rafmacalaba/datause-encoder-data huggingface dataset:
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Graph 2 Pakislan -- Trend in Tolal and Fixed InvesIment Rate <!-- Start of picture text --> 20<br>O ~~~~~~................................................... . . . . . . . . . . . . . . .<br>r _...................................................................................................<br>72 73 74 75 75 77 7 8 7 9 8 D 81 8 2 B3 8 4 8 5 86 87 8 8 89 90 91 92<br>-Tolal Investment -+Fixed Investment<br><!-- End of picture text --> 12. The relatively weakter statistical significance of the labor coefficient, especialy in the maufrIng growth equation, partly reflec= the growing capital intensity of prodchltion.<sup>But it</sup> is also an indication that, coloris paribuis, population growth is too fast in Paldstan. Labor markets cann Ot productively absorb such a rapid growth in population, particularly with Pakistan's very low skill leveles. The increase in capital inte nsity could be the effect of two forces at work- First, Palistan's macrocemoomic policies have generaly favored greater capital intensity of produotn, resulting from under-priced capual unports through over-vbalued exchange rate (well unt the mid 1980s), low interet rts and other imentives. Seconxd, extemal migra:tion of skilled an d se misldlled labor in the 1970s and early 1980s tedd to raise real wages (see Irfan and Ahmed (19B81).

13. The positive impact of greater openness to itraonltrade and external compeiition on aggregate growth is a very important r-c;ult. Again, this is intLiitively appealing and consistent with the findings of other research (see, for example, the East Asia Mirale Study (1993)). The lower statistical significance of the trade variable in the mauimwregresion is ralher difficult to explain as, a priori, a large part of the effec of greater efficiency resultmg from increased openness should have come frnom the mariX sector.
loss of family members leads to higher dependency ratios. Further, refugee households are more likely to be headed by a woman than those of non-refugee households in various lowand middle-income destination countries (Mejia-Mantilla et al., 2019; Miguel et al., 2022; World Bank, 2019a; World Bank and UNHCR, 2020).

**Deterioration in mental health** Refugees and IDPs are also characterized by the traumatic events that either preceded their decision to migrate or along their journey away from their homes. Difficult conditions at arrival can reinforce negative mental health effects. Thus, studies usually find that refugees and IDPs suffer from worse mental health compared to the – host population although there is strong variation in the levels of incidence the studies find, due to the respective context and the methodology used (Porter and Haslam, 2005). The experiences of violence and displacement also affect their aspirations, attitude toward risk, and willingness to make investments specific to the host country (Schuettler and Caron, 2020; Chiovelli et al., 2021).

# **4 Characteristics of host communities**

Beyond the attributes of migrants discussed earlier, critical determinants of the welfare of refugees and IDPs include the characteristics of the communities that host them. These can be exogenous or themselves the outcome of the incoming flow of forcibly displaced individuals. In host communities, an inflow of refugees and IDPs can affect labor market outcomes, prices, provision of social services, availability of infrastructure and natural resources, crime rates, and social cohesion, among others (Becker and Ferrara, 2019; Verme and Schuettler, 2021). The perceptions of such impacts do not always align with the actual (aggregate) impact (Kreibaum, 2016). Nonetheless, perceptions influence attitudes and policies toward those forcibly displaced. In investigating the conditions under which the forcibly displaced are able to successfully integrate into their host communities, the discussion first examines the socio-economic environment where refugees and IDPs end up, in terms of the labor market, social networks and attitudes and perceptions of hosts. It then looks at the roles of policies and rights in encouraging or impeding social integration.

7
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Table 30: Urban and Rural Literacy Rates, By<sup>Age and Sex, 1981</sup>

|||Age Groups||
|---|---|---|---|
||------|-----------------------------|All ages|
|Location/sex|10-15|<br>15-35<br>35 and over|over 10|
|||(a) Literacy rates||
|Urban||||
|Male|82.6|<br>81.5<br>69.4|65.8|
|Female|72.7|<br>63.6<br>35.9|47.8|
|Both|78.1|<br>73.1<br>54.3|57.4|
|Rural||||
|Male|62.8|<br>56.1<br>38.0|40.8|
|Female|36.0|<br>25.7<br>8.6|18.0|
|Both|50.2|<br>41.5<br>23.2|29.7|
|Total||||
|Male|67.2|<br>63.9<br>44.6|46.9|
|Female|44.4|<br>35.3<br>14.4|24.8|
|Both|56.5|<br>50.0<br>30.2|36.2|
|||(b) Percentage rise, 1971-81||
|Urban||||
|Male|1.8|<br>4.1<br>7.6|7.5|
|Female|3.7|<br>13.8<br>18.9|13.5|
|Both|2.9|<br>7.3<br>10.1|9.5|
|Rural||||
|Male|14.0|<br>15.0<br>21.8|20.7|
|Female|20.8|<br>41.2<br>32.3|37.4|
|Both|16.2|<br>24.3<br>19.6|25.3|
|Total||||
|Male|11.4|<br>14.1<br>18.0|18.7|
|Female|17.5|<br>35.2<br>33.3|32.6|
|Both|13.7|<br>21.1<br>19.8|22.7|

