Josheski, Dushko and Lazarov, Darko and Fotov, Risto and Koteski, Cane (2011): ISLM model for US economy: testing in JMULTI.

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Abstract
In this paper ISLM model, has been introduced as time series model. Standard VAR, VECM test have been applied .Three variables that we estimated were: logarithm of real GDP (q), 3 month interbank interest rate (i), real monetary base (m).VECM mechanism shows that if the system is in disequilibrium alteration in the change of interbank interchange interest rate, log of real US gdp , and monetary base will be downward 5,5%,4,6% and 0,4% respectively.
Item Type:  MPRA Paper 

Original Title:  ISLM model for US economy: testing in JMULTI 
English Title:  In this paper ISLM model, has been introduced as time series model. Standard VAR, VECM test have been applied .Three variables that we estimated were: logarithm of real GDP (q), 3 month interbank interest rate (i), real monetary base (m).VECM mechanism shows that if the system is in disequilibrium alteration in the change of interbank interchange interest rate, log of real US gdp , and monetary base will be downward 5,5%,4,6% and 0,4% respectively. 
Language:  English 
Keywords:  ISLM, VAR, VECM,JMULTI 
Subjects:  N  Economic History > N1  Macroeconomics and Monetary Economics ; Industrial Structure ; Growth ; Fluctuations E  Macroeconomics and Monetary Economics > E1  General Aggregative Models > E12  Keynes ; Keynesian ; PostKeynesian C  Mathematical and Quantitative Methods > C4  Econometric and Statistical Methods: Special Topics > C40  General E  Macroeconomics and Monetary Economics > E2  Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy > E21  Consumption ; Saving ; Wealth 
Item ID:  34024 
Depositing User:  DJ Josheski 
Date Deposited:  10. Oct 2011 11:13 
Last Modified:  14. Mar 2015 01:33 
References:  1. Lutkepohl, H. & Poskitt, D. S. (1991). Estimating orthogonal impulse responses via vector autoregressive models, Econometric Theory 7: 487–496. 2. Lutkepohl, H. & Poskitt, D. S. (1996). Testing for causation using infinite order vector autoregressive processes, Econometric Theory 12: 61–87. 3. Lutkepohl, H. & Poskitt, D. S. (1998). Consistent estimation of the number of cointegration relations in a vector autoregressive model, in R. Galata & H. K¨uchenhoff 4. (eds), Econometrics in Theory and Practice. Festschrift for Hans SchneeweiЯ, Physica, Heidelberg, pp. 87–100. 5. Lutkepohl, H. & Reimers, H.E. (1992a). Grangercausality in cointegrated VAR processes: The case of the term structure, Economics Letters 40: 263–268. 6. Lutkepohl, H. & Reimers, H.E. (1992b). Impulse response analysis of cointegrated systems, Journal of Economic Dynamics and Control 16: 53–78. 7. L¨utkepohl, H. & Saikkonen, P. (1999a). A lag augmentation test for the cointegrating rank of a VAR process, Economics Letters 63: 23–27. 8. L¨utkepohl, H. & Saikkonen, P. (1999b). Order selection in testing for the cointegrating rank of a VAR process, in R. F. Engle & H. White (eds) 9. Cointegration,Causality, and Forecasting. A Festschrift in Honour of Clive W.J. Granger,Oxford University Press, Oxford, pp. 168–199. 10. L¨utkepohl, H. & Saikkonen, P. (2000). Testing for the cointegrating rank of a VAR process with a time trend, Journal of Econometrics 95: 177–198. 11. L¨utkepohl, H., Saikkonen, P. & Trenkler, C. (2001). Maximum eigenvalue versus trace tests for the cointegrating rank of a VAR process, Econometrics Journal4: 287–310. 12. L¨utkepohl, H., Saikkonen, P. & Trenkler, C. (2004). Testing for the cointegrating rank of a VAR process with level shift at unknown time, Econometrica 72: 647– 662. 13. L¨utkepohl, H. & Schneider, W. (1989). Testing for nonnormality of autoregressive time series, Computational Statistics Quarterly 5: 151–168. 14. MacKinnon, J. G., Haug, A. A. & Michelis, L. (1999). Numerical distribution functionsof likelihood ratio tests for cointegration, Journal of Applied Econometrics 14: 563–577. 15. Magnus, J. R. (1988). Linear Structures, Charles Griffin, London. 16. Magnus, J. R. & Neudecker, H. (1988). Matrix Differential Calculus with Applications in Statistics and Econometrics, John Wiley, Chichester. 17. Mann, H. B. & Wald, A. (1943). On the statistical treatment of linear stochastic difference equations, Econometrica 11: 173–220. 18. Mardia, K. V. (1980). Tests for univariate and multivariate normality, in P. R. 19. Krishnaiah (ed.), Handbook of Statistics, Vol. 1, NorthHolland, Amsterdam, pp. 279–320 20. Harris. R, and Sollis R. (2003) Applied time series modelling and forecasting Chichester : John Wiley & Sons 21. Holden K, and Thompson J, (1992) Cointegration : An introductory Survey , British Review of Economic Issues,14.(33)(June) : 156 22. Perron P. (1989) , The great crash the oil price , and the unit root hypothesis ,Econometrica , Vol 57, No 6 , 1361 1401 24. Oskooe Bahmani Monsen (1992) A Time Series Approach to test productivity bias hypothesis in Purchasing Power Parity, Kyklos Vol.45 ,227236 25. Mac Donald Ronald , Ricci Luca, (2001) PPP and Ballasa Samuelson Effect 
URI:  http://mpra.ub.unimuenchen.de/id/eprint/34024 