rafmacalaba/datause-encoder-data huggingface dataset:
Table 3. Ratio of Imports a/ to GNP, Selected Industrial Countries, 1966, 1970, 1980, 1984 -1986 ( Unit: percent )

|Country|1966|1970|1980|1984|1985|1986|
|---|---|---|---|---|---|---|
|Japan|9.0|9.5|14.6|12.4|11.2|7.6|
|Australia|15.7|14.8|18.4|18.7|19.5|18.7|
|Austria|26.6|30.2|39.1|39.0|40.6|36.2|
|Belgium|44.9|49.0|63.5|76.6|73.7|65.3|
|Canada|20.0|20.5|27.3|25.7|26.7|27.0|
|Denmark|30.0|31.0|34.6|37.3|37.9|33.4|
|Finland|21.6|27.2|34.3|28.5|28.7|25.8|
|France|12.7|14.9|22.6|23.6|23.5|20.6|
|Germany, FR|17.5|19.1|27.0|28.2|28.9|24.9|
|Italy|12.5|15.0|24.4|23.4|23.5|18.7|
|Netherlands|42.8|46.3|53.1|57.0|58.8|50.0|
|Norway|42.8|43.4|42.6|39.3|39.5|41.8|
|Sweden|22.0|24.7|32.0|33.1|33.9|30.2|
|Switzerland|28.6|33.3|38.7|35.9|36.5|34.0|
|United Kingdom|19.5|22.2|25.3|29.1|28.2|27.0|
|United Stateg|4.7|5.4|10.5|10.3|10.0|10.2|

a/ Imports of goods and nonfactor services.

Source: The World Bank, World Tables 1987, 4th ed., 1988 macroeconomic balances. In fact, these variables are all determined simultaneously, in a general equilibrium framework, including other important variables such as GNP, terms of trade, exchange rates and price levels. 1/ 7. Even if the question is redirected, to whether or not Japan imports too little compared to its GNP rather than its exports, the question remains. Does it import too little because the access to Japan's market is limited by official and/or unofficial barriers, or because there

# 1/ See Lincoln (1988), p. 71 and Turner (1986).
see it with how own eyes, he will understand’: How gender informed the content and deliver of a maternal nutrition intervention in Burkina Faso. _Health Policy and Planning_ 35:536-545. doi: 10.1093/heapol/czaa012

- Kadiyala, S., Harris, J., Headey, D., Yosef, S., & Gillespie, S. (2014). Agriculture and nutrition in India: Mapping evidence to pathways. Annals of the New York Academy of Sciences, 1331 (1): 43–56. <u><mark>https://doi.org/10.1111/nyas.12477.</mark></u>

- <mark>Keer, R., Chilanga, E., Nyantakyi-Frimpong, H., Luginaah, I., & Lupafya, E. (2016). Integrated agriculture programs to address malnutrition in northern Malawi.</mark> _<mark>BMC Public Health</mark>_ <mark>16: 1197. DOI 10.1186/s12889-016-3840-0.</mark>

- <mark>Labrecht, I., Vanlauwe, B., & Maertens, M. (2016). Agricultural extension in Eastern Democratic Republic of Congo: Does gender matter?</mark> _<mark>European Review of Agricultural Economics</mark>_ <mark>, 43(5): 841-874. doi:10.1093/erae/jbv039.</mark>

- <mark>Lecoutere, E., Spielman, D., & Van Campenhout, B. (2023). Empowering women through targeting information or role models: Evidence from an experiment in agricultural extension in Uganda.</mark> _<mark>World Developmen</mark>_ <mark>t, 167: 106240. https://doi.org/10.1016/j.worlddev.2023.106240.</mark>

- <mark>Lecoutere, E. & Van Campenhout, B. (2023). Joint forces: The impact of intrahousehold cooperation on welfare in East African agricultural households.</mark> _<mark>Feminist Economics</mark>_ <mark>, 29(1): 266-297. doi:10.1080/13545701.2022.2120206.</mark>

- Miller, D., & Welch, R. (2013). Food system strategies for preventing micronutrient malnutrition. _Food Policy_ 42: 115-128. https://doi.org/10.1016/j.foodpol.2013.06.008.

