The credit channel in Chile through the lens of a semi-structural model

In this paper, we estimate a semi-structural model with a banking sector for the Chilean economy. Our innovation consists of incorporating a system of equations that reflects the dynamics of credit, interest rate spreads, and loan-loss provisions to the Central Bank of Chile's semi-structural model (modelo semi-estructural de proyección). We estimate the model and analyze the macroeconomic effects of incorporating this sector. We find that the banking sector plays a role in accelerating the business cycle through lower spreads and procyclical credit supply, in contrast to its counter-cyclical role in the COVID-19 crisis. Additionally, we find that credit growth can explain about 0.3 pp of total output gap variation on average. Moreover, we find that in episodes of severe stress, this gap can grow to 1.9 pp, as it did during the COVID-19 pandemic. We also identify a credit multiplier of up to 0.06 pp of GDP for each 1 pp of growth in commercial credit. Our results suggest not only that these nonconventional policies through the credit channel can be useful but also that our model can be used for evaluation purposes.