Financial nowcasts and their usefulness in macroeconomic forecasting

Knotek, Edward S.; Zaman, Saeed

doi:10.1016/j.ijforecast.2018.10.012

Cited by 21 publications

(7 citation statements)

References 47 publications

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“…6. Tallman and Zaman (2020) show that augmenting vector autoregressive (VAR) model forecasts with nowcasts of inflation, as is the typical practice in forecasting (Knotek and Zaman, 2019), leads to forecasts for CPI inflation that are comparably accurate to those of the Survey of Professional Forecasters. Based on these exercises, we augment the Stock and Watson (2007) model with monthly CPI inflation nowcasts from the inflation nowcasting model of Knotek and Zaman (2017).…”

Section: Footnotesmentioning

confidence: 99%

Whose Inflation Expectations Best Predict Inflation?

Verbrugge

Zaman

2021

EC (FRB Cleveland)

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We examine the predictive relationship between various measures of inflation expectations and future inflation. We find that the expectations of professional economists and of businesses have tended to provide more accurate predictions of future inflation than the expectations of households and of financial market participants. However, the forecasts coming from a relatively simple and popular benchmark inflation forecasting model have historically been roughly as accurate as the expectations of businesses and professional economists.

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Section: Footnotesmentioning

confidence: 99%

Whose Inflation Expectations Best Predict Inflation?

Verbrugge

Zaman

2021

EC (FRB Cleveland)

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“…16 Bayesian VARs are widely used to forecast macroeconomic variables. We use BVAR models similar to those used in Banbura, Giannone, and Reichlin (2010) and Knotek and Zaman (2019). We set lag length=3 to be consistent with the AR(3) benchmark model.…”

Section: Models and Forecasting Setupmentioning

confidence: 99%

Improving Inflation Forecasts Using Robust Measures

Verbrugge

Zaman

2022

Working Paper (Federal Reserve Bank of Cleveland)

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Both theory and extant empirical evidence suggest that the cross-sectional asymmetry across disaggregated price indexes might be useful in the forecasting of aggregate inflation. Trimmed-mean inflation estimators have been shown to be useful devices for forecasting headline PCE inflation. But does this stem from their ability to signal the underlying trend, or does it mainly come from their implicit signaling of asymmetry (when included alongside headline PCE)? We address this question by augmenting a “hard to beat” benchmark inflation forecasting model of headline PCE price inflation with robust measures of trimmed-mean estimators of inflation (median PCE and trimmed-mean PCE) and robust measures of the cross-sectional asymmetry (Bowley skewness; Kelly skewness) computed using the 180+ components of the PCE price index. We also construct new trimmed-mean measures of goods and services PCE inflation and their accompanying robust skewness. Our results indicate significant gains in the point and density accuracy of PCE inflation forecasts over medium- and longer-term horizons, up through and including the COVID-19 pandemic. We find that improvements in accuracy stem mainly from the trend information implicit in trimmed-mean estimators, but that skewness is also useful. Median PCE slightly outperforms trimmed-mean PCE; both outperform core PCE. For point forecasts, Kelly skewness is preferred; but for estimating stochastic volatility, Bowley skewness is preferred. An examination of goods and services PCE inflation provides similar inference.

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“…While the predictive content of the yield curve is not its main concern, papers are on the lookout for anything that helps forecast output, and at times the yield curve makes an appearance. Often, it is part of a suite of financial variables, as in Koop (2013) or Knotek and Zaman (2019), though the marginal contribution of the spread by itself is not split out. Stock and Watson (1989), in creating a new index of leading economic indicators, find the 10-year-6-month Treasury spread important enough to include in their new index, though it is not as important as a shorter risk spread.…”

Section: Tangentsmentioning

confidence: 99%

Does the Yield Curve Predict Output?

Haubrich

2021

Annu. Rev. Financ. Econ.

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Does the yield curve have the ability to predict output and recessions? At some times and in certain places, of course! But when and where, which aspects of the curve matter most, and which economic forces account for the predictive ability are matters of dispute. Over the years, an increasingly sophisticated set of tools, both statistical and theoretical, has addressed the issue. For the United States, an inverted yield curve, particularly when the spread between the yield on 10-year and 3-month Treasuries becomes negative, has been a robust indicator of recessions in the post–World War II period. The spread also predicts future real GDP growth for the United States, although the forecast ability varies by time period in ways that appear to depend on monetary policy. The evidence is less clear in other countries, but the yield curve shows some predictive ability for the United Kingdom and Germany, among others. Expected final online publication date for the Annual Review of Financial Economics, Volume 13 is March 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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Financial nowcasts and their usefulness in macroeconomic forecasting

Cited by 21 publications

References 47 publications

Whose Inflation Expectations Best Predict Inflation?

Whose Inflation Expectations Best Predict Inflation?

Improving Inflation Forecasts Using Robust Measures

Does the Yield Curve Predict Output?

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