Use the STATA output to answer the following questions.

Questions:

a. Report the least squares estimates of the coefficients and corresponding pvalues.

b. Are the signs of these estimates consistent with economic theory? Explain your answer.

c. Determine whether the estimated coefficients are statistically significant at the 5% level of significance.

d. Is the overall significance of the model at the 5% level of significance?

e. Based on part d above, will stimulating output growth or controlling for inflation have an impact on the rate of return? Explain your answer.

f. How much of the variation in the real rate of return (on common stocks) does this model explain?

A financial analyst wishes to test the relationship between GNP and foreign earnings from developing countries. Theoretically, growth should be higher for those countries with a high foreign income and is external to the local economy. The two sources most readily measured are foreign direct investment and earning from exports. Use the STATA output to answer the questions. GNP is in billion dollars while all other variables are expressed in million dollars. 10.0 copyright 1984-2008 Statistics/Data Analysis tatacorp 1905 Lakeway Drive pecial Edition lege Station, Texas 77845 USA 800-STATA-PC http://www.stata. com 979-696-4600 stata@stata. com 979-696-4601 (fax) 20-user Stata for Windows (network) perpetual license: Serial number: 81910524292 Licensed to: school of Economics and Finance university of Western sydent Notes : (/m# option or -set memory-) 10.00 MB allocated to data (/vi option or -set maxvar-) 5000 maximum variables New update available; type -update all- insheet using "E: \\My Documents\\Teaching\\ FM2009\\Exercises\\sessi on\\ForeignEarnings. txt" (4 vars, 25 obs) tsset obs time variable: obs, 1 to 25 delta: 1 unit summarize gnp directforeigninvestment exports variable Obs Mean Std. Dev. Min Max gnip 124.2 111 . 4342 451 directfore~t exports 22 142 . 64 256.72 189 . 4172 22 388 regress gnp directforeigninvestment exports source 55 MS Number of obs 25 F ( 2, 22) 65 . 90 Model 255393.33 0 . 0000 Residual 12628 . 6696 22 127696 . 665 Prob> F 1937. 6668 R-squared 0. 8570 Adj R-squared = 0.8440 Total 298022 24 12417.5833 Root MSE 44.019 gnp coef. std. Err. P>It1 [95% conf. Interval] directfore~t -. 001395 . 1593158 -0. 01 0. 993 . 3317957 . 3290056 exports . 545196 . 0827292 6. 59 0.000 . 3736261 . 7167659 cons -15.56372 15.94247 -0. 98 0.340 -48 . 62639 17. 49894 Revision Page 1 estat hettest Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: constant variance Variables: fitted values of gnp chi2 (1) 11. 94 Prob > chi2 0.000 es tat vi f variable VI /VIE di rectforent 3.04 0. 328784 exports 3.04 0. 328784 Mean VIE 3.04 es tat hettest, ii d Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance variables: fitted values of gnp chi 2(1) 8.46 Prob > chiz 0.0036 estat dwatson Durbin-Watson d-statistic( 3, 25) = 1. 215631 correlate directforeigninvestment exports (obs=25) direct~t exports directfore~t 1.0000 exports . 8193 1.0000 Dickey-Fuller test for unit root Number of obs Interpolated Dickey-Fuller . Test H Critical 5 Catlcal 10% Critical Stat IstIc value Value -5.137 4.159 -3.301 -3.182 Mackmnon approximate p-value for Z(1) 0.0001 predict error, ,;b s>;test error Skewness/Kurtosis tests for Normality --Joint-- Van able Qba PetSkewnessl Py(KUnOSIS) adl ch12121 Prob Ch12 error 50 0.0007 0.1770 10.91 summarize error, detail Linear prediction Percentiles Smallest 8.39421 3.39421 S! 14.88495 3.39421 10% 25.2339 14.88495 Obs 50.79673 14.88495 Sum of Wgt. 50% 98.7405 Mean 124.2 Largest Sid. Dev. 102.0991 75! 171.471 353.781 90! JJS.0458 151.7814 Variance 10424.22 95! 351.7814 178.0717 Skewnes 1.2602 178.0717 378.0717 Kurtosis 3. 70064