rafmacalaba/datause-encoder-data huggingface dataset:
are identified using the GTI index, which is based on ISCO-08 task statements (described in section 3.A). For the purpose of this discussion, occupations are classified into three categories: Zero GTI (occupations without any green tasks), Low GTI (occupations with less than 30% of their tasks being green), and High GTI (occupations with 30% or more of their tasks being green). It is important to note that, due to the inherent biases of the OV data, only high-skilled occupations with at least 30 job posts in the database are considered for application #2.<sup>62</sup> Project management skills are particularly crucial for high-skilled occupations that involve green tasks. On average, 60% of job advertisements for high GTI occupations require at least one project management skill, which is 10% higher compared to occupations without green tasks (Figure 4.3). Specifically, jobs in high GTI occupations typically require an average of 2.19 management skills. Examples of in-demand project management skills for these occupations include quality assurance and control, planning, people development, and compliance management (Table 4.1). There is a high demand for these skills in green occupations compared to non-green occupations. For instance, the skill of quality assurance appears 4.2 times more frequently in green jobs than in non-green jobs.

Similarly, jobs in high GTI occupations are more likely to require cognitive skills and specific field expertise. Table 4.1 illustrates the relative importance of these skills in high GTI occupations compared to occupations without green tasks (column 5). Skills such as fiber optics, research, occupational health and safety, and environmental management are particularly relevant to jobs that involve green tasks.

**Figure 4.3. Average share of posts with at least one skill demanded in a skill group, by GTI index**

<!-- Start of picture text --> 0 10 20 30 40 50 60<br>Cognitive (analytical)<br>Social<br>Character<br>Writing<br>Customer<br>Project management and business<br>People management<br>Financial<br>Computer (basic)<br>Software and information technology<br>Foreign language<br>Field of study and industry knowledge<br>Zero GTI Low GTI <30% High GTI +30%<br><!-- End of picture text --> _Notes_ : analysis restricted to high-skilled occupations with at least 30 posts. For each occupation, we calculate the percentage of posts that required at least one skill in each of the skills groups. Then, we calculate the average of this percentage by the three categories: Zero GTI, Low GTI, and High GTI.

**Table 4.1. Top 20 skills demanded in high GTI occupations**

|**Skill ranking**<br>**Skill**|
|---|

> 62 See Granata, Posadas, Testaverde (2021) for a discussion on the biases of Indonesia’s online vacancy data.

30
# **6 Discussion and Conclusion**

Three key insights emerge from this study that have important implications for policy makers and future research. Firstly, there is clearly a strong correlation between people’s willingness (or lack thereof) to get vaccinated within the same household. This pattern is evident in all three surveys. As such, in many instances it would seem to be appropriate to consider the attitudes towards vaccines of household members as a collective unit as opposed to a group of individuals. Similar points have been made about other topics, such as political preferences whereby the correlation of attitudes within households tends to be extremely high (e.g., see Zuckerman and Kotler-Berkowitz, 1998).

Secondly, even though household members tend to share similar attitudes towards vaccines, communicating accurate information about the benefits of getting vaccinated can counter intra-household dynamics that undermine acceptance. The strong correlation about attitudes within households may at face value be a cause of concern for policy makers because household members that are unwilling to get vaccinated may not change their minds regardless of the content of communication campaigns. This partly underpinned our third hypothesis that suggested the elasticity of attitudes towards COVID-19 vaccines from the treatments would be lower among respondents in these “hostile” households. However, the opposite was the case. The experimental results show there is great value in communicating the benefits of COVID-19 vaccinations to members of households that were not accepting of vaccines. Respondents in these households were more likely to respond positively to the treatments than those in households who were more supportive of vaccination in the first place. In fact, the treatments led to not only the respondents being more willing to get vaccinated, but there is some evidence of a second-round effect whereby they were more likely to encourage others in their household to get vaccinated. In other words, communicating accurate information may create a virtuous cycle whereby both recipients of the information as well as others in previously “hostile” households become more willing to get vaccinated. Collectively, these first two insights suggest that there would be considerable value in 38
# **Table S8. Estimated total number of households that report income loss due to COVID-19** **<u>pandemic and average household-level incidence of income loss, by source</u>**

||Any type of<br>income loss|Farm<br>income<br>reduced|Business<br>income<br>reduced|Wage<br>income<br>reduced|Remittances<br>reduced|Other income<br>sources<br>reduced|
|---|---|---|---|---|---|---|
|Total|748,720,384|223,353,008|174,818,736|67,815,688|44,469,788|38,765,196|
||(4,869,609)|(4,087,100)|(2,156,618)|(2,204,293)|(1,403,495)|(1,964,309)|
|Mean|0.773|0.637|0.856|0.527|0.707|0.522|
||(0.009)|(0.012)|(0.011)|(0.020)|(0.026)|(0.027)|
|Observations|9,153|5,624|3,849|3,447|1,687|1,574|

