Assuming the model is re-estimated with additional new variable (lagged of LGDP), based on the new estimated results, what is your conclusion about the autocorrelation diagnostic test? If there is diagnostic problem, show how to solve the problem. Table 2C: Estimated Regression ResultDependent Variable: LSDRMethod: Least SquaresSample (adjusted): 2000Q2 2012Q4Included observations: 51 after adjustmentsVariableLM2LREERLGDPLTBRLSDR(-1)сR-squaredAdjusted R-squaredS.E. of regressionSum squared residLog likelihoodF-statisticProb(F-statistic)Coefficient Std. Error t-StatisticProb.0.85930.02240.029879 0.167618 0.178259-0.199495 0.084326 -2.3657540.001576 0.207831 0.0075850.006450 0.0117330.99400.5497070.58520.717507 0.096076 7.468094 0.00001.100717 0.811970 1.3556130.1820Mean dependent var0.8224580.802731 S.D. dependent var0.068386Akaike info criterion0.210447Schwarz criterion67.63794 Hannan-Quinn criter.41.69215Durbin-Watson stat0.0000002.0904980.153970-2.417174-2.189900-2.3303261.003093

Assuming the model is re-estimated with additional new variable (lagged of LGDP), based on the new estimated results, what is your conclusion about the autocorrelation diagnostic test? If there is diagnostic problem, show how to solve the problem.

Assuming the model is re-estimated with additional new variable (lagged of LGDP), based on the new estimated results, what is your conclusion about the autocorrelation diagnostic test? If there is diagnostic problem, show how to solve the problem.

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter7: Distance And Approximation

Section7.3: Least Squares Approximation

Problem 31EQ

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