Final Report Summary - MEF (The macroeconomic effects of microeconomic inaction)
Our project constructs models that are able to reproduce such cross-sectional evidence. A key feature of the theoretical models we build is (i) they embed several classic models as special cases and (ii) they retain enough tractability to allow studying the output effects of a monetary shock analytically. A key result is a simple formula, which applies to a large class of models, and is useful to approximate the total cumulative output effect of a small unexpected monetary shock. The formula states that the cumulative output effect of a monetary shock depends on the ratio between two steady-state statistics: the kurtosis of the distribution of price changes K(∆p) and the average number of price changes per year N(∆p). Formally, given the labor supply elasticity 1/e and a small monetary shock d, the cumulative output effect M, namely the area under the output impulse response function, is given by
M =d K(∆p)/(6eN(∆p)) (1)
The impact of the frequency N(∆p) on the real output effect echoes a standard result in the “New Keynesian” literature: the stickier prices are, the more the inflation response is muted after a monetary policy shock, and the larger is the output response. It is precisely this result which motivated a large body of empirical literature on measuring the frequency of price changes.
The formula in (1) captures this in a stark fashion: halving the frequency of price change doubles the output response. The main novelty of the formula is that the effect of K(∆p) is equally important.
This formula explains the different results obtained by previous models, such as the examples listed at the beginning, by mapping them into a single observable statistics: the kurtosis. Surprisingly, the formula is able to explain model differences that have been obtained in very different sticky price models within a unified setup. In particular, this formula applies to the 2 main workhorse sticky price models, namely models where the decision rules for price setting are state dependent and models where they are time-dependent. The result suggest that the role of the specific microeconomic assumptions used to model sticky prices is completely summarized by the two observable statistics: K(∆p) and N(∆p) .
This result highlights the importance of measuring the cross-sectional kurtosis as well as the frequency of price changes to learn about the effectiveness of monetary policy. This task has led to new developments in estimating such moments using micro data, which are often affected by measurement errors and unobserved heterogeneity. Our work has produced new suggestions to handle those issues. A preliminary empirical analysis of the US and France datasets suggests the value of Kurtosis, and hence the effect of a monetary shock, is between that predicted by a Calvo and a menu cost model, and overall close to that predicted by a Taylor model. If one were to select a simple model matching the distribution of price changes, the Taylor model would fare well.
Our study of the temporary price changes also led to an improved understanding of the monetary transmission mechanism. We showed that the introduction of a 2-price plan in a standard menu cost environment generates a persistent reference price level and many short lived deviations from it, as seen in many datasets. We also showed that modeling temporary price changes substantially alters the real effect of monetary shock. In the continuous time model, the real effect of monetary shocks is inversely proportional to the number of plan changes, and independent of the number of price changes. Thus one can have a very modest amount of aggregate price response to a monetary shock and simultaneously have an arbitrarily large number of price changes. Our preferred exercise is that the net effect, over and above the standard menu cost model is to add some extra flexibility to the aggregate price level, and hence to have a smaller real effect relative to this benchmark.