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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. The Ramsey Regression Equation Specification Error Test (RESET) test (Ramsey, 1969) is a general specification test for the linear regression model. More specifically, it tests whether non-linear combinations of the estimated values help explain the endogenous variable. The intuition behind the test is that, if non-linear combinations of the explanatory variables have any power in explaining the endogenous variable, then the model is mis-specified.Consider the model…mehr

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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. The Ramsey Regression Equation Specification Error Test (RESET) test (Ramsey, 1969) is a general specification test for the linear regression model. More specifically, it tests whether non-linear combinations of the estimated values help explain the endogenous variable. The intuition behind the test is that, if non-linear combinations of the explanatory variables have any power in explaining the endogenous variable, then the model is mis-specified.Consider the model hat{y}=E{y x}=beta x.The Ramsey test then tests whether ( 1x)2,( 2x)3...,( k 1x)k has any power in explaining y. This is executed by estimating the following linear regression y=beta x + beta_1hat{y}^2+...+beta_{k-1}hat{y}^k+epsilon, and then testing, by a means of a F-test whether beta_1~ through ~beta_{k-1} are zero. If the null-hypothesis that all regression coefficients of the non-linear terms are zero is rejected, then the model suffers from mis-specification.