rafmacalaba/data-use-mentions-extended huggingface dataset:
DIALOGIC READING AND STORYBOOK EVALUATION IN KENYA 13 kilometers of another school in the study or within three kilometers of any school included in other ongoing research projects.

Within in each community (i.e., primary school catchment area) chosen for inclusion in our sample, we conducted a census to generate a listing of all households living within a radius of 750 meters of the school. Compounds including at least one child aged 24 to 83 months as well as the primary caregiver of that child met the inclusion criteria to participate in the study (irrespective of whether the household’s children were enrolled in school). Through our census activities, we identified 592 households with children in the eligible age range. These households resided in 524 unique compounds. A further 451 compounds did not include any children in the eligible age range.

In order to avoid cross-contamination, we randomly selected a subset of eligible households from neighborhoods where dwellings were less than 100 meters apart. When a community contained a large number of households grouped together, a subset was randomly chosen for inclusion in the baseline sample. We then grouped selected households that were less than 100 meters apart into clusters of no more than two households. Otherwise-eligible households that were excluded from the study for proximity reasons were invited to attend a book-sharing training that occurred after the follow-up data collection.

After randomly selecting eligible households from areas where dwellings were densely spaced, we generated a list of 410 eligible households that we invited to participate in the study. After obtaining written consent from the primary caregiver within a household, field workers enrolled participants between March and October of 2016. We enrolled 357 caregivers (87% of those invited) with 510 children between the ages of 24 and 83 months.
LAYS, respectively. These metrics fall short of an artificial high-performance benchmark of 0.80, chosen by Angrist et al. (2020b) due to its stability and non-political properties. In terms of relative effectiveness, _T_ 2 ranks 5 _th_ relative to the 72 studies we consider for this comparison. Table 9 shows the twelve interventions with the largest impacts on LAYS. This list includes studies of two edtech interventions evaluated in India, computer-assisted learning by Banerjee et al. (2007) and vouchers for the Mindspark adaptive learning software by Muralidharan et al. (2019).<sup>19</sup> Considering that _T_ 2 had similar effects on literacy and numeracy outcomes for older

> 17The study of Angrist et al. (2020b) uses data of 150 impact evaluations for its effectiveness estimates. It then calculates a cost-effectiveness measure for a subset of 72 interventions for which cost data were available. We compare our effectiveness and cost-effectiveness measures to the same list of 72 interventions.

> 18See more details about this methodology at `https://www.povertyactionlab.org/resource/ conducting-cost-effectiveness-analysis-cea.`

> 19Our _T_ 2 and these two edtech interventions in India share characteristics that Angrist et al. (2020b) note are common among top performing educational interventions, including being multidimensional combined programs and instruction adjusted to the students’ learning level.

35
less likely to be captured in the sampling frame, due to informality, and they would require further adjustment in the survey instrument and sampling design.<sup>52</sup> This decision is aligned with other firm-level standardized surveys with comparability across countries. The World Bank Enterprise Survey (WBES) also uses a threshold of 5 employees. The World Management Survey (WMS) uses a threshold of 50 employees. In the case of Senegal, our sampling frame includes all firms registered in the establishment census of ANSD.<sup>53</sup> The RGE in Senegal has 407,882 businesses, but most of them (82%) refers to individual businesses or self-employees. Firms with 5+ employees represent 6% of total, but they are responsible for about 50% of total employment and 81% of total sales in the RGE database. For Brazil, the RAIS has 85,441 establishments formally registered in Cear ́a. Establishments with 5+ employees represent about 39% of total establishments and 93% of total employment.

> 52Establishments below this threshold often lack the organizational structure to respond to some of the questions.

> 53The ANSD uses a definition of formality based on the accounting system used by the firms. According to their definition, formal firms are those with an accounting system that is compatible with the West African Accounting System (SYSCOA). Our sample includes all firms with 5 or more employees registered under RGE, given that they tend to be also registered through the _num ́ero d’Identification nationale des entreprises et associations_ (NINEA), which makes them more comparable with formal firms in Brazil and Vietnam.

