Refine your search
Collections
Co-Authors
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Bhatt, M. S.
- Counting Child Labour in India: A Critique of Epistemology
Abstract Views :373 |
PDF Views:1
Authors
Affiliations
1 Department of Economics, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, IN
1 Department of Economics, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, IN
Source
Artha Vijnana: Journal of The Gokhale Institute of Politics and Economics, Vol 52, No 2 (2010), Pagination: 113-132Abstract
This paper underscores the significance of reliable and up-to-date data bases on child labour for an informed understanding of policy formulation, implementation and evaluation. The available data sources on child labour in India have been examined to illustrate the arguments. The paper concludes that, the available data bases have indeed proved helpful in understanding some critical dimensions of child labour. But these do not capture all the dimensions of child labour and hence cannot be fully trusted for a systematic analysis of the processes of socialization of children or even policy formulation for the abolition of child labour. There is need for fresh data generation on a sustained basis. The paper is organised in three sections. Section I explains the backdrop of the subject. Section II deals with the epistemological issues using the available data bases on child labour as the reference material. The last section presents summary and conclusions.
- Tin Scarcity in India: Evidence from a Structural Time Series Approach
Abstract Views :464 |
PDF Views:0
Authors
Affiliations
1 Department of Economics, JamiaMillia Islamia, New Delhi 110025, IN
2 ICAR-National Institute of Agricultural Economics and Policy Research, DPS Marg, PUSA, New Delhi 110012, IN
1 Department of Economics, JamiaMillia Islamia, New Delhi 110025, IN
2 ICAR-National Institute of Agricultural Economics and Policy Research, DPS Marg, PUSA, New Delhi 110012, IN
Source
Artha Vijnana: Journal of The Gokhale Institute of Politics and Economics, Vol 62, No 2 (2020), Pagination: 121-140Abstract
The paper evaluates the Resource Scarcity Hypothesis in the case of tin, a strategic metal in the Indian economy, using data from 1958 till 2013. Estimation was carried out using the Structural Time Series Model. Results of model estimations identify a stochastic long term growth with significant cyclical movements. Compared to the large amplitude of the cycles, the growth rate of the long-term trend is small and punctuated by structural breaks. Our approach provides a flexible and reasonably accurate fitting procedure for quantifying the effects of separate structural components. On the whole, the model works well as a description of resource prices but does not support the resource scarcity hypothesis. Results of the present study can help in the formulation of an informed policy response to the problems associated with the growing demand fort in India.References
- Agbeyegbe, T.D. (1989), Interest Rates and Metal Price Movements: Further Evidence, Journal of Environmental Economics and Management,16(2): 184–92.
- Ahrens, W.A. and V.R. Sharma (1997), Trends in Natural ResourceCommodity Prices: Deterministic or Stochastic?, Journal of Environmental Economics and Management, 33(1): 59-74.
- Bai, J. and P. Perron (1998), Estimating and Testing Linear Models with Multiple Structural Change, Econometrica, 66(1): 47-78.
- ---------- (2003), Computation and Analysis of Multiple Structural Change Models,Journal of Applied Econometrics,18(1): 1-22.
- Berck, P. and M. Roberts (1996), Natural Resource Prices: Will They Ever Turn up?, Journal of Environmental Economics and Management, 31(1): 65-78.
- Bernard, J.T., L. Khalaf and M. Kichian (2004), Structural Change and Forecasting Long-run, Energy Prices, Bank of Canada,Working Paper.
- Cuddington, J.T. and D. Jerrett (2008), Super Cycles in Real Metals Prices, IMF Staff Papers, 55(4): 541-565.
- Elder, J. and A. Serletis (2008), Long Memory in Energy FuturesPrices, Review of Financial Economics, 17(2): 146-155.
- Erten, B. and J.A. Ocampo (2012), Super-Cycles of Commodity Prices since the Mid-Nineteenth Century, UN-DESA,Working paper No. 110.
- Fisher, A.C. (1979), Measures of Natural Resource Scarcity, in:Smith, V.K. (Ed.),Scarcity and Growth Reconsidered,Baltimore, JohnsHopkins University Press, pp. 198-224.
- Hanley, Nick, J.F. Shojren and B. White (1997), Environmental Economics— Theory and Practice, Macmillan India, LTD.
- Harvey, A. (1997), Trends, Cycles and Auto-regressions,Economic Journal, 104(440):1324-1345.
