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Empirical Methods for Microeconomic Applications - PowerPoint PPT Presentation

Empirical Methods for Microeconomic Applications. William Greene Department of Economics Stern School of Business. Lab 5. Random Parameters and Latent Classes. Upload Your Project File. Commands for Random Parameters. Random Parameter Specifications.

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Empirical Methods for Microeconomic Applications

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Empirical Methods for Microeconomic Applications

William Greene

Department of Economics

Lab 5. Random Parameters and Latent Classes

Random Parameter Specifications

All models in LIMDEP/NLOGIT may be fit with random parameters, with panel or cross sections. NLOGIT has more options (not shown here) than the more general cases.

Options for specifications

; FCN = name ( type ), name ( type ), …

Type is N = normal,

U = uniform,

L = lognormal (positive),

T = tent shaped distributions.

C = nonrandom (variance = 0 – only in NLOGIT)

Name is the name of a variable or parameter in the model orA_choice for ASCs (up to 8 characters). In the CLOGIT model, they are A_AIR A_TRAIN A_BUS.

; Correlated parameters (otherwise, independent)

Replicability

Consecutive runs of the identical model give different results. Why? Different random draws.

Achieve replicability

(1) Use ;HALTON

(2) Set random number generator before each run with the same value.

CALC ; Ran( large odd number) \$

(Setting the seed is not needed for ;Halton)

Random Parameters Models

SETPANEL; Group = id ; Pds = ti \$

PROBIT ; Lhs = doctor

; Rhs = One,age,educ,income,female

; RPM ; Pts = 25 ; Halton ; Panel

; Fcn = one(N),educ(N) ; Correlated \$

POISSON ; Lhs = Doctor

; Rhs = One,Educ,Age,Income,Hhkids

; Fcn = educ(N)

; Panel ; Pts=100 ; Halton

; Maxit = 25 \$

And so on…

Saving Individual Expected Values

SETPANEL; Group = id ; Pds = ti \$

PROBIT ; Lhs = doctor

; Rhs = One,age,educ,income,female

; RPM ; Pts = 25 ; Halton ; Panel

; Fcn = one(N),educ(N) ; Correlated

; Parameters

\$

Commands for Latent Class Models