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| Publications of A Ronald Gallant :recent first alphabetical combined listing:
%% Journal Articles
@article{fds266639,
Author = {AR Gallant},
Title = {SOME ARGUMENTS AGAINST THE USE OF STATISTICAL PACKAGES IN
TEACHING STATISTICAL METHODS.},
Pages = {223-225},
Year = {1973},
Abstract = {Some points in favor of the use of a simple programming
language in teaching statistical methods rather than a
statistical package are presented.},
Key = {fds266639}
}
@article{fds266638,
Author = {NPC Chao and JA Cuculo and AR Gallant and TW George},
Title = {Statistical method for determining the glass transition
temperature from dilatometric data},
Year = {1975},
Key = {fds266638}
}
@article{fds266640,
Author = {NPC Chao and JA Cuculo and AR Gallant and TW George},
Title = {STATISTICAL METHOD FOR DETERMINING THE GLASS TRANSITION
TEMPERATURE FROM DILATOMETRIC DATA.},
Journal = {Appl Polym Symp},
Number = {27},
Pages = {193-204},
Year = {1975},
Abstract = {An objective procedure for estimating the glass transition
temperature (T//g) from dilatometric data is described. The
method uses the technique of fitting a segmented linear
regression model by least squares. The regression model
employed may be specified so as to allow a transition either
of the first order in the thermodynamic sense or may be
constrained to fit a second order. Methods are given for
finding statistical confidence intervals for the estimated
glass transition temperature (T//g). Experimental data
obtained from PET (polyethylene terephthalate) fiber are
used for illustration; these data indicate a preference for
the second-order transition model. 8 refs.},
Key = {fds266640}
}
@article{fds266641,
Author = {AR Gallant},
Title = {Seemingly unrelated nonlinear regressions},
Journal = {Journal of Econometrics},
Volume = {3},
Number = {1},
Pages = {35-50},
Year = {1975},
ISSN = {0304-4076},
Abstract = {The article considers the estimation of the parameters of a
set of nonlinear regression equations when the responses are
contemporaneously but not serially correlated. Conditions
are set forth such that the estimator obtained is strongly
consistent, asymptotically normally distributed, and
asymptotically more efficient than the single-equation least
squares estimator. The methods presented allow estimation of
the parameters subject to nonlinear restrictions across
equations. The article includes a discussion of methods to
perform the computations and a Monte Carlo simulation. ©
1975.},
Key = {fds266641}
}
@article{fds266642,
Author = {CR Shumway and PM Maher and MR Baker and WE Souder and AH Rubenstein and AR Gallant},
Title = {DIFFUSE DECISION-MAKING IN HIERARCHICAL ORGANIZATIONS: AN
EMPIRICAL EXAMINATION.},
Journal = {Management Science},
Volume = {21},
Number = {6},
Pages = {697-707},
Year = {1975},
Abstract = {The applied research resource allocation decision process in
a complex, hierarchical federal organization is explored in
this paper. This decision process includes the
identification of research objectives and the funding of
projects selected to achieve the objectives. The
hierarchical, geographical, and temporal diffuseness of
participation in the decision process is
described.},
Key = {fds266642}
}
@article{fds266644,
Author = {AR Gallant},
Title = {Three-stage least-squares estimation for a system of
simultaneous, nonlinear, implicit equations},
Journal = {Journal of Econometrics},
Volume = {5},
Number = {1},
Pages = {71-88},
Year = {1977},
ISSN = {0304-4076},
Abstract = {The article describes a nonlinear three-stage least-squares
estimator for the parameters of a system of simultaneous,
nonlinear, implicit equations; the method allows the
estimation of these parameters subject to nonlinear
parametric restrictions across equations. The estimator is
shown to be strongly consistent, asymptotically normally
distributed, and more efficient than the nonlinear two-stage
least-squares estimator. Some practical implications of the
regularity conditions used to obtain these results are
discussed from the point of view of one whose interest is in
applications, Also, computing methods using readily
available nonlinear regression programs are described. ©
1977.},
Key = {fds266644}
}
@article{fds266643,
Author = {AR Gallant and DW Jorgenson},
Title = {Statistical inference for a system of simultaneous,
non-linear, implicit equations in the context of
instrumental variable estimation},
Journal = {Journal of Econometrics},
Volume = {11},
Number = {2-3},
Pages = {275-302},
Year = {1979},
ISSN = {0304-4076},
Abstract = {Statistical inference for a system of simultaneous,
non-linear, implicit equations is discussed. The discussion
considers inference as an adjunct to two- and three-stage
least squares estimation rather than in a general setting.
For both of these cases the non-null asymptotic distribution
of a test statistic based on the optimization criterion and
a test based on the asymptotic distribution of the estimator
is found; a total of four. It is argued that the tests based
on the optimization criterion are to be preferred in
applications. The methods are illustrated by application to
hypotheses implied by the theory of demand using a translog
expenditure system and data on personal consumption
expenditures for durables, non-durables, and energy for the
period 1947- 1971. © 1979.},
Key = {fds266643}
}
@article{fds266646,
Author = {AR Gallant and TM Gerig},
Title = {Computations for constrained linear models},
Journal = {Journal of Econometrics},
Volume = {12},
Number = {1},
Pages = {59-84},
Year = {1980},
ISSN = {0304-4076},
Abstract = {The article presents an algorithm for linear regression
computations subject to linear parametric equality
constraints, linear parametric inequality constraints, or a
mixture of the two. No rank conditions are imposed on the
regression specification or the constraint specification.
The algorithm requires a full Moore-Penrose g-inverse which
entails extra computational effort relative to other
orthonormalization type algorithms. In exchange, auxiliary
statistical information is generated: feasibility of a set
of constraints may be checked, estimability of a linear
parametric function may be checked, and bias and variance
may be decomposed by source. © 1980.},
Key = {fds266646}
}
@article{fds266645,
Author = {AR Gallant},
Title = {On the bias in flexible functional forms and an essentially
unbiased form. The fourier flexible form},
Journal = {Journal of Econometrics},
Volume = {15},
Number = {2},
Pages = {211-245},
Year = {1981},
ISSN = {0304-4076},
Abstract = {The Fourier flexible form and its derived expenditure system
are introduced. Subject to smoothness conditions on the
consumer's true indirect utility function, the consumer's
true expenditure system must be of the Fourier form over the
region of interest in an empirical investigation.
