Relevant bibliographies by topics / Cointegration

Academic literature on the topic 'Cointegration'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 June 2024

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Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Journal articles on the topic "Cointegration":

1

Gallimore, Paul, J. Andrew Hansz, Wikrom Prombutr, and Ying Zhang. "International Real Estate Review." International Real Estate Review 17, no. 3 (December 31, 2014): 359–94. http://dx.doi.org/10.53383/100189.

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We investigate long-term cointegrative and short-term causal relations among seven U.S. sectoral REITs. First, cointegration tests identify one long-term cointegrative relation among five of the sectors, which suggests that two of the sectors are outside the cointegrative space. Second, short-term Granger causality tests identify three leading and two following cointegrated sectors. Third, a proposed vector autoregressive model indicates that a stronger cointegrating effect is induced by declining real estate markets and a multivariate sensitivity regression model shows that unexpected inflation significantly and negatively influences the cointegrative disequilibrium. Lastly, our cointegration-based portfolio performance analyses show that the inferior performance of the all-sector market portfolio stems from containing the redundant cointegrated sectors which shatter portfolio diversification.
2

COOK, STEVEN. "ARE STOCK PRICES AND ECONOMIC ACTIVITY COINTEGRATED? EVIDENCE FROM THE US, 1950–2005." Annals of Financial Economics 02, no. 01 (June 2006): 0650003. http://dx.doi.org/10.1142/s2010495206500035.

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The potential cointegrating relationship between stock prices and economic activity suggested by financial and economic theory is examined. It is found that the commonly employed tests of Engle and Granger (1987) and Johansen (1988) fail to detect cointegration between stock prices and industrial production for a long span of US data. In recognition of factors which may result in a failure to detect a genuine cointegrating relationship, the analysis is extended to consider higher-powered cointegration tests, tests which allow for structural change in the cointegrating relationship and tests of asymmetric cointegration. However, despite considering a range of tests, no evidence of cointegration is detected. The results therefore do not support the predictions of financial and economic theory.
3

Bernstein, David, and Bent Nielsen. "Asymptotic Theory for Cointegration Analysis When the Cointegration Rank Is Deficient." Econometrics 7, no. 1 (January 18, 2019): 6. http://dx.doi.org/10.3390/econometrics7010006.

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We consider cointegration tests in the situation where the cointegration rank is deficient. This situation is of interest in finite sample analysis and in relation to recent work on identification robust cointegration inference. We derive asymptotic theory for tests for cointegration rank and for hypotheses on the cointegrating vectors. The limiting distributions are tabulated. An application to US treasury yields series is given.
4

Aue, Alexander, Lajos Horváth, Clifford Hurvich, and Philippe Soulier. "LIMIT LAWS IN TRANSACTION-LEVEL ASSET PRICE MODELS." Econometric Theory 30, no. 3 (November 18, 2013): 536–79. http://dx.doi.org/10.1017/s0266466613000406.

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We consider pure-jump transaction-level models for asset prices in continuous time, driven by point processes. In a bivariate model that admits cointegration, we allow for time deformations to account for such effects as intraday seasonal patterns in volatility and nontrading periods that may be different for the two assets. We also allow for asymmetries (leverage effects). We obtain the asymptotic distribution of the log-price process. For the weak fractional cointegration case, we obtain the asymptotic distribution of the ordinary least squares estimator of the cointegrating parameter based on data sampled from an equally spaced discretization of calendar time, and we justify a feasible method of hypothesis testing for the cointegrating parameter based on the correspondingt-statistic. In the strong fractional cointegration case, we obtain the limiting distribution of a continuously averaged tapered estimator as well as other estimators of the cointegrating parameter, and we find that the rate of convergence can be affected by properties of intertrade durations. In particular, the persistence of durations (hence of volatility) can affect the degree of cointegration. We also obtain the rate of convergence of several estimators of the cointegrating parameter in the standard cointegration case. Finally, we consider the properties of the ordinary least squares estimator of the regression parameter in a spurious regression, i.e., in the absence of cointegration.
5

Kim, Soohyeon, and Surim Oh. "Impact of US Shale Gas on the Vertical and Horizontal Dynamics of Ethylene Price." Energies 13, no. 17 (August 31, 2020): 4479. http://dx.doi.org/10.3390/en13174479.

