In a time-series model, such as Yt = b1 + b2Yt–1 + ut , OLS estimators are biased, because the disturbance terms violate one of the conditions necessary for unbiasedness. Which of the following best explains the condition that is responsible for this?

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In a time-series model, such as Y<sub>t</sub> = b<sub>1</sub> + b<sub>2</sub>Y<sub>t–1</sub> + u<sub>t</sub> , OLS estimators are biased, because the disturbance terms violate one of the conditions necessary for unbiasedness. Which of the following best explains the condition that is responsible for this?






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