rafmacalaba/data-use-mentions-extended huggingface dataset:
slope, and soil type. Standard errors are clustered at the administrative level to account for spatial and temporal correlation in the disturbance terms.

To the extent that unobservable factors like farmers' agronomic know-how might be correlated with both yields and inputs, the estimation could lead to an underestimation of the impact of increasing fertilizer use on yields, and therefore these results should be interpreted as lower bound estimates.

To account for the varying distribution of nitrogen usage in each region, equation (1) is modified to estimate region level regressions based on regional-specific quintiles. In the regional analysis, five quintiles are used and the middle or third quintile is omitted and becomes the reference quintile. The responsiveness of yield to the first, second, fourth and fifth quintiles are therefore measured relative to quintile three. Note that depending on the spread of the distribution of fertilizer in each region, the third quintile may or may not represent the optimum level of nitrogen.

To estimate the impact of nitrogen fertilizer on water pollution, equation 1 is modified to examine the total impact of nitrogen fertilizer use on water pollution spillovers. The sample period for this analysis extends from 1995 to 2013. A considerable body of literature has attempted to explain how human and environmental changes impact freshwater quality. Many of these pollution elasticities are available for individual countries or case specific studies but have not previously been quantified at the global level for water pollution. This paper employs a global gridded dataset of nitrogen fertilizer and nitrogen pollution in water to calculate the change in water quality for every percentage change in nitrogen fertilizer use.

The following equation is estimated at the global scale where i denotes grid cell and t denotes year: ′ i 1 1 i i i (2) Water quality data is sourced from GEMStat which is a globally harmonized database on freshwater ln(WWQQ ) = αα + ββ ln (NN ) + XX λλ+ ffcc(tt) + θθii + γγii + εε quality developed by UNEP-GEMS, maintained by the International Centre for Water Resources and Global Change (ICWRGC
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# IV. **Antidumping Practice in Latin America**

Antidumping activity has increased significantly in the recent decade across the world and also in Latin America GATT records show that during 1985-92 there were 1,148 antidumping cases, an average of over 150 cases per year, while there were no more than 12 case per year from 1947-68. Between 1985 and 1992, the United States brought some 300 cases, Australia 282 cases, the European Union 242, Canada 129 cases, Mexico 84, and Brazil 13. The concern is that these measures have become protectionist devices. The increase is associated with the liberalization of the trade regimes. Moreover, with the appreciations of exchange rates particularly with countries that adopted nominal anchor strategies, antidumping was an appealing weapon to reduce external competition in "sensitive" sectors and to help with the increased current account deficits that resulted from external shocks.<sup>6</sup> The incidence of antidumping actions are shown in Table 2. From 1988 through 1994, Argentina led the way in Latin America during that period with 135 petitions alleging dumping or subsidizations of imports<sup>7</sup> . Of these, 50 petitions resulted in the opening of an investigations and of those 19 resulted in the application of temporary or permanent remedial measures. Antidumping activity in Brazil is a relatively new phenomena. The early 1990s witnessed a dramatic increase in the number of antidumping cases brought before the Brazilian authorities. Not surprisingly this coincide with the implementation of trade liberalization policies. Seven cases were initiated in Brazil in 1991, another seven in 1992 and 18 in 1993, with favorable determinations of 1, 5 and 5 for the respective years. The most significant increases in antidumping occurred during 1994 and 1996. Argentina led the Latin American countries in the use of antidumping. Mexico and Brazil came second and third respectively. In the consideration of all those cases the respective competition policies agencies had no role, advisory or otherwise. They were total strangers, when indeed they should have been
Fay and Herriot, 1979; Torabi and Rao, 2014). Unit-context models represent another alternative and are characterized by an estimation stage wherein household-level measures are modeled exclusively as a linear function of area-level characteristics (Nguyen, 2012; Lange et al., 2018; Masaki et al., 2020).<sup>1</sup> Recent developments in poverty mapping have focused on the application of machine learning to remotely-sensed data, largely in response to the issue of out-of-date census information. These approaches also use survey-derived welfare measures but are distinguished by a first stage where a machine-learning model is fit to remotely-sensed covariates (e.g., data derived from satellite imagery or call detail records) rather than census-based covariates. For example, Chi et al. (2022) matched data from several remotely-sensed data sources to survey-based measures of “village” wealth for 56 countries, and then fit a prediction model using gradient boosting machines.<sup>2</sup> They then applied the model to the populated surface of all 135 low- and middle-income countries to develop granular poverty maps for each country. Similar approaches have been used for individual countries, including Rwanda (Blumenstock et al., 2015), Senegal (Pokhriyal and Jacques, 2017),

> 1Despite their desirable features, the gains in precision offered by area-level models is often quite limited (see Molina and Morales (2009)).

