Showing 1 - 10 of 15
<p>The  robust version of the classical  instrumental variables, called Instrumental Weighted Variables (IWV) and the conditions for its consistency and $\sqrt{n}$-consistency  are recalled. The reasons  why the classical instrumental variables as well as  IWV were introduced and the idea of...</p>
Persistent link: https://www.econbiz.de/10011152546
  <p><span style="font-size: 11.000000pt; font-family: 'CMTI10';">Consistency </span><span style="font-size: 11.000000pt; font-family: 'CMR10';">of the </span><span style="font-size: 11.000000pt; font-family: 'CMTI10';">least weighted squares with constraints </span><span style="font-size: 11.000000pt; font-family: 'CMR10';">under </span><span style="font-size: 11.000000pt; font-family: 'CMTI10';">heteroscedasticity </span><span style="font-size: 11.000000pt; font-family: 'CMR10';">is proved and the patterns of numerical study (for the whole collection of situations) reveals its finite sample properties (on the background of the well-known </span><span style="font-size: 11.000000pt; font-family: 'CMTI10';">least trimmed squares</span><span style="font-size: 11.000000pt; font-family: 'CMR10';">). The possibility of...</span></p>
Persistent link: https://www.econbiz.de/10011152552
N/A
Persistent link: https://www.econbiz.de/10008528792
Paper shows that, under assumption that the single forecasts which enter the combination are unbiased, imposing some constraints on coordinates of <em>M </em>-estimator (of corresponding regression coefficients) leads to a gain in the asymptotic variance of one-step forward prediction evaluated by means...
Persistent link: https://www.econbiz.de/10008528813
The famous Durbin-Watson statistic is studied for the residuals from the least trimmed squared regression analysis. Having proved asymptotic linearity of corresponding functional (namely sum of h smallest squared residuals), an asymptotic representation of the least trimmed squares estimator is...
Persistent link: https://www.econbiz.de/10008528827
The consistency and the asymptotic normality of the least weighted squares is proved and its asymptotic representation derived. Although the proof includes rather large amount of technicalities, it is not difficult to follow. The technique as follows from the analogy with the least trimmed...
Persistent link: https://www.econbiz.de/10008528864
An example of possible misIeading role of the basic charaeteristics of the c1assical LB regression analysis is given. Another example using high breakdown point estimators demonstrates that in the case of contaminated data various estimators may give considerably different estimates....
Persistent link: https://www.econbiz.de/10008528865
Paper recalls motivation for generalized method of moments (GMM) as well as the idea estimated generalized method of moments. Having demonstrated the danger of underrating the heteroscedasticity of disturbances and recalling Cragg's idea of improvement of estimation under heteroscedasticity, it...
Persistent link: https://www.econbiz.de/10008528866
Consistency, asymptotic representation and asymptotic normality of the least trimmed squares estimator of regression coefficients is derived in the framework with random carriers. Also a result describing sensitivity to the deletion of an observation is given.
Persistent link: https://www.econbiz.de/10008528873
The consistency and the asymptotic normality of the least weighted squares is proved and its asymptotic representation derived. Although the proof includes rather large amount of technicalities, it is not difficult to follow. The technique as follows from the analogy with the least trimmed...
Persistent link: https://www.econbiz.de/10008528880