International Journal of Econometrics and Financial Management

ISSN (Print): 2374-2011

ISSN (Online): 2374-2038

Website: http://www.sciepub.com/journal/IJEFM

Article

Impact of ADP on GDP in Bangladesh: A Cointegration Approach

1Lecturer in Economics, Chibbari M. A. Motaleb College, Satkania, Chittagong, Bangladesh

2Graduate Research Assistant, Department of Economics, South Dakota State University, Brookings, USA

3Professor, Departmentof Economics, University of Chittagong, Chittagong, Bangladesh


International Journal of Econometrics and Financial Management. 2015, 3(2), 44-56
DOI: 10.12691/ijefm-3-2-1
Copyright © 2015 Science and Education Publishing

Cite this paper:
Mahi Uddin, Niaz Murshed Chowdhury, Mudabber Ahmed. Impact of ADP on GDP in Bangladesh: A Cointegration Approach. International Journal of Econometrics and Financial Management. 2015; 3(2):44-56. doi: 10.12691/ijefm-3-2-1.

Correspondence to: Mahi  Uddin, Lecturer in Economics, Chibbari M. A. Motaleb College, Satkania, Chittagong, Bangladesh. Email: mahiecocu@gmail.com

Abstract

The main purpose of this paper is to introduce and interpret the relation between governments Annual Development Programme (ADP) and economic growth. ADP traditionally holds the main structure of Bangladesh economy. We consider ADP is the main determinant of Gross Domestic Product (GDP) in Bangladesh and also consider the Gross Capital Formation (GCF) for more reliable results. This paper uses various econometric tools where time series analysis is gained main focus to find out the proper result. According to our result, there is a positive impact of ADP on economic development. Findings point out that keeping the high level of public planning in Bangladesh together with improvement in institutional surroundings would be beneficial for economic growth. It has been widely documented that ADP can promote economic growth, when it is efficiently handled by the authority.

Keywords

References

[1]  Ahmed, H. A., Uddin, G. S. and Awrangajeb, N. U. H. (2010) “Growth, Public and Private Investment in Bangladesh: An Empirical Analysis” Conference paper on Business Competencies in a Changing Global Environment 2010, Organized by South East University, Dhaka, Bangladesh and Global Business and Management Forum (USA).
 
[2]  Ahmed, S. (2010), Problems of ADP Implementation in Bangladesh: An Analytical Review, A Dissertation Paper of MAGD, Institute of Governance Studies, BRAC University, Dhaka, Bangladesh.
 
[3]  Anderson, E., Renzio, P. de and Levy, S. (2006) “The role of public investment in poverty reduction: Theories, evidence and methods”, Working Paper 263, Overseas Development Institute, London SE 1 7 JD, UK.
 
[4]  Barro, R. J., and X. Sala-i-Martin, (1999) Economic Growth, Cambridge, MA: The MIT Press.
 
[5]  Benefits of public investment in the nations road infrastructure, Australian Automobile Association Report, Update of The Allen Consulting Group (1993) and DoTaRs (2002).
 
Show More References
[6]  Brinca, P. (2006) “The impact of public investment in Sweden a VAR approach” Msc thesis in Economics, Stockholm University, Stockholm, Sweden.
 
[7]  Bukhari, S. A., Ali, L. and Saddaqat, M. (2007) “Public investment and Economic Growth in the three little dragons: Evidence from heterogeneous dynamic panel data” International Journal of Business and Information, Volume 2, Number 1, June 2007, pp. 57-79.
 
[8]  Baltagi, Badi H., Kao, Chihwa. (2000): Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey, Center for Policy Research, WorskingPaper No. 16, New York.
 
[9]  Cavallo, E. and Daude, C. (2008) “Public investment in developing countries: a blessing or a curse?” Working paper number 648, Research Department, Inter-American Development Bank, Washington, DC 20577, USA.
 
[10]  Carter, R Hill, William e. Griffiths and Guay C. Lim, Principle of Econometrics, Fourth Edition, John Wiley & Sons, Inc., 111 River Street, Hoboken.
 
[11]  Clarida, R. H. (1993) “International capital mobility and Public investment and Economic growth” NBER Working Paper Series, Working Paper No. 4506, National Bureau of Economic Research, Cambridge, MA 02138.
 
[12]  Clements, B., Bhattacharya, R. and Nguyen, T. Q. (2003) “External debt, Public investment and Growth in low income countries” IMF Working Paper WP/03/249, Fiscal Affairs Department, International Monetary Fund.
 
[13]  Cullision, W. E. (1993) “Public investment and Economic Growth” Economic Quarterly, Volume 79/4 Fall 1993, Federal Reserve Bank of Richmond, pp. 19-33 Different reports of Implementation Monitoring and Evaluation Division (IMED), Bangladesh Government.
 
[14]  Costa, J. da Silva, R. W. Ellson, and R. C. Martin (1987) Public Capital, Regional Output and Developments: Some Empirical Evidence. Journal of Regional Science 27: 3, 419-437.
 
[15]  Deno, K. T. (1988) The Effect of Public Capital on U.S. Manufacturing Activity: 1970 to 1978. Southern Economic Journal 55: 1, 400-411.
 
[16]  Doan, T. A. (2000), Rats, User’s Guide, Estima, Evanston, IL.E-views users guide i and ii.
 
[17]  Eberts, R. W. (1986) Estimating the Contribution of Urban Public Infrastructure to Regional Growth. Federal Reserve Bank of Cleveland. (Working Paper No. 8610)
 
[18]  Fuller, W. A. (1976). Introduction to Statistical Time Series. New York: Willey.
 
[19]  Ghani, E. and Uddin, M. (2006) “The impact of Public investment on Economic Growth in Pakistan” The Pakistan Development Review, 45: 1 (Spring 2006) pp. 87-98.
 
[20]  Gonzalez, R. L. and Montolio, D. (2011) “Growth, Convergence and Public Investment A Bayesian Model Averaging Approach”.
 
[21]  Gerd S, Ana C, and Funke, K Public Investment and Public-Private Partnerships, International Monetary Fund, pp. 21-36.
 
[22]  Gregory, N Mankiw (2002), Economic Policy Institute, Briefing Paper # 34A, USA
Macroeconomics, 5th edition, Worth Publishers.
 
[23]  Gujarati, Damoder N. Basic Econometrics, Fourth Edition, McGraw-Hill Higher Education.
 
[24]  Haque, M. E. and Kneller, R. (2008) “Public investment and Growth : the rule of corruption” Discussion Paper Series Number 098, Centre for Growth & Business Cycle Research, University of Manshester, Manchester.
 
[25]  Hsiao, Cheng: Analysis of Panel Data, Second Edition, Cambridge University Press, New York, 2003.
 
[26]  http://en.wikipedia.org/wiki/Economy_of_Bangladesh#p-search 81
 
[27]  http://www.investorwords.com/2599/investment.html#ixzz1UQ8VvErw Hussain, Z. (2009) Is Bangladesh getting public investment right?, World Bank
 
[28]  Jimenz, E. (1995) “Human and physical infrastructure: public investment and pricing polices in developing countries” Hand book of development economics, PP. 2774-2836, Volume 3 Edited by J. Behrman and T. N. Srinivasan Elsevier Science B. V 1995.
 
[29]  “Investing in Public investment: An index of public investment efficiency” IMF Working Paper WP/11/37, Strategy, Policy and Review Department, International Monetary Fund.
 
[30]  James. B and Srinivasan, T.N B. V 1995 pricing polices in developing countries” Hand book of development economics, PP. 2774-2836, Volume 3 Elsevier Science B. V 1995.
 
[31]  kalaitzidakis, P. and kalyvitisy, S. (2003) “Financing New public investment and or maintenance in public capital for long run growth” Canadian Studies Program, Department of Foreign Affairs and International Trade, Canada.
 
[32]  Kamps, Christophe: The Dynamic Macroeconomic Effects of Public Capital, Theory and Evidence for OECD countries, Springer, New York, 2004.
 
[33]  Keynes, J. M &Kuttner, R. (1992) “The Collected Writings of John Maynard Keynes” Vol. xxvii, edited by D. Moggridge (London: Macmillan, 1980), pp. 264-419 “The slow growth trap and the public investment cure”.
 
[34]  Kappeler, A and Valila, T. (2007) “Composition of Public Investment and Fiscal Federalism: Panel Data Evidence from Europe” economics and financial report 2007/02, European investment bank.
 
[35]  Kuttner, R. (1992) “The slow growth trap and the public investment cure” The Economic Policy Institute, Briefing Paper # 34A, USA.
 
[36]  Uddin, M & Aziz, S (2014) Effect of Public Investment on Economic Growth in Bangladesh: An Econometric Analysis "Journal of Economics and Sustainable Development.
 
[37]  Naqvi, N. H. (2002) Crowding-in or Crowding out? Modeling the Relationship between Public and Private Fixed Capital Formation using Co-Integration Analysis, The Case of Pakistan 1964-2000. The Pakistan Development Review, 41: 3, 255-276.
 
[38]  Pal, S. (2008) “Does public investment boost economic growth? Evidence from an open economy macro model for India” Cardiff Economics Working Papers E2008/24, Cardiff CF10 3 EU, United Kingdom.
 
[39]  Pereira, A. M. and Pinho, M. D. F. (2006) “Public investment and budgetary consolidation in Portugal” Working Paper number 41, College of William & Mary, Department of Economics, Williamsburg, VA 23187-8795, USA.
 
[40]  Peree, E. and Valila, T. (2008) “A primer on public investment in Europe”.
 
[41]  Public Investment Draft Paper (May 2009), National 5-year plan (2010-2014), Public Investment Development Committee, Republic of Iraq.
 
[42]  Romer, Paul M. (1998) Increasing Returns and Long-run Growth, Journal of Political Economy 94: 5 (October), pp. 1002-1037 Sims, C. A. (1980a). “Macroeconomics and Reality” Econometrica, 48 (10), pp. 1-48.
 
