FABIO MILANI - Research
FABIO MILANI - ResearchRecent Working Papers
"The Effects of Monetary Policy "News" and "Surprises" ",(with John Treadwell)
University of California, Irvine, July 2009. (abstract)
"Has Globalization Transformed U.S.
Macroeconomic Dynamics?",
University of California, Irvine, June 2009. (abstract)
"The Effect of Global Output on U.S. Inflation and Inflation
Expectations: A Structural Estimation",
University of California, Irvine, April 2009. (abstract)
"Global Slack and Domestic Inflation Rates: A Structural Investigation for G-7 Countries",
University of California, Irvine, February 2009. (abstract)
"Learning About the Interdependence Between the Macroeconomy and the Stock Market",
University of California, Irvine, May 2008. (abstract)
"The Impact of Foreign Stock Markets on
Macroeconomic Dynamics in Open Economies: a Structural Estimation",
(coming soon), July, 2008. (abstract)
"Learning and Time-Varying Macroeconomic Volatility", (under revision)
University of California, Irvine, May 2007. (abstract)
"Learning and the Evolution of the Fed's Inflation Target"
University of California, Irvine, July 2009. (abstract)
"Adaptive Learning and Inflation
Persistence",
Princeton University, June 2004. This version: February 2005. (abstract)
Publications
"Expectations, Learning, and the Changing Relationship between Oil Prices and the Macroeconomy",
Energy Economics, forthcoming, 2009. (abstract)
"Has Global Slack Become More Important than Domestic Slack in Determining U.S. Inflation?",
Economics Letters, Volume 102, Issue 3, March 2009, pages 147-151. (abstract)
"Political Business Cycles in the New Keynesian Model",
Economic Inquiry, forthcoming, 2009. (abstract)
"Adaptive Learning and Macroeconomic Inertia in the Euro Area",
Journal of Common Market Studies, forthcoming, May 2009. (abstract)
"Learning, Monetary Policy Rules, and Macroeconomic Stability",
Journal of Economic Dynamics and Control, Vol. 32, No. 10, October 2008, pages 3148-3165. (abstract)
"Monetary Policy with a Wider Information Set: a Bayesian Model
Averaging Approach",
Scottish Journal of Political Economy, Vol. 55, No. 1, February, 2008. (abstract)
"Expectations, Learning and Macroeconomic Persistence",
Journal of Monetary Economics, Volume 54, Issue 7, Pages 2065-2082, October 2007. (abstract)
"Econometric Issues in DSGE Models", (with Dale Poirier)
Comment on "Bayesian Analysis of DSGE Models" by An and Schorfheide ,
Econometric Reviews, Volume 26, Issue 2 - 4, March 2007, pages 201 - 204.
"A Bayesian DSGE Model with Infinite-Horizon Learning:
Do "Mechanical" Sources of Persistence Become Superfluous?",
International Journal of Central Banking, Iss. 6, September 2006. (abstract)
"Structural Factor-Augmented VARs (SFAVARs) and the Effects of Monetary Policy",
(with Francesco Belviso), Topics in Macroeconomics, Vol. 6, Iss. 3, 2006. (abstract)
"Parameter Instability, Model Uncertainty and the Choice of Monetary
Policy",
(with Carlo A.
Favero), Topics in
Macroeconomics, Vol. 5, Iss. 1, 2005.
Work in progress
"Estimating and Comparing NK Models with Adaptive Learning", in progress.
Comments & Discussions
Discussion on "Evaluating An Estimated New Keynesian Small Open Economy Model",
by M. Adolfson, S. Laséen, J. Lindé, and M. Villani, August 2006.
Discussion on "The Lucas Critique and the Stability of Empirical Models",
by Thomas Lubik and Paolo Surico, October 2006.
Discussion on "Monetary Policy with Model Uncertainty: Distribution Forecast Targeting",
by Lars Svensson and Noah Williams, January 2007.
Discussion on "Revealing the Secrets of the Temple: the Value of Publishing Central Bank's Forecasts",
by Glenn Rudebusch and John Williams, June 2007.
"HAS GLOBALIZATION TRANSFORMED U.S. MACROECONOMIC DYNAMICS?"
Fabio Milani, June, 2009.
Abstract
| This paper estimates a structural New
Keynesian model to test whether globalization has changed the
behavior of U.S. macroeconomic variables. Several key coefficients
in the model - such as the slopes of the Phillips and IS curves,
the sensitivities of domestic inflation and output to "global"
output, and so forth - are allowed in the estimation to depend on
the extent of globalization (modeled as the changing degree of
openness to trade of the economy), and, therefore, they become
time-varying.
