**Library of
Gauss Procedures for**

** Econometrics and Computational Methods in
Economics**

(with examples of programs that call the procedures)

*by Victor Aguirregabiria*

**MONTE CARLO EXPERIMENTS IN AGUIRREGABIRIA & MIRA (ECONOMETRICA,
2007)**

am_econometrica_2007_montecarlo.prg Program

am_econometrica_2007_montecarlo_1.pdf Results 1

am_econometrica_2007_montecarlo_2.pdf Results 2

am_econometrica_2007_montecarlo_3.pdf Results 3

am_econometrica_2007_montecarlo_4.pdf Results 4

am_econometrica_2007_montecarlo_5.pdf Results 5

am_econometrica_2007_montecarlo_6.pdf Results 6

**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.