.png){kind=icon}
.png){kind=icon}
Return
Hidden panel cointegration
.png){kind=icon}
OA
AI
DOI：10.1016/j.jksus.2018.07.011.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper focuses on an important empirical and methodological research question, namely possibly asymmetric and hence nonlinear cointegrating relationships between variables. It extends the Granger and Yoon (2002) method on hidden cointegration for time series data to a panel data framework. Solutions are provided for transforming the panel data variables with deterministic as well as stochastic trend parts into partial cumulative sums for positive and negative components. The transformed data can then be used to test for the long run relationship between the underlying components. The proposed method is applied to a small panel of three Scandinavian countries examining the presence of a long-term relationship between government consumption and economic growth based on quarterly data. First, the standard method that does not allow for asymmetry was implemented. The results do not provide evidence of a long-term relationship between the two variables. However, the results based on the tests suggested in this paper indicate that the underlying variables are indeed related in the long run. Thus, it might be important to separate the impact of positive shocks from the negative ones when the long run relationships between panel data variables are investigated. (C) 2018 The Author. Production and hosting by Elsevier B.V. on behalf of King Saud University.
Keywords:
Asymmetry
Panel data
Cointegration
Testing
Government consumption
Output
Scandinavia
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
J
IF:
3.6
Papers:
2.8K
Citations:
1.0W