Arbitrarily accurate finite parameter approximations of the
consumer's true expenditure system are obtained by dropping
all high-order terms of the Fourier expenditure system past
an appropriate truncation point. The resulting finite
parametersystem is tractable in empirical studies. The
reader who is primarily interested in applications need only
read the second and fifth sections. The remainder of the
article is concerned with the verification of these claims
and an investigation of some aspects of the bias in Translog
specifications. © 1981.},
Key = {fds266645}
}
@article{fds266648,
Author = {AR Gallant},
Title = {Unbiased determination of production technologies},
Journal = {Journal of Econometrics},
Volume = {20},
Number = {2},
Pages = {285-323},
Year = {1982},
ISSN = {0304-4076},
Abstract = {To determine whether an industry exhibits constant returns
to scale, whether the production function is homothetic, or
whether inputs are separable, a common approach is to
specify a cost function, estimate its parameters using data
such as prices and quantities of inputs, and then test the
parametric restrictions corresponding to constant returns, a
homothetic technology, or separability. Statistically, such
inferences are valid if the true cost function is a member
of the parametric class considered, otherwise the inference
is biased. That is, the true rejection probability is not
necessarily adequately approximated by the nominal size of
the statistical test. The use of fixed parameter flexible
functional forms such as the Translog, the generalized
Leontief, or the Box-Cox will not alleviate this problem.
The Fourier flexible form differs fundamentally from other
flexible forms in that it has a variable number of
parameters and a known bound, depending on the number of
parameters, on the error, as measured by the Sobolev norm,
of approximation to an arbitrary cost function. Thus it is
possible to construct statistical tests for constant
returns, a homothetic technology, or separability which are
asymptotically size α by letting the number of parameters
of the Fourier flexible form depend on sample size. That is,
the true rejection probability converges to the nominal size
of the test as sample size tends to infinity. The rate of
convergence depends on the smoothness of the true cost
function; the more times is differentiable the true cost
function, the faster the convergence. The method is
illustrated using the data on aggregate U.S. manufacturing
of Berndt and Wood (1975, 1979) and Berndt and Khaled
(1979). © 1982.},
Key = {fds266648}
}
@article{fds266647,
Author = {V Aguirre-Torres and AR Gallant},
Title = {The null and non-null asymptotic distribution of the Cox
test for multivariate nonlinear regression. Alternatives and
a new distribution-free Cox test},
Journal = {Journal of Econometrics},
Volume = {21},
Number = {1},
Pages = {5-33},
Year = {1983},
ISSN = {0304-4076},
Abstract = {The asymptotic distribution of the generalized Cox test for
choosing between two multivariate, nonlinear regression
models in implicit form is derived. The data is assumed to
be generated by a model that need not be either the null or
the non-null model. As the data-generating model is not
subjected to a Pitman drift the analysis is global, not
local, and provides a fairly complete qualitative
description of the power characteristics of the generalized
Cox test. Some investigations of these characteristics are
included. A new test statistic is introduced that does not
require an explicit specification of the error distribution
of the null model. The idea is to replace an analytical
computation of the expectation of the Cox difference with a
bootstrap estimate. The null distribution of this new test
is derived. © 1983.},
Key = {fds266647}
}
@article{fds266649,
Author = {AR Gallant and RW Koenker},
Title = {Costs and benefits of peak-load pricing of electricity. A
continuous-time econometric approach},
Journal = {Journal of Econometrics},
Volume = {26},
Number = {1-2},
Pages = {83-113},
Year = {1984},
ISSN = {0304-4076},
Abstract = {We address the following question of current policy
interest: Would the efficiency gains from residential
time-of-use pricing for electricity exceed the metering
costs necessitated by these more complex rates? A model of
consumer preferences for daily electricity consumption is
estimated based on data from the North Carolina Rate
Experiment. The model is formulated in continuous time and
thus is capable of evaluating demand responses and welfare
consequences of quite arbitrary changes in pricing policy. A
model of long-run electricity costs - viewed as a functional
of the daily load cycle - is constructed based on
engineering data. The models of demand and cost are combined
to compute solutions to several optimal pricing problems and
to estimate the potential long-run welfare gain from several
alternative time-of-use pricing policies including policies
incorporating so-called 'demand charges'. We find that the
best of the rate treatments used in the North Carolina
experiment achieves a net welfare gain of 5¢ per day per
household, or roughly half the cost of current metering
equipment. Smoothly varying rates are capable of achieving
nearly 18¢ per day per household, but would require more
complex metering. Demand charges while they are quite
successful in smoothing the demand cycle are not as
successful as conventional pricing policies in achieving our
welfare objective. © 1984.},
Key = {fds266649}
}
@article{fds266651,
Author = {AR Gallant and GH Golub},
Title = {Imposing curvature restrictions on flexible functional
forms},
Journal = {Journal of Econometrics},
Volume = {26},
Number = {3},
Pages = {295-321},
Year = {1984},
ISSN = {0304-4076},
Abstract = {A general computational method for estimating the parameters
of a flexible functional form subject to convexity,
quasi-convexity, concavity, or quasi-concavity at a point,
at several points, or over a region, is set forth and
illustrated with an example. © 1984.},
Key = {fds266651}
}
@article{fds266650,
Author = {JA Chalfant and AR Gallant},
Title = {Estimating substitution elasticities with the Fourier cost
function. Some Monte Carlo results},
Journal = {Journal of Econometrics},
Volume = {28},
Number = {2},
Pages = {205-222},
Year = {1985},
ISSN = {0304-4076},
Abstract = {The Fourier flexible form possesses desirable asymptotic
properties that are not shared by other flexible forms such
as the translog, generalized Leontief, and generalized
Box-Cox. One of them is that an elasticity of substitution
can be estimated with negligible bias in sufficiently large
samples regardless of what the true form actually is, save
that it be smooth enough. This article reports the results
of an experiment designed to determine whether or not this
property obtains in samples of the sizes customarily
encountered in practice. A three-input, homothetic version
of the generalized Box-Cox cost function was used to
generate technologies that were oriented in a
two-dimensional design space according to a central
composite rotatable design; the two factors of the design
were the Box-Cox parameter and a measure of the dispersion
of the substitution matrix. The Fourier cost function was
