Do disaggregated CPI data improve the accuracy of inflation forecasts?

In this paper, we evaluate the role of using consumer price index (CPI) disaggregated data to improve the accuracy of inflation forecasts. Our forecasting approach is based on extracting the factors from the subcomponents of the CPI at the highest degree of disaggregation. The data set contains 54 macroeconomic series and 243 CPI subcomponents from 1992 to 2009 for Mexico. We find that the factor models that include disaggregated data outperform the benchmark autoregressive model and the factor models containing alternative groups of macroeconomic variables. We provide evidence that using disaggregated price data improves forecasting performance. The forecasts of the factor models that extract the information from the CPI disaggregated data are as accurate as the forecasts from the survey of experts.     

Multi-horizon inflation forecasts using disaggregated data

In this paper we use multi-horizon evaluation techniques to produce monthly inflation forecasts for up to twelve months ahead. The forecasts are based on individual seasonal time series models that consider both, deterministic and stochastic seasonality, and on disaggregated Consumer Price Index (CPI) data. After selecting the best forecasting model for each index, we compare the individual forecasts to forecasts produced using two methods that aggregate hierarchical time series, the bottom-up method and an optimal combination approach. Applying these techniques to 16 indices of the Mexican CPI, we find that the best forecasts for headline inflation are able to compete with those taken from surveys of experts.     

Do FOMC forecasts add value to staff forecasts?

This paper compares the economic forecasts of members of the Board of Governors and presidents of the Federal Reserve Banks, and then investigates the value of each group's forecasts in supplementing the forecasts of the Board of Governors' staff. We find that the presidents tend to forecast higher inflation and real GDP growth, and lower unemployment than the members of the Board of Governors. We also find that the presidents' real GDP and unemployment rate forecasts add value to the real economy forecasts of the staff, while the governors' inflation forecasts add value to the staff's inflation forecasts.     

Forecasting Canadian time series with the New Keynesian model

Abstract.  This paper assesses the out-of-sample forecasting accuracy of the New Keynesian Model for Canada. We estimate a variant of the model on a series of rolling subsamples, computing out-of-sample forecasts one to eight quarters ahead at each step. We compare these forecasts with those arising from vector autoregression (VAR) models, using econometric tests of forecasting accuracy. We show that the forecasting accuracy of the New Keynesian Model compares favourably with that of the benchmarks, particularly as the forecasting horizon increases. These results suggest that the model could become a useful forecasting tool for Canadian time series.     

Forward-looking monetary policy and anticipated shocks to inflation

This paper extends a standard New Keynesian model to describe the effects of anticipated shocks to inflation and forward-looking monetary policy. Using the data generated from this modified model suggests that overlooking these two factors in the standard Cholesky structural vector autoregressive identification scheme will generate a price puzzle. Furthermore, this paper demonstrates that failing to account for these two factors may result in significant estimates of two other explanations of the price puzzle—the cost channel of transmission of monetary policy and indeterminacy due to violation of the Taylor principle—even though neither features in the data generating process.     

Taylor rules and the Great Inflation

Can US monetary policy in the 1970s be described by a stabilizing Taylor rule when policy is evaluated with real-time inflation and output gap data? Using economic research on the full employment level of unemployment and the natural rate of unemployment published between 1970 and 1977 to construct real-time output gap measures for periods of peak unemployment, we find that the Federal Reserve did not follow a Taylor rule if appropriate measures are used. We estimate Taylor rules and find no evidence that monetary policy stabilized inflation, even allowing for changes in the inflation target. While monetary policy was stabilizing with respect to inflation forecasts, the forecasts systematically under-predicted inflation following the 1970s recessions and this does not constitute evidence of stabilizing policy. We also find that the Federal Reserve responded too strongly to negative output gaps.     

Estimating potential output for New Zealand

One of the main indicators of inflationary pressures used by the Reserve Bank of New Zealand is the output gap. An alternative to the Reserve Bank's incumbent measure of potential output is obtained using a structural vector autoregression (SVAR) methodology with long–run restrictions. The Reserve Bank's official measure of the output gap and the estimate obtained from the SVAR model tend to agree about the state of the cycle, especially during the 1970s and 1990s. However, during the 1980s, the period of economic reforms, they are more dissimilar.     

Foreign output shock in small open economies: A welfare evaluation of monetary policy regimes

We examine the impact of negative foreign output shocks, which entail negative demand side effects by lowering exports and positive supply side effects by lowering oil prices, on the welfare of non-oil producing, small open economies under five exchange rate and monetary policy regimes. We use a dynamic stochastic general equilibrium model with parameter values calibrated for Hong Kong, Israel, Singapore, South Korea and Taiwan. We find that welfare levels among the five policy regimes depend on the economy's share of oil imports in world oil consumption. Hong Kong, Singapore and Israel, which have smaller shares, maximize welfare under the Taylor rule, which targets both CPI inflation and real output. South Korea, with higher shares, and Taiwan, with more rigid prices, maximize welfare under real output targeting. CPI inflation targeting, nominal output growth targeting and fixed exchange rate regimes generate lower welfare. However, optimal monetary policy, which generates the highest welfare, gives greater weight on real output than CPI inflation.     

