rafmacalaba/datause-encoder-data huggingface dataset:
to be embodied in electric capital vintages. A technology that is especially relevant in our framework is the heating system, used pervasively in manufacturing to shape components or transform materials. For instance, old generations of boilers are powered by coal or gasoline, while new generations of the same technology are electric (Malek, 2005). Similarly, the arc furnace, an electric heating system, came to replace the older blast furnace powered by fuel. Thus, an increase in fuel prices may induce plants to scrap old fuel-powered machinery and purchase new electric equipment. Case studies evidence suggest that electric heating technologies are not only more energy-efficient, but also able to generate non-energy productivity gains, such as better product quality, process flexibility, speed and reliability (EPRI, 2007). Since electric machinery is more productive and energy-efficient, the negative effect of the fuel price increases is compensated by the positive effect on technological upgrading, with a potentially positive net effect on performance. It follows that electricity price hikes do not trigger substitution, because electric technologies are less likely to be outdated. Hence, the negative impact on performance.

# **5.1 Energy Prices and Technology Upgrading**

We turn to testing this mechanism. Our working hypothesis is that fuel price hikes trigger technology upgrading towards electric machinery, and that electricitypowered machinery is more productive than fuel-powered machinery. In line with this hypothesis, we should observe that upon an increase in fuel prices, plants invest in electric machinery and increase their technical efficiency.

Although our data provide information on sales and purchases of capital by type of asset, we cannot observe whether transactions on equipment refer to machinery powered by fuel or electricity. However, using energy consumption data we can infer changes in capital composition by looking at the energy content of plants’ capital stock. Columns 1 and 2 of Table 3 show that an increase in fuel prices boosts machinery turnover, as measured by the absolute value of the sum of purchase and sale of machinery.<sup>37</sup> At the same time, electricity prices tend to have a negative

> 37Given the lumpiness of investment data at the plant level, we smooth the series by constructing a measure of machinery turnover (sales + purchase of machinery and equipment), which allows us to use OLS. The logs of the residual zeros are replaced with zero. We also

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Samsung Electronics, Nokia, and Intel, trade primarily intra-firm. Samsung, the world’s biggest communications equipment multinational, has 158 subsidiaries across the world, including 43 subsidiaries in Europe, 32 in China and 30 in North and South America (Samsung 2014). Other multinationals, such as Apple, Motorola, and Nike, rely mainly on outsourcing, and hence on arm’s-length trade with non-affiliated suppliers (Lanz and Miroudot 2011).

Multinational companies and their affiliates accounted for one-tenth of global GDP and their sales amounted to about half of global GDP in 2015 (UNCTAD 2016; Figure 1). The world’s largest multinationals (Shell, Toyota, and General Electric in advanced economies; China National Offshore Oil, Vale SA, and Petronas in EMDEs) are systemically important in both their home and host economies. Post-crisis, foreign affiliates of multinational companies have fared better than their domestic counterparts and contributed more significantly to the recovery of global GDP. For example, during 2010-14, the value added of multinationals grew faster-than-average, at 6.6 percent—well above global GDP growth of 4.4 percent.

Unfortunately, data on global intra-firm trade are not available. However, a unique dataset on bilateral U.S. exports and imports can provide an indication of developments in intrafirm trade growth. The United States plays an important role in global trade (Figure 2): it accounts for about 11 percent of global goods trade and 23 percent of global foreign direct investment (FDI) stocks. It is the largest export destination for one-fifth of the world’s countries and the largest import source for one-tenth. U.S. multinationals account for about 30 percent of the employment and sales of the world’s largest 100 non-financial multinational companies. Most of the post-crisis slowdown in U.S. trade growth can be attributed to the sharp slowdown in arm’s-length rather than intra-firm trade. By 2014, intra-firm trade growth had returned to near pre-crisis rates while arm’s-length trade growth has lagged significantly below elevated pre-crisis rates.

We show that compositional effects combined with a higher income and real exchange rate elasticity of arm’s-length trade contributed to the strong pre-crisis growth and the steep postcrisis slowdown of arm’s-length trade compared to that of intra-firm trade. First, arm’s-length trade depends more heavily than intra-firm trade on sectors with rapid pre-crisis growth that boosted arm’s-length trade pre-crisis but that have languished post-crisis. Second, arm’slength trade is also more concentrated in emerging market and developing economies, where output growth has slowed sharply from elevated pre-crisis rates.

