Tag: assumption tests in STATA
Time series data requires some diagnostic tests in order to check the properties of the independent variables. This is called ‘normality’. This article explains how to perform normality test in STATA.
assumption tests in STATA, empirical analysis with econometrics, STATA for data analysis, time series analysisThis article shows a testing serial correlation of errors or time series autocorrelation in STATA. Autocorrelation problem arises when error terms in a regression model correlate over time or are dependent on each other.
assumption tests in STATA, correlation, empirical analysis with econometrics, STATA for data analysis, time series analysis, trend analysisHeteroskedastic means “differing variance” which comes from the Greek word “hetero” (‘different’) and “skedasis” (‘dispersion’). It refers to the variance of the error terms in a regression model in an independent variable.
assumption tests in STATA, empirical analysis with econometrics, STATA for data analysis, time series analysisThe previous article based on the Dickey-Fuller test established that GDP time series data is non-stationary.
assumption tests in STATA, empirical analysis with econometrics, STATA for data analysis, stationarity test, time series analysisThe purpose of this article is to explain the process of determining and creating stationarity in time series analysis. Creating a visual plot of data is the first step in time series analysis. Graphical representation of data helps understand it better.
assumption tests in STATA, empirical analysis with econometrics, STATA for data analysis, stationarity test, time series analysis, trend analysis