Library of
Gauss Procedures for
Econometrics and Computational Methods in
Economics
(with examples of programs that call the
procedures)
by Victor Aguirregabiria
ESTIMATION OF (STANDARD)
DISCRETE CHOICE MODELS
milogit.src Procedure
for the Maximum Likelihood estimation of a Logit
model.
milogit example Program that runs an example calling the
procedure milogit.src.
miprobit.src Procedure
for the Maximum Likelihood estimation of a Probit
model.
miprobit example Program that runs an example calling the
procedure miprobit.src.
multilog.src Procedure
for the Maximum Likelihood estimation of a Multinomial Logit.
multilog example Program that runs an example calling the
procedure multilog.src.
clogit.src Procedure for the Maximum
Likelihood estimation of McFadden's Conditional Logit.
clogit example Program that runs an example calling the
procedure clogit.src.
ESTIMATION OF SINGLE-AGENT DISCRETE-CHOICE
DYNAMIC-PROGRAMMING MODELS
npl_sing.src Procedure that estimates the
structural parameters of a discrete-choice single-agent dynamic programming
model using the Nested Pseudo Likelihood
(NPL) algorithm in Aguirregabiria and Mira (Econometrica,
2002). It
calls the following procedures:
·
clogit.src Procedure
for the Maximum Likelihood estimation of McFadden's Conditional Logit.
npl_sing.e Program that estimates the bus
replacement model in Rust (Econometrica, 1987). This
program calls the library nplprocs.lcg and the procedures npl_sing.src, multilog.src , discthre.src and the GAUSS dataset:
·
bus1234.dat Rust’s
bus replacement data set (bus engine groups 1, 2, 3 and 4).
ESTIMATION OF STATIC DISCRETE GAMES
nplgame.src
Procedure that estimates the structural parameters of an entry model of
incomplete information using a Nested Pseudo-Likelihood (NPL) algorithm.
equiprob.src
Procedure that computes players' choice probabilities of Bayesian Nash
Equilibrium in a static game of firms' market entry.
probmat.src
Procedure for the mapping from probabilities to probabilities in a model of
entry with incomplete information.
simgame.src
Procedure that simulates observations from a model of entry.
dynprob.src
Procedure for the mapping from probabilities to probabilities in a static model
of entry with incomplete information.
kpiegame.src
Procedure that estimates the structural parameters of an entry model of
incomplete information using 1-stage of the Nested Pseudo-Likelihood (NPL)
algorithm.
psumbern.src
Procedure that obtains the probability distribution of a sum of independent but
heterogeneous Bernoullis.
ESTIMATION OF DYNAMIC DISCRETE GAMES
mpeprob.src
Procedure that computes players' choice probabilities of Markov Perfect
Equilibrium in a dynamic game of firms' market entry/exit with incomplete
information.
mlegame.src
Procedure that estimates the structural parameters of a model of entry of
incomplete information using Maximum Likelihood.
npldygam.src
Procedure that estimates the structural parameters of dynamic game of firms'
entry/exit using a Nested Pseudo-Likelihood (NPL) algorithm.
simdygam.src
Compute the steady-state distribution of state and decision variables in a
Markov Perfect Equilibrium of a dynamic game of firms' market entry/exit with
incomplete information.
NONPARAMETRIC METHODS
kernel1.src Procedure
for the kernel estimation of a univariate density
function.
nadaraya_cv.src Procedure for Nadaraya-Watson
estimation of a nonparametric regression function. Cross-Validation
for bandwidth choice.
nadaraya_cv e Program that runs an example calling the
procedure nadaraya_cv.src.
isonpreg.src Procedure that obtains a
nonparametric isotonic (monotonic) regression using the max-min estimator first
proposed by Brunk (AS, 1958).
mono_si.src Procedure that estimates a
nonparametric regression function using the SI (Smoothing- Isotonising)
estimator in Mammen (AS, 1991).
mono_is.src Procedure that estimates a
nonparametric regression function using the IS (Isotonising-Smoothing)
estimator in Mammen (AS, 1991).
freqprob.src Procedure that obtains a frequency
estimation of Prob(Y|X) where Y is discrete and X is
a vector of discrete variables.
dchokern.src Procedure for the kernel estimation of
Prob(Y|X) where Y is a binary variable and X is a
vector of continuous variables.
dchokern.e Program that runs an example
calling the procedure dchokern.src.
iniprob.src
Obtains initial reduced form estimates of conditional choice probabilities to
be used as starting value for the K-stage PIE.
nplld.src
Procedure that estimates a dynamic labor demand model with lump-sum and linear
hiring and firing costs, using a nested fixed point algorithm.
disckpie.src
It discretizes a vector of variables according to a
criterion selected by the user.
ccpld.src
Procedure that estimates a dynamic labor demand model with lump-sum and linear
hiring and firing costs, using a nested fixed point algorithm.
disckld.src
Discretizes decision and state variables and obtains
matrices of transition probabilities in a labor demand model with linear hiring
and firing costs.
solvld.src
Procedure that solves a labor demand model with with
two types of labor. The algorithm exploits a "smooth" Bellman's
equation.
simld.src
Procedure that simulates data of state and decision variables in a labour demand model with linear hiring and firing costs.
dissolld.src
Procedure that discretizes decisions and state
variables and obtains matrices of transition probabilities in a dynamic labor
demand model with two types of labor.