constraints. When selecting a point that maximizes incidence in a rudimentary simulation of an urban setting, a considerable improvement (to [78.3 %] incidence) appears feasible over both current practice ([65.6%]) and a more streamlined approach based on 28
respectively), while utilities and energy score very poorly, with a score of 1. Industry, trade and construction are all on the low side.

So far, out of 9 different measures considered, some sectors score well on some measures, while they score poorly on other measures. To aggregate the results in a simple index, we add the number of times the sector is noted as having high vulnerability and subtract the number of times that sector is noted as low vulnerability. The overall vulnerability index then shows the net effect of different measures. Positive overall index suggest that the sector is more often noted as having higher vulnerability, while negative overall index shows overall lower vulnerability.

Figure 1 plots the values of the overall vulnerability index. The industrial sector turns out to have the highest vulnerability, followed by trade, transportation and construction. Other sectors present lower overall vulnerability. Note that these results are static, for the end of 2006.

**Figure 1.  Overall Vulnerability Index**

<!-- Start of picture text --> Overall Vulnerability Index<br>6.00<br>5.00<br>4.00<br>3.00<br>2.00<br>1.00<br>0.00<br>-1.00<br>-2.00<br>-3.00<br>-4.00<br>-5.00<br>5.<br>1. Mining<br>Hotels Energy 8. Financial 3. General 2. Industry<br>6. Tourism and 7. Utilities and 4. Construction Transportation Trade/Services<br><!-- End of picture text --> Source: ASE data An important caveat to consider is that some of these sectors are not homogeneous. Thus the sector referred to as industry contains 48 firms, out of which 11 are in the chemical industry, 11 are in food processing, 7 are in the medical and pharmaceutical industry and a smaller number of firms are spread out in other industries. In the financial sector 27 firms are in real estate, while 24 are in diversified financial services. Different industries might be differentially affected by 10
over assets was approximately 18 p.p. higher for connected firms than for unconnected firms, starting from similar values before 2014 (Figure 4, Panel B).

The results with the PSM sample show that the differences between connected and unconnected firms of similar characteristics became significant in 2014 and were larger than for the full sample. The amount of equity raised over assets was about 3 p.p. higher for connected firms than for unconnected firms in 2014, 8 p.p. higher in 2015, and 18 p.p. higher in 2016. The amount of equity raised over assets was still 7 p.p. higher for connected firms in 2017. While the differences declined further during 2018-20, they were still significant. By 2020, the cumulative amount of equity raised over assets by connected firms was 51 p.p. higher than that of unconnected firms of similar characteristics, starting from similar values before 2014 (Figure 4, Panel B).<sup>26</sup> Overall, these results suggest significant and lasting effects of the 2014-20 internationalization process on equity issuances. Connected firms started to raise more equity (relative to unconnected firms) during the 2014-16 Stock Connect implementation and continued to do so, but to a lower extent during the 2018-20 MSCI incorporation. However, it is difficult to fully disentangle the importance of each event because both the Stock Connect and the MSCI events targeted the same connected firms and occurred back-to-back. Firms subject to the Stock Connect effect could have also anticipated the MSCI incorporation by raising more funds before 2018, given that the MSCI reviews about the incorporation started in 2014.

_Firm Size_ One plausible reason why PSM sample results show larger equity issuance effects than full sample results relates to differences in firm size. Our previous estimates show that connected firms are substantially larger than unconnected firms in the full sample (Table 2, Panel B). However, the largest connected firms are dropped from the PSM sample (Appendix Figure 2). If smaller firms were more reactive to the internationalization events, the difference in the firm size between the

> 26 The low levels of equity issuance activity by connected and unconnected firms during 2000-12 (below 1 percent of equity to assets ratios) indicate that differences since 2014 were economically large (Appendix Figure 3).

16
_indepreg_ as an independent variable in the previous model. We can see from our findings summarized in Table 12 that economic growth and the overall financial sector’s development still positively and significantly affect the volume of private investment. Moreover, the existence of an independent regulator also appears to significantly help improving private investors’ participation in energy projects’ funding, which is consistent with our previous findings.

