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The Limits of Mathematics and NP Estimation in ... - Chichilnisky

The Limits of Mathematics and NP Estimation in ... - Chichilnisky

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Us<strong>in</strong>g the SUR Model <strong>of</strong> Tourism Dem<strong>and</strong> for Neighbour<strong>in</strong>g Regions <strong>in</strong> Sweden <strong>and</strong> Norway 113This gives us ˆt 2. Run an OLS on:ˆ X y ˆ ˆ ... ˆ uit t ti 1 t1 2 t2P tP tThis equation can be used for any AR(P) process. From this equation the unrestrictedresidual sum <strong>of</strong> squares (RSS u ).<strong>The</strong> restricted residual sum <strong>of</strong> squares (RSS R ) is given from the follow<strong>in</strong>g equation:<strong>The</strong> null hypothesis is:3. Run an F-test: Xy ˆt t t 1t: .... 0H0 1 2 PF=((RSS R -RSS U )/p) / (RSS U /(T-k-P))This has a distribution: F(P,T-k-P) under the null hypothesis.<strong>The</strong> Breusch-Godfrey test can be tested for AR(P) processes which gives this test a clearadvantage over other available tests for autocorrelation.6.1.3 <strong>The</strong> Ramsey RESET-testRESET test st<strong>and</strong>s for Regression Specification Error Test. <strong>The</strong> test is very general <strong>and</strong> canonly tell you if you have a problem or not. It tests for omitted variables <strong>and</strong> <strong>in</strong>correctfunctional forms or misspecified dynamics <strong>and</strong> also if there is a correlation between theerror term <strong>and</strong> the <strong>in</strong>dependent variable. <strong>The</strong> null hypothesis is:H 0 : E (ε i /X i ) = 0H 1 : E (ε i /X i ) ≠ 0(<strong>and</strong> an omitted variable effect is present)Thus, by reject<strong>in</strong>g the null hypothesis <strong>in</strong>dicates some type <strong>of</strong> misspecification. First a l<strong>in</strong>earregression is specified:y X i i iThis gives the restricted residual sum <strong>of</strong> squares (RSSR). After the RSS R has been found theunrestricted model is presented by add<strong>in</strong>g variables (three fitted values):y X yˆyˆu2 3t i 1 i 2i tThis gives us the unrestricted residual sum <strong>of</strong> squares (RSS U ). In the third step the RESETtestuses a F-test:F= ((RSS R - RSS U )/number <strong>of</strong> restrictions under H 0 ) / (RSS U / (N- number <strong>of</strong> parameters <strong>in</strong>unrestricted model))<strong>The</strong> F-test checks if θ 1 =θ 2 =0, if θ 1 =θ 2 ≠0 I have an omitted variable or a misspecification <strong>in</strong>the model.

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