ABSTRACT Dynamic stochastic general equilibrium (DSGE) models are a prominent tool for forecasting at central banks, and the competitive forecasting performance of these models relative to alternatives, including official forecasts, has been documented. When evaluating DSGE models on an absolute basis, however, we find that the benchmark estimated medium-scale DSGE model forecasts inflation and GDP growth very poorly, although statistical and judgmental forecasts do equally poorly. Our finding is the DSGE model analogue of the literature documenting the recent poor perfor-mance of macroeconomic forecasts relative to simple naive forecasts since the onset of the Great Moderation. Although this finding is broadly consistent with the DSGE model we employ—the model itself implies that especially under strong monetary policy, inflation deviations should be unpredictable—a “wrong ” model may also have the same implication. We therefore argue that forecasting ability during the Great Moderation is not a good metric by which to judge models.

We find that the answer is no, in an estimated DSGE model of the US economy in which exogenous movements in workers’ market power are not a major driver of observed economic fluctuations. If they are, the tension between the conflicting stabilization objectives of monetary policy increases, but the equilibrium under optimal policy changes little.

This paper estimates a two-country model with a global bank, using US and Euro Area (EA) data, and Bayesian methods. The estimated model matches key US and EA business cycle statistics. Empirically, a model version with a bank capital requirement outperforms a structure without such a constraint. A loan loss originating in one country triggers a global output reduction. Banking shocks matter more for EA macro variables than for US real activity. Banking shocks account for 2%-5 % of the unconditional variance of US GDP and for 4%-15 % of the variance of EA GDP. During the Great Recession (2007-09), banking shocks accounted for about 12-20 % of the fall in US and EA GDP, and for more than a third of the fall in EA investment and employment.

W hat are the sources of aggregate fluctuations? To answer this question, macroeconomists often rely on aggregate data and the representative agent framework, thereby abstracting from underlying heterogeneity in the economy. One common approach is to use aggregate productivity shocks, preference shocks, or more generally wedges on the optimality conditions of the representative agent to account for aggregate fluctuations. An obvious advantage of this approach is its simplicity, and it has, for example, been used to infer the relative importance of financial frictions as a driver of business cycles. 1 To evaluate the usefulness of this exercise, we take an off-the-shelf model with financial frictions and heterogeneity, and study the mapping from a credit crunch, modeled as a shock to collateral constraints, to simple aggregate efficiency, investment and labor wedges. We study three variants of this model that only differ in the form of underlying heterogeneity.

Abstract: This paper analyses the real-time forecasting performance of the New Keynesian DSGE model of Galí, Smets, and Wouters (2012) estimated on euro area data. It investigates to what extent forecasts of inflation, GDP growth and unemployment by professional forecast-ers improve the forecasting performance. We consider two approaches for conditioning on such information. Under the “noise ” approach, the mean professional forecasts are assumed to be noisy indicators of the rational expectations forecasts implied by the DSGE model. Under the “news ” approach, it is assumed that the forecasts reveal the presence of expected future structural shocks in line with those estimated over the past. The forecasts of the DSGE model are compared with those from a Bayesian VAR model and a random walk.

We study a model with heterogeneous producers that face collateral and cash in advance constraints. These two frictions give rise to a non-trivial financial market in a monetary economy. A tightening of the collateral constraint results in a credit-crunch generated recession. The model can suitable be used to study the effects on the main macroeconomic variables- and on welfare of each indi-vidual- of alternative monetary- and fiscal- policies following the credit crunch. The model reproduces several features of the recent financial crisis, like the per-sistent negative real interest rates, the prolonged period at the zero bound for the nominal interest rate, the collapse in investment and low inflation, in spite of the very large increases of liquidity adopted by the government. The policy implications are in sharp contrast with the prevalent view in most Central Banks, based on the New Keynesian explanation of the liquidity trap.

We investigate the macroeconomic consequences of fluctuations in the effectiveness of the labor market matching process with a focus on the Great Recession. We conduct our analysis in the context of an estimated medium-scale DSGE model with sticky prices and equilibrium search unemployment that features a shock to the matching effi ciency. We find that this shock is almost irrelevant for unemployment fluctuations in normal times. However, it plays a somewhat larger role during the Great Recession when it contributes to raise the actual unemployment rate by 1.25 percentage points and the natural rate by 2 percentage points. In 2010:Q3 the natural rate of unemployment is roughly equal to 8 percent, while the size of the unemployment gap is about 1 percentage point.

Abstract We build a general equilibrium model that features uninsurable idiosyncratic shocks, search frictions and an operative labor supply choice along the extensive margin. The model is calibrated to match the average levels of gross flows across the three labor market states: employment, unemployment, and non-participation. We use it to study the implications of two kinds of aggregate shocks for the cyclical behavior of labor market aggregates and flows: shocks to search frictions (the rates of job finding and job loss) and shocks to the return on the market activity (any factors affecting aggregate productivity). We find that both kinds of shocks are needed to explain the labor market data, and that an active labor supply channel is key. A model with friction shocks only, calibrated to match unemployment fluctuations, accounts for only a small fraction of employment fluctuations and has counterfactual cyclical predictions for participation.

We combine questions from the Michigan Survey about the future path of prices, interest rates, and unemployment to investigate whether U.S. households are aware of the so-called Taylor (1993) rule. For comparison, we perform the same analysis using questions from the Survey of Professional Forecasters. Our findings support the view that some households form their expectations about the future path of interest rates, inflation, and unemployment in a way that is consistent with Taylor-type rules. The extent to which this happens, however, does not appear to be uniform across income and education levels. In particular, we find evidence that the relationship between unemployment and interest rates is not properly understood by households in the lowest income quartile, and by those with no high school diploma. We also find evidence that the perceived effect of unemployment on interest rates is asymmetric, being relevant only for interest-rate decreases. Finally, we argue that the relationships we uncover can be given a causal interpretation.

This paper presents preliminary findings and is being distributed to economists and other interested readers solely to stimulate discussion and elicit comments. The views expressed in this paper are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors.