scholarly journals TESTING FOR A UNIT ROOT IN A TIME SERIES WITH A LEVEL SHIFT AT UNKNOWN TIME

2002 ◽  
Vol 18 (2) ◽  
pp. 313-348 ◽  
Author(s):  
Pentti Saikkonen ◽  
Helmut Lütkepohl
Keyword(s):  
Time Series ◽  
Unit Root ◽  
Small Sample ◽  
Unit Root Tests ◽  
Nuisance Parameters ◽  
Level Shift ◽  
Generation Process ◽  
Data Generation ◽  
Level Shifts ◽  
Small Sample Properties

Unit root tests for time series with level shifts of general form are considered when the timing of the shift is unknown. It is proposed to estimate the nuisance parameters of the data generation process including the shift date in a first step and apply standard unit root tests to the residuals. The estimation of the nuisance parameters is done in such a way that the unit root tests on the residuals have the same limiting distributions as for the case of a known break date. Simulations are performed to investigate the small sample properties of the tests, and empirical examples are discussed to illustrate the procedure.

scholarly journals Comparison of unit root tests for time series with level shifts

2002 ◽  
Vol 23 (6) ◽  
pp. 667-685 ◽  
Author(s):  
MARKKU LANNE ◽  
HELMUT LUTKEPOHL ◽  
PENTTI SAIKKONEN
Keyword(s):  
Time Series ◽  
Unit Root ◽  
Unit Root Tests ◽  
Level Shifts

scholarly journals HAS INFLATION TARGETING BEEN SUCCESSFUL? EVIDENCE FROM UNIT ROOT TESTS

2019 ◽  
Vol 78 (308) ◽  
pp. 120
Author(s):  
Mesut Turkay ◽  
Burak Sencer Atasoy
Keyword(s):  
Time Series ◽  
Unit Root ◽  
Inflation Targeting ◽  
Inflation Rate ◽  
Unit Root Tests ◽  
Policy Framework ◽  
Panel Unit Root Tests ◽  
Panel Unit Root ◽  
The World ◽  
Monetary Policy Framework

<p class="run-in" align="center"><strong>ABSTRACT</strong></p><p>The popularity of inflation targeting has risen in the last decade and the number of countries that adopted inflation targeting as their monetary policy framework surpassed 40 by the end of 2016. This study analyzes whether inflation targeting around the world has been successful in terms of achieving the announced target and keeping inflation rate around it. We argue that a successful inflation targeting necessitates the deviation of inflation from the target be stationary. We employ both time series and panel unit root tests in order to analyze the stationarity properties of deviation of inflation from the target. Results of unit root tests provide evidence in favor of the success of inflation targeting framework around the world.</p><p align="center"><strong> </strong></p><p align="center"><strong>¿HAN SIDO EXITOSAS LAS METAS DE INFLACIÓN? RESULTADOS DE LAS PRUEBAS DE RAÍZ UNITARIA</strong></p><p class="run-in" align="center"><strong>RESUMEN</strong></p>La popularidad de las metas de inflación ha aumentado en la última década y el número de países que adoptaron metas de inflación como su marco de política monetaria sobrepasó los 40 a finales del 2016. Este estudio analiza si las metas de inflación alrededor del mundo han tenido éxito en términos de alcanzar el objetivo anunciado y mantener la tasa de inflación alrededor de su meta. Argumentamos que una meta exitosa de inflación requiere que la desviación de la inflación respecto a la meta sea estacionaria. Empleamos tanto series de tiempo como pruebas de raíz unitaria en panel con el fin de analizar las propiedades estacionarias de la desviación de la inflación en relación con el objetivo. Los resultados de las pruebas de raíz unitaria proporcionan evidencia a favor del éxito del marco de metas de inflación en todo el mundo.

scholarly journals Structural Breaks and Explosive Behavior in the Long-Run: The Case of Australian Real House Prices, 1870–2020

2021 ◽  
Vol 15 (1) ◽  
pp. 72-84
Author(s):  
Vicente Esteve ◽  
Maria A. Prats
Keyword(s):  
Time Series ◽  
Unit Root ◽  
Structural Breaks ◽  
House Prices ◽  
Unit Root Tests ◽  
Annual Data ◽  
Bubble Behavior ◽  
Long Period ◽  
Long Run ◽  
Long Time

Abstract In this article, we use tests of explosive behavior in real house prices with annual data for the case of Australia for the period 1870–2020. The main contribution of this paper is the use of very long time series. It is important to use longer span data because it offers more powerful econometric results. To detect episodes of potential explosive behavior in house prices over this long period, we use the recursive unit root tests for explosiveness proposed by Phillips et al. (2011), (2015a,b). According to the results, there is a clear speculative bubble behavior in real house prices between 1997 and 2020, speculative process that has not yet been adjusted.

