rafmacalaba/datause-encoder-data huggingface dataset:
<!-- Start of picture text --> Venezuela Zimbabwe<br>10 60<br>0706<br>1108 12<br>0 13<br>10<br>151409 40<br>-10 09<br>16 17<br>18<br>20 09<br>-20<br>10<br>1112<br>19 1908 0 671615 1 34 17 18<br>-30 0<br>-40<br>-20<br>-40 -30 -20 -10 0 10 -20 0 20 40 60<br>Reported % Chg. Real GDP Reported % Chg. Real GDP<br>Venezuela Zimbabwe<br>Reported Composite Difference Reported Composite Difference<br>2009 46.70 19.89 26.82<br>* 29.81 16.89<br>2019 -43.08 -27.71 -15.37<br>Composite Estimate Composite Estimate<br><!-- End of picture text --> Figure 8: Hyperinflation.

important to measure such uncounted income since civil wars are much more likely to occur in low-income countries where GDP is most unreliable (Blattman and Miguel, 2010).

**Oil Supply.** Figure 10 depicts Azerbaijan and Nigeria, both Grade C countries which experienced issues pertaining to oil in the sample. Thus, Azerbaijan reported world-leading GDP growth of 29.61% in 2006 and 22.68% in 2007. Much of this was due to the completion of the Baku-Tbilisi-Ceyhan oil pipeline which began moving oil pumped in Azerbaijan to world markets. While this no doubt resulted in a sudden increase in income, the question we may ask with satellites is how much of this is reflected in actual, measurable economic activities within Azerbaijan, rather than ledger income entries upon which GDP is based. We find evidence of slightly less steep inclines in economic activity, at 20.44% in 2006 and 16.43% in 2007.

Nigeria, Africa’s largest economy, on the other hand experienced the first decline in its GDP in 25 years in 2016. This was primarily attributed to a decline in oil prices. We find that the reported decline of -1.63% may not have existed; in fact, the economy may have _grown_ by up to 0.74% that year. We note that, similar to Zimbabwe, over 60% of Nigeria’s overall economic activity is thought to arise from shadow economies (Omodero, 2019). At the same time, we find that the actual increase in Nigerian output during the 2009 Financial Crisis may have been 2.68%, less than previously thought, perhaps also due to similar concerns.

29
|Table 4.4|Balance of payments in 2012 and by simulation for 2013-2030 (Percent of nominal GDP)... 27|
|---|---|
|Table 4.5|Sectoral GDP shares in 2012 and by simulation for 2012-2030 (Percent of nominal GDP at<br>factor cost) .............................................................................................................................. 28|
|Table 4.6|Real GDP at factor cost by sector: level in 2012 (constant US$ million) and growth 2013-2030<br>by simulation (Percent per year) ............................................................................................. 28|
|List of Appe|ndices|
|Appendix 1|Figures with Simulation Results .............................................................................................. 29|
|Appendix 2|The MAMS Database ............................................................................................................... 37|

iii
Kamitonda and Kushimoto using the bypass is 49 minutes. The traffic volume between Kamitonda and Kushimoto is assumed to be the design traffic volume in the ordinary state, whereas the volume in the disrupted state is assumed to be zero, based on expert opinion. The expected time for recovery in the case of a disruption of the existing route is 255 hours (10.625 days), based on the road clearance plan for a tsunami disaster prepared by MLIT.