- Mogues, T., Cohen, M., Birner, R., Lemma, M., Randriamamonjy, Tadesse, F., & Paulos, Z. (2010). Agricultural extension in Ethiopia through a gender and governance lens. _ESSP2 Discussion Paper 007_ . IFPRI.

- Mudege, N.N., Mdege, N., Abidin E. P., & Bhatasara, S. (2017). The role of gender norms in access to agricultural training in Chikwawa and Phalombe, Malawi. _Gender, Place and Culture_ , 24(12): 1689-1710. https://doi.org/10.1080/0966369X.2017.1383363

- Netsayi, N., Mdege, N., Abidin, P., & Bhatasara, S. (2017). The role of gender norms in access to agricultural training in Chikwawa and Phalombe, Malawi. _Gender, Place, and Culture_ , 24(12): 1689-1710. doi: 10.1080/0966369X.2017.1383363

- Nyqvist, M. B., Jayachandran, S., & Zipfel, C. (2024). A mother’s voice: Impacts of spousal communication training on child health investments. _Journal of Development Economics,_ 168. <u>https://doi.org/10.1016/j.jdeveco.2024.103263</u>

- Ragasa, C., Aberman, N., & Mingote, C. (2017). Does providing agricultural and nutrition information to both men and women improve household food security? Evidence from Malawi. _IFPRI Discussion Paper 01653._

18
from forestland into agricultural production which might be reflected in lower observable increases in agricultural production and agricultural trade, relative to agreements that do not include such provisions. But these environmental provisions may also support the process of agricultural intensification, by creating incentives to invest in agricultural capital and technology as they limit opportunities for agricultural land expansion. The overall impact of RTAs with environmental provisions on agricultural output and exports might thus reflect a combination of these two effects.

We measure agricultural activity using data from UNFAO that includes total agricultural exports, the total land area harvested, and the total weight of agricultural output. The land area harvested will capture land use change at the extensive margin while the total weight of agricultural output will reflect changes in both the extensive and intensive production margins. As above, our trade measures aggregate bilateral trade flows across all trading partners which we likewise argue is the relevant measure to consider in our setting.

In Table 2 we report estimates of our triple-difference model on agricultural and forest product outcomes. We find strong evidence that environmental provisions limit agricultural extensification. In Column (1) we find that land area harvested increases approximately 6% following entry into force of an RTA without environmental provisions. The inclusion of such provisions offsets these increases, with 6% lower area harvested that is statistically significant at the 5% level. For RTAs that include these provisions, entry into force does not lead to any discernible changes in agricultural harvest area. Likewise, entry into force of RTAs without environmental provisions leads to an approximately 6% increase in the weight of agricultural output, however inclusion of environmental provisions does not totally offset this increase and the effect is not statistically differentiable from zero. Taken together, we interpret these findings as evidence that environmental provisions mitigate agricultural land expansion at the extensive margin while apparently still leading to output increases at the intensive margin–e.g. through increased yields. Agricultural exports exhibit similar patterns, with an increase of approximately 14% following entry into force for agreements without environmental provisions that are partially offset by provision inclusion, with approximately 10% lower increase in exports. We conclude that these provisions limit agricultural trade but note that agricultural exports still appear to increase following entry into force of agreements with environ18
increase). The schemes are revenue neutral for the government, meaning that the incremental government revenue after the introduction of the policies will be recycled to the economy.

**Table 3: Schemes to recycle savings or increased government revenues**

|**Scenario Name**|**Scenario definition**|
|---|---|
|Excise tax|Use the savings or revenue to cut excise or indirect tax rates on all goods and<br>services consumed in Bangladesh|
|Income tax|Use the savings or revenue to cut income or direct tax rates imposed on<br>individuals and firms in Bangladesh|
|Lump-sum|Transfer the savings or revenue to households increasing their disposable income|
|Investment|Invest in the economy to increase the total capital stock in Bangladesh|

A large number of other options, such as using the savings for public consumption (or providing larger fiscal space), using the savings for reducing public debt, and using the savings to subsidize or finance clean energy technologies, are possible. However, we have not included them here because these additional schemes may not be necessarily better than the ones we considered here. Reviewing a large number of existing studies on the recycling of carbon tax revenues, Timilsina (2018) implies that using the savings or new revenues for public consumption would be the least preferred option because of its costs (GDP and welfare loss). The study also shows that recycling revenues for cutting public debt or financing clean energy technologies would not be efficient from the options considered here.

