格兰杰因果关系
协整
经济
计量经济学
物价指数
批发价格指数
背景(考古学)
膨胀(宇宙学)
因果关系(物理学)
单位根
消费价格指数(南非)
订单(交换)
价格水平
宏观经济学
货币政策
中等价位
生物
财务
理论物理学
古生物学
物理
量子力学
出处
期刊:Indian Growth and Development Review
[Emerald (MCB UP)]
日期:2012-09-21
卷期号:5 (2): 151-172
被引量:6
标识
DOI:10.1108/17538251211268071
摘要
Purpose The purpose of this study is to attempt to analyze Granger causality in the frequency domain framework between producers' prices measured by wholesale price index (WPI) and consumers' prices measured by consumer price index (CPI) in the context of India. Design/methodology/approach Analysis was carried out in the framework of time series and for analysis Johansen and Juselius's maximum likelihood approach for cointegration was applied after confirming that variables are integrated of order one, i.e. I(1) through the Lee and Strazicich unit root test. Finally, Granger causality was tested in the frequency domain by utilizing a recently developed approach of Lemmens et al. over the period January 1957‐February 2009. Findings The paper finds that CPI Granger cause WPI at a lower, intermediate as well as higher levels of frequency, reflecting very long‐run, intermediate as well as short‐run cycles. By contrast WPI Granger cause CPI at 5 percent level of significance was found at intermediate frequencies, reflecting significant intermediate cycles. Research limitations/implications The study reveals that CPI is a leading indicator of producers' prices and inflation (i.e. WPI). This gives an indication that Indian policy analysts ought to control for factors affecting CPI in order to have control on WPI since WPI is used for making various macroeconomic indicators in real terms. Originality/value The main contribution of the paper is to show the evidence of bidirectional causality between WPI and CPI. Furthermore, use of a recent approach developed by Lemmens et al. for Granger causality in the frequency domain in this study is also relatively new. To the best of the author's knowledge there is no such study in this area either for developed or developing economy to date.
科研通智能强力驱动
Strongly Powered by AbleSci AI