|Table 2. C<br>Indicators|ase 2 Resilience Indicator Data|||
|---|---|---|---|
|of LoF|Relevant Data|Data source|Content|
||Traffic volume per min under theordinarystate (x�)|Design traffic<br>Volume|5.14 pcu/min<br>(7,400 pcu/day)|
||Traffic volume per minwithoutthe project under thedisruptedstate (x�)||0 pcu/min|
|Ei|Travel time between representative OD (Kamitonda – Kushimoto)without<br>the project under theordinarystate (t<sup>�����</sup>)|Route search<br>system|60 mins|
|conomc<br>Loss|Travel time between representative OD (Kamitonda – Kushimoto)withthe<br>project under theordinarystate (t<sup>����</sup>)|Route search<br>system|49 mins|
||Travel time between representative OD (Kamitonda – Kushimoto)without<br>the project under thedisruptedstate (t<sup>�����</sup>)|Route search<br>system|119 mins|
||Travel time between representative OD (Kamitonda – Kushimoto)withthe<br>project under thedisruptedstate (t<sup>����</sup>)|Route search<br>system|49 mins|
||Population of coverage area (Kinan Area) (Pop<sup>����</sup>)|Population<br>statistics|243,025|
||The percentage of population who can access major hospitals in 30<br>minuteswithoutthe project under theordinarystate|Route search<br>system|78.1%|
|Saving<br>Lives|The percentage of population who can access major hospitals in 30<br>minuteswiththe project under theordinarystate|Route search<br>system|78.5%|
||The percentage of population who can access major hospitals in 30<br>minuteswithoutthe project under thedisruptedstate|Route search<br>system|52.8%|
||The percentage of population who can access major hospitals in 30<br>minuteswiththe project under thedisruptedstate|Route search<br>system|52.8%|
|Relief|The number of isolated populationwithoutthe project (Pop�<br>�����)|Population<br>of|61,571|

27
# **_1. Introduction_**

For decades, Kenya has suffered from low and volatile economic growth—per capita real GDP growth averaged 1.2 percent over the period 1960-2000, overwhelmed by a standard deviation of 4.8 percent.<sup>3</sup> More recently, notwithstanding deeply-entrenched skepticism, Kenya has done well on growth and macroeconomic stabilization. Over the four years 2003-2006, growth averaged 4.9 percent in contrast to virtual stagnation between 1991 and 2002.<sup>4</sup> Inflation remained relatively contained at an average 9 percent, but more convincingly, the ratio of government debt-to-GDP fell by 5.8 percentage points _per year_ over this period as interest rates fell and growth picked up. These impressive developments fueled optimism that Kenya might at last be turning the corner and embarking on a path of sustained growth and poverty reduction. However, the violent and disruptive aftermath of the Presidential elections of December 2007 have placed such optimism on hold.

# 1.1  Objectives and Background

Kenya’s reputation has been overshadowed to such an extent by its image of being corrupt and weakly governed that it might come as a surprise that serious reform began as early as 1993. We highlight the crucial role played by declining political risk after 2002 in at last bringing the reforms implemented by Kenya over the previous decade to fruition. Our analysis was completed before the December 2007 elections. It began in mid-2006, at which point our priors were formed on the basis of available reports. Typical were the following quotes from the May 2006 Economist Intelligence Unit report:<sup>5</sup> _The president....will struggle to see out the remainder of his term because of the damage to his authority and credibility caused by the “no” vote in the constitutional referendum and corruption scandals that have led to the resignation of three senior ministers._ _The Government of National Unity continues to confront serious divisions...._

> 3 Hnatkovska and Loayza (2005), Appendix A pp. 95-96.

> 4The 2007 growth estimate is 6.8 percent, a little short of 5 percent per capita. For 8 out of 12 years from 1991 to 2002, per capita income growth was almost zero or negative.

> 5 All three quotes from “Kenya at a glance: 2006-07” of _Country Report Keny_ a May 2006, EIU.

2
16

-

- * Quarterly and annual gas for delivery during a specified quarter or year.

-

- * Time spread gas for delivery against gas under contract for a different time of delivery.

The products most commonly traded in the U.K. spot markets are day-ahead and monthly gas contracts for delivery to the Bacton or St. Fergus terminals.

