Press the Save button on the Workfile toolbar to save a copy of the Workfile to disk. The Print button allows you to print the current view of the object (the contents of the window).
STUDY AT A TOP RANKED
Perhaps the easiest way is to select Object/New Object from the main menu or toolbar of the work file and click Group. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more.
INTERNATIONAL BUSINESS SCHOOL
Eviews Functions
- Operators
- Basic Mathematical Functions
- Statistical functions
- Statistical Distribution Functions
Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. per ad to read more.
Programming in Eviews
- Program Variables
Control variables are assigned in the usual way, with the name of the control variable to the left of the character and the numeric value or expression to the right. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. on the ad to read more Click on the ad to read more.
CLICK HERE
Alternatively, you can run this program by clicking the Run button in the program window or by selecting File/Run. Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on ad to read more Click on ad to read more Click on ad to read more Click on ad to read more.
Regression Model
Introduction
Linear Regression Model
- Hypothesis testing
- Residual diagnostics
- Example: Factor Model
- Programming Example
Note that in the latter specification the dependent variable must come first. EViews also provides a number of tests to test the hypothesis of homoscedasticity on the regression.
Nonlinear Regression
Interpretation of estimation results, residual diagnostics and inference can be done in the same way as in OLS regression. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. per ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more. Click on the ad to read more Click on the ad for more Click on the ad for more Click on the ad for more Click on the ad for more.
EXPERIENCE THE POWER OF FULL ENGAGEMENT…
RUN FASTER
Univariate Time Series: Linear Models
Introduction
Stationarity and Autocorrelations
- Stationarity
- Autocorrelation
- Example: Variance Ratio Test
The least squares predictor of Yt based on the past Yt−1 is the function f(Yt−1) that minimizes E[(Yt−f(Yt−1))2]. Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more to read Click on the ad to read more.
SETASIGNThis e-book
ARMA processes
- Autoregressive process
- Moving average process
- ARMA process
- Estimation of ARMA processes
- Example: ARMA in EViews
- Programming example
Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more Click the ad to read more to read Click on the ad to read more Click on the ad to read more. Remember that to build a correlogram one must click on the icon when examining the time series and choose View/Correlogram.
Stationarity and Unit Roots Tests
- Introduction
- Unit Roots tests
- Dickey-Fuller test
- Augmented Dickey-Fuller test
- Phillips and Perron tests
- Stationarity tests
- Example: Purchasing Power Parity
On the other hand, stationarity tests take the null hypothesis that Yt trend is stationary. The above test is based on the assumption that the error terms are iid and there is no drift (intercept term) in the model.
Univariate Time Series: Volatility Models
- Introduction
- The ARCH Model
- Example: Simulating an ARCH (p) model in EViews
- The GARCH Model
- Example: Simulating an GARCH(p, q) model in EViews
- GARCH model estimation
- GARCH Model Extensions
- EGARCH Model
- TGARCH Model
- PGARCH Model
- Prediction
- Example: GARCH Estimation
According to the GARCH(p, q) model, the conditional variance of ut, σt2, depends on the squared residuals in the previous p periods, and the conditional variance in the previous q periods. You must then specify the conditional mean equation as in the case of the least squares model (the dependent variable must be first).
Multivariate Time Series Analysis
Introduction
Vector Autoregression Model
- Estimation of VARs and Inference on coefficients
- Granger Causality
- Impulse Response and Variance Decompositions
- VAR in EViews
Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more. Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more Click on the ad to read more.
Cointegration
- Spurious Regression
- Cointegration
- Error Correction Models
- Tests for Cointegration: The Engle-Granger Approach
- Example in EViews: Engle-Granger Approach
- Tests for Cointegration: The Johansen’s Approach
- Example in EViews: Johansen’s Approach
The Phillips-Perron test produces a test statistic whose value is at the border of the rejection region. Note the warning at the top of the output window that says critical values do not predict exogenous sets.
Bibliography
MacKinnon, J.: 1996, Numerical distribution functions for unit root and cointegration tests, Journal of Applied Econometrics11, 601–618. Osterwald-Lenum, M.: 1992, Notation with quantiles of the asymptotic distribution of the maximum likelihood cointegration rank statistic, Oxford Bulletin of Economics and Statistics.