_Note_ : Each column reports the estimated total number of households that report loss of income and the average household-level incidence of reporting a loss of income. The estimates are based on the pooled data from 4 countries. Reporting loss of income from a given source is conditional on receiving income from that source prior to the COVID19 pandemic. Data are only from the first phone survey round in each country. Standard errors on the estimates are in parenthesis.

35
- Pop-Eleches, C., H. Thirumurthy, J. P. Habyarimana, J. G. Zivin, M. P. Goldestein, D. de Walque, L. MacKeen, J. Haberer, S. Kimaiyo, J. Sidle, D. Ngare, and D. R. Bangsberg (2011). Mobile phone technologies improve adherence to antiretroviral treatment in a resource-limited setting: a randomized controlled trial of text message reminders. _AIDS 25_ (6), 825–834.

- Torgler, B. (2004). Moral suasion: An alternative tax policy strategy? Evidence from a controlled field experiment in Switzerland. _Economics of Governance 5_ (3), 235–253.

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recursive model; Techiman price3 would not<sup>be endogenous although Bolgatanga</sup> maize prices would be simultaneously determined with millet and sorghum.

The underlying assumption on this market structure<sup>can be tested in the</sup> analysis. The test for market segmentation offered<sup>by Ravallion (1986) will</sup> indicate not only the degree to which<sup>local price movements are integrated with</sup> those in the exporting region, but whether there<sup>are seasonal patterns in the</sup> link. Similarly, the model can also directly<sup>test the assumption that local</sup> demand conditions do not influence the market<sup>clearing price. In the present</sup> study these conditions are indicated by the prices<sup>of millet and sorghum as well</sup> as indirectly through seasonal dummy variables.

The data in this study are monthly wholesale<sup>prices from regional offices</sup> of the Ministry of Agriculture in Bolgatanga<sup>(Upper East) and Sunyani (Brong-</sup> Ahafo). Techiman, on the main north-south road<sup>in Brong-Ahafo, is taken as the</sup> reference market for maize. The data cover<sup>the period from 1977 to 1990.1</sup> Given the high level of inflation in the period covered,<sup>all prices are deflated</sup> using a CPI deflator. Some gaps exist in the<sup>data around 1983 as drought and a</sup> severe fiscal crisis contributed to a breakdown<sup>in administration capacity in</sup> that year. Wherever there is such a gap, of course,<sup>the lag structure requires</sup> that a number of periods for which information<sup>is available should also be</sup> excluded. Apart from a loss of information, however, this should not directly affect the estimation technique. Moreover,<sup>to test the sensitivity of results,</sup> alternative specifications were run in which all observations from the drought period covering 18 u&onths in 1983 and 1984 were excluded. No change<sup>in any of</sup> the tests was observed in such explorations. The<sup>conclusions of the study also</sup> Greater detail is available in Alderman and Shively<sup>(1991).</sup>
significantly higher in language and math tests in the early years of primary school compared to their peers who enrolled only in playgroup or kindergarten. In addition to the sequence of early education service participation, we found that the timing of entry into playgroups and kindergartens was an important predictor of children’s subsequent learning outcomes. Children who enrolled in playgroup at age 3-4 followed by kindergarten at age 5-6 performed significantly higher in language and math tests in primary school than their peers who enrolled in other early education pathways. Finally, over and above the sequence and timing, we found that duration of early education was a significant predictor of children’s math test scores in primary school, as those who enrolled in at least two years of playgroup and kindergarten scored significantly better than their peers who enrolled for shorter periods of time.<sup>5</sup>

# **8. Costs of various early education pathways**

The Indonesian government is currently weighing alternatives for investing smartly in early childhood education to ensure that all young children enter primary school ready to learn.

