Vector Autoregression or VAR can be estimated using several packages. We will use the "vars" and "tsDyn" packages to illustrate the application of VAR in R. In addition, we will…
There are several packages available for estimating the ARIMA and SARIMA in Rstudio. Autoregressive Integrated Moving Average (ARIMA) and Seasonal Autoregressive Integrated Moving Average (SARIMA) models are often used for…
After estimating Ordinary Least Squares or OLS in Rstudio, we must ensure that the model is a good fit. The model must satisfy the assumptions of OLS including heteroscedasticity, no…
The method of Ordinary Least Squares (OLS) is one of the basic types of analysis in Econometrics. It is widely used in other fields of study as well. R programming…
Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) can provide valuable insights into the behaviour of time series data. They are often used to decide the number of Autoregressive (AR)…
Seasonality, sometimes referred to as seasonal variation, is common in economic time series. The time series variables may change in a cyclical pattern with time. This cyclical pattern is termed…
Autoregressive Integrated Moving Average (ARIMA) models are often used for forecasting purposes. These models for time series data have been observed to provide accurate forecasts. Additionally, these models allow dynamic…
The Sargan Test of Overidentifying Restrictions is applied to check the validity of the instruments used in simultaneous equation models. As the name suggests, it is applicable to overidentified model…
The Two-Stage Least Squares or 2SLS is used to estimate simultaneous equation models or system of equations. Moreover, 2SLS uses a single equation approach. That is, each equation in the…
The Durbin-Wu-Hausman Test of Endogeneity is used to determine whether the endogenous regressors in a simultaneous equation model are truly endogenous. Simultaneous equation models include both endogenous and exogenous variables.…
The VAR-VECM Goodness of fit can be analyzed using similar methods. After estimating Vector Autoregressive (VAR) or Vector Error Correction Mechanism (VECM), it is essential to assess how well the…
The Vector Error Correction Mechanism (VECM) is estimated in the presence of cointegration among the system of variables. It allows us to estimate short-run as well as long-run coefficients. Using…
Vector Error Correction Mechanism (VECM) models are a special application of VAR or Vector Autoregressive Models. The specification of VECM models involves the introduction of error correction terms into the…
Impulse Response Functions or IRFs are used to study the effects of shocks or impulses in a VAR or VECM system. It traces out one unit or one standard deviation…
Information Criteria are used to compare and choose among different models with the same dependent variable. Akaike Information Criterion (AIC) and Schwarz or Bayesian Information Criterion (SIC or BIC) are…
