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Empirical Methods for Microeconomic Applications

Empirical Methods for Microeconomic Applications. William Greene Department of Economics Stern School of Business. Upload Your Project File. Restrictions. Testing a Hypothesis – LM Test. PROBIT ; LHS = doctor ; RHS = one,age,educ $ PROBIT ; LHS = doctor

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Empirical Methods for Microeconomic Applications

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  1. Empirical Methods for Microeconomic Applications William Greene Department of Economics Stern School of Business

  2. Upload Your Project File

  3. Restrictions

  4. Testing a Hypothesis – LM Test PROBIT ; LHS = doctor ; RHS = one,age,educ $ PROBIT ; LHS = doctor ; RHS = one,age,educ,female,married ; Start = b,0,0 ; MAXIT = 0 $

  5. Results of an LM test

  6. Wald Test Note: LM equaled 485.27.

  7. Wald Test Using Matrix Algebra Note: LM equaled 485.27.

  8. Likelihood Ratio Test Note: LM equaled 485.27.Wald equaled 484.55

  9. Using Matrix Algebra Namelists with the current sample serve 2 major functions: (1) Define lists of variables for model estimation (2) Define the columns of matrices built from the data. NAMELIST ; X = a list ; Z = a list … $ Set the sample any way you like. Observations are now the rows of all matrices. When the sample changes, the matrices change. Lists may be anything, may contain ONE, may overlap (some or all variables) and may contain the same variable(s) more than once

  10. Matrix Functions Matrix Product: MATRIX ; XZ = X’Z $ Moments and Inverse MATRIX ; XPX = X’X ; InvXPX = <X’X> $ Moments with individual specific weights in variable w. Σiwi xixi’ = X’[w]X. [Σiwi xixi’ ]-1 = <X’[w]X> Unweighted Sum of Rows in a Matrix Σi xi = 1’X Column of Sample Means (1/n) Σi xi = 1/n * X’1 or MEAN(X) (Matrix function. There are over 100 others.) Weighted Sum of rows in matrix Σiwi xi = 1’[w]X

  11. LM Test for Normality in Probit Thanks to Joachim Wilde, Univ. Halle, Germany for suggesting this.

  12. Normality Test for Probit NAMELIST ; XI = One,... $ CREATE ; yi = the dependent variable $ PROBIT ; Lhs = yi ; Rhs = Xi ; Prob = Pfi $ CREATE ; bxi = b'Xi ; fi = N01(bxi) $ CREATE ; zi3 = -1/2*(bxi^2 - 1) ; zi4 = 1/4*(bxi*(bxi^2+3)) $ NAMELIST ; Zi = Xi,zi3,zi4 $ CREATE ; di = fi/sqr(pfi*(1-pfi)) ; ei = yi - pfi ; eidi = ei*di ; di2 = di*di $ MATRIX ; List ; LM = 1'[eidi]Zi * <ZI'[di2]Zi> * Zi'[eidi]1 $

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