rafmacalaba/data-use-mentions-extended huggingface dataset:
the program aims to put a stronger focus on the provision of more customized support taking into account different beneficiary profiles and needs.

The analysis in this paper is based on a three-wave household panel of VUP beneficiaries and a matched comparison group collected between 2009 and 2014 which formed the basis of a quantitative impact evaluation (Hartwig, 2014). To obtain a more nuanced picture, we complement the survey data with qualitative life-history interviews conducted in 2015 with a sub-set of beneficiaries from the panel data. Combining and comparing the quantitative and qualitative data suggests that gender, household composition and responsibilities, disabilities and dependency ratios, marital arrangements, intra-household communication and inheritance norms play crucial roles for access to and use of the VUP transfer. For example, households with both spouses present are more flexible in labor allocation and thus also more likely to access the public works opportunities offered compared to households with only one able bodied laborer, a common feature among female headed households. Domestic responsibilities, notably care for children or disabled or elderly household members, further limit labor supply and access to public works opportunities. The heterogeneity of effects for different households and household characteristics suggests that social protection programs need to offer enough flexibility or complementary programming in order to address the range of needs of the targeted households. A similar conclusion has also already been put forward by Banerji and Gentili (2013) arguing that it is important to build systems of social protection that work together as a portfolio to cover multiple risks and needs across the life cycle.

The remainder of this paper is structured as follows. Section 2 gives an overview of the program, its components and objectives. Section 3 presents a conceptual framework linking household characteristics to access to the income transfer and consequent asset accumulation, informed by the qualitative data. Section 4 describes the data and empirical approach to test some of the linkages described in the conceptual framework. The results are discussed in Section 5 and Section 6 concludes.

5
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6. The RWMA in Poznań covers the Warta River basin from its source to its mouth at the Oder River.

7. The RWMA in Szczecin covers the Oder River basin from the mouth of the Nysa Łużycka River to the mouth at the sea, excluding the Warta. It also includes the basin of the west littoral rivers.

On behalf of the central government, RWMAs perform IWRM planning and coordinating functions within river basins, overseeing the actions of voivodeship and local governments and private users for compatibility with basin water management plans, and maintaining specified water works and state-owned reservoirs and other facilities. Tasks related to these functions include:

- monitoring and forecasting surface water and groundwater demand conditions,

- determining the conditions of use of integrated water resources in the basin,

- acting as a party in legal proceedings in cases regarding the specific use of inland waters and in other administrative proceedings pertinent to water management and protection,

- formation of, and communication with, Regional Councils of Water Management (RCWMs) composed of representatives of water users and other organizations, to have opportunities to comment on water management plans and environmental impact assessments,

- collecting charges and fees for navigation and sluice operation, for materials extracted from surface waters, and for leasing of the shore or river bank areas and use of facilities,

- providing opinions on designs and siting of developments that may appreciably affect water conditions and facilities located along river banks,

- cooperating on water management with, among others, the Inspectorates of Environmental Protection, the Institute of Meteorology and Water Management, maritime offices and regional forestry boards,

- cooperating on transboundary waters in compliance with the effective legal provisions and international agreements,

- keeping water resource databases (cadasters) and GIS,

- initiating studies and research on the development and protection of surface and underground waters,

- developing plans and programs for water resources management, water protection, and flood and drought prevention, and

- participating in flood emergency operations.

RWMAs have a legally recognized role in the water use and discharge permitting procedures that
traffic statistics from the Suez canal for a traffic estimate in each year, and compute the costs of a one percentage point increase of protected vessels per year. As the Suez canal traffic underestimates overall traffic through the troubled waters off Somalia, our estimates of private team costs tend to be underestimations as well. For this reason, we carry out a set of robustness checks with doubled costs of armed protection. The results presented in Figure 16 are essentially the same as in our benchmark case.

The estimated costs of navy patrols also come from various OBP reports. In 2010, OBP provided a first estimate of around US$30.2 million per patrol – including the costs of personnel, fuel, and other administrative supports (Oceans Beyond Piracy 2013). This estimate is almost surely an upper bound, as it assumes that the warship patrols year-around.

40
. For the analysis, Anukriti (2017) pooled women’s birth-history data from the NFHS and the District Level Household Survey of India (DLHS). To isolate the treatment effect of the scheme on the number and sex-composition of children, she uses a difference-in-difference approach that exploits variation in the year and state of program commencement, and variation in future incentives by the composition of existing children who were born before the program was launched.

