Problem 2 The above linear regression model states that the industrial productiv

Question

Problem 2 The above linear regression model states that the industrial productivity trip is positively affected by the stock market retums 1mrsrl and the employment ratio (em and negatively affected by the oil prices anlo). pl) We are examining the USA market growth during the period 1960-1999. In 1980 we have the introduction of the personal computer and we want to test whether there is any structural change after the year of 1980: Ho: There was no s break for change after 1980 tructural H1: There was a structural break (or change after 1980 You get the follow three outputs by doing the Chow Test. ing Dependent Variable: LNIP Method: Least Squares Sample: 1960 1999 ncluded observations: 40 Variable Coefficient Std. Error t-Statistic 27.59394. 1.584458 17.4 1539 0.0000 LNOL -0.007100 0.157120 -3.884300 0.000 NRSR 0.092188 0.039883 2.311452. 0.0266 EMPL. 0.244800 0.011095 22.08882. 0.0000 R-squared 0.990391 ean dependent var 50.56725 19.53879 Adjusted R-squared 0.989590 S.D. dependent var info criterion 4.312350 S.E. of regression 1.993549 Akaike Sum squared resid 143.0720 Schwarz criterion 481238 Log likelihood -82.24700 H annan-Quinn criter. 414 F-statistic 1236.770 D urbin-Watson stat 0.897776 Prob(F-statistic) 0.000000

Explanation / Answer

Part-A

To apply chow test we proceed as follows:

Run regression of full sample, sample before break and after break and name their residual um of squares as RSS, RSS1, RSS2 respectively.

Calculated F-statistics F=[(Rss-Rss1-Rss2)/k]/[(Rss1+Rss2)/(n-2k)] where k is number of predictors with constant

Compare calculated F with critical F and accept or reject null hypothesis accordingly.

Part-B

From given regression results, Rss=143.07, Rss1=63.27, Rss2=24.30, n=40 and k=4

So, F=[(143.07-63.27-24.30)/4]/[( 63.27+24.30)/(40-2*4)]= 5.07

As this F-value is greater than critical F, null hypothesis is rejected and hence presence of a structural break after 1980 is established.

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