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Artículos de revistas sobre el tema "Structural breaks"

Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 25 de julio de 2025

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1

Muhammad Aslam, Atiq-ur-Rehman, Amada, and Ruqia Naz. "Comparing of Unit Root with and without Structural Breaks: A Monte Carlo Evaluation." Indus Journal of Social Sciences 1, no. 01 (2023): 23–34. https://doi.org/10.59075/ijss.v1i01.22.

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Background: The unit root became the most important feature that directed to the construction of new time series econometrics. Objectives: The study of time series structural breaks was a specific area of unit root research. Methods: Conventional procedures assume the break and apply a test accordingly. This leads to identification of spurious breaks, and therefore biased results, Lee and Strazicich, (2001). Results: We suggust an alternative strategy where we propose to test for structural breaks before applying unit root test. The debates of Structural breaks in unit root testing starts with

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2

Czech, Katarzyna. "Structural Changes in Wheat Market." Zeszyty Naukowe SGGW w Warszawie - Problemy Rolnictwa Światowego 16, no. 4 (2016): 92–98. http://dx.doi.org/10.22630/prs.2016.16.4.102.

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Time series analysis is based on the assumption of stationarity. Stationarity implies the parameters are constant over time. Structural break occurs when at least one of the parameters changes at some date. Structural breaks can lead to huge forecasting errors and unreliability of the model. Modelling structure breaks is very popular in the literature of macroeconomics and finance. However, there are still too few publications about structural breaks in agricultural market. The goal of research is to identify structural breaks in wheat prices time series. A few structural break tests are appli

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3

Ngene, Geoffrey, Ann Nduati Mungai, and Allen K. Lynch. "Long-Term Dependency Structure and Structural Breaks: Evidence from the U.S. Sector Returns and Volatility." Review of Pacific Basin Financial Markets and Policies 21, no. 02 (2018): 1850008. http://dx.doi.org/10.1142/s021909151850008x.

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The study investigates the impact of structural breaks on the long memory of daily returns and variance of 11 sectors. Using multiple sequential structural breaks tests, we uncover numerous and roughly shared structural breaks. Results from two non-parametric, three semi-parametric, and three parametric fractional differencing models using break-adjusted and break-unadjusted returns reveal incidence of short memory and anti-persistence in sector returns. Regarding variance, we find that the removal of breaks from the sector series dampens the fractional differencing parameter estimates. Theref

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4

Raifu, Isiaka Akande. "Is Tourism-Led-Growth Hypothesis Valid in the Presence of Structural Breaks?" Tourism 72, no. 2 (2024): 270–74. http://dx.doi.org/10.37741/t.72.2.11.

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This study revisited the tourism-led growth hypothesis (TLGH) in the presence of structural breaks using the structural break technique of Ditzen et al. (2021). To estimate the impact of tourism on economic growth along the identified structural breaks, we employed Fixed Effects and Feasible Generalised Least Squares methods. Findings showed four structural break dates (1999, 2004, 2009 and 2014), two of which coincided with the Global Financial Crisis (2008-2009) and the Ebola outbreak (2014). Despite the presence of structural breaks, the TLGH remains valid.

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5

Galadima, Mukhtar Danladi, and Abubakar Wambai Aminu. "STRUCTURAL BREAKS IN NATURAL GAS CONSUMPTION AND ECONOMIC GROWTH IN NIGERIA: EVIDENCE FROM NEW TIME SERIES TESTS THAT ALLOW FOR STRUCTURAL BREAKS." International Journal of New Economics and Social Sciences 9, no. 1 (2019): 275–92. http://dx.doi.org/10.5604/01.3001.0013.3049.

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This paper analyzed the issue of structural breaks in natural gas consumption and economic growth in Nigeria. The newly residual augmented least squares (RALS-LM) unit root test with breaks also known as “RALS-LM test with trend breaks and non-normal errors” proposed by Meng-Lee-Payne (2017) and the new structural breaks testing proposed by Kejriwal–Perron (2010) are among the tools used for the investi-gation. Our empirical findings provide significant evidence that the series of natural gas consumption and economic growth are stationary with one or two trend breaks. Furthermore, the investig

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6

Groothuis, Peter A., Kurt W. Rotthoff, and Mark C. Strazicich. "Structural Breaks in the Game." Journal of Sports Economics 18, no. 6 (2015): 622–37. http://dx.doi.org/10.1177/1527002515593113.

