The Timing of Asset Trade and Optimal Policy in Dynamic Open Economies

Using a standard open economy DSGE model, it is shown that the timing of asset trade relative to policy decisions has a potentially important impact on the welfare evaluation of monetary policy at the individual country level. If asset trade in the initial period takes place before the announcement of policy, a national policymaker can choose a policy rule which reduces the work effort of households in the policymaker’s country in the knowledge that consumption is fully insured by optimally chosen international portfolio positions. But if asset trade takes place after the policy announcement, this insurance is absent and households in the policymaker’s country bear the full consumption consequences of the chosen policy rule. The welfare incentives faced by national policymakers are very different between the two cases. Numerical examples confirm that asset market timing has a significant impact on the optimal policy rule.

Forecasting Inflation Using Dynamic Model Averaging

We forecast quarterly US inflation based on the generalized Phillips curve using econometric methods which incorporate dynamic model averaging. These methods not only allow for coe¢ cients to change over time, but also allow for the entire forecasting model to change over time. We nd that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and more sophisticated approaches such as those using time varying coe¢ cient models. We also provide evidence on which sets of predictors are relevant for forecasting in each period.

Notes on Agents’ Behavioral Rules Under Adaptive Learning and Studies of Monetary Policy

These notes try to clarify some discussions on the formulation of individual intertemporal behavior under adaptive learning in representative agent models. First, we discuss two suggested approaches and related issues in the context of a simple consumption-saving model. Second, we show that the analysis of learning in the NewKeynesian monetary policy model based on “Euler equations” provides a consistent and valid approach.

On Identification of Bayesian DSGE Models

In recent years there has been increasing concern about the identification of parameters in dynamic stochastic general equilibrium (DSGE) models. Given the structure of DSGE models it may be difficult to determine whether a parameter is identified. For the researcher using Bayesian methods, a lack of identification may not be evident since the posterior of a parameter of interest may differ from its prior even if the parameter is unidentified. We show that this can even be the case even if the priors assumed on the structural parameters are independent. We suggest two Bayesian identification indicators that do not suffer from this difficulty and are relatively easy to compute. The first applies to DSGE models where the parameters can be partitioned into those that are known to be identified and the rest where it is not known whether they are identified. In such cases the marginal posterior of an unidentified parameter will equal the posterior expectation of the prior for that parameter conditional on the identified parameters. The second indicator is more generally applicable and considers the rate at which the posterior precision gets updated as the sample size (T) is increased. For identified parameters the posterior precision rises with T, whilst for an unidentified parameter its posterior precision may be updated but its rate of update will be slower than T. This result assumes that the identified parameters are pT-consistent, but similar differential rates of updates for identified and unidentified parameters can be established in the case of super consistent estimators. These results are illustrated by means of simple DSGE models.

Realised and Optimal Monetary Policy Rules in an Estimated Markov-Switching DSGE Model of the United Kingdom

This paper investigates underlying changes in the UK economy over the past thirtyfive years using a small open economy DSGE model. Using Bayesian analysis, we find UK monetary policy, nominal price rigidity and exogenous shocks, are all subject to regime shifting. A model incorporating these changes is used to estimate the realised monetary policy and derive the optimal monetary policy for the UK. This allows us to assess the effectiveness of the realised policy in terms of stabilising economic fluctuations, and, in turn, provide an indication of whether there is room for monetary authorities to further improve their policies.

UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?

Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting model as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.

Forecasting Inflation Using Dynamic Model Averaging

We forecast quarterly US inflation based on the generalized Phillips curve using econometric methods which incorporate dynamic model averaging. These methods not only allow for coe¢ cients to change over time, but also allow for the entire forecasting model to change over time. We nd that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and more sophisticated approaches such as those using time varying coe¢ cient models. We also provide evidence on which sets of predictors are relevant for forecasting in each period.

Forward Looking and Myopic Regional Computable General Equilibrium Models. How Significant is the Distinction?

We present a stylized intertemporal forward-looking model able that accommodates key regional economic features, an area where the literature is not well developed. The main difference, from the standard applications, is the role of saving and its implication for the balance of payments. Though maintaining dynamic forward-looking behaviour for agents, the rate of private saving is exogenously determined and so no neoclassical financial adjustment is needed. Also, we focus on the similarities and the differences between myopic and forward-looking models, highlighting the divergences among the main adjustment equations and the resulting simulation outcomes.

The Monetary policy rules in Europe: heterogeneity and common patters

The objective of this study is the empirical identification of the monetary policy rules pursued in individual countries of EU before and after the launch of European Monetary Union. In particular, we have employed an estimation of the augmented version of the Taylor rule (TR) for 25 countries of the EU in two periods (1992-1998, 1999-2006). While uniequational estimation methods have been used to identify the policy rules of individual central banks, for the rule of the European Central Bank has been employed a dynamic panel setting. We have found that most central banks really followed some interest rate rule but its form was usually different from the original TR (proposing that domestic interest rate responds only to domestic inflation rate and output gap). Crucial features of policy rules in many countries have been the presence of interest rate smoothing as well as response to foreign interest rate. Any response to domestic macroeconomic variables have been missing in the rules of countries with inflexible exchange rate regimes and the rules consisted in mimicking of the foreign interest rates. While we have found response to long-term interest rates and exchange rate in rules of some countries, the importance of monetary growth and asset prices has been generally negligible. The Taylor principle (the response of interest rates to domestic inflation rate must be more than unity as a necessary condition for achieving the price stability) has been confirmed only in large economies and economies troubled with unsustainable inflation rates. Finally, the deviation of the actual interest rate from the rule-implied target rate can be interpreted as policy shocks (these deviation often coincided with actual turbulent periods).

