In India, in the last two decades, the inflow of FDI has grown significantly. Similarly, its environmental pollution has also been rising since 1991 due to an increase in economic activity. This article empirically investigates the impact of FDI on air pollution in India.
environmental cost of fdi, fdi environment relation, the two faces of fdiThis article focuses on a number of water pollution indicators and their use in economic studies. This is because indicators of water pollution help analyse the impact of economic growth on the environment.
environmental cost of fdi, fdi environment relation, the two faces of fdiThe previous article (Pooled panel data regression in STATA) showed how to conduct pooled regression analysis with dummies of 30 American companies. The results revealed that the joint hypothesis of dummies reject the null hypothesis that these companies do not have any alternative or joint effects. Therefore pooled regression is not a favourable technique for […]
exploratory model analysis, panel data analysis, STATA for data analysisThe underlying assumption in pooled regression is that space and time dimensions do not create any distinction within the observations and there are no set of fixed effects in the data.
exploratory model analysis, panel data analysis, STATA for data analysisThis article of the module explains how to perform panel data analysis using STATA. In the case of panel data, the observations are present in time and space dimensions. For instance, a survey of the same cross-sectional unit such as firm, country or state over time.
panel data analysis, STATA for data analysisThe problem of multicollinearity arises when one explanatory variable in a multiple regression model highly correlates with one or more than one of other explanatory variables. It is a problem because it underestimates the statistical significance of an explanatory variable (Allen, 1997).
STATA for data analysisThe previous article showed how to initiate the AutoRegressive Conditional Heteroskedasticity (ARCH) model on a financial stock return time series for period 1990 to 2016. It showed results for stationarity, volatility, normality and autocorrelation on a differenced log of stock returns.
STATA for data analysis, time series analysisIn multivariate time series, the prominent method of regression analysis is Vector Auto-Regression (VAR). It is important to understand VAR for more clarity.
exploratory model analysis, STATA for data analysis, time series analysis