# **3.3 Data**

The main data required for this analysis are as follows:

- (i) Social Accounting Matrix (SAM) for Bangladesh

- (ii) Elasticity of substitution and other parameters

- (iii) Direct government transfers (subsidies) made to electric utilities in Bangladesh

- (iv) Prices of domestically supplied natural gas in Bangladesh and delivered price of LNG in India

The latest SAM available for Bangladesh is for 2012 and, because of this, 2012 is the base year for the analysis in this paper. The SAM was provided to us by SANEM, a policy think-tank based in Dhaka, Bangladesh. The SAM was adjusted to overcome some missing values by 14
# **1 Introduction**

Informality and under-employment are pervasive and associated with stagnant productivity in low and middle income countries (Busso et al. (2012)). Informality rates have not declined significantly in most countries despite a general trend towards reducing payroll tax wedges in formal employment, and even in the presence of high economic growth (La Porta and Shleifer (2014)). One reason for persistent informality is that the formal private sector has struggled to absorb bulging cohorts of youth exiting school, a problem that is likely to persist given that the median population age is lower than labor market entry in many cases.

This paper studies the extent to which the labor market opportunities faced by young men entering the labor market shape their access to formal employment and broader employment trajectories. It uses data from 14 rounds of the Arab Republic of Egypt’s labor force survey that record employment outcomes for individuals in successive graduation cohorts. The dataset contains information on multiple measures and proxies for formal vs. informal employment and under-employment, such as working without social security coverage, being employed full-time, working without a contract, working for a wage, working for the public sector, working in agriculture, and the size of the employing establishment (number of employees). We exploit variation across cohorts, regions, and schooling levels in the labor market conditions faced by an individual upon graduating to achieve identification, following Schwandt and von Wachter (2019).

Middle-Eastern and North African countries (“MENA region”), and Egypt in particular, exemplify the “youth bulge” phenomenon.<sup>1</sup> Public employment historically absorbed labor market slack, creating distortions in the supply of skills by encouraging credentialism and overeducation.<sup>2</sup> Youth labor markets are thus characterized by high levels of informality, unemployment, or underemployment while queuing for public jobs (Assaad and Krafft 2015). In this context, the opportunities of the successive cohorts entering the labor market can vary substantially depending on shocks affecting private but also pub-

> 1See Assaad and Roudi-Fahimi (2007), Saliola (2022), and projections by Assaad (2022)

> 2El-Kogali and Krafft (2019)

1
U.S. imports from China as a share of overall U.S. imports and shows the post-1980 period featured sustained growth in U.S. imports from China, although at a slowing rate.

The entry of new firms into exporting—growth on the _extensive margin_ —is an important way that aggregate trade grows in response to a tariff cut (Kehoe and Ruhl, 2013; Alessandria et al., 2020), and this is an important mechanism in our quantitative model. In Figure 3, we plot a measure of the extensive margin for exports from China to the United States. The fraction of SITC goods that China exports to the United States grows gradually from about 0.2 in 1974 to 0.6 in 2008.<sup>10</sup> In the median NTR country, this measure is flat.

The prolonged growth of Chinese exports could be due to the gradual response of trade to the very large past reforms, or it could be due to the expectations of future tariff reversals becoming less likely. We explore these two possibilities, next, taking advantage of the rich heterogeneity in trade policy in this period.

# **3 Empirical Evidence**

This section documents two main facts about China’s NTR tariff liberalization. First, China’s trade response was especially gradual relative to the average trade response to tariff changes. Second, the level of tariffs prior to the NTR liberalization has a persistent role in explaining the variation across goods in the volume of U.S. imports from China. Consequently, the delayed effect of the NTR liberalization is instrumental in accounting for the findings of the TPU literature regarding the impact of China’s PNTR status grant in 2000 (Pierce and Schott, 2016; Handley and Lim ̃ao, 2017).

