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The global financial crisis and the ensuing criticism of macroeconomics have inspired researchers to explore new modeling approaches. There are many new models that deliver improved estimates of the transmission of macroeconomic policies and aim to better integrate the financial sector in business cycle analysis. Policy making institutions need to compare available models of policy transmission and evaluate the impact and interaction of policy instruments in order to design effective policy strategies. This paper reviews the literature on model comparison and presents a new approach for comparative analysis. Its computational implementation enables individual researchers to conduct systematic model comparisons and policy evaluations easily and at low cost. This approach also contributes to improving reproducibility of computational research in macroeconomic modeling. Several applications serve to illustrate the usefulness of model comparison and the new tools in the area of monetary and fiscal policy. They include an analysis of the impact of parameter shifts on the effects of fiscal policy, a comparison of monetary policy transmission across model generations and a cross-country comparison of the impact of changes in central bank rates in the United States and the euro area. Furthermore, the paper includes a large-scale comparison of the dynamics and policy implications of different macro-financial models. The models considered account for financial accelerator effects in investment financing, credit and house price booms and a role for bank capital. A final exercise illustrates how these models can be used to assess the benefits of leaning against credit growth in monetary policy.
In the New-Keynesian model, optimal interest rate policy under uncertainty is formulated without reference to monetary aggregates as long as certain standard assumptions on the distributions of unobservables are satisfied. The model has been criticized for failing to explain common trends in money growth and inflation, and that therefore money should be used as a cross-check in policy formulation (see Lucas (2007)). We show that the New-Keynesian model can explain such trends if one allows for the possibility of persistent central bank misperceptions. Such misperceptions motivate the search for policies that include additional robustness checks. In earlier work, we proposed an interest rate rule that is near-optimal in normal times but includes a cross-check with monetary information. In case of unusual monetary trends, interest rates are adjusted. In this paper, we show in detail how to derive the appropriate magnitude of the interest rate adjustment following a significant cross-check with monetary information, when the New-Keynesian model is the central bank’s preferred model. The cross-check is shown to be effective in offsetting persistent deviations of inflation due to central bank misperceptions. Keywords: Monetary Policy, New-Keynesian Model, Money, Quantity Theory, European Central Bank, Policy Under Uncertainty
This paper reviews the rationale for quantitative easing when central bank policy rates reach near zero levels in light of recent announcements regarding direct asset purchases by the Bank of England, the Bank of Japan, the U.S. Federal Reserve and the European Central Bank. Empirical evidence from the previous period of quantitative easing in Japan between 2001 and 2006 is presented. During this earlier period the Bank of Japan was able to expand the monetary base very quickly and significantly. Quantitative easing translated into a greater and more lasting expansion of M1 relative to nominal GDP. Deflation subsided by 2005. As soon as inflation appeared to stabilize near a rate of zero, the Bank of Japan rapidly reduced the monetary base as a share of nominal income as it had announced in 2001. The Bank was able to exit from extensive quantitative easing within less than a year. Some implications for the current situation in Europe and the United States are discussed.
Research with Keynesian-style models has emphasized the importance of the output gap for policies aimed at controlling inflation while declaring monetary aggregates largely irrelevant. Critics, however, have argued that these models need to be modified to account for observed money growth and inflation trends, and that monetary trends may serve as a useful cross-check for monetary policy. We identify an important source of monetary trends in form of persistent central bank misperceptions regarding potential output. Simulations with historical output gap estimates indicate that such misperceptions may induce persistent errors in monetary policy and sustained trends in money growth and inflation. If interest rate prescriptions derived from Keynesian-style models are augmented with a cross-check against money-based estimates of trend inflation, inflation control is improved substantially.
The global financial crisis has lead to a renewed interest in discretionary fiscal stimulus. Advocates of discretionary measures emphasize that government spending can stimulate additional private spending — the so-called Keynesian multiplier effect. Thus, we investigate whether the discretionary spending announced by Euro area governments for 2009 and 2010 is likely to boost euro area GDP by more than one for one. Because of modeling uncertainty, it is essential that such policy evaluations be robust to alternative modeling assumptions and different parameterizations. Therefore, we use five different empirical macroeconomic models with Keynesian features such as price and wage rigidities to evaluate the impact of fiscal stimulus. Four of them suggest that the planned increase in government spending will reduce private spending for consumption and investment purposes significantly. If announced government expenditures are implemented with delay the initial effect on euro area GDP, when stimulus is most needed, may even be negative. Traditional Keynesian multiplier effects only arise in a model that ignores the forward-looking behavioral response of consumers and firms. Using a multi-country model, we find that spillovers between euro area countries are negligible or even negative, because direct demand effects are offset by the indirect effect of euro appreciation.
