A New unit root test for unemployment hysteresis based on the autoregressive neural network*
Document Type
Article
Publication Date
8-1-2021
Abstract
This paper proposes a nonlinear unit root test based on the autoregressive neural network process for testing unemployment hysteresis. In this new unit root testing framework, the linear, quadratic and cubic components of the neural network process are used to capture the nonlinearity in a given time series data. The theoretical properties of the test are developed, while the size and the power properties are examined in a Monte Carlo simulation study. Various empirical applications with unemployment and inflation rates across a number of countries are carried out at the end of the article.
Keywords
Neural network, Monte Carlo simulation, Mathematical Methods
Divisions
aei
Funders
Spanish Government European Commission[ECO2017-85503-R],Universidad Francisco de Vitoria,Tun Ismail Ali Chair Research Grant[TIACRG2018.23]
Publication Title
Oxford Bulletin of Economics and Statistics
Volume
83
Issue
4
Publisher
Wiley
Publisher Location
111 RIVER ST, HOBOKEN 07030-5774, NJ USA