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the theory and practice of econometrics

By: Contributor(s): Language: English Series: wiley series in probability and mathematical statistics. applied probability and statistics | bradley, ralph a. (ed.) | hunter, j. stuart (ed.) | kendall, david g. (ed.) | et alPublication details: new york, chichester, brisbane : john wiley and sons 1980Edition: 1. edDescription: xxvii, 793 ppISBN:
  • 0-471-05938-2
Subject(s): DDC classification:
  • 330 economics
Contents:
from the table of contents: preface; introduction; estimation and inference: traditional statistical models, estimators, and sampling properties; combining sample and other information; choice of stochastic assumptions: heteroscedasticity; autocorrelation; disturbance-related sets of regression equations; nonnormal disturbances; pooling of data and varying parameter models: inference in models that combine time series and cross-sectional data; inference in stochastic parameter models; inference in variable parameter models that use aggregate data; choosing the dimension and form of the design matrix: on selecting the set of regressors; multicollinearity; unobservable and qualitative variables: unobservable variables; qualitative and limited dependent variables; leads and lags: finite distributed lags; inifinite distributed lags; nonlinear statistical models: nonlinear statistical models. estimation, computational methods, and inference; the state of econometric theory and practice;
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Loanable Institute for Advanced Studies (IHS) Book 9766-A Available IHS103134402

from the table of contents: preface; introduction; estimation and inference: traditional statistical models, estimators, and sampling properties; combining sample and other information; choice of stochastic assumptions: heteroscedasticity; autocorrelation; disturbance-related sets of regression equations; nonnormal disturbances; pooling of data and varying parameter models: inference in models that combine time series and cross-sectional data; inference in stochastic parameter models; inference in variable parameter models that use aggregate data; choosing the dimension and form of the design matrix: on selecting the set of regressors; multicollinearity; unobservable and qualitative variables: unobservable variables; qualitative and limited dependent variables; leads and lags: finite distributed lags; inifinite distributed lags; nonlinear statistical models: nonlinear statistical models. estimation, computational methods, and inference; the state of econometric theory and practice;

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