scholarly journals Modeling seasonality: An extension of the HEGY approach in the presence of two structural breaks

2008 ◽  
Vol 55 (4) ◽  
pp. 465-484 ◽  
Author(s):  
Ozlem Tasseven
Keyword(s):  
Structural Breaks ◽  
Structural Changes ◽  
Unit Roots ◽  
Testing Procedure ◽  
Small Sample ◽  
Seasonal Unit Roots ◽  
Monte Carlo Experiments ◽  
Turkish Economy ◽  
Annual Frequency ◽  
Break Points

In this paper the HEGY testing procedure (Hylleberg et al. 1990) of analyzing seasonal unit roots is tried to be re-examined by allowing for seasonal mean shifts with exogenous break points. Using some Monte Carlo experiments the distribution of the HEGY and the extended HEGY tests for seasonal unit roots subject to mean shifts and the small sample behavior of the test statistics have been investigated. Based on an empirical analysis upon the conventional money demand relationships in the Turkish economy, our results indicate that seasonal unit roots appear for the GDP deflator, real M2 and the expected inflation variables while seasonal unit roots at annual frequency seem to be disappear for the real M1 balances when the possible structural changes in one or more seasons at 1994 and 2001 crisis years have been taken into account. .

DETECTING FOR SMOOTH STRUCTURAL CHANGES IN GARCH MODELS

2015 ◽  
Vol 32 (3) ◽  
pp. 740-791 ◽  
Author(s):  
Bin Chen ◽  
Yongmiao Hong
Keyword(s):  
Structural Breaks ◽  
Structural Changes ◽  
Garch Model ◽  
Parametric Bootstrap ◽  
Garch Models ◽  
Time Varying ◽  
Finite Samples ◽  
Time Varying Parameter ◽  
Break Points ◽  
Quasi Maximum Likelihood

Detecting and modeling structural changes in GARCH processes have attracted increasing attention in time series econometrics. In this paper, we propose a new approach to testing structural changes in GARCH models. The idea is to compare the log likelihood of a time-varying parameter GARCH model with that of a constant parameter GARCH model, where the time-varying GARCH parameters are estimated by a local quasi-maximum likelihood estimator (QMLE) and the constant GARCH parameters are estimated by a standard QMLE. The test does not require any prior information about the alternatives of structural changes. It has an asymptotic N(0,1) distribution under the null hypothesis of parameter constancy and is consistent against a vast class of smooth structural changes as well as abrupt structural breaks with possibly unknown break points. A consistent parametric bootstrap is employed to provide a reliable inference in finite samples and a simulation study highlights the merits of our test.

scholarly journals Characterizing growth instability: new evidence on unit roots and structural breaks in countries’ long run trajectories

2021 ◽  
Author(s):  
Emanuele Russo ◽  
Neil Foster-McGregor
Keyword(s):  
Unit Root ◽  
Structural Breaks ◽  
Structural Changes ◽  
Alternative Hypothesis ◽  
Unit Root Test ◽  
Unit Roots ◽  
Finite Sample ◽  
Aggregate Shocks ◽  
Long Run ◽  
Finite Sample Properties

AbstractIn this paper we investigate whether long run time series of income per capita are better described by a trend-stationary model with few structural changes or by unit root processes in which permanent stochastic shocks are responsible for the observed growth discontinuities. For a group of advanced and developing countries in the Maddison database, we employ a unit root test that allows for an unspecified number of breaks under the alternative hypothesis (up to some ex ante determined maximum). Monte Carlo simulations studying the finite sample properties of the test are reported and discussed. When compared with previous findings in the literature, our results show less evidence against the unit root hypothesis. We find even fewer rejections when relaxing the assumption of Gaussian shocks. Our results are broadly consistent with the implications of evolutionary macro models which posit frequent growth shifts and fat-tailed distribution of aggregate shocks.