[43]  Saad, W. and Kalakech, K. (2009) “The nature of government expenditure and its impact on sustainable economic growth” Middle Eastern Finance & Economics, Issue 4 (2009), EuroJournals Publishing, Inc. 2009, pp. 38-47.
 
[44]  Sims, C. A. (1980a). “Macroeconomics and Reality” Econometrica, 48 (10), pp. 1-48.
 
[45]  Sturm, J.E.: Public Capital Expenditures inOECD Countries: The Causes and Impact of the Decline in Public Capital Spending, Edward Elgar, Cheltenham, 1998.
 
[46]  The Daily Ittefaq (10 April 2011), Dhaka, Bangladesh.
 
[47]  Zainah, P. (2009) “The role of public investment in promoting economic growth: A case study of Mauritious” Services Sector Development and Impact on Poverty Thematic Working Group, TIPS Project, Trade and Industrial Policy Strategies, Pointes-Aux-Sables, Mauritius.
 
[48]  Zhang, X. and Fan, S. (2000) “Public investment and regional inequality in rural china” EPTD discussion paper no. 71, Washington, DC 20006 USA.
 
Show Less References

Article

The Impact of the Ownership Structure and the Quality of Financial Information on the Cost of Debt of Tunisian Firms

1Depatment of Finance, Higher Institute of Management of Sousse, University of Sousse, Tunisia

2Department of Economy, Faculty of Economic Sciences and Management of Sousse, University of Sousse, Tunisia


International Journal of Econometrics and Financial Management. 2015, 3(2), 57-63
DOI: 10.12691/ijefm-3-2-2
Copyright © 2015 Science and Education Publishing

Cite this paper:
Abdelkader Derbali, Manel Ben Ayeche. The Impact of the Ownership Structure and the Quality of Financial Information on the Cost of Debt of Tunisian Firms. International Journal of Econometrics and Financial Management. 2015; 3(2):57-63. doi: 10.12691/ijefm-3-2-2.

Correspondence to: Abdelkader  Derbali, Depatment of Finance, Higher Institute of Management of Sousse, University of Sousse, Tunisia. Email: derbaliabdelkader@outlook.fr

Abstract

The objective of this paper is to highlight the interaction of the board with other internal governance mechanisms such as ownership structure, the quality of financial reporting and the cost of debt. The relationship between the ownership structure and the quality of financial information on the one hand and the other debt cost was well treated in the financial literature. Tests conducted on a sample of 28 Tunisian firms show that the ownership structure and the quality of financial information plays an important role in determining the characteristics of the cost of debt. The results also indicate that the cost of debt is related to factors from the board, the size of the company and the stock exchange listing.

Keywords

References

[1]  Agrawal, A, and Mandelker, G. (1992). Shark repellents and the role of institutional investors in corporate governance. Managerial and Decision Economics, 13, 15-22.
 
[2]  Agrawal, A. and Mandelker, G. (1990). Large shareholders and the monitoring of managers, the case of antitakeover charter amendment. Journal of Financial and Quantitative analysis, 25, 143-167.
 
[3]  Alexandre, H. and Paquerot, M. (2000). Efficacité des structures de contrôle et enracinement des dirigeants. Finance Contrôle Stratégie, 3, 2, 5-29.
 
[4]  Bathala, C. and Rao, R. (1995). The determinants of Board composition: an agency perspective. Managerial and Decision Economics, 19, 59-69.
 
[5]  Boyd, B. (1995). CEO duality and firm performance: a contingency model. Strategic Management Journal, 16, 301-312.
 
Show More References
[6]  Caby, J. and Hirigoyen, G. (2001). La création de valeur de l’entreprise, 2ème édition, Economica, Paris, p. 197.
 
[7]  Charreaux, G. and Pitol-Belin, J.P. (1990). Le conseil d'administration, VUIBERT.
 
[8]  Core, J., Holthausen, R. and Larcker, D. (1999). Corporate governance, CEO compensation and firm performance. Journal of Financial Economics, 51, 371-406.
 
[9]  Dalton, D., Daily, C., Ellstrand, A. and Johnson, J. (1999). Number of directors and financial performance: A meta-analysis. Academy of Management Journal, 42, 674-686.
 
[10]  Demsetz, H. (1983). The structure of ownership and the theory of the firm. Journal of Law and Economics, 26, 375-390.
 
[11]  Denis, D. and Sarin, A. (1999). Ownership and board structures in publicly traded corporations. Journal of Financial Economics, 52, 187-223.
 
[12]  Eisenberg, T., Sundgren, S. and Wells, M. (1998). Larger board size and decreasing value in small firms. Journal of Financial Economics, 48, 35-54.
 
[13]  Fama, E. and Jensen, M. (1983). Separation of ownership and control. Journal of Law and Economics, 26, 301-326.
 
[14]  Fernandez, C. and Arrondo, R. (2005). Alternative internal controls as substitute of the board of directors. Corporate governance: an international review, 13, 6, 856-866.
 
[15]  Godard, J. (2001). Beyond the High Performance Paradigm? An Analysis of Managerial Perceptions of Reform Program Effectiveness. British Journal of Industrial Relations, 38, 25-52.
 
[16]  Godard, L. (1998). Les déterminants du choix entre un conseil d’administration et un conseil de surveillance. Finance Contrôle Stratégie, 1, 4, 39-61.
 
[17]  Godard, L. and Schatt, A. (2000). Faut-il limiter le cumul des fonctions dans les conseils d’administration?. La revue du Financier, 127, 36-47.
 
[18]  Grossman, S. J. and Hart, O. D. (1982). Corporate Financial Structure and Managerial Incentives. The Economics of Information and Uncertainty, McCall, J.J. (ed.), University of Chicago Press.
 
[19]  Harris, M. and Raviv, A. (1991). The theory of Capital Structure. Journal of Finance, 46, 297-355.
 
[20]  Hermalin, B. and Weisbach, M. (1988). The Determinants of Board Composition. RAND Journal of Economics, 19 (4), 589-606.
 
[21]  Hermalin, B. and Weisbach, M. (1991). The Effects of Board Composition and Direct Incentives on Firm Performance.” Financial Management, 20 (4), 101-112.
 
[22]  Jensen M. C. and Meckling, W. H. (1976). Theory of the Firm: Managerial Behavior, Agency Costs and Ownership Structure. Journal of Financial Economics, 3, 305-360.
 
[23]  Jensen, M. (1993). The modern industrial revolution, exit and the failure of internal control systems. Journal of Finance, 48, 831-880.
 
[24]  Jensen, M. C. and Meckling, W. H. (1976). Theory of the firm: managerial behavior, agency costs and ownership structure. Journal of Financial Economics, 3.
 
[25]  Leland, H. and Pyle, D. (1977). Informational Asymetries, Financial Structure, and Financial Intermediation. Journal of Finance, 32 (2), 371-384.
 
[26]  Lipton, M. and Lorsch, J. (1992). A modest proposal for improved corporate governance. Business Lawyer, 59, 59-77.
 
[27]  Mak, Y. and Ong, P. 1999. Changes in ownership structure and board structure after an initial public offering, online at: http://papers.ssrn.com.
 
[28]  Minow, N. and Bingham, K. (1995). The Ideal Board. Corporate Governance, Blackwell Publishers, Cambridge, Massachusetts.
 
[29]  Patton, A. and Baker, J. (1987). Why do not directors rock the boat?. Harvard Business Review, 65, 10-12.
 
[30]  Pearce, J. and Zahra, S. (1992). Board composition from a strategic contingency perspective. Journal of Management Studies, 29, 411-438.
 
[31]  Rediker, K., and Seth, A. (1995). Boards of directors and substitution effects of alternative governance mechanisms. Strategic Management Journal, 16, 85-99.
 
[32]  Shleifer, A. and Vishny, R. (1986). Large shareholders and corporate control. Journal of Political Economy, 94, 461-479.
 
[33]  Stulz, R. (1990). Managerial discretion and optimal financing policies. Journal of Financial Economics, 26, 3-27.
 
[34]  Yermack, D. (1996). Higher market valuation of companies with a small board of directors. Journal of Financial Economics, 40, 185-211.
 
Show Less References

Article

Dependence between Non-Energy Commodity Sectors Using Time-Varying Extreme Value Copula Methods

1Faculty of Economics and Management sciences, University of Sfax, Tunisia


International Journal of Econometrics and Financial Management. 2015, 3(2), 64-75
DOI: 10.12691/ijefm-3-2-3
Copyright © 2015 Science and Education Publishing

Cite this paper:
Zayneb Attaf, Ahmed Ghorbel, Younes Boujelbène. Dependence between Non-Energy Commodity Sectors Using Time-Varying Extreme Value Copula Methods. International Journal of Econometrics and Financial Management. 2015; 3(2):64-75. doi: 10.12691/ijefm-3-2-3.

Correspondence to: Zayneb  Attaf, Faculty of Economics and Management sciences, University of Sfax, Tunisia. Email: attafi.zeineb@hotmail.fr

Abstract

In this work, our objective is to study the intensity of dependence between six non-energy commodity sectors in a bivariate context. Our methodology is to chose, in a first step, the appropriate copula flowing Akaike criteria. In a second step, we aim to calculate the dependence coefficients (Kendall’s tau, Spearman’s rho and tail dependence) using filtered data by the AR(1)-GARCH(1.1) model to study the dependence between the extreme events. Empirical results show that dependence between non-energy commodity markets increases during volatile periods but they offer many opportunities to investors to diversify their portfolio and reduce their degree of risk aversion in bearish market periods.

Keywords

References

[1]  Aloui,R., Ben Aïssa, M.S., & Nguyen, D.K. (2014). Market risk in agricultural commodity markets: a wavelet-based copula modeling approach. Working Paper, 412, Department of Research, Ipag Business School.
 