> 2Their remotely-sensed data includes high-resolution satellite imagery, mobile phone data, topographic maps, and connectivity data from Facebook.

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in 2007 and in 2008, respectively. We also find that the more citizens listen to the radio, the greater their likelihood of trusting their local government councillors. In contrast, higher attendance to the ward committees does not seem to be associated with changes in citizens beliefs. All together, these results speak of the positive effects played by councillors’ outreach efforts in shaping the attitudes of ordinary citizens toward state authorities. They are also consistent with recent qualitative research pointing at the positive impact of outreach radio campaigns in aiding more effective communication and physical interactions with political authorities, eventually generating a stronger sense of ownership of local development process and inclusion among the local communities (Larizza and Glynn, 2011).<sup>15</sup> — Membership in community associations a political party, cooperative or a religious — group is positively correlated with views about the trustworthiness of local councillors. The predicted probability of viewing the local council as trustworthy is 9.0, 5.0 and 3.0 percentage points higher for respondents who in 2008 belonged to a political party, a cooperative or a religious group, respectively. This is consistent with previous research pointing at a growing level of civic activism at the grassroots level in post-conflict Sierra Leone (Zhou, 2009, pp. 97-99), and suggest that citizens might take advantage of their membership of interests groups to collectively mobilize and become active in demanding service improvements and government responsiveness to their needs.

In contrast to our expectations, very few of our socio-demographic measures are significantly associated with trustworthy local government councillors. We do not find any correlation between our ethnic fractionalization measure and views about the trustworthiness of local councillors. We also do not find any relationship between whether respondents belong to a minority ethnic group and views about the trustworthiness of local councillors. There is no evidence that respondents who are members of a ruling family are more likely to see local government councillors as trustworthy. Further, there is no association between whether a respondent supports the ruling party, the APC, and
benefit estimates are based on simple coverage criteria, applied uniformly to all districts. In practice, criteria for post-disaster support may vary by province and disaster magnitude. This framework can model all such complexities, to the and of the household and hazard up granularity representativeness survey maps used as inputs.

# 5 conclusions

This paper has presented the results of a risk assessment based on an expanded framework, which includes in the analysis the ability of affected households to cope with and recover from disaster asset losses and uses “wellbeing losses” as its main measure of disaster severity. This framework adds to the three usual components
making decisions and solving problems” are also very important activities in electronics (ranking third and second), they are much less important in textiles (11<sup>th</sup> and 10<sup>th</sup> ). Conversely, “repairing and maintaining mechanical equipment” is barely important in electronics (34<sup>th</sup> ) but above average important in textiles (17<sup>th</sup> ).<sup>3</sup> More generally, one can statistically test for the significance of adding an industry dimension to the occupational class category. To this end, we make use of O*NET’s importance indicators for the full set of industries, occupations and work activities.<sup>4</sup> More

> 3 Based on work activity data from O*NET for job codes 51-2022 - Electrical and Electronic Equipment Assemblers and 51-6062 - Textile Cutting Machine Setters, Operators, and Tenders (assessed 22 July 2022).

> 4 This is data for the U.S. only. Caunedo et al. (2021) document some cross-country differences

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SEDLAC, a regional data harmonization effort that increases cross-country comparability, they may differ from official statistics reported by governments and national statistical offices. The LAC aggregate is based on 18 countries in the region for which microdata are available. In cases where data are unavailable for a given country in a given year, values have been interpolated using WDI data or using microsimulations to calculate regional measures. Type of employment and sector limited to working individuals ages 15–64.

Table 7. Profile of the Middle Class

|||**Middl**|**e C**|**la**|**ss$**|**13-**|**$7 **|**0**|**(2011 P**|**PP)**|**Middl**|**e Clas**|**s$1**|**4**|**-$81**|**(**|**201**|**7 P**|**PP)**|||**Dif**|**f**||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|||**2015 **|**201**|**6 **|**201**|**7 2**|**0**|**18 **|**
BNLA survey provides rich information on labor outcomes such as (current) employment status, work sectors, labor income, and receipt of government benefits. Following the existing literature (e.g., Beaman, 2012; LoPalo, 2019), we use two measures of labor market outcomes available from the BNLA: (i) employment status conditional on being in the labor force (i.e., this variable equals one if having a paid job in the last seven days and zero otherwise); and (ii) weekly labor income (as measured by total real income of all jobs in thousand Australian dollars). We also examine other outcomes such as refugees’ own labor market outcomes (including labor force participation (LFP), employment type, and employment skills levels and sector) and life satisfaction outcomes as well as their partners’ and children’s outcomes (including partner’s employment status, child mental health, and school performance).