In this section, we estimate the cost of various early education pathways to inform public resource allocation decisions for early childhood education in Indonesia. We do not have causal estimates of ECED pathways on primary school test scores. Thus we cannot calculate actual estimates of the different pathways. Despite this, we feel that our controls and robustness checks validate the presentation of these estimates as cost-effectiveness estimates.<sup>6</sup> We do so by calculating the marginal effect at representative values (MER) of the ECED timing variable at discrete values of ECED duration (shown in Tables 5c). We used the average of the language and math assessments for our effectiveness measure as these two tests were aligned with what children were expected to know in the early years of primary school.

The cost of each early education pathway was drawn from the Indonesia ECED Project evaluation data (World Bank 2014) and the 2012 _Nomor Unik Pendidik Dan Tenaga Kepandidikan_

> 5 As a robustness check, we re-estimated the model in Table 5c using a sub-sample of children (N=2,874) for whom we have child development measures at age 4 using the Early Development Instrument (EDI). For this sub-group analysis, we included EDI scores at age 4 to control for children’s early childhood developmental outcomes. We find similar results: compared to their peers who enrolled in other early education pathways, children who enrolled in playgroup at age 3-4 followed by kindergarten at age 5-6 performing significantly better in language and math tests in primary schools. The results of this sub-sample analysis are available upon request.

> 6 Our analysis based on the sub-sample of children for whom we have data on development outcomes at age 4 gives us qualitatively very similar results. (See footnote 6) However, we choose to be conservative in our interpretation and present the cost-effectiveness results as _indicative_ cost-effectiveness.

19
After specifying the hypothesized relationship to be econometrically tested, our second goal was to construct a MENA database on variables to be used as proxies for the 3Ps and estimate it. While some indices that could reasonably be used as proxies were readily available for protection and participation, this was not the case for provision, which is supposed to represent a set of a meaningfully broad basket of economic and social benefits to citizens, including infrastructure, health, and education services. Faced with the difficulty of getting hold of these data and testing our methodology, we used telecommunication and Internet services as a "proxy basket" for these benefits. We introduced control variables to mitigate any potential omitted variable bias. We also built a similar database for OECD countries that we use as a benchmark, in particular, to evaluate the relative "quality" of the social contract in MENA countries.

Our third objective was to propose a method for evaluating the quality of the social contract in MENA countries and analyze how digitalization impacts it. To do so, we focused on the relationship between provision and participation and found that it is negative, significant, and robust suggesting that the benefits provided to citizens in the form of improved delivery of telecommunication and Internet services came at the (social) cost of impaired participation.<sup>59</sup> This characteristic of the social contract could be seen as one of the root causes of the social unrest that MENA countries have experienced in history, in particular, over the past two decades. We found that digitalization had a three-year lagged positive effect on the (participation) quality of the social contract and that this effect is inversely U-shaped. This relationship suggests that in-depth structural institutional improvements in MENA countries are called for before the quality of their social contract can reach levels comparable to those of OECD countries.

<mark>In a recent Economic Research Forum column, Arezki et Ghanem (2018) advocate for a digital moonshot for the MENA region as a new groundwork upon which a new economy will likely emerge. Their idea is to unite people/governments in the region behind a common goal (digital transformation) and transform how governments, firms, financial institutions and civil societies interact or conduct business and help to ensure that millions of the region's young people can find the good jobs they deserve. According to these authors, the digital moonshot would involve a collective commitment to achieve parity with advanced economies in information and communication technology - meaning that MENA could seek to match or even</mark>

> 59 This result is in line with Desai et al.'s (2009) "authoritarian bargain" view of the social contract documented in section 2 and the "populist" view discussed by Hinnebusch (2020).

37
This paper uses data from the 2004 Quantitative Baseline Survey of the Tea sector to assess the potential impact of privatization of tea estates. The analysis is framed within the logic of causal inference. This entails a normalized comparison of outcomes to account for household heterogeneity in terms of observable and non-observable determinants of the outcomes of interest. These outcomes relate to productivity. Three main findings emerge from this comparison. Productivity outcomes such as yield, time taken to carry leaves to the collection point, and fertilizer use are generally better in the private sector than in the public sector. Also, male-headed households out perform female-headed households along all dimensions consider here. Finally, in a welfare comparison between the tea and non-tea sectors, the former tend to be better off than the latter.

