rafmacalaba/datause-encoder-data huggingface dataset:
aspirations, and many of the existing ones employ such diverse methodologies that meaningful comparisons become challenging. As a result, there is a lack of comprehensive data regarding the aspirations of the general population, especially among young individuals. A key contributing factor to this data gap is the absence of standardized instruments and guidelines for measuring youth aspirations. Incorporating an aspirations module into household surveys can help capture aspirations over time and establish connections with household characteristics. Collecting individual-level data within nationally representative multi-topic household surveys enables the identification of various attributes concerning young people and their families. This, in turn, enriches our comprehension of how aspirations impact the future prospects of youth.

However, it is crucial to acknowledge that the measurement of youth aspirations requires ongoing research and refinement. Rigorous testing of assessment tools and their adaptation to local contexts are essential steps, as they can incentivize countries to comprehensively assess the state of youth aspirations. This comprehensive understanding is vital for elucidating how aspirations influence future outcomes, including how they may evolve with age, respond to external shocks, and adapt in light of available coping mechanisms. Furthermore, delving into the connections between current youth aspirations and family-related factors, such as the educational achievements of their parents or the socio-economic background of the household, can significantly contribute to a more nuanced policy discourse aimed at aligning aspirations with viable job opportunities.

# **7. References**

Akosah-Twumasi, P. et al., 2018. A Systematic Review of Factors That Influence Youths Career Choices—the Role of Culture.. _Front. Educ,_ p. 3:58..

Appadurai, A., 2004. The Capacity to Aspire: Culture and the Terms of Recognition. In: _Culture and Public Action._ Washington: World Bank, pp. 59-84.

Bandura, A., Barbaranelli, C., Caprara, G. V. & Pastorelli, C., 2001. Self-efficacy beliefs as shapers of children's aspirations and career trajectories. _Child Development ,_ p. 72(1): 187–206..

Bastianon, C. D., 2019. Youth Migration Aspirations in Georgia and Moldova. _Migration Letters,_ 16(1), pp. 105-121.

Beaman, L., Duflo, E., Pande , R. & Topalova, P., 2012. Female Leadership Raises Aspirations and Educational Attainment for Girls: A Policy Experiment in India. _Science,_ p. 335(6068): 582– 586.

Beaman, L., Duflo, E., Pande, R. & Topalova, P., 2012. Female Leadership Raises Aspirations and Educational Attainment for Girls: A Policy Experiment in India.. _Science,_ p. 582–586..

Bernard, T. & Taffesse, A., 2014. Aspirations: An Approach to Measurement with Validation Using Ethiopian Data. _Journal of African Economies,_ p. 23(2): 189–224.

26
- 1) The extent of women’s support for women with children under 12 years working for pay outside the home (reflecting the underestimates among men and women of the level of women’s support found in the first survey)

- 2) The extent of men’s support for childcare being shared among husbands and wives (reflecting the underestimates among men and women of the level of men’s support in the first survey); and

- 3) The extent of older women’s (from the respondents’ mothers’ generation) support for women with children working for pay outside the home (reflecting the concern about mothers’ and mothers-in-law’s support found in the first survey).<sup>21</sup>

The control group received no such information. Figure A.2 in the appendix shows the format in which this information was presented to each treatment group.

Our main outcome measure is respondents’ choices as to whether to receive payment for their participation in the form of an online career mentoring course for women or an online shopping voucher of equal value. Respondents were told that about one in every three participants in the survey would be randomly selected to receive a reward for participating in the research project (and they would be told at the end of the survey whether they had been selected for the reward). They were then asked to indicate whether they would prefer to receive:

- Free access to an online career mentoring course for female participants or the wives of male respondents. The course provides practical career advice from HR professionals and was valued at Rp100,000 (USD6.50). It equips participants with the skills to create a CV, write a cover letter, prepare for a job interview, and create a LinkedIn profile; or

- a Rp100,000 convenience store shopping voucher.<sup>22</sup>

Choosing the career mentoring course is taken to indicate support for their own (for female respondents) or their wife’s (for male respondents) labor force participation. A comparison of this variable across the control and treatment groups provides an estimate of the interventions’ impacts.<sup>23</sup>

> 21In the first survey we did not collect information on the support of mothers or mothers-in-law for married women with children working outside the home. The information provided on norms in this domain is constructed from 2018 Indonesian World Values Survey data on the proportion of women aged 40 to 60 who disagree or strongly disagree with the statement “When a mother works for pay, the children suffer”. For more information on the World Values Survey, see Haerpfer et al. (2022).

