Mohamed, Issam A.W. (2011): Utilizing System Dynamics Models in Analyzing Macroeconomic Variables of Yemen.

PDF
MPRA_paper_31692.pdf Download (4Mb)  Preview 
Abstract
The purpose of the System Dynamics method is to study the relationship between structure and behavior in nonlinear, dynamic systems. In such systems, the significance of various structural components to the behavior pattern exhibited, changes as the behavior unfolds. Changes in structural significance modify that behavior pattern which, in turn, feeds back to change the relative significance of structural components. We develop a macroeconomic model through which we can study the characteristics of the feedback between structure and behavior. This model is based on multiplieraccelerator model, and inventory – adjustment model. This work is an extension of the work by Nathan Forrester on the use of basic macroeconomic theory to stabilize policy analysis. The design of a System Dynamics model begins with a problem and a time frame that contribute to the problem. They are listed and their structural relationships sketched the factors with particular attention to characterizing them as levels (or stocks) and rates (or flows) that feed or drain them. Levels and rates must alternate in the model; no level can control another without an intervening rate or any rate influence another without an intervening level.
Item Type:  MPRA Paper 

Original Title:  Utilizing System Dynamics Models in Analyzing Macroeconomic Variables of Yemen 
English Title:  Utilizing System Dynamics Models in Analyzing Macroeconomic Variables of Yemen 
Language:  English 
Keywords:  System Dynamics, Macroeconomic Variable, Economic Analysis, Yemen 
Subjects:  C  Mathematical and Quantitative Methods > C6  Mathematical Methods; Programming Models; Mathematical and Simulation Modeling > C68  Computable General Equilibrium Models C  Mathematical and Quantitative Methods > C0  General A  General Economics and Teaching > A1  General Economics C  Mathematical and Quantitative Methods > C0  General > C00  General C  Mathematical and Quantitative Methods > C6  Mathematical Methods; Programming Models; Mathematical and Simulation Modeling > C67  InputOutput Models A  General Economics and Teaching > A1  General Economics > A10  General C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C10  General B  History of Economic Thought, Methodology, and Heterodox Approaches > B4  Economic Methodology > B40  General C  Mathematical and Quantitative Methods > C2  Single Equation Models; Single Variables > C20  General C  Mathematical and Quantitative Methods > C0  General > C02  Mathematical Methods C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C15  Statistical Simulation Methods: General C  Mathematical and Quantitative Methods > C2  Single Equation Models; Single Variables > C22  TimeSeries Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models C  Mathematical and Quantitative Methods > C3  Multiple or Simultaneous Equation Models; Multiple Variables > C30  General C  Mathematical and Quantitative Methods > C0  General > C01  Econometrics 
Item ID:  31692 
Depositing User:  Professor Issam A.W. Mohamed 
Date Deposited:  21. Jun 2011 13:36 
Last Modified:  14. Feb 2013 01:50 
References:  1. Dominick S. (1982) Statistics and econometrics, theory and problems. McGraw Hill. 2. Hinkeley, N., Reid L. and Snell, E. (1991) Statistical theory and modeling. Chapman hall. 3. Frederic Barlat, LongQing Chen (2004) MONTE CARLO METHODS. Wiley Verlag GmbH. 5. Anthony S. Campagna, (1974) Macroeconomics Theory and Policy. University of Vermont. 6. Paul Samuelson & William D. Nordhous (1992) Economics. Fourteenth edition 7. Karl E, case, Ray c. fair 19891992, Principles of macroeconomic. second edition, prentice hall inc 8. Paul, W. (1989) Macroeconomic from theory to practice,. McGraw Hill, 9. FernandezVillaverde, Juan F. RubioRamerez (2004) Estimating Macroeconomic Models: A Likelihood Approach. 10. Central Bank of Yemen (2006) World Economic Situation and Domestic Economic Developments report. 11. Central Statistical Organization (2005) Trade Statistics Indicators book. 12. Kevin Dooley (2002) Simulation Research Methods. Arizona State University. 13. Kristin den Exter (2004) Integrating Environmental Science and Management: The Role of System Dynamics Modeling, PhD Dissertation. 14. Allenna Leonard with Stafford Beer (19994)The system perspective: Methods and Models for the future. 15. Ford, A. (1999) Modeling the Environment: An Introduction to System Dynamics Modeling of Environmental Systems. 16. Craig W. Kirkwood (1998) System Dynamics Methods: A Quick Introduction, College of Business, Arizona State University, Original material copyright, 1998 17. Bernhard J. Angerhofer, Marios C. Angelides (2000) System Dynamics Modeling in supply chain Management: Research Review, Department of Information Systems and Computing, Brunel University,Uxbridge, Middlesex. UK. 18. Rudolf J. Freund, William J. Wilson (1998) Regression analysis, statistical modeling of a response variable. Academic Press. 19. Bill Harris (2000) Applying System Dynamics to Business: An Expense Management Example, http://facilitatedsystems.com/ 20. Forrester, J. (1989) The Beginning of System Dynamics. System Dynamics Society, Stuttgart, Germany. 21. King, I. (2002) A Simple Introduction to Dynamic Programming in Macroeconomic Models, Department of Economics, University of Auckland. New Zealand. 22. Fernando Bignami, Luca Colombo, Gerd Weinrich (2000) A Dynamic Macroeconomic Model with Stochastic Rationing. 23. Schneider, M. and Spitzer, M. (2004) Forecasting Austrian GDP using the generalized dynamic factor model. 24. Jiuping Xu (2006) Modeling and simulation of a System Dynamics model for counrty cycle economy, World Journal of Modeling and Simulation Vol. 2, No. 3. 25. Lucia Breierova amd Choudhari, M. (2001) An Introduction to Sensitivity Analysis. Massachusetts Institute of Technology. 26. James M. Lyneis (1998) System Dynamics in Business Forecasting: A Case Study of the Commercial Jet Aircraft Industry. 27. Loutfi M., Moscardini, O. and Lawler K., (1995) Using System Dynamics to analyse the Economic Impact of Tourism Multipliers, School of Computing, Engineering and Technology, University of Sunderland, Sunderland, United Kingdom. 28. Goldstein, H. (1999) Multilevel statistical models,, institute of education, multilevel models project. New York. 29. Kleijen, J. (1990) Sensitivity Analysis of System Dynamics Models: Regression Analysis and Statistical Design. 30. Shoukath Ali. and Ramaswamy, N. (1993) Statistical Methods for Improving Confidence in System Dynamics Models. A case Study on Blood Bank Inventory Management Systems. 31. Lucia Breierova, Mark Choudhari (1996) An Introduction to Sensitivity Analysis Prepared for the MIT System Dynamics. Education Project Under the Supervision of Jay W. Forrester. 32. John D. Sterman (2000) Business Dynamics, system thinking and modeling for a complex world. McGrawHill. 
URI:  http://mpra.ub.unimuenchen.de/id/eprint/31692 