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The rise of shale resources in the United States is changing the petrochemical industries. Ethylene, the first building block of petrochemical products, is becoming the first target to be hit by the shale boom, and its shifting price dynamics needs to be explored. This study analyzes the transition of ethylene prices from crude oil to natural gas (vertical price dynamics) and investigates widening gaps among regional ethylene prices (horizontal price dynamics). To do this, we detect structural changes in cointegrating relationships and derive time-varying cointegration equations. In addition, for the long- and short-run dynamics, this study established and estimated an error correction model (ECM), with controlling, time-varying cointegrations. This study develops econometric studies by applying time-varying cointegration to nonenergy uses of fossil fuels. Thereby, our results discover that the feedstock structure of US ethylene is moving from crude oil to natural gas and that the comovement of US and Japanese prices is getting intensified.
6

Sugita, Katsuhiro. "Time Series Analysis of the US Term Structure of Interest Rates Using a Bayesian Markov Switching Cointegration Model." International Journal of Economics and Finance 9, no. 3 (February 9, 2017): 49. http://dx.doi.org/10.5539/ijef.v9n3p49.

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This paper examines the US term structure of interest rates using a Bayesian Markov switching cointegration model that allows the cointegrating vectors, the number of cointegrating rank, the risk premium, and other parameters to change when regime shifts. We find that for any pair of the interest rates there is a strong support for the cointegrating implication of the expectation hypothesis at least in a stable regime, while for some pairs of the interest rates the cointegration does not occur in a high volatility regime. We find that a Markov switching cointegration model captures regime shifts that are corresponding to high inflation regime. In high inflation regime, variance is much higher for both the long and short rates and adjustment toward equilibrium is much faster than those in the other regime.
7

Shin, Yongcheol. "A Residual-Based Test of the Null of Cointegration Against the Alternative of No Cointegration." Econometric Theory 10, no. 1 (March 1994): 91–115. http://dx.doi.org/10.1017/s0266466600008240.

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This paper proposes a residual-based test of the null of cointegration using a structural single equation model. It is shown that the limiting distribution of the test statistic for cointegration can be made free of nuisance parameters when the cointegrating relation is efficiently estimated. The limiting distributions are given in terms of a mixture of a Brownian bridge and vector Brownian motion. It is also shown that this test is consistent. Critical values are given for standard, demeaned, and detrended cases. Combining results from our test for cointegration with results from the Phillips-Ouliaris test for no cointegration, we find that there is evidence of cointegration between real consumption and real disposable income over the postwar period.
8

Bierens, Herman J., and Luis F. Martins. "TIME-VARYING COINTEGRATION." Econometric Theory 26, no. 5 (March 5, 2010): 1453–90. http://dx.doi.org/10.1017/s0266466609990648.

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In this paper we propose a time-varying vector error correction model in which the cointegrating relationship varies smoothly over time. The Johansen setup is a special case of our model. A likelihood ratio test for time-invariant cointegration is defined and its asymptotic chi-square distribution is derived. We apply our test to the purchasing power parity hypothesis of international prices and nominal exchange rates, and we find evidence of time-varying cointegration.
9

LEAN, HOOI HOOI, PARESH NARAYAN, and RUSSELL SMYTH. "EXCHANGE RATE AND STOCK PRICE INTERACTION IN MAJOR ASIAN MARKETS: EVIDENCE FOR INDIVIDUAL COUNTRIES AND PANELS ALLOWING FOR STRUCTURAL BREAKS." Singapore Economic Review 56, no. 02 (June 2011): 255–77. http://dx.doi.org/10.1142/s0217590811004250.

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This article examines the relationship between exchange rates and stock prices in eight Asian countries. We test for cointegration and Granger causality for both individual countries using the Gregory and Hansen cointegration test that accommodates a structural break in the cointegrating vector, and for a panel using the Westerlund panel Lagrange multiplier (LM) cointegration test that allows for multiple structural breaks in the level of the individual cointegrating equations. Our results for individual countries suggest that the only country for which exchange rates and stock prices are cointegrated over the entire period is Korea where there is a weak long-run unidirectional Granger causality running from exchange rates to stock prices. Employing the panel LM cointegration test with multiple structural breaks, we find that exchange rates and stock prices are not cointegrated. We conclude that for the eight Asian countries, exchange rates and stock prices primarily have only a contemporaneous effect on each other that is reflected in the short-run intertemporal comovements between these financial variables.
10

Dao, Phong B. "On Cointegration Analysis for Condition Monitoring and Fault Detection of Wind Turbines Using SCADA Data." Energies 16, no. 5 (March 1, 2023): 2352. http://dx.doi.org/10.3390/en16052352.

