Abstract
ABSTRACTAmiti and Weinstein proposed an estimation framework to disentangle credit demand and supply shocks using matched bank-firm loan data. Here, we show that their estimator can be generalized to capture shocks arising in an arbitrary number of dimensions. Our algorithm permits empirical researchers to analyse multi-dimensional data sets using the Amiti–Weinstein framework. This may be beneficial both for studies on micro-level outcomes as well as for the literature on assessing the macroeconomic impact of idiosyncratic shocks. In an empirical application to a firm-product-country export data set, we highlight the usefulness of the generalized Amiti–Weinstein estimator, and we demonstrate the importance of considering additional dimensions when gauging the effect of granular shocks on aggregate fluctuations.
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