Mental health of refugees is measured by the six-item Kessler Screening Scale for Psychological Distress (K6), developed by Kessler et al. (2002). The six items ask individuals how often, during the past four weeks preceding the survey, an individual felt: (1) nervous, (2) hopeless, (3) restless or fidgety, (4) so depressed that nothing could cheer them up, (5) everything was an effort, and (6) life is meaningless (worthless). The answers are subsequently scored on a five-point scale, with total scores ranging from 6 to 30, where a higher score indicates worse mental health. For easier interpretation, we follow the common practice in the literature by standardizing mental health scores, such that the total score has a mean of zero and a standard deviation of one (e.g., Frijters et al., 2014). Respondents in the BNLA survey were also asked whether they had experienced or witnessed any traumatic events before arriving in Australia. These include extreme living
Policy Research Working Paper 9204

# **Abstract**

This paper uses data from the National Financial Inclusion Survey 2018 to understand the determinants of financial inclusion in Sri Lanka and their significance for inclusive growth. The findings highlight that gender, education, and formal employment are important determinants of financial inclusion in the country. The results indicate that being a male, having better education, and having formal employment increase a person’s access to, and usage of, formal finance. The results also suggest that despite high levels and gender parity in education, Sri Lankan women seem to access more informal finance (and less formal finance) compared with men. There is a general lack of familiarity and low use of digital finance among women. Comparative analysis using the World Bank Group’s Global Financial Inclusion (Global Findex) Database 2017 indicates that although Sri Lanka leads its regional peers in access to finance, it lags its more aspirational East Asian counterparts in usage of savings and credit products as well as digital finance. The paper’s findings complement recent policy initiatives such as the National Financial Inclusion Strategy for Sri Lanka. The findings also help in designing targeted actions to address the remaining gaps in financial inclusion in Sri Lanka.

This paper is a product of the Finance, Competitiveness and Innovation Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at tarandara@ifc.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper
methods, and country contexts. The few existing recent studies on middle-income countries offer mixed evidence as well. Focusing on women with at least one child age 4 in Argentina, Berlinksi, Galiani, and McEwan (2011) find a positive impact for childcare use on women’s labor force participation (LFP) and work hours. Yet, Li (2017) recently observes no such effects on urban Chinese women.<sup>2</sup> We add to these studies by investigating nationally representative household surveys for Vietnam and all children age 1-5.

> 2 Li (2017), however, finds some positive impact on women’s LFP for informal childcare provided by grandparents. Other studies indirectly examine the impacts of childcare use through the presence in the household of young children or older people (Maurer-Fazio et al., 2011) or available childcare facilities in the community (Du and Dong, 2013). For earlier studies on childcare and women’s employment for developing countries, see, e.g., Lokshin, Glinskaya, and Garcia (2004) for Kenya, Hallman et al. (2005) and Quisumbing, Hallman, and Ruel (2007) for Guatemala, and those reviewed in Akgunduz and Plantega (2018).

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business knowledge. Overall, we conclude that the entrepreneurship track did not have a lasting impact on latent or nascent entrepreneurship.

These findings have a number of policy implications. Most importantly, they highlight the limited effectiveness of entrepreneurship education and training offered to university students with relatively little screening. The CEFE training offered by ANETI is a widely used curriculum that was already well established in Tunisia and beyond prior to the evaluation. It is likely that the overall program, especially the coaching sessions, could have benefitted from further improvements in implementation. In particular, coaching and follow-up support was concentrated during an academic semester and did not continue after students’ graduation. The program was not accompanied with widespread facilitation of access to financing either. Still, the study results provide strong indications that the type of skills imparted by the training may not be the main constraint to entrepreneurship for highly educated young men and women. As such, the results should at least temper policy makers’ enthusiasm in considering entrepreneurship education as a potential broad-based solution to the employment challenge. Additional long-term evaluations would be welcome to justify large investments in traditional entrepreneurship education.