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To search for eras in a sports league, we utilize time-series tests with structural breaks in Major League Baseball performance. Using data from 1871-2010, the mean and standard deviation of four different performance measures are examined. Throughout, rather than assume that a break point is known a priori, we identify breaks endogenously from the data. Perhaps most notable among our findings, we identify a deterministic trend in mean slugging percentage with breaks in 1921 and 1992. Interestingly, these years closely coincide with the early years of the free-swinging (Babe Ruth) era and the

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7

Huang, Yirong, Liang Ding, Yan Lin, and Yi Luo. "A new approach to detect long memory by fractional integration or short memory by structural break." AIMS Mathematics 9, no. 6 (2024): 16468–85. http://dx.doi.org/10.3934/math.2024798.

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<abstract> <p>Long memory in test statistics can either originate from fractional integration or be spuriously induced by a short memory process with a structural break. This research estimated and detected long memory from the two causes by simulations and empirical analysis. The simulation results showed that fractional integration and structural break processes could demonstrate long memory properties. The 2ELW estimator was stable for fractional integration but not stable for time series with structural breaks. The modified W statistic based on 2ELW was efficient in discriminat

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8

Smith, Simon C., George Bulkley, and David S. Leslie. "Equity Premium Forecasts with an Unknown Number of Structural Breaks." Journal of Financial Econometrics 18, no. 1 (2019): 59–94. http://dx.doi.org/10.1093/jjfinec/nby034.

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Abstract Estimation of models with structural breaks usually assumes a pre-specified number of breaks. Previous models which do allow an endogenously determined number of breaks require a simple structural model, and rarely allow for information transfer across the break. We introduce a methodology that allows the number of breaks to be determined endogenously and including an economically motivated model of transition regimes between each break. We demonstrate the usefulness of our approach for forecasts of the equity premium. We find the demonstrated success of the historical average can be

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9

Skrobotov, Anton. "Time series forecasting under structural breaks." Applied Econometrics 76, no. 4 (2024): 120–39. https://doi.org/10.22394/1993-7601-2024-76-120-139.

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In this paper, we overview the forecasting methods in the presence of structural breaks. Methods for selecting a forecast window that includes the break date, weighted average methods of pre- and post-break estimators, and averaging-based methods are discussed. The considered methods are compared in terms of predictive power using Russian macroeconomic time series. The results demonstrate the superiority of forecasts that take into account the presence of break.

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10

Tsuji, Chikashi. "Structural Breaks and Volatility Spillovers: The Case of the US and Canadian Stock Markets." Journal of Management Research 11, no. 2 (2019): 30. http://dx.doi.org/10.5296/jmr.v11i2.14513.

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This paper investigates the relations of structural breaks and volatility spillovers by using the US and Canadian stock return data. Specifically, applying spillover MGARCH models without and with structural break dummy variables to the two stock returns, this study derives the following interesting evidence. (1) First, we reveal that for both the US and Canadian stock returns, the volatility persistence parameter values in our spillover MGARCH models decline when structural break dummy variables are incorporated. (2) Second, we further clarify that when we do not take structural breaks into a

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11

Jiang, Zhuhua, Walid Mensi, and Seong-Min Yoon. "Risks in Major Cryptocurrency Markets: Modeling the Dual Long Memory Property and Structural Breaks." Sustainability 15, no. 3 (2023): 2193. http://dx.doi.org/10.3390/su15032193.

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This study estimates the effects of the dual long memory property and structural breaks on the persistence level of six major cryptocurrency markets. We apply the Bai and Perron structural break test, Inclán and Tiao’s iterated cumulative sum of squares (ICSS) algorithm, and the fractionally integrated generalized autoregressive conditional heteroscedasticity (FIGARCH) model, with different distributions. The results show that long memory and structural breaks characterize the conditional volatility of cryptocurrency markets, confirming our hypothesis that ignoring structural breaks leads to a

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12

Skrobotov, Anton. "Structural breaks in cointegration models: Multivariate case." Applied Econometrics 64, no. 4 (2021): 83–106. http://dx.doi.org/10.22394/1993-7601-2021-64-83-106.