49
models and to limit sample selection bias,<sup>7</sup> we divide greenfield FDI into FDI by geographically diversified firms and FDI by other firms. Whereas we restrict the coefficients of our control variables to be fixed at the country-year level, the effect of political conflict and the constant are allowed to vary over the values of the diversification dummy. In the section containing our robustness analysis, we also present the results of a firm-level model.

The data on our control variables come primarily from the World Bank’s World Development Indicators Database. We control for _GDP_ given in millions of US$ in 2013 prices; the size of the _population_ ; and _inflation_ measured as the annual growth rate of the GDP implicit deflator. In addition, we add three variables that control for continuous political risk: the _level of democracy_ ; _regulatory quality_ ; and _control of corruption_ . Democracy is measured by the Polity Index developed by Marshall ‐ et al. (2013), which ranges from 10 to +10, where low negative numbers indicate autocracies and high positive numbers correspond to democracies. The quality of regulations indicator, part of Kaufman’s World Governance Index (WGI), measures perceptions of a government’s ability to formulate and implement sound policies and regulations that permit and promote private sector development. The control of corruption measure also comes from the WGI and measures the extent to which public officials use power for private gain. Both WGI variables are measured as a z-score varying from approximately -2.5 to 2.5, with higher values corresponding to better governance. Furthermore, we control for nominal _exchange rates_ (level and standard deviation<sup>8</sup> ) using data collected through OANDA. Appendix 1 provides descriptive statistics and the correlation matrix. Appendix 2 shows a list of all countries included in the sample.

# 4. ESTIMATION AND EMPIRICAL RESULTS

Using a fixed effects estimator to estimate the dynamic model (1) presents a problem. In panels with a large number of countries
# **6. References**

- Adams, R.H. and A. Cuecuecha. Remittances, household expenditure, and investment in Guatemala. _World Development_ , 38(11): 1626–41.

- Akresh, R., P. Verwimp and T. Bundervoet. 2011. Civil war, crop failure, and child stunting in Rwanda. _Economic Development and Cultural Change_ , 59:  777–810

- Almond, D. and J. Currie. 2010. Human capital development before age five. National Bureau of Economic Research Working Paper No. 15827. NBER: Cambridge MA.

- Bevis, L.E.M, and K. Villa. 2020. Intergenerational transmission of maternal health: Evidence from Cebu, Philippines. _Journal of Human Resources_ (forthcoming).

- Borjas, G.J. and H. Cassidy. (2020). The adverse effect of the COVID-19 labor market shock on immigrant employment. National Bureau of Economic Research Working Paper 27243. NBER: Cambridge MA.

- Camus, M. (Ed.), 2007. _Comunidades en movimiento: La migración internacional en el norte de Huehuetengano_ . _Instituto Centroamericano de Desarrollo y Estudios Sociales (INCEDES)_ and _Centro de Documentación de la Frontera Occidental de Guatemala (CEDFOG)_ , Antigua, Guatemala.

- Carletto, C., K. Covarrubias and J.A. Maluccio. 2011. Migration and child growth in Guatemala. _Food Policy_ 36(February), 16–27.

- Carletto, C. and A. de Brauw. 2007. Measuring Migration Using Household Surveys, Migration Operational vehicles, Operational Note No. 2, The World Bank: Washington, DC.

- Coates J., A. Swindale and P. Bilinsky. 2007. Household Food Insecurity Access Scale (HFIAS) for Measurement of Food Access: Indicator Guide (V3). Food and Nutrition Technical Assistance Project, Academy for Education: Washington DC.