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Cointegration theory has been recently proposed for condition monitoring and fault detection of wind turbines. However, the existing cointegration-based methods and results presented in the literature are limited and not encouraging enough for the broader deployment of the technique. To close this research gap, this paper presents a new investigation on cointegration for wind turbine monitoring using a four-year SCADA data set acquired from a commercial wind turbine. A gearbox fault is used as a testing case to validate the analysis. A cointegration-based wind turbine monitoring model is established using five process parameters, including the wind speed, generator speed, generator temperature, gearbox temperature, and generated power. Two different sets of SCADA data were used to train the cointegration-based model and calculate the normalized cointegrating vectors. The first training data set involves 12,000 samples recorded before the occurrence of the gearbox fault, whereas the second one includes 6000 samples acquired after the fault occurrence. Cointegration residuals—obtained from projecting the testing data (2000 samples including the gearbox fault event) on the normalized cointegrating vectors—are used in control charts for operational state monitoring and automated fault detection. The results demonstrate that regardless of which training data set was used, the cointegration residuals can effectively monitor the wind turbine and reliably detect the fault at the early stage. Interestingly, despite using different training data sets, the cointegration analysis creates two residuals which are almost identical in their shapes and trends. In addition, the gearbox fault can be detected by these two residuals at the same moment. These interesting findings have never been reported in the literature.
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Journal articles Dissertations / Theses Books

Dissertations / Theses on the topic "Cointegration":

1

Löf, Mårten. "On seasonality and cointegration." Doctoral thesis, Handelshögskolan i Stockholm, Ekonomisk Statistik (ES), 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-614.

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This thesis, which consists of four essays, focus on seasonal and periodic cointegration models. These models are tools to describe changing seasonality.Essay 1 "Forecasting performance of seasonal cointegration models", with Johan Lyhagen. Forecasts from two different seasonal cointegration specifications are compared in an empirical forecasting example and in a Monte Carlo study. One of the two specifications include a certain parameter restriction at the annual frequency, wheras the other specification is more general. In the empirical forecasting example we also include a standard cointegration model based on first differences and seasonal dummies and analyze the effects of restricting or not restricting seasonal dummies in the seasonal cointegration models. While the Monte Carlo results favor the general specification, and definitely so if larger sample sizes are considered, we do not find such clear cut evidence in the empirical example.Essay 2 "On forecasting cointegrated seasonal time series", with Philip Hans Franses. In this essay we analyze periodic and seasonal cointegration models for bivariate quarterly observed time series in an empirical forecasting study. We include both single equation and multiple equations methods for those two classes of models. A VAR model in first differences, with and without cointegration restrictions, and a VAR model in annual differences are also included in the analysis, where they serve as benchmark models. Our empirical results indicate that the VAR model in first differences without cointegration is best if one-step ahead forecasts are considered. For longer forecast horizons however, the VAR model in annual differences is better. When comparing periodic versus seasonal cointegration models, we find that the seasonal cointegration models tend to yield better forecasts. Essay 3 "Size and power of the likelihood ratio test for seasonal cointegration in small samples: A Monte Carlo study", This essay investigates the small sample size and power properties of the likelihood ratio test in the seasonal error correction model. Two specifications of the model at the annual frequency are analyzed. One is more restricted (RS), designed for the particular case of 'synchronous cointegration', whereas the other specification is general (GS). The results indicate that RS has poor size properties in cases where non-synchronous cointegration clearly should play a role. There is a risk of finding 'evidence' of too many cointegrating vectors at the annual frequency when using RS. On the other hand, if the restriction is almost satisfied, the general specification looses power at least for small sample sizes, while tests in RS have good properties. Essay 4 "On seasonal error correction when the processes include different numbers of unit roots", with Johan Lyhagen. We propose a seasonal error correction model (SECM) for quarterly data which includes variables with different numbers of unit roots and thus needs to be transformed in different ways in order to yield stationarity. A Monte Carlo simulation is carried out to investigate the consequences of specifying a SECM with all variables in annual diffrerences in this situation. The SECM in annual differences is compared to the correctly specified model. Pre-testing for unit roots using two different approaches, and where the models are specified according to the unit root test results, is also considered. The results indicate that, in practice, a cointegration model where all variables are transformed with the annual difference filter is more robust than one obtained by pre-testing for a smaller number of unit roots.
Diss. Stockholm : Handelshögsk., 2001 [4], iv s., s. 1-23: sammanfattning, s. 25-110, [5] s.: 4 uppsatser
2

Löf, Mårten. "On seasonality and cointegration /." Stockholm : Economic Research Institute, Stockholm School of Economics (Ekonomiska forskningsinstitutet vid Handelshögsk.) (EFI), 2001. http://www.hhs.se/efi/summary/556.htm.

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3

Pashourtidou, Nicoletta. "Cointegration in misspecified models." Thesis, University of Southampton, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.252324.

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Clements, Michael P. "Cointegration and dynamic econometric modelling." Thesis, University of Oxford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334980.

