A similarity-based approach for macroeconomic forecasting

TY - JOUR

T1 - A similarity-based approach for macroeconomic forecasting

AU - Dendramis, Y.

AU - Kapetanios, G.

AU - Marcellino, M.

PY - 2020/6/1

Y1 - 2020/6/1

N2 - In the aftermath of the recent financial crisis there has been considerable focus on methods for predicting macroeconomic variables when their behaviour is subject to abrupt changes, associated for example with crisis periods. We propose similarity-based approaches as a way to handle parameter instability and apply them to macroeconomic forecasting. The rationale is that clusters of past data that match the current economic conditions can be more informative for forecasting than the entire past behaviour of the variable of interest. We apply our methods to predict both simulated data in a set of Monte Carlo experiments, and a broad set of key US macroeconomic indicators. The forecast evaluation exercises indicate that similarity-based approaches perform well, in general, in comparison with other common time-varying forecasting methods, and particularly well during crisis episodes.

AB - In the aftermath of the recent financial crisis there has been considerable focus on methods for predicting macroeconomic variables when their behaviour is subject to abrupt changes, associated for example with crisis periods. We propose similarity-based approaches as a way to handle parameter instability and apply them to macroeconomic forecasting. The rationale is that clusters of past data that match the current economic conditions can be more informative for forecasting than the entire past behaviour of the variable of interest. We apply our methods to predict both simulated data in a set of Monte Carlo experiments, and a broad set of key US macroeconomic indicators. The forecast evaluation exercises indicate that similarity-based approaches perform well, in general, in comparison with other common time-varying forecasting methods, and particularly well during crisis episodes.

KW - Empirical similarity

KW - Forecast comparison

KW - Kernel estimation

KW - Macroeconomic forecasting

KW - Parameter time variation

UR - http://www.scopus.com/inward/record.url?scp=85086030670&partnerID=8YFLogxK

U2 - 10.1111/rssa.12574

DO - 10.1111/rssa.12574

M3 - Article

AN - SCOPUS:85086030670

SN - 0964-1998

VL - 183

SP - 801

EP - 827

JO - Journal of the Royal Statistical Society. Series A: Statistics in Society

JF - Journal of the Royal Statistical Society. Series A: Statistics in Society

IS - 3

ER -