**Table 11** <u>SYS-GMM parameter estimates</u>

|Variable|Coefficient|Std error|
|---|---|---|
|_lag(privinvt)_|.6756518***|.0402636|
|_growth_|.5322045**|.2874486|
|_findev_|99.72341**|57.81029|
|Obs.|307||
|Fisher test|F(3, 28) = 94.67***||
|Arellano Bond test - Order 1|-2.38***||
|Arellano Bond test - Order 2|0.05||
|Hansen-J|chi2(29) = 24.52||
|Dif-Hansen|chi2(15)= 12.20||

**Table 12** <u>SYS-GMM parameter estimates</u>

|Variable|Coefficeint|Std error|
|---|---|---|
|_lag(privinvt)_|.6449181***|.0806958|
|_growth_|.3440047*|.239676|
|_findev_|96.74427**|56.93634|
|_indepreg_|293.5705*|189.4488|
|Obs.|307||
|Fisher test|F(4, 28) = 20.78***||
|Arellano Bond test - Order 1|-2.21***||
|Arellano Bond test - Order 2|0.05||
|Hansen-J|chi2(25) = 24.89||
|Dif-Hansen|chi2(13)= 11.29||

# **8. Disentangling the effects of the banking sector and the financial market development levels on private investment in the power sector**

Now that the importance of the financial sector’s development in explaining the volume of private investment in developing countries’ energy projects is established, let us examine which of the banking sector and capital markets level of development drives these effects. We apply the same estimation methodology as in the previous sections and present results derived from equation (2). Table 13 displays estimation results with _bsdev_ and _cmdev_ as the sole independent variables _._ Estimates emphasize that the effect of the banking sector’s development level on private investment 19
improvements in female secondary school enrollment rates are estimated to be responsible for 43 percent of the total 15.5 percent reduction in the child underweight rate (see Smith and Haddad (2000)). For Sub-Saharan Africa as a whole, it has been estimated that five additional years of education for women could reduce infant mortality rates by up to 40 percent (see Summers (1994)). In the cross-section regressions for developing countries reported by McGuire (2006), average years of female schooling have a statistically significant impact on under-five mortality rates<sup>15</sup> . In Niger alone, researchers have found that infant mortality rates are lower by 30 percent when mothers have a primary education level, and by 50 percent when they have completed secondary education. Similarly, Paxson and Schady (2005), in a study of Ecuador, found that the cognitive development of children aged 3 to 6 years varies inversely with the level of education of their mother.

A low level of education may also lead to _maternal_ malnutrition, with dire consequences for children. Inadequate intakes of nutrients during pregnancy have been found to have irreversible effects on children. Recent research at the National institute of Health in the United States, for instance, has shown that the children of mothers who ate food with little omega-3 fatty acids had a lower IQ than children whose mothers ate food higher in omega-3 aftty acids. In addition, they also lacked physical coordination and had greater difficulties to engage in normal social relations. Inadequate diets may also have adverse effects on mental health (and therefore the ability to raise children), as argued in a report by the Mental Health Foundation (2006).

# **6.3  Magnification Effect**

The foregoing discussion suggests that the close interactions between health and education can magnify the effects of an increase in public infrastructure on growth. By investing in roads, for instance, governments may not only reduce have other traditions and policies in place that are more favorable to them; in turn, these traditions and policies could have an independent effect on health.

24
to closure by their second follow-up. Our paper builds on this work and not only shows no significant spillovers, but significant growth at the market level.

The remainder of the paper is structured as follows: Section 2 discusses the selection of our sample and randomization procedure; Section 3 the training and mentoring interventions; Section 4 our data collection and estimation approach; Section 5 impacts on primary and secondary outcomes; Section 6 mechanisms for these results; Section 7 cost-effectiveness; and Section 8 concludes.

# **2. Selection of the Sample, Randomization Procedure, and Baseline Characteristics**

# **2.1 Selecting a Sample**

A participatory process involving the ILO, government ministries, and organizations serving female entrepreneurs<sup>1</sup> was used to select four counties for the study: Kakamega and Kisii in the Western region, and Embu and Kitui in the Eastern region. These regions are largely rural, with an average population for each county of approximately 1 million, and the majority of the population below the poverty line. In each of the four counties, field staff from Innovations for Poverty Action, Kenya, mapped out all market centers deemed as “medium” or “large” outside of the main cities and conducted a market census of all female-owned businesses between June and November 2013 (see timeline in Appendix 1). After listing, an eligibility filter was applied (Appendix 2) and a baseline survey administered to 3,537 individuals located in 157 separate markets.

These markets are typically small and remote, largely consisting of women<sup>2</sup> operating a limited variety of businesses such as selling fruits, vegetables, grains, and dried fish products from tables; and offering services like hairdressing, dressmaking and small food kiosks. The market is a designated place in the village, and authorities typically build several stalls for the sellers to display

> 1 Stakeholders consulted included the Department of Micro and Small Enterprise Development (DMSED) of the Ministry of Labour, Ministry of Youth Affairs, Ministry of Cooperative Development and Marketing, Ministry of Youth, Federation of women entrepreneurs associations (FEWA), Women Enterprise Fund (WEF), Youth Employment Development Fund (YEDF), Business Development Service providers, and Inoorero University. 2 While men operate some businesses in these markets, they tend to specialize in other products, and women are the dominant sellers of the products in our sample.

