We propose a macroeconomic model with a nonlinear Phillips curve that has a flat slope when inflationary pressures are subdued and steepens when inflationary pressures are elevated. The nonlinear Phillips curve in our model arises due to a quasi-kinked demand schedule for goods produced by firms. Our model can jointly account for the modest decline in inflation during the Great Recession and the surge in inflation during the Post-Covid period. Because our model implies a stronger transmission of shocks when inflation is high, it generates conditional heteroscedasticity in inflation and inflation risk. Hence, our model can generate more sizeable inflation surges due to cost-push and demand shocks than a standard linearized model. Finally, our model implies that the central bank faces a more severe trade-off between inflation and output stabilization when inflation is high.

A resolution of the missing deflation puzzle is proposed. Our resolution stresses the importance of nonlinearities in price- and wage-setting when the economy is exposed to large shocks. We show that a nonlinear macroeconomic model with real rigidities resolves the missing deflation puzzle, while a linearized version of the same underlying nonlinear model fails to do so. In addition, our nonlinear model reproduces the skewness of inflation and other macroeconomic variables observed in post-war U.S. data. All told, our results caution against the common practice of using linearized models to study inflation and output dynamics.

Recent financial crises have prompted the interest in understanding how banking globalization interacts with domestic institutions in shaping foreign shocks’ transmission. This paper uses regional banking data from Brazil to show that a foreign funding shock to banks negatively affects lending by their regional branches. This effect increases in the presence of frictions in internal capital markets, which affect branches’ capacity to access funding from other regions via intra-bank linkages. These results also matter on an aggregate level, as municipality-level credit and job flows drop in exposed regions. Policies aiming to reduce the fragmented structure of regional banking markets could moderate the propagation of foreign shocks.

The unexpected shock represented by the COVID-19 pandemic illustrates the importance of building robust macroprudential frameworks to increase countries’ resilience against sudden disruptions in financial markets. By now, a widespread opinion among commentators and policy makers is that the macroprudential frameworks that were implemented over the past decades were effective in moderating market stress, a view supported by ample evidence on the effectiveness of macroprudential policies.

Asset prices are a valuable source of information about financial market participants' expectations about key macroeconomic variables. However, the presence of time-varying risk premia requires an adjustment of market prices to obtain the market's rational assessment of future price and policy developments. This paper reviews empirical approaches for recovering market-based expectations. It starts by laying out the two canonical modeling frameworks that form the backbone for estimating risk premia and highlights the proliferation of risk pricing factors that result in a wide range of different asset-price-based expectation measures. It then describes a key methodological innovation to evaluate the empirical plausibility of risk premium estimates and to identify the most accurate market-based expectation measure. The usefulness of this general approach is illustrated for price expectations in the global oil market. Then, the paper provides an overview of the body of empirical evidence for monetary policy and inflation expectations with a special emphasis on market-specific characteristics that complicate the quest for the best possible market-based expectation measure. Finally, it discusses a number of economic applications where market expectations play a key role for evaluating economic models, guiding policy analysis, and deriving shock measures.

We argue that wage inertia plays a pivotal role in allowing empirically plausible variants of the standard search and matching model to account for the large countercyclical response of unemployment to shocks.

This paper provides evidence for the propagation of idiosyncratic mortgage supply shocks to the macroeconomy. Based on micro-level data from the Home Mortgage Disclosure Act for the 1990-2016 period, our results suggest that lender-specific mortgage supply shocks affect aggregate mortgage, house price, and employment dynamics at the regional level. The larger the idiosyncratic shocks to newly issued mortgages, the stronger are mortgage, house price, and employment growth. While shocks at the level of shadow banks significantly affect mortgage and house price dynamics, too, they do not matter much for employment.

Can a model with limited labor market insurance explain standard macro and labor market data jointly? We construct a monetary model in which: i) the unemployed are worse off than the employed, i.e. unemployment is involuntary and ii) the labor force participation rate varies with the business cycle. To illustrate key features of our model, we start with the simplest possible framework. We then integrate the model into a medium-sized DSGE model and show that the resulting model does as well as existing models at accounting for the response of standard macroeconomic variables to monetary policy shocks and two technology shocks. In addition, the model does well at accounting for the response of the labor force and unemployment rate to these three shocks.

The paper analyzes how actual monetary policy changed following the official adoption of inflation targeting in the Czech Republic, Hungary, and Poland and how it affected the volatilities of important macroeconomic variables in the years thereafter. To disentangle the effects of the policy shift from exogenous changes in the volatilities of these variables, a Markov-switching dynamic stochastic general equilibrium model is estimated that allows for regime switches in the policy parameters and the volatilities of shocks hitting the economies. Whereas estimation results reveal periods of high and low volatility for all three economies, the presence of different policy regimes is supported by the underlying data for the Czech Republic and Poland, only. In both economies, monetary policy switched from weak and unsystematic to strong and systematic responses to inflation dynamics. Simulation results suggest that the policy shifts of both central banks successfully reduced inflation volatility in the following years. The observed reduction in output volatility, on the other hand, is attributed more to a reduction in the size of external shocks.