Forecasting using a random coefficient autoregression

Abstract We consider point forecasts for economic time series using a basic random coefficient autoregression. We show using simulations that these point forecasts do not improve much on the point forecasts from fixed coefficient autoregressive models. Various empirical illustrations emphasize the simulations-based evidence.

Authors

Institutions

Publication Details

Journal
Empirical Economics
Published
2025-09-24
DOI
https://doi.org/10.1007/s00181-025-02824-y
Primary Topic
Financial Risk and Volatility Modeling
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Forecasting using a random coefficient autoregression

Philip Hans Franses, Dmitriy Knyazhitskiy
Empirical Economics
Financial Risk and Volatility Modeling
article

Forecasting using a random coefficient autoregression

Philip Hans Franses, Dmitriy Knyazhitskiy
article en

Abstract

Abstract We consider point forecasts for economic time series using a basic random coefficient autoregression. We show using simulations that these point forecasts do not improve much on the point forecasts from fixed coefficient autoregressive models. Various empirical illustrations emphasize the simulations-based evidence.

Empirical EconomicsVol. 69(6)
Tinbergen Institute (NL)
Openalex Percentile: Top 66%
Financial Risk and Volatility Modeling
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Forecasting using a random coefficient autoregression — Philip Hans Franses, Dmitriy Knyazhitskiy · Empirical Economics (2025) | TGRS Research Map | TGRS