The empirical results indicate that globalization can explain only a small part of the reduction in the slope of the Phillips curve. The sensitivity of U.S. inflation to global measures of output may have increased over the sample, but it remains very small. The changes in the IS curve caused by globalization are similarly modest. Globalization does not seem to have led to an attenuation in the effects of monetary policy shocks. The nested closed economy specification still appears to provide a substantially better fit of U.S. data than various open economy specifications with time-varying degrees of openness. Some time variation in the model coefficients over the post-war sample exists, particularly in the volatilities of the shocks, but it is unlikely to be related to globalization. Keywords: Globalization and Inflation, Global Slack, Openness, New Keynesian
model, Expectations and Adaptive Learning, DSGE model with
Time-Varying Coefficients.
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"THE EFFECT OF GLOBAL OUTPUT ON U.S. INFLATION AND INFLATION
EXPECTATIONS: A STRUCTURAL ESTIMATION"
Fabio Milani, April, 2009.
Abstract
| Recent research has suggested that
globalization may have transformed the U.S. Phillips curve by making
inflation a function of global, rather than domestic, economic
activity.
This paper tests this view by estimating a structural model for the U.S., which incorporates a role of global output on the domestic demand and supply relations and on the formation of expectations. Expectations are modeled as near-rational and economic agents are allowed to learn about the economy's coefficients over time. The estimation reveals small and negative coefficients for the sensitivity of inflation to global output; moreover, the fit of the model improves when global output is excluded from the Phillips curve. Therefore, the evidence does not support altering the traditional closed-economy Phillips curve to include global output. The data suggest, instead, that global output may play an indirect role through the determination of domestic output. But the overall impact of global economic conditions on U.S. inflation remains negligible. Keywords: Globalization; Global Output; Inflation Dynamics; New Keynesian
Phillips Curve; Global Slack Hypothesis; Constant-Gain Learning.
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"GLOBAL SLACK AND DOMESTIC INFLATION RATES: A Structural Investigation for G-7 Countries"
Fabio Milani, February, 2009.
Abstract
| Recent papers have argued that one
implication of globalization is that domestic inflation rates may
have now become more a function of ``global", rather than domestic,
economic conditions, as postulated by closed-economy Phillips
curves.
This paper aims to assess the empirical importance of global output in determining domestic inflation rates by estimating a structural model for a sample of G-7 economies. The model can capture the potential effects of global output fluctuations on both the aggregate supply and the aggregate demand relations in the economy and it is estimated using full-information Bayesian methods. The empirical results reveal a significant effect of global output on aggregate demand in most countries. Through this channel, global economic conditions can indirectly affect inflation. The results, instead, do not seem to provide evidence in favor of altering domestic Phillips curves to include global slack as an additional driving variable for inflation. Keywords: Globalization; Global Slack; Inflation Dynamics; Phillips Curve;
Bayesian Estimation.
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"LEARNING ABOUT THE INTERDEPENDENCE BETWEEN THE MACROECONOMY AND THE STOCK MARKET"
Fabio Milani, May, 2008.
Abstract
| How strong is the interdependence
between the macroeconomy and the stock market?
This paper estimates a New Keynesian general equilibrium model, which includes a wealth effect from asset price fluctuations to consumption, to assess the quantitative importance of interactions among the stock market, macroeconomic variables, and monetary policy. The paper relaxes the assumption of rational expectations and assumes that economic agents learn over time and form near-rational expectations from their perceived model of the economy. The stock market, therefore, affects the economy through two channels: through a traditional ``wealth effect" and through its impact on agents' expectations. Monetary policy decisions also affect and are potentially affected by the stock market. The empirical results show that the direct wealth effect is modest, but asset price fluctuations have had important effects on output expectations. Shocks in the stock market can account for a large portion of output fluctuations. The effect on expectations, however, has declined over time. Keywords: Stock Market, Wealth Channel, Monetary Policy,
Constant-Gain Learning, Bayesian Estimation, Expectations.
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"POLITICAL BUSINESS CYCLES IN THE NEW KEYNESIAN MODEL"
Fabio Milani, October, 2007.
Abstract
| This paper tests various Political Business Cycle theories in a New
Keynesian model with a monetary and fiscal policy mix. All the
policy coefficients, the target levels of inflation and the budget
deficit, the firms' frequency of price setting, and the standard
deviations of the structural shocks are allowed to depend on
`political' regimes: a pre-election vs. post-election regime, a
regime that depends on whether the President (or the Fed Chairman)
is a Democrat or a Republican, and a regime under which the
President and the Fed Chairman share party affiliation in
pre-election quarters or not.
