The Monetary Transmission Mechanism and Business Cycles: The Role of Multi-stage Production with Inventories

Abstract

This thesis studies the role of multi-stage production for the monetary transmission mechanism. I employ a monetary search model to show how multi-stage production influences both the long run and the short run effects of money growth. Multi-stage production provides an additional channel for money growth having effects through intermediate goods between different production stages. Extending Shi's (1998) model from a single-stage to a multi-stage production model, I show that money growth rate has an unconventional long run effect on quantities per match, and the long run response of input inventory investment is different from that of output inventory investment. Contrary to classic search models, the steady state effect of money growth on the quantity of finished goods per match is not monotonic and depends on the money growth rate. Furthermore, in steady state the quantities per match first increase with the growth rate of money, before falling for large growth rates. Input inventories arise due to search frictions. Money growth also has hump-shaped real effects on steady state input inventory investment. The intermediate goods build a bridge between the labor market and the finished goods market. Intuitively, households hire more labor with higher future revenue and produce more intermediate goods in order to match the employment level. With more labor and more intermediate goods, finished goods producers can produce more when matched. As a consequence, they are stuck with more input inventories. Moreover, my model suggests that changes in the money growth rate would be one of the reasons for the decline of the inventory-to-sales ratio since the mid-1980s. Finally, I calibrate my model to quarterly US data. Contrary to other work, my model is able to replicate the stylized facts on inventory movements over the business cycle by solely relying on monetary shocks. The theoretical impulse response functions can quantitatively reproduce the corresponding empirical ones estimated in a structure autoregressive model. Moreover, the quantitative analysis supports the argument that input inventories amplify aggregate fluctuations over business cycles.