rafmacalaba/data-use-mentions-extended huggingface dataset:
588|0.595|0.261|0.125|0.150|0.125|
|Mean WTP > K 600|0.327|0.211|0.527|0.536|0.239|0.125|0.075|0.083|
|Mean WTP > K 700|0.295|0.179|0.495|0.500|0.196|0.042|0.075|0.083|
|**Title demand**|||||||||
|> 90% wanting title|0.234|0.150|0.379|0.500|0.152|0.000|0.125|0.063|
|> 70% wanting title|0.370|0.288|0.511|0.631|0.304|0.208|0.200|0.125|
|<br>> 60% wanting title|0.442|0.367|0.571|0.690|0.413|0.354|0.250|0.125|
|< 40% wanting title|0.325|0.419|0.165|0.107|0.261|0.250|0.675|0.646|
|Number of villages|495|313|182|84|46|48|40|48|

_Notes_ : Own computation from 2017/18 Quarterly Labor Force Survey conducted by Zambia’s Central Statistical Office. Sampling weights adjusted with non-response probabilities are used to estimate the mean values.

23
# Policy Research Working Paper Series

|Title|Author|Date|Contact<br>for paper|
|---|---|---|---|
|WPS1746 The Role of Long-Term Finance:<br>Theory andEvidence|Gerard Caprio, Jr.<br>**Asli**DemirgOt-Kunt|April 1997|P. Sintim-Aboagye<br>38526|
|WPS1747 Protection and Trade in Services:<br>A Survey|Bernard Hoekman<br>Carlos A. Primo Braga|April 1997|J. Ngaine<br>37947|
|WPS1748 Has Agricultural Trade Liberalization<br>Improved Welfare in the Least-Devel<br>Countries? Yes|Merlinda D. Ingco<br>oped|April 1997|J. Ngaine<br>37947|
|WPS1749 Applying Economic Analysis to<br>Technical Assistance Projects|Gary McMahon|April 1997|C. Bernardo<br>37699|
|WPS1 750 Regional Integration and Foreign<br>Direct Investment: A Conceptual<br>Framework and Three Cases|Magnus Bl6mstrom<br>Ari Kokko|April 1997|J. Ngaine<br>37947|
|WPS1751 Using Tariff Indices to Evaluate<br>Preferential Trading Arrangements:<br>An Application to Chile|Eric Bond|April 1997|J. Ngaine<br>37947|
|WPS1 752 Ghana's Labor Market (1987-92)|Sudharshan Canagarajah<br>Saji Thomas|April 1997|B. Casely-Hayford<br>34672|
|WPS1753 Can Capital Markets Create<br>Incentives for Pollution Control?|Paul Lanoie<br>Benoit Laplante|April 1997|R. Yazigi<br>37176|
|WPS1754 Research on Land Markets in South<br>Asia: What Have We Learned?|Rashid Faruqee<br>Kevin Carey|April 1997|C. Anbiah<br>81275|
|WPS1755 Survey Responses from Women<br>Workers in Indonesia's Textile,<br>Garment, and
-0.82|0.07|

ITT = intention-to-treat effect estimate; HH = household; FIB = fecal indicator bacteria; MPN = most probable number; IHS = inverse hyperbolic spline; WHO = World Health Organization; WVS = World Values Survey. Effects are estimated with models that include controls for randomization blocks based on province and number of villages per cluster. There were 121 clusters in total. The WASH governance perceptions index and the hygiene and behavior index were calculated by rescaling each variable in the index (e.g., satisfaction with water access) so that higher values imply better outcomes, then standardizing relative to the control group, following Kling _et al_ . Effects are in standard deviation units.
consumption section, which asks female respondents about consumption of 91 food items belonging to nine food groups consumed over the previous week. The broad coverage of foods, including seasonal varieties, allows for better calculation of calorie and nutrient intake than surveys with fewer items.

Another key component of the NRVA is the district market price survey; data were collected on the prevailing prices of all food items included in the consumption section, domestic and imported grains, and fuel. Given Afghanistan’s mountainous terrain and poor infrastructure, transportation costs most likely vary greatly across the country, and in particular in remote and insecure areas; therefore in order to identify correctly the impact of the price increases at the household level, it is necessary to obtain data on actual prices that households face in their local markets.