used to estimate the substitution elasticities at each
design point, and the bias at each point was estimated using
the Monte Carlo method. A response surface over the entire
design space was fitted to these estimates. An examination
of the surface reveals that the bias is small over the
entire design space. Roughly speaking, the estimates of
elasticities of substitution are unbiased to three
significant digits using the Fourier flexible form no matter
what the true technology. Our conclusion is that the small
bias property of the Fourier form does obtain in samples of
reasonable size; this claim must be tampered by the usual
caveats associated with inductive inference. ©
1985.},
Key = {fds266650}
}
@article{fds266652,
Author = {WA Barnett and AR Gallant},
Title = {Editor's introduction},
Journal = {Journal of Econometrics},
Volume = {30},
Number = {1-2},
Pages = {1-},
Year = {1985},
ISSN = {0304-4076},
Key = {fds266652}
}
@article{fds266653,
Author = {AR Gallant and JF Monahan},
Title = {Explicitly infinite-dimensional Bayesian analysis of
production technologies},
Journal = {Journal of Econometrics},
Volume = {30},
Number = {1-2},
Pages = {171-201},
Year = {1985},
ISSN = {0304-4076},
Abstract = {The firm's cost function is viewed as a point in a function
space and data is viewed as following some probability law
that has as its parameters various functionals evaluated at
the firm's cost function. The Fourier flexible form is used
to represent a cost function as an infinite-dimensional
vector whose elements are the parameters of the Fourier
form. This representation is used to assign a prior
distribution to the function space. A procedure for
numerical computation of the posterior distribution of an
elasticity of substitution is set forth. The ideas are
illustrated with an example. © 1985.},
Key = {fds266653}
}
@article{fds266654,
Author = {AR Gallant and H White},
Title = {There exists a neural network that does not make avoidable
mistakes},
Pages = {657-664},
Year = {1988},
Abstract = {The authors show that a multiple-input, single-output,
single-hidden-layer feedforward network with (known)
hardwired connections from input to hidden layer, monotone
squashing at the hidden layer and no squashing at the output
embeds as a special case a so-called Fourier network, which
yields a Fourier series approximation properties of Fourier
series representations. In particular, approximation to any
desired accuracy of any square integrable function can be
achieved by such a network, using sufficiently many hidden
units. In this sense, such networks do not make avoidable
mistakes.},
Key = {fds266654}
}
@article{fds266655,
Author = {AR Gallant and LP Hansen and G Tauchen},
Title = {Using conditional moments of asset payoffs to infer the
volatility of intertemporal marginal rates of
substitution},
Journal = {Journal of Econometrics},
Volume = {45},
Number = {1-2},
Pages = {141-179},
Year = {1990},
ISSN = {0304-4076},
Abstract = {Previously Hansen and Jagannathan (1990a) derived and
computed mean-standard deviation frontiers for intertemporal
marginal rates of substitution (IMRS) implied by asset
market data. These frontiers give the lower bounds on the
standard deviations as a function of the mean. In this paper
we develop a strategy for utilizing conditioning information
efficiently, and hence improve on the standard deviation
bounds computed by Hansen and Jagannathan. We implement this
strategy empirically by using the seminonparametric (SNP)
methodology suggested by Gallant and Tauchen (1989) to
estimate the conditional distribution of a vector of monthly
asset payoffs. We use the fitted conditional distributions
to calculate both conditional and unconditional standard
deviation bounds for the IMRS. The unconditional bounds are
as sharp as possible subject to robustness considerations.
We also use the fitted distributions to compute the moments
of various candidate marginal rates of substitution
suggested by economic theory, and in particular the
time-nonseparable preferences of Dunn and Singleton (1986)
and Eichenbaum and Hansen (1990). For these preferences, our
findings suggest that habit persistence will put the moments
of the IMRS inside the frontier at reasonable values of the
curvature parameter. At the same time we uncover evidence
that the implied IMRS fails to satisfy all of the
restrictions inherent in the Euler equation. The findings
help explain why Euler equation estimation methods typically
find evidence in favor of local durability instead of habit
persistence for monthly data. © 1990.},
Key = {fds266655}
}
@article{fds266656,
Author = {AR Gallant and G Souza},
Title = {On the asymptotic normality of Fourier flexible form
estimates},
Journal = {Journal of Econometrics},
Volume = {50},
Number = {3},
Pages = {329-353},
Year = {1991},
ISSN = {0304-4076},
Abstract = {Rates of increase in the number of parameters of a Fourier
factor demand system that imply asymptotically normal
elasticity estimates are characterized. This is the
multivariate analog of work by Andrews (1991). Our proof
strategy is new and consists of relating the minimum
eigenvalue of the sample sum of squares and cross-products
matrix to the minimum eigenvalue of the population matrix
via a uniform strong law with rate that is established using
results from the empirical processes literature. In its
customary form, the minimum eigenvalue of the Fourier sum of
squares and cross-products matrix, considered as a function
of the number of parameters, decreases faster than any
polynomial. The consequence is that the rate at which
parameters may increase is slower than any fractional power
of the sample size. In this case, we get the same rate as
Andrews. When our results are applied to multivariate
regressions with a minimum eigenvalue that is bounded or
declines at a polynomial rate, the rate on the parameters is
a fractional power of the sample size. In this case, our
method of proof gives faster rates than Andrews. Andrews'
results cover the heteroskedastic case, ours do not. ©
1991.},
Key = {fds266656}
}
@article{fds266658,
Author = {S Ellner and AR Gallant and D McCaffrey and D Nychka},
Title = {Convergence rates and data requirements for Jacobian-based
estimates of Lyapunov exponents from data},
Journal = {Physics Letters A},
Volume = {153},
Number = {6-7},
Pages = {357-363},
Year = {1991},
ISSN = {0375-9601},
Abstract = {We present a method for estimating the dominant Lyapunov
exponent from time-series data, based on nonparametric
regression. For data from a finite-dimensional deterministic
system with additive stochastic perturbations, we show that
the estimate converges to the true values as the sample size
increases, and give the asymptotic rate of convergence. ©
1991.},
Key = {fds266658}
}
@article{fds266657,
Author = {AR Gallant and H White},
Title = {On learning the derivatives of an unknown mapping with
multilayer feedforward networks},
Journal = {Neural Networks},
Volume = {5},
Number = {1},
Pages = {129-138},
Year = {1992},
ISSN = {0893-6080},
Abstract = {Recently, multiple input, single output, single hidden-layer
feedforward neural networks have been shown to be capable of
approximating a nonlinear map and its partial derivatives.