Her results suggest that while families responded to the incentives to reduce fertility, they did not forgo their preference for sons despite the higher benefits provided for having daughters. The incentives provided for one-boy only were sufficient for couples to cease childbearing or sex select at first birth. However, the higher incentives provided for one-girl only were not sufficient for couples to forgo their demand for sons; these couples did not cease child-bearing after the first child and sex-selected for a son at second birth. The net result of this program was a reduction fertility, but an increase in the SRB (ibid).

A conceivable way to improve the short-term effectiveness of this kind of program in balancing the SRB would be to remove the financial benefits for the one-boy only families. However, even programs that do not provide benefits for male children show mixed results in lowering son

> 10 BeneficiaryA beneficiary household is one which has at least one girl child enrolled in the scheme at the time of the survey, and a non-beneficiary household is one which has an eligible girl (age 1-4 years) who is not enrolled in the scheme.

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Croke et al. (2016) where is the underlying true average effect, is a normally distributed random variable EE denoting the difference between the average effect and the effect in the particular context, ββ μμ and represents measurement error due to sampling variation, which is assumed to be EE captured in the study-specific standard errors. σσ Finally, under the assumption that deworming has no effect on uninfected children, one can calculate for each study an implied estimated effect on weight for infected children as the estimated intention-to-treat effect divided by prevalence. If one takes the estimated prevalence to be accurate and not subject to measurement error, then standard errors for these estimated effects are straightforward to compute. One can then apply a random effects model to estimate the average treatment effect on infected children. In a few cases, a study does not report an exact value for prevalence, but we are able to identify whether the study has below or above 50% prevalence. If prevalence is above 50%, we then compute the average prevalence among all studies in the sample reporting greater than 50% prevalence and assign that value to the study. We proceed similarly for studies with below 50% prevalence that do not report an exact value for prevalence.<sup>22</sup>

# **5 Results**

Subsection 5.1 first replicates the results of the TMSDG subsample. Subsection 5.2 tests the hypothesis of a common zero effect. Finally, subsection 5.3 reports estimated effects of MDA on weight.

# **5.1 Verifying replication of results in the TMSDG sample**

> 22 See Appendix A.7 for more detail on how prevalence categories were assigned when STH prevalence was not reported in the study text.

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The survey-based LPI captures the ease of establishing reliable and effective supply chain connections to export target countries. The survey does this by pooling the information from the six LPI components, as assessed by logistics and freight forwarding professionals. LPI respondents rate countries according to their supply chain experience when providing their macro-level qualitative knowledge of them. Micro-level tracking data, however, informs about the performance outcomes along the LPI dimensions except for affordability, as cost information is not available in this data. Attributes of supply chain performance accessible from the data include two main categories.

The first category comprises indicators of timeliness and reliability. Domestic and international supply chains have a skewed lead time distribution with a long tail. Therefore, the significance of lead time at a port or along a corridor is not captured just but its average but by how likely much longer delays are. The shape of the right side of the distribution, i.e., the length of the “tail”, reflects reliability. Corresponding KPIs include:

- Mean/Median lead time for legs of the supply chain (between two subsequent events), with focus on time at and within border.

- Indicators of reliability as statistical dispersion such as interquartile range defined as the difference between the 75<sup>th</sup> and 25<sup>th</sup> percentile.

The second category includes indicators of connectivity. The structure of the network matters. More connections mean more options to access markets, also contributing to reliability and performance. This is like human mobility where more options to reach destinations increase accessibility of individuals to reach jobs or services. Connectivity indicators are provided by mode: container shipping, aviation, postal. They mostly consist of simple counts of connections in the network.

# Definition of the KPI

The set of indicators below focuses on (i) delays experienced at the same place or dwell time at ports or airports, (ii) delays in motion, and (iii) connectivity information. From a policy standpoint, dwell time
the results of a household survey and concludes that an influx of internally displaced persons (IDPs) is associated with ’non-decreasing’ wealth and is uncorrelated with inequality and poverty. Similarly, in Switzerland, (Mullera et al., 2021) analyze the labor market integration of refugees and find that early labor market integration is vital to their long-term integration and the reduction of unequal access to the labor market between natives and migrants. In contrast to these results, (Sedova et al., 2021) identified that poorer local communities in Nigeria are negatively affected by forced migrant influxes as the competition for access to scarce welfare services increases. Similarly, (Hoseini and Jahan Dideh, 2021) argue that turbulent economic periods have larger detrimental effects for Afghan forced 3
countries in the region in June and July 2009 and the Business Environment and Enterprise Performance Survey (BEEPS), which was conducted in 28 countries in the region in 2002, 2005, and late 2008 and early 2009.<sup>7</sup> The fourth section discusses the estimation methodology used to test the various hypotheses; the fifth discusses the empirical results and presents robustness checks. The final section concludes.

