What is the relation between infrequent price adjustment and the dynamic response of the aggregate price level to monetary shocks? The answer to this question ranges from a one-to-one link (Calvo, 1983) to no connection whatsoever (Caplin and Spulber, 1987). The purpose of this paper is to provide a unified framework to understand the mechanisms behind this wide range of results. In doing so, we propose new interpretations of key results in this area, which in turn suggest the kind of Ss model that is likely to generate substantial price rigidity. The first result we revisit is Caplin and Spulber’s monetary neutrality model. We show that when price stickiness is measured in terms of the impulse response function, this result is not a consequence of aggregation, but is due instead to the absence of price-stickiness at the microeconomic level. We also show that the “selection effect,” according to which units that adjust their prices are those that benefit the most, is neither necessary nor sufficient to account for the higher aggregate flexibility of Ss-type models compared to Calvo models. Instead, the key concept is the contribution of the extensive margin of adjustment to the aggregate price response. The aggregate price level is more flexible than suggested by the microeconomic frequency of adjustment if and only if this term is positive.
Microeconomic flexibility is at the core of economic growth in modern market economies because it facilitates the process of creative-destruction, The main reason why this process is not infinitely fast, is the presence of adjustment costs, some of them technological, others institutional. Chief among the latter is labor market regulation. While few economists object to the hypothesis that labor market regulation hinders the process of creative-destruction, its empirical support is limited. In this paper we revisit this hypothesis, using a new sectoral panel for 60 countries and a methodology suitable for such a panel. We find that job security regulation clearly hampers the creative-destruction process, especially in countries where regulations are likely to be enforced. Moving from the 20th to the 80th percentile in job security, in countries with strong rule of law, cuts the annual speed of adjustment to shocks by a third while shaving off about one percent from annual productivity growth. The same movement has negligible effects in countries with weak rule of law.
Cooper and Willis (2003) is the latest in a sequence of criticisms of our methodology for estimating aggregate nonlinearities when microeconomic adjustment is lumpy. Their case is based on “reproducing” our main findings using artificial data generated by a model where microeconomic agents face quadratic adjustment costs. That is, they supposedly find our results where they should not be found. The three claims on which they base their case are incorrect. Their mistakes range from misinterpreting their own simulation results to failing to understand the context in which our procedures should be applied. They also claim that our approach assumes that employment decisions depend on the gap between the target and current level of unemployment. This is incorrect as well, since the ‘gap approach’ has been derived formally from at least as sophisticated microeconomic models as the one they present. On a more positive note, the correct interpretation of Cooper and Willis’s results shows that our procedures are surprisingly robust to significant departures from the assumptions made in our original derivations.
The dynamic response of aggregate variables to shocks is one of the central concerns of applied macroeconomics. The main measurement procedure for these dynamics consists of estimating an ARMA or VAR (VARs, for short). In non- or semi-structural approaches, the characterization of dynamics stops there. In other, more structural approaches, researcher try to uncover underlying adjustment cost parameters from the estimated VARs. Yet, in others, such as in RBC models, these estimates are used as the benchmark over which the success of the calibration exercise, and the need for further theorizing, is assessed. The main point of this paper is that when the microeconomic adjustment underlying the corresponding aggregates is lumpy, conventional VARs procedures are often inadequate for all of the above practices. In particular, the researcher will conclude that there is less persistence in the response of aggregate variables to aggregate shocks than there really is. Paradoxically, while idiosyncratic productivity and demand shocks smooth away microeconomic non-convexities and are often used as a justification for approximating aggregate dynamics with linear models, their presence exacerbate the bias. Since in practice idiosyncratic uncertainty is many times larger than aggregate uncertainty, we conclude that the problem of missing aggregate dynamics is prevalent in empirical and quantitative macroeconomic research.