## **3.1 Data**

We work with annual U.S. imports from 1974 to 2008, aggregated at the 5-digit level of the Standard International Trade Classification (SITC), revision 2.<sup>11</sup> We refer to this level of aggregation as a _good_ and denote it by _g_ . Our data include applied duties, cost-insuranceand-freight (CIF) charges, and the free-on-board (FOB) value of imports. The log FOB value of imports is denoted by _vgjt_ , where _j_ indexes the exporting country and _t_ indexes

> 10 Ideally, we would like to measure the number of new firm-goods being traded, but we lack data on firm-level trade in China going back to the 1970s.

> 11The data are from Feenstra (1996). Although more disaggregated import data are available, building a consistent concordance is difficult and noisy.

9
Dorn D. 2009. Essays on inequality, spatial interaction, and the demand for skills. Dissertation 3613, University of St. Gallen.

Eden M, Gaggl P. 2015. Do poor countries really need more IT ? the role of relative prices and industrial composition. Policy Research Working Paper Series 7352, The World Bank.

URL http://ideas.repec.org/p/wbk/wbrwps/7352.html Elsby MW, Hobijn B, Sahin A. 2013. The decline of the us labor share. _Brookings Papers on Economic Activity_ .

Gaggl P, Wright GC. 2015. A short run view of what computers do: Evidence from a uk tax incentive. Working paper, UNC Charlotte. URL http://belkcollegeofbusiness.uncc.edu/pgaggl/wp-content/uploads/sites/36/2014/09/UK_ICT_ 05-08-2015_WP.pdf Goldin C, Katz L. 2008. _The Race Between Education and Technology_ . Harvard University Press. ISBN 9780674028678.

URL https://books.google.com/books?id=mcYsvvNEUYwC Goldin C, Katz LF. 1998. The Origins Of Technology-Skill Complementarity. _The Quarterly Journal of Economics_ **113** : 693–732.

URL http://ideas.repec.org/a/tpr/qjecon/v113y1998i3p693-732.html

- Goos M, Manning A. 2007. Lousy and lovely jobs: The rising polarization of work in britain. _The Review of Economics and Statistics_ **89** : 118–133.

URL http://ideas.repec.org/a/tpr/restat/v89y2007i1p118-133.html Goos M, Manning A, Salomons A. 2009. Job polarization in europe. _American Economic Review_ **99** : 58–63.

URL http://ideas.repec.org/a/aea/aecrev/v99y2009i2p58-63.html

- Guvenen F. 2006. Reconciling conflicting evidence on the elasticity of intertemporal substitution: A macroeconomic perspective. _Journal of Monetary Economics_ **53** : 1451–1472.

URL http://ideas.repec.org/a/eee/moneco/v53y2006i7p1451-1472.html Hall RE, Jorgenson DW. 1967. Tax policy and investment behavior. _The American Economic Review_ **57** : pp. 391–414. ISSN 00028282.

URL http://www.jstor.org/stable/1812110

- Hennessy J, Patterson D, Asanovi ́c K. 2012. _Computer Architecture: A Quantitative Approach_ . Computer Architecture: A Quantitative Approach. Morgan Kaufmann/Elsevier. ISBN 9780123838728.

URL https://books.google.com/books?id=v3-1hVwHnHwC Jones CI, Kim J. 2014. A schumpeterian model of top income inequality. Working Paper 20637, National Bureau of Economic Research. URL http://www.nber.org/papers/w20637 Jorgenson DW. 1995. _Productivity: Postwar US economic growth_ , volume 1. Mit Press.

Jorgenson DW, Vu K. 2007. Information Technology and the World Growth Resurgence. _German Economic Review_ **8** : 125–145.

URL http://ideas.repec.org/a/bla/germec/v8y2007ip125-145.html

- Karabarbounis L, Neiman B. 2014. The global decline of the labor share. _The Quarterly Journal of Economics_ **129** : 61–103.