The U.K. spot markets are still generally thin, illiquid, and volatile. Trading volume ranges from 2 million to 8 million therms a day, 5 to 10 percent of the total daily supply. - Prices vary accordingly ranging from 9 to 14 pence a therm (table 2 and figure 3) Traded volumes and prices are reported by the media or specialized newsletters, such as British Spot Gas Markets, published by PH Energy Analysis, and European Natural Gas Daily, published by Petroleum Argus. British Spot Gas Markets introduced the Heren Index, which is the weighted average price of traded gas contracts for delivery in a particular month. The index, which is based on volume andl price information collected from traders, is an indicator of the market price of short-term, gas and is increasingly used as a price reference in bilateral contracts (Powel 1996).

**Table 2 Spot Market Prices and Volumes at the Bacton Tterminal, June-July 1996**

|Indicator|June 1996|July 1996|
|---|---|---|
|Heren Index (pence per thern)|12.1275|9.6546|
|Number of transactions|38|35|
|Total volume (millions of therms|2.278|2.072|
|per day)|||
|Lowest price (pence per therm)|10.50|9.00|
|Highest price (pence per therm)|13.575|11.5|
|Smallest volume (therms per day)|18,000|15,000|
|Largest volume (therms per day)|250,000|300,000|
|Source: The Heren Index, July 1996|||

The most important issue in the further development of spolt markets in the U.K. is the need for a standardized gas contract. An efficient short-termn market should facilitate the pricing of gas according to the system short-run marginal cost of gas. A short-term gas contract has fewer parameters than a long-term gas contract, which includes a number of delivery characteristics in addition to price. A standardized short-term contract specifying a delivery to a major terminal or an interconnection in the pipeline system therefore improves the efficiency of trading short-term gas. The introduction of the "on-system" market at the National Balancing Point in BGT's pipeline system provides a "systemwide" trading point for such a contract. This is complemented by the activities of the International Petroleum Exchange (IPE) to launch the trading of standardized physical and financial gas contracts at the National Balancing Point. The IPE has succeeded in
# **Table 4: Sensitivity of penetration level of energy efficiency measures in the mitigation scenario**

# **(a) Armenia**

|Energy efficiency|Margin<br>|al abatement c<br>(US$/tCO2)<br>|ost<br>|Reducti<br>(‘0|on of CO2emi<br>00 tons of CO2<br>|ssions<br>)<br>|
|---|---|---|---|---|---|---|
|measures|Main|Sensitivityan<br>|alysis<br>|Main|Sensitivitya<br>|nalysis<br>|
||analysis|1%<br>decrease|1%<br>increase|analysis|1%<br>decrease|1%<br>increase|
|||Residential b|uildings||||
|Lightbulbs|-199.8|-199.8|-199.8|5861.5|5036.1|6633.6|
|Refrigerators|-96.1|-95.6|-96.4|2894.4|2388.5|3353.4|
|Air conditioners|-119.0|-115.5|-121.5|1089.3|923.2|1240.8|
|TV sets|56.2|61.5|52.3|1538.3|1331.6|1727.8|
|Insulation|-125.6|-125.6|-125.6|4587.9|4587.9|4587.9|
|||Commercial|buildings||||
|Air conditioners|29.4|36.0|23.7|115.5|110.3|120.2|
|Public lighting|-72.2|-72.0|-72.4|353.9|307.7|397.1|

## **(b) Georgia**

||Marg|inal abatement<br> (US$/tCO2)|cost|Reduct<br>(‘0|ion of CO2emi<br>00 tons ofCO|ssions<br>2)|
|---|---|---|---|---|---|---|
|||Sensitivity an|alysis|Main<br>analysis|Sensitivity an|alysis|
|Energy efficiency<br>measures|Main<br>analysis|1%<br>decrease|1%<br>increase||1%<br>decrease|1%<br>increase|
|||Resident|ialbuildings||||
|Refrigerator|-138.9|-105.3|-149.3|100|41|157|
|Televisionsets|80.9|85.4|78.7|169|113|224|
|Washingmachine|-5.9|11.9|-12.7|28|15|41|
|Lightbulbs|-164.2|-159.7|-167.1|975|785|1,160|
|Double-glazed<br>windows|-55.7|-51.3|-|1,639|1,495|-|
|Roof insulation|-63.3|-62.3|-64|508|393|622|
|Wall Insulation|-27|-26.1|-27.5|843|563|1,124|
|||Commerc|ialbuildings||||
|Public Lights|-123.9|-112.5|-131.7|109|84|133|
|Lightbulbs|-239.9|-236.1|-242.2|540|438|637|
|Double-glazed<br>windows|-88.9|-79.4|-|118|82|-|
|Roof insulation|-109|-108.7|-109.2|399|342|451|
|Wall Insulation|-55|-54.7|-55.2|550|465|627|