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Giese, Julia V. "Essays in Applied Cointegration Analysis." Thesis, University of Oxford, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.517139.

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Huber, Florian, and Thomas Zörner. "Threshold cointegration and adaptive shrinkage." WU Vienna University of Economics and Business, 2017. http://epub.wu.ac.at/5577/1/wp250.pdf.

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This paper considers Bayesian estimation of the threshold vector error correction (TVECM) model in moderate to large dimensions. Using the lagged cointegrating error as a threshold variable gives rise to additional difficulties that are typically solved by relying on large sample approximations. Relying on Markov chain Monte Carlo methods we circumvent these issues by avoiding computationally prohibitive estimation strategies like the grid search. Due to the proliferation of parameters we use novel global-local shrinkage priors in the spirit of Griffin and Brown (2010). We illustrate the merits of our approach in an application to five exchange rates vis-á-vis the US dollar and assess whether a given currency is over or undervalued. Moreover, we perform a forecasting comparison to investigate whether it pays off to adopt a non-linear modeling approach relative to a set of simpler benchmark models.
Series: Department of Economics Working Paper Series
7

Schmidt, Arlen David. "Pairs Trading: A Cointegration Approach." Thesis, Discipline of Finance, 2009. http://hdl.handle.net/2123/4072.

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This study uses the Johansen test for cointegration to select trading pairs for use within a pairs trading framework. A long-run equilibrium price relationship is then estimated for the identified trading pairs, and the resulting mean-reverting residual spread is modeled as a Vector-Error-Correction model (VECM). The study uses 5 years of daily stock prices starting from the beginning of July, 2002. The search for trading pairs is restricted to 17 financial stocks listed on the ASX200. The results show that two cointegrated stocks can be combined in a certain linear combination so that the dynamics of the resulting portfolio are governed by a stationary process. Although a trading rule is not employed to access the profitability of this trading strategy, plots of the residual series show a high rate of zero crossings and large deviations around the mean. This would suggest that this strategy would likely be profitable. It can also be concluded that in the presence of cointegration, at least one of the speed of adjustment coefficients must be significantly different from zero.
8

Örsal, Deniz Dilan Karaman. "Essays on panel cointegration testing." Doctoral thesis, Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät, 2009. http://dx.doi.org/10.18452/15894.

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Diese Dissertation beinhaltet vier Aufsätze, die zur Literatur der Panelkointegrationsmethodik beitragen. Der erste Aufsatz vergleicht die Eigenschaften der vier Residuen-basierten Panelkointegrationstests von Pedroni (1995, 1999) mit dem Likelihood-basierten Panelkointegrationstest von Larsson et al. (2001) in endlichen Stichproben. Die Simulationsergebnisse zeigen, dass unter den fünf untersuchten Panelkointegrationsteststatistiken die Panel-t Teststatistik von Pedroni (1995, 1999) die besten Eigenschaften in endlichen Stichproben besitzt. Der zweite Aufsatz präsentiert eine Korrektur des Beweises von Larsson et al. (2001) bezüglich der Endlichkeit der Momente der asymptotischen Trace-Statistik für den Fall, dass die Differenz zwischen der Anzahl der Variablen und der Anzahl der existierenden Kointegrationsbeziehungen eins ist. Im dritten Aufsatz wird ein neuer Likelihood-basierter Panelkointegrationstest vorgestellt, der die Existenz eines linearen Trends in dem datengenerierenden Prozess erlaubt. Dieser neue Test ist eine Erweiterung des Likelihood-Quotienten-Tests von Saikkonen und Lütkepohl (2000a) für trendbereinigte Daten auf die Paneldatenanalyse. Unter der Nullhypothese folgt die Panel-SL Teststatistik einer standardisierten Normalverteilung, wenn die Anzahl der Beobachtungen über die Zeit (T) und die Anzahl der Querschnitte (N) sequentiell gegen unendlich gehen. In einer Monte-Carlo-Studie werden die Eigenschaften des Panel-SL Tests in endlichen Stichproben untersucht. Der neue Test hat ein annehmbares empirisches Signifikanzniveau für wachsende T und N sowie eine hohe Güte in kleinen Stichproben. Der letzte Aufsatz der Dissertation analysiert die langfristige Geldnachfragefunktion in OECD Ländern mit Hilfe von Paneleinheitswurzel- und Panelkointegrationstests. Um eine mögliche Existenz einer stationären langfristigen Geldnachfragefunktion zu untersuchen, werden der Panel-SL Kointegrationstest und die Tests von Pedroni (1999) verwendet. Im Anschluss daran wird eine Paneldatenschätzung für die Geldnachfragefunktion mittels der dynamischen Kleinste-Quadrate-Methode von Mark und Sul (2003) durchgeführt.
This thesis is composed of four essays which contribute to the literature in panel cointegration methodology. The first essay compares the finite sample properties of the four residual-based panel cointegration tests of Pedroni (1995, 1999) and the likelihood-based panel cointegration test of Larsson et al. (2001). The simulation results indicate that the panel-t test statistic of Pedroni has the best finite sample properties among the five panel cointegration test statistics evaluated. The second essay presents a corrected version of the proof of Larsson et al. (2001) related to the finiteness of the moments of the asymptotic trace statistic. The proof is corrected for the case, in which the difference between the number of variables and the number of existing cointegrating relations is one. The third essay proposes a new likelihood-based panel cointegration test in the presence of a linear time trend in the data generating process. This new test is an extension of the likelihood ratio test of Saikkonen and Lütkepohl (2000) for trend-adjusted data to the panel data framework, and is called the panel SL test. Under the null hypothesis, the panel SL test statistic is standard normally distributed as the number of time periods (T) and the number of cross-sections (N) tend to infinity sequentially. By means of a Monte Carlo study the finite sample properties of the test are investigated. The new test presents reasonable size with the increase in T and N, and has high power in small samples. The last essay of the thesis analyzes the long-run money demand relation among OECD countries by panel unit root and cointegration testing techniques. The panel SL cointegration test and the tests of Pedroni (1999) are used to detect the existence of a stationary long-run money demand relation. Moreover, the money demand function is estimated with the panel dynamic ordinary least squares method of Mark and Sul (2003).
9