Source: Census of India, 1981, Paper<sup>2 (1983), as quoted in R.M.</sup> Sundaram (1987).
of age or older. Also unsurprisingly, participation rates are much higher among men than among women. Our sample consists of more women than men, especially among the relatively younger group. This merely reflects the five-year lower minimum age for women to qualify for the benefit.

**Table 9: Descriptive Statistics on Labor Force Participation**

||_Observations, number_|_Mean_|_Standard deviation_|_Minimum_|_Maximum_|
|---|---|---|---|---|---|
|All|22,546|0.42|0.49|0|1|
|_Younger than 70_||||||
|All|12,644|0.53|0.50|0|1|
|Male|4,805|0.79|0.41|0|1|
|Female|7,839|0.38|0.48|0|1|
|_70 or older_||||||
|All|9,902|0.28|0.45|0|1|
|Men|4,686|0.44|0.50|0|1|
|Women|5,216|0.13|0.34|0|1|

Globally, with respect to the treatment variable, 26 percent of the potential beneficiaries live in households that receive the Colombia Mayor benefit (table 10). Among household members under 70 years of age, the rate is 18 percent, whereas, among household members 70 years of age or older, it is 37 percent. These rates are fairly consistent between men and women.

**Table 10: Descriptive Statistics on Receipt of the Colombia Mayor Benefit**

|_Laborforceparticipation_|_Observations, number_|_Mean_|_Standard deviation_|_Minimum_|_Maximum_|
|---|---|---|---|---|---|
|All|22,546|0.26|0.44|0|1|
|_Younger than 70_||||||
|All|12,644|0.18|0.38|0|1|
|Male|4,805|0.17|0.37|0|1|
|Female|7,839|0.18|0.39|0|1|
|_70 or older_||||||
|All|9,902|0.37|0.48|0|1|
|Men|4,686|0.36|0.48|0|1|
|Women|5,216|0.39|0.49|0|1|

For our control variables, we present numbers only for the whole sample (table 11). A few observations are lost because of missing values in the education-related variables. Most of our observations are in urban areas outside the 14 major cities (59 percent), followed by individuals living in rural settings (32 percent), which leaves a remainder of less than 9 percent who reside in one of Colombia’s major cities. This low number mostly reflects the lower incidence of poverty in the big cities, but also partially arises because of the stratification of the sample. The average potential beneficiary is around 68 years old, and 58 percent are women (mainly because of the lower eligibility 24
# **Table 17 Mean amount of annual capital top-ups received by LIFEMOD population at age 65 with minimum pension replacement target of 33% of male full-time earnings**

|________________|__________________|Mean(£)|
|---|---|---|
|ALL LIFEMOD|Own<br>contributions|9585.3|
||Joint<br>contributions|5750.0|
|MEN|Own<br>contributions|2313.8|
||Joint contributions|4110.0|
||Own|16085.1|
|WOMEN|contributions||
||Joint contributions|7216.0|

The number of people aged 65 in 1985 was about 561,000. This allows us to estimate the cost of lump-sum capital top-ups for the UK population reaching age 65 in 1985; for a funded pension system based on individual contributions of 15% of earnings and a minimum pension target of 33% of average male full-time earnings, the cost is £5.4 billion, and for joint contributions the cost is £3.2 billion. This compares with the actual cost of the public retirement pension in the UK in 1985 of £15.7 billion and a gross national product of £305 billion. These capital top-ups would have required an increase in income tax of between 3 and 5 per cent.