> 22For information on the career mentoring course, see https://skillacademy.com/p/career-mentoringregular-bimbingan-untuk-dapat-kerja?courseType=SingleCourse. The shopping vouchers were redeemable at Indomaret and Alfamart stores which are ubiquitous throughout urban Indonesia.

> 23We also conducted a list experiment which generates an alternative outcome measure. At the end of the survey (just prior to the choice of reward), respondents were asked how many of the following statements they agreed with (in randomized order): a) The minimum wage should be kept at its current

11
<!-- Start of picture text --> 300<br>250 —] Marine<br>200 Lo @ Small Hydro<br>@ Biomass<br>— Solar<br>- ati I ea<br>100 hl<br>Don= es ~ w @ Wind<br>50 = -<br>o =<br>2004 2005 2006 2007 2008 2009 2010 2011<br><!-- End of picture text --> <!-- Start of picture text --> Developed “Developing<br>Solar<br>Biomass<br>na<br>Small Hydro<br>Geothermal<br>0 50 100 150 200<br><!-- End of picture text -->
# _Land Access_

Our review of the history of land reform and redistribution indicated that land access is governed principally by land allocations made by government officials and through inheritance. We see this in Table 1. In the Highland and Lowland regions, between 69 and 87 percent of parcels were obtained from local officials or through inheritance. In the Highlands, consistent with the Constitution, land received from local leaders is the primary means of acquiring land. Because the lowlands were dominated by sharecropping, there was less redistribution, as is particularly evident in SNNP where only 20% report receiving land from local leaders and where access through inheritance dominates.

In pastoral areas (Afar and Somali) most plots are acquired from local leaders or via inheritance but a considerable fraction (38 and 27 percent respectively) are acquired “without permission”. Where this has occurred, land acquisition and therefore fragmentation becomes partly endogenous. Given this feature, along with the fact that pastoralism, not sedentary agriculture, is the principal livelihood strategy in Afar and Somali, we exclude these two regions from our subsequent work.

Excluding Afar and Somali, just over 70 percent of parcels are acquired either from local leaders or through inheritance. Because land purchases were illegal, these were not asked about in rounds 1 and 2 but the relatively large number of ‘other’ acquisitions prompted follow-up work which revealed that some households were taking advantage of a loophole allowing land transactions if they include a built structure. The survey therefore added an explicit question regarding land purchases in round 3. A significant fraction of parcels, however, are rented in through cash or sharecropping or rented out. Households with fewer working age adults, often headed by widows and the elderly, lease out their land to those with the manpower and capital to farm it. Households renting 8
Eichengreen, B., and P. Gupta. 2016. “Managing Sudden Stops.” In Monetary Policy and Global Spillovers: Mechanisms, Effects and Policy Measures, edited by E. G. Mendoza, E. Pastén, and D. Saravia, 9-47. Santiago: Central Bank of Chile.

Eickmeier, S., and T. Ng. 2015. “How do US Credit Supply Shocks Propagate Internationally? A GVAR Approach.” European Economic Review 74: 128-145.

Federal Reserve Board. 1958. “Federal Reserve Bulletin.” October, Board of Governors of the Federal Reserve System, Washington, DC.

Feenstra, R. C., R. Inklaar, and M. P. Timmer. 2015. “The Next Generation of the Penn World Table.” American Economic Review 105(10): 3150-3182.

Ferrara, L., and C. Marsilli. 2019. “Nowcasting Global Economic Growth: A Factor-Augmented Mixed-Frequency Approach.” World Economy 42(3): 846-875.

Feyen, E., R. Letelier, I. Love, S. M. Maimbo, and R. Rocha. 2014. “The Impact of Funding Models and Foreign Bank Ownership on Bank Credit Growth.” Policy Research Working Paper 6783, World Bank, Washington, DC.

Forbes, K. J., and F. E. Warnock. 2012. “Capital Flow Waves: Surges, Stops, Flight, and Retrenchment.” Journal of International Economics 88(2): 235-251.

