The Differential Regional Effects of Monetary Policy

Firm heterogeneity and regional business cycles differentials

“…Specifically, firm size may be responsible for the transmission of monetary shocks through the so called "balance-sheet" and the "banklending" channels (Bernanke and Gertler, 1995;Carlino and DeFina, 1998;Guiso et al, 2000;Ehrmann, 2000;Dedola and Lippi, 2000). In the balance-sheet view, given asymmetric information, access to credit depends on the value of firms" assets, acting as collateral.…”

“…Moreover, Carlino and DeFina (1998) We use the logarithm of the number of employees ( ln emp ) as proxy for capital market access (ability to borrow), so as we expect a positive effect of firm size on the probability to produce a high level of output, Pr y 3 , and a negative effect on the probability to produce a low level of output, Pr y 1 . Uncertainty remains for the effect of firm size on the probability to produce a normal level of output, Pr y 2 .…”

“…Due to the high inter-industry heterogeneity in export propensity, regional differences in the industry mix are therefore the major responsible for regional differentials in business cycle intensity. The role of industry mix is also highlighted within the "interest rate channel view" of the monetary policy transmission theory (Carlino and DeFina, 1998;Dedola and Lippi, 2000): the output sensitiveness to a policy induced variation in the short-term interest rate varies significantly across industries, so as the monetary policy may have asymmetric effects on regions with large differences in the industrial structure. It is puzzling that, after controlling for industrial composition, these studies still find significant regional cyclical heterogeneity, so as the industry mix can only partially explain these differences.…”

Oil Price Shocks: Bank Size and Firm Size Effects

“…Lastly, we conduct simultaneous monetary policy and oil price shocks and find that the addition of a monetary policy shock changes the response patterns across the states very little compared to an oil price shock alone. 1 Carlino and DeFina (1998) developed the primary framework used in our paper, connecting monetary policy and regional variation. With nearly two decades of additional research at our disposal, however, we refine their methodology, expand the model's predictive capacity, and augment the dataset in the following ways.…”

“…First, we recast their VAR to handle oil price shocks, instead of just federal funds rate shocks. Second, Carlino and DeFina (1998) only estimate their VARs in first differences, losing some of the information embedded in the levels of the data. Sims (1980) and Sims, Stock, and Watson (1990) warn about the hazards of transforming nonstationary data in VARs.…”