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Econometrics - Heteroskedasticity

 Econometrics -- Heteroskedasticity Dissertation Econometrics -- Heteroskedasticity Dissertation

ECONOMETRICS EXERCISE 3

TRAN THI ANH NGUYET twenty-eight March, 2013

1 . The information set CEOSAL2. DTA includes information on 177 CEOs. From this sample, the standard annual income is $865, 864, 4 hundred with the tiniest and greatest being $100, 000 and $5, 299, 000, 1000, respectively. Another most interesting variable can be sales with all the average being $3, 5329, 463, 000, and its the actual and major being $29, 000 and $51, three hundred, 000. Using the data arranged, the following OLS regression is definitely obtained: (1). Л† lnsalary = 5. 58 + 0. 192. lnsales + 0. 094. lnmktval + 0. 017. ceoten в€’ 0. 009comten 0. 253. 0398 0.. 0489 zero. 0055 zero. 0033

reg lnsalary lnsales lnmktval ceoten comten

Supply Model Left over Total ln_salary ln_sales ln_mktval ceoten comten _cons. DURE 22. 5202805 42. 1259326 64. 6462131 Coef.. 1918844. 0940901. 0169211 -. 009415 4. 576374 df four 172 176 MS your five. 63007012. 244918213. 367308029 capital t 4. 82 1 . ninety two 3. 05 -2. 82 18. 05 P> |t| 0. 1000 0. 056 0. 003 0. 005 0. 500 Number of obs F( 4, 172) Prob > F R-squared Adj R-squared Root MSE = = sama dengan = sama dengan = 177 22. 99 0. 0000 0. 3484 0. 3332. 49489

Std. Err.. 039824. 0489194. 0055389. 0033341. 2535074

[95% Conf. Interval]#@@#@!!. 1132777 -. 0024696. 0059882 --. 0159959 5. 075988. 2704911. 1906498. 0278541 -. 002834 5. 07676

Interprete the effect. OLS Coefficients The main changing of interest can be lnsales. In the event that all other elements are the same, 10 even more percentage of annual product sales increases salary per year of any CEO simply by 1 . 92%. By mean of level changes, $353, 294, 630 increase in annual sales, typically, raises the CEO's earnings by $101, 740, 800. This seems like a reasonably large influence. β2 = 0. 94 means that anytime the market benefit of the firm is 10% higher, the CEO's earnings is forecasted to rise regarding 0. 94%, holding other factors fixed. When compared with 1 . 92%, this is not a huge effect, but it should not negligible, either. The variable ceoten is years as CEO with the current company and comten is total years with the firm with the OLS estimators getting 0. 0169 and −0. 0094, respectively. Other factors fixed, one more yr as a CEO with the firm increases his salary by about 1 . 69%. However , one more year while using firm but is not as a CEO, lowers roughly his earnings by 0. 094%. The first one is likely while our requirement since, however the second a single, the effect of comten at first seems unusual. " Superstar” effect hypothesis of Rosen (1990) declares that the industry must identify new ability and reassign control over jobs from more mature to young generations. It implies that when a firm employs a CEO on labor market with long-time knowledge working as non-CEO, it's likely he was not hired like a " superstar” (CEO) by simply other firms. Therefore , the firm may possibly have no willingness to bet up his salary. In case the model meant is certainly not mispecified or perhaps problematic, the intercept coefficient seems fewer practically important as every independent factors have no alter, the total annual salary remains predicted to enhance about four. 57%. This can be a very large number in comparison with influences of changes in sales plus the firm's market value. Otherwise, if there is any disregarded variables, this kind of change could be more important.

Statistical Significance The big t statistic upon lnsales, ceoten and comten are four. 82, several. 05, and−2. 82 which can be large enough in magnitude in conclusion that all these variables are statiscally significant at the five per cent level. How about the statistical significance in the market value varying? The to statistic in lnmktval sama dengan 1 . 92 and it is likely not to end up being high to imply that lnmktval is statistically significant at 5% with 2-sided test. However , whenever we expand the significance level to 10%, with 177 − six = 171 df pertaining to the 2-sided alternative, H0: β = 0, the 10% critical value is around 1 . 645. Hence, lnmktval is almost significant against the 2-sided alternative on the 10% level. In fact , all of us will show later on that some outliers and influential findings make the significantly less satistical significance of lnmktval. R-squared R2 = 0. 3484, therefore the four predictors with each other explain regarding 34. 84% of the percentage change in...