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Jel Classification:C53 

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Real-time inflation forecasting in a changing world

This paper revisits the accuracy of inflation forecasting using activity and expectations variables. We apply Bayesian-model averaging across different regression specifications selected from a set of potential predictors that includes lagged values of inflation, a host of real activity data, term structure data, nominal data, and surveys. In this model average, we can entertain different channels of structural instability by incorporating stochastic breaks in the regression parameters of each individual specification within this average, allowing for breaks in the error variance of the ...
Staff Reports , Paper 388

Working Paper
Indeterminacy and forecastability

Recent studies document the deteriorating performance of forecasting models during the Great Moderation. This conversely implies that forecastability is higher in the preceding era, when the economy was unexpectedly volatile. We offer an explanation for this phenomenon in the context of equilibrium indeterminacy in dynamic stochastic general equilibrium models. First, we analytically show that a model under indeterminacy exhibits richer dynamics that can improve forecastability. Then, using a prototypical New Keynesian model, we numerically demonstrate that indeterminacy due to passive ...
Globalization Institute Working Papers , Paper 91

Working Paper
Do Phillips Curves Conditionally Help to Forecast Inflation?

This paper reexamines the forecasting ability of Phillips curves from both an unconditional and conditional perspective by applying the method developed by Giacomini and White (2006). We find that forecasts from our Phillips curve models tend to be unconditionally inferior to those from our univariate forecasting models. Significantly, we also find conditional inferiority, with some exceptions. When we do find improvement, it is asymmetric - Phillips curve forecasts tend to be more accurate when the economy is weak and less accurate when the economy is strong. Any improvement we find, ...
Working Papers , Paper 17-26

Working Paper
Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors : The Federal Reserve's Approach

Since November 2007, the Federal Open Market Committee (FOMC) of the U.S. Federal Reserve has regularly published participants? qualitative assessments of the uncertainty attending their individual forecasts of real activity and inflation, expressed relative to that seen on average in the past. The benchmarks used for these historical comparisons are the average root mean squared forecast errors (RMSEs) made by various private and government forecasters over the past twenty years. This paper documents how these benchmarks are constructed and discusses some of their properties. We draw several ...
Finance and Economics Discussion Series , Paper 2017-020

Journal Article
Machine Learning Approaches to Macroeconomic Forecasting

Forecasting macroeconomic conditions can be challenging, requiring forecasters to make many discretionary choices about the data and methods they use. Although forecasters underpin the choices they make about models and complexity with economic intuition and judgement, these assumptions can be flawed. {{p}} Machine learning approaches, on the other hand, automate as many of those choices as possible in a manner that is not subject to the discretion of the forecaster. Aaron Smalter Hall applies machine learning techniques to find an optimal forecasting model for the unemployment rate. His ...
Economic Review , Issue Q IV , Pages 63-81

Working Paper
Mind the Gap!—A Monetarist View of the Open-Economy Phillips Curve

In many countries, inflation has become less responsive to domestic factors and more responsive to global factors over the past decades. We introduce money and credit into the workhorse open-economy New Keynesian model. With this framework, we show that: (i) an efficient forecast of domestic inflation is based solely on domestic and foreign slack, and (ii) global liquidity (global money as well as global credit) is tied to global slack in equilibrium. Then, motivated by the theory, we evaluate empirically the performance of open-economy Phillips-curve-based forecasts constructed using global ...
Globalization Institute Working Papers , Paper 392

Working Paper
Diverging Tests of Equal Predictive Ability

We investigate claims made in Giacomini and White (2006) and Diebold (2015) regarding the asymptotic normality of a test of equal predictive ability. A counterexample is provided in which, instead, the test statistic diverges with probability one under the null.
Working Papers , Paper 2019-018

Working Paper
Using Payroll Processor Microdata to Measure Aggregate Labor Market Activity

We show that high-frequency private payroll microdata can help forecast labor market conditions. Payroll employment is perhaps the most reliable real-time indicator of the business cycle and is therefore closely followed by policymakers, academia, and financial markets. Government statistical agencies have long served as the primary suppliers of information on the labor market and will continue to do so for the foreseeable future. That said, sources of ?big data? are becoming increasingly available through collaborations with private businesses engaged in commercial activities that record ...
Finance and Economics Discussion Series , Paper 2018-005

Working Paper
Regular Variation of Popular GARCH Processes Allowing for Distributional Asymmetry

Linear GARCH(1,1) and threshold GARCH(1,1) processes are established as regularly varying, meaning their heavy tails are Pareto like, under conditions that allow the innovations from the, respective, processes to be skewed. Skewness is considered a stylized fact for many financial returns assumed to follow GARCH-type processes. The result in this note aids in establishing the asymptotic properties of certain GARCH estimators proposed in the literature.
Finance and Economics Discussion Series , Paper 2017-095

Working Paper
Forecasting Consumption Spending Using Credit Bureau Data

This paper considers whether the inclusion of information contained in consumer credit reports might improve the predictive accuracy of forecasting models for consumption spending. To investigate the usefulness of aggregate consumer credit information in forecasting consumption spending, this paper sets up a baseline forecasting model. Based on this model, a simulated real-time, out-of-sample exercise is conducted to forecast one-quarter ahead consumption spending. The exercise is run again after the addition of credit bureau variables to the model. Finally, a comparison is made to test ...
Working Papers , Paper 20-22

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