Measuring business cycles: Empirical evidence based on an unobserved component approach

Huthaifa Alqaralleh,Juan Sapena

doi:10.1080/23322039.2019.1571692

Abstract

We adopt an unobserved components time series model to track the business cycles in the G7 countries using the Industrial production index over the period from 1:1961 to 8:2017. The advantage of ad...

Highlights

The variations in economic fortune and economic instability associated with business boom and bust draw much attention to the economic situation all over the world
It is striking that our analysis shows that the industrial production index captures the classical characteristics of the business cycle
Denoted by yi;t 1⁄4 log Yi;t an industrial production index for country i observed at t, the unobserved component model (UCM) decomposes such series into unobserved cycle-trend components

Summary

Introduction

The variations in economic fortune and economic instability associated with business boom and bust draw much attention to the economic situation all over the world. The framework proposed in the present paper takes on board the contribution of high frequency over an extended period to account for most of the fluctuation in the economies under consideration In line with this picture, our aim here is, first, to extract the classical cycle by dating the peaks and troughs and investigating the characteristics of the business cycle at a higher frequency for the G7 countries. We adapt the work presented in Galati, Hindrayanto, Koopman, and Vlekke (2016) to extract such cycles, based on an unobserved components time series model (UCTSM) Such a decomposition technique is useful in studying cyclical movement because it tends to model fat tails data using a driven parameter through the Kalman filter (Durbin & Koopman, 2012; Harvey & Trimbur, 2003).

Model-based filters approach

Data and empirical results

Findings

Conclusions