German business cycle forecasts, asymmetric loss and financial variables

We examine the efficiency of German forecasts for output growth and inflation allowing for an asymmetric loss function of the forecasters. We find the loss of output growth forecasts to be approximately symmetric while there is an asymmetry in the loss of the inflation forecasts. The information of financial variables seems to be adequately incorporated into the output forecasts but to a lesser extent into the inflation forecasts.     

Inflation-Plus Targeting at the Reserve Bank of Australia

This article first outlines the dynamics of what appear to be increasingly prevalent cycles of asset price inflation in liberalised financial systems, as well as the difficulties entailed in successful monetary policy responses. The article then analyses the Reserve Bank of Australia's policy responses to recent rises in credit growth and asset price inflation in the property sector. The Bank's responses are characterized in terms of an inflation‐plus targeting framework which has subtly redefined the Bank's approach to inflation targeting to include vaguely defined factors such as mediumterm‘risks’, as well as extending the time frame of such risk assessment. The article explains why, for a variety of reasons, the Bank has been reticent to fully declare its hand.     

The empirical validity of the New Keynesian Phillips curve using survey forecasts of inflation

This paper investigates the performance of the New Keynesian Phillips curve when survey forecasts of inflation are used to proxy for inflation expectations. Previous authors such as Brissimis and Magginas (2008) have applied survey measures of inflation expectations to the NKPC, and have concluded that these estimates are superior to those estimated using actual data on future inflation. However this approach employs the use of the labor income share as the proxy for real marginal cost, something which is highly problematic once we consider the countercyclicality of this variable. This paper develops and tests a procyclical marginal cost variable alongside various survey measures of inflation forecasts in the NKPC, while recognizing the problem of weak instruments that occurs when estimating the model using conventional GMM. We find that the NKPC produces a counter-intuitive negative and significant coefficient on procyclical marginal cost when surveys of inflation forecasts are used, which casts serious doubt on the empirical viability of the NKPC model, even when estimated with survey inflation forecasts.     

Directional analysis of consumers’ forecasts of inflation in a small open economy: evidence from South Korea

We evaluate the directional accuracy of consumers’ forecasts of inflation in predicting the movement of the actual CPI in a small open economy. In order to do so, we use a method developed by Pesaran and Timmermann (2009), based on South Korean data. By illustrating an application of the new market-timing test, we show that consumers’ expectations of inflation are not a useful predictor of the CPI in South Korea. Our findings suggest that the directional accuracy of consumers’ 1-year-ahead forecasts of inflation is not affected by the inflation targeting of the Bank of Korea. Our findings also suggest that consumers’ 1-year-ahead forecasts of inflation are scattered away from the Bank of Korea’s inflation target.     

What drives inflation in New Keynesian models?

This paper estimates variants of a small-scale New Keynesian model using observations on inflation, inflation expectations and nominal interest rates. We ask whether those variables alone can tell us something about the time series properties of real marginal costs.     

Inflation forecasting using the New Keynesian Phillips Curve with a time-varying trend

Does theory aid inflation forecasting? To address this question, we develop a novel forecasting procedure based upon a New Keynesian Phillips Curve that incorporates time-varying trend inflation, to capture shifts in central bank preferences and monetary policy frameworks. We generate theory-implied predictions for both the trend and cyclical components of inflation, and recombine them to obtain an overall inflation forecast. Using quarterly data for the Euro Area and the United States that cover almost half a century, we compare our inflation forecasting procedure against the most popular time series models. We find that our theory-based forecasts outperform these benchmarks that previous studies found difficult to beat. Our results are shown to be robust to structural breaks, geographic areas, and variants of the econometric specification. Our findings suggest that the scepticism concerning the use of theory in forecasting is unwarranted, and theory should continue to play an important role in policymaking.     

The Halle Economic Projection Model

In this paper we develop an open economy model explaining the joint determination of output, inflation, interest rates, unemployment and the exchange rate in a multi-country framework. Our model—the Halle Economic Projection Model (HEPM)—is closely related to studies published by Carabenciov et al. (2008a,b,c). Our main contribution is that we model the Euro area countries separately. In doing so, we consider Germany, France, and Italy which represent together about 70% of Euro area GDP. The model combines core equations of the New-Keynesian standard DSGE model with empirically useful ad-hoc equations. We estimate this model using Bayesian techniques and evaluate the forecasting properties. Additionally, we provide an impulse response analysis and historical shock decomposition.     

