rafmacalaba/data-use-mentions-extended huggingface dataset:
1985.<sup>15</sup> The 1975 migrant is observed in all three censuses, the 1985 migrant only in the last two censuses. The individual arriving in 1975 is 30 years old in 1980 (therefore 40 in 1990, and 50 in 2000), while the one arriving in 1985 is 30 years old in 1990 (and 40 in 2000). Since our hypothetical individuals have tertiary education, all predictions from this point on will be associated with skilled migrants, justifying the title of the paper.

Finally, our analysis produces the following eight sets of predicted occupational placement indicators for each of the 112 countries that will be used in section 3.2. to assess skilled immigrants’ performance over time and by country: (1)ÔP1980 , ÔP1990 , ÔP2000 , ΔÔP19801990<sup>, ΔÔP</sup> 1990-2000<sup>, for the hypothetical individual who arrived in the 1975; (2) ÔP</sup> 1990<sup>, ÔP</sup> 2000<sup>,</sup> ΔÔP1990-2000 , for the hypothetical individual who arrived in the 1985.<sup>16</sup> Summary statistics including size of cohorts, weighted and not-weighted, and information on sample structure by age, years since in the US and education are presented in Table 2. The first three columns refer to the individuals who arrived during the 1970s and whose performance levels are captured by Censuses 1970, 1980, 1990. Arrivals in the 1980s are summarized in columns 4 and 5. The first row indicates the size of the five samples, while the second row shows the equivalent in the whole US population. In principle, the numbers for each decade should decline across censuses due to return migration or mortality. Counter-intuitively, it can be observed that samples sometimes increase over time. For example, there are 1,668,342 migrants arriving in the 1980s according to 1990 census and they increase to 1,704,575 in 2000 census. The biggest
_ FINDEX is an individual level data base and LITS is household level. In FINDEX, 145 countries are sorted on Coverage, and only nearest neighbors in coverage rates are shown. In LITS, 35 countries are sorted on Coverage, and only nearest neighbors are shown. See Appendix for all countries. _Sources_ : FINDEX, LITS The role of gender in having a debit card is reduced substantially at the hosuehold level from 57.4 percent to 16.8 percent. (Figure 16) The sources of this decline are likely to be parallel to the reduction in the contribution of gender to the dissimilarity index in the usage of bank accounts. Income and education are the main sources of dissimilarity as they collectviely account for almost 75 percent of the d-index. Comapred to benchmark countries, this value is relatively higher as age or the urban/rural divide play a more important role in countries with similar coverage rates at the household level.

17
Bianchi, M. and M. Bobba (2013). Liquidity, Risk, and Occupational Choices. _Review of Economic Studies 80_ (2), 491–511.

- Blattman, C. and J. Annan (2015). Can Employment Reduce Lawlessness and Rebellion? A Field Experiment with High-Risk Men in a Fragile State. _forthcoming in American Political Science Review_ .

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- Blattman, C., N. Fiala, and S. Martinez (2014). Generating skilled employment in developing countries: Experimental evidence from Uganda. _Quarterly Journal of Economics 129_ (2), 697–752.

- Blattman, C., J. Jamison, T. Koroknay-Palicz, K. Rodrigues, and M. Sheridan (2015). Measuring the measurement error: A method to qualitatively validate survey data. _forthcoming in Journal of Development Economics_ .

- Borghans, L., A. L. Duckworth, J. J. Heckman, and B. t. Weel (2008, September). The Economics and Psychology of Personality Traits. _Journal of Human Resources 43_ (4), 972–1059.

42
Table (E17) Impacts of the Program on Education and Cognition

|**Outcomes**|**Treatment**|**(se)**|**FDR**<br>**q-values**|**Control**<br>**mean**|**(sd)**|**N**|
|---|---|---|---|---|---|---|
|FR Years of Schooling|0.39|(0.71)|[1.00]|6.49|(3.97)|1,422|
|FR Private Education (=1)|0.02|(0.02)|[1.00]|0.01|(0.11)|1,422|
|FR Religious Education (=1)|0.00|(0.01)|[1.00]|0.01|(0.09)|1,422|
|FR Fluid Intelligence (Z-Score)|-0.09|(0.37)|[1.00]|7.42|(2.94)|1,422|

**_Notes_** :

- The table shows the regression results on pre-specified education and cognition outcomes using the 2021 in-person data. Each row is its own dependent variable.

