rafmacalaba/datause-encoder-data huggingface dataset:
**Table 8: Biofuels penetration (2020) due to carbon tax of US$50/tCO2 with 50% biofuels subsidy**

||Bio<br>|fuels market share<br>|Percentage chang<br>|e in GDP<br>|
|---|---|---|---|---|
||Comprehensive<br>carbon tax|Carbon tax on<br>gasoline & diesel|Comprehensive<br>carbon tax|Carbon tax on<br>gasoline & diesel|
|**World total**|15.7%|15.8%|-1.0|-0.2|
|**High-income**|14.0%|14.4%|-0.2|-0.1|
|**Aus-NZ**|3.3%|3.4%|-0.5|0.0|
|**Japan**|3.9%|4.2%|-0.1|0.0|
|**Canada**|9.6%|9.7%|-0.5|-0.1|
|**United States**|22.7%|22.9%|-0.5|-0.2|
|**France**|14.2%|15.2%|0.1|0.0|
|**Germany**|18.7%|19.4%|0.1|0.0|
|**Italy**|9.6%|10.3%|-0.1|0.0|
|**Spain**|8.3%|8.9%|0.0|0.0|
|**UK**|3.2%|3.3%|0.1|0.0|
|**Rest of EU & EFTA**|6.1%|6.3%|-0.1|0.0|
|**Middle & Low-income**|18.2%|17.8%|-2.2|-0.3|
|**China**|19.4%|16.7%|-4.0|-0.2|
|**Indonesia**|13.7%|12.7%|-1.0|0.0|
|**Malaysia**|21.3%|20.8%|-1.1|-0.3|
|**Thailand**|8.7%|9.0%|-0.3|0.0|
|**Rest of EAP**|3.6%|3.6%|-0.2|0.1|
|**India**|17.4%|17.6%|-1.8|-0.2|
|**Rest of SA**|4.1%|3.5%|-1.2|-0.1|
|**Argentina**|13.2%|13.3%|-1.7|-0.2|
|**Brazil**|65.9%|66.6%|-0.8|-0.5|
|**Rest of LAC**|8.4%|8.4%|-1.1|-0.3|
|**Russia**|26.6%|23.5%|-4.3|-0.6|
|**Rest of ECA**|9.3%|8.8%|-1.4|0.0|
|**MENA**|0.8%|0.8%|-2.9|-0.8|
|**South Africa**|15.8%|15.1%|-1.7|-0.2|
|**Rest of SSA**|11.9%|12.0%|-1.7|-0.6|

# **5. Policy Insights**

Under a partial equilibrium setting, an introduction of a higher carbon-based tax to fossil fuels could make biofuels economically attractive, thereby causing significant substitution of fossil 33
tries. Even if Chinese workers, building on the learning by doing of the workforce over the last 20 years, are able to move into complementary higher paying jobs, where will automation leave the follower countries with very unskilled labor that in the past might have expected to inherit the routine jobs that China is now shedding, but which are now in fact, disappearing altogether? Vietnam, which has benefited from redirection of off-shoring as China’s wages have risen, also has seen substantial automation of, for instance, the textile industry over the last decade.<sup>7</sup> The worry, then, is that there remains a large global population with relatively weak cognitive and non-cognitive skills who will not be writing code and programming robot routines anytime soon, but who will not inherit unskilled jobs either.

# **6 Conclusion**

This paper has used census data to explore to what degree findings of polarization in the advanced world can be found in the developing world. We first offer several reasons why we might not expect to see the same tendencies found in the advanced world, or at least not yet. It is also possible that between being destinations for off-shoring, and the fact that new technologies may enable LDC citizens to overcome myriad structural and political economy obstacles that form barriers to creating better jobs, the net impact might be expected to be positive in the medium term. We then confirm previous findings of polarization graphically for the US and France. However, we do not find strong evidence for polarization in LDCs. The key category- plant and machine operators and assemblers, does not show absolute or relative decrease in most developing countries across the last decades. Regression analysis supports the graphical findings that on average, we do not find evidence of polarization in LDCs.