19
Policy Research Working Paper 6637

# **Abstract**

The Amazon Rainforest is a global public good. As such, and given that 15 percent of the original Amazon forest area has already been lost, households worldwide might be willing to pay to reduce or avoid additional losses. A full elicitation of global preferences for valuing preservation of the current forest, using stated-preference population surveys, would be costly and time consuming. Alternatively, this paper uses a Delphi stated-preference technique in which 48 European environmental valuation experts were asked to provide “best guesses” on the possible outcomes of population surveys in their own countries and Europe as a whole. The expert judgments indicate willingness to pay in Europe for preserving the current Amazon Rainforest of about 28 € per household per year on average; a slightly lower value is inferred for a plan that allows a 10 percent future reduction from the current rainforest area. The income elasticity of experts’ stated willingness to pay with respect to per-capita income in their own countries is in the range 0.5–0.8. These findings indicate that Delphi studies might be used more widely as a tool for global benefit transfer.

This paper is a product of the Environment and Energy Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at jstrand1@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
- 12 -

Table 2

# United States "301" Cases Completed through August 15, 1991

# by Outcome and Country Group

|_Target country,_<br>_by group_|_Total_|_Negative_<br>_Dtei.rmination_|_Tarre Cou_<br>_Multilkeral_|_ntry Liberali_<br>_Bilateral_|_zation_<br> <br>_Total_|_US_<br>_Retaliation_|_Other_<br>_Reatrichtv_<br> <br>_OUjCOmeaSJ_|
|---|---|---|---|---|---|---|---|
|AN Countrsa||||||||
|fNurnber of cas.s|74|11|35|12|47|10|5|
|(% of total number)|(100)|(15)|(47)|(16)|(64)|(14)|(7)|
|Develoed Countriest||||||||
|Number of cases|47|7|17|9|26|8|5|
|(% of total number)|(100)|(15)|(36)|(19)|(55)|(17)|(11)|
|Developing Countries||||||||
|Number of cases|26|3|18|3|21|2|2|
|(% of total number)|(100)|(12)|(69)|(12)|(81)|(8)|(8)|
|Developing exd. Korea||||||||
|Number of cases|18|3|13|1|14|1|0|
|(% of total number)|(100)|(17)|(72)|(6)|(78)|(6)|(0)|
|Korea||||||||
|Number of cases|8|0|5|2|7|1|0|
|(% of total number|(100)|(0)|(63)|(25)|(88)|(13)|(0)|

Source: Tabulated from Office of the US Trade Representative, "Section<sup>301 Table of Cases,' Washington, DC, USTR,</sup> August 15, 1991, photocopied.

- _a/l_ In three of these, on the US govemment's recommendation the petitioner withdrew his<sup>"301" petition and</sup> petitioned instead for an import-restrcting action - an antidumping or a safeguards action. One of the others was the Canadian softwood lumber case, in which Canada imposed an export tax.<sup>The fifth was the Japanese</sup> semiconductor case in which Japan agreed to import more US semiconductors<sup>and to observe a minimum</sup> price on Japanese sales in third markets.