ARMILLOTTA, EMANUELE. "Issues in Nonlinear Cointegration Modelling." Doctoral thesis, Università Politecnica delle Marche, 2017. http://hdl.handle.net/11566/251236.

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In letteratura sempre maggiore è l’attenzione rivolta ai modelli di cointegrazione non lineari. Nella struttura a termine dei tassi di interesse i modelli a soglia permettono di considerare quei fattori, come i premi per il rischio variabili, i costi di transazione e gli interventi di politica monetaria, che ostacolano l’aggiustamento attorno l’equilibrio di lungo periodo. Nel contesto del mercato obbligazionario statunitense viene indagata la capacità di un modello che ammette una maggior flessibilità di approssimare le dinamiche non lineari del meccanismo di aggiustamento soprattutto in occasione degli ultimi avvenimenti finanziari ed economici. Nonostante la semplicità di questo modello alcune tra la più significative problematiche si riscontrano in ambito asintotico. In letteratura non vi è alcuna teoria generale per i modelli di cointegrazione non lineari, ma viene di volta in volta ridefinita per ogni singola famiglia di modelli. In questa tesi vengono investigate alcune proprietà asintotiche del modello considerato sia cercando di collegare alcuni dei risultati principali sia ricorrendo a tecniche di simulazione.
Literature is paying more and more attention to nonlinear cointergration models. In the term of structure of interest rates, threshold models consider all elements, such as time variables risk premium, transaction costs and monetary policy interventions, that prevent the adjustment towards long-run equilibrium. I analysed the performance of a framework that allows more flexibility to approximate non linear dynamics in the adjustment mechanism in the US bond market and I paid attention to the last international financial and economic events. Although the model is straightforward, there are some problems with its asymptotic proprieties. In literature there is not any general asymptotic theory for the nonlinear cointegration models, because it is always redefined and at the end there is a specific theorem for each family of models. So I investigated on the limit distribution test of this nonlinear model by putting in connection some of the most important results already present in literature and by using simulation methods.
10

Göttfert, Joline. "Cointegration among cryptocurrencies : A cointegration analysis of Bitcoin, Bitcoin Cash, EOS, Ethereum, Litecoin and Ripple." Thesis, Umeå universitet, Nationalekonomi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-161079.

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The purpose of this paper is to examine if there is cointegration between the daily closing price of the cryptocurrency Bitcoin and five other cryptocurrencies; Ethereum, Ripple, Bitcoin Cash, EOS and Litecoin in five different time periods, all ending April 9, 2019. To test if there is a long-run relationship between Bitcoin and these mentioned cryptocurrencies, two different tests for cointegration are applied; the Engle-Granger two step approach and Johansen’s cointegration test as well as a Vector Error Correction Model (VECM). The results from both cointegration tests suggest that Bitcoin is cointegrated with Bitcoin Cash, Ethereum, Litecoin and Ripple. The Johansen test and the Engle-Granger method for cointegration demonstrate that Bitcoin and EOS do not have any cointegrating relationship. Another finding is that, based on the results from the VECM estimation, the price of Bitcoin has a statistically significant long-run impact on the prices of Bitcoin Cash, Ethereum, Litecoin and Ripple.
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Books on the topic "Cointegration":

1

Rao, B. Bhaskara, ed. Cointegration. London: Palgrave Macmillan UK, 1994. http://dx.doi.org/10.1007/978-1-349-23529-2.