This does not imply much about the future. We find that Indonesia, Brazil and Mexico do show relative decline in the operators category which could suggest potential polarizing

> 7John Luke Gallup _End of Development? The Peril of Automation for Vietnam._ 2015.

13
|**Table 2: Correlates of Baseline Capital St**|**ock**<br>(1)|(2)|(3)|
|---|---|---|---|
|Hyperbolic Discounter|‐196.1**<br>(82.13)|||
|Low Discount Rate|94.53<br>(73.46)|||
|Lack of self‐control index||‐60.34*<br>(32.48)||
|Feels pressure to share in household|||‐201.3**<br>(87.38)|
|Digitspan Recall|34.02*|35.51*|44.34**|
||(18.24)|(18.32)|(18.10)|
|Raven test score|13.20|15.85|21.77|
||(13.49)|(13.51)|(13.32)|
|Education Years|13.95|13.42|6.674|
||(11.15)|(11.19)|(11.09)|
|Female|‐193.9**|‐198.5***|‐137.8*|
||(75.45)|(75.87)|(75.17)|
|Age|13.63***|14.02***|12.57***|
||(4.162)|(4.179)|(4.228)|
|Father's schooling|1.880|2.144|0.168|
||(7.408)|(7.445)|(7.283)|
|Mother's schooling|4.200|3.842|2.374|
||(8.064)|(8.106)|(8.001)|
|Constant|‐244.5|‐263.3|‐207.3|
||(220.8)|(220.9)|(220.0)|
|Observations|652|650|621|
|R‐squared|0.053|0.049|0.043|
|Standard errors in parentheses||||
|*** p<0.01, ** p<0.05, * p<0.1||||
Table 4: Trends in Real Basic Starting Salaries in the Public Sector, Selected Countries

|Country/Level|An|nual Rate of G|rowth|(%)|
|---|---|---|---|---|
|<br>________________|Period|<br>Salary|Real|GDP Canita|
|Bantladesh|1970-83||||
|Senior Civil Servants||-16.2%||1.3|
|Jamaica|1972-82||||
|Top of Scale<br>Bottomof Scale||-8.8% to -11<br>- 2.7%|.3%|-3.0|
|Sri Lanka|1975-83||||
|Administrative<br>Post<br>(Class I; Grade II)<br>Unskilled||- 3.6%<br>4.8%||3.6|
|Thailand|1976-84|||3.8|
|Grade 9 - Deputy<br>Director<br>General||- 1.5%|||
|Grade1- Secondary||- 2.3%|||
|Education<br>Required|||||

So'trces: Banuladesh: World Bank Report No. 4822, Bangladesh: Economic Trends and Development Administration, Feb. 27, 1984; p. 111. Jamaica: World Bank Report No. P-3796-JM, Public Administration Reform Proiect, May 3, 1984, pp. 9-10. Sri Lanka: Research notes, B. Nunberg (1987), World Bank, Table 4. Thailand: World Bank Background Paper, P. Bloch, S. Chutikul and N. Poapengsakon, "Public Sector Employment in Thailand", p. 58.

31
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took approximately four times the time required for GPS.<sup>7</sup> In Ethiopia, GPS required 13.9 minutes on average, while the compass and rope measurement on the same plots required an average of 57 minutes. In Tanzania, the duration averages were 7.4 minutes and 29.3 minutes for GPS and compass and rope respectively. These findings are consistent with previous studies such as Schoning et al. (2005) and Keita and Carfagna (2009) who find that compass and rope takes approximately 3.5 times as long as GPS on average.

To put the time considerations into context, given the sample size and average measurement durations in Ethiopia, the field teams spent a total of 416 hours measuring plots with GPS (1797 plots * 13.89 minutes) and 1,707 hours measuring with compass and rope. Using GPS instead of compass and rope, therefore, saved 1,291 hours of labor – over 160 person/days (at 8 hours per day). This estimate of time savings is for a relatively small-scale methodological experiment; savings in nationally representative household surveys would be proportionally larger. Minimizing the amount of time required to collect quality land area data can significantly reduce costs and improve the flow of fieldwork.