# _iii) Hybrid pension systems_

In practice, hybrid pension systems are likely to be rather more complex than simply a lump-sum addition at retirement to personal funded pensions. Below we present the results of a series of simulations which investigate the effect of combining public pay-as-you-go and private defined contribution pension systems in a number of different ways. For the central analyses of this paper we have adopted i=3%, dY=1.5% as the most plausible assumptions, and when these rates are applied to the income streams of the LIFEMOD population, they produce the replacement rates shown in 57
<!-- Start of picture text --> 4<br>3<br>2<br>4 a<br><= 4 3 = Mobile Services<br>& 2 = Leased Lines<br>1 | ] = Internet Services<br>4 PERT 12005 2008 2010 2012 2018005 2008 2010 2012 2016 aie<br>3<br>2<br>1<br>2005 2008 2010 2012 2015<br><!-- End of picture text -->

Competition Rank (4=Monopoly; 1=Fully Competitive)
# **1. Introduction**

In recent years, learning outcomes have gained increasing importance in the policy debate on basic education in India. Recent findings reveal that although about 93 percent of Indian children in age group 6-14 years are in school, learning achievements are low. According to the ASER survey, 67 percent of children in grades 3 to 5 cannot read a simple text (ASER, 2005-2006). The NCERT (2006) baseline surveys across Indian states find average scores between 40 and 60 percent on curriculum based math and language tests. The problem of poor quality of outcome is not a problem of India alone or of education sector alone. A number of developing countries have a dismal record on the delivery of basic services like education, health and sanitation despite the fact that governments as well as donor agencies have channeled significant resources into these services (World Development Report, 2004).

Poor learning in schools may be, in part, due to high absence rates among teachers. A view that has gained consensus is that the mechanisms of accountability in public service delivery are often weak resulting in dysfunctional services. School teachers and health workers, among other public workers, have high rates of absenteeism in many countries. Chaudhury et. al. (2006) document provider absence in schools in several developing countries including India. Absence ranges from 11 to 27 percent among primary school teachers.

Interventions that provide physical resources alone are not enough to improve outcomes if workers delivering the service do not perform as expected. With the aim of increasing the accountability of public workers, various Indian states have decentralized control over local public services to local communities. The _Sarva shiksha abhiyan_ which is a nation wide government scheme initiated in 2001 to universalize quality education envisages increasing accountability of schools to the community through greater involvement of village education committees and parent-teacher associations. Nevertheless, high teacher absence rates recorded in recent studies confirm that teachers continue to have low levels of accountability and motivation.

The lack of accountability may be partly attributed to the fact that the communities are largely uninformed about the controls that have been devolved to them, as found in recent surveys. This study is designed to carry out a randomized evaluation of an information campaign that provided information to communities about their roles and responsibilities in school management. It covers three Indian states, Karnataka (KA), Madhya Pradesh (MP) and Uttar Pradesh (UP).

This paper presents findings from the study’s baseline surveys in 2006 on students’ learning achievement, teachers’ effort and community participation. The results from the impact evaluation of the information campaign are reported in a separate paper (Pandey et. al., 2008).

We present learning achievement in the context of the minimum level of learning outlined by government of India. We report on the gain in achievement across grade 2
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1.28 Training and employment systems are linked in several ways. For example, the product of the training system, skilled persons (12.0), is used by the employment system. Labor markets (13.0) or employment mechanisms in the enterprise mediate this flow between the training and employment systems. The employment system sends demand signals (14.0) to the labor force (3.0). The labor force also receives supply signals (15.0) related to training places from the training system. The moel includes, in addition, institutional linkages (7.0) between the two systems. These may come in various forms ranging from advisory committees of employers on training curricula to formal contracts for training services. The equilibrium of the skills development process is maintained by the feedback mechanisms on employwent, which are used to modify policy, and by demand and supply signals (14.0, 15.0).

1.29 The connecting linkages between the three systems play a vital role in the efficiency of skills development. The internal efficiency of VET, for example, is shaped by institutional policy and management within the training system; these determine how a training institution uses inputs of information and resources to produce skilled persons. As a consequence, the effectiveness of institutional policy and management will depend in part on the nature of externally determined training policies and resources (9.0) furnished by the political and economic system (2.0), the demand signals (14.0) received, and the institutional linkages (11.0) in place. If training policies are unclear or resources inadequate, or information flows and linkages weak or ineffective, the internal efficiency of the training system will be threatened.

1.30 By the same token, the external efficiency of VET will be influenced by management in the employment system and its determination of how enterprises will use skilled labor and other resources along with technology in the production process. The effectiveness of management in this task will be influenced by externally determined economic policies and resources (10.0), non-governmental resource flows (i.e., revenue to the firm) (17.0), supply signals received through the labor market (13.0) and other formal and informal linkages between production and training (11.0, 16.0, 14.0) in signaling relative skills scarcities and in guiding the orientation and design of training systems.