The Nature of Seasonality in Spanish Tourism Time Series

2005 ◽  
Vol 11 (4) ◽  
pp. 483-499 ◽  
Author(s):  
J. Cunado ◽  
L.A. Gil-Alana ◽  
F. Péarez de Gracia
Keyword(s):  
Time Series ◽  
White Noise ◽  
Unit Roots ◽  
Testing Procedure ◽  
Fractional Differentiation ◽  
Integrated Models ◽  
Seasonal Unit Roots ◽  
Long Run ◽  
Noise Disturbances ◽  
Hotel Accommodation

This paper deals with the analysis of seasonality in the context of tourism time series. The authors present a general testing procedure that permits them to consider the cases of deterministic and/or stochastic (with integer and fractional differentiation) seasonality in a unified treatment. The procedure is applied to four Spanish tourism time series: the total (foreign and domestic) number of tourists, the number of domestic tourists, the number of nights spent in hotel accommodation by tourists, and the number of nights spent in hotel accommodation by domestic tourists. The results show that the series can be well described in terms of seasonally fractionally integrated models, with the orders of integration ranging between 0.4 and 0.6 in the case of white noise disturbances, and values slightly smaller with autocorrelated disturbances. Thus the standard practice of taking seasonal dummies (deterministic seasonality) or integer differentiation (seasonal unit roots) may lead to erroneous conclusions about the stochastic behaviour of the series. Moreover, the series seem to be mean reverting, implying that shocks affecting them disappear in the long run though at a very slow hyperbolic rate.

scholarly journals Structural Breaks in Time Series

2019 ◽  
Author(s):  
Alessandro Casini ◽  
Pierre Perron
Keyword(s):  
Structural Breaks ◽  
Structural Changes ◽  
Linear Models ◽  
Forecast Accuracy ◽  
Unit Roots ◽  
Practical Applications ◽  
Endogenous Regressors ◽  
Recent Developments ◽  
Computational Aspects ◽  
Direct Use

This article covers methodological issues related to estimation, testing, and computation for models involving structural changes. Our aim is to review developments as they relate to econometric applications based on linear models. Substantial advances have been made to cover models at a level of generality that allow a host of interesting practical applications. These include models with general stationary regressors and errors that can exhibit temporal dependence and heteroskedasticity, models with trending variables and possible unit roots and cointegrated models, among others. Advances have been made pertaining to computational aspects of constructing estimates, their limit distributions, tests for structural changes, and methods to determine the number of changes present. A variety of topics are covered including recent developments: testing for common breaks, models with endogenous regressors (emphasizing that simply using least-squares is preferable over instrumental variables methods), quantile regressions, methods based on Lasso, panel data models, testing for changes in forecast accuracy, factors models, and methods of inference based on a continuous records asymptotic framework. Our focus is on the so-called off-line methods whereby one wants to retrospectively test for breaks in a given sample of data and form confidence intervals about the break dates. The aim is to provide the readers with an overview of methods that are of direct use in practice as opposed to issues mostly of theoretical interest.

Convergence in per capita carbon footprint and ecological footprint for G7 countries: Evidence from panel Fourier threshold unit root test

2021 ◽  
pp. 0958305X2110114
Author(s):  
Veli Yilanci ◽  
Muhammed Sehid Gorus ◽  
Sakiru Adebola Solarin
Keyword(s):  
Unit Root ◽  
Structural Breaks ◽  
Structural Changes ◽  
Unit Root Test ◽  
G7 Countries ◽  
Convergence Hypothesis ◽  
International Climate ◽  
Per Capita ◽  
Nonlinear Behaviors ◽  
Nonlinear Unit Root Tests

This paper aims to explore the convergence of per capita carbon and ecological footprints in G7 countries during 1961–2016. For this purpose, we propose a new unit root test in the panel setting–the panel Fourier threshold unit root test. This test takes into consideration both multiple smooth structural changes and nonlinearity. According to the literature, the power of the nonlinear unit root tests is reduced in the case of ignoring structural breaks. Therefore, we expect to get more reliable empirical findings by utilizing this methodology. The empirical results of this paper show that these series have nonlinear behaviors for the period 1961–2016. Furthermore, they demonstrate that the absolute convergence hypothesis is valid in G7 countries for both regimes. Thus, governments can conduct common environmental policies, including international climate summits and agreements, instead of national-based policies to mitigate environmental deterioration in their countries.