Model Switching and Model Averaging in Time- Varying Parameter Regression Models

This paper investigates the usefulness of switching Gaussian state space models as a tool for implementing dynamic model selecting (DMS) or averaging (DMA) in time-varying parameter regression models. DMS methods allow for model switching, where a different model can be chosen at each point in time. Thus, they allow for the explanatory variables in the time-varying parameter regression model to change over time. DMA will carry out model averaging in a time-varying manner. We compare our exact approach to DMA/DMS to a popular existing procedure which relies on the use of forgetting factor approximations. In an application, we use DMS to select different predictors in an in ation forecasting application. We also compare different ways of implementing DMA/DMS and investigate whether they lead to similar results.

How Optimal is US Monetary Policy?

Most of the literature estimating DSGE models for monetary policy analysis assume that policy follows a simple rule. In this paper we allow policy to be described by various forms of optimal policy - commitment, discretion and quasi-commitment. We find that, even after allowing for Markov switching in shock variances, the inflation target and/or rule parameters, the data preferred description of policy is that the US Fed operates under discretion with a marked increase in conservatism after the 1970s. Parameter estimates are similar to those obtained under simple rules, except that the degree of habits is significantly lower and the prevalence of cost-push shocks greater. Moreover, we find that the greatest welfare gains from the ‘Great Moderation’ arose from the reduction in the variances in shocks hitting the economy, rather than increased inflation aversion. However, much of the high inflation of the 1970s could have been avoided had policy makers been able to commit, even without adopting stronger anti-inflation objectives. More recently the Fed appears to have temporarily relaxed policy following the 1987 stock market crash, and has lost, without regaining, its post-Volcker conservatism following the bursting of the dot-com bubble in 2000.

Monetary Policy Delegation and Equilibrium Coordination

This paper revisits the argument that the stabilisation bias that arises under discretionary monetary policy can be reduced if policy is delegated to a policymaker with redesigned objectives. We study four delegation schemes: price level targeting, interest rate smoothing, speed limits and straight conservatism. These can all increase social welfare in models with a unique discretionary equilibrium. We investigate how these schemes perform in a model with capital accumulation where uniqueness does not necessarily apply. We discuss how multiplicity arises and demonstrate that no delegation scheme is able to eliminate all potential bad equilibria. Price level targeting has two interesting features. It can create a new equilibrium that is welfare dominated, but it can also alter equilibrium stability properties and make coordination on the best equilibrium more likely.

Co-movements in Real Effective Exchange Rates: Evidence from the Dynamic Hierarchical Factor Model

We analyze and quantify co-movements in real effective exchange rates while considering the regional location of countries. More specifically, using the dynamic hierarchical factor model (Moench et al. (2011)), we decompose exchange rate movements into several latent components; worldwide and two regional factors as well as country-specific elements. Then, we provide evidence that the worldwide common factor is closely related to monetary policies in large advanced countries while regional common factors tend to be captured by those in the rest of the countries in a region. However, a substantial proportion of the variation in the real exchange rates is reported to be country-specific; even in Europe country-specific movements exceed worldwide and regional common factors.

Modeling Dependence Structure and Forecasting Portfolio Value-at-Risk with Dynamic Copulas

We study the asymmetric and dynamic dependence between financial assets and demonstrate, from the perspective of risk management, the economic significance of dynamic copula models. First, we construct stock and currency portfolios sorted on different characteristics (ex ante beta, coskewness, cokurtosis and order flows), and find substantial evidence of dynamic evolution between the high beta (respectively, coskewness, cokurtosis and order flow) portfolios and the low beta (coskewness, cokurtosis and order flow) portfolios. Second, using three different dependence measures, we show the presence of asymmetric dependence between these characteristic-sorted portfolios. Third, we use a dynamic copula framework based on Creal et al. (2013) and Patton (2012) to forecast the portfolio Value-at-Risk of long-short (high minus low) equity and FX portfolios. We use several widely used univariate and multivariate VaR models for the purpose of comparison. Backtesting our methodology, we find that the asymmetric dynamic copula models provide more accurate forecasts, in general, and, in particular, perform much better during the recent financial crises, indicating the economic significance of incorporating dynamic and asymmetric dependence in risk management.

Time Varying Dimension Models

Time varying parameter (TVP) models have enjoyed an increasing popularity in empirical macroeconomics. However, TVP models are parameter-rich and risk over-fitting unless the dimension of the model is small. Motivated by this worry, this paper proposes several Time Varying dimension (TVD) models where the dimension of the model can change over time, allowing for the model to automatically choose a more parsimonious TVP representation, or to switch between different parsimonious representations. Our TVD models all fall in the category of dynamic mixture models. We discuss the properties of these models and present methods for Bayesian inference. An application involving US inflation forecasting illustrates and compares the different TVD models. We find our TVD approaches exhibit better forecasting performance than several standard benchmarks and shrink towards parsimonious specifications.