The model is estimated using full-information Bayesian methods. The assumption of rational expectations is relaxed: economic agents can learn about the effect of political variables over time. The results provide evidence that several coefficients depend on political variables. The best-fitting specification is one that allows coefficients to depend on a pre-election vs. non-election regime. Monetary policy becomes considerably more inertial before elections and fiscal policy deviations from a simple rule are more common. The results overall support the view of an independent Fed that avoids taking policy decisions right before elections. There is some evidence, however, that policies become more expansionary before elections, but this evidence seems to disappear in the post-1985 sample. The estimates also indicate that firms similarly delay their price-setting decisions until after the upcoming Presidential election. Keywords: Political
Business Cycles, Opportunistic Cycles, Partisan Cycles, Monetary and
Fiscal Policy, Adaptive Learning, Bayesian Estimation.
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"LEARNING AND TIME-VARYING MACROECONOMIC VOLATILITY"
Fabio Milani, May, 2007.
Abstract
| This paper presents a DSGE model in which agents' learning about the economy can endogenously generate time-varying macroeconomic volatility.
Economic agents use simple models to form expectations and need to learn the relevant parameters. Their gain coefficient
is endogenous and is adjusted according to past forecast errors.
The model is estimated using likelihood-based Bayesian methods. The endogenous gain is jointly estimated with the structural parameters of the system. The estimation results show that private agents appear to have often switched to constant-gain learning, with a high constant gain, during most of the 1970s and until the early 1980s, while reverting to a decreasing gain later on. As a result, the model can generate a pattern of volatility, which is increasing in the 1970s and falling in the second half of the sample, with a decline that can roughly match the magnitude of the "Great Moderation". The paper also documents how a failure to incorporate learning into the estimation may lead econometricians to spuriously find time-varying volatility in the exogenous shocks, even when these have constant variance by construction. Keywords: adaptive learning, constant gain, monetary policy, macroeconomic
volatility, inflation dynamics.
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"LEARNING, MONETARY POLICY RULES, AND MACROECONOMIC STABILITY"
Fabio Milani, April, 2005.
Abstract
| This paper estimates a DSGE model with learning to reexamine the evidence on time variation in post-war U.S. monetary policy. Several papers document a regime switch, by showing that policy went from `passive' and destabilizing in the pre-1979 period to `active' and stabilizing in the following decades. These papers typically work with DSGE models with rational expectations.
This paper relaxes the assumption of rational expectations and it allows for learning instead. Economic agents form expectations from simple models and update the parameters through constant-gain learning. I estimate the model by Bayesian methods. The constant gain coefficient is jointly estimated with the structural and policy parameters of the system. I find that the feedback coefficient to inflation was well above 1 also in the 1960s and 1970s and therefore policy was not leading to macroeconomic instability. The results reconcile the evidence from DSGE models with what obtained by time-varying VAR studies, which typically find only modest changes in policy coefficients over the post-war sample. Keywords: monetary policy, new Keynesian DSGE model, constant-gain learning, expectations, Bayesian estimation, macroeconomic instability.
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"A BAYESIAN DSGE MODEL WITH INFINITE_HORIZON LEARNING:
DO "MECHANICAL" SOURCES OF PERSISTENCE BECOME SUPERFLUOUS?"
Fabio Milani,
International Journal of Central Banking, Iss. 6, September 2006.
Abstract
| This paper estimates a monetary DSGE model with learning introduced from the primitive assumptions. The model nests infinite-horizon learning and features, such as habit formation in consumption and inflation indexation, that are essential for the model fit under rational expectations.
I estimate the DSGE model by Bayesian methods, obtaining estimates of the main learning parameter, the constant gain, jointly with the deep parameters of the economy. The results show that relaxing the assumption of rational expectations in favor of learning may render mechanical sources of persistence superfluous. In particular, learning appears a crucial determinant of inflation inertia. Keywords: Infinite-Horizon Learning, DSGE model, Bayesian Estimation, Non-Rational Expectations, Inflation Persistence, Habit Formation.
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"EXPECTATIONS, LEARNING AND MACROECONOMIC PERSISTENCE"
, click here for (shorter version)
Fabio Milani, November 2004.
Abstract
| This paper presents an estimated model with learning and provides evidence that learning can improve the fit of popular monetary DSGE models and endogenously generate realistic levels of persistence. The standard rational expectations specification is nested in the model as a limiting case. The paper starts with an agnostic view, developing a model that nests learning and some of the structural sources of persistence, such as habit formation in consumption and inflation indexation, that are typically needed in monetary models with rational expectations to match the persistence of macroeconomic variables. I estimate the model by likelihood-based Bayesian methods, which allow the estimation of agents' beliefs and constant-gain coefficient jointly with the 'deep' parameters of the economy. The empirical results show that when learning replaces fully rational expectations, the estimated degrees of habits and indexation drop to zero. This finding suggests that persistence arises in the model economy mainly from expectations and learning. The posterior model probabilities show that the specification with learning fits significantly better than does the specification with rational expectations. Finally, if learning rather than mechanical sources of persistence provides a more appropriate representation of the economy, the implied optimal policy will be different. The policymaker will also incur substantial costs from misspecifying private expectations formation. Keywords: persistence, constant-gain learning, expectations, habit formation in consumption, inflation inertia, Phillips curve, Bayesian econometrics, New-Keynesian model, gain estimation.
