000			04044cam a2200337 a 4500
999			_c230552 _d189114
001			1210493
003			CO-BoCAI
005			20190703103322.0
008			170417s1999 enka010fr 0|1 eeng d
020			_a9780521669672
040			_aCO-BoCAIE _cCO-BoCAIE _erda
041	1		_aeng
082	0	4	_a330.015195 _bG35 _221
084			_2JEL _aC01
245	0	0	_aGeneralized method of moments estimation
250			_aEditor Laszlo Matyas.
260			_aCambridge : _bCambridge University Press, _c1999.
300			_aix, 316 páginas : _btablas ; _c23 cm.
336			_2rdacontenido _aTexto _btxt
337			_2rdamedio _aSin mediación _bn
338			_2rdasoporte _aVolumen _bnc
490			_aThemes in modern econometrics
504			_aIncluye bibliografías
505			_a1. Introduction to the generalized method of moments estimation /David Harris and Lásló Mátyás: 1.1. The method of moments ; 1.2. Generalized method of moments (GMM) estimation ; 1.3. Asymptotic properties of the GMM estimator ; 1.4. Conclusion -- 2. GMM estimation techniques / Masao Ogaki: 2.1. GMM estimation ; 2.2. Nonlinear instrumental variable ; 2.3. GMM applications with stationary ; 2.4. GMM in the presence of nonstationary variables ; 2.5. Some aspects of GMM estimation -- 3. Covariance matrix estimation / Matthew J. Cushing and Mary G. MacGarvey: 3.1. Preliminary results ; 3.2. The estimated ; 3.3. Kernel estimators of Vt ; 3.4. Optimal choice of covariance estimator ; 3.5. Finite sample properties of HAC -- 4. Hypothesis testing in models estimated by GMM / Alastair R. Hall: 4.1. Identifying and overidentifying restrictions ; 4.2. Testing hypotheses about E[f(xt, 0o)] ; 4.3. Testing hypotheses abour subsets of E[f(xt,0o)] ; 4.4. Testing hypotheses about the parameter vector ; 4.5. Testing hypotheses about structural stability ; 4.6. Testing non-nested hypotheses ; 4.7. Conditional moment test -- 5. Finite sample properties of GMM estimators and test / Jan M. Podivinsky: 5.1. Related theoretical literature ; 5.2. Simulation evidence ; 5.3. Extensions of standard GMM ; 5.4. Concluding comments -- 6. GMM estimation of time series models / David Harris: 6.1. Estimation of moving average models ; 6.2. Estimation of ARMA models ; 6.3. Applications to United Root testing ; Appendix: Proof of theorem 6.1. -- 7. Reduced rank regression using GMM / Frank Kleibergen: 7.1. GMM-2SLS Estimators in reduced rank models ; 7.2. Testing cointegration using GMM-2SLS estimators ; 7.3. Cointegration in model with Heteroskedasticity ; 7.4. Cointegration with structural breaks ; 7.5. Conclusion -- 8. Estimation of linear pnale data models using GMM / Seung C. Ahn and Peter Schmidt: 8.1. Preliminaries ; 8.2. Models with weakly exogenous ; 8.3. Models with strictly exogenous regressors ; 8.4. Simultaneous equations ; 8.5. Dynamic panel data models ; 8.6. Conclusion -- 9. Alternative GMM methods for nonlinear panel data models / Jorg Breitung and Michael Lechner: 9.1. A class of nonlinear panel data models ; 9.2. G, estimators for the conditional mean ; 9.3. Higher order moment conditions ; 9.4. Selecting moment conditions: the gallant-tauchen approach ; 9.5. A minimum distance approach ; 9.6. Finite sample properties ; 9.7. Results ; 9.8. An application ; 9.9. Concluding remarks -- 10. Simulation based method of moments / Roman Liesefeld an dJörg Breitung: 10.1. General setup and applications ; 10.2. The method of simulated moments (MSM) ; 10.3. Indirect inference estimator ; 10.4. The SNP approach ; 10.5. Some practical issues ; 10.6. Conclusion -- 11. Logically inconsistent limited dependent variables models J.S. Butler and Gabriel Picone: 11.1. Logical inconsistency ; 11.2. Identification ; 11.3. Estimation ; 11.4. Conclusion and extensions.
650		4	_aModelos econométricos _938426
650		4	_aMétodo de momentos (Estadística) _939239
690		0	_aC01 - Econometría _938744
700	1		_aMátyás, László _943539 _eeditor
942			_2ddc _cLIBRO