Fosu, A. K. 2013. “Impact of the Global Financial and Economic Crisis on Development: Whither Africa?” Journal of International Development 25(8): 1085-1104.

Francis, N., L. E. Jackson, and M. T. Owyang. 2018. “Countercyclical Policy and the Speed of Recovery after Recessions.” Journal of Money, Credit and Banking 50(4): 675-704.

Frankel, J. 2014. “China is Not Yet Number One.” VoxEU.org, May 9.

Freund, C. 2009. “The Trade Response to Global Downturns: Historical Evidence.” Policy Research Working Paper 5015, World Bank, Washington, DC.

Golinelli, R., and G. Parigi. 2014. “Tracking World Trade and GDP in Real Time.” International Journal of Forecasting 30(4): 847-862.

Graetz, G., and G. Michaels. 2017. “Is Modern Technology Responsible for Jobless Recoveries?” American Economic Review 107(5): 168-173.

Grjebine, T., U. Szczerbowicz, and F. Tripier. 2018. “Corporate Debt Structure and Economic Recoveries.” European Economic Review 101: 77-100.

Ha, J., M. A. Kose, and F. Ohnsorge, eds. 2019. Inflation in Emerging and Developing Economies: Evolution, Drivers, and Policies. Washington, DC: World Bank.

Hall, R. E. 1993. “Macro Theory and the Recession of 1990-1991.” American Economic Review 83(2): 275-279.

Hamilton, J. D. 2013. “Historical Oil Shocks.” In Routledge Handbook of Major Events in Economic History, edited by R. E. Parker and R. Whaples, 239-265. London: Routledge.

Hamilton, J. D. 2019. “Measuring Global Economic Activity.” Journal of Applied Econometrics, forthcoming.

Hamilton, J. D., E. S. Harris, J. Hatzius, and K. D. West. 2016. “The Equilibrium Real Funds Rate: Past, Present, and Future.” IMF Economic Review 64(4): 660-707.

Hansen, A. H. 1939. “Economic Progress and Declining Population Growth.” American Economic Review 29(1): 1-15.

26
The CGE model is based on a standard neoclassical dynamic general equilibrium model and the following subsections describe its main features. Given our focus on labor markets and dynamic structural trends, more detailed explanations are provided on the modeling of factor markets and growth.

_<u>Production</u>_ <u>. Output results from nested CES (Constant Elasticity of Substitution)</u> functions that, at the top level, combine intermediate and value added aggregates. At the second level, on the one hand, the intermediate aggregate is obtained combining all products in fixed proportions (Leontief structure), and, on the other hand, value added results by aggregating the primary factors. At this level, primary factors are a capitallabor bundle and aggregate land. Lower levels disaggregate capital and labor, and then labor into different categories. The full nesting structure is presented in the annex in Figure 4.

_<u>Income Distribution and Absorption</u>_ <u>. Labor income and capital revenues are allocated to</u> households according to a fixed coefficient distribution matrix derived from the original SAM. Notice that one of the main advantages of using the micro-module is to enrich, as described above, this rather crude macro distribution mechanism. Private consumption demand is obtained through maximization of household specific utility function following the Linear Expenditure System (LES). Private savings are a fixed proportion of income. Once the total value of private consumption is determined, government and investment demands<sup>9</sup> are disaggregated in sectoral demands according to fixed coefficient functions.

_<u>International Trade</u>_ <u>. The model assumes imperfect substitution among goods originating</u> in different geographical areas.<sup>10</sup> Imports demand results from a CES aggregation function of domestic and imported goods. Export supply is symmetrically modeled as a Constant Elasticity of Transformation (CET) function. Producers decide to allocate their output to domestic or foreign markets responding to relative prices. The assumptions of imperfect substitution and imperfect transformability grant a certain degree of autonomy of domestic prices with respect to foreign prices and prevent the model from generating corner solutions. This single country Brazilian model has been linked to a global CGE model by adding export demand functions so that the increased market access

> 9 Aggregate investment is set equal to aggregate savings, while aggregate government expenditures are exogenously fixed.

> 10 See Armington (1969) for details.