# **_B. Comparison of competing measurements_**

## _1. Compass and Rope vs. GPS_

In the literature, the main reservation regarding the use of GPS measurement in surveys is its performance on small plots. Furthermore, Keita and Carfagna (2009), Schoning et al. (2005), and Palmegiani (2009) all found that GPS tends on average to err on the negative side, i.e. to understate the area with respect to compass and rope.

Table 3 presents descriptive statistics on the GPS and compass and rope area measurements completed as part of the methodological studies. Mean plot size is small in all countries, ranging from 0.27 acres in Tanzania to 1.31 acres in Nigeria. The mean difference between compass and rope and GPS measurement is very small. The sample mean bias in all three countries is plus or minus 0.01 acre, which translates in a 1 to 3 percent difference when expressed in relative terms (note that the values are not expressed in absolute value and as such negative and positive figures are averaged). Mean GPS and CR measurements are significantly different at the 1% level in Ethiopia, Tanzania, and the pooled data. In Nigeria, GPS and CR area measurements are significantly different at 10% level. Furthermore, in Nigeria the GPS and

> 7 Data on measurement duration are not available for Nigeria.

17
a visible virtual presence: the increased availability and use of online services in a province leads to a bigger boost in export outcomes for firms in industries more reliant on an online presence. We also find that these benefits were enhanced by, but not contingent on, access to broadband, approximated by the availability of fiber optic cables in the provinces.

An interesting implication of these results is that access to the internet boosted firm-level exports in China even before the emergence of Alibaba as a widely-used, large scale e-commerce platform and before eBay’s expansion in China. The results suggest that the internet significantly reduces trade costs, even in the absence of broadband and major international e-commerce platforms serving the domestic market. This finding is relevant for the many developing countries trying to strike a balance between widening access to basic services and deepening it through the creation of a broadband network and connecting to major e-commerce platforms.

The rest of the paper is organized as follows. Section 2 reviews the literature while Section 3 describes the data. Section 4 describes the empirical specification while Section 5 presents the results. Section 6 concludes.

# **2. Literature Review**

Early work on the effect of the internet on trade relied on aggregate country-level data (Freund and Weinhold, 2002, 2004; Clarke and Wallsten, 2006). For example, Freund and Weinhold (2004) show a significant effect of the number of web hosts on trade during the period 1995-1999. Their estimates suggest that a 10 percentage-point increase in the growth of the number of web hosts in a country leads to a 0.2 percentage point increase in export growth. Recently Lin (2015) finds similar magnitudes for the impact of internet users on export growth based on data for the period 1990-2006. Other research finds that the relationship depends on destination countries’ income levels: higher internet use in a developing country is related to higher exports to highincome countries but not necessarily to other developing countries (Osnago and Tan, 2015).

Recent work in this area has moved from country-level to firm-level analysis. Kneller and Timmis (2016) estimate a strong positive causal impact of broadband internet use by business services firms in the United Kingdom on their propensity to export. To address potential endogeneity, these researchers use spatial differences in broadband availability (linked to the 4
interest rates, a further increase of public indebtedness is to be avoided, and inflation is to be constrained at 5 per cent annually. This result is largely -- but not exclusively -- determined by the currently observed public debt ratio, which is approximately equal to GDP in Mexico, but only half as high in Brazil. In 1988, the Mexican authoritie **s** eem to have achieved the requ.ired fiscal adjustment. while the fiscal disequilibrium in Brazil is estimated at about 3 per cent of GDP. While the Mexican achievement is very impressive, it is too focused on cuts in public investment.

Second, the burden of the domestic public debt will matter more than the burden of foreign debt, provided that further devaluation-induced increases in the real cost of servicing foreign debt can be avoided and that the interest cost of domestic debt continues to exceed the cost of foreign debt.

Third, bringing down inflation from current levels to those observed in stable debtor countries would yield an important once-for-all gain in seignorage. especially in Mexico. If this gain is used to amortize part of the high-cost domestic debt, the required non-interest budget surplus will be reduced.

