scholarly journals Spurious Regression

2009 ◽  
Vol 2009 ◽  
pp. 1-27 ◽  
Author(s):  
D. Ventosa-Santaulària

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.

2017 ◽  
Vol 6 (6) ◽  
pp. 127
Author(s):  
Ed Herranz ◽  
James Gentle ◽  
George Wang

Many financial time series are nonstationary and are modeled as ARIMA processes; they are integrated processes (I(n)) which can be made stationary (I(0)) via differencing n times. I(1) processes have a unit root in the autoregressive polynomial. Using OLS with unit root processes often leads to spurious results; a cointegration analysis should be used instead. Unit root tests (URT) decrease spurious cointegration. The Augmented Dickey Fuller (ADF) URT fails to reject a false null hypothesis of a unit root under the presence of structural changes in intercept and/or linear trend. The Zivot and Andrews (ZA) (1992) URT was designed for unknown breaks, but not under the null hypothesis. Lee and Strazicich (2003) argued the ZA URT was biased towards stationarity with breaks and proposed a new URT with breaks in the null. When an ARMA(p,q) process with trend and/or drift that is to be tested for unit roots and has changepoints in trend and/or intercept two approaches that can be taken: One approach is to use a unit root test that is robust to changepoints. In this paper we consider two of these URT's, the Lee-Strazicich URT and the Hybrid Bai-Perron ZA URT(Herranz, 2016.)  The other approach we consider is to remove the deterministic components with changepoints using the Bai-Perron breakpoint detection method (1998, 2003), and then use a standard unit root test such as ADF in each segment. This approach does not assume that the entire time series being tested is all I(1) or I(0), as is the case with standard unit root tests. Performances of the tests were compared under various scenarios involving changepoints via simulation studies.  Another type of model for breaks, the Self-Exciting-Threshold-Autoregressive (SETAR) model is also discussed.


1996 ◽  
Vol 11 (2) ◽  
pp. 277-303 ◽  
Author(s):  
Chunchi Wu ◽  
Chihwa Kao ◽  
Cheng F. Lee

This paper investigates the time-series properties of a wide range of corporate financial and accounting series. Unit root tests developed by Dickey and Fuller (1979) are applied to these series. The results support the hypothesis that most of these series contain both permanent (random walk) and transitory components. The results show that most financial series are dominated by a random walk component. However, for some series, such as net sales, net income, earnings per share, and returns on investments, there is a relatively significant stationary component, which suggests the presence of successful smoothing for these series. We show that smoothing may reduce volatility of financial series but it cannot produce a deterministic growth trend. Implications of nonstationarity for financial modeling are explored.


Nova Economia ◽  
2005 ◽  
Vol 15 (3) ◽  
pp. 145-176 ◽  
Author(s):  
Gilberto A. Libanio

The theme of unit roots in macroeconomic time series has received a great amount of theoretical and applied research in the last two decades. This paper presents some of the main issues regarding unit root tests, explores some of the implications for macroeconomic theory and policy, and reviews the recent evidence on the presence of unit roots in GDP series for Latin American countries. We conclude that a consensual view on many of the aspects involved has not emerged from this literature.


2019 ◽  
Vol 78 (308) ◽  
pp. 120
Author(s):  
Mesut Turkay ◽  
Burak Sencer Atasoy

<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.


2021 ◽  
Vol 15 (1) ◽  
pp. 72-84
Author(s):  
Vicente Esteve ◽  
Maria A. Prats

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.


Author(s):  
David McDowall ◽  
Richard McCleary ◽  
Bradley J. Bartos

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.


2012 ◽  
Vol 28 (5) ◽  
pp. 1121-1143 ◽  
Author(s):  
Tomás del Barrio Castro ◽  
Denise R. Osborn ◽  
A.M. Robert Taylor

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.


1994 ◽  
Vol 10 (5) ◽  
pp. 917-936 ◽  
Author(s):  
Joon Y. Park ◽  
Jaewhan Sung

This paper considers the unit root tests in models with structural change. Particular attention is given to their dependency on the limiting ratios of the subsample sizes between breaks. The dependency is analyzed in detail, and the invariant testing procedure based on a transformed model is developed. The required transformation is essentially identical to the generalized least-squares correction for heteroskedasticity. The limiting distributions of the new tests do not depend on the relative sizes of the subsamples and are shown to be simple mixtures of the limiting distributions of the corresponding tests from the independent unit root models without structural change.


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