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2

Hansen, Peter Reinhard. Workbook on cointegration. Oxford [England]: Oxford University Press, 1998.

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Tsolaki, E. Cointegration in time series. Manchester: UMIST, 1996.

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Hussain, Shakir. On cointegration and persistence. Stockholm, Sweden: Almqvist & Wiksell International, 1995.

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Fund, International Monetary, ed. Cointegration and long-horizon forecasting. Washington, D.C: International Monetary Fund, 1997.

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1939-, Bhaskara Rao B., ed. Cointegration for the applied economist. New York: St. Martin's Press, 1994.

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Davidson, James E. H. Cointegration in linear dynamic systems. London: London School of Economics and Political Science, 1986.

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Hendry, David F. Cointegration and dynamics in economics. Amsterdam: North-Holland, 1997.

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Hylleberg, Svend. Cointegration and error correction mechanisms. Aarhus, Denmark: Institute of Economics, University of Aarhus, 1988.

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Christoffersen, Peter F. Cointegration and long-horizon forecasting. Philadelphia: Federal Reserve Bank of Philadelphia, Economic Research Division, 1997.

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Book chapters on the topic "Cointegration":

1

Rao, B. Bhaskara. "Editor’s Introduction." In Cointegration, 1–8. London: Palgrave Macmillan UK, 1994. http://dx.doi.org/10.1007/978-1-349-23529-2_1.

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Dickey, David A., Dennis W. Jansen, and Daniel L. Thornton. "A Primer on Cointegration with an Application to Money and Income." In Cointegration, 9–45. London: Palgrave Macmillan UK, 1994. http://dx.doi.org/10.1007/978-1-349-23529-2_2.

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Holden, Darryl, and Roger Perman. "Unit Roots and Cointegration for the Economist." In Cointegration, 47–112. London: Palgrave Macmillan UK, 1994. http://dx.doi.org/10.1007/978-1-349-23529-2_3.

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Perron, Pierre. "Trend, Unit Root and Structural Change in Macroeconomic Time Series." In Cointegration, 113–46. London: Palgrave Macmillan UK, 1994. http://dx.doi.org/10.1007/978-1-349-23529-2_4.

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Mehra, Yash P. "Wage Growth and the Inflation Process: An Empirical Approach." In Cointegration, 147–59. London: Palgrave Macmillan UK, 1994. http://dx.doi.org/10.1007/978-1-349-23529-2_5.

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Otto, Glenn. "Diagnostic Testing: An Application to the Demand for M1." In Cointegration, 161–84. London: Palgrave Macmillan UK, 1994. http://dx.doi.org/10.1007/978-1-349-23529-2_6.

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Kirchgässner, Gebhard, Jürgen Wolters, and Uwe Hassler. "Cointegration." In Introduction to Modern Time Series Analysis, 205–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33436-8_6.

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Kirchgässner, Gebhard, and Jürgen Wolters. "Cointegration." In Introduction to Modern Time Series Analysis, 199–239. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73291-4_6.

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Burgess, A. Neil. "Cointegration." In Perspectives in Neural Computing, 181–91. London: Springer London, 2002. http://dx.doi.org/10.1007/978-1-4471-0151-2_21.

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Zivot, Eric, and Jiahui Wang. "Cointegration." In Modeling Financial Time Series with S-Plus®, 415–60. New York, NY: Springer New York, 2003. http://dx.doi.org/10.1007/978-0-387-21763-5_12.

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Conference papers on the topic "Cointegration":

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Diniz, M., C. A. B. Pereira, J. M. Stern, Marcelo de Souza Lauretto, Carlos Alberto de Bragança Pereira, and Julio Michael Stern. "FBST for Cointegration Problems." In BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING: Proceedings of the 28th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering. AIP, 2008. http://dx.doi.org/10.1063/1.3038994.

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Xia, Zeyu, and Changle Lin. "Cointegration identification with metric learning." In Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), edited by Yuanchang Zhong. SPIE, 2023. http://dx.doi.org/10.1117/12.2667621.

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Özmen, Mehmet, and Sera Şanlı. "Seasonal Cointegration Approach on Expenditure Based Gross Domestic Product and Its Some Sub-Components for Turkey." In International Conference on Eurasian Economies. Eurasian Economists Association, 2017. http://dx.doi.org/10.36880/c09.01980.