- The outcomes that require definitions are: FR Years of Schooling is calculated as follows: first, because few FRs reported total years of schooling rather than the marginal years at their latest stage, each stage is capped at its correct upper bound (10 years for primary in Jordan; 9 years for primary in other countries; 2 years for secondary in Jordan; 3 years for secondary in other countries; 3 years for college; 8 years for university). After that, those who never
impact on open defecation rates in households without toilets at the baseline, and that are the major beneficiaries of the project, might be because such changes take time to materialize, especially considering project delays in the construction of new toilets. Since the midline survey was undertaken right after the completion of the project interventions, some households with brand new toilets might not have gotten accustomed to using them.

In Punjab, both adults and school-going children surveyed at the baseline displayed high levels of awareness of basic hygiene and sanitation issues. Almost all households reported having soap, and a large majority of baseline survey respondents were aware of the reasons for using soap as well as the ill effects of open defecation on communities’ health in general and children’s health in particular. After the completion of the project interventions, we observed large improvements in hygiene knowledge and sanitary practices among both adults and school-going children—and in the control GPs as well. This was mainly due to statewide information and education campaigns undertaken by the India’s central government as well as the Punjab state government through television, radio, and social media to reinforce the messages of the BCC campaign. Our estimation techniques eliminated these time-varying fixed effects to capture the true impact of the project.

Our results indicate that the BCC campaign had a positive and significant impact in raising awareness of the importance of handwashing before eating and after defecation among adults across all treatment arms. The project’s impact appeared to be strongest on households that had access to toilets at the baseline. For households without access to toilets at the baseline, the project’s impact on adults’ awareness of handwashing before eating seemed mostly insignificant, whereas significant improvement in awareness of handwashing after defecation among adults was restricted to GPs receiving regular project interventions and the intensive school awareness campaigns.

The BCC campaign was also very successful in raising awareness of handwashing among school-going children in all treatment arms. Significant improvements in awareness of handwashing before eating were also observed among subgroups of children from households with and without access to
source of all control variables at the bilateral level is CEPII’s GeoDist database. The only exception is the variable on economies’ common legal origin, which comes from La Porta et al. (1998). The GDP data come from the World Bank’s WDI database.

> 6 The following offshore financial centers were excluded from the analysis: Andorra, Anguilla, Aruba, Bahamas, Belize, Bermuda, British Virgin Islands, Cayman Islands, Cook Islands, Cyprus, Gibraltar, Guernsey, Isle of Man, Jersey, Liechtenstein, Macao, Monaco, Montserrat, Netherlands Antilles, Palau, Panama, Samoa, Seychelles, Turks and Caicos Islands, and Vanuatu. The list comes from https://www.imf.org/external/NP/ofca/OFCA.aspx.

7
br>HIV Prevalence<br>0,30%<br>0,10%<br><!-- End of picture text -->

**Sources:** Adapted by Técnicas de Salud using data from the following sources:

- a. UNGASS 2012: p.28.

- b. UNGASS 2010: p.41.

- c. Personal communication from Dr. Luque, Asesor de la Dirección de Promoción y Prevención del Ministerio de Salud y Protección Social.

- d. Análisis estimaciones de la epidemia de VIH en Colombia 2011. Spectrum versión 4.47 generado el 30 de marzo de 2012. Ministerio de Salud y Protección Social.

> 20 UNGASS 2010: p.41

> 21 Personal communication from Dr. Luque, Asesor de la Dirección de Promoción y Prevención del Ministerio de Salud y Protección Social.

20
_a. Formal Sector firms_ : This study is limited to the formal private sector. We omit firms that operate informally because business registries are unable to provide accurate cross-country tallies of these firms. This is an important caveat, as there is a strong and inverse relationship between the size of the informal economy (defined by Schneider, 2007, as a percentage of GDP) and our variable of interest: new business density (Figure 1), defined as newly registered firms as a percentage of the country’s working age population (ages 15-64), normalized by 1,000.

