# Tag: time series for econometrics

## How to perform Granger causality test in STATA?

By Rashmi Sajwan & Priya Chetty on October 16, 2018

Applying Granger causality test in addition to cointegration test like Vector Autoregression (VAR) helps detect the direction of causality. It also helps to identify which variable acts as a determining factor for another variable. This article shows how to apply Granger causality test in STATA.

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## How to identify ARCH effect for time series analysis in STATA?

By Divya Dhuria & Priya Chetty on October 4, 2018

Volatility only represents a high variability in a series over time.This article explains the issue of volatility in data using Autoregressive Conditional Heteroscedasticity (ARCH) model. It will identify the ARCH effect in a given time series in STATA.

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## How to perform Johansen cointegration test in VAR with three variables?

By Divya Dhuria & Priya Chetty on September 27, 2018

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.

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## How to build the univariate ARIMA model for time series in STATA?

By Divya Narang & Priya Chetty on February 6, 2018

Autoregressive Integrated Moving Average (ARIMA) is popularly known as Box-Jenkins method. The emphasis of this method is on analyzing the probabilistic or stochastic properties of a single time series. Unlike regression models where Y is explained by X1 X2….XN regressor (like the introductory case where GDP is explained by GFC and PFC), ARIMA allows Y (GDP) to be explained by its own past or lagged values.

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