Evaluating the effect of monetary policy on unemployment with alternative inflation forecasts

This paper explores the role that inflation forecasts play in the uncertainty surrounding the estimated effects of alternative monetary rules on unemployment dynamics in the euro area and the US. We use the inflation forecasts of 8 competing models in a standard Bayesian VAR to analyse the size and the timing of these effects, as well as to quantify the uncertainty relative to the different inflation models under two rules. The results suggest that model uncertainty can be a serious issue and strengthen the case for a policy strategy that takes into account several sources of information. We find that combining inflation forecasts from many models not only yields more accurate forecasts than those of any specific model, but also reduces the uncertainty associated with the real effects of policy decisions. These results are in line with the model-combination approach that central banks already follow when conceiving their strategy.     

Output gap measurement and the New Keynesian Phillips curve for China

The New Keynesian Phillips curve implies that the output gap, the deviation of the actual output from its natural level due to nominal rigidities, drives the dynamics of inflation relative to expected inflation and lagged inflation. This paper exploits the empirical success of the New Keynesian Phillips curve in explaining China's inflation dynamics with a new measure of the output gap. We estimate the output gap using the Bayesian multivariate Beveridge–Nelson decomposition method, based on a multivariate dynamic model featuring distinct interactions among inflation, money, and real output in China. The empirical results using quarterly data spanning 1979–2010 show that the new measure of the output gap outperforms the traditional measures in fitting the New Keynesian Phillips curve. This result provides useful insights for inflation dynamics and monetary policy analysis in China.     

Tracking real-time data revisions in inflation persistence

Regarding the forecasting of real-time data, it is assumed that the third quarter release produces the best forecasts since it includes data from new and revised sources, which this paper finds is not necessarily the case. There seems to be a benchmark effect when estimating the local nonparametric regressions and the forecasts of real-time PCE and core PCE when examining the four benchmark periods beginning in 1996:Q1, 1999:Q4, 2003:Q4, and 2009:Q3. There is a benchmark effect with respect to the estimated local nonparametric slopes with the demarcation being at the 2003:Q4 benchmark, which is also the demarcation for the forecasting results. For the benchmark revisions periods of 1996:Q1 and 1999:Q4, the second quarter real-time data releases produce the smaller RMSE and for the benchmark revisions of 2003:Q4 and 2009:Q3, the third quarter real-time data releases produce forecasts with smaller RMSE approximately 58% and 60% of the time, respectively.

Abbreviations: PCE, Personal Consumption Expenditures; KWLS, Kernel Weighted Least Squares; "V_" as a prefix stand for vintage, i.e. V_2003:Q4 is vintage 2003:Q4, which means that the data sample ends in 2003: Q3; IRSC, integrated residual squares criterion; NPISH, Non-Profit Institutions Serving Households; SNA, System of Accounts; RMSE, Root Mean Square Error; MAE, Mean Absolute Error; NAICS, North American Industry Classification System; SIC, Standard Industrial Classification; ARSC, Average Residual Squares Criterion; I-O, Input – Output; EIA, Energy Information Administration; ATM, Automated Teller Machines; BEA, Bureau of Economic Analysis; SNA, System of Accounts     

Taylor rules in the open economy

Taylor rules, which link short-term interest rates to fluctuations in inflation and output, have been shown to be a good guide (both positively and normatively) to the conduct of monetary policy. As a result they have been used extensively to model policy in the context of both closed and open economy models. Their determinacy properties have also been analysed in the context of closed and, to a more limited degree, in small open economy models. In this paper, we extend the analysis of the determinacy properties of Taylor rules to the case of a benchmark two-country model. When the rules are specified in terms of output-price inflation we confirm and extend the conventional results from the closed economy literature—satisfying the Taylor principle is the key to ensuring determinacy, although the presence of backward-looking price-setting can affect the determinacy properties of the two-country model. However, the conventional results do not hold when we replace output-price inflation with consumer price inflation in the specification of the rule. In this case, Taylor rules which satisfy the Taylor principle will be indeterminate, unless there is an unusually large home bias in consumption. Similar indeterminacy problems arise when one country targets CPI inflation and the other output-price inflation. In this case we show that, even if determinacy is achieved, large spillovers may occur between countries.     

The diversity of forecasts from macroeconomic models of the US economy

This paper investigates the accuracy and heterogeneity of output growth and inflation forecasts during the current and the four preceding NBER-dated US recessions. We generate forecasts from six different models of the US economy and compare them to professional forecasts from the Federal Reserve??s Greenbook and the Survey of Professional Forecasters (SPF). The model parameters and model forecasts are derived from historical data vintages so as to ensure comparability to historical forecasts by professionals. The mean model forecast comes surprisingly close to the mean SPF and Greenbook forecasts in terms of accuracy even though the models only make use of a small number of data series. Model forecasts compare particularly well to professional forecasts at a horizon of three to four quarters and during recoveries. The extent of forecast heterogeneity is similar for model and professional forecasts but varies substantially over time. Thus, forecast heterogeneity constitutes a potentially important source of economic fluctuations. While the particular reasons for diversity in professional forecasts are not observable, the diversity in model forecasts can be traced to different modeling assumptions, information sets and parameter estimates.