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Cointegration Analysis of Long-run PPP:Testing Purchasing Power Parity (PPP) between India and the US

论文作者:留学生论文论文属性:调研报告 Research Proposal登出时间:2011-04-17编辑:anterran点击率:10272

论文字数:2123论文编号:org201104171818125713语种:英语论文 English地区:美国价格:免费论文

关键词:ointegration AnalysisLong-run PPPTesting Purchasing Power Parity

Testing Purchasing Power Parity (PPP) between India and the US
Part II: Cointegration Analysis of Long-run PPP
The analysis in Seminars 6 and 7 involved univariate tests of PPP based on an analysis of the stability of the (log) real exchange rate. In this 代写留学生论文context the series was: tested for non-stationarity/unit roots using ADF, P-P and KPSS tests; and tested for mean reversion using the GPH long memory test. The results from this analysis suggested conclusively that PPP does not hold in the sample for India and the US.
The main objective in Seminar 8 is to re-assess the evidence for PPP using cointegration techniques applied to the same data-set (ppp_ind_us.wf1). This analysis involves:
• Testing for cointegration using the Engle-Granger 2-Step estimator.
• Testing for cointegration using Johansen’s Full Information Maximum Likelihood (FIML) estimator:
o Estimating the cointegrating rank, long-run parameters and equilibrium adjustment parameters.
• Testing PPP and weak exogeneity restrictions in the Johansen model.
The learning outcomes from this analysis will be to develop your understanding of:
• Applying and interpreting the Engle-Granger 2-Step estimator in Eviews.
• The contexts in which the Engle-Granger 2-Step estimator may be a poor estimator of long-run relationships:
o When regressors are not weakly exogenous for the long run parameters
o In the presence of multiple cointegrating relationships.
• The utility of the Johansen estimator in the above contexts.
• Applying and interpreting the Johansen estimator in Eviews.
• The pitfalls of Johansen. Principally the importance of basing your analysis soundly in economic/Finance theory to help you to:
o Determine the number of cointegrating relationships.
o Identify the long-run parameters.
1
1. Background and overview
The application of cointegration tests is conditional on the individual series following I(1) processes.
Be sure to go through the unit root tests for the (logs of the) nominal exchange rate, Indian WPI and US WPI (as outlined in the handout for Seminars 6/7). Testing for unit roots in the individual series is a necessary preliminary step in a cointegration analysis.
The evidence of the ADF, P-P and KPSS tests indicated conclusively that the (logs of the) nominal exchange rate and Indian WPI are I(1) processes. The evidence for the US WPI was less conclusive with there being some evidence that the series is a trend stationary I(0) process. However this is an unusual result and we will take this series as being I(1) for the purposes of the cointegration analysis.
Firstly we will carry out a single equation cointegration test: the Engle-Granger 2-step estimator. Then we will look at evidence for cointegration based on Johansen’s systems estimator. A summary of the techniques is given below (see also the notes for Lectures 8 and 9).
Engle-Granger 2-Step Estimator
Step 1 is centred on the long-run equation.
ttttPPSεβββ+++=*321lnlnln
The residual term is tested for a unit root using an ADF test: a unit root (non-stationarity) implies that there is no cointegrating relationship. If we reject the null there is evidence of a cointegrating relationship. In this framework, cointegration is a necessary condition for long-run PPP.
PPP also implies the following restrictions on the long-run parameters:
1:320=−=ββH.
These restrictions 论文英语论文网提供整理,提供论文代写英语论文代写代写论文代写英语论文代写留学生论文代写英文论文留学生论文代写相关核心关键词搜索。

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