- Cox Edwards, A. and M. Ureta. 2003
The principal caveat of the data sources used in this paper is that the universe of firms and workers corresponds to only formal economic activity and specifically the subset of formal firms and workers that pay into CIT and PAYE, respectively. Thus, informal firms and workers are necessarily excluded, as are formal firms and workers not meeting or complying with the filing thresholds for CIT. Given statutory thresholds for tax filing and firm- and worker-specific drivers of tax compliance, firms and workers in the CIT and PAYE databases are likely to be quite different from excluded firms and workers. However, the firms and workers in the datasets constitute an economically significant portion of the Zambian economy. For 2021, the CIT dataset covers over 5,000 firms, which collectively account for ZMK 329 billion in sales, ZMK 118 billion in value added (equivalent to 27 percent of GDP), and 527,000 estimated workers. For the same year, the PAYE dataset covers over 800,000 unique workers, filing over 6.3 million monthly returns. Beyond their collective size, formal firms, and workers—as proxied through these datasets—are especially critical to economic transformation as they are likely to constitute the most productive segment of the economy and most likely to export (Amin, Ohnsorge and Okou 2019).

# 4. Firm dynamics and productivity

## 4.1. Methodology for productivity analyses

Leveraging these data, productivity-related analyses in this paper focus on labor productivity (LP) rather than total factor productivity (TFP). LP and TFP are two ways of computing firms’ efficiency in converting inputs (capital, labor, etc.) to produce goods or services (output). Conceptually, LP measures output per worker and therefore looks only at how labor is converted into output, while TFP incorporates adjustments in other production factors (e.g., capital stock and intermediate inputs) as well as technology, innovation, management practices, and other ways of augmenting firm output with the same input endowment (Syverson 2011)
‐barreling, only a fraction θ� �1 of measured public capital is useful for production. The measured capital stock K��� is what is recorded in international statistical databases, constructed using the perpetual inventory method. θ� is the average _efficiency/quality_ of the public capital stock. Equations (1), (2A) and (2B) can be written in a more conventional production function as:

# <u>Congestion ( ζ ∈�0,1� )</u>

In principle, the congestion parameter in Equations (2A) and (3) can take values between: ζ�1 (full congestion) and ζ�0 (no congestion). As long as ζ�0 , it is the _ratio_ of public capital to private capital that provides public services, rather than the absolute amount of public capital (Barro and Sala‐i‐ Martin 1992).<sup>9</sup> When there is a large amount of private capital relative to public capital, the public capital

> 8 See Appendix A1.5 for a general idea of how the Standard LTGM differs from the LTGM‐PC.

> 9 Congestion can also be measured in terms of both private capital and labor supply (see for instance Glomm and Ravikumar (1997)) or aggregate output, but these do not result in substantial changes to the analysis (Eicher and Turnovsky 2000). Aside from absolute congestion, there can also be relative congestion, in which case, congestion increases only if aggregate usage increases relative to individual usage (see Eicher and Turnovsky (2000) for further details on how relative and absolute congestion affect growth analysis).

5
## **Figure 11. Proportion of applicants whose industrial specialization matches vacancies**

_Source_ : Authors’ calculation using the data from Rozee.pk. _Note_ : Shown is the proportion of applicants whose self-claimed specialization matches vacancy’s industry.

# 3.2 Skill demands

The concept of skills is broader than the educational qualifications or degrees. According to the World Bank’s Skills Toward Employment and Productivity (STEP) framework, there are three types of skills, namely cognitive skills, noncognitive skills and technical skills (World Bank 2010). Cognitive skills include the ability to understand complex ideas, to solve problems, or to engage various forms of reasoning. Noncognitive skills involve socio-emotional skills, personality, behavior, work ethics, and attitude. Technical skills are specific and specialized skills on technical subjects. As adopted by Nomura et al. (2017) for an Indian job portal, a first step of analyzing skill demands is to look at skill keywords used by employers in job descriptions. Applying a text analysis technique, Figure 12 graphically represents the frequency of required skills that show up in job descriptions.