As previously noted, the NRVA household survey combined with the matching market-level price survey reveals a 40% increase in a weighted food price index from August 2007 to September 2008 (the duration of the survey fieldwork). Basic descriptive statistics indicate that this increase coincided with sharp declines in household wellbeing. Average monthly real food expenditure dropped from 1,200 Afghani in fall 2007 to 798 Afghani in summer 2008, while the percentage of households consuming less than 2,100 calories per person per day rose from 24% to 34%.

# _3.2  Empirical specification_

To assess the impact of rising price of staple foods on the welfare of Afghan households, we estimate the relationship between several measures of household wellbeing and the price of domestic wheat flour. To isolate the price effect from other potentially confounding correlates, our basic specification is as follows:

## ���������� ������������ ����� ���������

where _x_ is a measure of household wellbeing for household _h_ . Prices denotes a vector of commodity prices, averaged by area _a_ (urban or rural), province _p_ , and quarter _q
banks are able to fund themselves at lower rates. However, they also generate less interest income per unit of asset which is surprising, especially considering that they finance the government to a lesser extent. At the same time, listed banks generate much larger income from fees and commissions, which helps explain their higher profitability.

Listed banks have higher cost ratios vis-à-vis non-listed banks. Since average wages in the two groups are similar, this is due essentially to a higher ratio of employees to assets. This result may be partly explained by their smaller size, but could also be explained by the stricter corporate governance, disclosure and compliance requirements imposed on listed banks, which may translate into more staff requirements and higher costs. At the same time, these requirements probably also explain why these banks are able to maintain better quality portfolios and lower levels of provisioning, and are ultimately able to generate higher profits despite their higher operating costs.

# **_5.2 Regression Results_**

In this section we use regression analysis on a sample of annual bank observations in nine nonGCC MENA countries for the period 2001-08 to elaborate on our two-group comparison findings. Table 6 reports the mains results while Appendix C reports additional results involving weighted regressions. Our weights are inversely proportional to the number of banks in a given country to account for differences in the number of banks per country which could skew the results in favor of countries with more banks.

Our main independent variables of interest are a set of dummies: public, foreign, and listed. By including these dummies simultaneously, their regression coefficients need to be interpreted relative to the reference group of private, domestic, and non-listed banks. To account for confounding factors we also include the following bank-level, time-varying controls. As a measure of bank size we use the 1-period lag of the log of total assets. To distinguish between the different strategies on income-generating activities of banks, we also include the non-interest income to total assets. In line with other empirical studies, to control for different asset
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. Livestock indicator takes the value 1 if the household owns any livestock and 0 otherwise. Access to electricity and cell or land-line phones are used as measures of a proxy for access to infrastructure and communication. The Upazila population is expected to proxy for economic development.

# **_Rainfall variability_**

We considered two sources of rainfall data. First, historical monthly rainfall data from 1948 to 2010 was from the Meteorological Department of Bangladesh for 35 weather stations around the country. The weather station data represents actual measured rainfall at the specific station and time and thus, are more accurate. On the other hand, substantial manipulation is needed to estimate rainfall at each Upazila from the weather station data. We used inverse distance weighted average of three nearest stations to estimate the rainfall for each Upazila for each month. However, this method does not control for altitude and other geographical characteristics and Upazilas near international boundaries do not take weather stations in other countries that may be closer than those in Bangladesh into account.

The second source of rainfall data is from the Climate Research Unit of the University of East Anglia. Estimated monthly rainfall for most of the world is available by the half degree resolution from 1902 to 2009. The CRU estimation combines weather station data with other information to arrive at the estimates. Previous versions of the CRU data were homogenized to reduce variability and provide more 6
1.052|
|Kenema|-0.336|-0.095|0.356|0.790|
|Port Loko|0.227|-0.007|1.892|0.979|
|Western Area Urban<br>_Source_: Authors’ calculations from CIMS (202|0.199<br>0)._Note_: This Balanc|0.093<br>e check table includes R|0.999<br>ound 1 beneficiaries|0.999<br>in the largest|

_<mark>Source</mark>_ <mark>: Authors’ calculations from CIMS (2020).</mark> _<mark>Note</mark>_ <mark>: This Balance check table includes Round 1 beneficiaries in the largest estimation sample of our ECT-R1 analysis. “Raw” columns show the values prior to the inverse-probability weighting and “Weighted” columns show the values post weighting. The standardized differences should be equal to zero and the variance ratio should be equal to 1 if the samples are perfectly balanced.</mark> 33
World's Cities. Local Action for Global Goals. Earthscan, London, Table 2.8. Based on consumer surveys by Asian Development Bank, reported in McIntosh, A.C. and Yfiiguez, C.E. (1997) Second Water Utilities Data Book. Asian Development Bank, Manila.