URL http://qje.oxfordjournals.org/content/129/1/61.abstract 36
- 26 -

# Table 2.5. Extent of Losses from Power Fallures

|ExtentofLoss.s<br>Nigeria|IndoneIsi|ThoIlond|
|---|---|---|
|Percent of<br>24.6<br>Estabtlshmants<br>Used OvertimWorkers|38.6|19.3|
|Percent of<br>21.8<br>Estabis himents<br>Reported<br>Produetion<br>Loss or Hours LostY|65.9|42.3|
|Averag<br>Proportion<br>of<br>10.1<br>Production<br>Loss or<br>Hours Lost(X)_W_|6.9|5.8|

NOTE: Frm Appendix Tables B10C 3li, C0 Clil 010. nd D0l.

A/ Production Loss in the **cose** of Nigeria; production hours Lost In the case of Indoneswi and Thallwnd.

Source: World Bank Nigeria Infrastructure Project Estobtlshment Survey 198. World Bank **Research** Project (RPO 676-71) EstabLishment Survey for **Indonsia** and Thalland 1992.
|Second-order stochastic dominance<br>**Social Sustainability Index by cutoff and scenario**<br>**Social gaps**<br>**Metrics**<br>**Rank correlation**<br>**coefficient**|**k = 33%**<br>**k = 50%**<br>**Cutoff value**|**k = 75%**<br>**s**|
|---|---|---|
|.4<br>Spearman<br>**H**|0.85***<br>0.87***|0.77**|
|.3<br>**Index**<br>Kendall tau-b<br>|0.72***<br>0.67**|0.61**|
|**nability**<br>Spearman<br>**A**|0.98***<br>0.85***|0.58*|
|.2<br>**l Sustai**<br>Kendall tau-b<br>|0.94***<br>0.67**|0.5*|
|.1<br>**Socia**<br>Spearman<br>|0.97***<br>0.88***|0.77**|
|0<br>Kendall tau-b<br>**M0**|0.89***<br>0.72***|0.61**|
|0<br>20<br>40<br>60<br>80<br>100<br>**Cutoff**_k_**(relative scale)**<br>Baseline<br>Alternative<br>***p<0.01, **p<0.05, *p<0.1|||
|_B4. Change in the weights assigned to each dimension. Baseline scenario: Ev_<br>_(25% each). Alternative scenario: Skewed weighting scheme in favor of th_<br>_Process Legitimacy, and 20% for the rest of dimensions)._<br>Peru<br>B4.1. FOSD: Counting Vector<br>B4.2. Domi<br>First-order stochastic dominance<br>**Counting vector CCDF by scenario**<br>**Difference between**|_enly distributed weig_<br>_e Process Legitima_<br>nance Analysis<br>(α=0)<br>**counting vector CDF c**|_hts across_<br>_cy dimensi_<br>**urves**|
|.2<br>.4<br>.6<br>.8<br>1<br>**CCDF**<br>-.4<br>-.3<br>-.2<br>-.1<br>0<br>**Difference**|||
|0<br>0<br>.2<br>.4<br>.6<br>.8<br>1<br>**Counting vector (relative scale)**<br>Baseline<br>Alternative<br>-.5<br>0<br>.2<br>.4<br>**Counting**<br>Confidence interval|.6<br>.8<br>**vector (relative scale)**<br>(95 %)<br>Estimated di|1<br>fference|
|B4.3. SOSD: Social Sustainability Index<br>B4.4. Ran<br>Second-order stochastic dominance<br>**Social Sustainability Index by cutoff and scenario**<br>**Social gaps**<br>**Metrics**<br>**Rank correlation**<br>**coefficient**|k correlations<br>**k = 33%**<br>**k = 50%**<br>**Cutoff value**|**k = 75%**<br>**s**|
|.5<br>Spearman<br>|0.24<br>0.25|0.8***|
|.4<br>**Index**<br>Kendall tau-b<br>**H**|0.18<br>0.18|0.63***|
|.3<br>**ability**<br>Spearman<br>|0.35*<br>0.76***|0.7***|
|.2<br>**Sustain**<br>Kendall tau-b<br>**A**|0.23<br>0.57***|0.57***|
|.1<br>**Social**<br>Spearman|0.29<br>0.28|0.8***|
|0<br>Kendall tau-b<br>**M0**|0.19<br>0.21|0.63***|
|0<br>20<br>40<br>60<br>80<br>100<br>**Cutoff**_k_**(relative scale)**<br>Baseline<br>Alternative<br>***p<0.01, **p<0.05, *p<0.1|||

_B4. Change in the weights assigned to each dimension. Baseline scenario: Evenly distributed weights across all indicators (25% each). Alternative scenario: Skewed weighting scheme in favor of the Process Legitimacy dimension (40% for Process Legitimacy, and 20% for the rest of dimensions)._ South Africa B4.1. FOSD: Counting Vector B4.2. Dominance Analysis 45
markedly late in 2008, but has not shown the continued decline in 2009 exhibited by consumer confidence.

