The efficiency of OLS estimator in the linear-regression model with spatially correlated errorsdoi:10.4314/SINET.V24I1.18173Butte GotuFaculty of Science, Addis Ababa University
moreefficientthanOLSforthemodelwithoutaninterceptterm. 1.Introduction Itiswidelyacceptedthattheordinaryleastsquares(OLS)estimator, thoughunbiased,isingeneralinefficientinthepresenceofautocorrelated disturbances.InthecaseofAR(1)disturbances,Cochrane96Orcutt(1949) ...
THEREVIEWOFECONOMICSANDSTATISTICS efficiencyobtainedbyusingtheancillarydataisin- vestigated. Supposethat,givenavectorx,twovariatesYjandY2 arebivariatenormallydistributed: [Yi X - N2 I I Ia/ I] (1) Y2~~ [X'"TT][PUri 1JJ RealisationsofYiareobservedbutY2isnotobserv- ...
In recent years, the quality of the environment has declined dramatically as a result of human activities, which threaten the sustainability of our ecosyst
(around −3.0), that is, of the opposite sign to our OLS fixed effects estimates and the usual findings of the literature (Chen et al., 2016;Wang et al., 2018). Therefore, while energy is a growth-enhancing factor for our sample, economic growth may favor a more efficient use of ...
The final estimator is α¯=P−1∑p=1Pα^P. Finally, we can estimate H using the usual relationship between α and H.This alternative algorithm is especially useful for financial data, which are often irregularly sampled or have missing observations. Anyway, the algorithm can also be used...
The Johansen co-integration test was not used in the present investigation because it assumes that the variables under examination must be integrated into the first difference when assessing the presence of a unit root. However, the GMM estimator also includes several assumptions that solely deal ...
First and second generation unit root tests are used to assess the stationarity of the series, Pedroni and Kao tests are used to test co-integration. The long-term associations are examined using fully modified ordinary least square (FMOLS) and panel dynamic ordinary least square (DOLS) for ...
Then, the variance of u i is λ 2 , so the standard deviation of the OLS residuals is a consistent estimator of E[u i ] = λ. Since this is a one parameter distribution, the entire model for u i can be characterized by this parameter and functions of it. The estimated ...
where\(\beta _1^{i *} = \beta _1^{i} - 1\)and\(v_{t,(j)}^{*i} = v_{t,(j)}^{i} - N^{-1} \sum _{s \in \mathcal {T}} v_{s,(j)}^{i}\). The OLS estimator for\(\beta _1^{i *}\)is $$\begin{aligned} {\hat{\beta }}_1^{i *}&= \frac{ \fra...