<!-- Start of picture text --> Source Price/payment Shillings/ USS/m*<br>litre<br>Own connection Monthly lump sum, flat rate, based on: 0.27 0.34<br>Neighbour’s tap / water 20 shillings per 20-litre container 1.00 1.25<br>kiosk<br>Pushcart water vendor 70-200 shillings per 20-litre container 3.50—-10.00 4.38-12.50<br>Tanker truck (10,000 litres) 60—80,000 shillings per truckload 6.00-8.00 7.50—10.00<br>Sources: Kjellén, M. (2000a) Complementary water systems in Dar es Salaam, Tanzania: The case of water<br><!-- End of picture text --> vending, Water Resources Development 16(1): 143-154; and Kjellen, M. (2000b) Uuzaji wa Maji katika Jiji la Dar es Salaam. Environment and Development Studies Unit (EDSU), Stockholm. Data source: Water Vendor Survey 1998/1999,
, combining Equations (C.3) and (C.4) and plugging in the estimated parameters for PP 1 and the estimated distributions of the error terms for and 1, we have 1 2 1 ββ 1 2 2) (C.5) cc1 υυ εε cc1 EE(PP(ββ̂ ′xx + υυ� + εε̂ ≤zz )) = PP(yy ≤zz Since we do not exactly know the predicted error terms and 1 in survey 1 that are associated with the characteristics _x2_ for each household in survey 2, we can simulate these error terms from cc1 their estimated distributions and approximate the first term on the left hand side in equality (C.5) as υυ� εε̂ 1 ∑ 1 1) 1 2 1 1)) (C.6) pp SS ss=1 2,ss cc1 SS PP(yy� ≤zz →EE(PP(ββ̂ ′xx + υυ� + εε̂ ≤zz 1 _th_ where 1 2 , and and represent the _s_ random draw from their estimated distributions for and 1, for s= 1,..., S (see, e.g., Gourieroux and Monfort, 1997). The 2,ss cc1,ss 1,ss cc1,ss 1,ss number of simulations S should thus be large enough for the term on the left-hand side to converge yy� = ββ̂ ′xx + υυ�� + εε̂̃ υυ�� εε̂̃ cc1 to the term on the right-hand side of Equation (C.6), which results in Equation (4). We recommend υυ εε using 1,000 simulations. The terms on the left-hand side of Equations (C.4) and (C.5) also make it clear that we should use the poverty line 1 in the base survey (rather than the poverty line 2 in the target survey) together with the imputed consumption for the base survey 21 to obtain poverty
46.0%|2.6|
|Individuals aged 18-59|60.6|28.2%|29.4%|1.2|
|Individuals aged 60 or more|13.9|28.6%|13.3%|-15.3|

Source: authors’ estimations based on PNAD-C 2019. Notes: Pre-fiscal income considers the household-level market income plus pensions, while the post-fiscal income considers the household-level consumable income. The proportion of individuals indicates the number of individuals in each group as a share of the total number of individuals in PNAD-C.

To understand the effects of headship structure, Table 6 presents the poverty rates for three related dimensions. In panel A, we show the categorization in terms of whether the household is single-headed or two-headed. In panel B, in turn, we split households into those headed by a female and those headed by a male and, finally, in panel C we show the combination of these two criteria.

Table 6 indicates that the change in poverty rates is larger in absolute terms for (i) single-headed households, and (ii) those headed by men. Poverty changes for each group are small for many groups. Individuals living in a household headed by a single male show the largest drop in poverty (-4.8 p.p.).

33
three mechanisms: i) Decreasing the income threshold would curtail beneficiary numbers, ii) reallocating funds from reduced expenditure could finance larger benefit amounts, and iii) mirroring the tax deduction approach, larger benefits would be directed toward households with many children, who are shown to be highly vulnerable in this analysis. However, a balance must be reached when adjusting the maximum qualifying income for beneficiaries; if set too low, specific economically vulnerable households might not receive benefits and could experience increased vulnerability after accounting for the negative impacts of indirect taxes. Therefore, the envisioned scenario finds a middle ground, reconciling the intervention's fiscal impact limitations and its potential for reducing child poverty. Finally, a substantial increase in the generosity of child benefits is expected to yield significant welfare increases among eligible families with children.

