Department of Economics and Business Economics

Forecaster’s utility and forecasts coherence

Research output: Working paperResearch

Standard

Forecaster’s utility and forecasts coherence. / Chini, Emilio Zanetti.

Aarhus : Institut for Økonomi, Aarhus Universitet, 2018.

Research output: Working paperResearch

Harvard

Chini, EZ 2018 'Forecaster’s utility and forecasts coherence' Institut for Økonomi, Aarhus Universitet, Aarhus.

APA

Chini, E. Z. (2018). Forecaster’s utility and forecasts coherence. Aarhus: Institut for Økonomi, Aarhus Universitet. CREATES Research Papers, No. 2018-01

CBE

Chini EZ. 2018. Forecaster’s utility and forecasts coherence. Aarhus: Institut for Økonomi, Aarhus Universitet.

MLA

Chini, Emilio Zanetti Forecaster’s utility and forecasts coherence. Aarhus: Institut for Økonomi, Aarhus Universitet. (CREATES Research Papers; Journal number 2018-01). 2018., 46 p.

Vancouver

Chini EZ. Forecaster’s utility and forecasts coherence. Aarhus: Institut for Økonomi, Aarhus Universitet. 2018 Jan 9.

Author

Chini, Emilio Zanetti. / Forecaster’s utility and forecasts coherence. Aarhus : Institut for Økonomi, Aarhus Universitet, 2018. (CREATES Research Papers; No. 2018-01).

Bibtex

@techreport{b920f721bd46459f9f3d0d660852218f,
title = "Forecaster’s utility and forecasts coherence",
abstract = "I provide general frequentist framework to elicit the forecaster’s expected utility based on a Lagrange Multiplier-type test for the null of locality of the scoring rules associated to the probabilistic forecast. These are assumed to be observed transition variables in a nonlinear autoregressive model to ease the statistical inference. A simulation study reveals that the test behaves consistently with the requirements of the theoretical literature. The locality of the scoring rule is fundamental to set dating algorithms to measure and forecast probability of recession in US business cycle. An investigation of Bank of Norway’s forecasts on output growth leads us to conclude that forecasts are often suboptimal with respect to some simplistic benchmark if forecaster’s reward is not properly evaluated.",
keywords = "Business Cycle, Evaluation, Locality Testing, Nonlinear Time Series, Predictive Density, Scoring Rules, Scoring Structures",
author = "Chini, {Emilio Zanetti}",
year = "2018",
month = "1",
day = "9",
language = "English",
publisher = "Institut for {\O}konomi, Aarhus Universitet",
type = "WorkingPaper",
institution = "Institut for {\O}konomi, Aarhus Universitet",

}

RIS

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T1 - Forecaster’s utility and forecasts coherence

AU - Chini,Emilio Zanetti

PY - 2018/1/9

Y1 - 2018/1/9

N2 - I provide general frequentist framework to elicit the forecaster’s expected utility based on a Lagrange Multiplier-type test for the null of locality of the scoring rules associated to the probabilistic forecast. These are assumed to be observed transition variables in a nonlinear autoregressive model to ease the statistical inference. A simulation study reveals that the test behaves consistently with the requirements of the theoretical literature. The locality of the scoring rule is fundamental to set dating algorithms to measure and forecast probability of recession in US business cycle. An investigation of Bank of Norway’s forecasts on output growth leads us to conclude that forecasts are often suboptimal with respect to some simplistic benchmark if forecaster’s reward is not properly evaluated.

AB - I provide general frequentist framework to elicit the forecaster’s expected utility based on a Lagrange Multiplier-type test for the null of locality of the scoring rules associated to the probabilistic forecast. These are assumed to be observed transition variables in a nonlinear autoregressive model to ease the statistical inference. A simulation study reveals that the test behaves consistently with the requirements of the theoretical literature. The locality of the scoring rule is fundamental to set dating algorithms to measure and forecast probability of recession in US business cycle. An investigation of Bank of Norway’s forecasts on output growth leads us to conclude that forecasts are often suboptimal with respect to some simplistic benchmark if forecaster’s reward is not properly evaluated.

KW - Business Cycle, Evaluation, Locality Testing, Nonlinear Time Series, Predictive Density, Scoring Rules, Scoring Structures

M3 - Working paper

BT - Forecaster’s utility and forecasts coherence

PB - Institut for Økonomi, Aarhus Universitet

CY - Aarhus

ER -