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This review discusses methods of testing for a cointegration rank in a multivariate time series in the presence of structural breaks. The review covers both the methods with known and unknown break date. Multiple breaks are also considered. The issues of testing for cointegration with a possible change in the cointegration rank over time are discussed separately.

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13

Angelini, Paolo. "Testing for structural breaks." Journal of Monetary Economics 34, no. 3 (1994): 561–66. http://dx.doi.org/10.1016/0304-3932(94)90034-5.

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14

Canarella, Giorgio, and Stephen M. Miller. "Inflation persistence and structural breaks." Journal of Economic Studies 43, no. 6 (2016): 980–1005. http://dx.doi.org/10.1108/jes-10-2015-0190.

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Purpose The purpose of this paper is to report on a sequential three-stage analysis of inflation persistence using monthly data from 11 inflation targeting (IT) countries and, for comparison, the USA, a non-IT country with a history of credible monetary policy. Design/methodology/approach First, the authors estimate inflation persistence in a rolling-window fractional-integration setting using the semiparametric estimator suggested by Phillips (2007). Second, the authors use tests for unknown structural breaks as a means to identify effects of the regime switch and the global financial crisis

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15

Hewag, Rishan Sampath, Jaafar Pyeman, and Norashida Othman. "Effect of Structural Break on Financial Development and Economic Growth Nexus in Middle-Income Countries in Asia: Moderating Role of Technological Advancements." Information Management and Business Review 15, no. 2(I)SI (2023): 205–14. http://dx.doi.org/10.22610/imbr.v15i2(i)si.3407.

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Asian countries have experienced many financial catastrophes and pandemics in the past couple of decades. Therefore, evaluating the effect of structural breaks on economies has taken substantive attention in the empirical literature. Thus, this study aims to investigate the effect of structural breaks on the Financial Development (FD) and Economic Growth (EG) of middle-income countries in Asia. The study considered the global financial crisis of 2008 as a key structural break. The sample consisted of 24 middle-income countries while the sample period was 20 years from 2000 to 2019. Technologic

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16

Burgaç Çil, Almıla, and Burhan Biçer. "Dynamics of Stock Prices and Exchange Rate with Structural Breaks and Asymmetry: Evidence From Türkiye." Ekonomi Politika ve Finans Arastirmalari Dergisi 9, no. 3 (2024): 438–61. http://dx.doi.org/10.30784/epfad.1516880.

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This study investigates the impacts of the nominal exchange rate on Turkish stock prices using a structural break cointegration test with endogenously determined multiple structural breaks and an asymmetric cointegration test for the period of 2002-2021. The study differs from previous research on this relation in two respects. First, it takes into account structural breaks in relation to both regimes and trends (C/S/T). Second, it extends the asymmetric cointegration with multiple structural breaks. The findings of structural break cointegration capture the break dates in line with the Turkis

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17

Tekin, Bilgehan, and Fatma Temelli. "The credit volume and its relations with money supply in Türkiye." Ekonomski pregled 75, no. 5 (2024): 363–79. http://dx.doi.org/10.32910/ep.75.5.1.

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Structural breaks in credit volume refer to sudden and significant changes in the extent to which credit is extended by financial institutions. These breaks can occur for various reasons, such as changes in lending standards, shifts in economic conditions, or changes in government policies. A structural break in credit volume can have important implications for the broader economy, including impacts on economic growth, inflation, and financial stability. This study focuses on multiple structural breaks and the relationship with the money supply of the credit volume of deposit banks from 2006 t

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18

Bastos, Felipe S., Elano F. Arruda, Rafael B. Barbosa, and Roberto T. Ferreira. "Speed of Reversion to PPP with Structural Breaks for Brazilian Cities." International Journal of Economics and Finance 10, no. 4 (2018): 15. http://dx.doi.org/10.5539/ijef.v10n4p15.

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This article analyzes the effect of introducing structural breaks in calculating the convergence speed of relative prices for Brazilian cities in the period from 1991.01 to 2016.11. Three structural break dates were endogenously chosen (1996.02, 2001.12 and 2010.10) and they represent different situations of the Brazilian economy, with impacts on intra-national relative prices. The convergence speed, measured by the half-life, declined by approximately 77% after controlling for these structural changes. The result was robust to changes in numeraire both for calculation of the half-life and est

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19

Chib, Siddhartha, and Simon C. Smith. "Factor Selection and Structural Breaks." Finance and Economics Discussion Series, no. 2024-037 (May 2024): 1–47. http://dx.doi.org/10.17016/feds.2024.037.

