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La monnaie unique europeenne et sa relation au ... - Eumed.net

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<strong>La</strong> régression linéaire est plus appropriée que la semi-logarithmique (meilleur R² est le T<br />

de Student du trend est plus élevé (plus significatif)).<br />

4) Polynomial.<br />

Dependent Variable: DET<br />

M<strong>et</strong>hod: Least Squares<br />

Date: 09/12/06 Time: 09:01<br />

Sample: 1880 1913<br />

Included observations: 30<br />

Excluded observations: 4<br />

DET=C(1)+C(2)*@TREND+C(3)*@TREND^2+C(4)*@TREND^3+C(5)<br />

*@TREND^4<br />

L<strong>La</strong>a moonnnnaai iiee uunni iiqquuee eeuur rooppééeennnnee. ..<br />

Coefficient Std. Error t-Statistic Prob.<br />

C(1) 707.4560 20.62418 34.30226 0.0000<br />

C(2) 2.319773 9.115614 0.254484 0.8012<br />

C(3) 0.372116 1.178640 0.315717 0.7548<br />

C(4) -0.029357 0.054716 -0.536529 0.5963<br />

C(5) 0.000345 0.000824 0.418899 0.6789<br />

R-squared 0.816175 Mean dependent var 696.0667<br />

Adjusted R-squared 0.786763 S.D. dependent var 61.29237<br />

S.E. of regression 28.30336 Akaike info criterion 9.674850<br />

Sum squared resid 20027.00 Schwarz criterion 9.908383<br />

Log likelihood -140.1227 Durbin-Watson stat 1.109067<br />

L’ajustement polynomial est le meilleur : il tient compte de la rupture de la série, le R²<br />

est très bon.<br />

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TToomee IIVV I<br />

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