9
**Annex 3: Worker Approach—Monthly earnings by education level and industry (2007/08)**

|**Education**<br>**level**||**Government**<br>**Administration**<br>**(1)**|**Health**<br>**& Social**<br>**Relief**|**Education**<br>**&**<br>**Training**|**Private**<br>**Sector &**<br>**SOEs (2)**|**Agriculture**<br>**&**<br>**Agricultural**<br>**Services**|**Private/SOE to**<br>**Government**<br>**Administration**<br>**Pay Ratio**|**Government**<br>**Administration**<br>**to Agriculture**<br>**Pay Ratio**|
|---|---|---|---|---|---|---|---|---|
|**Some**<br>**primary**<br>**or below**|**Average monthly**<br>**earnings, '000 kip**|**509**|**421**|**916**|**1,052**|**551**|**2.1**|**0.9**|
||Std. deviation,<br>'000 kip|806|53|1,370|1,841|1,929|||
||<br># observations|23|4|10|330|456|||
||t|0.63|7.89|0.67|0.57|0.29|||
||p-value|0.27|0.00|0.26|0.28|0.39|||
|**Some**<br>**secondary**|**Average monthly**<br>**earnings, '000 kip**|**633**|**663**|**475**|**954**|**541**|**1.5**|**1.2**|
||Std. deviation,<br>'000 kip|524|91|285|1,423|901|||
||<br># observations|49|6|34|485|258|||
||t|1.21|7.28|1.67|0.67|0.60|||
||p-value|0.12|0.00|0.05|0.25|0.27|||
|**Some**|**Average monthly**|**613**|**539**|**588**|**872**|**597**|**1.4**|**1.0**|
|**vocational**|**earnings, '000 kip**||||||||
||Std. deviation,<br>'000 kip|391|308|346|747|667|||
||<br># observations|77|22|72|181|59|||
||t|1.57|1.75|1.70|1.17|0.89|||
||p-value|0.06|0.05|0.05|0.12|0.19|||
|**Some**|**Average monthly**|**845**|**857**|**621**|**1,328**|**689**|**1.6**|**1.2**|
|**higher**<br>**education**|**earnings, '000 kip**||||||||
||Std. deviation,<br>'000 kip|709|603|348|1,903|580|||
||<br># observations|59|7|42|113|15|||
||t|1.19|1.42|1.79|0.70|1.19|||
||p-value|0.12|0.10|0.04|0.24|0.13|||
|**All levels**|**Average monthly**<br>**earnings, '000 kip**|**672**|**608**|**598**|**1,007**|**557**|**1.5**|**1.2**|
||Std. deviation,<br>'000 kip|589|363|494|1,531|1,518|||
||<br># observations|208|39|158|1,109|788|||
||t|1.14|1.67|1.21|0.66|0.37|||
||p-value|0.13|0.05|0.11|0.26|0.36|||

**Source:** World Bank analysis of Lao Expenditure and Consumption Survey (LECS) data **Notes:** (1) Government Administration excludes Defense, and Party, Mass Organizations, and Professional Organizations; (2) Excludes Agriculture and Agricultural Services

Note on data analysis: Some respondents reported working in more than one industry. In such cases, the analysis uses data for the main industry of employment; where a respondent worked an equal time in two industries, one industry was randomly selected.

38
tariff is reduced to t<sup>∗</sup> i<sup>is:</sup> The term in the fi rst parenthesis represents the subsidy cost minus the tariff revenue collected on imports from the SRC. The second term represents tariff revenue that would have been collected if the preference scheme had been in place, where m<sup>p∗</sup> denotes import quantities from LDCs under the preference scheme after the MFN tariff reduction.<sup>28</sup> There is an additional budgetary implication associated with the introduction of the subsidy scheme. The theoretical model predicts that the move will allow an additional MFN tariff reduction, which will change world prices and thus affect tariff revenue and the subsidy. Using estimates from Limão (2005) we estimate this additional liberalization to be 25% of the 33% benchmark (or an additional 8.3%). With this additional liberalization the budgetary cost of switching to the subsidy relative is: where the prime notation denotes the value of the variables evaluated at the equilibrium under the subsidy with a larger MFN liberalization than under the preference scheme, and the superscript r is for imports from ROW. The last term is the change in tariff revenue, which can be positive or negative depending on the import demand elasticities.