[2]  Arezki,R., Dumitrescu,E., Freytag,A & Quintynd,M. (2014). Commodity prices and exchange rate volatility: Lessons from South Africa's capital account liberalization. Journal of Emerging Markets Review, 19, 96-105.
 
[3]  Baffes John. (2007). Oil spills on others commodities. Journal of Resources Policy, 32, 126-134.
 
[4]  Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31, 307-327.
 
[5]  Ciner, C. (2001). On the long run relationship between gold and silver prices: A note. Global Finance Journal, 12, 299-303.
 
Show More References
[6]  Chkili, W,. Hammoudeh, S. & Nguyen, D. K. (2014). Volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory. Journal of Energy Economics, 41, 1-18.
 
[7]  Chuanguo Zhang & Xiaoqing Chen. (2013). The impact of global oil price shocks on China’s bulk commodity markets and fundamental industries. Journal of Energy Policy. In press.
 
[8]  Choi, K and Hammoudeh, S. (2010). Volatility behavior of oil, industrial commodity and stock markets in a regime-switching environment. Journal of Energy Policy, 38, 4388-4399.
 
[9]  Chong, J. and Miffre, J. (2010). Conditional correlation and Volatility in Commodity Futures and Traditional Asset Markets. Journal of Alternative Investments, 61-75.
 
[10]  Delatte Anne-Laure & Lopez Claude. (2013). Commodity and equity markets: Some stylized facts from a copula approach. Journal of Banking & Finance, 37, 5346-5356.
 
[11]  Erb, C.B., Harvey, C.R. (2006). The strategic and tactical value of commodity futures. Financial Analysts Journal, 62, 69-97.
 
[12]  Engle, R.F. (1982). Autoregressive Conditional Heteroskedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50, 987-1007.
 
[13]  Forbes, K., & Rigobon, R. (2002). No contagion, only interdependence: measuring stock market comovements. Journal of Finance, 57, 2223-2261.
 
[14]  Greer, R. (2000). The nature of commodity index returns. Journal of Alternative Investments, 45-53.
 
[15]  Gorton, G.B., Rouwenhorst, G.K. (2006). Facts and fantasies about commodity futures. Financial Analysts Journal 62, 47-68.
 
[16]  Genest, C., Quessy, J,F., & Rémillard, B. (2006). Goodness-of-fit procedures for copula models based on the probability integral transformation. Scandinavian Journal of Statistics, 33, 2, 337-366.
 
[17]  Hammoudeh, S., Malik, F., & McAleer, M. (2011). Risk management of precious metals. The Quarterly Review of Economics and Finance, 51, 435-441.
 
[18]  Hammoudeh, S., & Yuan, Y. (2008). Metal volatility in presence of oil and interest rate shocks. Journal of Energy Economics, 30, 2, 606-620.
 
[19]  Juan C. Reboredo. (2013). Is gold a hedge or safe haven against oil price movements?. Journal of Resources Policy, 38, 130-137.
 
[20]  Kantaporn, C,. Aree, W,. Songsak, S. & Chukiat, C. (2012). Application of Extreme Value Copulas to Palm oil prices analysis. Journal of Business Management Dynamics, 2, 1, 25-31.
 
[21]  Li Liu. (2014). Cross-correlations between crude oil and agricultural commodity markets. Journal of Physica A, 395, 293-302.
 
[22]  Leybourne, S.J., Lloyd, T.A., and Reed, G.V. (1994). The excess Co-movement of Commodity Prices Revisited. World Development, 22, 11, 1747-1758.
 
[23]  Mensi,W., Hammoudeh,S., Nguyen, D.K &Yoon,S.M. (2014). Dynamic spillovers among major energy and cereal commodity prices. Journal of Energy Economics, 43, 225-243.
 
[24]  Mensi,W,. Beljid,M,. Boubaker,A., & Managi,S. (2013). Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold. Journal of Economic Modelling, 32, 15-22.
 
[25]  Nazlioglu, S,. Erdem, C and Soytas, U. (2013). Volatility spillover between oil and agricultural commodity markets. Journal of Energy Economics, 36, 658-665.
 
[26]  Nazlioglu S. (2011). World oil and agricultural commodity prices: Evidence from nonlinear causality. Journal of Energy Policy, 39, 2935-2943.
 
[27]  Patton, A.J. (2007), Estimation of Multivariate Models for Time Series of Possibly Different Lengths, Journal of Applied Econometrics, 21, 2, 147-173.
 
[28]  Palaskas, T.B., and Varangis, P.N. (1991). Is there Excess Co-movement of primary commodity prices?: A cointegration test. Working paper series, 758, International Economie Department, The World Bank.
 
[29]  Pindyck, R.S., and Rotemberg, J.J. (1990). The Excess Co-Movement of Commodity Price. The Economic Journal, 100, 403, 1173-1189.
 
[30]  Power,G.J., Vedenov.D.V., Anderson,D.P., & Klose, S. (2013). Market volatility and the dynamic hedging of multi-commodity price risk. Applied Economics, 45, 3891-3903.
 
[31]  Qiang Ji and Ying Fan. (2012). How does oil price volatility affect non-energy commodity markets?. Journal of Applied Energy, 89, 273-280.
 
[32]  Saban Nazlioglu & Ugur Soytas. (2012). Oil price, agricultural commodity prices, and the dollar: A panel cointegration and causality analysis. Journal of Energy Economics, 34, 1098-1104.
 
[33]  Sadorsky P. (2014). Modeling volatility and correlations between emerging market stock prices and the prices of copper, oil and wheat. Journal of Energy Economics, 43, 72-81.
 
[34]  Śmiech, S., & Papież, M. (2012). A dynamic analysis of causality between prices on the metals market. In: Reiff, M. (Ed.), Proceedings of the International Conference Quantitative
 
[35]  Methods In Economics (Multiple Criteria Decision Making XVI), Bratislava: Slovakia, 221-225.
 
[36]  Reboredo J.C. (2012). Do food and oil prices co-move?. Journal of Energy Policy,49, 456-467.
 
[37]  Sklar, A. (1959). Fonctions de répartition à n dimensions et leurs marges, Vol. 8, pp. 229-231, Publications de l’Institut de Statistique de L’Université de Paris.
 
[38]  Viviana Fernandez. (2014). Linear and non-linear causality between price indices and commodity prices. Journal of Resources Policy, 41, 40-51.
 
[39]  Wang,Y., Wu, C and Yang, L. (2014). Oil price shocks and agricultural commodity prices. J Energy Economics, 44, 22-35.
 
Show Less References

Article

Dynamic Patterns of Structural Change and Economic Growth during the High Growth Regime in India: A Panel Data Analysis

1Department of Economics, Government College Jaitaran (Raj), INDIA


International Journal of Econometrics and Financial Management. 2015, 3(2), 76-83
DOI: 10.12691/ijefm-3-2-4
Copyright © 2015 Science and Education Publishing

Cite this paper:
M. R. Singariya. Dynamic Patterns of Structural Change and Economic Growth during the High Growth Regime in India: A Panel Data Analysis. International Journal of Econometrics and Financial Management. 2015; 3(2):76-83. doi: 10.12691/ijefm-3-2-4.

Correspondence to: M.  R. Singariya, Department of Economics, Government College Jaitaran (Raj), INDIA. Email: mr.singariya@gmail.com

Abstract

Using panel data collected from the CSO for thirty two states and UTs of India for the recent period of 2004-05 to 2013-14 at the constant 2004-05 prices, the present paper highlights the effect of structural change on economic growth. We examine these relationships in an augmented Chenery-Syrquin Model, and test whether the high income states, EAG (Empowered Action Group) States and high densely states have had any structural impact and what type of structural trends have been adopted by the economy in such a high growth period. Results of random effect model show that any increases in the shares of manufacturing sector and industrial sectors (mining and Quarrying, manufacturing and construction) have significant positive effect on economic growth (Income Coefficient), while the patterns of industrial sector has significant positive effects on population density (Size Coefficient). However, the coefficient of population density is insignificant yet positive for manufacturing orientation. These relationships suggest that most densely populated states can achieve economies of scale, resource endowments and scale of domestic demand easily and hence population density plays an important role in the patterns of industrial and manufacturing development. The time trend seems to have significant negative association with industrial orientation and dummy for high income states has significant positive association with service sector and significant negative association with agriculture and manufacturing sectors.

Keywords

References

[1]  Bhatacharya, B.B. and A Mitra (1997): “Changing Composition of Employment in Tertiary Sector: A Cross Country Analysis”, Economic and Political Weekly, 21 March, Vol. 32, 529-34.
 
[2]  Blecker, R.A., 2009. External shocks, structural change and economic growth in Mexico, 1979-2007. World Development 37, 1274-1284.
 
[3]  Chenery, Hollis B., “Patterns of Industrial Growth,” American Economic Review, Vol. 50, No. 3 (September 1960), pp. 624-54.
 
[4]  Chenery, Hollis B. and Lance Taylor, “Development Patterns: Among Countries and Over Time,” Review of Economics and Statistics, Vol. 50, No. 4 (November 1968), pp. 391-416.
 
[5]  Chenery, Hollis B. and Moises Syrquin, Patterns of Development: 1950-1970 (New York: Oxford University Press for the World Bank, 1975).
 
Show More References
[6]  Elhiraika, A. B. (2008). Promoting manufacturing to accelerate economic growth reduce volatility in Africa. Paper prepared at the African Economic Conference, jointly organized by the African Development Bank and UNECA in Tunis, Tunisia.
 
[7]  Kalirajan, K. (2004). “Economic reforms and the transmission of growth impulses across Indian states”, International Journal of Social Economics, 31 (5/6), 623-636.
 
[8]  Keesing, D.B. and Sherk, D.R> (1971), “Population Density in Patterns of Trade and Development”, American Economic Association, 61(5):956-961.
 
