In multivariate time series, the prominent method of regression analysis is Vector Auto-Regression (VAR). It is important to understand VAR for more clarity.
The aim of this article is to empirically analyse and investigate the impact of FDI inflows on GDP in India after establishing long run association and causality between these two variables.
The previous article showed lag selection and stationarity for Vector Auto Regression (VAR) with three variables; Gross Domestic Product (GDP), Gross Fixed Capital Formation (GFC) and Private Final Consumption (PFC). This article shows the co-integration test for VAR with three variables.
The previous article showed that the three-time series values Gross Domestic Product (GDP), Gross Fixed Capital Formation (GFC) and Private Final Consumption (PFC) are non-stationary. Therefore they may have long-term causality. The general assumption, in this case, is that consumption PFC affects GDP, therefore these variables might be cointegrated.
The purpose of this article is to empirically examine the impact of FDI inflows on the rate of inflation in India. Therefore this article considers the relation between FDI and another important macroeconomic variable namely rate of inflation.
This article investigates the impact of FDI inflows in India on the reduction of poverty. It examines whether FDI has a positive relationship with per capita income.
The inflow of foreign direct investment (FDI) in India has paved the path for the economical and financial development of a country. There has been significant increase in economic growth after the liberalization policies undertaken by India in 1991 (Nagaraj 1997).
India is gaining importance globally as a rapidly developing economy. Investors from all over the world has showed faith in the flexible Indian economy. One of the major factor for rapid economic growth in India after 1991 can be attributed to huge inflow of foreign capital.