A Bounded Model of Time Variation in Trend Inflation,Nairu and the Phillips Curve

In this paper, we develop a bivariate unobserved components model for inflation and unemployment. The unobserved components are trend inflation and the non‐accelerating inflation rate of unemployment (NAIRU). Our model also incorporates a time‐varying Phillips curve and time‐varying inflation persistence. What sets this paper apart from the existing literature is that we do not use unbounded random walks for the unobserved components, but rather bounded random walks. For instance, NAIRU is assumed to evolve within bounds. Our empirical work shows the importance of bounding. We find that our bounded bivariate model forecasts better than many alternatives, including a version of our model with unbounded unobserved components. Our model also yields sensible estimates of trend inflation, NAIRU, inflation persistence and the slope of the Phillips curve. Copyright © 2015 John Wiley & Sons, Ltd.     

Nonlinear dynamics of interest rate and inflation

According to several empirical studies US inflation and nominal interest rates as well as the real interest rate can be described as unit root processes. These results imply that nominal interest rates and expected inflation do not move one‐for‐one in the long run, which is incongruent with theoretical models. In this paper we introduce a new nonlinear bivariate mixture autoregressive model that seems to fit quarterly US data (1953 : II–2004 : IV) reasonably well. It is found that the three‐month Treasury bill rate and inflation share a common nonlinear component that explains a large part of their persistence. The real interest rate is devoid of this component, indicating one‐for‐one movement of the nominal interest rate and inflation in the long run and, hence, stationarity of the real interest rate. Copyright © 2006 John Wiley & Sons, Ltd.     

Evolving macroeconomic perceptions and the term structure of interest rates

We explore the role of evolving beliefs regarding the structure of the macroeconomy in improving our understanding of the term structure of interest rates within the context of a simple macro-finance model. Using quarterly vintages of real-time data and survey forecasts for the United States over the past 40 years, we show that a recursively estimated VAR on real GDP growth, inflation and the nominal short-term interest rate generates predictions that are more consistent with survey forecasts than a benchmark fixed-coefficient counterpart. We then estimate a simple term structure model under the assumption that investor risk attitude is driven by near-term expectations of the three state variables. When we allow for evolving beliefs about the macroeconomy, the resulting term structure model provides a better fit to the cross section of yields than the benchmark model, especially at longer maturities, and exhibits better performance in out-of-sample predictions of future yield movements.     

Forecasting Australia’s economic performance during the Asian crisis

During the Asian economic crisis of 1997–98, published forecasts from a Bayesian vector autoregressive (BVAR) model consistently indicated that the crisis would have little or no effect on Australia’s economic performance, despite the deterioration in the trade balance. The worsening trade deficit led many other forecasters to predict a sharp fall in Australia’s GDP growth rate, as the countries most severely affected by the crisis represent over 60 percent of Australia’s export markets. This paper argues that the more pessimistic forecasts attached too much weight to the links between Australia’s external accounts and GDP growth. In particular, I show that forecasts for the period September 1997 to December 1998, conditional on the actual path of the merchandise trade balance, predict higher inflation and interest rates than unconditional forecasts from a model without the trade balance. There does, however, appear to be useful information in the individual components of the trade deficit. Conditioning on the actual paths of both exports and imports generally produces more accurate forecasts than conditioning on net exports. In particular, conditioning on the trade balance results in the least accurate forecasts for inflation and interest rates of any of the models considered here. On the other hand, conditioning on the individual trade flows produces the most accurate forecasts for inflation, and the second-most accurate for interest rates. Taken together, the results presented here lend support to the argument that Australia’s trade flows represent the outcomes of optimizing decisions, rather than defining constraints on economic growth.     