These compositional effects were compounded by a greater elasticity of arm’s-length trade than intra-firm trade to demand and real exchange rate movements. Using an econometric framework of the determinants of bilateral U.S. exports by sector, we show that arm’s-length exports are more sensitive to changes in demand and real exchange rates than intra-firm 3
P a g e <u>|</u> **16**

and the municipality or development authority is obliged to develop more land in suburban areas.

In addition, even when land and property titles are clear, the high transaction cost and time involved in transmitting titles act as supply constraints. High stamp duties are not the only transaction costs. The time and expertise required to transmit titles legally might discourage formal transactions for small lots, although these are precisely the type of lots that should be readily marketable. They allow for an efficient expansion of built space in local areas without requiring major infrastructure expansion. Simplifying the procedure for changing land use and transmitting title would increase immediately the number of urban lots that could be developed and would contribute to alleviating the land and floor space shortages in Indian cities.

We illustrate the specific difficulties and types of transactions costs incurred using an analysis of land conversion at the urban periphery taken from Ahmedabad.

<u>Conversion of land at the urban periphery. The topography of the surrounding</u> countryside does not pose an impediment to the expansion of the city. However, before anyone can legally build there, land surrounding the city that is classified as agricultural<sup>5</sup> has to be legally converted to urban land. This is a complex process involving a number of physical, cadastral and tenure related transformations. Completing each of those steps involves a great deal of time, financial outlays, and risks for a developer. These in turn drive costs which must ultimately be built into the price of the final housing product (or commercial or industrial space). Interest during construction is one of the most important cost drivers for developers. It accounts for about half of total development costs in a typical development project in a relatively expeditious regulatory environment. The cost burden, direct and indirect, of these procedures can be very substantial.

Key steps in the entire process, starting from the conversion of agricultural land up to sale of housing as well as the different agencies involved are listed in Figure 5 below. All new housing provided on the periphery of Ahmedabad must pass through these laborious procedures. The process for redeveloping and intensifying land use on existing plots within the city is similar except that steps 4 to 8 are not relevant—if the plot has already passed through the agricultural to urban conversion process, which is not the case for many plots in the city.

> 5 By agricultural land, we mean land classified as agricultural. This can be the case where or not the land is under cultivation.

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where V is the wind speed, V������ is the wind speed at and below which no damage occurs (set at 92.6km/h) and V���� is the wind speed at which half the property is destroyed (set at 203.7km/h).

The wind speed data we use follows Strobl (2012), which in turn is based on a wind field model developed by Boose, Serrano and Foster (2004), which in turn is based on Holland (1980). The base equation is given as: where V is the wind speed at point P , V� is the maximum sustained wind velocity anywhere in the hurricane, T is the clockwise angle between the forward path of the hurricane and a radial line from the hurricane center to the point of interest (the centroid of a Parish), P , V� is the forward velocity of the hurricane, R� is the radial distance from the center of the hurricane to point P , and G is the gust wind factor (water = 1.2, land = 1.5). Finally, F is a scaling parameter for surface friction (water = 1.0, land = 0.8), S is the asymmetry due to the forward motion of the hurricane (1.0) and B is the shape of the wind profile curve (1.2). These parameter values have been verified in Boose, Chamberlin and Foster, Landscape and Regional Impacts of Hurricanes in New England (2001) and Boose, Serrano and Foster (2004).

The source for the localized wind speeds is the IBTrACS database that provides the strength and tracks every 6 hours of all typhoons that affected Southeast Asia during the period.

As for earthquakes, the damage index and the different data sets are combined and a final data set with the nightlights, population and damage data are made, ref Figure 4. This is used for a case study of typhoon Haiyan in 2013 and in the fixed effect regression: which is the same as in section II.c, giving typhoon effect coefficients for the event month and the 12 months following. As the Philippines and Vietnam were the only two countries to experience any damaging typhoons during our period, the regression was only run for those two countries.

_Results.—_ Once again the first analysis will cover a case study, the typhoon Haiyan. It is also known as typhoon Yolanda on the Philippines and was active from November 3, 2013 through November 11, 2013. It made landfall in the eastern parts of the Philippines on November 7 with wind speeds that were 305km/h, a then‐record velocity. It continued across the middle islands of the Philippines leaving the islands on November 8. It is widely known as the deadliest and costliest typhoon to ever hit the Philippines in modern times, killing 6,300 people and causing damages worth US$2.2 billion. As a side‐note, in July 2014 typhoon Rammasun struck some of 22
- 21 -

relations, as important as strategic arms reduction talks as a measure of change U.S.-Soviet relationship. This political reality will no doubt cause discomfort for the IMF and the World Bank, yet to ignore it could prove to be more dangerous than prudent.