# **References**

- Brambilla, Irene and Porto, Guido G.  2005.  Farm Productivity and Market Structure: Evidence from Cotton Reforms in Zambia.  Discussion Paper No.919.  New Haven: Economic Growth Center (Yale University).

- Dabalen, Andrew, Paternostro, Stefano and Gaëlle, Pierre.  2004.  The Returns to Participation in the Nonfarm Sector in Rural Rwanda.  World Bank Policy Research Working Paper No. 3462.

- Diop, Ndiame, Brenton, Paul and Asarkaya, Yakup.  2005.  Trade Costs, Export Development and Poverty in Rwanda.  World Bank Policy Research Paper No. 3784.

- Essama-Nssah, B.  2006.  Propensity Score Matching and Policy Impact Analysis: A Demonstration in EViews.  World Bank Policy Research Working Paper No. 3877.

- Holland, Paul W.  1986.  Statistics and Causal Inference.  Journal of the American Statistical Association, Vol. 81, No. 396: 945-960.

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Table 8: Results of Achievement Equation with Student and Peer Group Characteristics Held Constant

|Variable|Public|School T_Ue<br>Private 0|Private F|
|---|---|---|---|
|Intercept|6.64***<br>(1.25)|2.45<br>(3.30)|6.46*<br>(3.26)|
|Pretest|0.36***<br>(0.03)|0.35***<br>(0.06)|0.67***<br>(0.05)|
|Mother's education|-0.03|-0.12|0.10|
||(0.03)|(0.09)|(0.11)|
|Age in months|-0.01*<br>(0.01)|0.01<br>(0.02)|-0.04<br>(0.02)|
|Block house|-0.07<br>(0.19)|-0.16<br>(0.54)|-0.16<br>(0.69)|
|Female|-0.53**<br>(0.15)|-1.18***<br>(0.35)|0.03<br>(0.37)|
|Full-time working|0.13|0.99*|-0.18|
|<br>mother|(0.21)|(0.42)|(0.41)|
|Father's occupation||||
|<br>White-collar|-0.27|-0.46|0.67|
||(0.25)|(0.71)|(0.95)|
|Agricultural|-0.18<br>(0.21)|0.12<br>(0.74)|0.37<br>(0.83)|
|Unclassified|-0.32|0.29|0.87|
||(0.30)|(0.68)|(0.98)|
|Commuting time||||
|<br>Ab.ut 30 min.|-0.02|0.50|-0.30|
||(0.17)|(0.41)|(0.44)|
|More than 45 min.|-0.63*|-2.25*|-1.75|
||(0.27)|(0.87)|(0.93)|
|No response|0.77|-2.24|1.39|
||(0.91)|(3.40)|(2.01)|
Type of payment Description 9. Payments for the use Payments for hunting wild animals consist of a permit per of terrestrial biological animal killed or day spent hunting, and a penalty for resources infractions. Payrnents are determined in relation to the minimum wage _(e.g.,_ the license to kill a beaver equals 0.20.6 * the minimum wage, while for a bear it equals 3-6 * the minimum wage). For plants and animals listed as protected species in the Red Book, no regular licenses can be granted but fines are applicable to punish hunting or collection. These fines are set as a multiple of the minimum wage as well (e.g. for plants, they range from 0.2 to 300 times the minimum wage). Finally, small entrance fees are sometimes charged for the right to visit national parks.

Sources: Arthur Andersen (1998); GOR (1996); IFEI (1998); Kasyanov (2001); Mikheva and Sheingauz (1999); Roskoshnaya (2000); Sagers _et al._ (1995); Shevchuk (1999); Titova (2000).

# **Oil and Natural Gas**

# **Oil and Natural Gas in the Russian Economy**

2.2 The energy sector, in particular oil and gas, is central to the Russian economy. Depending on economic conditions, oil and gas **earn** 20-40% of consolidated budget revenues and 30-40% of foreign exchange earnings. In 1999, the oil and gas industry employed 618,000 people, including 416,000 in oil extraction, 117,000 in oil processing, and 85,000 in gas extraction. It is thought that the relative recovery of the Russian economy in 1999 and 2000 is owed to the comparative advantage of local production following the depreciation of the ruble, and to the soaring crude oil prices on world markets. Despite years of adjustment, energy is still much cheaper in Russia than abroad, which distorts resource allocation by subsidizing domestic industry (IFEI 2000). For example, domestic oil refining is in some cases value-subtracting since its actual revenues are lower than the potential exports of crude oil.