# VI.Summary and Policy Recommendations

**Child poverty is a pressing social issue in Bulgaria, standing among the EU's highest rates, with significant implications for several long-term development outcomes.** The country exhibits a strikingly high (albeit diminishing) occurrence of child poverty within the European Union. Yet, while fiscal incidence analysis is a frequently employed approach, it often overlooks the perspective of children or gender, owing to the intricate methodological challenges involved in reconciling individual and household-level concepts. It is critical to understand the role of fiscal policy in reducing overall poverty and child poverty in particular, and the efficacy of family-oriented interventions in reducing child poverty.

**This paper revisits the previous fiscal incidence analysis of Bulgaria. It formulates a specialized fiscal incidence analysis focusing on children to measure the current effects of public expenditure and taxation on overall poverty and child poverty.** The World Bank conducted a comprehensive fiscal incidence analysis (CEQ) for 2018 to comprehensively assess the distributional implications of fiscal policies and programs. This analysis is now revisited and updated to offer a dynamic perspective on the impact of fiscal policies on poverty and inequality, considering the effects of the COVID-19 pandemic. The study extends its scope by introducing an
included on the 4<sup>th</sup> Quarter Bangladesh Business Confidence Survey. We ask a series of ten questions of varying political sensitivity. This ranges from questions about underpaying taxes and paying bribes to using the office phone for personal use. The method and structure of these questions comes from Azfar and Murrell (2009) and Clausen et al (2010). While we build on this existing method, we use this approach to both to identify the types of firms that are likely providing false responses to corruption questions.

The instructions provided to the survey administer for our coin flip strategy are: _[Instructions: Respondents are given a coin. If they flip heads, the respondent should answer “yes.” Otherwise the respondent should respond to the questions. The enumerator shouldn’t observe the toss.]_ We present the exact questions in the Appendix (Question 3). We include politically non-sensitive questions such as if the respondent has ever lied in their own self-interest or used a work phone for a personal call. Other questions are designed to be highly sensitive, such as if the respondent pays less in taxes than they should in taxes. Our main question on corruption focuses on a very specific form of corruption relevant for starting and expanding business. Our question is, “Did your business have to pay a bribe to get permits to start a business?” This randomized response technique (RRT) can help mitigate a number of problems with potential false responses to surveys. First, it allows respondents deniability for any illegal or unethical answers given in the survey. For example, one question asks if the manager’s firm pays less than they should in taxes. Firms responding “yes” to this question can credibly claim that their “yes” response was driven by randomization, rather than an admission of guilt. Second, this question is a specific, 11
scribes the data collection protocol, present selected summary statistics, and show that by chance the means of some covariates were not balanced at baseline, highlighting the importance of controlling for baseline characteristics in our estimates (the adjusted and unadjusted estimates remain qualitatively similar). Section 4 presents the conceptual framework that guided the study design and the interpretation of the results provided in Section 5. The cost effectiveness of the interventions is evaluated in Section 6. Finally, Section 7 concludes and highlights limitations of the results.

# **2 Program Description and Study design**

This study was carried out in Sonargaon, a 171 km<sup>2</sup> sub-administrative unit (or _upazila_ ) of Narayanganj district, located approximately 25 kilometers south-east of the capital Dhaka. According to the 2011 Census of Bangladesh, Sonargaon had a population of about 400,000, and at the time of the study it included 365 villages. According to the BAMWSP blanket testing, conducted locally in 1999-2000, about 40% of villages in Sonargaon contained _>_ 90% of wells that did not meet the national standard of 50 ppb.<sup>4</sup>

## **2.1 Study Area and Program Description**

The study area for this trial was initially formed by the list all 128 villages in Sonargaon with more than 10 wells and with a 40-90% share of unsafe wells based on the BAMWSP testing conducted years earlier. A lower bound was chosen to focus on areas where a sizeable fraction of new untested wells were likely to be unsafe, while the upper bound was designed to avoid areas where switching to safe wells was not likely to be a viable option for most households.