[9]  Kuznets, S. (1966), Modern Economic Growth: Rate, Structure and Spread, New Delhi, Oxford and IBH Publishing Co.
 
[10]  Libanio, G. (2006). Manufacturing industry and economic growth in Latin America: A Kaldorian approach. CEDEPLAR, Brazil: Federal University of Minas Gerais.
 
[11]  Linden, M. and T. Mahmood, (2007), Long run relationships between sector shares and economic growth: A panel data analysis of the schengen region. Economics and Business administration University of Joensuu, Finland Nachane, D.M., S.D. Sawant& C.V. Achuthan, (1989), Agriculture and industry: A study of selected linkages. Indian J. Agric. Econ., 44: 140-149.
 
[12]  Syrquin, Moshe and Hollis B. Chenery, “Patterns of Development, 1950 to 1983,” World Bank Discussion Papers, No. 41 (Washington, D.C.: World Bank, 1989)
 
[13]  Syrquin, Moshe, Lance Taylor, and Larry E. Westphal (eds.), Economic Structure and Performance: Essays in Honor of Hollis B. Chenery (Orlando: Academic Press, 1984).
 
[14]  Wang, S., & Li, D. (2010) “A empirical analysis on the relationship between service industry and economic growth”, Proceedings of 2010 International Conference on Industry Engineering and Management.
 
Show Less References

Article

An Econometric Analysis on the Relationship between Tourism and Economic Growth: Empirical Evidence from Nepal

1Central Department of Economics, Tribhuvan Univercity, Kathmandu, Nepal


International Journal of Econometrics and Financial Management. 2015, 3(2), 84-90
DOI: 10.12691/ijefm-3-2-5
Copyright © 2015 Science and Education Publishing

Cite this paper:
Kamal Raj Dhungel. An Econometric Analysis on the Relationship between Tourism and Economic Growth: Empirical Evidence from Nepal. International Journal of Econometrics and Financial Management. 2015; 3(2):84-90. doi: 10.12691/ijefm-3-2-5.

Correspondence to: Kamal  Raj Dhungel, Central Department of Economics, Tribhuvan Univercity, Kathmandu, Nepal. Email: kamal.raj.dhungel@gmail.com

Abstract

A sector potential to carry Nepal in a new economic dimension is tourism. To ensure this to happen, this study tries to examine the relationship between tourism earning and economic growth during the period 1974-2012. Econometric tools such as unit root, co-integration, and error correction are used to examine the equilibrium position. In spite of the low contribution in economic growth, a share of 2% only is a present status; empirical findings reveal a robust fact that a unit change in tourism income will change the gross domestic product by 8.79 units with tourism income elasticity coefficient of 0.2. The causality analysis suggests that there is no short run causality running from either way. However unidirectional causality exists running from gross domestic product to tourism earning in the long run. This study has single implication which advises policy makers of Nepal that they should devise strategies to attain the causality running from tourism to economic growth. It ensures to attain the tourism led-economic growth. In addition, it indicates the speed of adjustment of previous level disequilibrium. The system would correct this at the speed of 39% annually to come at the steady state. These are the self-evident fact that tourism sector has a large potentiality to contribute to economic growth.

Keywords

References

[1]  Suresh, J., and S. Sentilnathan, (2014). “Relationship between Tourism and Economic Growth in Sri Lanka”, “Economic Issues in Sri Lanka” compiled by Dr. S. Vijayakumar, pp. 115-132.
 
[2]  Burger, Veit, (1978). “The Economic Impact of Tourism in Nepal: An Input Output Analysis”. A Ph. D. Thesis Submitted to Faculty of the Graduate School, Cornell University, Austria.
 
[3]  Pradhnanga, (2000).”Tourists’ Consumption Pattern and Its Economic Impact in Nepal”, Delhi: Adroit Publishers.
 
[4]  Shrestha, Sunity, (1995). “Portfolio Behaviour of Commercial Banks in Nepal”, Kathamandu: Mandala Book Point.
 
[5]  Sharma, Om Prakash, (2001). “Tourism Development and Planning in Nepal”, A Ph. D. Thesis presented to Faculty of Social Sciences, Banaras Hindu University India.
 
Show More References
[6]  Adamou,A., and S. Clerides, (2009).”Tourism Development and Economic Growth: Internal Evidence and Lessons for Cyprus”, Cyprus Economic Policy Review, 3(2), pp.3-22.
 
[7]  Dhungel, K.R.,(2008). “A causal relationship between energy consumption and economic growth in Nepal” Asia-Pacific Development Journal, Vol.15, No.1, pp.137-150.
 
[8]  Dhungel,K.R.,(2014a). “On the relationship between electricity consumption and selected macroeconomic variables: empirical evidence from Nepal” Modern Economy, 5(4), PP.360-366.
 
[9]  Dhungel, K.R.,(2014b). “Does Remittance in Nepal Cause Gross Domestic Product? An Empirical Evidence Using Vector Error Correction Model”. International Journal of Econometrics and Financial Management, 2(5), 168-174.
 
[10]  Gautam,B.P.,(2011).”Tourism and Economic Growth in Nepal”, NRB Economic Review, 23(2), pp.18-29.
 
[11]  Tayebi, S.K., A. Jabbori and R.Babaki, (2009). “Studying the Causal Relationship between Tourism and Economic Growth”, Knowledge and Development (Scientific Research) autumn 24.
 
[12]  Zortuk, Mohmut, (2009). “Economic Impact of Tourism on Turkey's Economy: Evidence from Co-integration Tests”, International Research Journal of Finance and Economics 25, pp.231-239.
 
[13]  Khalil, Samina, M. K. Kakar and Walieullah, (2007). “Role of Tourism in Economic Growth: Empirical Evidence from Pakistan Economy”. The Pakistan Development Review 46 (4); 985-995.
 
[14]  Kim, H., Chan, H. and Jan, S., (2006). “Tourism Expansion and Economic Development: The Case of Taiwan”, Tourism management 27, pp.925-933.
 
[15]  Scutariu, L.A., (2009). “Tourism Economic Growth Factor and Essential in Regional Development of Romania”, University of Suceava.
 
[16]  Suresh, J. and L. S.Selthinnathan, (n.a.). “Relationship between Tourism and Economic Growth in Sri Lanka”, available at: http://ssrn.com/abstract=2373931.
 
[17]  Engle R. and Granger C. (1987), “Co-integration and error correction; representation, estimation and testing”, Econometrica, 55: pp-251-276.
 
Show Less References

Article

Optimizing the Operational Process at Container Terminal

1Laboratory of Operations Research, Decision and Control of Processes, Department of Quantitative Methods, Higher Institute of Business Administration of Gafsa Tunisia

2Department of Quantitative Methods, Higher Institute of Business Administration of Gafsa, Laboratory of Modeling and Optimization for Decisional, Industrial and Logistic Systems, (MODELIS)


International Journal of Econometrics and Financial Management. 2015, 3(2), 91-98
DOI: 10.12691/ijefm-3-2-6
Copyright © 2015 Science and Education Publishing

Cite this paper:
Khaled MILI, Tarek SADRAOUI. Optimizing the Operational Process at Container Terminal. International Journal of Econometrics and Financial Management. 2015; 3(2):91-98. doi: 10.12691/ijefm-3-2-6.

Correspondence to: Tarek  SADRAOUI, Department of Quantitative Methods, Higher Institute of Business Administration of Gafsa, Laboratory of Modeling and Optimization for Decisional, Industrial and Logistic Systems, (MODELIS). Email: tarek_sadraoui@yahoo.fr, Tarek.Sadraoui@fsegs.rnu.tn

Abstract

This paper presents a general study of different elements that comprise the operation process for working a maritime container terminal, defining the operation ratios concerned and the interactions between them; similarly, the parameters that affect the operational process are designated. This paper aims to develop an approach to the problem focused on case-study: the Tunisian Terminal. A quantitative analysis is carried out which allows comparative strategies to be recognized and applied to practical cases. The correct planning and execution of operations on a container terminal is a critical element in the strategy of a terminal. Experience and knowledge of the problems that can arise is fundamental when attempting to treat these operations. In this paper, we identify the different measures of the various types of production, and the difficulties that could be faced when maximizing the container terminal’s productivity. Lastly, we recommend some propositions concerning what is being done presently at the terminals to realize their operational objectives.

Keywords

References

[1]  Baird, Aj (2002). Port privatization: objectives, extent, process, and the UK exprience. Int J Marit Econ 2(3): 177-194.
 
[2]  Blanco, B; Pérez-Labajos, C; Sanchez, L; Serrano, A; Lopez, M; Ortega, A (2010). Innovation in Spanich port sector Journal of Maritime Research Vol. VII(1): 71-86.
 
[3]  Brook, Q (2009). Six Sigma and Minitab. QSB Consulting.
 
[4]  Brown, GG; Lawphongpanich, S; Thurman, KP (1994). Optimizing ship berthing. Nav Res Log 41: 1-15.
 
[5]  Castillo-Manzo, JI; Castro-Nuno, M; Gonzalez-Laxe, F; Lopez-Valpuesta, L; Arévalo-Quija-da, MT (2009). Low-cost port competitiveness index: Implementation in the Spanish port system. Mar Pol 33: 591-598.
 
Show More References
[6]  Cooper, MD (2000). Towards a Model of Safety Culture. Safety Sci 36: 111-136.
 
[7]  Daj, J; Lin, W; Moorthy, R; Teo, C-P (2004). Berth Allocation Planning; Optimization in a container Terminal. Georgia Institute of Technology, Atlanta and National University of Singapore.
 
[8]  Dowd, T; Leschine, T (1990). Container terminal productivity: a perspective. Mar Policy Manag 17(2): 107-112.
 