Specifically, neural nets have been shown to be dense in
various Sobolev spaces. Building upon this result, we show
that a net can be trained so that the map and its
derivatives are learned. Specifically, we use a result of
Gallant's to show that least squares and similar estimates
are strongly consistent in Sobolev norm provided the number
of hidden units and the size of the training set increase
together. We illustrate these results by an application to
the inverse problem of chaotic dynamics: recovery of a
nonlinear map from a time series of iterates. These results
extend automatically to nets that embed the single hidden
layer, feedforward network as a special case. © 1992
Pergamon Press plc.},
Key = {fds266657}
}
@article{fds266660,
Author = {M Davidian and AR Gallant},
Title = {Smooth nonparametric maximum likelihood estimation for
population pharmacokinetics, with application to
quinidine.},
Journal = {J Pharmacokinet Biopharm},
Volume = {20},
Number = {5},
Pages = {529-556},
Year = {1992},
Month = {October},
ISSN = {0090-466X},
url = {http://www.ncbi.nlm.nih.gov/pubmed/1287201},
Abstract = {The seminonparametric (SNP) method, popular in the
econometrics literature, is proposed for use in population
pharmacokinetic analysis. For data that can be described by
the nonlinear mixed effects model, the method produces
smooth nonparametric estimates of the entire random effects
density and simultaneous estimates of fixed effects by
maximum likelihood. A graphical model-building strategy
based on the SNP method is described. The methods are
illustrated by a population analysis of plasma levels in 136
patients undergoing oral quinidine therapy.},
Key = {fds266660}
}
@article{fds266659,
Author = {M Davidian and AR Gallant},
Title = {The nonlinear mixed effects model with a smooth random
effects density},
Journal = {Biometrika},
Volume = {80},
Number = {3},
Pages = {475-488},
Year = {1993},
ISSN = {0006-3444},
url = {http://dx.doi.org/10.1093/biomet/80.3.475},
Abstract = {SUMMARY: The fixed parameters of the nonlinear mixed effects
model and the density of the random effects are estimated
jointly by maximum likelihood. The density of the random
effects is assumed to be smooth but is otherwise
unrestricted. The method uses a series expansion that
follows from the smoothness assumption to represent the
density and quadrature to compute the likelihood. Standard
algorithms are used for optimization. Empirical Bayes
estimates of random coefficients are obtained by computing
posterior modes. The method is applied to data from
pharmacokinetics, and properties of the method are
investigated by application to simulated data. © 1993
Biometrika Trust.},
Doi = {10.1093/biomet/80.3.475},
Key = {fds266659}
}
@article{fds266661,
Author = {DF McCaffrey and AR Gallant},
Title = {Convergence rates for single hidden layer feedforward
networks},
Journal = {Neural Networks},
Volume = {7},
Number = {1},
Pages = {147-158},
Year = {1994},
ISSN = {0893-6080},
Abstract = {By allowing the training set to become arbitrarily large,
appropriately trained and configured single hidden layer
feedforward networks converge in probability to the smooth
function that they were trained to estimate. A bound on the
probabilistic rate of convergence of these network estimates
is given. The convergence rate is calculated as a function
of the sample size n. If the function being estimated has
square integrable mth order partial derivatives then the
L2-norm estimation error approaches Op(n- 1 2) for large m.
Two steps are required for determining these bounds. A bound
on the rate of convergence of approximations to an unknown
smooth function by members of a special class of single
hidden layer feedforward networks is determined. The class
of networks considered can embed Fourier series. Using this
fact and results on approximation properties of Fourier
series yields a bound on L2-norm approximation error. This
bound is less than O(q- 1 2) for approximating a smooth
function by networks with q hidden units. A modification of
existing results for bounding estimation error provides a
general theorem for calculating estimation error convergence
rates. Combining this result with the bound on approximation
rates yields the final convergence rates. ©
1994.},
Key = {fds266661}
}
@article{fds266663,
Author = {WA Barnett and AR Gallant and MJ Hinich and JA Jungeilges and DT Kaplan and MJ Jensen},
Title = {Robustness of nonlinearity and chaos tests to measurement
error, inference method, and sample size},
Journal = {Journal of Economic Behavior and Organization},
Volume = {27},
Number = {2},
Pages = {301-320},
Year = {1995},
ISSN = {0167-2681},
Abstract = {Interest has been growing in testing for nonlinearity and
chaos in economic data, but much controversy has arisen
about the available results. This paper explores the reasons
for these empirical difficulties. We apply five tests for
nonlinearity or chaos to various monetary aggregate data
series. We find that the inferences vary across tests for
the same data, and within tests for varying sample sizes and
various methods of aggregation of the data. Robustness of
inferences in this area of research seems to be low and may
account for the controversies surrounding empirical claims
of nonlinearity and chaos in economics. ©
1995.},
Key = {fds266663}
}
@article{fds266692,
Author = {R Bansal and AR Gallant and R Hussey and G Tauchen},
Title = {Nonparametric estimation of structural models for
high-frequency currency market data},
Journal = {Journal of Econometrics},
Volume = {66},
Number = {1-2},
Pages = {251-287},
Year = {1995},
ISSN = {0304-4076},
url = {http://hdl.handle.net/10161/1902 Duke open
access},
Abstract = {Empirical modeling of high-frequency currency market data
reveals substantial evidence for nonnormality, stochastic
volatility, and other nonlinearities. This paper
investigates whether an equilibrium monetary model can
account for nonlinearities in weekly data. The model
incorporates time-nonseparable preferences and a transaction
cost technology. Simulated sample paths are generated using
Marcet's parameterized expectations procedure. The paper
also develops a new method for estimation of structural
economic models. The method forces the model to match (under
a GMM criterion) the score function of a nonparametric
estimate of the conditional density of observed data. The
estimation uses weekly U.S.-German currency market data,
1975-90. © 1995.},
Doi = {10.1016/0304-4076(94)01618-A},
Key = {fds266692}
}
@article{fds266662,
Author = {VM Fenton and AR Gallant},
Title = {Convergence rates of SNP density estimators},
Journal = {Econometrica},
Volume = {64},
Number = {3},
Pages = {719-727},
Year = {1996},
Key = {fds266662}
}
@article{fds266664,
Author = {AR Gallant and G Tauchen},
Title = {Which moments to match?},
Journal = {Econometric Theory},
Volume = {12},
Number = {4},
Pages = {657-681},
Year = {1996},
url = {http://hdl.handle.net/10161/2542 Duke open
access},
Abstract = {We describe an intuitive, simple, and systematic approach to
generating moment conditions for generalized method of
moments (GMM) estimation of the parameters of a structural
model. The idea is to use the score of a density that has an
analytic expression to define the GMM criterion. The
auxiliary model that generates the score should closely
approximate the distribution of the observed data, but is
not required to nest it. If the auxiliary model nests the
structural model then the estimator is as efficient as
maximum likelihood. The estimator is advantageous when
expectations under a structural model can be computed by
simulation, by quadrature, or by analytic expressions but
the likelihood cannot be computed easily. © 1996 Cambridge
University Press.},
Key = {fds266664}
}
@article{fds266666,
Author = {VM Fenton and AR Gallant},
Title = {Qualitative and asymptotic performance of SNP density
estimators},
Journal = {Journal of Econometrics},
Volume = {74},
Number = {1},
Pages = {77-118},
Year = {1996},
url = {http://dx.doi.org/10.1016/0304-4076(95)01752-6},
Abstract = {The SNP estimator is the most convenient nonparametric
method for simultaneously estimating the parameters of a
nonlinear model and the density of a latent process by
maximum likelihood. To determine if this convenience comes
at a price, we assess the qualitative behavior of SNP in
finite samples using the Marron-Wand test suite and verify
theoretical convergence rates by Monte Carlo simulation. Our
results suggest that there is no price for convenience
because the SNP estimator is both qualitatively and
asymptotically similar to the kernel estimator which is
optimal.},
Doi = {10.1016/0304-4076(95)01752-6},
Key = {fds266666}
}
@article{fds266665,
Author = {AR Gallant and G Tauchen},
Title = {Estimation of continuous-time models for stock returns and
interest rates},
Journal = {Macroeconomic Dynamics},