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"ADAPTIVE LEARNING AND INFLATION PERSISTENCE"
Fabio Milani, March, 2004.
This draft: February 25, 2005.
Abstract
| What generates persistence in inflation? Is inflation persistence structural? This paper investigates learning as a potential source of persistence in inflation. The paper focuses on the price-setting problem of firms and presents a model that nests structural sources of persistence (indexation) and learning. Indexation is typically necessary under rational expectations to match the inertia in the data and to improve the fit of estimated New Keynesian Phillips curves. The empirical results show that when learning replaces the assumption of fully rational expectations, structural sources of persistence in inflation, such as indexation, become unsupported by the data. The results suggest learning behavior as the main source of persistence in inflation. This finding has implications for the optimal monetary policy. The paper finally shows how one's results can heavily depend on the assumed gain coefficient. It illustrates how the estimated persistence and the model fit vary across the whole range of constant gain values. The paper derives the best-fitting constant gains in the sample and shows that the learning speed has substantially changed over time. Keywords: adaptive learning, inflation persistence, sticky prices, best-fitting constant gain, learning speed, expectations.
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"STRUCTURAL FACTOR-AUGMENTED VAR (SFAVAR) AND THE EFFECTS OF MONETARY POLICY"
Francesco Belviso and Fabio Milani, First version: January, 2003.
Published in:Topics in Macroeconomics, Vol. 6, Iss. 3, 2006.
Abstract
| Factor-augmented VARs (FAVARs) have combined standard VARs with factor analysis to exploit large data sets in the study of monetary policy. FAVARs enjoy a number of advantages over VARs: they allow a better identification of the monetary policy shock; they can avoid the use of a single variable to proxy theoretical constructs, such as the output gap; they allow researchers to compute impulse responses for hundreds of variables. Their shortcoming, however, is that the factors are not identified and, therefore, lack any economic interpretation.
This paper seeks to provide an interpretation to the factors. We propose a novel Structural Factor-Augmented VAR (SFAVAR) model, where the factors have a clear meaning: "Real Activity" factor, "Price Pressures" factor, "Financial Market" factor, "Credit Conditions" factor, "Expectations" factor, etc. The paper employs a Bayesian approach to extract the factors and jointly estimate the model. This framework is then suited to study the effects on a wide range of macroeconomic variables of monetary policy and non-policy shocks. Keywords: VAR, Dynamic Factors, Monetary Policy, Structural FAVAR.
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"MONETARY POLICY WITH A WIDER INFORMATION SET: A BAYESIAN MODEL AVERAGING APPROACH"
Fabio Milani, August 2002 (Revised December 2003).
Abstract
| Monetary policy has been usually analyzed in the context of small macroeconomic models, where central banks are allowed to exploit a limited amount of information. Under these frameworks, researchers typically derive the optimality of aggressive monetary rules, contrasting with the observed policy conservatism and interest rate smoothing.
This paper allows the central bank to exploit a wider information set, while taking into account the associated model uncertainty, by employing Bayesian Model Averaging with Markov Chain Model Composition (MC³). In this enriched environment, we derive the optimality of smoother and more cautious policy rates, together with clear gains in macroeconomic efficiency.
Keywords: Bayesian model averaging, leading indicators, model uncertainty, optimal monetary policy, interest rate smoothing..
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"PARAMETER INSTABILITY, MODEL UNCERTAINTY AND THE CHOICE OF MONETARY POLICY"
Carlo Favero and Fabio Milani,
IGIER Working Paper n.196, May 2001, and CEPR Discussion Paper No. 4909, February 2005.
Published in:Topics in Macroeconomics, Vol. 5, Iss. 1, 2005.
Final version: February 2005.
Abstract
| This paper starts from the observation that parameter instability and model uncertainty are relevant problems for the analysis of monetary policy in small macroeconomic models.
We propose to deal with these two problems by implementing a novel "thick recursive modelling" approach. At each point in time we estimate all models generated by the combinations of a base-set of k observable regressors for aggregate demand and supply.
We compute optimal monetary policies for all possible models and consider alternative ways of summarizing their distribution. Our main results show that thick recursive modelling delivers optimal policy rates that track the observed policy rates better than the optimal policy rates obtained under a constant parameter specification with no role for model uncertainty.
Keywords: model uncertainty, parameter instability, optimal monetary policy.
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Comments are welcome.
to be continued...