A. Colin Cameron and Pravin K. Trivedi
MICROECONOMETRICS: Methods and Applications
Cambridge University Press, New York
EXPLANATION OF BOOK PROGRAMS
FILE NAMING CONVENTIONS:
- Most programs
are in Stata version 8.0, executed on a MSWindows PC with Stata 8.2.
Stata 7 will usually be okay. Exceptions where Stata 8 is needed
(1) Estimates command (for tabulating regression results) is not available
in version 7.
Comment out occurrences of "estimates store ..." and "estimates
(2) Graphics commands (used to obtain the figures in the book)
changed substantially from 7 to 8.
This only effects generating figures. If graphs are important, it is
best to upgrade to Stata 8 as so much better.
(3) In some places free Stata add-ons have been included. These are noted
To download these programs e.g. knnreg in Stata give command "search
knnreg" and follow directions.
The Stata programs vary from very problem-specific code to code that potentially
can be adapted to one's own needs.
- Some programs use Limdep version 7.0 and Nlogit 2.0, executed on an
- Some programs use SAS / IML. SAS version 8.0 used on a Unix machine.
PROGRAM CPU TIME
- For Stata: as an example for chapter 4.5.3 we provide:
- mma04p1wls.do Stata program
- mma04p1wls.txt Output from this program
- mma04p1wls.asc The generated data as fixed width
ascii data set
[permits analysis with
programs other than Stata]
- For Limdep: as an example for chapter 14.5.3 we provide:
- mma15p3mnl.lim Limdep program
- mma15p3mnl.out Output from this program
- For SAS: as an example for chapter 13.6 we provide:
- mma15p2bayesgibbs.sas SAS program
- mma13p2bayesgibbs.lst SAS output
- mma13p2bayesgibbs.log SAS logfile
- For data sets the extensions are:
- .dta for Stata data set
- .asc for ascii (text) data set that is usually both
space delimited and fixed width
- For descriptions of the data sets see the relevant program that uses
the data set, and the associated output.
generally take little time to run.
- Exception is programs that entail simulation, including bootstrapping.
- Programs can be speeded up by reducing the number of simulations /
replications, though final analysis should use many simulations / replications.
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