Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We provide a simple framework for interpreting instrumental variable regressions when there is a gap in time between the impact of the instrument and the measurement of the endogenous variable, highlighting a particular violation of the exclusion restriction that can arise in this setting. In the presence of this violation, conventional IV regressions do not consistently estimate a structural parameter of interest. Building on our framework, we develop a simple empirical method to estimate the long-run effect of the endogenous variable. We use our bias correction method to examine the role of institutions in economic development, following Acemoglu et al. (2001). We find long-run coefficients that are smaller than the coefficients from the original work, demonstrating the quantitative importance of our framework.