Identifying Assumptions and Research Dynamics

A representative researcher has repeated opportunities for empirical research. To process findings, she must impose an “identifying assumption†ensuring that repeated observation would provide a definitive answer to her question. She conducts research when the assumption is sufficiently plausible (given the quality of the opportunity and her current belief), and updates beliefs as if the assumption were perfectly valid. We study the dynamics of this learning process. While the rate of research cannot always increase over time, research slowdown is possible. We characterize environments in which the rate is constant. Long-run beliefs can be biased and history-dependent. We apply the model to stylized examples of empirical methodologies: experiments, causal-inference techniques, and more structural identification methods such as “calibration†and “Heckman selection.â€