53. Eastern European economic reformers, after all, are devising policies never before attempted; reliable guidelines for dismantling centrally planned economies do not exist and such experimentation must be carried out with the support of highly politicized publics who have been antagonized by pabt failures and with the tolerance of a powerful neighbor whose own government might fall should its hegemonic role in the region appear threatened. Active support by the International Financial Institutions in the reform process can provide local policy makers more options, resources, and authority -- economic and political -- foi I a-.ncing interests and building consensus. As a recent report by the Institute fur East- WHet &:;curity Studies concludes: support by the international financial institutions for policy ieforms, structural adjustment, trade expansion, technical cooperation and other joint ventures with the West, will be much more effective if they are designed and executed within a long range strategic framework that encompasses all of the European region, including the Soviet Union. 36 54. If the international financial institutions are able to play a vital role in the successful economic restructuring of Eastern Europe countries and thereby help to advance East-West cooperation this could reduce the risk that European donors will become so preoccupied with their own regional concerns that they will neglect the needs of developing countries.<sup>37</sup> The international financial institutions can also help manage any problems that could emerge should expanding exports from CMEA countries be granted preference over products from developing countries or otherwise disrupt their markets.

- h/ Gevasina Bissolino, Laszlo Lang, Paul McCarthy and Katarzyna Zukowska, "Toward A New East-West Security Relationship: the Economic Agenda," conference paper, Seventh Annual Conference, Institute for East-West Security Studies, Potsdam, German Democratic Republic, June 9-11, 1988.

- 3_/ A rather dramatic indication of this new interest in helping finance economic activity in the Soviet Union was the report that over the ten days beginning October 10, 1988, commercial banks in Western Europe and Japan pledged a total of $9 billion in loans to Moscow's Bank for Foreign Economic Affairs, $1 billion more than the total new lending to the Soviet Union during the three years ending December 31, 1987. New York Times, October 20, 1988.
- (2015) “The Hidden American Immigration Consensus: A Conjoint Analysis of

- Attitudes toward Immigrants,” _American Journal of Political Science_ , 59 (3), 529–548.

- Halla, Martin, Alexander F Wagner, and Josef Zweim ̈uller (2017) “Immigration and Voting for the Far Right,” _Journal of the European Economic Association_ , 15 (6), 1341–1385.

- Hangartner, Dominik, Elias Dinas, Moritz Marbach, Konstantinos Matakos, and Dimitrios Xefteris (2019) “Does Exposure to the Refugee Crisis Make Natives More Hostile?” _American Political Science Review_ , 113 (2), 442–455.

- Harmon, Nikolaj A (2017) “Immigration, ethnic diversity, and political outcomes: Evidence from Denmark,” _The Scandinavian Journal of Economics_ .

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- Hennig, Jakob (2021) “Neighborhood quality and opposition to immigration: Evidence from German refugee shelters,” _Journal of Development Economics_ , 150, 102604.

- Hopkins, Daniel J, John Sides, and Jack Citrin (2019) “The muted consequences of correct information about immigration,” _The Journal of Politics_ , 81 (1), 315–320.

- Ib ́a ̃nez, Ana Mar ́ıa, Andr ́es Moya, Mar ́ıa Adelaida Ortega, Sandra V Rozo, and Maria Jos ́e Urbina (2024) “Life Out of the Shadows: the Impacts of Regularization Programs on the Lives of Forced Migrants,” _Journal of the European Economic Association_ , 10.1093/jeea/ .

- jvae044

- Kaushal, Neeraj (2006) “Amnesty Programs and the Labor Market Outcomes of Undocumented Workers,” _Journal of Human resources_ , 41 (3), 631–647.

- Kling, Jeffrey R, Jeffrey B Liebman, and Lawrence F Katz (2007) “Experimental Analysis of Neighborhood Effects,” _Econometrica_ , 75, 83–119.