<!-- Start of picture text --> 10<br>8<br>6<br>4<br>2<br>0<br>0 20 40 60 80<br>Informal Economy (% GDP)<br>Entry Density ‘04-’09<br><!-- End of picture text -->

**Figure 1: Entrepreneurship and Informality**

_b. New Firms:_ The database does not include the number of total or closed firms, since most countries do not accurately collect data on total ‘active’ or ‘inactive’ firms. Therefore, we are concerned that the stock number of total firms includes many closed firms that did not formally de-register. Furthermore, the process to remove inactive firms varies widely across countries: For example, in Sweden, firms are removed from the registry if they do not submit financial statements and an audited account within eleven months of the end of the financial year; Austria and Slovakia remove firms that fail to file financial reports for two consecutive years; while other countries report that firms are never removed from the registry. Consequently, 6
industry. The fund was announced in 2014 for a duration of 10 years. The form of the intervention was state loans available to all firms. The HS6 products reported as potentially affected by this intervention include products at different stages of the semiconductor value chains, from the “Machines and apparatus for the manufacture of boules or wafers” (HS code 858610) to the “Processors And Controllers, Electronic Integrated Circuits” (HS code 854231). Examples #1 and #2 illustrate the virtues of a comprehensive cross-country database of rich information about many different aspects of different types of policies. On the other hand, the association of these measures with the potentially affected products is inevitably imperfect. This might introduce significant measurement error in an important explanatory variable of interest.<sup>4</sup>

> 4We consider for our exercise all the measures reported by the GTA for which a set of potentially products is reported. The alternative would be to consider only the interventions directed to specific firms, with the benefit of isolating better discriminatory measures, but the cost would be excluding important industrial policy episodes such as the establishment of the “Big Fund” in China in 2013.

6
serve for these purposes, this paper relies on quantitative results generated through the Survey on Monitoring the Paris Declaration (the PD survey) given the survey‘s three key advantages. First, it has comprehensive country coverage with 78 countries participating in the latest survey round in 2011. Second, as it was conducted three times – in 2006, 2008 and 2011 – it allows us to conduct some degree of time series analysis over the past half-decade. Third, it has a comprehensive coverage of aid effectiveness issues, consisting of 15 indicators (including subindicators). Among the 15 indicators, this paper selects 10 which directly relate to the delivery and management of aid. However, as the indicators have different definitions and methodology, they cannot be directly compared to each other. Therefore, this paper translates indicator values into standardized scores so that indicators can be more easily compared.

As both recipients of aid (FCS) and providers of aid (development partners) are mutually accountable for aid effectiveness, analyses are conducted by focusing on both sides of the equation. First, performance in 2010 is compared across partner countries and indicators, which enables us to

> 2 This paper uses the World Bank classification of FCS in FY2012.

> 3 <u>A New Deal for engagement in fragile states</u>

> 4 <u>World Development Report 2011: Conflict, Security and Development (World Bank)</u>

> 5 <u>The World Bank defines aid effectiveness as</u> ― a cross-cutting mandate for partner countries, donors, and other aid providers- including the Bank; embodying a reform agenda to better deliver and manage aid‖

2
# **Does Parental Disability Matter to Child Education?**

# **Evidence from Vietnam**

Nguyen Viet Cuong National Economics University, Hanoi Daniel Mont The World Bank

**Keywords:** Child education, disability, impact evaluation, household survey, Vietnam. **JEL classification:** I12; I21; O15

The findings, interpretations and conclusions expressed herein are those of the authors, and do not necessarily reflect the views of the International Bank for Reconstruction and Development/The World Bank and its affiliated organizations, or those of the Executive Directors of The World Bank or the governments they represent.
# Table C.1: The Effect of VAT Rebates on Tax Compliance Difference-in-Difference Estimates, Annual Data

(a) Balanced Sample

||Taxabl|e Sales|Outpu|t VAT|Net VAT|Liability|
|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|
|Retailer _·_ PostReform|-.059|-.056|.047|.037|-.022|-.065|
||(.046)|(.046)|(.041)|(.041)|(.074)|(.077)|
|State _·_ Year FE|No|Yes|No|Yes|No|Yes|
|Firm Size Decile _·_ Year|No|Yes|No|Yes|No|Yes|
|N Treated|2822|2822|2822|2822|2822|2822|
|N Control|3014|3014|3014|3014|3014|3014|

## (b) Unbalanced Sample

||Taxabl|e Sales|Outpu|t VAT|Net VAT|Liability|
|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|(6)|
|Retailer _·_ PostReform|.032|.018|-.026|-.045|.019|-.01|
||(.04)|(.041)|(.036)|(.037)|(.049)|(.051)|
|State _·_ Year FE|No|Yes|No|Yes
)||||-0.293***|-0.123***|
|||||(0.001)|(0.001)|
|Observations|34,128|32,231|28,344|18,138|18,138|
|Year Fixed Effects|Yes|yes|yes|yes|yes|
|Sector Fixed effect|Yes|yes|yes|yes|yes|
|Sector-Year Fixed effect|No|no|no|no|yes|

