Lecture 32 Summary of previous lecture PANEL DATA SIMULTANEOUS EQUATION MODELS.

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Presentation transcript:

Lecture 32 Summary of previous lecture PANEL DATA SIMULTANEOUS EQUATION MODELS

Topics for today JARQUE BERA TEST F-TEST PARTIAL CORRELATIONS A JOURNEY THROUGH THE COURSE

Jarque Berra (JB)test- A test of normality The JB test of normality is an asymptotic, or large-sample, test. It is based on the OLS residuals. This test first computes the Skewness and kurtosis measures of the OLS residuals and uses the following test statistic. Where n = sample size, S = skewness coefficient, and K = kurtosis coefficient. For a normally distributed variable, S= 0 and K = 3. Therefore, the JB test of normality is a test of the joint hypothesis that S and K are 0 and 3,respectively. Under the null hypothesis that the residuals are normally distributed, Jarque and Bera showed that asymptotically the JB statistic follows the chi-square distribution with 2 df. If the computed p value of the JB statistic is sufficiently low, we reject the hypothesis that the residuals are normally distributed and vice versa.

Example JB- test  Suppose the value of the JB is  The p value of obtaining such a value from the chi-square distribution with 2 df is about 0.68, which is quite high.  In other words, we may not reject the normality assumption.  Of course, bear in mind the warning about the sample size.

F-test-Testing the Overall Signiﬁcance of a Multiple Regression  For certain reasons we cannot use the usual t test to test the joint hypothesis.  However, this joint hypothesis can be tested by the F-test which can be demonstrated as follows.

Partial Correlation

Partial coefficients…

A journey through the course Quantitative Technique: How the Quantitative Techniques Data Sampling Population Sampling Probability Non probability Derivatives Regression: Correlation Assumptions OLS Estimators BLUE Coefficient of determination Problems Standardize variables Eviews

A journey through the course … Hypothesis Testing Dummy Variables: ANOVA Models ANCOVA Models Dummy Variable Trap Qualitative Response Models: LPM LOGIT PROBIT Ordinal Logit and Probit Multinomial Logit and Probit Panel data Simultaneous equation models

THANK YOU