Recent evaluations of the fiscal stimulus packages recently enacted in the United States and Europe such as Cogan, Cwik, Taylor and Wieland (2009) and Cwik and Wieland (2009) suggest that the GDP effects will be modest due to crowding-out of private consumption and investment. Corsetti, Meier and Mueller (2009a,b) argue that spending shocks are typically followed by consolidations with substantive spending cuts, which enhance the short-run stimulus effect. This note investigates the implications of this argument for the estimated impact of recent stimulus packages and the case for discretionary fiscal policy.
In this paper we investigate the comparative properties of empirically-estimated monetary models of the U.S. economy. We make use of a new data base of models designed for such investigations. We focus on three representative models: the Christiano, Eichenbaum, Evans (2005) model, the Smets and Wouters (2007) model, and the Taylor (1993a) model. Although the three models differ in terms of structure, estimation method, sample period, and data vintage, we find surprisingly similar economic impacts of unanticipated changes in the federal funds rate. However, the optimal monetary policy responses to other sources of economic fluctuations are widely different in the different models. We show that simple optimal policy rules that respond to the growth rate of output and smooth the interest rate are not robust. In contrast, policy rules with no interest rate smoothing and no response to the growth rate, as distinct from the level, of output are more robust. Robustness can be improved further by optimizing rules with respect to the average loss across the three models.
Renewed interest in fiscal policy has increased the use of quantitative models to evaluate policy. Because of modeling uncertainty, it is essential that policy evaluations be robust to alternative assumptions. We find that models currently being used in practice to evaluate fiscal policy stimulus proposals are not robust. Government spending multipliers in an alternative empirically-estimated and widely-cited new Keynesian model are much smaller than in these old Keynesian models; the estimated stimulus is extremely small with GDP and employment effects only one-sixth as large.
This paper introduces adaptive learning and endogenous indexation in the New-Keynesian Phillips curve and studies disinflation under inflation targeting policies. The analysis is motivated by the disinflation performance of many inflation-targeting countries, in particular the gradual Chilean disinflation with temporary annual targets. At the start of the disinflation episode price-setting firms’ expect inflation to be highly persistent and opt for backward-looking indexation. As the central bank acts to bring inflation under control, price-setting firms revise their estimates of the degree of persistence. Such adaptive learning lowers the cost of disinflation. This reduction can be exploited by a gradual approach to disinflation. Firms that choose the rate for indexation also re-assess the likelihood that announced inflation targets determine steady-state inflation and adjust indexation of contracts accordingly. A strategy of announcing and pursuing short-term targets for inflation is found to influence the likelihood that firms switch from backward-looking indexation to the central bank’s targets. As firms abandon backward-looking indexation the costs of disinflation decline further. We show that an inflation targeting strategy that employs temporary targets can benefit from lower disinflation costs due to the reduction in backward-looking indexation.
Monetary policy analysts often rely on rules-of-thumb, such as the Taylor rule, to describe historical monetary policy decisions and to compare current policy to historical norms. Analysis along these lines also permits evaluation of episodes where policy may have deviated from a simple rule and examination of the reasons behind such deviations. One interesting question is whether such rules-of-thumb should draw on policymakers "forecasts of key variables such as inflation and unemployment or on observed outcomes. Importantly, deviations of the policy from the prescriptions of a Taylor rule that relies on outcomes may be due to systematic responses to information captured in policymakers" own projections. We investigate this proposition in the context of FOMC policy decisions over the past 20 years using publicly available FOMC projections from the biannual monetary policy reports to the Congress (Humphrey-Hawkins reports). Our results indicate that FOMC decisions can indeed be predominantly explained in terms of the FOMC´s own projections rather than observed outcomes. Thus, a forecast-based rule-of-thumb better characterizes FOMC decision-making. We also confirm that many of the apparent deviations of the federal funds rate from an outcome-based Taylor-style rule may be considered systematic responses to information contained in FOMC projections.