[9]  Dragovic, B; Park, NK; Radmilovic, Z (2006). Shipberth link performance evaluation: simulation and analytical approaches. Mar Policy Manag 33: 281-299.
 
[10]  Gunther, HO; Kim, KH (2006). Container terminals and terminal operations. OR Spectrum 28: 437-445.
 
[11]  Kim, KH; Park, Y-M; Jin, M-J (2008). An optimal layout of container yards. OR Specktrum 30: 675-695.
 
[12]  Kim, KH; Park, KT (2003a). Anote on a dynamic space allocation method for outbound containers. Eur J Oper Res 148(1): 109-136.
 
[13]  Kim, KH; Lee, KM; Hwang, H (2003b). Sequencing delivery and receiving operations for yard cranes in port container terminals. Int J Product Econ 84: 283-292.
 
[14]  Kim, KH; Park, YM; Ryu, KR (2000). Deriving decision rules to locate export containers in container yards. Eur J Oper Res 124: 89-101.
 
[15]  Kim, KH; Bae, JW (1999a). A dispatching method for automated guided vehicles to minimize delays of containership operations. Int J Manag Sci 5(1): 1-25.
 
[16]  Kim, KH; Kim, HB (1999b). Segregating space allocation models for container inventories in port container terminals. Int J Product Econ 59(1-3): 415-423.
 
[17]  Kim, KH; Kim, KY (1999c). Routing straddle carriers for the loading operation of containers using a beam search algorithm. Comput Ind Eng 36(1): 109-136.
 
[18]  Kim, KY; Kim, KH (1999d). Arouting algorithm for a single straddle carrier to load export containers onto a containership. Int J Product Econ 59(13): 425-433.
 
[19]  Kim, KY; Kim, KH (1999e). An optimal routing algorithm for a transfer crane in port container terminals. Transport Sci 33(1): 17-33.
 
[20]  Kim, KY; Kim, HB (1998). The optimal determination of the space requirement and the number of transfer cranes for import containers. Comput Ind Eng 35(3-4): 427-430.
 
[21]  Kim, KH (1997). Evaluation of the number of rehandles in container yards. Comput Ind Eng 32(4): 701-711.
 
[22]  Lau, HYK; Zhao, Y (2008). Integrated scheduling of handling equipement at automated container terminals. Int J Product Econ 112(2): 665-682.
 
[23]  Lee, D; Cao, Z; Meng, Q (2007). Scheduling of two-transtainer systems for loading outbound containers in port container terminals with simulated annealing algorithm. Int J Product Econ 107(1): 115-124.
 
[24]  Legato, P; Monaco, MF (2004). Human resources management at a marine container terminal. Eur J Oper Res 156(3): 769-781.
 
[25]  Lim, A (1998). On the ship berthing problem. Oper Res Lett 22(2-3): 105-110.
 
[26]  Longo. F(2010). Design and integration of the containers inspection activities in the container terminal operations. Int J Product Econ 125: 272-283.
 
[27]  Onyemechi, C(2010). Regional Hubs and Multimodal Logistic Efficiency in the 21st Century. JMR VII(2) 63-72.
 
[28]  Petering, MEH (2011). Decision support for yard capacity, fleet composition, truck substituability, and scalability issues at seaport container terminals. Transportation Res E-Log 47: 85-103.
 
[29]  Sammarra, M; Cordeau, J-F; Laporte, G; Monaco, MF (2007). A tabu search heuristic for quay crane scheduling problem. J Scheduling 10(4-5): 327-336.
 
[30]  Stahlbock, R; Voss S (2008). Operations research at container terminals: A literature update. OR Spektrum 30(1): 1-52.
 
[31]  Steenken, D; Voss, S; Stahlbock, R(2004). Container terminal operation and operations research-a classification and literature review. OR Spektrum 26:3-49.
 
[32]  Trelleborg Marine Systems (2010). Barometer Reports: .
 
[33]  Vis, I; de Koster, R (2003). Transhipement of containers at a container terminal: An overview. Eur J Oper Res 147(1): 1-16.
 
[34]  Zhang, C; Liu, J; Wan, Y-W; Murty, KG; Linn, RJ (2003). Storage space allocation in container terminals. Transportation Res B-Meth 37(10): 883-903.
 
Show Less References

Article

Optimal Portfolio Selection Using Multi-Objective Fuzzy-Genetic Method

1Faculty of Electrical and Computer Engineering, ShahidBeheshti University, Tehran, Iran


International Journal of Econometrics and Financial Management. 2015, 3(2), 99-103
DOI: 10.12691/ijefm-3-2-7
Copyright © 2015 Science and Education Publishing

Cite this paper:
Iman Goroohi Sardou, Ataa Nazari, Esmaeil Ghodsi, Ehsan Bagherzadeh. Optimal Portfolio Selection Using Multi-Objective Fuzzy-Genetic Method. International Journal of Econometrics and Financial Management. 2015; 3(2):99-103. doi: 10.12691/ijefm-3-2-7.

Correspondence to: Iman  Goroohi Sardou, Faculty of Electrical and Computer Engineering, ShahidBeheshti University, Tehran, Iran. Email: i_goroohi@sbu.ac.ir

Abstract

The purpose of investors is to maximize the expected returnin an acceptable level of risk. A genetic algorithm (GA) based on multi-objective fuzzy approach is presented in this paper to solve the multi-objective problem of portfolio selection. The expected return maximization and the risk minimization are the objective functions of the proposed portfolio selection problem. Since GA does not require prespecified information of the problem, it has more flexibility rather than the other nonlinear methods. Furthermore, the GA is able to model the nonlinear manner of the objective functions of the problem. In the proposed fuzzy-genetic method the objective functions are transmitted to a fuzzy domain using a fuzzy membership function and after that the weighted sum method is employed to determine the total objective function. Besides, the Pareto front of the objectives of return and risk are obtained by varying the weighting coefficients and solving the new single-objective problems. To demonstrate the effectiveness of the proposed method, a case study including several active companies is studied.

Keywords

References

[1]  X. Sun, J. Li, L. Tang, and D. Wu. Identifying the risk-return tradeoff and exploring the dynamic risk exposure of country portfolio of the FSU's oil economies, Economic Modelling, 29. (2012). pp. 2494-2503.
 
[2]  J. Mencía. Assessing the risk-return trade-off in loan portfolios, Journal of Banking & Finance, 36. (2012). pp. 1665-1677.
 
[3]  G. Palomba, Luca Riccetti. Portfolio frontiers with restrictions to tracking error volatility and value at risk, Journal of Banking & Finance, 36. (2012). pp. 2604-2615.
 
[4]  S. Kumar Mishra, G. Panda,R. Majhi.A comparative performance assessment of a set of multiobjective algorithms for constrained portfolio assets selection, Swarm and Evolutionary Computation, 16.(2014). pp. 38-51
 
[5]  Joel WeiqiangGoh, Kian Guan Lim, Melvyn Sim, Weina Zhang. Portfolio value-at-risk optimization for asymmetrically distributed asset returns, European Journal of Operational Research, 221. (2012). pp. 397-406.
 
Show More References
[6]  R. J. Bianchi, G. Bornholt, M. E. Drew, M. F. Howard. Long-term U.S. infrastructure returns and portfolio selection, Journal of Banking & Finance, 42. (2014). pp. 314-325.
 
[7]  Wei. Zhang, Q. Mei, Q. Lu, W. Xiao. Evaluating methods of investment project and optimizing models of portfolio selection in fuzzy uncertainty, Computers & Industrial Engineering, 61. (2011). pp. 721-728.
 
[8]  C. Aranha, C. R.B. Azevedo, H. Iba. Money in trees: How memes, trees, and isolation can optimize financial portfolios, Information Sciences, 182. (2012). pp. 184-198.
 
[9]  Min Zhu, Return distribution predictability and its implications for portfolio selection, International Review of Economics & Finance, 27 (2013). pp. 209-223.
 
[10]  F. Makhatabrafiei, M.A. Fatahzadeh, Linear regression and multiobjective method to solve the portfolio selection problem, 9th international conference of industrial engineering, Tehran, Iran, 2013.
 
[11]  X. Li, Z. Qin, Interval portfolio selection models within the framework of uncertainty theory, Economic modeling, 41 (2014), pp. 338-344.
 
[12]  H. Yao, Z. Li, Sh. Chen, Continuous-time mean-variance portfolio selection with only risky assets, Economic modeling, 36 (2014), pp. 244-251.
 
[13]  F. He, R. Qu, A two-stage stochastic mixed-integer program modeling and hybrid solution approach to portfolio selection problems, Information Sciences, (2014), In press.
 
Show Less References

Article

Procedures Designing Composite Progressive Indicators

1Department of Geography & Regional Planning, School of Rural & Surveying Engineering, National Technical University of Athens, Irron Polytechniou Str., Zographou Campus, Athens, Greece


International Journal of Econometrics and Financial Management. 2015, 3(2), 104-109
DOI: 10.12691/ijefm-3-2-8
Copyright © 2015 Science and Education Publishing

Cite this paper:
Azniv Petrosyan. Procedures Designing Composite Progressive Indicators. International Journal of Econometrics and Financial Management. 2015; 3(2):104-109. doi: 10.12691/ijefm-3-2-8.

Correspondence to: Azniv  Petrosyan, Department of Geography & Regional Planning, School of Rural & Surveying Engineering, National Technical University of Athens, Irron Polytechniou Str., Zographou Campus, Athens, Greece. Email: pet_azniv@yahoo.com

Abstract

The contemporary manuscript proposes eight (8) procedures to prescribe concepts and define ways to composite progressive indicators (CPI). Composite appraising supportive progress (CASP) is processed using proper defined indicators as per apt methods. The emphasis is on CPI to express its unification with CASP. Huge range of authors papers is contributed to obtain and estimate the best procedures guiding CPI to progressive economy. The imposed conceptions of CPI are aspects, goals, criteria, categorization and principles with pressure-state-response (PSR) framework. The characterized means to compulsory CPI are design process, framework model and top-down and bottom-up approaches to assess CASP.

