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Probability of Chi Square Statistics

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Running head: BASIC ECONOMETRICSBasic EconometricsName of the StudentName of the UniversityAuthor note
1BASIC ECONOMETRICSTable of ContentsCase Study One..........................................................................................................................2Answer a.................................................................................................................................2Answer b................................................................................................................................2Answer c.................................................................................................................................3Answer d................................................................................................................................3Answer e.................................................................................................................................5Answer f.................................................................................................................................6Answer g................................................................................................................................7Answer h................................................................................................................................7Answer i.................................................................................................................................9Answer j.................................................................................................................................9Answer k..............................................................................................................................10Answer i...............................................................................................................................10Case Study Two.......................................................................................................................11Answer a...............................................................................................................................11Answer b..............................................................................................................................12Answer c...............................................................................................................................12Answer d..............................................................................................................................14Answer e..............................................................................................................................14Bibliography.............................................................................................................................16
2BASIC ECONOMETRICSCase Study OneAnswer aDependent Variable: LN_S_AUD_NZD_Method: Least SquaresDate: 10/06/17 Time: 15:56Sample: 3/01/1984 12/01/2015Included observations: 128VariableCoefficientStd. Errort-StatisticProb.C-0.9582700.108660-8.8190100.0000LN_NZ_MS_0.0659740.0094247.0003090.0000R-squared0.280018Mean dependent var-0.199089Adjusted R-squared0.274304S.D. dependent var0.089656S.E. of regression0.076376Akaike info criterion-2.290794Sum squared resid0.734995Schwarz criterion-2.246231Log likelihood148.6108Hannan-Quinn criter.-2.272688F-statistic49.00433Durbin-Watson stat0.256500Prob(F-statistic)0.000000The estimated model for predicting the exchange rate isst=0.958+0.06597ln¿The model explains 28% variation in the exchange rate. The Predictor that is New Zealandmoney supply is statistically significant as shown from the p value of the concerned variable.Answer bThe p value of the intercept is 0.0000. This means the null hypothesis of nonsignificance of the model is rejected implying significance of the intercept term. Therefore,the intercept is required for the model.
3BASIC ECONOMETRICSAnswer cResidual plot9.51010.51111.51212.513-0.3-0.2-0.100.10.2ln(NZ MS) Residual Plotln(NZ MS)ResidualsFigure 1: graph of residual against predictor variableAnswer dIn order to test the presence of autocorrelation LM test is used. The null hypothesishere is that the series has no serial autocorrelation and the alternative hypothesis is that theseries has serial autocorrelation problem.Autocorrelation testBreusch-Godfrey Serial Correlation LM Test:F-statistic205.1078Prob. F(2,124)0.0000Obs*R-squared98.28914Prob. Chi-Square(2)0.0000Test Equation:Dependent Variable: RESIDMethod: Least SquaresDate: 10/06/17 Time: 15:57Sample: 3/01/1984 12/01/2015Included observations: 128Presample missing value lagged residuals set to zero.VariableCoefficientStd. Errort-StatisticProb.C-0.0093070.052781-0.1763350.8603LN_NZ_MS_0.0008360.0045780.1826200.8554RESID(-1)1.0516690.08812211.934290.0000RESID(-2)-0.2062680.088168-2.3394760.0209
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