## **<u>Figure 12. Graphical representation of required skills for all sectors</u>**

<!-- Start of picture text --> HtmlCreativity<br>Android SDKCSS3Ajax WordSocial Media MarketingMarket ResearchAngularJSMS WordMagentoDOCUMENTATIONleadership skillsExcellent Selling SkillsLaravelAdobe IllustratorPhotoshopClient Follow-upSales ExecutionExecutive Presentation SkillsMarketing Accounts ReconciliationChannel SalesLeadership qualitiesProject ManagementFacebook Real Estate/Propertytarget orientedOWLAnalytical skillsXMLC# ASP.NET MVCCodeIgniterReport WritingWriting ProposalsC++Fluent in EnglishMS OfficetelemarketingWordpressGoogle AdwordsPresentation SkillsPHPResearchPython SEO<br>Problem Solving Good communication skills Time management Jquery Excel Team Player MS Excel Adobe PhotoshopEnglish<br>Excellent Verbal and Written Communication SkillsComputer KnowledgeSales PromotionCSSMicrosoft OfficeAndroidCustomer CareGitWeb ServicesSoftwareJavaScriptCustomer Service ManagementSwiftiOSNegotiationsASP.netGood CommunicationMVC Excellent communication skillsAPI developmentillustratorHTML/XHTMLnegotiationERP Communication SkillsIdentifying Sales OpportunitiesSQLSelling SkillsContent OptimizationManagementMicrosoft WordJSONConfidentMicrosoft ExcelCorelDrawLead GenerationSales and TradingMicrosoft Office SuiteSalesCold CallingOOPEnglish FluencyBusiness DevelopmentContent writingAdobe Creative SuiteGoogle AnalyticsBootstrapClosing Seo ExpertDirect Salesnegotiation skillsSales ConversionSales ForecastingJavaStrong Communication skillsAdobe In DesignMySQLComputer skillsInterpersonal SkillsCOMMUNICATIONHTML5Customer serviceAutoCAD Android StudioObjective-C<br><!-- End of picture text --
This value is, without doubt, acutely low. According to the Maastricht treaty, by 1999 countries wishing to lock into the EMU fixed exchange rate system are requested ( among other things) to have a debt to GDP ratio smaller than 0.60. Germany, like Brazil, suffers from a low k, which implies low revenue from seignorage. Hence, Germany is compelled to make a greater fiscal adjustment than otherwise would have been the case.

Next Chart 6 shows the evolution of k for Germany Chart 6 **Germany: Base Money** Ratio to GDP <!-- Start of picture text --> 0.125 __l<br>0.120<br>0.115<br>0.110<br>0.105<br>0.100<br>0.095<br>°°-~~~~ -GEHffP<br>0.090 *2 9<br>70 7~74 76 78 8b 82 84 86 ~'b' 49<br><!-- End of picture text --> Source: IMF, International Financial Statistics This diagram shows a substantial variability in German demand for base money, which is in fact quite interesting given its strong record of stability.

# **Costa Rica**

Costa Rica is an interesting example of the costly switch from foreign to domestic financing. One reason can be traced to the sterilization of capital flows. From 1989 through 1995 foreign reserves of the Monetary Authorities increased twofold (IFS). Also, and most importantly, the operational deficit was 4.8 percent of GDP in 1994, 2 percent in 1995 and about 3.2 percent in 1996. This was mainly due to the high cost of real interest rates, as displayed in the following table: 24
The two districts use several types of POS machines, Regular POS (RPOS), Transaction Monitoring Device (TMD), and Web Service (WS). Gorontalo, however, also employs an additional POS type for hotel taxpayers called PAC Hotel and a modification of RPOS with connection to third-party data, namely RPOS-Grab. RPOS refers to a complete set of sales recording systems from the cash register machine and interface which helps users record transactions and print receipts. TMD, on the other hand, refers to a tapping device which is planted to an existing sales recording system and steals the transaction data. While WS is an API based software that reads users’ online sales system and sends the transaction records to the local governments. The POSs were distributed based on preexisting condition of the receivers, which we describe in detail in the next section of the paper.

Our research demonstrates that the influence of various POS device types on tax compliance varies. In West Manggarai, both TMD and WS have successfully improved restaurant tax compliance. We estimate that TMD and WS led to 180 percent and 55 percent increases of restaurant tax payments compared to the control group, respectively. WS, however, proved to have no significant effect on improving hotel tax compliance in the district.

In Gorontalo, restaurants that obtained RPOS-Grab on average paid 68 percent higher restaurant tax compared to those in the control group. On the other hand, restaurants that received RPOS units without Grab connection and TMD have indifferent tax payments on average compared to their control.

