Discrete Choice Modeling William Greene Stern School of Business New York University Lab Sessions.

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Discrete Choice Modeling William Greene Stern School of Business New York University Lab Sessions

Lab Session 10 Discrete Choice Combining RP and SP Data

Application Survey sample of 2,688 trips, 2 or 4 choices per situation Sample consists of 672 individuals Choice based sample Revealed/Stated choice experiment: Revealed: Drive,ShortRail,Bus,Train Hypothetical: Drive,ShortRail,Bus,Train,LightRail,ExpressBus Attributes: Cost –Fuel or fare Transit time Parking cost Access and Egress time

Data Set Load data set RPSP.LPJ 9408 observations We fit separate models for RP and SP subsets of the data, then a combined, nested model that accommodates the different scaling.

Each person makes four choices from a choice set that includes either two or four alternatives. The first choice is the RP between two of the RP alternatives The second-fourth are the SP among four of the six SP alternatives. There are ten alternatives in total.

Model for Revealed Preference Data ? Using only Revealed Preference Data sample;all$ reject;sprp=2$ deleting SP data dstats;rhs=autotime,fcost,mptrtime,mptrfare$ NLOGIT ;lhs=chosen,cset,altij ;choices=RPDA,RPRS,RPBS,RPTN ;descriptives;crosstab ;maxit=100 ;model: U(RPDA) = rdasc+ fl*fcost+tm*autotime/ U(RPRS) = rrsasc+ fl*fcost+tm*autotime/ U(RPBS) = rbsasc + ptc*mptrfare+mt*mptrtime/ U(RPTN) = ptc*mptrfare+mt*mptrtime$

Model for Stated Preference Data ? Using only Stated Preference Data sample;all$ reject;sprp=1$ deleting RP data ? BASE MODEL nlogit ;lhs=chosen,cset,alt ;choices=SPDA,SPRS,SPBS,SPTN,SPLR,SPBW ;descriptives;crosstab ;maxit=150 ;model: U(SPDA) = dasc +cst*fueld+ tmcar*time+prk*parking +pincda*pincome +cavda*carav/ U(SPRS) = rsasc+cst*fueld+ tmcar*time+prk*parking/ U(SPBS) = bsasc+cst*fared+ tmpt*time+act*acctime+egt*eggtime/ U(SPTN) = tnasc+cst*fared+ tmpt*time+act*acctime+egt*eggtime/ U(SPLR) = lrasc+cst*fared+ tmpt*time+act*acctime +egt*eggtime/ U(SPBW) = cst*fared+ tmpt*time+act*acctime+egt*eggtime$

A Nested Logit Model for RP/SP Data NLOGIT ;lhs=chosen,cset,altij ;choices=RPDA,RPRS,RPBS,RPTN,SPDA,SPRS,SPBS,SPTN,SPLR,SPBW /.592,.208,.089,.111,1.0,1.0,1.0,1.0,1.0,1.0 ;tree=mode[rp(RPDA,RPRS,RPBS,RPTN),spda(SPDA), sprs(SPRS),spbs(SPBS),sptn(SPTN),splr(SPLR),spbw(SPBW)] ;ivset: (rp)=[1.0];ru1 ;maxit=150 ;model: U(RPDA) = rdasc+ invc*fcost+tmrs*autotime ?+prkda*vehprkct+ + pinc*pincome+CAVDA*CARAV/ U(RPRS) = rrsasc + invc*fcost+tmrs*autotime/?+ U(RPBS) = rbsasc + invc*mptrfare+mtpt*mptrtime/?+acegt*rpacegtm/ U(RPTN) = cstrs*mptrfare+mtpt*mptrtime/?+acegt*rpacegtm/ U(SPDA) = sdasc + invc*fueld + tmrs*time+cavda*carav ?+prkda*parking + pinc*pincome/ U(SPRS) = srsasc + invc*fueld + tmrs*time/? cavrs*carav/ U(SPBS) = invc*fared + mtpt*time +acegt*spacegtm/ U(SPTN) = stnasc + invc*fared + mtpt*time+acegt*spacegtm/ U(SPLR) = slrasc + invc*fared + mtpt*time+acegt*spacegtm/ U(SPBW) = sbwasc + invc*fared + mtpt*time+acegt*spacegtm$

A Random Parameters Approach NLOGIT ;lhs=chosen,cset,altij ;choices=RPDA,RPRS,RPBS,RPTN,SPDA,SPRS,SPBS,SPTN,SPLR,SPBW /.592,.208,.089,.111,1.0,1.0,1.0,1.0,1.0,1.0 ; rpl ; pds=4 ; halton ; pts=25 ; fcn=invc(n) ; model: U(RPDA) = rdasc+ invc*fcost+tmrs*autotime ?+prkda*vehprkct+ + pinc*pincome+CAVDA*CARAV/ U(RPRS) = rrsasc + invc*fcost+tmrs*autotime/?+ ?egt*autoegtm+prk*vehprkct+ U(RPBS) = rbsasc + invc*mptrfare+mtpt*mptrtime/?+acegt*rpacegtm/ U(RPTN) = cstrs*mptrfare+mtpt*mptrtime/?+acegt*rpacegtm/ U(SPDA) = sdasc + invc*fueld + tmrs*time+cavda*carav ?+prkda*parking + pinc*pincome/ U(SPRS) = srsasc + invc*fueld + tmrs*time/? cavrs*carav/ U(SPBS) = invc*fared + mtpt*time +acegt*spacegtm/ U(SPTN) = stnasc + invc*fared + mtpt*time+acegt*spacegtm/ U(SPLR) = slrasc + invc*fared + mtpt*time+acegt*spacegtm/ U(SPBW) = sbwasc + invc*fared + mtpt*time+acegt*spacegtm$

Connecting Choice Situations through RPs Variable| Coefficient Standard Error b/St.Er. P[|Z|>z] |Random parameters in utility functions INVC| *** |Nonrandom parameters in utility functions RDASC| TMRS| *** PINC| CAVDA|.35750*** RRSASC| *** RBSASC| *** MTPT| *** CSTRS| *** SDASC| SRSASC| ACEGT| *** STNASC| SLRASC|.27250** SBWASC| |Distns. of RPs. Std.Devs or limits of triangular NsINVC|.45285***