- b/ In 1979 a US firm complained about the Swiss customs service's testing of<sup>the gold content of</sup><sup>**eyegass**</sup> frames. USTR's investigation revealed that US standards for testing and making<sup>gold content were different</sup> from those used by many other countries. The US industry agreed to<sup>shift to the more common standards and</sup> markings which the Swiss customs service would accept without further testing.<sup>This action is claified as</sup> "liberaliation by the US," and does not fit into any of the categories listed in this table.
# **8. REFERENCES**

Adams, R. (2003), “International migration, remittances and the brain drain: a study of 24 labor-exporting countries”, World Bank Policy Research Working Paper No. 2972.

Barro, R.J. and J.W. Lee (2000), “International Data on Educational Attainment: Updates and Implications”, CID Working Papers 42, Center for International Development (Harvard University).

Beine, M., F. Docquier and H. Rapoport. 2008. “Brain Drain and Human Capital Formation in Developing Countries: Winners and Losers.” _Economic Journal_ 118 (April): 631-52.

Bhorat, H., J-B. Meyer and C. Mlatsheni (2002), “Skilled labor migration from developing countries: study on South and Southern Africa”, ILO International Migration Papers, International Labor Office, Geneva.

Carrington, W.J. and E. Detragiache (1998), “How big is the brain drain?”, IMF Working Paper WP/98/102.

Cohen and Soto (2001), “Growth and Human Capital: Good Data, Good Results,” CEPR Discussion Papers 3025, CEPR, London.

Debuisson, M., F. Docquier, A. Noury and M. Nantcho (2004), “Immigration and aging in the Belgian regions,” _Brussels Economic Review_ (2004), Special issue on skilled migration, 47(1), 139-158.

De la Fuente, A. and R. Domenech (2002), “Human capital in growth regressions: how much difference does data quality make? An update and further results.” CEPR Discussion Paper No. 3587.

Docquier, F. et A. Marfouk (2006), “International migration by educational attainment (19902000)”, in Ozden, C. et M. Schiff (eds), _International Migration, Remittances and the Brain Drain_ , Chap 5, Palgrave-Macmillan.

Fargues, Philippe (2006) “...”in Ozden, C. et M. Schiff (eds), op. cit.

Lucas, R.B. (1988), “On the mechanics of economic development,” _Journal of Monetary Economics_ .

> Ozden, C. and M. Schiff. 2006. (eds.) _International Migration, Remittances and the Brain_ , Palgrave-Macmillan.

Rosenzweig, M.R. (2005), “Consequences of migration for developing countries”, Paper prepared for the UN Conference on International Migration and Development, Population Division.

Schiff, M. (2007), "Optimal Immigration Policy: Permanent, Guest-Worker, or Mode IV? Version 2" IZA Discussion Paper 3083, September 2007, <u>http://ftp.iza.org/dp3083.pdf .</u> Schiff, M. and Y. Wang. 2008. “North-South Trade-related Technology Diffusion, Brain Drain and Productivity Growth: Are Small States Different?” Mimeo, DECRG, World Bank.

32
employment of new migrants, the relative size of the migrant population in the local labor-market decreases it. They interpret the latter result as a congestion effect among migrants competing for jobs.

A criticism of this kind of work is that the potential endogeneity of the social network is seldom controlled for. One exception is Munshi (2003) who studies the role of social networks in the migration of Mexicans to the United States, using a panel dataset of individual location decisions and labor outcomes from multiple communities. In this work, the number of other migrants from the same origin-community is instrumented with rainfall in the origin-community since rainfall is a push factor that naturally affects rain-fed agriculture employment.<sup>28</sup> With this endogeneity control, it is found that an individual is more likely to be employed and to hold a higher paying job when his network is larger.