- Harvey, A.C. (1989), Forecasting, Structural Time Series Models and the Kalman Filter, Cambridge University Press, London.
- Herfindahl, O.C. (1959), Copper Costs and Prices: 1870-1957, Johns Hopkins Press, Baltimore.
- Hotelling, H. (1931), The Economics of Exhaustible Resources, Journal of Political Economy, 39(2):137-175.
- Howie, P.A. (2002),A Study of Mineral Prices: Analyzing Long-term Behavior and Testing for Non-competitive Markets,Ph.D. Dissertation, Colorado School of Mines, Golden, CO.
- Indian Minerals Yearbook-Part- II : Metals & Alloys, 52nd Edition, Advance Release (2014),INDIAN BUREAU OF MINES, GOVERNMENT OF INDIA, Indira Bhavan, Civil Lines, NAGPUR – 440 001.
- International Monetary Fund (2010), World Economic Outlook: A Survey by the Staff of the International Monetary Fund, International MonetaryFund ,Washington, D.C.
- Kalman, R.E. (1960), A New Approach to Linear Filtering and Prediction Problems---, Transactions of the ASME, Journal of Basic Engineering, 82(Series D): 35–49.
- Koopman, S.J., A.C. Harvey, J.A. Doornikand N. Shephard (2009), Structural Time Series Analyser, Modeller and Predictor, London, Timberlake Consultants.
- Lee, C. and J.D. Lee (2009), Energy Prices, Multiple StructuralBreaks, and Efficient Market Hypothesis, Applied Energy, 86(4): 466–479.
- Lee, J., J. List and M.C. Strazicich (2006), Non-renewable Resource Prices: Deterministic or Stochastic trends? Journal of Environmental Economics and Management, 51(3): 354-370.
- ---------- (2003), Minimum Lagrange Multiplier Unit Root Test with two Structural Breaks, The Review of Economics and Statistics, 85(4): 1082-1089.
- Livernois, John (2009), On the Empirical Significance of the Hotelling Rule, Review of Environmental Economics and Policy,3(1): 22–41.
- Lund, D. (1993),The Lognormal Diffusion is Hardly an Equilibrium Price Process for Exhaustible Resources, Journal of Environmental Economics and Management, 25(3): 235-241.
- Mackellar, F.L. and D.R. Vining (1989), Measuring Natural Resource Scarcity, Social Indicators Research, 21(5): 517-530.
- Maslyuk, S. and Smyth, R. (2008), Unit Root Properties of CrudeOil Spot and Futures Prices, The Energy Policy, 36 (7): 2591-2600.
- Mu, X., and Ye, H. (2015), Small Trends and Big Cycles in CrudeOil Prices, The Quarterly Journalof the IAEE's Energy Economics Education Foundation, 36(1): 49-72.
- Ozdemir, Z.A., K. Gokmenoglu and C. Ekinci (2013), Persistence in Crude Oil Spot and Futures Prices, Energy, 59: 29-37.
- Perron, P. (1989), The Great Crash, Oil Price Shocks and the Unit Root Hypothesis, Econometrica, 57(6): 1361–1401.
- Pindyck, R.S. (1999), The Long-run Evolution of Oil Prices, The Energy Journal, 20(2): 1-26.
- Presno, M.J., M. Landajo and P. Fernández (2014), Non-renewableResource Prices: A Robust Evaluation from the Stationarity Perspective, Resource and Energy Economics, 36(2): 394-416.
- Sadorsky, P. (1999), Oil Price Shocks and Stock Market Activity, Energy Economics, 5(5): 449- 469.
- Serletis, A. (1992), Unit Root Behavior in Energy Futures Prices, Energy Journal, 13(2): 119-128.
- Slade, M.E. (1982), Trends in Natural-resource Commodity Prices: An Analysis of the Time Domain, Journal of Environmental Economics and Management, 9(2): 122-137.
- Slade, M.E. (1988), Grade Selection under Uncertainty: Least Cost Last and Other Anomalies, Journal of Environmental Economics and Management, 15(2): 189-205.
- Tilton, J.E. (2002), On Borrowed Time--- Assessing the Threat of Mineral Depletion,Resources for the Future,Washington, D.C.
- World Economic Outlook (2010), Rebalancing Growth, International Monetary Fund, Research Department.