Between January and June 2016, surveyors conducted home visits to identify all wells in the selected villages, regardless of whether they had been tested before. Privately owned wells were linked to household who owned it, while public wells were linked to the main caretaker or user. Almost all wells (98.6%)
prohibitive impact on imports (Staiger and Wolak 1994; Prusa 2001; Bown 2004c), we use as our proxy for lost imports the log of the value of 10-digit Harmonized Tariff Schedule (HTS) imports of the targeted product in year _t1_ , i.e. the year before the trade remedy was imposed. The 10-digit HTS import data for the United States comes from Feenstra, Romalis and Schott (2002) and updates from the ITC’s _DataWeb_ database.

Second, the removal of the U.S.-imposed trade remedy may not be particularly important to some exporting countries that have substantial access to alternative export markets and can thus “deflect” trade that is eliminated from the U.S. to other markets.<sup>17</sup> Put differently, the removal of the U.S.-imposed remedy may be more beneficial to a less-diversified exporter than to a more-diversified exporter. To address the possibility that this affects the WTO litigation decision, we include as an additional explanatory variable the share of the exporter’s product-level exports to the non-U.S. markets in _t-1_ relative to its total product-level world exports of the goods targeted by the U.S. remedy.<sup>18</sup> We expect this variable to be negatively related to the decision of whether to initiate a dispute – a country that is highly diversified (i.e., with a large share of remedy-affected exports already being exported to third markets), should be less likely to challenge a U.S.-imposed remedy at the WTO, because it more easily shift those lost U.S. exports to such third markets.

Third, we also include the _level_ of the U.S.-imposed trade remedy in the case, which we define as the trade weighted-average final duty reported in the _Federal Register_ . We are admittedly agnostic as to how this variable would affect the likelihood of WTO dispute initiation. While an extremely high duty may also be more likely
<u>OAF (Other African countries): South Africa and North African countries, i.e.</u> Morocco incl. Western Sahara, Algeria, Tunisia, Libya, Egypt.

5. <u>EUC (EU28): the 28 EU countries</u> 6. <u>USA (United States)</u> 7. <u>CHN (China): including Hong Kong and Macau</u> 8. <u>ROW (rest of the world): there already is a ROW category in the original Eora</u> database, but we enlarge this group, adding all countries not in sub-Saharan Africa, nor in regions 4 to 7.

In addition, we distill the information of the full, integrated MRIO table into a series of country-specific (and year-specific) input-output tables, one for each sub-Saharan country. Breaking-up the information by country is a more efficient way of maintaining some regional detail than working with a single IO table that includes all 45 sub-Saharan countries with the above 5 regions. Given that a single IO table for the 45 countries of interest and the 5 regions listed above would still contain more than 200,000 coefficients, it would still be very difficult to distill useful insights from it. Moreover, bilateral trading relationships between many individual countries in the region are extremely limited.

> 12 The 6 final demand components are final consumption by households, non-profit institutions, and government, as well as gross fixed capital formation, changes in inventories, and the net change in valuables.

20
the past year|feels unsafe most of the days<br>lives in a household where at least<br>one member has experienced<br>burglary or assault in the past 5<br>years|
||**Agency and**<br>**voice**|Civil participation|lives in a household where no<br>member has participated in a group,<br>organization and/or association|has not participated in march,<br>and/or contacted traditional<br>leader and/or government official|
|**Process**<br>**Legitimacy**|**Social**<br>**accountability**|Satisfaction with<br>democracy<br>Government<br>effectiveness<br>Equality before the law|lives in a household where at least<br>one member thinks democracy is not<br>working in Peru<br>lives in a household where at least<br>one member thinks the government<br>is performing poorly|is dissatisfied with the way<br>democracy is working in South<br>Africa<br>is dissatisfied with the local<br>government basic service<br>provision in the neighborhood|
|||<br>(PE)/<br>Satisfaction with the<br>way corruption is<br>combatted (SA)|lives in a household where at least<br>one member thinks there is no<br>equality before the law in society|is dissatisfied with the way<br>corruption is combatted in their<br>neighborhood|

(a) All indicators are equally weighted within a dimension. Each indicator has a weight of 1/16 or 6.25% .

(b) Inadequate floor/walls/roof is defined per the SDG guidelines. Assets includes all durables listed in the survey of each country (i.e TV, radio,