# **II. Related Literature and Hypotheses**

In this section, we develop hypotheses about how the economic crisis affected firms in the ECA region. Although our regressions will control for a number of factors that could affect firms‘ financial constraints and survival, the hypotheses in this section focus on two main themes: the pecking order theory of external finance and foreign bank participation.

# **A. Pecking Order Theory of Financial Services**

The first set of hypotheses derives from the pecking-order theory of financial services. This theory holds that internal funds are less costly than external funds (Myers and Majluf, 1984), because borrowing firms have better information about the quality of their investment opportunities than lenders do. The lender, therefore, requires compensation in the form of higher interest rates. Because external funds are more costly, firm owners first exhaust internal funds before turning to credit markets, leading to a pecking order with respect to the two sources of finance.

Informational asymmetries between borrower and lender tend to be more severe for small, young firms, and lenders, therefore, charge them higher interest rates or do not extend credit to them at all. As a result, small, young firms use less external credit than others. This is the case in Eastern Europe and Central Asia. Whereas about 64 percent of large firms had loans or lines of credit in 2008-2009, only about 38 percent of small firms did.<sup>8</sup>

> 7 Though BEEPS was conducted in 28 countries, our sample is comprised only of firms that were interviewed in all three
that they voluntarily reported their new income at a local social assistance office.

Administrative data showed that under the 2019 system, the vast majority of exits from BF occurred because families’ per capita income rose above the eligibility threshold. The so-called _Averigua ̧c ̃ao e Revis ̃ao Cadastral_ – inquiry and registration review – of existing beneficiaries cross-checked administrative records (such as those on formal employment) against beneficiaries’ self-reported data in CadUnico. This process was carried out centrally in Bras ́ılia and operated independently of municipalities’ economic conditions (Ministerio da Cidadania, 2013). BF beneficiaries were aware of the implications of taking up formal employment for eligibility, as it often led to either program exit or a transition into the permanence rule. Once family income exceeded the threshold, households were removed from the program. While some families left voluntarily, exclusion through the inquiry and registration review could also be considered voluntary since people aimed for higher income despite being aware of the consequences – namely, exclusion from the program (Ministerio da Cidadania, 2008).

BF’s design and its interaction with the broader tax-benefit system created an incentivecompatible framework that should not have discouraged individuals from pursuing formal employment. The program had low marginal tax rates on acquired labor income compared to most social assistance programs (Fietz _et al._ , 2021). This was because the value of the BF benefit remained relatively low, fluctuating between a fourth and a fifth of the MW during the observation period. Additionally, Brazil extended automatic benefits to low-wage workers with children ( _Sal ́ario Fam ́ılia_ ), which partially offset reductions in BF payments and social insurance contributions. Furthermore, personal income tax exemptions applied to workers at entry wage levels. Lastly, BF’s permanence rule, _Regra de Permanencia_ , acted as a temporary income disregard. Figure 1 visually illustrates the design of the BF program as it operated in 2019, including the implications of its permanence rule for a family in which an individual transitioned into fulltime formal employment. Thus,
rely on liquid assets such as livestock to mitigate negative effects. In our sample, just over half the households own agricultural land, and 60 percent own some type of livestock.<sup>33</sup> In Figures 13 and 14, we do find evidence that landed households are able to protect their consumption in a time of adverse vegetation anomalies, whereas the consumption of the landless decreases. However, the trends in consumption are no different between landed and landless households when temperature anomalies are positive. Livestock ownership does not seem to protect a household’s consumption in times of adverse weather shocks. Our findings are in line with Christiaensen and Subbarao (2004), and Kazianga and Udry (2006), who show livestock ownership as ineffective in mitigating consumption losses due to drought in Kenya and Burkina Faso, respectively.

