SAMVAD: International Journal of Management

Open Access Open Access  Restricted Access Subscription Access

Long-term Association in Time-Series through Cointegration Analysis: A Case Study


Affiliations
1 SIBM Pune, Symbiosis International University, Pune, India
 

The association among variables, especially when endogeneity is not defined, can be modelled using Optimum Least Square. In the case of endogeneity, Two Stage Least Square Method (TSLS) can be deployed. However, presence of Cointegration can jeopardise the existing association among the variables in both the cases. Even if, either Optimum Least Square (OLS) or TSLS can be estimated but the estimated coefficients in the presence of Cointegration will not be appropriate and may be misleading. Testing of cointegration is done by any of the three methods, which is further elaborated by Error Correction Models (ECM) to explore the nature of Cointegration relation.

Keywords

Cointegration, Endogeneity, Error Correction Model (ECM), Stationarity, Vector Auto Regression (VAR).
User
Notifications
Font Size

  • Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19, 716-723. https://doi.org/10.1109/TAC.1974.1100705.

  • Brooks, Chris (2002). Introductory econometrics for finance. United Kingdom: Oxford University Press.

  • Engle, R.F. & Granger, C.W. (1987). Co-integration and error correction: Representation, estimation and testing. Econometrica, 55(2), 251-276. https://doi.org/10.2307/1913236.

  • Engle, R.F. & Yoo, B.S. (1987). Forecasting and testing in co-integrated systems. Journal of econometrics, 35(1), 143-159. https://doi.org/10.1016/0304-4076(87)90085-6.

  • Ghosh, Sajal (2010). Examining carbon emission economic growth nexus for India: A multivariate co-integration approach. Energy Policy, 38(6), 3008-3014. https://doi.org/10.1016/j.enpol.2010.01.040.

  • Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control, 12(2-3), 231-254. https://doi.org/10.1016/0165-1889(88)90041-3.

  • Johansen, S. (1991). Estimation and hypothesis testing of cointegration vectors in gaussian vector autoregressive models. Econometrica, 59(6), 1551-1580. https://doi.org/10.2307/2938278.

  • Johansen, S. & Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration-with applications to the demand for money. Oxford Bulletin of Economics and Statistics, 52(2), 169-210. https://doi.org/10.1111/j.1468-0084.1990.mp52002003.x.

  • Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461-464. https://doi.org/10.1214/aos/1176345415, https://doi.org/10.1214/aos/1176344136.


Abstract Views: 223

PDF Views: 107




  • Long-term Association in Time-Series through Cointegration Analysis: A Case Study

Abstract Views: 223  |  PDF Views: 107

Authors

Shailesh Rastogi
SIBM Pune, Symbiosis International University, Pune, India

Abstract


The association among variables, especially when endogeneity is not defined, can be modelled using Optimum Least Square. In the case of endogeneity, Two Stage Least Square Method (TSLS) can be deployed. However, presence of Cointegration can jeopardise the existing association among the variables in both the cases. Even if, either Optimum Least Square (OLS) or TSLS can be estimated but the estimated coefficients in the presence of Cointegration will not be appropriate and may be misleading. Testing of cointegration is done by any of the three methods, which is further elaborated by Error Correction Models (ECM) to explore the nature of Cointegration relation.

Keywords


Cointegration, Endogeneity, Error Correction Model (ECM), Stationarity, Vector Auto Regression (VAR).

References