scholarly journals Interbase-FRET binding assay for pre-microRNAs

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mattias Bood ◽  
Anna Wypijewska del Nogal ◽  
Jesper R. Nilsson ◽  
Fredrik Edfeldt ◽  
Anders Dahlén ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Drug Targets ◽  
Structural Changes ◽  
Small Sample Size ◽  
Resonance Energy ◽  
Small Sample ◽  
Titration Calorimetry ◽  
Drug Candidate ◽  
Binding Studies ◽  
Aberrant Expression

AbstractThe aberrant expression of microRNAs (miRs) has been linked to several human diseases. A promising approach for targeting these anomalies is the use of small-molecule inhibitors of miR biogenesis. These inhibitors have the potential to (i) dissect miR mechanisms of action, (ii) discover new drug targets, and (iii) function as new therapeutic agents. Here, we designed Förster resonance energy transfer (FRET)-labeled oligoribonucleotides of the precursor of the oncogenic miR-21 (pre-miR-21) and used them together with a set of aminoglycosides to develop an interbase-FRET assay to detect ligand binding to pre-miRs. Our interbase-FRET assay accurately reports structural changes of the RNA oligonucleotide induced by ligand binding. We demonstrate its application in a rapid, qualitative drug candidate screen by assessing the relative binding affinity between 12 aminoglycoside antibiotics and pre-miR-21. Surface plasmon resonance (SPR) and isothermal titration calorimetry (ITC) were used to validate our new FRET method, and the accuracy of our FRET assay was shown to be similar to the established techniques. With its advantages over SPR and ITC owing to its high sensitivity, small sample size, straightforward technique and the possibility for high-throughput expansion, we envision that our solution-based method can be applied in pre-miRNA–target binding studies.

scholarly journals Sugar Prices vs. Financial Market Uncertainty in the Time of Crisis: Does COVID-19 Induce Structural Changes in the Relationship?

Agriculture ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 93
Author(s):  
Pavel Kotyza ◽  
Katarzyna Czech ◽  
Michał Wielechowski ◽  
Luboš Smutka ◽  
Petr Procházka
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Financial Market ◽  
Structural Breaks ◽  
Structural Changes ◽  
Global Financial Crisis ◽  
Market Uncertainty ◽  
Volatility Index ◽  
The Global Financial Crisis ◽  
The Relationship

Securitization of the agricultural commodity market has accelerated since the beginning of the 21st century, particularly in the times of financial market uncertainty and crisis. Sugar belongs to the group of important agricultural commodities. The global financial crisis and the COVID-19 pandemic has caused a substantial increase in the stock market volatility. Moreover, the novel coronavirus hit both the sugar market’s supply and demand side, resulting in sugar stock changes. The paper aims to assess potential structural changes in the relationship between sugar prices and the financial market uncertainty in a crisis time. In more detail, using sequential Bai–Perron tests for structural breaks, we check whether the global financial crisis and the COVID-19 pandemic have induced structural breaks in that relationship. Sugar prices are represented by the S&P GSCI Sugar Index, while the S&P 500 option-implied volatility index (VIX) is used to show stock market uncertainty. To investigate the changes in the relationship between sugar prices and stock market uncertainty, a regression model with a sequential Bai–Perron test for structural breaks is applied for the daily data from 2000–2020. We reveal the existence of two structural breaks in the analysed relationship. The first breakpoint was linked to the global financial crisis outbreak, and the second occurred in December 2011. Surprisingly, the COVID-19 pandemic has not induced the statistically significant structural change. Based on the regression model with Bai–Perron structural changes, we show that from 2000 until the beginning of the global financial crisis, the relationship between the sugar prices and the financial market uncertainty was insignificant. The global financial crisis led to a structural change in the relationship. Since August 2008, we observe a significant and negative relationship between the S&P GSCI Sugar Index and the S&P 500 option-implied volatility index (VIX). Sensitivity analysis conducted for the different financial market uncertainty measures, i.e., the S&P 500 Realized Volatility Index confirms our findings.

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