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In this study, it has been aimed to investigate the existence of co-integration relationship between quarterly gross domestic product (GDP), final consumption expenditures of resident households (CONS), exports of goods and services (EXP), government final consumption expenditures (GOV) and private sector machinery-equipment (PRIEQ) series for the period 1998Q1-2014Q4 for Turkey. Since, Engle and Granger (1987) cointegration test does not take unit roots at seasonal frequencies into account; seasonal cointegration approach proposed by Engle, Granger, Hylleberg and Lee (EGHL) (1993) has been conducted in order to be able to detect the long-run equilibrium relationship among variables which are integrated at the same seasonal frequency. With the aim of determining the stationarity order of series, HEGY seasonal unit root test has been applied. Consequently, there has been found a cointegrating relationship only between GDP and GOV series at quarterly frequencies for only the auxiliary regression including constant term and seasonal dummies.
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Dao, P. B. "Cointegration Modelling for Health and Condition Monitoring of Wind Turbines - An Overview." In Floating Offshore Energy Devices. Materials Research Forum LLC, 2022. http://dx.doi.org/10.21741/9781644901731-2.

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Abstract. The cointegration method has recently attracted a growing interest from scientists and engineers as a promising tool for the development of wind turbine condition monitoring systems. This paper presents a short review of cointegration-based techniques developed for condition monitoring and fault detection of wind turbines. In all reported applications, cointegration residuals are used in control charts for condition monitoring and early failure detection. This is known as the residual-based control chart approach. Vibration signals and SCADA data are typically used with cointegration in these applications. This is due to the fact that vibration-based condition monitoring is one of the most common and effective techniques (used for wind turbines); and the use of SCADA data for condition monitoring and fault detection of wind turbines has become more and more popular in recent years.
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WORDEN, KEITH, and ELIZABETH J. CROSS. "ON ENGLE-GRANGER COINTEGRATION USING TREED GAUSSIAN PROCESSES." In Structural Health Monitoring 2023. Destech Publications, Inc., 2023. http://dx.doi.org/10.12783/shm2023/37058.

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Over the last decade or so, cointegration has emerged as arguably the state-of-the-art in terms of removing Environmental and Operational Variations (EOVs) from structural health monitoring (SHM) data. When data channels share common trends which can be removed by linear projection, the Johansen procedure, a maximum-likelihood approach developed within the field of econometrics, is provably optimal. Unfortunately, SHM problems can present where the trends occupy a nonlinear submanifold of the feature space, and in this case, linear cointegration/projection fails. It is still possible to make progress in this case by moving to the older Engle-Granger approach to cointegration, where one linearly regresses one of the feature space variables on the others; nonlinear cointegration is then ‘simply’ the application of an appropriate nonlinear regressor. Over the years, a number of nonlinear regression algorithms have been applied, motivated by machine learning or evolutionary computation; each with pros and cons. The aim of the current paper is to demonstrate an approach based on Treed Gaussian Processes (TGP); the advantage being that the algorithm allows switching between cointegration models in different parts of the feature space. Examination of the switching points can provide insight into the physical processes driving the nonlinearity. The approach is demonstrated here on the well-known Z24 Bridge data set, where the ambient temperature drives EOVs which cannot be removed by linear methods.
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Şanlı, Sera, and Mehmet Özmen. "A Different Look at Cointegration Relationship between Quarterly Inflation Rates and Growth via Seasonal Integration Tests." In International Conference on Eurasian Economies. Eurasian Economists Association, 2019. http://dx.doi.org/10.36880/c11.02293.

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Detecting the direction of inflation-growth relationship has been a controversial issue in terms of the theoretical framework, notedly since the rise of Mundell-Tobin effect which is based upon the assumption of substitutability between money and capital. In this study, it has been aimed to investigate the cointegrating relationship and its direction between inflation and economic growth covering the period 1998Q1:2014Q4 for Turkey as grounded on the testing sequence that is illustrated by Ilmakunnas (1990) in order to handle unit root testing in a seasonal context by testing the appropriate order of differencing and concerns with the case where SI(2,1) (seasonally integrated of order (2,1)) is the maximum order of seasonal integration. It has been also utilized from ADF unit root test and DHF, HEGY & OCSB seasonal unit root tests in seasonal integration analysis. In the study, five cointegration regressions have been considered in the level, seasonally averaged, quarterly differenced, first differenced and twice differenced forms and two series have been found to have the same degree of seasonal integration as SI(1,1). Applying various residual tests have revealed the presence of a cointegrating relationship between two variables. In addition, the inflation-growth relationship in Turkey has been concluded to perform in an opposite direction.
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Hongming Yang, Enfeng He, Xiaojiao Tong, and Zhuo-wa Luo. "Panel cointegration modelling and forecasting of power tariff." In 2008 5th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE). IEEE, 2008. http://dx.doi.org/10.1109/iceee.2008.4723387.