Debt dynamics continue to impose restrictive fiscal policies on high-debt OECD countries, too (OECD. 1989). Calculations on debt stability requirements, based on a somewhat simpler procedure than that described for Brazil and Mexico, above, show that Belgium, Ireland and Italy still have a fiscal disequilibrium so that debt ratios are currently rising rapidly. The current public borrowing requirements still exceed the level that would stabilize debt ratios. by 3.5 % of GDP in Belgium, 2.0 1 in Ireland, and 3.2 X in Italy (OECD, 1989, table 5.23).

# 2. Growth-Oriented Fiscal Adjustment

If the medium-term strategy is to stabilize (and then to reduce) the public debt ratio, just to run a certain non-interest surplus will not be enough. For such a strategy to be sustainable, GDP growth will have to be fostered and real depreciation of the exchange rate as well as a rise in real

-18-
# **2.3. Descriptive Statistics**

Figure 1 shows the proportion of household farms in our working sample producing tobacco, separately for households with above and below-median female non-cognitive ability. Farms managed by high non-cognitive ability women are almost 7 percentage points more likely to produce tobacco (p-value<.05). This difference corresponds to a 43 percent increase in the likelihood of tobacco adoption relative to the sample mean of 16 percent. The remainder of the paper will try to explain what causes this difference.

## **2.3.1. Differences across Communities**

Table 2 presents summary statistics. Column 1 reports means and standard deviations for the full working sample of 494 households. Column 2 shows the average difference and corresponding p-value on each characteristic between household farms with above and below-median non-cognitive ability women.

Panel A examines the community environment within which women operate their farms. We use information from the FAO’s _Global Agro-Ecological Zones_ (GAEZ) database to proxy for the agroclimatic suitability of the community for cultivating tobacco [Fischer _et al._ 2012].<sup>6</sup> The tobacco suitability index combines information on local climate conditions, soil and terrain characteristics, with the growing requirements of tobacco to measure whether tobacco can be grown productively in the area (on a continuous scale from 0 to 100). We see that farms managed by high non-cognitive ability women are located in communities with higher potential tobacco yields (p-value<.01).

We proxy for access to tobacco markets and farm inputs with whether a tobacco club is present in the community. Tobacco clubs provide local communities with improved access to the tobacco auction floors (where most of the tobacco produced in Malawi is sold to international buyers), as well as to farm labor, non-labor inputs, and information [Negri and Porto 2016]. Nearly 40 percent of the women operate in communities where such clubs

> 6 The GAEZ project supplies global estimates of tobacco (and other crops) suitability at a spatial resolution of 5 arc minutes (approximately in grids with cells size of 9x9 km). This corresponds to an area larger than most enumeration areas (“communities”). We construct an average tobacco suitability index value derived for each enumeration area.

8
# **Liberian Women Count: Evidence from a Macrosimulation of the Gender Dividend**

Mahesh Karra,<sup>1</sup> Mitja Del Bono,<sup>2</sup> Joshua Wilde,<sup>3</sup> Wendy Cunningham,<sup>2</sup> Sarika Gupta<sup>2</sup> 1: Frederick S. Pardee School of Global Studies, Boston, MA, USA 2: World Bank, Washington, DC, USA 3: Max Planck Institute of Demographic Research, Rostock, Germany Key words: gender, gender dividend, women’s empowerment, inequality, demography, human capital, employment, time allocation, economic growth, macrosimulation, Liberia JEL: J11, J16, J22, J24, E24, O40
funds comes directly from abroad. The results reported in Panel A of Figure 13 allow the differential effect of the event to depend on a country’s degree of capital account openness (captured by the Ito and Chinn, 2008 index). Wholesale dependent banks located in more financially open countries experience a similar decline than those in less open countries. Only four days after the Lehman event (September 19) there is a significantly larger relative decline in more open countries.