- Lehmann, M Christian and Daniel TR Masterson (2020) “Does aid reduce anti-refugee

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**Figure 2: Death probability in 1994, by age and gender. From siblings' mortality data, Demographic and Health Survey, Rwanda 2000.**

<!-- Start of picture text --> 30<br>25<br>20<br>15<br>10<br>5<br>0<br> 1 to 5 6 to 10 11 to 15 16-20 21-25 26-30 31-35 36-40 41-45 46-50 Above 50<br>Age in 1994<br>Females Males<br>Death probabliity<br><!-- End of picture text --> 22
37 Lekfuangfu, W.N., Piyapromdee, S., Porapakkarm, P., and Wasi, N. 2020. On COVID-19: New Implications of Job Task Requirements and Spouse's Occupational Sorting. Covid Economics: Vetted and Real-Time Papers, May 1.

38 Estupinan, X., Sharma, M., Gupta, S., and Birla, B. 2020. El impacto de la pandemia de COVID19 en la Oferta Laboral, los Salarios y el Valor Agregado Bruto en India (Impact of COVID-19 Pandemic on Labour Supply, Wages and Gross Value Added in India). Available at SSRN: https://ssrn.com/abstract=3637880 or <u>http://dx.doi.org/10.2139/ssrn.3637880</u> 39 Aucejo, E.M., French, J.F., Ugalde Araya, M.P., and Zafar, B. 2020. The Impact of COVID-19 on Student Experiences and Expectations: Evidence from a Survey. NBER Working Paper No. 27392.

40 As formulated by Becker, G.S. 1975. Human Capital, Chicago: University of Chicago Press; and Schultz, T.W. 1961. Investment in human capital. American Economic Review 51: 1-17.

> 41 Mincer, J. 1974. _Schooling, Experience, and Earnings,_ New York: National Bureau of Economic Research.

42 See Banerjee, A.V. and Duflo, E., 2005. Growth theory through the lens of development economics. _Handbook of economic growth_ , _1_ , pp.473-552; Peet, E.D., Fink, G. and Fawzi, W., 2015. Returns to education in developing countries: Evidence from the living standards and measurement study surveys. _Economics of Education Review_ , _49_ , pp.69-90; and 42 Psacharopoulos, G., and Patrinos, H.A. 2018. Returns to investment in education: a decennial review of the global literature. _Education Economics_ 26(5): 445-458: <u>https://www.tandfonline.com/doi/full/10.1080/09645292.2018.1484426.</u>

> 43 <u>https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-</u> - <u>lending groups</u>

44 Psacharopoulos, G., and Patrinos, H.A. 2018. Returns to investment in education: a decennial review of the global literature. _Education Economics_ 26(5): 445-458: <u>https://www.tandfonline.com/doi/full/10.1080/09645292.2018.1484426</u> 45Kuhfeld, M., Soland, J., Tarasawa, B., Johnson, A., Ruzek, E., and Liu, J. 2020. Projecting the potential impacts of COVID-19 school closures on academic achievement. EdWorkingPaper: 20- 226. Retrieved from Annenberg Institute at Brown University: https://doi.org/10.26300/cdrv <u>yw05</u> 46 Azevedo, J.P., Hasan, A., Goldemberg, D., Iqbal, S.A., and Koen, G. 2020. Simulating the Potential Impacts of COVID-19 School Closures on Schooling and Learning Outcomes: A Set of Global Estimates. Policy Research Working Paper No. 9284. World Bank, Washington, DC <u>https://openknowledge.worldbank.org/handle/10986/33945.</u> 47 Azevedo, J.P., Hasan, A., Goldemberg, D., Iqbal, S.A., and Koen, G. 2020. Simulating the Potential Impacts of COVID-19 School Closures on Schooling and Learning Outcomes: A Set of 15
**Table 3 Projections of Percentage Change in Temperature and Rainfall for the Southwest Region in 2050**

|Emission|20|50 Temperatu|re||2050 Rainfall||
|---|---|---|---|---|---|---|
|Scenario|||||||
||IPS-CM4L|MIROC 3.2|ECHO-G|IPS-CM4L|MIROC 3.2|ECHO-G|
|A2|8.03|2.61|3.33|-30.91|26.42|4.88|
|A1b|8.16|3.32|4.16|-6.96|11.72|21.86|
|B1|7.11|3.34|3.04|-23.37|21.18|17.7|

