Results 1 to 10 of about 50 (45)

Estimating Euler Equations [PDF]

Working Paper Series, 2000
In this paper we consider conditions under which the estimation of a log-linearized Euler equation for consumption yields consistent estimates of the preference parameters. When utility is isoelastic and a sample covering a long time period is available, consistent estimates are obtained from the log-linearized Euler equation when the innovations to ...
Orazio P. Attanasio, Hamish Low
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Aggregated estimating equation estimation [PDF]

Statistics and Its Interface, 2011
Motivated by the recent active research on online analytical processing (OLAP), we develop a computation and storage efficient algorithm for estimating equation (EE) estimation in massive data sets using a “divide-and-conquer” strategy. In each partition of the data set, we compress the raw data into some low dimensional statistics and then discard the
Nan Lin, Ruibin Xi
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Time-Invariance Estimating Equations [PDF]

Bernoulli, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Solving Non-Linear Estimation Equations

Journal of the Royal Statistical Society Series B: Statistical Methodology, 1993
SUMMARY In this paper we consider the numerical computation of a vector parameter estimate θ^ which is a root of a system of unbiased non-linear estimation equations. A sequence {θ  (r)} is constructed which converges with a probability approaching 1 to θ^ from any starting value θ  (0).
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Estimating Demand Equations [PDF]

Econometrica, 1968
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Estimating export equations [PDF]

Applied Economics Letters, 2007
Accurate estimates of the price and income elasticities of exports are valuable for growth policies based on trade promotion. However, not sufficient attention seems to have been paid to the specification of the relative price variable in some influential empirical works.
B Bhaskara Rao, Rup Singh
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Robust Estimation Through Estimating Equations

Biometrika, 1984
The paper deals with the choice of parameter definition. It develops the concepts of parameter defining function and effective parameter. It also provides theory and techniques for choosing from a given set of robust parameters the one that can most efficiently be estimated. This theory is applied to location parameters.
Godambe, V. P., Thompson, M. E.
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Generalized Estimating Equations

2002
Correlated datasets develop when multiple observations are collected from a sampling unit (e.g., repeated measures of a bank over time, or hormone levels in a breast cancer patient over time), or from clustered data where observations are grouped based on a shared characteristic (e.g., observations on different banks grouped by zip code, or on cancer ...
James W. Hardin, Joseph M. Hilbe
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Penalized Estimating Equations

Biometrics, 2003
Summary. Penalty models—such as the ridge estimator, the Stein estimator, the bridge estimator, and the Lasso—have been proposed to deal with collinearity in regressions. The Lasso, for instance, has been applied to linear models, logistic regressions, Cox proportional hazard models, and neural networks.
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Estimating demand equations

European Economic Review, 1977
The sum over individuals of the differentials of demand functions is the basic starting point of the Rotterdam model. In this paper, we show that this global differential can be inverted. Moreover, it can be parametrized according to the lines of the Rotterdam model.
Lise Salvas-Bronsard, D. Leblanc, C. Bronsard   +2 more
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