This paper develops a tractable version of the Lucas and Prescott (1974) search model. Each of a continuum of industries produces a heterogeneous good using a production technology that is continually hit by idiosyncratic shocks. In response to adverse shocks, some workers search for new industries while others are rest unemployed, waiting for their industry's condition to improve. We obtain closed-form expressions for key aggregate variables and use them to evaluate the model's quantitative predictions for unemployment and wages. Both search and rest unemployment are important for understanding the behavior of wages at the industry level.

We measure the cost of consumption fluctuations using an approach that does not require the specification of preferences and instead uses asset prices. We measure the marginal cost of consumption fluctuations, the per unit benefit of a marginal reduction in consumption fluctuations expressed as a percentage of lifetime consumption. We find that the gains from eliminating all consumption uncertainty are very large. However, for consumption fluctuations corresponding to business cycle frequencies, we estimate the marginal cost to be between 0.08 percent and 0.49 percent of lifetime consumption.

We propose an analytical method to analyze the propagation of an aggregate shock in a broad class of sticky‐price models. The method is based on the eigenvalue‐eigenfunction representation of the dynamics of the cross‐sectional distribution of firms' desired adjustments. A key novelty is that we can approximate the whole profile of the impulse response for any moment of interest in response to an aggregate shock (any displacement of the invariant distribution). We present several applications for an economy with low inflation and idiosyncratic shocks. We show that the shape of the impulse response of the canonical menu cost model is fully encoded by a single parameter, just like the Calvo model, although the shapes are very different. A model with a quadratic hazard function, arguably a good fit to the micro data on price setting, yields an impulse response that is close to the canonical menu cost model.

We document cash management patterns for households that are at odds with the predictions of deterministic inventory models that abstract from pre-cautionary motives. We extend the Baumol-Tobin cash inventory model to a dynamic environment that allows for the possibility of withdrawing cash at random times at a low cost. This modification introduces a precautionary motive for holding cash and naturally captures developments in withdrawal technology, such as the increasing diffusion of bank branches and ATM termi-nals. We characterize the solution of the model and show that qualitatively it is able to reproduce the empirical patterns. Estimating the structural pa-rameters we show that the model quantitatively accounts for key features of the data. The estimates are used to quantify the expenditure and interest rate elasticity of money demand, the impact of financial innovation on money demand, the welfare cost of inflation, the gains of disinflation and the benefit of ATM ownership.

We analyze the effects of money injections on interest rates and exchange rates when agents must pay a Baumol‐Tobin‐style fixed cost to exchange bonds and money. Asset markets are endogenously segmented because this fixed cost leads agents to trade bonds and money infrequently. When the government injects money through an open market operation, only those agents that are currently trading absorb these injections. Through their impact on these agents’ consumption, these money injections affect real interest rates and real exchange rates. The model generates the observed negative relation between expected inflation and real interest rates as well as persistent liquidity effects in interest rates and volatile and persistent exchange rates.

We study models where prices respond slowly to shocks because firms are rationally inattentive. Producers must pay a cost to observe the determinants of the current profit maximizing price, and hence observe them infrequently. To generate large real effects of monetary shocks in such a model the time between observations must be long and/or highly volatile. Previous work on rational inattentiveness has allowed for observation intervals that are either constant-but-long (e.g. Caballero, 1989 or Reis, 2006) or volatile-but-short (e.g. Reis's, 2006 example where observation costs are negligible), but not both. In these models, the real effects of monetary policy are small for realistic values of the duration between observations. We show that non-negligible observation costs produce both of these effects: intervals between observations are infrequent and volatile. This generates large real effects of monetary policy for realistic values of the average time between observations.

We study the propagation of monetary shocks in a sticky‐price general equilibrium economy where the firms' pricing strategy features a complementarity with the decisions of other firms. In a dynamic equilibrium, the firm's price‐setting decisions depend on aggregates, which in turn depend on the firms' decisions. We cast this fixed‐point problem as a Mean Field Game and prove several analytic results. We establish existence and uniqueness of the equilibrium and characterize the impulse response function (IRF) of output following an aggregate shock. We prove that strategic complementarities make the IRF larger at each horizon. We establish that complementarities may give rise to an IRF with a hump‐shaped profile. As the complementarity becomes large enough, the IRF diverges, and at a critical point there is no equilibrium. Finally, we show that the amplification effect of the strategic interactions is similar across models: the Calvo model and the Golosov–Lucas model display a comparable amplification, in spite of the fact that the non‐neutrality in Calvo is much larger.

Abstract In a broad class of sticky-price models, the non-neutrality of nominal shocks is captured by a simple sufficient statistic: the ratio of the kurtosis of the price change distribution over the frequency of price changes. We test the sufficient statistic proposition using data for a large sample of products representative of the French economy. We first extend the theory to allow for empirically relevant monetary shocks with a transitory predictable component. We then use the microdata to measure kurtosis and frequency for about 120 producer price indices industries and 220 consumer price indices categories. We use a Factor-Augmented Vector Autoregressive (FAVAR) model to measure the industries’ response to monetary shocks, under alternative identification schemes. The estimated degree of non-neutrality correlates with the kurtosis and the frequency consistently with the predictions of the theory. Several robustness checks are discussed.