The Performance of Variance Ratio Unit Root Tests Under Nonlinear Stationary TAR and STAR Processes: Evidence from Monte Carlo Simulations and Applications

2007 ◽  
Vol 31 (1) ◽  
pp. 77-94 ◽  
Author(s):  
Daiki Maki
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Unit Root ◽  
Unit Root Tests ◽  
Variance Ratio ◽  
Ratio Unit

scholarly journals ARE UNIT ROOT TESTS USEFUL IN THE DEBATE OVER THE (NON)STATIONARITY OF HOURS WORKED?

2013 ◽  
Vol 19 (1) ◽  
pp. 167-188
Author(s):  
Amélie Charles ◽  
Olivier Darné ◽  
Fabien Tripier
Keyword(s):  
Monte Carlo ◽  
Business Cycle ◽  
Monte Carlo Simulations ◽  
Unit Root ◽  
Unit Root Tests ◽  
Cycle Model ◽  
Hours Worked ◽  
Simulated Series ◽  
Business Cycle Model ◽  
The Business Cycle

The performance of unit root tests on simulated series is compared, using the business-cycle model of Chang et al. [Journal of Money, Credit and Banking39(6), 1357–1373 (2007)] as a data-generating process. Overall, Monte Carlo simulations show that the efficient unit root tests of Ng and Perron (NP) [Econometrica69(6), 1519–1554 (2001)] are more powerful than the standard unit root tests. These efficient tests are frequently able (i) to reject the unit-root hypothesis on simulated series, using the best specification of the business-cycle model found by Chang et al., in which hours worked are stationary with adjustment costs, and (ii) to reduce the gap between the theoretical impulse response functions and those estimated with a Structural VAR model. The results of Monte Carlo simulations show that the hump-shaped behavior of data can explain the divergence between unit root tests.

scholarly journals Wavelet energy ratio unit root tests

2016 ◽  
Vol 38 (1) ◽  
pp. 69-94 ◽  
Author(s):  
Mirza Trokić
Keyword(s):  
Unit Root ◽  
Unit Root Tests ◽  
Energy Ratio ◽  
Wavelet Energy ◽  
Ratio Unit

Regime-switching purchasing power parity in Latin America: Monte Carlo unit root tests with dynamic conditional score

2016 ◽  
Vol 48 (29) ◽  
pp. 2675-2696
Author(s):  
Astrid Ayala ◽  
Szabolcs Blazsek ◽  
Juncal Cuñado ◽  
Luis Albériko Gil-Alana
Keyword(s):  
Monte Carlo ◽  
Latin America ◽  
Purchasing Power Parity ◽  
Unit Root ◽  
Regime Switching ◽  
Unit Root Tests ◽  
Purchasing Power ◽  
Power Parity

MULTIPLE TESTING FOR OUTPUT CONVERGENCE

2012 ◽  
Vol 18 (1) ◽  
pp. 199-214 ◽  
Author(s):  
Thomas Deckers ◽  
Christoph Hanck
Keyword(s):  
Monte Carlo ◽  
Unit Root ◽  
Multiple Testing ◽  
Unit Root Tests ◽  
Testing Problem ◽  
Testing Techniques ◽  
Per Capita ◽  
Definition Of ◽  
Output Gaps ◽  
Capita Output

This paper tests for output convergence across n = 51 economies, employing the definition of Pesaran [Journal of Econometrics 138, 312–355 (2007)]. The definition requires output gaps to be stationary around a constant mean. But when all n(n − 1)/2 pairs of log per capita output gaps are considered, this results in more than 1,000 unit root tests to be conducted. Hence, because of the ensuing multiplicity of the testing problem, a nontrivial number of output gaps will be falsely declared to be stationary when each of the n(n − 1)/2 hypotheses is tested at some conventional level like 5%. To solve the problem, we employ recent multiple testing techniques that allow us to bound the expected fraction of false rejections at a desired level. Monte Carlo results illustrate the usefulness of the techniques. The empirical results show that the data do not support the notion of output convergence after controlling for multiplicity.

Sign in / Sign up

Export Citation Format

Share Document