Keywords

References

[1]  IUCN-International Union for Conservation of Nature and Natural Resources. World Conservation Strategy: Living Resource Conservation for Sustainable Development. Gland, Switzerland, 1980.
 
[2]  Clement, K., Economic Development and Environmental Gain, Earthscan Publication Ltd, London, 2000, 192pp.
 
[3]  WCED-World Commission on Environment and Development. Our Common Future, Chair: Gro Harlem Brundtland. Oxford University Press, 1987.
 
[4]  Reed, D., Structural adjustment, the environment and sustainable development, Earthscan, London, 1996.
 
[5]  Pearce, D. W., Turner, R. K., Economics of natural resources and the environment, Baltimore: Johns Hopkins University Press, 1990.
 
Show More References
[6]  Pezzoli, K., “Sustainable development: a trans-disciplinary overview of the literature”, Journal of Environmental Planning and Management, 40 (5), 549-574, 1997.
 
[7]  Rees, W.E., “Consuming the Earth: the biophysics of sustainability”, Ecological Economics, 29, 23-27, 1999.
 
[8]  Sachs, W., Planet Dialectics: Explorations in Environment and Development, Zed Books, London, 1999.
 
[9]  Segnestam, L., “Indicators of Environment and Sustainable Development, Theories and Practical Examples”, World Bank Environment Group, Environmental Economics Paper No. 89, The World Bank, Washington, DC, 2002
 
[10]  Olewiler, N., “Environmental sustainability for urban areas: The role of natural capital indicators”, Cities, 23 (3), 184-195, 2006.
 
[11]  Petrosyan, A. F., Karathanassi, V., “Review Article of Landscape Metrics based on Remote Sensing Data”, Journal of Environmental Science and Engineering, 5 (11), 1542-1560, 2011.
 
[12]  Petrosyan, A. F., “A Model for Incorporated Measurement of Sustainable Development Comprising Remote Sensing Data and Using the Concept of Biodiversity”, Journal of Sustainable Development, 3 (2), 9-26. 2010
 
[13]  Spangenberg, J.H., Lorek, S., “Environmentally sustainable household consumption: from aggregate environmental pressures to priority fields of action”, Ecological Economics, 43 (2-3), 127-140, 2002.
 
[14]  Varma, V.K., Ferguson, I., Wild, I., “Decision support system for the sustainable forest management” Forest Ecology and Management, 128 (1-2), 49-55, 2000.
 
[15]  Bell, S., Morse, S., “Experiences with sustainability indicators and stakeholder participation: a case study relating to a Blue Plan project in Malta”, Sustainable Development, 12 (1), 1-14, 2004.
 
[16]  Simianer, H., “Decision making in livestock conservation”, Ecological Economics, 53, 559-572, 2005.
 
[17]  Finco, A., Nijkamp, P., “Pathways to urban sustainability”, Journal of Environmental Policy and Planning, 3 (4), 289-302, 2001.
 
[18]  Atkinson, G., Hamilton, K., “Accounting for progress: indicators for sustainable development”, Environment, 38 (7), 16-20, 1996.
 
[19]  Mickwitz, P., Melanen, M., Rosenstrom, U., Seppala, J., “Regional eco-efficiency indicators – a participatory approach”, Journal of Cleaner Production, 14 (18), 1603-1611, 2006.
 
[20]  McAlpine, P., Birnie, A., “Establishing sustainability indicators as an evolving process: experience from the island of Guernsey”, Sustainable Development, 14 (2), 81-92, 2006.
 
[21]  Peris-Mora, E., Diez Orejas, J.M., Subirats, A., Ibáñez, S., Alvarez, P., “Development of a system of indicators for sustainable port management”, Marine Pollution Bulletin, 50 (12), 1649-1660, 2005
 
[22]  Connolly, J., Goma, H.C., Rahim, K., “The information content of indicators in intercropping research”, Agriculture, Ecosystems and Environment, 87 (2), 191-207, 2001.
 
[23]  Gallopin, G., “Indicators and their use: information for decision making”, In: Moldan, B., Billharz, S. (Eds.), Sustainability Indicators, Report on the Project on Indicators of Sustainable Development, Wiley, Chicheste. 1997
 
[24]  Rigby, D., Woodhouse, P., Young, T., Burton, M., “Constructing a farm level indicator of sustainable agricultural practice”, Ecological Economics, 39 (3), 463-478, 2001.
 
[25]  Pagina, W., Measurement and indicators for sustainable development, Manitoba: International Institute for Sustainable Development, 2000.
 
[26]  Parsons, W., “Not just steering but weaving: relevant knowledge and the craft of building policy capacity and coherence”, Australian Journal of Public Administration, 63(1), 43-57, 2004.
 
[27]  Lehtonen, M., “Mainstreaming sustainable development in the OECD through indicators and peer reviews”, Sustainable Development, 16(4), 241-250, 2008.
 
[28]  Brodhag, C., “Information, governance et development durable”, International Political Science Review, 21, 311-327, 2000.
 
[29]  Paehlke, R., “Environmental politics, sustainability and social science”, Environmental Politics, 10, 1-22, 2001.
 
[30]  OECD - Organization for Economic Cooperation and Development, Better understanding our cities: the role of urban indicators, Paris: OECD Publications, 1997
 
[31]  Liu, W. H., Ou, C. H., A comparative analysis of sustainable fishery development indicator systems in Australia and Canada, Sustainable Development, 15 (1), 28-40, 2007.
 
[32]  Smith, S. L., “Devising Environment and Sustainable Development Indicators for Canada”, Corporate Environmental Strategy, 9 (3), 305-310, 2002.
 
[33]  Haberl, H., Wackernagel, M., Wrbka, T., “Land use and sustainability indicators: an introduction”, Land Use Policy, 21 (3), 193-198, 2004.
 
[34]  Moles, R., Foley, W., Morrissey, J., O'Regan, B., “Practical appraisal of sustainable development—Methodologies for sustainability measurement at settlement level”, Environmental Impact Assessment Review, 28 (2-3), 144-165, 2008.
 
[35]  Merkle, A., Kaupenjohann, M., “Derivation of ecosystemic effect indicators—method”, Ecological Modeling, 130, 39-46, 2000.
 
[36]  Diamantini, C., Zanon, B., “Planning the urban sustainable development The case of the plan for the province of Trento, Italy”, Environmental Impact Assessment Review, 20 (3), 299-310, 2000.
 
[37]  Repetti, A., Desthieux, G., “A Relational Indicator set Model for urban land-use planning and management: Methodological approach and application in two case studies”, Landscape and Urban Planning, 77 (1-2), 196-215, 2006.
 
[38]  OECD-Organization for Economic Cooperation and Development. Environmental Indicators: Towards Sustainable Development, OECD, Paris, 2001.
 
[39]  Jung, W., “Sustainable development in industrial countries: environmental indicators and targets as core elements of national action plans - the German case”, Sustainable Development, 5 (3), 139-147, 1997.
 
[40]  Pastilles Consortium, Indicators into Action, A Practitioners Guide for Improving Their Use at the Local Level, London School of Economics, London, 2002.
 
[41]  Azapagic, A., “Developing a framework for sustainable development indicators for the mining and minerals industry”, Journal of Cleaner Production, 12, 639-662, 2004.
 
[42]  Amajirionwu, M., Connaughton, N., McCann, B., Moles, R., Bartlett, J., O’Regan, B., “Indicators for managing biosolids in Ireland”, Journal of Environmental Management, 88 (4), 1361-1372, 2008.
 
[43]  Balkema, A. J, Preisig, H. A., Otterpohl, R., Lambert, F. J. D., “Indicators for the sustainability assessment of wastewater treatment systems”, Urban Water, 4, 153-161, 2002.
 
[44]  IISD-International Institute for Sustainable Development, City of Winnipeg Quality of Life Indicators, 1997, [Online]. Available: http://www.iisd.org/pdf/wpg.qoli.pdfS, accessed on 9/11/02.
 
[45]  Gustavson, K., Longeran, S., Ruitenbeek, H. J., “Selection and modeling of sustainable development indicators: a case study of the Fraser River Basin, British Columbia”, Ecological Economics, 28, 117-132, 1999.
 
[46]  Jollands, N., Harmsworth, G., “Participation of indigenous groups in sustainable development monitoring: Rationale and examples from New Zealand”, Ecological Economics, 62 (3-4), 716-726, 2007.
 
[47]  Kuik, O., Verbruggen, H. (Eds.), In Search of Indicators of Sustainable Development, Kluwer, Dordrecht, 1991.
 
[48]  Peterson, P. J., “Sustainable development indicators for rapidly industrializing countries”, In: Management Response Strategies, vol. 1. Penerbit UKM, Kuala Lumpur, 1997.
 
[49]  Tate, J., “Void dwellings - a “headline” indicator?”, Sustainable Development, 10 (1), 36-50, 2002.
 
[50]  Ekins, P., Dresner, S., Dahlstrom, K., “The four-capital method of sustainable development evaluation”, European Environment, 18 (2), 63-80, 2008.
 
[51]  De Kruijf, H.A.M., Van Vuuren, D. P., “Following Sustainable Development in Relation to the North–South Dialogue: Ecosystem Health and Sustainability Indicators”, Eco-toxicology and Environmental Safety, 40 (1-2), 4-14.
 
[52]  Ravetz, J., “Integrated assessment for sustainability appraisal in cities and regions”, Environmental Impact Assessment Review, 20 (1), 31-64, 2000.
 
[53]  Spangenberg, J.H, Pfahl, S., Deller, K., “Towards indicators for institutional sustainability: lessons from an analysis of Agenda 21”, Ecological Indicators, 2 (1-2), 61-77, 2002.
 