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We develop a new approach to select risk factors in an asset pricing model that allows the set to change at multiple unknown break dates. Using the six factors displayed in Table 1 since 1963, we document a marked shift towards parsimonious models in the last two decades. Prior to 2005, five or six factors are selected, but just two are selected thereafter. This finding offers a simple implication for the factor zoo literature: ignoring breaks detects additional factors that are no longer relevant. Moreover, all omitted factors are priced by the selected factors in every regime. Finally, the s

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20

Li, Qiang, Liming Wang, and Fei Qiu. "Detecting the Structural Breaks in GARCH Models Based on Bayesian Method: The Case of China Share Index Rate of Return." Journal of Systems Science and Information 3, no. 4 (2015): 321–33. http://dx.doi.org/10.1515/jssi-2015-0321.

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AbstractThis paper investigates the detection for structural breaks in GARCH models based on Bayesian method. The authors firstly introduce the background and significance of this problem, then present the current situation and recent developments in this field. Because the rates of return have heavy tails, the authors present GARCH models. In this paper, the authors innovatively suppose that the error term follows standard studenttdistribution with degree of freedomvinstead of standard normal distribution. The authors give the specific description of estimation using Bayesian method, includin

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21

Abu-Bader, Suleiman, and Aamer S. Abu-Qarn. "The Relationship between GATT Membership and Structural Breaks in International Trade." Global Economy Journal 8, no. 4 (2008): 1850148. http://dx.doi.org/10.2202/1524-5861.1398.

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Using sequential structural break tests, we attempt to determine if and when a new GATT member experiences statistically significant changes in the paths of its trade with incumbent members. To test for the nature of a change, we compare the averages of the actual postbreak trade shares with the averages of the postbreak extrapolated trade shares. Should a significant structural break be detected, we compare the break year with the accession year of that country to GATT. Our results show that only a small fraction of countries experience significant positive structural breaks in their trade sh

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22

Oliveira, Fernando Nascimento, and Fernando Cesar dos Santos Cunha. "Estimando Betas de Mercado com Quebras Estruturais." Brazilian Review of Finance 15, no. 2 (2018): 251. http://dx.doi.org/10.12660/rbfin.v15n2.2017.64058.

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This study verifies the contribution of a structural break (if any) to CAPM models. Therefore, we used all the assets listed in Bovespa and New York Stock Exchange in monthly frequencies. Three famous structural breaks tests were used. The results show that structural breaks are relevant in most models for most sectors of the economy. Then, the identified structural breaks are inserted in the models and the betas of CAPM models were re-estimated. The Betas that were statistically significant were chosen and their results compared to Market Beta for each sector of the economy. The results show

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23

Perez, Maria, Marco Palma, Bridget Behe, and Charles Hall. "Structural Breaks and Future Growth of the Green Industry." Journal of Environmental Horticulture 34, no. 2 (2016): 52–55. http://dx.doi.org/10.24266/0738-2898-34.2.52.

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Every industry undergoes changes, but structural changes can abruptly and radically alter business for many firms in that industry. Identifying the substantial shifts in the green industry with regard to consumer spending can help the industry better understand its history. Using an econometric model of that same consumer spending data to look forward to the future can show firms what might lie ahead. We analyzed the personal consumption expenditures for two items measured by the U.S. Bureau of Economic Analysis to identify structural breaks in the green industry. We then conducted an economet

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24

Kumar, Saurabh, Jitendra Kumar, Vikas Kumar Sharma, and Varun Agiwal. "Random order autoregressive time series model with structural break." Model Assisted Statistics and Applications 15, no. 3 (2020): 225–37. http://dx.doi.org/10.3233/mas-200490.

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This paper deals with the problem of modelling time series data with structural breaks occur at multiple time points that may result in varying order of the model at every structural break. A flexible and generalized class of Autoregressive (AR) models with multiple structural breaks is proposed for modelling in such situations. Estimation of model parameters are discussed in both classical and Bayesian frameworks. Since the joint posterior of the parameters is not analytically tractable, we employ a Markov Chain Monte Carlo method, Gibbs sampling to simulate posterior sample. To verify the or

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25

Perron, Pierre. "Unit Roots and Structural Breaks." Econometrics 5, no. 2 (2017): 22. http://dx.doi.org/10.3390/econometrics5020022.