The regime-switching risk premium in the gold futures market

A bivariate Markov-switching model identifies two regimes in the futures-price and risk-premium models. The persistent underlying states have very different implications for spot and risk-premium forecasts. In the “low” state, a positive bias predicts spot price appreciation. The “high” state is associated with lower spot appreciation and higher risk premiums. The regime-switching framework provides a new perspective on the intertemporal role of gold as a hedge or safe-haven asset. The gold spot-price appreciation regime is shown to be correlated with higher inflation rates and the complement regime is associated with high market returns and stock market risk premia. Since the state-space methodology procedure can be employed using only past data, forecasts of the persistent unobserved underlying state of the gold price appreciation regime will be augmented as more data becomes available.     

The expected real yield and inflation components of the nominal yield curve

The term structure of real yields and expected inflation are two unobserved components of the nominal yield curve. The primary objectives of this study are to decompose nominal yields into their expected real yield and inflation components and to examine their behaviour using state-space and regime-switching frameworks. The dynamic yield-curve models capture three well-known latent factors – level, slope, and curvature – that accurately aggregate the information for the nominal yields and the expected real and inflation components for all maturities. The nominal yield curve is found to increase slightly with a slope of about 120 basis points, while the real yield curve slopes upward by about 20 basis points, and the expected inflation curve is virtually flat at slightly above 2 per cent. The regime-switching estimations reveal that the nominal yield, real yield and expected inflation curves have shifted down significantly since 1999.     

Interest rate risk in an emerging economy

The sharp decrease in inflation over the last decade—from 26% in 1990 to 4% in 2001—led the Central Bank of Chile to set its monetary policy interest rate in nominal terms since August 2001. This paper analyzes the effect of nominalization on the behavior of nominal, inflation-linked, and real interest rates, and its subsequent effects on the financial market. We find that nominalization has made nominal interest rates less volatile, while the opposite holds for inflation-linked interest rates. The effect on real interest rates is less unambiguous, but nominalization appears to have increased the cost of borrowing.     

Inflation illusion and the Taylor principle: An experimental study

We develop a simple experimental setting to evaluate the role of the Taylor principle, which holds that the nominal interest rate has to respond more than one-for-one to fluctuations in the inflation rate to exert a stabilizing effect. In our setting, the average inflation rate fluctuates around the inflation target if the computerized central bank obeys the Taylor principle. If the Taylor principle is violated, the average inflation rate persistently deviates from the target. These deviations from the target are less pronounced, if inflation rates cannot be as readily observed as nominal interest rates. This result is consistent with the interpretation that subjects underestimate the influence of inflation on the real return to savings if the inflation rate is only observed ex post.     

Macroeconomic forecasting and structural change

The aim of this paper is to assess whether modeling structural change can help improving the accuracy of macroeconomic forecasts. We conduct a simulated real‐time out‐of‐sample exercise using a time‐varying coefficients vector autoregression (VAR) with stochastic volatility to predict the inflation rate, unemployment rate and interest rate in the USA. The model generates accurate predictions for the three variables. In particular, the forecasts of inflation are much more accurate than those obtained with any other competing model, including fixed coefficients VARs, time‐varying autoregressions and the naïve random walk model. The results hold true also after the mid 1980s, a period in which forecasting inflation was particularly hard. Copyright © 2011 John Wiley & Sons, Ltd.     

Nominal interest rate policy rules and the feasibility of real interest rate control

In this paper the author builds a financial market model to demonstrate that policy aimed at reducing the variance in nominal interest rates reduces the information content of these variables. This has the undesirable effect of destabilizing real interest rates. The researcher demonstrates that nominal interest rate policy rules stabilize the component of the variance in the ex ante real interest rate attributable to the variance in the nominal rate. The variability of the expected inflation rate can, however, be increased by such policy rules, making the net effect of a nominal interest rate policy on the variance in the real interest rate ambiguous.     