Auxiliary Modeling Procedures

2019 ◽  
pp. 136-153
Author(s):  
David McDowall ◽  
Richard McCleary ◽  
Bradley J. Bartos
Keyword(s):  
Time Series ◽  
Error Correction ◽  
Unit Root ◽  
Model Building ◽  
Causal Effect ◽  
Information Criteria ◽  
Unit Root Tests ◽  
Error Correction Models ◽  
Control Time ◽  
Model Building Strategy

Chapter 5 describes three sets of auxiliary methods that have emerged as add-on supplements to the traditional ARIMA model-building strategy. First, Bayesian information criteria (BIC) can be used to inform incremental modeling decisions. BICs are also the basis for the Bayesian hypothesis tests introduced in Chapter 6. Second, unit root tests can be used to inform differencing decisions. Used appropriately, unit root tests guard against over-differencing. Finally, co-integration and error correction models have become a popular way of representing the behavior of two time series that follow a shared path. We use the principle of co-integration to define the ideal control time series. Put simply, a time series and its ideal counterfactual control time series are co-integrated up the time of the intervention. At that point, if the two time series diverge, the magnitude of their divergence is taken as the causal effect of the intervention.

scholarly journals ON AUGMENTED HEGY TESTS FOR SEASONAL UNIT ROOTS

2012 ◽  
Vol 28 (5) ◽  
pp. 1121-1143 ◽  
Author(s):  
Tomás del Barrio Castro ◽  
Denise R. Osborn ◽  
A.M. Robert Taylor
Keyword(s):  
Unit Root ◽  
Unit Roots ◽  
Linear Process ◽  
Unit Root Tests ◽  
Nuisance Parameters ◽  
Martingale Difference ◽  
Linear Processes ◽  
Seasonal Unit Roots ◽  
Null Distributions ◽  
Augmented Dickey Fuller

In this paper we extend the large-sample results provided for the augmented Dickey–Fuller test by Said and Dickey (1984, Biometrika 71, 599–607) and Chang and Park (2002, Econometric Reviews 21, 431–447) to the case of the augmented seasonal unit root tests of Hylleberg, Engle, Granger, and Yoo (1990, Journal of Econometrics 44, 215–238), inter alia. Our analysis is performed under the same conditions on the innovations as in Chang and Park (2002), thereby allowing for general linear processes driven by (possibly conditionally heteroskedastic) martingale difference innovations. We show that the limiting null distributions of the t-statistics for unit roots at the zero and Nyquist frequencies and joint F-type statistics are pivotal, whereas those of the t-statistics at the harmonic seasonal frequencies depend on nuisance parameters that derive from the lag parameters characterizing the linear process. Moreover, the rates on the lag truncation required for these results to hold are shown to coincide with the corresponding rates given in Chang and Park (2002); in particular, an o(T1/2) rate is shown to be sufficient.

scholarly journals Spurious Regression

2009 ◽  
Vol 2009 ◽  
pp. 1-27 ◽  
Author(s):  
D. Ventosa-Santaulària
Keyword(s):  
Time Series ◽  
Unit Root ◽  
Long Memory ◽  
Unit Roots ◽  
Unit Root Tests ◽  
Modern Time ◽  
Spurious Regression ◽  
Time Series Econometrics ◽  
Wide Range ◽  
Applied Macroeconomics

The spurious regression phenomenon in least squares occurs for a wide range of data generating processes, such as driftless unit roots, unit roots with drift, long memory, trend and broken-trend stationarity. Indeed, spurious regressions have played a fundamental role in the building of modern time series econometrics and have revolutionized many of the procedures used in applied macroeconomics. Spin-offs from this research range from unit-root tests to cointegration and error-correction models. This paper provides an overview of results about spurious regression, pulled from disperse sources, and explains their implications.

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