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26

Skrobotov, A. A. "Structural breaks in cointegration models." Applied Econometrics 63 (2021): 117–41. http://dx.doi.org/10.22394/1993-7601-2021-63-117-141.

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27

Aue, Alexander, and Lajos Horváth. "Structural breaks in time series." Journal of Time Series Analysis 34, no. 1 (2012): 1–16. http://dx.doi.org/10.1111/j.1467-9892.2012.00819.x.

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28

Caporale, Guglielmo Maria, Nikitas Pittis, and Nicola Spagnolo. "IGARCH models and structural breaks." Applied Economics Letters 10, no. 12 (2003): 765–68. http://dx.doi.org/10.1080/1350485032000138403.

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29

Smith, Jeremy, and Jesus Otero. "Structural breaks and seasonal integration." Economics Letters 56, no. 1 (1997): 13–19. http://dx.doi.org/10.1016/s0165-1765(97)00156-0.

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30

Delgado, Miguel A., and Javier Hidalgo. "Nonparametric inference on structural breaks." Journal of Econometrics 96, no. 1 (2000): 113–44. http://dx.doi.org/10.1016/s0304-4076(99)00052-4.

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31

Chou, Pin-Huang, and Kuan-Cheng Ko. "Characteristics, covariances, and structural breaks." Economics Letters 100, no. 1 (2008): 31–34. http://dx.doi.org/10.1016/j.econlet.2007.10.025.

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32

Maheu, John M., and Stephen Gordon. "Learning, forecasting and structural breaks." Journal of Applied Econometrics 23, no. 5 (2008): 553–83. http://dx.doi.org/10.1002/jae.1018.

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33

Alammar, Radwan, and Almougheer Wardeh. "The impact of macroeconomic variables on stock market returns: Evidence from a sample of Arabic countries facing political and economic instability." International Journal of Business, Economics and Management 11, no. 1 (2024): 1–18. http://dx.doi.org/10.18488/62.v11i1.3633.

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The main purpose of this study is to determine the presence and timing of the structural breaks in the stock market returns and investigate their impact on the relationship between the macroeconomic variables (namely the inflation rate, the exchange rate, the oil prices) and the stock market returns of a sample of Arab countries facing political and economic instability, namely (Syria, Egypt, Tunisia and Bahrain), during the period (2010-2020). CUSUM test is performed in order to test the presence of structural breaks in stock market indexes. In case there is evidence of structural breaks, Bai

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34

Li, Wenjie, Hao Jin, and Minghua Wu. "Online Monitoring of Structural Change Points Based on Ratio-Type Statistics." Mathematics 13, no. 8 (2025): 1315. https://doi.org/10.3390/math13081315.

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For scenarios where the type of structural break in a time series is unknown, this paper proposes a modified ratio-type test statistic to enable effective online monitoring of structural breaks, while circumventing the estimation of long-term variance. Under specific assumptions, we rigorously derive the asymptotic distribution of the test statistic under the null hypothesis and establish its consistency under the alternative hypothesis. In cases where both variance and mean breaks coexist, we introduce a refined mixed-break monitoring procedure based on the consistent estimation of breakpoint

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35

Umoru, David, Solomon Edem Effiong, Malachy Ashywel Ugbaka, et al. "Estimating effects of nominal exchange rates and oil price shocks in the presence of structural breaks." Journal of Governance and Regulation 12, no. 3 (2023): 147–62. http://dx.doi.org/10.22495/jgrv12i3art16.

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Macroeconomic stability is an objective emerging economy desired to achieve but oil price shocks and fluctuations in nominal exchange rates tend to restrain the ability of these economies to achieve such macroeconomic balance. Regrettably, exchange rates and oil price shocks are prone to have structural breaks in defined periods. We therefore, implemented a bivariate diagonal BEKK model, Zivot-Andrews and Bai-Perron breakpoint tests to evaluate the effect of exchange rates and oil price shocks in the presence of structural breaks on macroeconomic stability in developing countries. Break dates

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36

Lean, Hooi Hooi, and Russell Smyth. "Do Asian Stock Markets Follow a Random Walk? Evidence from LM Unit Root Tests with One and Two Structural Breaks." Review of Pacific Basin Financial Markets and Policies 10, no. 01 (2007): 15–31. http://dx.doi.org/10.1142/s0219091507000933.

