Structural equation modeling: foundations and extensions David, Kaplan

By:

David, Kaplan

Series: Advanced quantitative techniques in the social sciences: NoPublication details: Los Angeles Sage Publications 2009Edition: 2nd edDescription: xi, 255 pISBN:

9781412916240

Subject(s):

DDC classification:

300.15118

Summary: The issues of identification, estimation, and statistical inferences of nonstationary time series and simultaneous equation models are reviewed. It is shown that prior information matters and the advantage of dichotomization of the traditional autoregressive distributed lag model into the long-run equilibrium relation and the short-run dynamic adjustment process as an empirical modeling device may be exaggerated. A Japanese money demand study is used to illustrate that a direct approach yields a more stable long-run and short-run relationship and has better predictive power than the approach of letting the data determine the long-run relationship and modeling the short-run dynamics as an adjustment of the deviation from its equilibrium position.

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Item type	Current library	Call number	Status	Date due	Barcode	Item holds
Book	Ahmedabad	300.15118 K2S8 (Browse shelf(Opens below))	Available		166223

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Previous	300.151 M3A7 Applied multivariate research: design and interpretation	300.151 M3A7 Applied multivariate research: design and interpretation	300.15118 B3M2 Marginal models: for dependent, clustered, and longitudinal categorical data	300.15118 K2S8 Structural equation modeling: foundations and extensions	300.1518282 C2M6 Monte Carlo simulation and resampling methods for social science	300.151932 B7G2 Game theory and the humanities: bridging two worlds

The issues of identification, estimation, and statistical inferences of nonstationary time series and simultaneous equation models are reviewed. It is shown that prior information matters and the advantage of dichotomization of the traditional autoregressive distributed lag model into the long-run equilibrium relation and the short-run dynamic adjustment process as an empirical modeling device may be exaggerated. A Japanese money demand study is used to illustrate that a direct approach yields a more stable long-run and short-run relationship and has better predictive power than the approach of letting the data determine the long-run relationship and modeling the short-run dynamics as an adjustment of the deviation from its equilibrium position.

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