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Like biased, inconsistent and, with great scorn, a "state bureaucrat".
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If any of these situations is present, OLS estimates are biased and inconsistent.
Excluding those variables may increase the risk of endogeneity and produce biased and inconsistent OLS estimator.
The OLS would, therefore, provide biased and inconsistent estimates of the model parameters due to simultaneity bias.
According to Engle and Grange [14], the parameter estimates from such regression may be biased and inconsistent.
The results shown in Table 4 are biased and inconsistent estimates when the unobserved heterogeneity is correlated with the lagged dependent variables.
Therefore, some valid instruments must be used to avoid biased and inconsistent estimated parameters.19 The tax revenue misestimation may be endogenous.
The endogeneity of remittances would cause biased and inconsistent estimates of the parameters (and of their standard errors) when assessing the propensity to save.
Since statistically omitting a variable that belongs in population models provides biased and inconsistent estimates, any comparative effectiveness studies in RA treatment should include severity scores.
An OLS estimation of Eq. (13) would be biased and inconsistent, as the error term is correlated with the parent's education.
There is an additional issue that must be taken into account: the potential endogeneity bias of some or all of the explanatory variables, causing the OLS estimator to be biased and inconsistent.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com