_Source:_ authors’ calculations based in the Orbis dataset for Turkey. _Notes:_ The regressions are estimated by GLS. LHS is log employment. FO is transformed as (FO _/_ 100)+1. FO is the share of foreign-owned equity. ∆<sup>_k_</sup> indicates the change between year _t_ and year _t_ − _k_ where _k_ = 1 _,...,_ 4. Standard errors clustered at the firm level are in parenthesis. *** , **, *, denote significance at 1%, 5%, and 10% levels.

Table 5 runs similar regressions as above but this time using log employment as the dependent variable. As we can see, there is an initial increase in employment but after four years this effect turns negative. This may mean that domestic content requirements imposed on multinationals upon arrival, in terms of hiring local workers, would vanish after the fourth year. This is not surprising since the four-year mark is also when productivity starts improving. Clearly, efficient use of labor explains part 10
generous nature of these subsidies, especially under the _régime spécial_ , was only applicable to a small number of loans. Thus, from the very beginning, sustainability problems were likely to occur given these interest rate parameters.

# <u>Subsidies through provisions in the Tax code</u>

- Deductions of mortgage interest payments from taxable income:  up to 10% of taxable income. The corresponding expenditure amounted to MDH 276 million in 1995. A World Bank study on CIH data from 1992 (World Bank, 1995) showed that the tax expenditure for CIH loans only was Mdh 115 million, out of MDH 277 million of deductible interests. This corresponded to an average subsidy rate of 41% on mortgage interests. The subsidy rate, corresponding to the marginal tax rate, was increasing in income. Households with income above MDH 60,000 per year (the highest three deciles of the income distribution), which represented 62% of the CIH mortgagers in 1992, benefited from 68% of the tax expenditure. Thus, the provision was highly regressive.

- For civil servants, the ability to deduct payments from the mortgage principal and interest from taxable income, without a ceiling, provided the dwelling is worth less than MDH 500,000. The cost of this provision is not known for 1995. However, this provision, which still applies today, is particularly inequitable, since it benefits only a specific household category, which is on average wealthier than most, and thus has easy access to funds because of their job security.

The combination of these two provisions was thus poorly targeted, with a redistribution pattern favoring the wealthy over those benefiting from interest rates subsidies. This pattern also suffered from the same coverage problems (only households to access housing finance covered), exacerbated by the income tax schedule, which resulted in the majority of interest rate subsidies being distributed to those in higher tax brackets.

Although this type of subsidy exists in many countries, it can be highly inefficient (see Skinner, 1996)
terns of participation in the two export finance support schemes we evaluate.

We use two data sets in this paper: (i) customs data, and (ii) information provided by SBP on the firms participating in EFS and LTFF. Customs data provided by the Federal Board of Revenue contain the universe of export and import transactions for firms in Pakistan over the period 2015-2017. These data have information on the value of firms’ exports and imports by product at the HS 8-digit level denominated in Pakistani rupees as well as the country of origin and destination of trade flows. Throughout this period there are 20,052 firms reporting at least one positive export transaction in at least one of 2,844 HS 8-digit products sold to 202 countries. The data on the usage of export finance support schemes include information on which firms made use of the EFS and LTFF financing facilities and the value of the loans they requested from commercial banks in each fiscal year.<sup>6</sup> The data are linked at the firm level using National Tax Numbers (NTN).

Table 1 provides a first pass at the export sector characteristics in our data. The number of active exporters remains stable throughout our period of study, with around 14,500 firms exporting each year on average. On average, Pakistani firms export five HS 8-digit products and serve four foreign markets. Export sales per firm are highly skewed towards high values, which is reflected in the large difference between the mean and median exports per exporter. These figures are closely in line with those reported by Fernandes et al. (2016) for developing countries of a similar size.

> 6We only observe the total value of loans obtained by a given firm through each scheme. Therefore, our data do not allow us to distinguish if loans are provided for some export transactions and not others. The data for EFS do not provide information about which variant(s) (Type I or II) a firm uses to obtain financing.

9
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