Policies to promote entrepreneurship among high-skilled youths would likely need to tackle other constraints than those addressed by the Tunisian entrepreneurship track. This may include de-emphasizing traditional business skills and focusing more on psychological mechanisms that enhance personal initiative, as Campos et al. (2017) have suggested. Most importantly, it is likely that capital constraints would also need to be addressed as they constitute the main binding constraint to entrepreneurship that graduates self-reported during the medium-term follow-up survey. McKenzie (2017b) documents positive impacts from a large-scale national business plan thesis competition among aspiring high-skill entrepreneurs in Nigeria. Winners were provided large grants averaging $50,000, and the capital injection led to the set-up of firms that created more jobs and with higher sales and profits. As such, reforms that improve access to capital and banking for high-skilled youths may be needed as a complement to traditional skills training.

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strategy to combat unconscious bias.<sup>27</sup> Many financial institutions do not track sex-disaggregated data, leaving them unaware of potential gender biases in their services. Therefore, collecting and analyzing sexdisaggregated data should be a strategic imperative for financial institutions, governments, regulators, and corporations (Bonfert et al. 2023).

# 5 Interventions to increase access to markets and technology

One leading explanation for the gender gap in business performance is that women-led businesses tend to be concentrated in lower-paying industries and sectors worldwide (World Bank Group 2021).<sup>28</sup>

> 26 An example is IFC’s Women Insurance Program, which has collaborated with eight insurance companies across Africa and Asia to pilot insurance solutions tailored for women. These include a life insurance policy to support personal goals of women entrepreneurs in Nigeria, an insurance bundle that protects against accidents, fire, and burglary for microbusinesses, and comprehensive insurance coverage for women-led MSMEs in Ghana.

> 27 IFC (2021) details Gender Sensitivity Training provided to 660 senior managers, staff, and agents at an insurance company in the Philippines. A non-causal evaluation indicated that the training led to noticeable changes in the participants’ gender biases and enhanced their interactions with women customers.

28 Evidence from Africa and Southeast Asia shows large gender gaps in profits even within sectors, which means that sectorial segregation cannot fully explain the profits gender gap (Campos et al. 2019, World Bank 2021). Moreover, 14
5-9 child 10-14 child 15-17 Total<br>MICS 2016/2017_NC MICS 2016/2017_NE MICS 2016/2017_NW MICS 2016/2017_NC MICS 2016/2017_NE MICS 2016/2017_NW<br>MICS 2016/2017_SE MICS 2016/2017_SS MICS 2016/2017_SW MICS 2016/2017_SE MICS 2016/2017_SS MICS 2016/2017_SW<br><!-- End of picture text -->

# c)

Source: Authors’ estimates based on GHS Wave 1-4 and MICS 2016/17.

Note: Individuals with missing age were dropped from the analysis. Total refers to all individuals with known age.

The below Figures 8 and 9 show the existence of an enormous heterogeneity in educational deprivation between states. In Bauchi 50% of the children of the age group of 15-17 years, have never attended and are not currently attending school, whereas there are also states where close to 100% of the children have at some point attended school. It however also shows that at least some of the over 60% of children in Bauchi not in school when 5-9 years old, as Figure 8 displays, will have likely been in school at least at some point when reaching towards the oldest child age category.

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and country is obtained from the IMF.<sup>12</sup> Prices are projected forward using this data in tandem with an average of IMF World Economic Outlook (WEO) and World Bank Commodity Markets Outlook (CMO) forecasts of international energy prices. Fuel price responsiveness is broadly consistent with standard empirical and energy model parameters and results. Refer to Black et al. (forthcoming) for more details on model parametrization and data sources.<sup>13</sup> The analysis within CPAT is subject to some limitations and caveats. First, the model does not explicitly incorporate gradual turnover of energy capital. This assumption overstates the short-term responsiveness of fuel use to carbon pricing but is reasonable, given the focus on medium-term scenario simulations (by 2030 in our case – see Section 3.3 below). Second, CPAT abstracts from the possibility of additional mitigation actions (beyond those implicit in current country-level price data) under the Business-As-Usual (BAU). Specifically, the BAU scenario is used as a ‘benchmark’ against which the performance of any modeled mitigation instruments is measured (a standard approach in the literature). Intuitively, the BAU scenario assumes absence of new (or tightening of existing) climate mitigation policies. Third, the fuel price response parameters in the model are plausible for marginal price changes. In other words, model elasticities may not apply under drastic price hikes that could cause major technological developments or non-linear adoption of technologies. Fourth, the model assumes flat (perfectly elastic) supply curves, absence of general equilibrium effects, and no changes in international fuel prices that might result from multiple countries introducing mitigation policies at the same time.<sup>14</sup> The incidence on household consumption deciles d = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10} from higher retail prices following the introduction of a climate mitigation policy is calculated as: where g stands for the main categories of goods/services consumed