Biased estimates are statistical estimates that systematically deviate from the true parameter values they are intended to estimate. This can lead to inaccurate conclusions and decisions based on the analysis, affecting the validity of the model. Biased estimates can arise from several issues, including omitted variables, incorrect model specifications, sample selection problems, and endogeneity, each of which can distort the relationship being analyzed.
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