# METHODOLOGY AND DATA

1.31 The taxonomy was used to select a sample of 121 of the 213 industry VET components in Bank-assisted investment projects financed between FY63 and FY86. These were chosen to be representative across country income levels, the four selected training modes and World Bank regions. 1/ The conceptual model was used as the basis for

1/ A detailed discu3sion of the methodology may be found in Annex I.
## **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 --> _Source_ : Authors using the data from Rozee.pk.

12
Roland-Holst David and Ferran Sancho. (1995). “Modeling Prices in SAM Structure”. The Review of Economics and Statistics. xx (x), 361-371.

Whalley and Hillaire. (1987). “A Microconsistent Data Set for Canada for Use in Regional General Equilibrium Policy Analysis”. No. 33, 327-343.

The World Bank (1996) “Cameroon: Country Assistance Strategy”. Report No. 12275-CM. The World Bank, Washington DC.

The World Bank (1998) “Cameroon: Country Assistance Strategy Progress Report”. IDA/R199814, The World Bank, Washington DC.

The World Bank (2000a) “Cameroon: Country Assistance Strategy Progress Report”. IDA/R2000-95, The World Bank, Washington DC.

The World Bank (2000b) “Cameroon: Preliminary Document on the Enhanced Initiative for Heavily Indebted Poor Countries (HIPC)”, IDA/R2000-96. The World Bank, Washington DC.

The World Bank (2000c) “Cameroon HIPC Debt Initiative: President’s Memorandum and Recommendation and Decision Point Document”, IDA/R2000-168. The World Bank, Washington DC.

The World Bank (2002) “World Development Indicators.” The World Bank, Washington DC.

Thorbecke, Erik (1990). "The Social Accounting Matrix and Consistency-Type Planning Models." in G. Pyatt and J. I. Round (1990) 33
(2) estimates equation (3), using the aggregate measure of depth. Columns (3) and (4) repeat the estimations including the spatial exporter controls.

Table 3: Third-country effects of RTAs

||(1)|(2)<br>Export pa|(3)<br>rticipation|(4)|(5)|(6)<br>Expor|(7)<br>t entry|(8)|
|---|---|---|---|---|---|---|---|---|
|Exp Other...(t-1)|||||||||
|... RTA|0.030***|0.022***|0.015***|0.009***|0.013***|0.009***|0.007***|0.005***|
||(0.001)|(0.001)|(0.000)|(0.001)|(0.000)|(0.000)|(0.000)|(0.000)|
|... Depth||0.020***||0.015***||0.008***||0.006***|
|||(0.002)||(0.002)||(0.001)||(0.001)|
|... Border|||0.060***|0.059***|||0.022***|0.021***|
||||(0.002)|(0.002)|||(0.001)|(0.001)|
|... Language|||0.006***|0.007***|||0.004***|0.004***|
||||(0.000)|(0.000)|||(0.000)|(0.000)|
|... Colony|||-0.017***|-0.016***|||-0.006***|-0.006***|
||||(0.001)|(0.001)|||(0.001)|(0.001)|
|Observations|20,797,980|20,797,980|20,797,980|20,797,980|20,694,604|20,694,604|20,694,604|20,694,604|
|R-squared|0.462|0.463|0.466|0.466|0.178|0.178|0.179|0.179|
|Firm-year FE|YES|YES|YES|YES|YES|YES|YES|YES|
|Dest-year FE|YES|YES|YES|YES|YES|YES|YES|YES|
|Firm-dest FE|YES|YES|YES|YES|YES|YES|YES|YES|

Robust standard errors, clustered at the firm level, are in parentheses. The dependent variable _yij,t_ is a dummy variable equal to 1 if firm _i_ exported (or started exporting) to country _j_ in year _t_ . *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1 Results in column (1) show that firms are more likely to export to a country if in the previous year they exported to a destination’s RTA partner. In other words, an RTA between two countries makes it more likely for Costa Rican firms to export to both countries if they have previously exported to one of the two. The probability of exporting increases by 3 percentage points if the firm previously exported to a country that has an RTA with the destination country. This provides evidence that on net RTAs have a positive spillover effect on non-member firms operating in one of the RTA markets.

This positive spillover effect is larger for deeper agreements — in terms of the number of strictly enforceable provisions included — as shown by the positive coefficient on the interaction term in column (2). Deep trade agreements increase the probability of export participation for firms with previous export experience in one of the member states by 2.1 percentage points, additional to the 2.2 percentage points that is estimated for shallow agreements.<sup>21</sup> The results are robust to the inclusion the extended gravity variables: controlling for previous export experience to countries that share a border, a common language, or a common colonizer with the destination country. The observed positive impact of extended border and language variables are consistent with existing studies. The

> 21These magnitudes are for the deepest and shallowest RTAs between current and past destination markets.

11