## Cointegration: Meaning, Tests and Models

Cointegration refers to the situation where the variables have a long-run or equilibrium relationship. Such variables move together over time and can be said to have a similar wavelength or…

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# Econometrics

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Cointegration: Meaning, Tests and Models

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Order of Integration of a time series

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ADF Test: Augmented Dickey Fuller Equation

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Dickey Fuller Test of Stationarity

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Autocorrelation function and Stationarity

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Random Walk Model and Stationarity

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Stationarity and Stationary Time Series

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3SLS: Three-Stage Least Squares

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Indirect Least Squares Estimation

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Identification: Rank and Order Conditions

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Simultaneous Equation Bias

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Adjusted R Square and its application

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R square and its drawback

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Ordinary Least Squares Estimation

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Interpreting ACF and PACF plots

Cointegration refers to the situation where the variables have a long-run or equilibrium relationship. Such variables move together over time and can be said to have a similar wavelength or…

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January 31, 2023

If a non-stationary time series has to be differenced “d” times to make it stationary, that time series is integrated of order "d". In other words, the order of integration…

January 30, 2023

The Augmented Dickey Fuller or ADF Test of stationarity is a unit root based test. It attempts to overcome the shortcomings of the original Dickey Fuller test. The Dickey Fuller…

January 27, 2023

The Dickey Fuller Test is a unit root based test of stationarity. The unit root based tests focus on the coefficient associated with the first lag of the time series…

January 26, 2023

The ACF or Autocorrelation Function is one of the most widely used methods to check for stationarity of a time series. Moreover, it also gives valuable insights into the autoregressive…

January 25, 2023

The Random Walk Model is an example of a non-stationary time series. This model is often used to discuss and illustrate the concepts of stationarity, unit root process and order…

January 24, 2023

A time series is said to be stationary if its characteristics do not change with time. Moreover, a stationary time series can be identified as strictly stationary or weak stationary.…

January 23, 2023

The Three-Stage Least Squares or 3SLS is applied to simultaneous equation models. It is different from single equation methods like Indirect Least Squares (ILS) and 2SLS because it is applied…

January 20, 2023

The Indirect Least Squares (ILS) is a method used to estimate simultaneous equation models that are exactly identified. It is a single equation method because it is applied to each…

January 18, 2023

A simultaneous equation model is said to be identified if we can obtain unique estimates of the coefficients in the model. The equations in identified models have a unique structure…

January 16, 2023

The OLS and other single equation models assume that variables treated as independent variables are exogenous. This implies a one-way relationship between independent and dependent variables. It is assumed that…

January 11, 2023

The Adjusted R square addresses the drawback of the R square by penalising the inclusion of additional independent variables. This ensures that additional unnecessary variables are not included simply to…

January 10, 2023

The R square and Adjusted R square are often used to assess the fit of the Ordinary Least Squares model. These measures help ascertain how well the estimated model accounts…

January 9, 2023

OLS or Ordinary Least Squares is the most common method used in Econometrics. It is a linear regression technique that minimizes the sum of squared residuals (error term) to estimate…

January 5, 2023

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)…

June 21, 2022