Combining multivariate density forecasts using predictive criteria

This paper combines multivariate density forecasts of output growth, inflationand interest rates from a suite of models. An out-of-sample weighting scheme based onthe predictive likelihood as proposed by Eklund and Karlsson (2005) and Andersson andKarlsson (2007) is used to combine the models. Three classes of models are considered: aBayesian vector autoregression (BVAR), a factor-augmented vector autoregression (FAVAR)and a medium-scale dynamic stochastic general equilibrium (DSGE) model. Using Australiandata, we find that, at short forecast horizons, the Bayesian VAR model is assignedthe most weight, while at intermediate and longer horizons the factor model is preferred.The DSGE model is assigned little weight at all horizons, a result that can be attributedto the DSGE model producing density forecasts that are very wide when compared withthe actual distribution of observations. While a density forecast evaluation exercise revealslittle formal evidence that the optimally combined densities are superior to those from thebest-performing individual model, or a simple equal-weighting scheme, this may be a resultof the short sample available.

The persistence of inflation in OECD countries: A fractionally integrated approach

The statistical properties of inflation and, in particular, its degree of persistence and stability over time is a subject of intense debate and no consensus has been achieved yet. The goal of this paper is to analyze this controversy using a general approach, with the aim of providing a plausible explanation for the existing contradictory results. We consider the inflation rates of 21 OECD countries which are modelled as fractionally integrated (FI) processes. First, we show analytically that FI can appear in inflation rates after aggregating individual prices from firms that face different costs of adjusting their prices. Then, we provide robust empirical evidence supporting the FI hypothesis using both classical and Bayesian techniques. Next, we estimate impulse response functions and other scalar measures of persistence, achieving an accurate picture of this property and its variation across countries. It is shown that the application of some popular tools for measuring persistence, such as the sum of the AR coefficients, could lead to erroneous conclusions if fractional integration is present. Finally, we explore the existence of changes in inflation inertia using a novel approach. We conclude that the persistence of inflation is very high (although non-permanent) in most post-industrial countries and that it has remained basically unchanged over the last four decades.

How much structure in empirical models?

This chapter highlights the problems that structural methods and SVAR approaches have when estimating DSGE models and examining their ability to capture important features of the data. We show that structural methods are subject to severe identification problems due, in large part, to the nature of DSGE models. The problems can be patched up in a number of ways but solved only if DSGEs are completely reparametrized or respecified. The potential misspecification of the structural relationships give Bayesian methods an hedge over classical ones in structural estimation. SVAR approaches may face invertibility problems but simple diagnostics can help to detect and remedy these problems. A pragmatic empirical approach ought to use the flexibility of SVARs against potential misspecificationof the structural relationships but must firmly tie SVARs to the class of DSGE models which could have have generated the data.

The evolution of conventions under incomplete information

We formulate an evolutionary learning process in the spirit ofYoung (1993a) for games of incomplete information. The process involves trembles. For many games, if the amount of trembling is small, play will be in accordance with the games' (semi-strict) Bayesian equilibria most of the time. This supports the notion of Bayesian equilibrium. Further, often play will most of the time be in accordance with exactly one Bayesian equilibrium. This gives a selection among the Bayesian equilibria. For two specific games of economic interest wecharacterize this selection. The first is an extension to incomplete information of the prototype strategic conflict known as Chicken. The second is an incomplete information bilateral monopoly, which is also an extension to incompleteinformation of Nash's demand game, or a simple version ofthe so-called sealed bid double auction. For both gamesselection by evolutionary learning is in favor of Bayesianequilibria where some types of players fail to coordinate, such that the outcome is inefficient.

Statistics in archaeology: New directions

Connections between Statistics and Archaeology have always appeared veryfruitful. The objective of this paper is to offer an outlook of somestatistical techniques that are being developed in the most recentyears and that can be of interest for archaeologists in the short run.

Improved estimation of the covariance matrix of stock returns with an application to portofolio selection

This paper proposes to estimate the covariance matrix of stock returnsby an optimally weighted average of two existing estimators: the samplecovariance matrix and single-index covariance matrix. This method isgenerally known as shrinkage, and it is standard in decision theory andin empirical Bayesian statistics. Our shrinkage estimator can be seenas a way to account for extra-market covariance without having to specifyan arbitrary multi-factor structure. For NYSE and AMEX stock returns from1972 to 1995, it can be used to select portfolios with significantly lowerout-of-sample variance than a set of existing estimators, includingmulti-factor models.