A possible explanation for this lack of relevance of capital account openness in the transmission of the crisis is that the relevant measure of openness should more directly capture the exposure of the banking sector to international sources of wholesale funds. Since there are no bank level data on the use of international funds, I rely instead on data from the Bank of International Settlements (BIS) on the external deposits and loans of banks in a country vis-à-vis the foreign bank and non-bank sector. The evidence, shown in panels B.1 and B.2, supports this idea. The CADR of high wholesale dependence banks in countries with external loans as a fraction of total bank assets below the cross-country median is much smaller than that of countries above the median. The exposure of the banking sector seems to matter. Overall, it seems that the liquidity crunch was particularly important for banks with high wholesale dependence located in countries with good banking sector integration. This further supports the role of wholesale dependence as a source of vulnerability that contributes to the transmission of money market shocks.

# **7 Are there real consequences?**

The results reported so far show that the stock price of banks with higher wholesale dependence declined significantly more than that of their country peers with lower wholesale dependence, suggesting that the use of wholesale funds helped to propagate the crisis across countries. The main advantage of looking at stock prices in an eventful period such as the 2007/2008 crisis is that this approach focuses on high frequency responses and isolates the impact of an event within a narrow window where one can safely assume that the event is the main news. Studying lower frequency data runs the risk of confounding the impact of the events with the policy responses they triggered such as the massive interventions by the Federal Reserve, the ECB, or the US and other governments. The main disadvantage of this approach is that it only shows the impact of the events on the financial value of banks but not the second round impact it has on the real economy. It is thus possible to wonder whether the mechanism reported here matters for real production decisions. The regressions reported in Table 2 explore the consequences of 24
# Table 2: Relative Benefits <u>of School Proofing/Retrofit Under Three Cost Scenarios</u>

||**low**|**medium**|**high**|**Notes**|
|---|---|---|---|---|
|Retrofit/build cost addition (over<br>non-proof) (%)|8|12.5|20|Costs of construction/retrofit to make building strong enough to avoid death in the<br>event of an earthquake. India estimate from Bhatia, 2008 for low case, Istanbul<br>estimate from Smyth et. al., 2004a for medium case, Algeria estimate from Wisner<br>et. al.2004 for highcase|
|Related reduction in attendance<br>(%)|7|11|17|Assuming retrofit/improved build costs lead to the construction of fewer schools<br>and (therefore)lowerschoolattendance.|
|Child mortality reduction<br>associated with female education<br>(%)|14|14|14|Reduction in child mortality taken from Desai and Alva, 1998|
|Current child mortality rate per<br>1000|32|85|200|Current child mortality rates from World Bank (2008). Low is for Turkey,<br>medium for India,high forChad.|
|Child mortality rate change per<br>1000|4|12|28|Absolute change expected based on expanded primary education.|
|Fertility rate (per woman)|2.2|2.9|6.4|Current fertility rates from World Bank (2008). Low is for Turkey, medium for<br>India,high forChad.|
|Fertility rate (per student)|0.9|1.3|1.9|Fertility rate per student, allowing for percentage of primary students that are girls<br>fromWorldBank(2008).Lowisfor Turkey,medium for India,high forChad.|
|Child mortality due to school<br>absence (deaths/1,000 students)|0.31|1.69|8.66|Student fertility rate multiplied by mortality rate change and reduction in<br>attendance|
|School earthquake deaths/yr (per<br>1,000 students)|0.1|0.025|0.0125|Based on global data on deaths in schools form earthquakes from Bhatia, 2008<br>(2,500/year) and estimates of students in schools potentially at risk of earthquake -<br>-25matrisk forthelowrate,100m for medium,200m for high.|
|Risk of death over eight years<br>(per 1,000 students)|0.8|0.2|0.1|Based on an eight year primary curriculum|
|**_Deaths saved from retrofit %_**<br>**_lives lost from school absence_**|**_258_**|**_12_**|**_1_**||
|Basic build cost/ student place<br>($)||100|400|Using percentage retrofit costs from above and school construction costs in low<br>case based on India from Bhatia, 2008, high case based on Algeria from Wisner et<br>al 2004.|
|Risk of death over 30 year<br>buildinglife (per 1,000 places)||0.75|0.375||
|**_Cost per student death averted_**<br>**_(not discounted) ($)_**|40|**_16,667_**|**_213,333_**||

30