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Assessing Point Forecast Bias Across Multiple Time Series : Measures and Visual Tools

Davydenko, Andrey; Goodwin, Paul - 2021

Measuring bias is important as it helps identify flaws in quantitative forecasting methods or judgmental forecasts. It … can, therefore, potentially help improve forecasts. Despite this, bias tends to be under represented in the literature …: many studies focus solely on measuring accuracy. Methods for assessing bias in single series are relatively well known and …

Persistent link: https://www.econbiz.de/10013314570

Identifying modern macro equations with old shocks

Barnichon, Régis; Mesters, Geert - 2019

Persistent link: https://www.econbiz.de/10012167326

Essays on consumption and expected returns

Yogo, Motohiro - 2004

Persistent link: https://www.econbiz.de/10003387664

Rounding bias in forecast uncertainty

Levenko, Natalia - In: Research in economics : an international review of economics 74 (2020) 4, pp. 277-291

Persistent link: https://www.econbiz.de/10012590377

Mean Squared Prediction Error Reduction with Instrumental Variables

Michis, Antonis - 2016

The mean squared prediction error of the linear regression model is examined when estimation is performed with instrumental variables. It is shown that increasing the number of instruments in the estimation procedure, can reduce the mean squared prediction error of the model through more...

Persistent link: https://www.econbiz.de/10012985339

Forecasting Total Energy’s CO2 Emissions

Iania, Leonardo; Algieri, Bernardina; Leccadito, Arturo - 2022

In recent years, the international community has been increasing its efforts to reduce the human footprint on air pollution and global warming. Total CO2 emissions are a key component of global emissions, and as such, they are closely monitored by national and supranational entities. This study...

Persistent link: https://www.econbiz.de/10014083572

Technological Interdependencies Predict Innovation Dynamics

Pichler, Anton; Lafond, Francois; Farmer, J. Doyne - 2020

We propose a simple model where the innovation rate of a technological domain depends on the innovation rate of the technological domains it relies on. Using data on US patents from 1836 to 2017, we make out-of-sample predictions and fond that the predictability of innovation rates can be...

Persistent link: https://www.econbiz.de/10014101485

Probabilistic Forecasting with Stationary VAR Models

Mojab, Ramin - 2016

I use a set of vector autoregressive models to forecast some of the main macroeconomic variables in a wide range of countries. The goal is to provide some insight about different forecast accuracy measures in a probabilistic forecasting framework. The countries are selected based on their...

Persistent link: https://www.econbiz.de/10012985801

The Macroeconomic Imbalance Procedure : A Useful Tool for Predicting Sovereign Crises?

Arahuetes García, Alfredo - 2018

This paper provides an empirical analysis of the Macroeconomic Imbalance Procedure (MIP). It explores the relationship between sovereign bond yields spreads and the variables contained in the MIP scoreboard using quantile regressions. Results suggest that MIP indicators can explain the behavior...

Persistent link: https://www.econbiz.de/10012916737

A Neural Network Extension of the Lee-Carter Model to Multiple Populations

Richman, Ronald - 2018

The Lee-Carter model is a basic approach to forecasting mortality rates of a single population. Although extensions of the Lee-Carter model to forecasting rates for multiple populations have recently been proposed, the structure of these extended models is hard to justify and the models are...

Persistent link: https://www.econbiz.de/10012909106