4
|**Table**|**B4: Regulatory Quality**|
|---|---|
|**Code**|**Concept Measured**|
|**Repre**|**sentative Sources**|
|**DRI**|Export Regulations<br>|
||Import Regulations|
||Other Regulation burdens|
||Restrict ions on ownership of Business by Non-Residents<br>Restrict ions on ownership of equity by Non-Residents|
|**EIU**|Unfair competitive pract ices<br>Price controls|
||Discriminatory tariffs|
||<br>Excessive protections|
|**GAD**|Stock Exchange / Capital Markets<br>Foreign Investment|
|**GCS**|<br>Administrative regulations are burdensome<br>T i ii|
||ax system s dstortonary<br>|
||Import barriers as obst acle to growth|
||Competition in local market is limited<br>|
||Anti monopoly policy is lax and ineffective|
||Environmental regulations hurt competitiveness<br>|
||Complexity of tax System<br>|
||Easy to st art company|
|**HER**|Foreign investment<br>Banking / finance|
||Wage/Prices|
|**IPD**|Administrative business start-up formalities<br>Administered prices and market prices<br>|
||Competition: productive sect or: ease of market entry for new firms|
|**PRS**|Competition between businesses: competition regulation arrangements<br>_Investment Profile._|
|**WMO**|_Tax Effectiveness:_How efficient the country’s tax collection syst em is.|
||<br>_Legislation:_An asse ssm ent of whether the necessa ry business laws are in place.|
|**Non-r**|**resentative Sources**|
|<br>**ADB**|**p**<br>Trade policy|
||Competitive environment|
||<br>Labor Market Policies|
|**ASD**|Trade Policy and Forex Regime<br>Ebli Eit f Pit St Dlt|
|**BPS**|nang nvronmen or rvae ecor eveopmen<br>How problematic are labor regulations for the growth of your business.|
||<br>How problematic are tax regulations for the growth of your business.<br>How problematic are cust om and trade regulations for the growth of your business.|
|**BTI**|<br>Competition|
||Price Stability|
|**CPIA**|Competitive environment<br>Td li|
|**EBR**|rae pocy<br>Price liberalization|
||Trade & forein exchane ss tem|
||g g y<br>Competition policy|
|**IFD**|<br>Enabling conditions for rural financial services development<br>|
||Invest ment climate for rural businesse s<br>Access to agricultural input and produce markets|
|**WCY**|<br>Access to capital markets (foreign and domestic) is easily available<br>Ease of Doing Business|
||<br>Banking regulation does not hinder competitiveness<br>|
||Competition legislation in your country does not prevent unfair competition<br>Customs' authorities do not facilitate the efficient transit of goods<br>Financial institutions' transparency is not widely developed in your country|
||Easy to st art company|
||<br>Foreign invest ors are free to acquire control in domestic companies<br>Price controls affect pricing of products in most industries<br>Public sector contracts are sufficiently open to foreign bidders<br>Real corporate taxes are non distortionary|
||Real personal taxes are non distortionary<br>'|
||The legal framework is detrimental to your countrys competitiveness<br>Protect ionism in your country negatively affects the conduct of business in your country<br>|
||Labor regulations hinder business activities<br>Subsidies impair economic development|

76
we did find one of the brick kilns in our rapid survey of kilns that relied 100% on biomass pellets in the western part of the country.

<!-- Start of picture text --> Min Max Average<br>20.6<br>16.6<br>16.0<br>15.4<br>12.5<br>10.9<br>9.3<br>8.5<br>6.8<br>6.1<br>5.1<br>4.1<br>2.1<br>10% 25% 50% 75% 100%<br>Percentage of coal substituted by biomass pellets (%)<br>Fuel cost savings (billion NRs)<br><!-- End of picture text -->

# **Figure 10. Annual fuel cost savings by switching from coal to biomass pellets with FC BTK and ZZK combined in 2022**

_Notes_ : The estimated total number of brick production in 2021 is 4.1 billion from FC BTK and ZZK. The ranges of values are dependent on the quality of coal (gross calorific value). Lower quality of coal yields lower cost savings. The calorific values considered are 4750 kcal/kg (low), 5,000 kcal/kg (average), and 5,500 kcal/kg (high) (SMSEE, 2017). The average price of coal for Nepal is NRs 43.4 per kg and the biomass pellets is NRs 12 per kg in 2022 from the survey.

# **6. Policy Discussion**

# 6.1 Increased coal prices through a carbon tax

The economic analysis shows that energy-efficient technologies such as the VSBKs are the most economical fired clay brick production technology in terms of total private costs currently followed by ZZK and FC BTK. However, VSBK technology has low penetration in the country due to its high upfront costs and lack of skilled manpower to operate it. The ZZK technology, which is slightly more expensive (by NRs. 2 per brick) than VSBK is the most common technology in the country. Existing government policies caused a large-scale switching of inefficient fixed chimneys 28