Quantile Aggregation of Density Forecasts

Busetti, Fabio

doi:10.2139/ssrn.2550809

Cited by 28 publications

(31 citation statements)

References 173 publications

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“…Manzan and Zerom (2013) argue that macroeconomic indicators are useful for predicting the distribution of US in ‡ation, while Wolters and Tillman (2015) …nd a decrease in persistence at all quantiles since the early Eighties. The distribution of euro area in ‡ation is analyzed in Busetti, Caivano, Rodano (2015), Busetti (2017), Bereau, Faubert, Schmidt (2018) and Tagliabracci (2019) with …ndings that are broadly comparable to what presented here for the case of …xed coe¢ cients.…”

Section: Introduction *supporting

confidence: 55%

“…The data for in ‡ation, GDP, import prices and nominal e¤ective exchange rate are taken from the area wide model database, while the measures of domestic and foreign output gap are those described in the previous section. Table 1 in the appendix shows the regression results for several speci…cations 8 , labelled (a) to (g); the coe¢ cients highlighted in bold are statistically signi…cant at least at the 5% level using HAC standard errors.…”

Section: Evidence From Ols Regressionsmentioning

confidence: 99%

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Domestic and Global Determinants of Inflation: Evidence from Expectile Regression

2019

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The paper investigates the role of domestic and global determinants of euro area core inflation. We analyse the entire conditional distribution of inflation by estimating a Phillips curve type relationship using an expectile regression approach, extended to capture time-varying effects. The main findings are as follows. First, both the domestic and foreign output gap are significant drivers of euro area core inflation, once external demand pressures are properly orthogonalized in a modified measure of domestic gap. However, the inflationary impact of the domestic component is relatively stronger. Second, the domestic output gap has a bigger influence in the right tail of the conditional distribution of inflation. Third, adding international price pressures in the regression weakens the link between inflation and the foreign output gap. Fourth, in a time-varying perspective, there is an increase in the response of inflation to the domestic gap in the last decade but only at the lower quantiles. Overall, the evidence on the so-called "globalization hypothesis" is mixed: while the pass-through to inflation of foreign prices and the exchange rate increased over time at all quantiles, the impact of global slack remained broadly stable, particularly in the central part of the distribution.

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Section: Introduction *supporting

confidence: 55%

Section: Evidence From Ols Regressionsmentioning

confidence: 99%

Domestic and Global Determinants of Inflation: Evidence from Expectile Regression

2019

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“…For further discussion, theoretical results and motivation for alternatives to the linear opinion pool such as the "trimmed linear pool", that seek to trim away from the combination forecasts with low or high means, or cumulative distribution function values, in order to decrease the variance, see Grushka-Cockayne et al (2017). 3 Quantile aggregation has also received some attention, with a macroeconomic application illustrating its utility provided by Busetti (2017); quantile aggregation involves taking a (perhaps weighted) linear combination of the i = 1, ..., N quantile functions rather than their inverse as in the linear opinion pool. For further analysis within management science/decision analysis see, for example , Lichtendahl Jr. et al (2013) and Hora et al (2013).…”

Section: A Digression Outside Economicsmentioning

confidence: 99%

The Evolution of Forecast Density Combinations in Economics

Aastveit¹,

Mitchell

Ravazzolo

et al. 2018

SSRN Journal

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Increasingly, professional forecasters and academic researchers present model-based and subjective or judgment-based forecasts in economics which are accompanied by some measure of uncertainty. In its most complete form this measure is a probability density function for future values of the variables of interest. At the same time combinations of forecast densities are being used in order to integrate information coming from several sources like experts, models and large micro-data sets. Given this increased relevance of forecast density combinations, the genesis and evolution of this approach, both inside and outside economics, is explored. A fundamental density combination equation is specified which shows that various frequentist as well as Bayesian approaches give different specific contents to this density. In its most simplistic case, it is a restricted finite mixture, giving fixed equal weights to the various individual densities. The specification of the fundamental density combination is made more flexible in recent literature. It has evolved from using simple average weights to optimized weights and then to 'richer' procedures that allow for time-variation, learning features and model incompleteness. The recent history and evolution of forecast density combination methods, together with their potential and benefits, are illustrated in a policy making environment of central banks.

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“…for a suitable choice of w. Note that the use of quantile averages as aggregate models has been proposed (although not in connection with the variational approach related to the 2-Wasserstein distance) in [12] and [13].…”

Section: Connection Of the Proposed Scheme With Existing Aggregation mentioning

confidence: 99%

A learning algorithm for source aggregation

Papayiannis

Yannacopoulos

2016

Math Methods in App Sciences

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The problem of model aggregation from various information sources of unknown validity is addressed in terms of a variational problem in the space of probability measures. A weight allocation scheme to the various sources is proposed, which is designed to lead to the best aggregate model compatible with the available data and the set of prior measures provided by the information sources. Copyright © 2016 John Wiley & Sons, Ltd.

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Quantile Aggregation of Density Forecasts

Cited by 28 publications

References 173 publications

Domestic and Global Determinants of Inflation: Evidence from Expectile Regression

Domestic and Global Determinants of Inflation: Evidence from Expectile Regression

The Evolution of Forecast Density Combinations in Economics

A learning algorithm for source aggregation

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