**Policy implications** -- These works suggest that education or social networks can help migrants in their gradual process of labor-market assimilation in the city even though _the specific channels through which networks and education operate are not identified_ . These channels probably include different kinds of support or opportunities that migrants may lack. In this respect, policies that could help migrants overcome assimilation barriers are diverse. Measures can aim at improving the bargaining power of migrants on the labor-market, for instance through sharing information and collective negotiation (Mosse _et al._ , 2002). Governments can see to it that migrants, and especially poor migrants, are not credit rationed so that entrepreneurship is not discouraged, that migrants are not discriminated against in the housing market, and that they find a satisfactory access to public goods, including child care, health and education.<sup>29</sup> Supporting the political involvement of migrants in local politics can help migrants ensure that their needs are taken into account by local policy makers. Several other measures can ensure the protection of rural migrants in cities, providing them with information on labor legislation and rights, favoring their unionization, and ensuring that they hold written

> 28 This instrument may nevertheless be less relevant when agriculture is irrigated in rural areas. 29 In China for instance, rural migrants still face strong obstacles to access healthcare services (Shaokang, Zhenwei and Blas, 2002) or to educate their children ( _China Daily_ , 2003).

36
.4 Table 1: Growth and Inflation in Eastern Europe and the former Soviet Un4on

||(P|Rea<br>ercentag|l<br>GD<br>e|P<br>Chang|e)|||<br>(Perc|Retail<br>Price<br>entage<br>Change|)||
|---|---|---|---|---|---|---|---|---|---|---|---|
|8|8|B9|90|91|92-|<br>93|B8|89|90<br>91|92|93|
|Country||||||(est.)|||||(est.)|
|Albania<br>.||||-30|-8|3|||36|200|130|
|Armenia||||-12|-50|-10|||100|1350|na|
|Azerbaijan||||-2|-30|-10|||138|1350|na|
|<br>Belarus|||.|-3|-11|-3||.|80|1076|1300|
|Bulgaria|.3|-2|-9|-12|-8|-5|2|6|26<br>334|83|<br>90|
|Croat:-ia||||-29|-11|-5|||123|664|790|
|Czechoslovakia|3|1|-1|-14|-7|na|0|2|11<br>.<br>57|11|20|
|EstonLa||||-13|-26|-10|||212|1050|200|
|Georgia||||-25|-30|-10|||81|1800|na|
|<br>Hungary|0|0|-4|-12|-S|-2|16|17|29<br>35|23|23|
|Kazakhstai||||-8|-13|-15|||91|1381|1000|
|Kyrgyzstan||||-5|-25|-16|||85|855|_600_|
|<br>Latvia||||-8|-44|-10|||172.|951|250|
|Lithuania||||-13|-35|-10|||225|1021|. 690|
|Macedonia||||-11|-15|-7|||115.|1691|<br>580|
|Noldova||||-12|-2-|-15|||_98_|1460|1000|
|Poland|:|0|-11|-7|1|.2|60|251|586<br>70|43|39|
|-Romania|1-|-7|-7|-14|-15|-9|3|1|7<br>161|210|210|
|Russia||-||-11|-19|-15||2|6<br>93|1354|1000|
|Slovak|3|1|0|-16|-6|-8|0|2|11<br>61|10|25|
|Slovenia|||-|-|-r|-1|||15S|207|47|
|Tajikistan||||-9|-32|-18|||103|1450|na|
|<br>Turkmenistan||||-7|-12|-9|||90|980|na|
|Ukraine|2|4|-4|-14|-14|-10|0|2|4<br>91|1450|1450|
|Uzbekistan||.||-1|_-14_|-10|||82|700|na|

Source: The Economics of Transition, vol. 1, no. 3 (September 1993): pp. 370-378.The situation could not have been more different in China. Reform there began at the end of 1978. Since then, GNP has grown at phenomenally high rates while prices have remained relatively stable (see Figure 1). Whether China's reforms provide any general implications for other reforming economies is the subject of lively debate. Several economists argue that China's success poses a challenge to the conventional wisdom that stabilization, liberalization and privatization are key to successful reform (McMillan and Naughton, 1992; Singh 1 991; Chen etal, 1992; Harrold 1992; Perkins 1992; McKinnon 1993). Theymaintain that China's recent economic history demonstrates the superiority of evolutionary,