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Jan 2010 : 2,100 Czech Koruny are worth about $117 US Dollars.

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Q: What is the us dollar value of 2100 korun ceskych?
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Since supply curves are upward sloping you would never see an increase in price accompanied by a decrease in quantity traded True or False?

34. As the price of beach front cottages in Florida was raised from $400,000 to 500,000, their quantity supplied rose from 2000 to 2100. Using the are convention, the elasticity of supply of beach front cottage is:


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Current scenario of e-business in term of Indian economy?

1 Purnamita Dasgupta Institute of Economic Growth, Delhi National Workshop2 Objectives • To develop alternative socio-economic scenarios that take into consideration a sustainable development objective for India • To develop a conceptual frame for indicative economic costs of policies for adaptation to climate change, specific focus on vulnerable groups. • To illustrate the methodology with detailed studies, focusing on agriculture as a key sector3 Methodology • Key markers of socio-economic vulnerability and adaptive capacity were identified • These include Geographical (inter-state variation and coastal location), Demographic (inter-state population distribution) and Coping vulnerability (income differentials and access to basic facilities) • Socio-Economic variables impacting each of the above (through either an increase/decrease in vulnerability) are then interacted in a dynamic simulation model • Model provides: (a) alternative development pathways through short to medium term projections over (b) varying time scales (c) key parameters which can be influenced to achieve desirable outcomes for decreasing vulnerability. 4 Gross Domestic Product Poverty Reduction Sectoral Gross Domestic Product Food security Unemployment Reduction Access to Basic Services Share of Agriculture Sector Food grain Production Conceptual Frame - Economy and Agriculture Module5 Area under Food grain Profitability Technology Climatic Factors Irrigation Other Socio-Economic Factor Share of Primary Sector Education Infrastructure Food Production Population Per Capita Production Conceptual Frame: Dynamic Simulation of Food grain Production6 Gross Domestic Product Poverty Reduction Food Security, Unemployment Reduction, Acess to Basic Services Sectoral Gross Domestic Product Share of Agriculture Sector Area under Foodgrain area change due to change in profitability factor change in relative profitability irrigated area food grain non-irrigated area foodgrain change in area foodgrain Proportion of land irrigated <Time> food production Yield (irrigated) Yield (nonirrigated) Per capita production Population in2 <Time> <Time>7 Emerging Scenarios • Time scale from current time period till 2030 • Reference scenario has current expectations and assumptions of structural stability, and, concerns for vulnerability without climate change impacts - results available • Optimistic Scenario improves on reference with rapid technological progress and adaptive strategies - results available • Longer term Scenario Simulation - in progress • Indicative Costs - framework developed; ongoing work 8 Variable Reference Scenario Optimistic Scenario GDP growth rate (2020-2030) 7 % 8 % Unemployment Rate 1% 1% Income Poverty (Percentage BPL) 5% 5% Sectoral Shares in GDP: Primary: (Secondary + Tertiary) 0.15: 0.85 0.10:0.90 Per capita Food Grain Production 182 kgs 198 kgs Urbanisation 0.45 0.50 Access to basic amenities 100% 100% Socio-Economic Scenarios for the Indian Economy, 20309 Per Capita Foodgrain Production 170.00 175.00 180.00 185.00 190.00 195.00 200.00 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 2017-18 2018-19 2019-20 2020-21 2021-22 2022-23 2023-24 2024-25 2025-26 2026-27 2027-28 2028-29 2029-30 reference scenario optimistic scenario10 Uncertainty Issues • TFP, technological progress • Limiting - cap values : land availability, irrigation potential, population, relative international prices • Turning points - thresholds : where these lie and extent of certainty of occurrence Quality Assurance • Face Validity through repeated iterations - expected and consistent signs and directions of flows • Historical behaviour tests • Reality checks with extreme values for parameters 11 Adaptation Framework • Response Levels - Variables determining potential for adaptation: education, technological development - Variables impacted by the potential: e.g. water use efficiency • Drivers of Change - Policies - State; Initiative - Public or Private or both - Agency - State as Enabler; Individual and Civil society - diffusion, uptake, funding12 Adaptation Framework • Costs - Knowledge Advancement Costs : Awareness and Media, R & D, Institutional Development - Sustainability Transition Costs: building a climate resilient society - most sectoral, context specific approaches/estimates capture these (on track with developmental goals) e.g.: R & D to installation of early warning systems; from institutional development to crop insurance at incremental premiums for climate change13 Some Conceptual Concerns • Developmental goals well defined for short term (e.g. MDGs); taken care of in setting the time frames and targets (e.g. literacy, poverty, access to basic amenities) • Adaptation Costs - in short run cover for derailment of the economy from the desired time path • Currently available CC data for 2071-2100; socio-economic modeling limitations beyond 2030. • Therefore, adopt a Systems Equilibrium approach ---- Moving from last three decades till 2004-05, to a future 30 year period: 2071 to 2100. Advantage - CC data available, disadvantages - too much uncertainty to risk putting one number to it, even for the economist!!! For the present, See Adaptation costs in terms of directions of change. Illustrate for food grain production.14 Food grain prod. 2004-05 10.54 10.5 13.4 12.15 5.26 37.84 14.1 13.11 25.67 16.0615 Foodgrain prod. 2030 (opt.) 15.19 11.18 14.28 12.93 5.6 40.28 26.04 13.96 27.34 17.1216 Foodgrain prod. 2071, 2100 21.56 17.18 18.86 22.74 15.77 31.95 27.3 19.73 23.93 20.64 18.85 17.93 20.91 18.32 18.83 24.26 20.63 24.82 28.91 24.3417 Relative Change in foodgrain production State Name 2030 relative to 2004-5 2071 relative to 2030 2100 relative to 2071 Andhra Pradesh + + + Gujrat + + + Haryana + + + Karnataka + + + Madhaya Pradesh + + - Maharastra + + - Punjab + - + Rajasthan + + - Uttar Pradesh + - - West Bengal + + + India + - -18 Indicative Transition & Knowledge Costs Adaptation to changing water availability for agriculture in vulnerable areas • Costs of weather insurance for typical rainfed agriculture - private (esp. large and medium); social / government (small and marginal) • Cost of water saving technology (drip and sprinkler irrigation) - mostly private costing • Cost of R & D in low water using crops - social/ government cost • Cost of institutional development and resilience build up for first two - both private and public; not so for last. Rather, private agent may have incentive to move into different land use. 19 Adaptation Costs • Various definitions and conceptual inconsistencies exist in adaptation literature and available estimates • Anticipated costs which maybe incurred by public and private agents to plan for a change foreseen with reasonable accuracy • Critical - precision of extent and probability of climate change impacts; incremental attributable to CC; agency which bears the cost. • Adaptation Funding for apportioning of costs between 2010 and 2100 • NREGA, BPL 20 % NREGA employment , % BPL 2.78 26.97 0 42.5 10.63 16.33 14.74 15.65 2.56 18.9421