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This paper applies univariate and panel Lagrange Multiplier (LM) unit root tests with one and two structural breaks to examine the random walk hypothesis for stock prices in eight Asian countries. The results from the univariate LM unit root tests and panel LM unit root test with one structural break suggest that stock prices in each country is characterized by a random walk, but the findings from the panel LM unit root test with two structural breaks suggest that stock prices in the eight countries are mean reverting.

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37

Emirmahmutoglu, Furkan, Tolga Omay, Syed Jawad Hussain Shahzad, and Safwan Mohd Nor. "Smooth Break Detection and De-Trending in Unit Root Testing." Mathematics 9, no. 4 (2021): 371. http://dx.doi.org/10.3390/math9040371.

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This study explores the methods to de-trend the smooth structural break processes while conducting the unit root tests. The two most commonly applied approaches for modelling smooth structural breaks namely the smooth transition and the Fourier functions are considered. We perform a sequence of power comparisons among alternative unit root tests that accommodate smooth or sharp structural breaks. The power experiments demonstrate that the unit root tests utilizing the Fourier function lead to unexpected results. Furthermore, through simulation studies, we investigate the source of such unexpec

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38

Hegerty, Scott W. "Housing loans and domestic credit in the Baltic States and Poland: Structural breaks and macroeconomic determinants." Journal of Economics and Management 42 (2020): 48–69. http://dx.doi.org/10.22367/jem.2020.42.03.

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Aim/purpose – This study examines the time-series properties of home loans and do-mestic credit in Poland and the three Baltic countries, first in the univariate sense by identifying structural breaks in the series, and then using a multivariate model to identify the key drivers of loan growth.Design/methodology/approach – Structural break tests are conducted using the method of Bai & Perron (1998), while orthgonalised VARs are used for the macroeconomic model.Findings – The Estonian and Lithuanian home lending growth series have structural breaks in 2007, preceding the onset of the 2008 G

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39

Sivri, Uğur. "Is Inflation Rate of Turkey Stationary? Evidence from Unit Root Tests with and Without Structural Breaks." Review of Economic and Business Studies 10, no. 2 (2017): 29–52. http://dx.doi.org/10.1515/rebs-2017-0053.

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AbstractTurkey has high inflation experience and in order to bring inflation rate down as well as maintaining macroeconomic stability many policy changes and reforms have been implemented. Despite some success, decreasing inflation rate is still an aim of monetary policy and price stability is still faraway. This article investigates time series properties of Turkish CPI inflation rate in both seasonally unadjusted and adjusted forms. Results of various unit root tests without structural breaks generally show that inflation rate is a nonstationary variable. This article also uses one and two b

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40

Khan, Muhammad Zaheer. "Revisiting the Environmental Kuznets Curve Hypothesis in Pakistan." Market Forces 16, no. 1 (2021): 18. http://dx.doi.org/10.51153/mf.v16i1.446.

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A number of studies have already determined the existence of inverted U-shaped environmental Kuznets curve in Pakistan however the role of structural breaks in determining the relationship is yet to be investigated. The objective of this study was to determine if the presence of possible structural breaks explain the existence of environmental Kuznets curve type relationship in Pakistan for the period 1980-2016 by using data of total energy consumption, Real GDP per capita, foreign direct investment and trade openness. For the analysis the study first used the conventional time series economet

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41

Stawiarski, Bartosz. "Selected Techniques of Detecting Structural Breaks in Financial Volatility." e-Finanse 11, no. 1 (2015): 32–43. http://dx.doi.org/10.1515/fiqf-2016-0104.

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Abstract We investigate several promising algorithms, proposed in literature, devised to detect sudden changes (structural breaks) in the volatility of financial time series. Comparative study of three techniques: ICSS, NPCPM and Cheng’s algorithm is carried out via numerical simulation in the case of simulated T-GARCH models and two real series, namely German and US stock indices. Simulations show that the NPCPM algorithm is superior to ICSS because is not over-sensitive either to heavy tails of market returns or to their serial dependence. Some signals generated by ICSS are falsely classifie

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42

Aly, Hassan Y., and Mark C. Strazicich. "Did the Global Financial Crisis of 2007-2009 Impact Economic Growth in North Africa?" Perspectives on Global Development and Technology 11, no. 4 (2012): 437–55. http://dx.doi.org/10.1163/15691497-12341235.

