Nonparametric econometrics / Adrian Pagan, Aman Ullah.
Material type:
TextPublication details: Cambridge [England] : Cambridge University Press, 1999.Description: xviii, 424 p. : ill. ; 24 cmISBN: - 0521355648 (h)
- 9780521355643 (h)
- 0521586119 (pbk.)
- 9780521586115 (pbk.)
- HB139 .P34 1999
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| HB139 .M35 Econometrics / | HB139 .M575 Econometric foundations / | HB139 .M575 Econometric foundations / | HB139 .P34 1999 Nonparametric econometrics / | HB139 .W665 2000 Introductory econometrics : | HB139 .W665 2000 Introductory econometrics : | HB139 .Z1 Statistical foundations for econometric techniques / |
Include index.
Methods of Density Estimation --
Nonparametric Density Estimation --
A "Local" Histogram Approach --
A Formal Derivation of andfirac;[subscript 1] (x) --
Rosenblatt-Parzen Kernel Estimator --
The Nearest Neighborhood Estimator --
Variable Window-Width Estimators --
Series Estimators --
Penalized Likelihood Estimators --
The Local Log-Likelihood Estimators --
Estimation of Derivatives of a Density --
Finite-Sample Properties of the Kernel Estimator --
The Exact Bias and Variance of the Estimator andfirac; --
Approximations to the Bias and Variance and Choices of h and K --
Reduction of Bias --
Asymptotic Properties of the Kernel Density Estimator andfirac; with Independent Observations --
Asymptotic Unbiasedness --
Consistency --
Asymptotic Normality --
Small-Sample Confidence Intervals --
Sampling Properties of the Kernel Density Estimator with Dependent Observations --
Unbiasedness --
Consistency --
Asymptotic Normality --
Bibliographical Summary (Approximate and Asymptotic Results) --
Choices of Window Width and Kernel: Further Discussion --
Choice of h --
Choice of Higher Order Kernels --
Choice of h for Density Derivatives --
Multivariate Density Estimation --
Testing Hypotheses about Densities --
Comparison with a Known Density Function --
Testing for Symmetry --
Comparison of Unknown Densities --
Testing for Independence --
Density of Stock Market Returns --
Estimating the Dickey-Fuller Density --
Conditional Moment Estimation --
Estimating Conditional Moments by Kernel Methods --
Parametric Estimation.
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