# Projections for Freshwater Flow from Himalayan Rivers

The rate at which glaciers will melt in the Hindu Kush Himalayan region with climate change is uncertain (Cogley et al. 2010; Immerzeel et al. 2010; Bolch et al. 2012; Miller et al. 2013). However, since glacier melt contributes only about 2 percent of the annual flow of the Ganges (Alford and Armstrong 2010), the Ganges system as a whole is unlikely to be significantly affected by glacier melt even if it increases in the future (World Bank 2013). However, it should be noted that the schedule of accumulation and melting of snow in the Himalayas could change and lead to key changes in the Ganges basin hydrology with climate change.<sup>22</sup> Bangladesh has a signed treaty with upper riparian country India on sharing the water of the Ganges under different river flow regimes. In light of the uncertainty of the effects of climate change on the Ganges basin hydrology, we have assumed strict adherence to the existing Ganges water treaty between Bangladesh and India for the Ganges water flow from India in this analysis.<sup>23</sup> An average of the measured Ganges water flow from India over past 16 years was

> 22 “Temperatures during the monsoons are expected to be warmer and the zero-degree isotherm is expected to rise to a higher altitude, some of the precipitation that falls as snow today will then become rain, resulting in lower snow accumulation and higher runoff.  Consequently, during the spring thaw, there will be less snow to melt, resulting in lower water flow in the pre-monsoon low-flow (dry) season and can have a significant impact in some catchments where snowmelt is a major input.” (World Bank 2013) 23 See Dinar et al. (2010) on trans-boundary river treaties and climate change.

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to be much lower for countries experiencing high inflation as indicated by the relatively high standard deviations on the average improvement measures.

Table 2.2

|% Ch<br>Cont<br>|anges in Performanc<br>rolling for Initial Ma<br>|e Indicators, All Fin<br>croeconomic And Fi<br>Macroeco<br>**Financial Sec**<br>|ancial Sector Adjust<br>nancial Sector Cond<br>nomic and<br>**tor Conditions**<br>|ments<br>itions<br>|
|---|---|---|---|---|
|Indicator|Group**I**<br>Inflation< 25%;<br>Dep Bank Pr Cred<br>< 20% of GDP|Groupn<br>Inflation > 25%;<br>Dep Bank Pr Cred<br>< 20% of GDP|**GroupEmI**<br>Inflation_<_25%;<br>Dep Bank Pr Cred<br>> 20% of GDP|**Group IV**<br>Inflation > 25%;<br>Dep Bank Pr Cred<br>> 20% of GDP<sup>2</sup>'|
|As**a %**of GDP:|||||
|M2<br>(M2/GDP)|+6.37 (3.86)*<br>N=6|+3.71 (7.15)<br>N=6|-0.74 (3.36)<br>N=7|-3.92 (5.88)<br>N=2|
|Liquid Liabilities<br>(LL/GDP)|+7.21 (3.99)<br>N=5|+2.09 (7.88)<br>N=5|-1.04 (3.68)<br>N=4|N=0|
|Dep Bank Pr Cred<br>(DBPC/GDP)|+3.47 (5.27)<br>N=7|+3.26 (9.09)<br>N=6|-0.39 (4.82)<br>N=7|-7.20 (12.89)<br>N=2|
|Non Bank Pr Cred<br>(NB/GDP)|+0.31 (1.02)<br>N=7|-1.17 (1.66)<br>N=6|**_-0.50_**(1.26)<br>N=6|0.00 (0.00)<br>N=2|
|Cen Bank Pr Cred<br>(CB/GDP)|+0.15 (0.04)<br>N=7|-0.12 (0.22)<br>N=6|-1.20 (3.17)<br>N=7|_-0.51_(0.89)<br>N=3|
|Fixed Cap. Form.<br>(FCF/GDP)|+0.28 (4.57)<br>N=8|+0.96 (5.13)<br>N=6|+0.85 (2.81)<br>N=7|+0.31 (0.57)<br>N=2|

-Standard Deviations in Parentheses

The inflation results should come as no surprise, as the banking sector is less apt to grow when savers, borrowers, and bankers face dramatic currency volatility. The financial development results are, however, less intuitive. Apparently, we can expect better developed financial sectors to grow more slowly as they approach an "appropriate" level and that DBPC/GDP is, in most instances, a reasonable indicator of financial sector development. 21 As described below, due to data measurement problems, Nicaragua was excluded from the regression results and from the M2/GDP, DBPC/GDP, and FCF/GDP figures for group IV. See fn. 34.

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