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Abstract In this paper, we utilize time series tests with structural breaks to test for evidence of an impact on economic growth rates in North African countries following the 2007−2009 U.S. and global financial crisis. One or two breaks in economic growth are identified in each country, except for Morocco where no break is found. However, breaks that coincide with the financial crisis are found in only two of the six countries (Libya and Mauritania), while other breaks coincide most often with earlier U.S. and EU recessions. To further examine the impact of shocks, impulse response functions

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Shameer Fahmi, Muhamad, Caroline Geetha, and Rosle Mohidin. "Testing for Unit Roots and Structural Breaks in Malaysia Unanticipated Macroeconomic Variables." Malaysian Journal of Business and Economics (MJBE) 6, no. 2 (2019): 1. https://doi.org/10.51200/mjbe.v0i0.2161.

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The objective of this study is to execute a comprehensive analysis of the unit root test and structural break in Malaysia unanticipated macroeconomic variables from January 2009 to December 2016 using an endogenous structural break. The findings obtained by using conventional regression methods without testing for the unit root in time series data might be misleading. The empirical results from the Zivot-Andrews model, which endogenously identifies the most significant structural breaks in each of the macroeconomic variables, clearly show that the null hypothesis of at least one-unit root coul

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44

Edeh, Inalegwu Akpo, Kunle Sofolabo, and Aleruchi Boniface Orji. "Evaluating the Impact of Structural Breaks on the Nexus between Natural Gas Investment and Economic Growth: Evidence from Nigeria." International Journal of Advances in Engineering and Management 7, no. 2 (2025): 613–31. https://doi.org/10.35629/5252-0702613631.

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This study examines the impact of structural breaks on the relationship between natural gas production and economic growth in Nigeria, with a focus on the 2010 policy reforms. Utilizing the Autoregressive Distributed Lag (ARDL) model, the analysis incorporates structural breaks to assess their influence on the natural gaseconomic growth nexus. Two models were estimated: One model assumed a single structural break in 2010, and the other introduced dummy variables to isolate the effects of structural changes. The findings indicate that the model that explicitly accounts for structural shifts usi

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45

Walakumbura, S. H. M. L., W. M. S. P. Weerasinghe, and T. U. I. Peiris. "Effect of Structural Breaks on Stock Market Performance during COVID-19 Period in Sri Lanka." Asian Journal of Management Studies 3, no. 2 (2024): 66–79. http://dx.doi.org/10.4038/ajms.v3i2.66.

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This study investigates the effects of structural breaks on the Colombo Stock Exchange (CSE) performance over the COVID-19 period. Stock market returns and volatility are used to proxy the stock market performance. Structural breaks were identified by using the Bai-Perron (2003) test. An ARMA (p,q) model fitted for stock returns was augmented using dummy variables for the structural breaks to measure the effect of structural breaks on stock market returns. The model was further extended as a volatility regression model (GARCH, EGARCH, or TGARCH) to measure the effect of structural breaks on st

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46

Pástor, Ľluboš, and Robert F. Stambaugh. "The Equity Premium and Structural Breaks." Journal of Finance 56, no. 4 (2001): 1207–39. http://dx.doi.org/10.1111/0022-1082.00365.

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Pendell, Dustin L., and Allen M. Featherstone. "Structural breaks and agricultural asset allocation." Agricultural Finance Review 67, no. 2 (2007): 259–78. http://dx.doi.org/10.1108/00214660780001208.

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48

Arestis, Philip, and Iris Biefang-Frisancho Mariscal. "OECD unemployment: structural breaks and stationarity." Applied Economics 32, no. 4 (2000): 399–403. http://dx.doi.org/10.1080/000368400322570.

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Dropsy, Vincent. "Real exchange rates and structural breaks." Applied Economics 28, no. 2 (1996): 209–19. http://dx.doi.org/10.1080/000368496328849.

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Kim, In-Moo. "Detecting the number of structural breaks." Economics Letters 57, no. 2 (1997): 145–48. http://dx.doi.org/10.1016/s0165-1765(97)00229-2.

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