A new fractional integration approach based on neural network nonlinearity with an application to testing unemployment hysteresis
Bibliographic Data
| ID | 21542226 |
|---|---|
| Authors | Fumitaka Furuoka (0000-0003-1863-387X, University of Malaya), Luis A Gil-Alana (0000-0002-5760-3123, Universidad Francisco de Vitoria, corresponding author), Olaoluwa S Yaya (0000-0002-7554-3507, University of Ibadan), Elayaraja Aruchunan (0000-0002-4629-0483, University of Malaya), Ahamuefula E Ogbonna (0000-0002-9127-5231, University of Ibadan) |
| Year | 2024 |
| Volume | 66 |
| Issue | 6 |
| Pages | 2471-2499 |
| Publication date | 2024-06-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Empirical Economics (JOURNAL) |
| Journal identifiers | ISSN: 0377-7332 • E-ISSN: 1435-8921 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s00181-023-02540-5 |
| OpenAlex | W4390502867 |
| Language | EN |
| Citations received | 4 |
| References cited | 75 |
This paper proposes a nonlinear fractional unit root approach which is known as the autoregressive neural network–fractional integration (ARNN–FI) test. This new fractional integration test is based on a new multilayer perceptron of a neural network process, proposed in Yaya et al. (Oxf Bull Econ Stat 83(4):960–981, 2021). The asymptotic theory and the properties of the proposed test are given. By setting up a Monte Carlo simulation experiment, the simulation results reveal that as the number of observations increases, size and power distortions would disappear in the test. The empirical application based on this new test reveals that the unemployment rates of three European countries are neither stationary nor mean-reverting in line with the hysteresis hypothesis
Artificial neural network · Autoregressive model · Econometrics · Economics · Hysteresis · Mean reversion · Monte Carlo method · Nonlinear system · Physics · Statistics · Unit root · Unit root test · Computer Science · Economic theories and models · Market Dynamics and Volatility · Mathematics · Monetary Policy and Economic Impact · Applied Mathematics · Artificial Intelligence
Breaking the panels
LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power
The Estimation and Application of Long Memory Time Series Models
A Stationarity Test in the Presence of an Unknown Number of Smooth Breaks
Testing for a unit root in the nonlinear STAR framework
The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis
Distribution of the Estimators for Autoregressive Time Series With a Unit Root
Efficient Tests of Nonstationary Hypotheses
Efficient Tests for an Autoregressive Unit Root
Unit root tests in panel data
Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root
Testing for unit roots in heterogeneous panels
Testing for a unit root in time series regression
Testing the null hypothesis of stationarity against the alternative of a unit root
Unemployment hysteresis in Middle East and North Africa countries
A New Unit Root Test for Unemployment Hysteresis Based on the Autoregressive Neural Network
Tests for Asymmetry in Possibly Nonstationary Time Series Data
Unit-Root Tests and Asymmetric Adjustment With an Example Using the Term Structure of Interest Rates
Markov Regime Switching and Unit-Root Tests
Multiple Trend Breaks and the Unit-Root Hypothesis
Hysteresis and the European Unemployment Problem
| Citations per year | 4 |
|---|---|
| Citation span | 2025 - 2025 (1) |
| Highly cited | No |