Volume = {1},
Number = {1},
Pages = {135-168},
Year = {1997},
ISSN = {1365-1005},
url = {http://hdl.handle.net/10161/2590 Duke open
access},
Abstract = {Efficient Method of Moments is used to estimate and test
continuous-time diffusion models for stock returns and
interest rates. For stock returns, a four-state, two-factor
diffusion with one state observed can account for the
dynamics of the daily return on the S&P Composite Index,
1927-1987. This contrasts with results indicating that
discrete-time, stochastic volatility models cannot explain
these dynamics. For interest rates, a trivariate
Yield-Factor Model is estimated from weekly, 1962-1995,
Treasury rates. The Yield-Factor Model is sharply rejected,
although extensions permitting convexities in the local
variance come closer to fitting the data.},
Key = {fds266665}
}
@article{fds266667,
Author = {AR Gallant and JR Long},
Title = {Estimating stochastic differential equations efficiently by
minimum chi-squared},
Journal = {Biometrika},
Volume = {84},
Number = {1},
Pages = {125-141},
Year = {1997},
ISSN = {0006-3444},
Abstract = {We propose a minimum chi-squared estimator for the
parameters of an ergodic system of stochastic differential
equations with partially observed state. We prove that the
efficiency of the estimator approaches that of maximum
likelihood as the number of moment functions entering the
chi-squared criterion increases and as the number of past
observations entering each moment function increases. The
minimised criterion is asymptotically chi-squared and can be
used to test system adequacy. When a fitted system is
rejected, inspecting studentised moments suggests how the
fitted system might be modified to improve the fit. The
method and diagnostic tests are applied to daily
observations on the U.S. dollar to Deutschmark exchange rate
from 1977 to 1992.},
Key = {fds266667}
}
@article{fds266668,
Author = {AR Gallant and D Hsiehb and G Tauchen},
Title = {Estimation of stochastic volatility models with
diagnostics},
Journal = {Journal of Econometrics},
Volume = {81},
Number = {1},
Pages = {159-192},
Year = {1997},
url = {http://hdl.handle.net/10161/2057 Duke open
access},
Abstract = {Efficient method of moments (EMM) is used to fit the
standard stochastic volatility model and various extensions
to several daily financial time series. EMM matches to the
score of a model determined by data analysis called the
score generator. Discrepancies reveal characteristics of
data that stochastic volatility models cannot approximate.
The two score generators employed here are 'semiparametric
ARCH' and 'nonlinear nonparametric'. With the first, the
standard model is rejected, although some extensions are
accepted. With the second, all versions are rejected. The
extensions required for an adequate fit are so elaborate
that nonparametric specifications are probably more
convenient. © 1997 Elsevier Science S.A.},
Key = {fds266668}
}
@article{fds266669,
Author = {AR Gallant and G Tauchen},
Title = {Reprojecting partially observed systems with application to
interest rate diffusions},
Journal = {Journal of the American Statistical Association},
Volume = {93},
Number = {441},
Pages = {10-24},
Year = {1998},
Abstract = {We introduce reprojection as a general purpose technique for
characterizing the dynamic response of a partially observed
nonlinear system to its observable history. Reprojection is
the third step of a procedure wherein first data are
summarized by projection onto a Hermite series
representation of the unconstrained transition density for
observables; second, system parameters are estimated by
minimum chi-squared, where the chi-squared criterion is a
quadratic form in the expected score of the projection; and
third, the constraints on dynamics implied by the nonlinear
system are imposed by projecting a long simulation of the
estimated system onto a Hermite series representation of the
constrained transition density for observables, The
constrained transition density can be used to study the
response of the system to its observable history. We utilize
the technique to assess the dynamics of several diffusion
models for the short-term interest rate that have been
proposed and to compare them to a new model that has
feedback from the interest rate into both the drift and
diffusion coefficients of a volatility equation.},
Key = {fds266669}
}
@article{fds266670,
Author = {SP Ellner and BA Bailey and GV Bobashev and AR Gallant and BT Grenfell and DW Nychka},
Title = {Noise and nonlinearity in measles epidemics: Combining
mechanistic and statistical approaches to population
modeling},
Journal = {American Naturalist},
Volume = {151},
Number = {5},
Pages = {425-440},
Year = {1998},
ISSN = {0003-0147},
url = {http://dx.doi.org/10.1086/286130},
Abstract = {We present and evaluate an approach to analyzing population
dynamics data using semimechanistic models. These models
incorporate reliable information on population structure and
underlying dynamic mechanisms but use nonparametric
surface-fitting methods to avoid unsupported assumptions
about the precise form of rate equations. Using historical
data on measles epidemics as a case study, we show how this
approach can lead to better forecasts, better
characterizations of the dynamics, and a better
understanding of the factors causing complex population
dynamics relative to either mechanistic models or purely
descriptive statistical time-series models. The
semimechanistic models are found to have better forecasting
accuracy than either of the model types used in previous
analyses when tested on data not used to fit the models. The
dynamics are characterized as being both nonlinear and
noisy, and the global dynamics are clustered very tightly
near the border of stability (dominant Lyapunov exponent λ
≃ 0). However, locally in state space the dynamics
oscillate between strong short-term stability and strong
short-term chaos (i.e., between negative and positive local
Lyapunov exponents). There is statistically significant
evidence for short-term chaos in all data sets examined.
Thus the nonlinearity in these systems is characterized by
the variance over state space in local measures of chaos
versus stability rather than a single summary measure of the
over-all dynamics as either chaotic or nonchaotic.},
Doi = {10.1086/286130},
Key = {fds266670}
}
@article{fds266671,
Author = {WA Barnett and AR Gallant and MJ Hinich and JA Jungeilges and DT Kaplan and MJ Jensen},
Title = {A single-blind controlled competition among tests for
nonlinearity and chaos},
Journal = {Journal of Econometrics},
Volume = {82},
Number = {1},
Pages = {157-192},
Year = {1998},
ISSN = {0304-4076},
Abstract = {Interest has been growing in testing for nonlinearity or
chaos in economic data, but much controversy has arisen
about the available results. This paper explores the reasons
for these empirical difficulties. We designed and ran a
single-blind controlled competition among five highly
regarded tests for nonlinearity or chaos with ten simulated
data series. The data generating mechanisms include linear
processes, chaotic recursions, and non-chaotic stochastic
processes; and both large and small samples were included in
the experiment. The data series were produced in a single
blind manner by the competition manager and sent by e-mail,
without identifying information, to the experiment
participants. Each such participant is an acknowledged
expert in one of the tests and has a possible vested
interest in producing the best possible results with that
one test. The results of this competition provide much
surprising information about the power functions of some of
the best regarded tests for nonlinearity or noisy chaos. ©
1997 Elsevier Science S.A.},
Key = {fds266671}
}
@article{fds266672,
Author = {AR Gallant and CT Hsu and G Tauchen},
Title = {Using daily range data to calibrate volatility diffusions
and extract the forward integrated variance},
Journal = {Review of Economics and Statistics},
Volume = {81},
Number = {4},
Pages = {617-631},
Year = {1999},
url = {http://hdl.handle.net/10161/1999 Duke open
access},
Abstract = {A common model for security price dynamics is the
continuous-time stochastic volatility model. For this model,
Hull and White (1987) show that the price of a derivative
claim is the conditional expectation of the Black-Scholes
price with the forward integrated variance replacing the
Black-Scholes variance. Implementing the Hull and White
characterization requires both estimates of the price
dynamics and the conditional distribution of the forward
integrated variance given observed variables. Using daily
data on close-to-close price movement and the daily range,
we find that standard models do not fit the data very well
and that a more general three-factor model does better, as
it mimics the long-memory feature of financial volatility.