**Table 5. Regression of consumer confidence on investor confidence components**

Dependent variable: Consumer Confidence Factor

||(Model 1)<br>(Model 2)|
|---|---|
|Volatility factor|-0.273***<br>-0.301***|
||(0.056)<br>(0.059)|
|Macro environment factor|0.233***|
||(0.056)|
|Macro environment factor (t-1)|0.237***|
||(0.051)|
|MSCI Developed World|0.012***<br>0.013***|
||(0.003)<br>(0.003)|
|Constant|-0.050<br>-0.069*|
||(0.042)<br>(0.040)|
|Observations|97<br>97|
|R-squared|0.72<br>0.75|
|_Volatility_<br>_CC_<br>+<br>×<br>+<br>=<br>2<br>1<br>β<br>β<br>α|_Equities_<br>_Macro_<br>×<br>+<br>×<br>3<br>β|

The dependent variable is the common factor of consumer confidence indices from United States, United Kingdom, Canada, Germany and Japan. Volatility is the monthly average of the predicted daily common factor across eight variables: VIX, US$/euro volatility, US$/yen volatility, US$/sterling volatility, agriculture commodities price index volatility, energy price index volatility, industrial metals price index volatility, and the TED spread. The macro environment factor is the predicted common factor across industrial production, employment and export growth rates (year-on-year) in the United States, United Kingdom, Germany, and Japan. Equity market growth is represented by the change (year-on-year) in the MSCI for developed economies. The estimation sample covers the period from January 2001 to Jan 2009.

14
a stock to spawn at least once in their life (Wallace and Fletcher, 1997; Paredes, 2014).

The regulator began implementing temporary spatial closures, called Suspensi ́ones Preventivas, in 2014. The regulator can temporarily close an area of ocean when the percentage of individuals caught in that area that are juvenile exceeds 10% (PRODUCE, 2012). The regulator exercises discretion; many instances of percentage juvenile greater than 10% do not lead to closures.<sup>9</sup> The regulator defines juvenile anchoveta as anchoveta smaller than 12 cm. Percentage juvenile therefore refers to the percentage of individual anchoveta that are less than 12 cm long.

Between 2014 and 2016, the regulator determined closures with data measured at the point of landing. I analyze the effects of the policy between 2017 and 2019, when the use of “electronic logbooks” enhanced the regulator’s ability to target high-juvenile areas. Electronic logbooks refer to software vessels use to record (“log”) their catch at sea. Beginning in 2017, the regulator required vessels to report to the regulator the location, estimated tons caught, and estimated percentage juvenile caught immediately after each fishing operation, called a “set”. Since estimating percentage juvenile at point of landing typically measures anchoveta from several sets, hours after they were caught at sea, electronic logbook data are both higher-resolution and timelier than landings data.

During my study period there are no penalties for catching juveniles or for reporting inaccurate percentage juvenile values (PRODUCE, 2016 _a_ ). The price fishers receive for their catch is exogenous and does not depend on percentage juvenile (Section V).

The regulator determines closures as follows.<sup>10</sup> An official monitors the electronic logbook data in real-time, which appear as points on a digital map. Each point is a set and the color of each point is the set’s percentage juvenile. When the official decides that the percentage juvenile values for a group of sets are too high, he selects that group of sets by drawing

> 9If the regulator applied the 10% threshold strictly, 69% of potential closures would have been closed, compared to the 19% that were in fact closed. Since potential closures represent fishing grounds, the regulator may use discretion to reduce the cost of the policy to the fishing industry. 10The government officials tasked with determining closures demonstrated their process to me in a December 2019 interview in their Lima office.

9