[54]  Energy & Biodiversity Initiative, Biodiversity Indicators for Monitoring Impacts and Conservation Actions, 2002.
 
[55]  Yuan, W., and James, P., “Evolution of the Shanghai city region 1978-1998: an analysis of indicators”, Journal of Environmental Management, 64, 299-309, 2002.
 
[56]  Ledoux, L., Mertens, R., Wolff, P., “EU sustainable development indicators: An overview”. Natural Resources Forum, 29 (4), 392-403, 2005.
 
[57]  Braat, L., “The predictive meaning of sustainability indicators”, In: Kuik, O., Verbruggen, H. (Eds.), In Search of Indicators of Sustainable Development. Kluwer Academic Press, Dordrecht, The Netherlands, 1991, 57-70.
 
[58]  Huang, S. L., Wong, J. H., Chen, T. C., “A framework of indicator system for measuring Taipei's urban sustainability”, Landscape and Urban Planning, 42 (1), 15-27, 1998.
 
[59]  Tils, R., “The German sustainable development strategy: facing policy, management and political strategy assessments”, European Environment, 17 (3), 164-176, 2007.
 
[60]  Patlitzianas, K.D., Doukas, H., Kagiannas, A.G., Psarras, J., “Sustainable energy policy indicators: Review and recommendations”, Renewable Energy, 33 (5), 966-973, 2008.
 
[61]  UK Biodiversity Partnership. Biodiversity Indicators in Your Pocket 2007, National Statistics, 2007.
 
[62]  Pittman, J. Wilhelm, K., “New economic and financial indicators of sustainability”, New Directions for Institutional Research, 134, 55-69, 2007.
 
[63]  Devkota, S. R., “Is strong sustainability operational? An example from Nepal”, Sustainable Development, 13 (5), 297-310, 2005.
 
[64]  Osinski, E., Meier, U., Buchs, W., Weickel, J., Matzdorf, B., “Application of biotic indicators for evaluation of sustainable land use—current procedures and future developments”, Agriculture, Ecosystems & Environment, 98 (1-3), 407-421, 2003.
 
[65]  Korhonen, J., “Special issue of the Journal of Cleaner Production, ‘From Material Flow Analysis to Material Flow Management’: strategic sustainability management on a principle level” Journal of Cleaner Production, 15 (17), 1585-1595, 2007.
 
[66]  Zahm, F., Viaux, P., Vilain, L., Girardin, P., Mouchet, C. “Assessing farm sustainability with the IDEA method - from the concept of agriculture sustainability to case studies on farms”, Sustainable Development, 16 (4), 271-281, 2008.
 
[67]  Veleva, V., Hart, M., Greiner, T., Crumbley, C., “Indicators of sustainable production”, Journal of Cleaner Production, 9 (5), 447-452, 2001.
 
[68]  Kates, R. W., “Sustainability 2001 Transition: Human–Environment Relationship”, International Encyclopedia of the Social & Behavioral Sciences, 15325-15329, 2004.
 
[69]  Lamberton, G., “Sustainability accounting—a brief history and conceptual framework”, Accounting Forum, 29 (1), 7-26, 2005.
 
[70]  Palme, U., Tillman, A.-M., “Sustainable development indicators: how are they used in Swedish water utilities?” Journal of Cleaner Production, 16 (13), 1346-1357, 2008.
 
[71]  Azapagic, A., Perdan, S., “Indicators of sustainable development for industry: a general framework”, Process Safety and Environmental Protection, 78 (4), 243-261, 2000.
 
[72]  Labuschagne, C., Brent, A. C., van Erck., R. P. G., “Assessing the sustainability performances of industries”, Journal of Cleaner Production, 13 (4), 373-385, 2005.
 
[73]  Boyd, H., Charles, A., “Creating community-based indicators to monitor sustainability of local fisheries”, Ocean & Coastal Management, 49 (5-6), 237-258, 2006.
 
[74]  Searcy, C., McCartney, D., Karapetrovic, S., “Identifying priorities for action in corporate sustainable development indicator programs”, Business Strategy and the Environment, 17 (2), 137-148, 2008.
 
[75]  Nijkamp, P., Vreeker, R., “Sustainability assessment of development scenarios: methodology and application to Thailand”, Ecological Economics, 33 (1), 7-27, 2000.
 
[76]  Azapagic, A., Perdan, S., Clift, R., Sustainable Development in Practice, Case Studies for Engineers, John Wiley & Sons Ltd, 2005, 446pp.
 
[77]  Potts, T., “A framework for the analysis of sustainability indicator systems in fisheries”, Ocean and Coastal Management, 49 (5-6), 259-280, 2006.
 
[78]  Hilden, M., Rosenstrom, U., “The use of indicators for sustainable development”, Sustainable Development, 16 (4), 237-240, 2008.
 
[79]  Morrone, M., Hawley, M., “Improving environmental indicators through involvement of experts, stakeholders, and the public”, Ohio Journal of Science, 98 (3), 52-58, 1998.
 
[80]  Brang, P., Courbaud, B., Fischer, A., Kissling-Naf, I., Pettenella, D., Schonenberger, W., Spork, J., Grimm, V., “Developing indicators for the sustainable management of mountain forests using a modeling approach”, Forest Policy and Economics, 4 (2), 113-123, 2002.
 
[81]  Malkina-Pykh, I. G., “Integrated assessment models and response function models: pros and cons for sustainable development indices design”, Ecological Indicators, 2 (1-2), 93-108, 2002.
 
[82]  Rosenstrom, U., Kyllonen, S., “Impacts of a participatory approach to developing national level sustainable development indicators in Finland”, Journal of Environmental Management, 84 (3), 282-298, 2007.
 
[83]  Slee, B., “Social indicators of multifunctional rural land use: The case of forestry in the UK”, Agriculture, Ecosystems & Environment, 120 (1), 31-40, 2007.
 
[84]  Macleod, C., Todnem, R., “Performance, conformance and change: towards a sustainable tourism strategy for Scotland”, Sustainable Development, 15 (6), 329-342, 2007.
 
[85]  Bell, S., Morse, S., “Delivering sustainability therapy in sustainable development projects”, Journal of Environmental Management, 75, 37-51, 2005.
 
[86]  Reed, M. S., Fraser, E. D. G., Dougill, A. J., “An adaptive learning process for developing and applying sustainability indicators with local communities”, Ecological Economics, 59 (4), 406-418, 2006.
 
[87]  Blue Plan-Regional Activity Centre, The Blue Plan, “Cradle of Mediterranean Futures”. Strategic orientations. Draft. Sophia Antipolis, December, 2006.
 
[88]  Hartmuth, G., Huber, K., Rink, D., “Operationalization and contextualization of sustainability at the local level”, Sustainable Development, 16 (4), 261-270, 2008.
 
[89]  Turner, R. K., “Ecosystem Functions and the Implications for Environmental Evaluation: An Executive Summary”, Report to English Nature, Peterborough. 2000.
 
[90]  Bellini, G., “Agri-environmental Issues: Policies, Definition of Indicators Lists and Related Implementation Processes”, Italian National Statistical Institute (ISTAT), Working Paper No. 19, 2005.
 
[91]  EEA-European Environment Agency, “A Framework for Assessing Policy Integration”, IRENA Indicators, EEA Report, No.2, 2006.
 
[92]  Zavadskas, E. K., Antucheviciene, J., “Development of an indicator model and ranking of sustainable revitalization alternatives of derelict property: a Lithuanian case study”, Sustainable Development 14 (5), 287-299, 2006.
 
[93]  Nuissl, H., Haase, D., Lanzendorf, M., Wittmer, H., “Environmental impact assessment of urban land use transitions— A context-sensitive approach”, Land Use Policy, 26, 414-424, 2009.
 
[94]  Smeets, E., Weterings, R., “Environmental Indicators: Typology and Overview”, Technical Report No. 25, European Environment Agency, Copenhagen, 1999.
 
[95]  OECD-Organization for Economic Cooperation and Development, OECD core set of indicators for environmental performance reviews, OECD Environment Monographs, 83, Paris, France, 1993
 
[96]  Keirstead, J., Leach, M., “Bridging the gaps between theory and practice: a service niche approach to urban sustainability indicators”, Sustainable Development, 16 (5), 329-340, 2008.
 
[97]  Buchs, W., “Biotic indicators for biodiversity and sustainable agriculture—introduction and background”, Agriculture, Ecosystems & Environment, 98 (1-3), 1-16, 2003.
 
[98]  Wiggering, H., Dalchow, C., Glemnitz, M., Helming, K., Muller, K., Schultz, A., Stachow, U., Zander, P., “Indicators for multifunctional land use—Linking socio-economic requirements with landscape potentials”, Ecological Indicators, 6 (1), 238-249, 2006.
 
[99]  Crabtree, B., Bayfield, N., “Developing sustainability indicators for mountain ecosystems: a study of the Cairngorms, Scotland”, Journal of Environmental Management, 52 (1), 1-14, 1998.
 
[100]  Huang, S. L., Yeh, C. T., Budd, W. W., Chen, L. L., “A Sensitivity Model (SM) approach to analyze urban development in Taiwan based on sustainability indicators”, Environmental Impact Assessment Review, 29 (2), 116-125, 2009.
 
[101]  Garcia, S. M., Staples, D. J., Chesson, J., “The FAO guidelines for the development and use of indicators for sustainable development of marine capture fisheries and an Australian example of their application”, Ocean & Coastal Management, 43 (7), 537-556, 2000.
 
[102]  Hammond, A., Adriaanse, A., Rodenburg, E., Bryant, D., Woodward, R., Environmental indicators: a systematic approach to measuring and reporting on environmental policy performance in the context of sustainable development, Washington DC: World Resources Institute, 1995.
 
[103]  Prescott-Allen, R., The wellbeing of nations: a country-by-country index of quality of life and the environment, Washington DC: Island Press, 2001.
 