We develop techniques for estimating the conditional
distribution of the forward integrated variance given
observed variables.},
Key = {fds266672}
}
@article{fds266673,
Author = {AR Gallant and G Tauchen},
Title = {The relative efficiency of method of moments
estimators},
Journal = {Journal of Econometrics},
Volume = {92},
Number = {1},
Pages = {149-172},
Year = {1999},
url = {http://hdl.handle.net/10161/1900 Duke open
access},
Abstract = {The asymptotic relative efficiency of efficient method of
moments when implemented with a seminonparametric auxiliary
model is compared to that of conventional method of moments
when implemented with polynomial moment functions. Because
the expectations required by these estimators can be
computed by simulation, these two methods are commonly used
to estimate the parameters of nonlinear latent variables
models. The comparison is for the models in the Marron-Wand
test suite, a scale mixture of normals, and the second
largest order statistic of the lognormal distribution. The
latter models are representative of financial market data
and auction data, respectively, which are the two most
common applications of simulation estimators. Efficient
method of moments dominates conventional method of moments
over these models. © 1999 Elsevier Science S.A. All rights
reserved.},
Key = {fds266673}
}
@article{fds266674,
Author = {AR Fleissig and AR Gallant and JJ Seater},
Title = {Separability, aggregation, and euler equation
estimation},
Journal = {Macroeconomic Dynamics},
Volume = {4},
Number = {4},
Pages = {547-572},
Year = {2000},
Abstract = {We derive a seminonparametric utility function containing
the constant relative risk aversion (CRRA) function as a
special case, and we estimate the associated Euler equations
with U.S. consumption data. There is strong evidence that
the CRRA function is misspecified. The correctly specified
function includes lagged effects of durable goods and
perhaps nondurable goods, is bounded as required by Arrow's
Utility Boundedness Theorem, and has a positive rate of time
preference. Constraining sample periods and separability
structure to be consistent with the generalized axiom of
revealed preference affects estimation results
substantially. Using Divisia aggregates instead of the NIPA
aggregates also affects results.},
Key = {fds266674}
}
@article{fds266675,
Author = {B Eraker and GB Durham and AR Gallant},
Title = {Comment [4] (multiple letters)},
Journal = {Journal of Business and Economic Statistics},
Volume = {20},
Number = {3},
Pages = {327-329+335+337},
Year = {2002},
Key = {fds266675}
}
@article{fds266676,
Author = {Y Aït-Sahalia and GB Durham and AR Gallant},
Title = {Comment [1] (multiple letters)},
Journal = {Journal of Business and Economic Statistics},
Volume = {20},
Number = {3},
Pages = {317-321+335},
Year = {2002},
Key = {fds266676}
}
@article{fds266677,
Author = {H Zhou and GB Durham and AR Gallant},
Title = {Comment [7] (multiple letters)},
Journal = {Journal of Business and Economic Statistics},
Volume = {20},
Number = {3},
Pages = {332-335+338},
Year = {2002},
Key = {fds266677}
}
@article{fds266678,
Author = {G Tauchen and GB Durham and AR Gallant},
Title = {Comment [6] (multiple letters)},
Journal = {Journal of Business and Economic Statistics},
Volume = {20},
Number = {3},
Pages = {331-332+335+337},
Year = {2002},
Key = {fds266678}
}
@article{fds266679,
Author = {GB Durham and AR Gallant},
Title = {Numerical techniques for maximum likelihood estimation of
continuous-time diffusion processes},
Journal = {Journal of Business and Economic Statistics},
Volume = {20},
Number = {3},
Pages = {297-316},
Year = {2002},
url = {http://dx.doi.org/10.1198/073500102288618397},
Abstract = {Stochastic differential equations often provide a convenient
way to describe the dynamics of economic and financial data,
and a great deal of effort has been expended searching for
efficient ways to estimate models based on them. Maximum
likelihood is typically the estimator of choice; however,
since the transition density is generally unknown, one is
forced to approximate it. The simulation-based approach
suggested by Pedersen (1995) has great theoretical appeal,
hut previously available implementations have been
computationally costly. We examine a variety of numerical
techniques designed to improve the performance of this
approach. Synthetic data generated by a Cox-Ingersoll-Ross
model with parameters calibrated to match monthly
observations of the U.S. short-term interest rate are used
as a test case. Since the likelihood function of this
process is known, the quality of the approximations can be
easily evaluated. On datasets with 1,000 observations, we
are able to approximate the maximum likelihood estimator
with negligible error in well under 1 min. This represents
something on the order of a 10,000-fold reduction in
computational effort as compared to implementations without
these enhancements. With other parameter settings designed
to stress the methodology, performance remains strong. These
ideas are easily generalized to multivariate settings and
(with some additional work) to latent variable models. To
illustrate, we estimate a simple stochastic volatility model
of the U.S. short-term interest rate.},
Doi = {10.1198/073500102288618397},
Key = {fds266679}
}
@article{fds266680,
Author = {S Chib and N Shephard and GB Durham and AR Gallant},
Title = {Comment [3] (multiple letters)},
Journal = {Journal of Business and Economic Statistics},
Volume = {20},
Number = {3},
Pages = {325-327+335},
Year = {2002},
Key = {fds266680}
}
@article{fds266681,
Author = {P Glynn and GB Durham and AR Gallant},
Title = {Comment [5] (multiple letters)},
Journal = {Journal of Business and Economic Statistics},
Volume = {20},
Number = {3},
Pages = {330-331+335+337},
Year = {2002},
Key = {fds266681}
}
@article{fds266682,
Author = {DH Ahn and RF Dittmar and AR Gallant},
Title = {Quadratic Term Structure Models: Theory and
Evidence},
Journal = {Review of Financial Studies},
Volume = {15},
Number = {1},
Pages = {243-288},
Year = {2002},
ISSN = {0893-9454},
Abstract = {This article theoretically explores the characteristics
underpinning quadratic term structure models (QTSMs), which
designate the yield on a bond as a quadratic function of
underlying state variables. We develop a comprehensive QTSM,
which is maximally flexible and thus encompasses the
features of several diverse models including the double
square-root model of Longstaff (1989), the univariate
quadratic model of Beaglehole and Tenney (1992), and the
squared-autoregressive-independent-variable nominal term
structure (SAINTS) model of Constantinides (1992). We
document a complete classification of admissibility and
empirical identification for the QTSM, and demonstrate that
the QTSM can overcome limitations inherent in affine term
structure models (ATSMs). Using the efficient method of