Bond risk, bond return volatility, and the term structure of interest rates

This paper explores the time variation in the bond risk, as measured by the covariation of bond returns with stock returns and consumption growth, and in the volatility of bond returns. A robust stylized fact in empirical finance is that the spread between the yields on long- and short-term bonds forecasts future excess returns on bonds at varying horizons positively; in addition, the short-term nominal interest rate forecasts both the stock return volatility and the exchange rate volatility positively. This paper presents evidence that movements in both the short-term nominal interest rate and the yield spread are positively related to changes in the subsequent realized bond risk and bond return volatility. The yield spread appears to proxy for business conditions, while the short rate appears to proxy for inflation and economic uncertainty. A decomposition of bond betas into a real cash flow risk component and a discount rate risk component shows that yield spreads have offsetting effects in each component. A widening yield spread is correlated with a reduced cash-flow (or inflationary) risk for bonds, but it is also correlated with a larger discount rate risk for bonds. The short rate only forecasts the discount rate component of the bond beta.     

Euro area real-time density forecasting with financial or labor market frictions

We compare real-time density forecasts for the euro area using three DSGE models. The benchmark is the Smets and Wouters model, and its forecasts of real GDP growth and inflation are compared with those from two extensions. The first adds financial frictions and expands the observables to include a measure of the external finance premium. The second allows for the extensive labor-market margin and adds the unemployment rate to the observables. The main question that we address is whether these extensions improve the density forecasts of real GDP and inflation and their joint forecasts up to an eight-quarter horizon. We find that adding financial frictions leads to a deterioration in the forecasts, with the exception of longer-term inflation forecasts and the period around the Great Recession. The labor market extension improves the medium- to longer-term real GDP growth and shorter- to medium-term inflation forecasts weakly compared with the benchmark model.     

Issue Information

Much research studies US inflation history with a trend‐cycle model with unobserved components, where the trend may be viewed as the Fed's evolving inflation target or long‐horizon expected inflation. We provide a novel way to measure the slowly evolving trend and the cycle (or inflation gap), by combining inflation predictions from the Survey of Professional Forecasters (SPF) with realized inflation. The SPF forecasts may be treated either as rational expectations (RE) or updating according to a sticky information (SI) law of motion. We estimate RE and SI state‐space models with stochastic volatility on samples of consumer price index and gross national product/gross domestic product deflator inflation and the associated SPF inflation predictions using a particle Metropolis–Markov chain Monte Carlo sampler. The trend converges to 2% and its volatility declines over time—two tendencies largely complete by the late 1990s.     

Inflation Uncertainty, Output Growth Uncertainty and Macroeconomic Performance

We use a bivariate generalized autoregressive conditionally heteroskedastic (GARCH) model of inflation and output growth to examine the causality relationship among nominal uncertainty, real uncertainty and macroeconomic performance measured by the inflation and output growth rates. The application of the constant conditional correlation GARCH(1,1) model leads to a number of interesting conclusions. First, inflation does cause negative welfare effects, both directly and indirectly, i.e. via the inflation uncertainty channel. Secondly, in some countries, more inflation uncertainty provides an incentive to Central Banks to surprise the public by raising inflation unexpectedly. Thirdly, in contrast to the assumptions of some macroeconomic models, business cycle variability and the rate of economic growth are related. More variability in the business cycle leads to more output growth.     

Discounting inflation — a note

The aim of this paper is to clarify the confused issue of the effect of inflation on the discounting procedure for investment appraisal. The standard approach is considered, together with the impact of inflation, and the problem of how to adjust the standard approach to take account of inflation. The point is made that it is usually easiest to estimate expected returns in current prices, in which case the discount rate should reflect the real opportunity cost of capital, to avoid mixing real returns and nominal interest in a manner which leads to the rejection of worthwhile projects. An example is given of how the real rate of interest can be computed from the nominal rate of interest and the rate of inflation, and the difference this makes to discounting a sample project. The paper then illustrates how real rates of interest have frequently been negative over the past decade and how this implies that projects may be acceptable even if the sum of future undiscounted returns is less than the initial outlay. The conclusion drawn is that investors should maximize economic profit defined as the surplus over opportunity cost, which reduces the deterrent of nominally high interest rates, for the maximization of surplus over opportunity cost has the corollary of minimization of opportunity loss.     