Afghanistan’s population is primarily rural (78 percent), who are either directly or indirectly dependent on agriculture or rearing livestock. Among households in urban areas, we may expect better resilience to adverse effects of weather due to their access to diversified livelihoods outside agriculture. In Figure A.3, we find that the adverse effects of low NVDI and high temperatures are concentrated in rural areas, while in urban areas the effect is noisier, suggesting that local weather extremes do not impact livelihoods in the same way.

# **6 Vulnerability to Poverty**

Beyond the observed impacts on household welfare, we want to understand long-term household vulnerability to poverty in the context of increasingly extreme climate in Afghanistan. Even for households not affected by the 2018 drought, similar or more severe shocks could drive them into poverty in the future. The identified households may live close to the edge of poverty and are vulnerable to backsliding.

Drawing from Hill and Porter (2017), we estimate the vulnerability to absolute poverty for Afghan households due to drought. We combine the historical weather data with the estimated impacts of droughts on consumption to predict future consumption based on a posited threshold for the probability of falling
). Fifty-six percent of the impact on the LICs is from the shock to employment/experience, whereas it is 45 and 57 in the MICs and HICs respectively.

That said, much of this has to do with the short run impact of the shock, whereas after 10 years (once the shock is over) it is the disruption to schooling that has the largest impact. At year 10, the total impact of schooling accounts for 86, 91 and 77 percent of the continuing welfare cost from the pandemic in the LIC, MIC and HIC respectively.

Finally, it is worth pointing out that the (conservative) assumption that college education is not disrupted implies that one effect of experience – its interaction with college schooling – is absent. Were it present, it would increase the impact of experience disruptions to some extent, primarily in the HIC where college education is common.

# **5. Welfare Impact for Different Scenarios**

So far we examined the welfare impact of the extreme pandemic shock scenario, to get a sense of how different factors would impact economies at different income levels. In this section, a range of feasible scenarios are considered.

> 36The losses equal $73 in PPP terms per year in the LIC, $423 per year in the MICs and $2 _,_ 342 per year in the HICs. Alternatively, this is equivalent to a one-off hit of $1 _,_ 812, $10 _,_ 585 or $58 _,_ 549 respectively. 37 This is equivalent to a one-time hit in year 10 of $214, $8 _,_ 831 or $44 _,_ 339 respectively.
discussed in detail below, suggests that children who enroll in preschool have superior learning outcomes later on. The results in Table 1 are therefore an indication that there is scope in many countries in the region for expansions in preschool coverage.

<u>Evidence of deficits in early childhood outcomes and socioeconomic gradients within countries: A handful of recent papers have used micro-level data to describe deficits in early</u> childhood outcomes in Latin America and the Caribbean, and to make comparisons of households with different levels of education, wealth, or income.

Fernald et al. (2005) and Gertler and Fernald (2004) present evidence of ECD shortfalls in Mexico. Fernald et al. focus on the relationship between deficits in child nutritional status and the Mental Development Index (MDI) of the Bayley Scales of Infant Development, a test of memory, learning, problem-solving, sensory-perceptual acuities, and receptive and expressive language development. Fernald et al. find significant reductions in the Bayley MDI scales with the age of the child: At age 13-14 months, 14.4 percent of children are one standard deviation or more below the normed value for the test, and 3.0 percent are 2 standard deviations or more below. By age 21-23 months, almost half the children are 1 standard deviation below the norm, and 11.3 are more than 2 standard deviations below. These deficits in mental development are mirrored by an increasing fraction of children with low height for age—at age 13-14 months, 25.9 percent of the children are stunted, compared to 42.7 percent by age 21-23 months. However, Fernald et al. find no association between height for age and the Bayley MDI score once family and environmental variables are included in a multivariate regression framework. More surprisingly, _none_ of the parental or socioeconomic factors they control for, including income, employment, parental age, education, and whether the head of the household spoke an indigenous language, are significant predictors of performance on the Bayley MDI score.
**|-0.072***|-0.019|0.005|
|National market dummy|0.029*|0.041**|-0.001|-0.013|
|International market dummy|0.056***|0.035**|0.025|0.011|
|Manufacturing sector|0.032*|0.042**|-0.008|0.001|
|Retail sector|-0.059***|-0.035**|-0.022|-0.021|
|Other services sector|0.015|-0.016|0.027*|0.017|

_Sources_ : Enterprise Surveys COVID-19 Follow-up Surveys and Enterprise Surveys. _Notes_ : Correlations matrix based on 3,647 observations. *** p < 0.01, ** p < 0.05, * p < 0.1.

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