moments of Gallant and Tauchen (1996), we test the empirical
performance of the model in determining bond prices and
compare the performance to the ATSMs. The results of the
goodness-of-fit tests suggest that the QTSMs outperform the
ATSMs in explaining historical bond price behavior in the
United States.},
Key = {fds266682}
}
@article{fds266683,
Author = {M Coppejans and AR Gallant},
Title = {Cross-validated SNP density estimates},
Journal = {Journal of Econometrics},
Volume = {110},
Number = {1},
Pages = {27-65},
Year = {2002},
url = {http://dx.doi.org/10.1016/S0304-4076(02)00121-5},
Abstract = {We consider cross-validation strategies for the
seminonparametric (SNP) density estimator, which is a
truncation (or sieve) estimator based upon a Hermite series
expansion with coefficients determined by quasi-maximum
likelihood. Our main focus is on the use of SNP density
estimators as an adjunct to efficient method of moments
(EMM) structural estimation. It is known that for this
purpose a desirable truncation point occurs at the last
point at which the integrated squared error (ISE) curve of
the SNP density estimate declines abruptly. We study the
determination of the ISE curve for iid data by means of
leave-one-out cross-validation and hold-out-sample
cross-validation through an examination of their performance
over the Marron-Wand test suite and models related to asset
pricing and auction applications. We find that both methods
are informative as to the location of abrupt drops, but that
neither can reliably determine the minimum of the ISE curve.
We validate these findings with a Monte Carlo study. The
hold-out-sample method is cheaper to compute because it
requires fewer nonlinear optimizations. We consider the
asymptotic justification of hold-out-sample
cross-validation. For this purpose, we establish rates of
convergence of the SNP estimator under the Hellinger norm
that are of interest in their own right. © 2002 Elsevier
Science B.V. All rights reserved.},
Doi = {10.1016/S0304-4076(02)00121-5},
Key = {fds266683}
}
@article{fds266691,
Author = {MW Brandt and P Santa-Clara and GB Durhama and AR
Gallant},
Title = {Comment [2] (multiple letters)},
Journal = {Journal of Business and Economic Statistics},
Volume = {20},
Number = {3},
Pages = {321-324+335},
Year = {2002},
Key = {fds266691}
}
@article{fds266684,
Author = {DH Ahn and RF Dittmar and AR Gallant and B Gao},
Title = {Purebred or hybrid?: Reproducing the volatility in term
structure dynamics},
Journal = {Journal of Econometrics},
Volume = {116},
Number = {1-2},
Pages = {147-180},
Year = {2003},
url = {http://dx.doi.org/10.1016/S0304-4076(03)00106-4},
Abstract = {This paper investigates the ability of mixtures of affine,
quadratic, and non-linear models to track the volatility in
the term structure of interest rates. Term structure
dynamics appear to exhibit pronounced time varying or
stochastic volatility. Ahn et al. (Rev. Financial Stud. xx
(2001) xxx) provide evidence suggesting that term structure
models incorporating a set of quadratic factors are better
able to reproduce term structure dynamics than affine
models, although neither class of models is able to fully
capture term structure volatility. In this study, we combine
affine, quadratic and non-linear factors in order to
maximize the ability of a term structure model to generate
heteroskedastic volatility. We show that this combination
entails a tradeoff between specification of heteroskedastic
volatility and correlations among the factors. By combining
factors, we are able to gauge the cost of this tradeoff.
Using efficient method of moments (Gallant and Tauchen,
Econometric Theory 12 (1996) 657), we find that augmenting a
quadratic model with a non-linear factor results in
improvement in fit over a model comprised solely of
quadratic factors when the model only has to confront first
and second moment dynamics. When the full dynamics are
confronted, this result reverses. Since the non-linear
factor is characterized by stronger dependence of volatility
on the level of the factor, we conclude that flexibility in
the specification of both level dependence and correlation
structure of the factors are important for describing term
structure dynamics. © 2003 Elsevier B.V. All rights
reserved.},
Doi = {10.1016/S0304-4076(03)00106-4},
Key = {fds266684}
}
@article{fds266685,
Author = {M Chernov and AR Gallant and E Ghysels and G Tauchen},
Title = {Alternative models for stock price dynamics},
Journal = {Journal of Econometrics},
Volume = {116},
Number = {1-2},
Pages = {225-257},
Year = {2003},
url = {http://hdl.handle.net/10161/1892 Duke open
access},
Abstract = {This paper evaluates the role of various volatility
specifications, such as multiple stochastic volatility (SV)
factors and jump components, in appropriate modeling of
equity return distributions. We use estimation technology
that facilitates nonnested model comparisons and use a long
data set which provides rich information about the
conditional and unconditional distribution of returns. We
consider two broad families of models: (1) the multifactor
loglinear family, and (2) the affine-jump family. Both
classes of models have attracted much attention in the
derivatives and econometrics literatures. There are various
tradeoffs in considering such diverse specifications. If
pure diffusion SV models are chosen over jump diffusions, it
has important implications for hedging strategies. If
logarithmic models are chosen over affine ones, it may
seriously complicate option pricing. Comparing many
different specifications of pure diffusion multifactor
models and jump diffusion models, we find that (1) log
linear models have to be extended to two factors with
feedback in the mean reverting factor, (2) affine models
have to have a jump in returns, stochastic volatility or
probably both. Models (1) and (2) are observationally
equivalent on the data set in hand. In either (1) or (2) the
key is that the volatility can move violently. As we obtain
models with comparable empirical fit, one must make a choice
based on arguments other than statistical goodness-of-fit
criteria. The considerations include facility to price
options, to hedge and parsimony. The affine specification
with jumps in volatility might therefore be preferred
because of the closed-form derivatives prices. © 2003
Elsevier B.V. All rights reserved.},
Doi = {10.1016/S0304-4076(03)00108-8},
Key = {fds266685}
}
@article{fds266686,
Author = {LJ Christiano and AR Gallant and CA Sims and J Faust and L Kilian, MD
Negro and F Schorfheide and F Smets and R Wouters},
Title = {Comment},
Journal = {Journal of Business and Economic Statistics},
Volume = {25},
Number = {2},
Pages = {143-162},
Year = {2007},
ISSN = {0735-0015},
url = {http://dx.doi.org/10.1198/073500107000000061},
Doi = {10.1198/073500107000000061},
Key = {fds266686}
}
@article{fds266687,