[104]  Krajnc, D., Glavic, P., “A model for integrated assessment of sustainable development”, Resources, Conservation and Recycling, 43, 189-208, 2005a.
 
[105]  Krajnc, D., Glavic, P., “How to compare companies on relevant dimensions of sustainability”, Ecological Economics, 55, 551-563, 2005b.
 
[106]  Tanzil, D., Beloff, B. R., “Assessing impacts: Overview on sustainability indicators and metrics”, Environmental Quality Management, 15 (4), 41-56, 2006.
 
[107]  Van Dijk, M.P., Mingshun, Z., “Sustainability indices as a tool for urban managers, evidence from four medium-sized Chinese cities”, Environmental Impact Assessment, 25, 667-688, 2006.
 
[108]  Hardi, P., DeSouza-Huletey, J. A., “Issues in analyzing data and indicators for sustainable development”, Ecological Modeling, 130 (1-3), 59-65, 2000.
 
Show Less References

Article

Research on the Potentials and Countermeasures of the Utilization of Foreign Direct Investment in Tibet of China

1School of International Business, Dalian Nationalities University, Dalian, China

2College of International Economics and Trade, Dongbei University of Finance and Economics, Dalian, China

3School of Economics and Management, Dalian Nationalities University, Dalian, China


International Journal of Econometrics and Financial Management. 2015, 3(3), 110-114
DOI: 10.12691/ijefm-3-3-1
Copyright © 2015 Science and Education Publishing

Cite this paper:
Zhu Ruixue, Xiao Yang, Xie Ningyu. Research on the Potentials and Countermeasures of the Utilization of Foreign Direct Investment in Tibet of China. International Journal of Econometrics and Financial Management. 2015; 3(3):110-114. doi: 10.12691/ijefm-3-3-1.

Correspondence to: Zhu  Ruixue, School of International Business, Dalian Nationalities University, Dalian, China. Email: oh-snow@dlnu.edu.cn

Abstract

Since the first introduction of foreign enterprise in 1988, foreign direct investment(FDI) in Tibet has been continuously increasing because of distinctive geographic location, great resource advantage, many featured industries and huge development potentials of Tibet. But there still exist some problems with the utilization of FDI in Tibet. Based on this, the paper analyzes the potentials of further utilization of FDI in Tibet and provides some countermeasures and suggestions for improving utilization of FDI and enhancing the harmonious development between FDI and Tibet’s economy, resources and environment.

Keywords

References

[1]  Statistical Office of Tibet Autonomous Region, National Bureau of Statistics Survey Office in Tibet, Tibet Statistical Yearbook (2007-2014), China Statistics Press, Beijing, 2014.
 
[2]  China Tibet-logy Research Center, “Tibet's economic and social development report,” [Online]. Available: http://news.xinhuanet.com/newscenter/2009- 03/30/ content_11098904.htm. [Accessed Feb. 2, 2015].
 
[3]  Luoli, Lacan. 50 Years of Tibet(economic volume), Ethnic Press, Beijing, 2001, 78-85.
 
[4]  Xuaiyan, Anyuqin, Wangdahai, “On Tibet's Eco-industrial System and Its Development Focus,” Journal of Tibet University(Social Science Edition), 12(2), 28-31, Dec. 2010.
 

Article

Smooth Bootstrap Methods on External Sector Statistics

1Department of Statistics, Michael Okpara University of Agriculture Umudike, Abia State, Nigeria

2Department of Banking and Finance, University of Uyo, Uyo, AkwaIbom State, Nigeria


International Journal of Econometrics and Financial Management. 2015, 3(3), 115-120
DOI: 10.12691/ijefm-3-3-2
Copyright © 2015 Science and Education Publishing

Cite this paper:
Acha Chigozie K, Acha Ikechukwu A. Smooth Bootstrap Methods on External Sector Statistics. International Journal of Econometrics and Financial Management. 2015; 3(3):115-120. doi: 10.12691/ijefm-3-3-2.

Correspondence to: Acha  Chigozie K, Department of Statistics, Michael Okpara University of Agriculture Umudike, Abia State, Nigeria. Email: specialgozie@yahoo.com

Abstract

The investigation of the possibility of a significant difference existing in the parametric and nonparametric bootstrap methods on external sector statistics, and establishing the sample data distribution using the smooth bootstrap is the focus of this study. The root mean square error (RMSE) and the kernel density will be used on the test statistic θ in the determination of such difference. Establishing this difference will lead to more detailed study to discover reasons for such difference. This will also aid the Nigeria economy to aim at improving the performance of the external sector statistics (ESS). The study used secondary data from Central bank of Nigeria (1983-2012). Analysis was carried out using R-statistical package. In the course of the analysis, 17280 scenarios were replicated 200 times. The result shows a significant difference between the performances of the parametric and nonparametric smooth bootstrap methods, namely; wild and pairwise bootstrap respectively. The significantly better performance of the wild bootstrap indicate the possible use of this technique in assessment of comparative performance of ESS with a view to further understanding the better performers in order to identify factors contributing to such better performance. Also, when the sample size and the bootstrap level are very high, the smooth bootstrap or kernel density estimates outperform the pair wise bootstrap notwithstanding that they are nonparametric methods. The kernel density plots revealed that the sampling distribution of the ESS was found to be a Chi-square distribution and was confirmed by the smooth bootstrap methods.

Keywords

References

[1]  Abney, S. (2002). "Bootstrapping", Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics.
 
[2]  Acha, C.K. Bootstrapping Normal and Binomial Distributions,” International journal of econometrics and financial management. 2014, 2 (6).
 
[3]  Botev, Z.I.; Grotowski, J.F.; Kroese, D.P. (2010). "Kernel density estimation via diffusion". Annals of Statistics 38 (5): 2916-2957.
 
[4]  Chernick, M. R. (2007). Bootstrap Methods: A Guide for Practitioners and Researchers, 2nd Edition Wiley, Hoboken.
 
[5]  Davidson, R. and Flachaire, E. (2001), The Wild Bootstrap, Tamed at Last, GREQAM Document de Travail 99A32, revised.
 
Show More References
[6]  Davidson, R. and Flachaire, E., (2008). The wild bootstrap, tamed at last, Journal of Econometrics, Elsevier, 146 (1), 162-169.
 
[7]  Davidson, R & MacKinnon, J. G. (1999).The Size Distortion of Bootstrap Tests, Econometric Theory, Cambridge University Press, vol. 15 (03), pages 361-376, June.
 
[8]  Davidson, R. and MacKinnon, J. (2000). Bootstrap tests: how many bootstraps? Econometric Reviews, Taylor and Francis Journals, 19 (1), 55-68.
 
[9]  Davidson, R. and MacKinnon, J.G. (2006), ‘Bootstrap Methods in Econometrics’, in Patterson, K. and Mills, T.C. (eds), Palgrave Handbook of Econometrics: Volume 1 Theoretical Econometrics. Palgrave Macmillan, Basingstoke; 812-38.
 
[10]  Davison, A. C. and D. V. Hinkley (1997). Bootstrap Methods and Their Application, Cambridge, Cambridge University Press.
 
[11]  Efron, B., & Tibshirani, R.J. (1993). An introduction to the bootstrap (Monographs on Statistics and Applied Probability 57). New York: Chapman & Hall.
 
[12]  Freedman, D.A. (1981) Bootstrapping regression models, Ann. Statist. 6, 1218-1228.
 
[13]  Hall, P., and Wang, Q. (2004). Exact convergence rate and leading term in the Central Limit Theorem for Student’s t-statistic. Ann. Probab. 32, 1419-1437.
 
[14]  Hansen, B. E. (2000). Testing for structural change in conditional models. J. Econ. 97, 93-115.
 
[15]  Lahiri, S. N. (2005a). Consistency of the jackknife-after-bootstrap variance estimator for the bootstrap quantiles of a studentizedstatistic. Ann. Statist. 33, 2475-2506.
 
[16]  Lahiri, S. N. (2003). Resampling Methods for Dependent Data. Springer-Verlag, New York.
 
[17]  Lahiri, S. N. (2005b). A note on the sub sampling, method under long-range dependence. Preprint, Department of Statistics, Iowa State University.
 
[18]  Lahiri, S. N., Lee, Y.-D., and Cressie, N. (2002). Efficiency of least squares estimators of spatial variogramparameters. J. Statist. Plann. Inf. 3, 65-85.
 
[19]  Lam, J.-P., and Veall, M. R. (2002). Bootstrap prediction intervals for single period regression forecasts. Int. J. Forecast. 18, 125-130.
 
[20]  Park, E., and Lee, Y. J. (2001). Estimates of standard deviation of Spearman’s rank correlation coefficients with dependent observations. Commun. Statist. Simul. Comput. 30, 129-142.
 
[21]  Shi, Q., Zhu, Y., and Lu, J. (2004). Bootstrap approach for computing standard error of estimated coefficients in proportional odds model applied to correlated assessments in psychiatric clinical trial. In ASA Proceedings of the Joint Statistical Meetings, pp. 845-854. American Statistical Association, Alexandria, VA. Statist. 8, 296-309.
 
[22]  Stefan Van Aelst, GertWillems (2012) Fast and Robust Bootstrap for Multivariate Inference: The R Package FRB 53 (3); 57-62.
 
[23]  Wang, F., and Wall, M. M. (2003). Incorporating parameter uncertainty into prediction intervals for spatial data modeled via a parametric variogram. J. Agr. Biol. Environ.
 
[24]  William G. J. and David A. A. (2014), Bootstrap Confidence Regions for Multidimensional Scaling Solutions. American Journal of Political Science, 58 (1); 264-278. Wolfsegger and Jaki (2006),
 
[25]  Zhou, X. H. (2005). Nonparametric confidence intervals for the one-and two-sample problems. Biostatistics, 6, 187-200.
 
Show Less References