TMD and WS significantly increased tax payments among observed hotels and restaurants in both districts. Our findings shed light on the influence of business size and existing technological mastery on the efficacy of POS adoption in boosting tax payments. Larger businesses with better proficiency in using electronic transaction technology tend to pay higher taxes on POS assignment. That leaves regular POS (RPOS) as the only POS type with consistent statistically insignificant impact on tax receipt in both districts.

Our study contributes to the literature on tax compliance by providing unique insights
influencing migration patterns. First, the sample includes the majority of provinces which attracted FDI.<sup>16</sup> Second, unlike the VHLSS data, the sampling framework of which is based on permanent registration status (thus excluding temporary migrants), the VMS includes migrants with temporary or no household registration. Coverage of the latter migrants is important since many migrants who work for foreign firms tend to hold a temporary status.<sup>17</sup> Third, the VMS includes detailed information on individual characteristics and migration outcomes in destination areas, this permits an analysis of differential patterns of migration depending on job outcomes. Finally, since one can identify from the VMS where migrants came from, this in turn makes it possible to examine the characteristics of their origin areas.

In order to study the characteristics of migrants relative to non-migrants, the data on nonmigrants are taken from the VHLSS 2004. The VHLSS 2004 was conducted by the GSO of Vietnam with the technical support of the World Bank and is generally recognized to be of high quality and representative of all of Vietnam. The VHLSS 2004 data are also used to compute the province (and urban/rural) level variables in origin and destination areas.

The first and second columns of Table 1 compare the descriptive statistics of migrants vs. nonmigrants constructed from the VMS 2004 and VHLSS 2004 respectively. For the sample of migrants taken from the VMS, individuals between 15-59 years of age who work, and those who do not work but sought employment, are included. As a comparison group, the sample of nonmigrants is constructed from the VHLSS 2004. Non-migrants are defined as those who are 15-59 years of age and either work, or don’t work but sought employment, and who resided at the same

> 16 The eleven provinces covered by the VMS accounted for 83.3 percent of foreign employment in 2004 (author’s calculation based on the _Enterprise Survey_ data (GSO)).

> 17 According to the VMS, only 10.
.016)||||-0_123***<br>(0.040)|
|YearFE|rs|é|rs|rs|rs|v|v|vw|
|<br>ISOS|vo|re|wo|ra|ra|ra|re|ve|
|C-D F Statistic<br>‘Observations<br>NumberofClusters|5,603<br>182|4,822<br>160|4,694<br>160|4.694<br>160|19.056,<br>5,603<br>182|11.462<br>4 822<br>160|13.293<br>4,004<br>160|13.018<br>4.604<br>160|

Notes: This table presents the main results wing OLS and the instrumental variable strategy. The dependent vanable im all columns ts the economic reforms article count in all languages normalized by the total number of articles. GDP growth is instrumented using contemporaneous and lagged changes in the groee export commodity price index, as described in the text. Standard errors are clustered at the country level and reported in parentheses, stars indicate *** po 0.01, ** p< 0.08, * p< 01.
), which control for village fixed effects. Finally, the effect of the education module on demand is economically small and statistically insignificant.

Columns (4)-(6) interact these treatments with three household variables in turn: an indicator for whether the household reports being unfamiliar with BASIX, an index of household wealth, and the log of per capita food consumption. Column (4) shows that LSA endorsement has sharply different effects depending on whether the household is familiar with BASIX, and thus is likely to have had past interactions with the LSA. For households familiar with BASIX, LSA endorsement increases take-up by 10.1 percentage points, statistically significant at the 5% level. In contrast, endorsement has no net effect on insurance demand amongst households unfamiliar with BASIX (the net effect is 10.1 - 17.1 = -7.0 and statistically insignificant). The other notable interaction is that in both columns (5) and (6) the effect of the high cash reward on

> 17 Because treatments are randomly assigned to households, estimates of the treatment effects are consistent with or without these controls. But including them may reduce error variance, leading to more precise parameter estimates.

14