Author = {AR Gallant and H Hong},
Title = {A statistical inquiry into the plausibility of recursive
utility},
Journal = {Journal of Financial Econometrics},
Volume = {5},
Number = {4},
Pages = {523-559},
Year = {2007},
ISSN = {1479-8409},
url = {http://dx.doi.org/10.1093/jjfinec/nbm013},
Abstract = {We use purely statistical methods to determine if the
pricing kernel is the intertemporal marginal rate of
substitution under recursive utility. We introduce a
nonparametric Bayesian method that treats the pricing kernel
as a latent variable and extracts it and its transition
density from payoffs on 24 Fama-French portfolios, on bonds,
and on payoffs that use conditioning information available
when portfolios are formed. Our priors are formed from an
examination of a Bansal-Yaron economy. Using both monthly
data and annual data, we find that the data support
recursive utility. © The Author 2007. Published by Oxford
University Press.},
Doi = {10.1093/jjfinec/nbm013},
Key = {fds266687}
}
@article{fds266693,
Author = {R Bansal and AR Gallant and G Tauchen},
Title = {Rational pessimism, rational exuberance, and asset pricing
models},
Journal = {Review of Economic Studies},
Volume = {74},
Number = {4},
Pages = {1005-1033},
Year = {2007},
ISSN = {0034-6527},
url = {http://dx.doi.org/10.1111/j.1467-937X.2007.00454.x},
Abstract = {The paper estimates and examines the empirical plausibility
of asset pricing models that attempt to explain features of
financial markets such as the size of the equity premium and
the volatility of the stock market. In one model, the
long-run risks (LRR) model of Bansal and Yaron,
low-frequency movements, and time-varying uncertainty in
aggregate consumption growth are the key channels for
understanding asset prices. In another, as typified by
Campbell and Cochrane, habit formation, which generates
time-varying risk aversion and consequently time variation
in risk premia, is the key channel. These models are fitted
to data using simulation estimators. Both models are found
to fit the data equally well at conventional significance
levels, and they can track quite closely a new measure of
realized annual volatility. Further, scrutiny using a rich
array of diagnostics suggests that the LRR model is
preferred. © 2007 The Review of Economic Studies
Limited.},
Doi = {10.1111/j.1467-937X.2007.00454.x},
Key = {fds266693}
}
@article{fds266689,
Author = {ARM Cheng and AR Gallant and C Ji and BS Lee},
Title = {A Gaussian approximation scheme for computation of option
prices in stochastic volatility models},
Journal = {Journal of Econometrics},
Volume = {146},
Number = {1},
Pages = {44-58},
Year = {2008},
ISSN = {0304-4076},
url = {http://dx.doi.org/10.1016/j.jeconom.2008.07.002},
Abstract = {We consider European options on a price process that follows
the log-linear stochastic volatility model. Two stochastic
integrals in the option pricing formula are costly to
compute. We derive a central limit theorem to approximate
them. At parameter settings appropriate to foreign exchange
data our formulas improve computation speed by a factor of
1000 over brute force Monte Carlo making MCMC statistical
methods practicable. We provide estimates of model
parameters from daily data on the Swiss Franc to Euro and
Japanese Yen to Euro over the period 1999-2002. © 2008
Elsevier B.V. All rights reserved.},
Doi = {10.1016/j.jeconom.2008.07.002},
Key = {fds266689}
}
@article{fds266688,
Author = {AR Gallant and RE Mcculloch},
Title = {On the determination of general scientific models with
application to asset pricing},
Journal = {Journal of the American Statistical Association},
Volume = {104},
Number = {485},
Pages = {117-131},
Year = {2009},
ISSN = {0162-1459},
url = {http://dx.doi.org/10.1198/jasa.2009.0008},
Abstract = {We consider a consumption-based asset pricing model that
uses habit persistence to overcome the known statistical
inadequacies of the classical consumption-based asset
pricing model. We find that the habit model fits reasonably
well and agrees with results reported in the literature if
conditional heteroskedasticity is suppressed but that it
does not fit nor do results agree if conditional
heteroskedasticity, well known to be present in financial
market data, is allowed to manifest itself.We also find that
it is the preference parameters of the model that are most
affected by the presence or absence of conditional
heteroskedasticity, especially the risk aversion parameter.
The habit model exhibits four characteristics that are often
present in models developed from scientific considerations:
(1) a likelihood is not available; (2) prior information is
available; (3) a portion of the prior information is
expressed in terms of functionals of the model that cannot
be converted into an analytic prior on model parameters; (4)
the model can be simulated. The underpinning of our approach
is that, in addition, (5) a parametric statistical model for
the data, determined without reference to the scientific
model, is known. In general one can expect to be able to
determine a model that satisfies (5) because very richly
parameterized statistical models are easily accommodated. We
develop a computationally intensive, generally applicable,
Bayesian strategy for estimation and inference for
scientific models that meet this description together with
methods for assessing model adequacy. An important adjunct
to the method is that a map from the parameters of the
scientific model to functionals of the scientific and
statistical models becomes available. This map is a powerful
tool for understanding the properties of the scientific
model. © 2009 American Statistical Association.},
Doi = {10.1198/jasa.2009.0008},
Key = {fds266688}
}
@article{fds266690,
Author = {EM Aldrich and AR Gallant},
Title = {Habit, long-run risks, prospect? A statistical
inquiry},
Journal = {Journal of Financial Econometrics},
Volume = {9},
Number = {4},
Pages = {589-618},
Year = {2011},
ISSN = {1479-8409},
url = {http://dx.doi.org/10.1093/jjfinec/nbq034},
Abstract = {We use recently proposed Bayesian statistical methods to
compare the habit persistence asset pricing model of
Campbell and Cochrane, the long-run risks model of Bansal
and Yaron, and the prospect theory model of Barberis, Huang,
and Santos. We improve these Bayesian methods so that they
can accommodate highly nonlinear models such as the three
aforementioned. Our substantive results can be stated
succinctly: If one believes that the extreme consumption
fluctuations of 1930-1949 can recur, although they have not
in the last sixty years even counting the current recession,
then the long-run risks model is preferred. Otherwise, the
habit model is preferred. © The Author 2011. Published by
Oxford University Press. All rights reserved.},
Doi = {10.1093/jjfinec/nbq034},
Key = {fds266690}
}
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