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Mohan, Anusree, and P. Balasubramanian. "Factors affecting inflation in India: A cointegration approach." In 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2015. http://dx.doi.org/10.1109/icacci.2015.7275717.

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Chun Ping, Chang, and Lee Chien-Chiang. "Multivariate Panel Cointegration Models and Money Demand Function." In 9th Joint Conference on Information Sciences. Paris, France: Atlantis Press, 2006. http://dx.doi.org/10.2991/jcis.2006.154.

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Jawadi, Fredj, and Patrick Leoni. "Threshold Cointegration Relationships between Oil and Stock Markets." In 2009 International Conference on Management and Service Science (MASS). IEEE, 2009. http://dx.doi.org/10.1109/icmss.2009.5301962.

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Reports on the topic "Cointegration":

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Christoffersen, Peter, and Francis Diebold. Cointegration and Long-Horizon Forecasting. Cambridge, MA: National Bureau of Economic Research, October 1997. http://dx.doi.org/10.3386/t0217.

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Müller, Ulrich, and Mark Watson. Low-Frequency Robust Cointegration Testing. Cambridge, MA: National Bureau of Economic Research, August 2009. http://dx.doi.org/10.3386/w15292.

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Campbell, John, and Robert Shiller. Cointegration and Tests of Present Value Models. Cambridge, MA: National Bureau of Economic Research, April 1986. http://dx.doi.org/10.3386/w1885.

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Bansal, Ravi, Robert Dittmar, and Dana Kiku. Cointegration and Consumption Risks in Asset Returns. Cambridge, MA: National Bureau of Economic Research, May 2007. http://dx.doi.org/10.3386/w13108.

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Engle, Robert, and Joao Victor Issler. Estimating Sectoral Cycles Using Cointegration and Common Features. Cambridge, MA: National Bureau of Economic Research, November 1993. http://dx.doi.org/10.3386/w4529.

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Flórez, Luz Adriana, Karen L. Pulido-Mahecha, and Mario Andrés Ramos-Veloza. Okun´s law in Colombia: a non-linear cointegration. Bogotá, Colombia: Banco de la República, February 2018. http://dx.doi.org/10.32468/be.1039.

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Hall, Stephen. Time-Series Methods: Dynamic Modeling, Non-Stationarity, and Cointegration. Instats Inc., 2023. http://dx.doi.org/10.61700/vksf9usteps6f469.

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This seminar provides a hands-on exploration of time-series methods useful for econometrics as well as social and health science research. Any modelling exercise involving time series data depends crucially on the correct treatment of any non-stationarity which may be present in the data. The seminar explores the developments in dynamic modelling and non-stationarity which have taken place over the last 50 years in Econometrics, including in-depth coverage types of non-stationarity and tests for them, including cointegrated relationships (shared trends) among multiple variables. A free version of the EViews software can be. An Instats certificate of completion is provided at the conclusion of the seminar. For European PhD students, the seminar offers 2 ECTS Equivalent points.
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Hall, Stephen. Time-Series Methods: Dynamic Modeling, Non-Stationarity, and Cointegration. Instats Inc., 2022. http://dx.doi.org/10.61700/nyrm5o8t47qqa469.

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Abstract:
This seminar provides a hands-on exploration of time-series methods useful for econometrics as well as social and health science research. Any modelling exercise involving time series data depends crucially on the correct treatment of any non-stationarity which may be present in the data. The seminar explores the developments in dynamic modelling and non-stationarity which have taken place over the last 50 years in Econometrics, including in-depth coverage types of non-stationarity and tests for them, including cointegrated relationships (shared trends) among multiple variables. A free version of the EViews software can be [url=https://register1.eviews.com/demo/][u]downloaded here[/u][/url]. An Instats certificate of completion is provided at the conclusion of the seminar. For European PhD students, the seminar offers 2 ECTS Equivalent points.
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Melo-Velandia, Luis Fernando, John Jairo León, and Dagoberto Saboyá. Cointegration vector estimation by dols for a three-dimensional panel. Bogotá, Colombia: Banco de la República, December 2007. http://dx.doi.org/10.32468/be.474.

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Horvath, Michael T., and Mark Watson. Testing for Cointegration When Some of the Contributing Vectors are Known. Cambridge, MA: National Bureau of Economic Research, December 1994. http://dx.doi.org/10.3386/t0171.

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