Forecasting economic and financial variables with global VARs

This paper considers the problem of forecasting economic and financial variables across a large number of countries in the global economy. To this end a global vector autoregressive (GVAR) model, previously estimated by Dees, di Mauro, Pesaran, and Smith (2007) and Dees, Holly, Pesaran, and Smith (2007) over the period 1979Q1–2003Q4, is used to generate out-of-sample forecasts one and four quarters ahead for real output, inflation, real equity prices, exchange rates and interest rates over the period 2004Q1–2005Q4. Forecasts are obtained for 134 variables from 26 regions, which are made up of 33 countries and cover about 90% of the world output. The forecasts are compared to typical benchmarks: univariate autoregressive and random walk models. Building on the forecast combination literature, the effects of model and estimation uncertainty on forecast outcomes are examined by pooling forecasts obtained from different GVAR models estimated over alternative sample periods. Given the size of the modelling problem, and the heterogeneity of the economies considered–industrialised, emerging, and less developed countries–as well as the very real likelihood of possibly multiple structural breaks, averaging forecasts across both models and windows makes a significant difference. Indeed, the double-averaged GVAR forecasts perform better than the benchmark competitors, especially for output, inflation and real equity prices.     

Forecasting aggregates and disaggregates with common features

This paper focuses on the provision of consistent forecasts for an aggregate economic indicator, such as a consumer price index and its components. The procedure developed is a disaggregated approach based on single-equation models for the components, which take into account the stable features that some components share, such as a common trend and common serial correlation. Our procedure starts by classifying a large number of components based on restrictions from common features. The result of this classification is a disaggregation map, which may also be useful in applying dynamic factors, defining intermediate aggregates or formulating models with unobserved components. We use the procedure to forecast inflation in the Euro area, the UK and the US. Our forecasts are significantly more accurate than either a direct forecast of the aggregate or various other indirect forecasts.     

Fisher equations inverted and not

Regressions of the realized real after-tax interest rate on theex post rate of inflation are shown to be incapable of discriminating between the competing hypotheses that the real after-tax interest rate is not effected by expected inflation due to the substitutability between debt and equity (the Fisher hypothesis); and, that the nominal after-tax interest rate is not effected by expected inflation due to the substitutability between money and debt (the inverted Fisher hypothesis). An alternative regression which is so capable, is shown to reject the inverted and support the original Fisher hypothesis.     

Evaluating Point and Density Forecasts of DSGE Models

This paper investigates the accuracy of forecasts from four dynamic stochastic general equilibrium (DSGE) models for inflation, output growth and the federal funds rate using a real‐time dataset synchronized with the Fed's Greenbook projections. Conditioning the model forecasts on the Greenbook nowcasts leads to forecasts that are as accurate as the Greenbook projections for output growth and the federal funds rate. Only for inflation are the model forecasts dominated by the Greenbook projections. A comparison with forecasts from Bayesian vector autoregressions shows that the economic structure of the DSGE models which is useful for the interpretation of forecasts does not lower the accuracy of forecasts. Combining forecasts of several DSGE models increases precision in comparison to individual model forecasts. Comparing density forecasts with the actual distribution of observations shows that DSGE models overestimate uncertainty around point forecasts. Copyright © 2013 John Wiley & Sons, Ltd.     

Forecasting the UK economy with a medium-scale Bayesian VAR

We estimate a Bayesian VAR (BVAR) for the UK economy and assess its performance in forecasting GDP growth and CPI inflation in real time relative to forecasts from COMPASS, the Bank of England’s DSGE model, and other benchmarks. We find that the BVAR outperformed COMPASS when forecasting both GDP and its expenditure components. In contrast, their performances when forecasting CPI were similar. We also find that the BVAR density forecasts outperformed those of COMPASS, despite under-predicting inflation at most forecast horizons. Both models over-predicted GDP growth at all forecast horizons, but the issue was less pronounced in the BVAR. The BVAR’s point and density forecast performances are also comparable to those of a Bank of England in-house statistical suite for both GDP and CPI inflation, as well as to the official Inflation Report projections. Our results are broadly consistent with the findings of similar studies for other advanced economies.