# **Tax Regime in the Upstream Oil Sector**

2.3 Taxation has been identified as one of the main issues deterring investments in the Russian oil sector. "The Russian system of taxation is generally believed to be one of the most complicated, burdensome and unpredictable in the world" (Arthur Andersen 1998, 5). The Russian system of upstream oil taxation consists of two regimes: the regime for licensed oil and the regime for production sharing agreements. By far the largest share of oil production is under the former regime, although badly needed foreign investments are overwhelmingly in favor of the latter.
# _LIST OF TABLES_

|_Tabk 1_|_Behavioral Equations and Estimated Coefficients in MULTIMOD_.<br>_.................._<br>_8_|
|---|---|
|_Table 2_|_Classiflcadon of Equations in MULT7MOD_<br>_................................... 10_|
|_Table 3_|_Effects of Four Percent Increase in the U.S. Money Supply in MULTIMOD ............_<br>_15_|
|_Table 4_|_Effects of a Four Percent One-7Time Increase in the U.S. Money Supply_<br>_in the Taylor Multi-County Rational ExpectationMode. .17_|
|_Table 5_|_Effects of a Five-Year Sustained Increase in Real Government Expenditures by_<br>_One Percent of Real GNP, on the Economy of the Shock Originating Regions .24_|
|_Table 6_|_Simnulation Effects in the Second Year of an Increase in the US. Govemment_<br>_Expenditures of One Percent of GNP .28_|
|_Table 7_|_Effects of Four Percent Sustained Increase in Money Base Target on the Economy_<br>_of ShockOriginatingRegions.........._<br>_.......29_|
|_Tabk 8_|_The Impact of Four Percent Increase in the US. Money Supply in_<br>_MULTIMOD (MUL77), Taylor, andLiveipool(LIIVPL) Model.32_|
|_Table 9_|_The Effects of a Five-Year Sustained Increase of $20 Billion i Fiancial Flows_<br>_toDeveloping Countries.39_|
|_Table 10_|_Effects of a Five-Year Sustained Increase in Fnancial Flows on output and_<br>_DomesticAbsorption of the Industialized and Developing Countries ................._<br>_40_|
|_Table 11_|_$60 Billion Reduction in the Stock of Developing Countries Debt ...................._<br>_43_|
|_Table12_|_The Impact of 20 Percent Sustained Increase In Oil Prices ........................._<br>_46_|
|_Table 13_|_Zelner-Peck Symmetry and Linear Measures for MULTIMOD ....................._<br>_51_|
|_Table 14_|_Pefurbation of the Parameters of the US. Money Demand Equations_<br>_and the Elasticity Responses of the Following Variables ..........................._<br>_62_|
|_Table 15_|_Muldplier Elasticity Responses to US. Govemment Pentubation ..................._<br>_65_|
|_Table 16_|_Muldplier Elasticity Responses to US. Monetary Base, 1% Pernbation .............._<br>_67_|

- _iii_ -
# **II. Future Directions for Poverty Measurements**

There are two large issues in the future directions for poverty measurement: expanding regional measures and broadening the concept of poverty measured. We discuss each in turn.

# _A)_ **_Regional comparisons_**

As we have seen even, coming to consensus on estimates by urban and rural areas of provinces was difficult. However the process of decentralization and of expenditure targeting already demand more, and more frequent, data. For expenditure allocation decision making, both for targeted safety net programs and for the fiscal decentralization of general revenues the "Daerah Tingkat II" (level two) (or kabupaten/kota) will be the relevant jurisdiction. There are certainly large variations in poverty within provinces. As we move toward district level of aggregation there will be two major problems:

- _Regionally comparable prices._ As seen above, the lack of directly comparable price indices leads to enormous difficulties. Even now the best that can be done for non-food prices is to assume they are the same in an entire province as in the CPI surveyed city. There are efforts underway to create meaningful rural price indices.

- _Sample sizes._ Even with 65,000 observations, the imprecision of estimating poverty levels for over 300 kabupaten/kota will raise concerns, particularly if these estimates actually become part of the expenditure allocation process, in

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