Estimating multi-country VAR models

This paper describes a methodology to estimate the coefficients, to test specification hypothesesand to conduct policy exercises in multi-country VAR models with cross unit interdependencies, unit specific dynamics and time variations in the coefficients. The framework of analysis is Bayesian: a prior flexibly reduces the dimensionality of the model and puts structure on the time variations; MCMC methods are used to obtain posterior distributions; and marginal likelihoods to check the fit of various specifications. Impulse responses and conditional forecasts are obtained with the output of MCMC routine. The transmission of certain shocks across countries is analyzed.

A structural model of Australia as a small open economy

This paper sets up and estimates a structuralmodel of Australia as a small open economyusing Bayesian techniques. Unlike other recentstudies, the paper shows that a small microfoundedmodel can capture the open economydimensions quite well. Specifically, the modelattributes a substantial fraction of the volatilityof domestic output and inflation to foreigndisturbances, close to what is suggested by unrestrictedVAR studies. The paper also investigatesthe effects of various exogenous shockson the Australian economy.

ClubMed? Cyclical fluctuations in the Mediterranean basin

We investigate macroeconomic fluctuations in the Mediterranean basin, their similarities and convergence. A model with four indicators, roughly covering theWest, the East and the Middle East and the North Africa portions of theMediterranean, characterizes well the historical experience since the early 1980.Idiosyncratic causes still dominate domestic cyclical fluctuations in many countries. Convergence and divergence coexist are local and transitory. The cyclicaloutlook for the next few years is rosier for the East than for the West.

Informational matching

This paper analyzes the problem of matching heterogeneous agents in aBayesian learning model. One agent gives a noisy signal to another agent,who is responsible for learning. If production has a strong informationalcomponent, a phase of cross-matching occurs, so that agents of low knowledgecatch up with those of higher one. It is shown that:(i) a greater informational component in production makes cross-matchingmore likely;(ii) as the new technology is mastered, production becomes relatively morephysical and less informational;(iii) a greater dispersion of the ability to learn and transfer informationmakes self-matching more likely; and(iv) self-matching leads to more self-matching, whereas cross-matching canmake less productive agents overtake more productive ones.

What explains the Great Moderation in the US? A structural analysis

This paper investigates what has caused output and inflation volatility to fall in the USusing a small scale structural model using Bayesian techniques and rolling samples. Thereare instabilities in the posterior of the parameters describing the private sector, the policyrule and the standard deviation of the shocks. Results are robust to the specification ofthe policy rule. Changes in the parameters describing the private sector are the largest,but those of the policy rule and the covariance matrix of the shocks explain the changes most.

The poor stay poor: Non-convergence across countries and regions

We study the issue of income convergence across countries and regions witha Bayesian estimator which allows us to use information in an efficient andflexible way. We argue that the very slow convergence rates to a commonlevel of per-capita income found, e.g., by Barro and Xavier Sala-i-Martin,is due to a 'fixed effect bias' that their cross-sectional analysisintroduces in the results. Our approach permits the estimation of differentconvergence rates to different steady states for each cross sectional unit.When this diversity is allowed, we find that convergence of each unit to(its own) steady state income level is much faster than previously estimatedbut that cross sectional differences persist: inequalities will only bereduced by a small amount by the passage of time. The cross countrydistribution of the steady state is largely explained by the cross countrydistribution of initial conditions.

Price differentials in monetary unions: The role of fiscal shocks

We study the effect of regional expenditure and revenue shocks on price differentials for47 US states and 9 EU countries. We identify shocks using sign restrictions on the dynamicsof deficits and output and construct two estimates for structural price differentials dynamics which optimally weight the information contained in the data for all units. Fiscal shocks explain between 14 and 23 percent of the variability of price differentials both in the US and in the EU. On average, expansionary fiscal disturbances produce positive price differential responses while distortionary balance budget shocks produce negative price differential responses. In a number of units, price differential responses to expansionary fiscal shocks are negative. Spillovers and labor supply effects partially explain this pattern while geographical, political, and economic indicators do not.

Worst-case bounds for the logarithmic loss of predictors

We investigate on-line prediction of individual sequences. Given a class of predictors, the goal is to predict as well as the best predictor in the class, where the loss is measured by the self information (logarithmic) loss function. The excess loss (regret) is closely related to the redundancy of the associated lossless universal code. Using Shtarkov's theorem and tools from empirical process theory, we prove a general upper bound on the best possible (minimax) regret. The bound depends on certain metric properties of the class of predictors. We apply the bound to both parametric and nonparametric classes ofpredictors. Finally, we point out a suboptimal behavior of the popular Bayesian weighted average algorithm.