# 3.1.2 Welfare for the SGC

Ultimately we are interested in the full welfare effects that arise from switching to the subsidy scheme, i.e. the relative cost of maintaining the preferential scheme in terms of lost multilateral liberalization. Denoting the welfare level for the SGC, L, by W<sup>Lp</sup> under the preference and W<sup>Ls</sup> under the subsidy if it reduced the MFN tariffs by the same amount, the difference between the two is simply the amount of the budgetary effect in (9):<sup>29</sup>

> 28 Note that equation (9) assumes —as we do later in the partial equilibrium model used to estimate the impact of tariff reduction on world prices–that these LDCs are too small to in fl uence world prices when preferences are granted (or replaced by the subsidy scheme). Panagariya et al (2001) provide detailed econometric evidence that this is a reasonable assumption for products that Bangladesh exports to the US under the Multi-Fibre Arrangement.

> 29 Assuming that the effect of small changes in the export supply of SRC on the world price are negligible.

12
- [18] Obstfeld M & K. Rogoff,1996, Foundation of International Economics, MIT Press.

- [19] Patillo, C., H. Poirson and L. Ricci, 2002, "External Debt and Growth", IMF Working Paper 02/69.

- [20] Patillo, C., H. Poirson and L. Ricci, 2003, "What are the Channels through which External Debt Affects Growth?", Brooking Trade Forum, 2003:259-274.

- [21] Piketty, T. 1997, "The Dynamics of the Wealth Distribution and the Interest Rate with Credit Rationing", Review of Economic Studies, 64:173-189

- [22] Robinson, P., 1988, "Root-n consistent semiparametric regressions, Econometrica, 56:931-954.

- [23] Velasco, 1997, "A Model of Endogenous Fiscal Deficit and Delayed Fiscal Reform", Fiscal Institutions and Fiscal Performance, James Poterba and Jurgen Von Hagen Eds., University of Chicago Press.

- [24] Warner, A, 1992, "Did the Debt Crisis cause the Investment Crisis", Quarterly Journal of Economics, 1161:1186

- [25] Windmeijer, F., 2005, "A finite sample correction for the variance of linear efficient two-step GMM estimators", Journal of Econometrics, 126(1):25-51.

- [26] Yatchew, A., 2003, Semi-Parametric Regressions for the Applied Econometrician, Cambridge University Press

22
been introduced for the electricity sector as a carbon pricing policy. Other carbon pricing instruments, such as carbon tax, could be another policy instrument to achieve its NDC. However, the government’s interest in enacting a carbon tax might be influenced by several factors, including its overall costs to the economy. This study assesses the general equilibrium effects of a carbon tax policy with several alternatives for carbon tax revenue recycling. It also compares the economic impacts of the carbon tax with those when the NDC will be met through an administrative/regulatory mandate on a national CO2 emission standard. We use a computable general equilibrium model of China calibrated with the most recent data (2017 Social Accounting Matrix) to simulate the carbon tax and emission standard policies.

The study finds that Chinese GDP in 2030 would be about 1% lower than that in the baseline if the country constraints its national CO2 emissions at its NDC target without specifying any policy measures. Emitters reduce their GHG emissions the way they find most economical, such as cutting their production, switching to cleaner fuels and technologies, deploying energy-efficient processes and devices, etc. If a carbon tax is introduced, it will cause lower economic costs no matter how the carbon tax revenue is recycled into the economy. Among the nine alternative design architectures considered for the carbon tax in terms of its revenue recycling, the economic costs would be lowest when the tax revenue is recycled to non-energy/electricity sectors, in proportion to the export intensiveness of their outputs, to cut their corporate income taxes. Recycling tax revenues to cut capital taxes would be the next better scheme. Recycling the carbon tax revenues to subsidize solar and wind electricity would be instrumental in promoting these clean technologies; however, doing so is the most expensive carbon tax design scheme considered in the study.

Several policy implications can be drawn from the analysis. First, the economic impacts of a carbon tax are sensitive to its design architecture, particularly the use of carbon tax revenues. There are many alternatives to recycling tax revenues; however recycling the revenues to reduce distortions faced by the production sectors (e.g., taxes on corporate income, taxes on capital rents) causes the carbon tax to be more efficient. One critical policy insight drawn from the study is that the implications of revenue recycling on costs of a carbon tax depend on the criteria chosen to recycle the revenues. Our study shows that when the carbon tax revenues are recycled to cut corporate income taxes, the economic costs of carbon are 27