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Brendan McCabe

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. David T. Frazier & Worapree Maneesoonthorn & Gael M. Martin & Brendan P.M. McCabe, 2018. "Approximate Bayesian forecasting," Monash Econometrics and Business Statistics Working Papers 2/18, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Gunadi, Christian, 2020. "Does immigrant legalization affect crime? Evidence from deferred action for childhood arrivals in the United States," Journal of Economic Behavior & Organization, Elsevier, vol. 178(C), pages 327-353.
    2. Henri Pesonen & Umberto Simola & Alvaro Köhn‐Luque & Henri Vuollekoski & Xiaoran Lai & Arnoldo Frigessi & Samuel Kaski & David T. Frazier & Worapree Maneesoonthorn & Gael M. Martin & Jukka Corander, 2023. "ABC of the future," International Statistical Review, International Statistical Institute, vol. 91(2), pages 243-268, August.
    3. Yuri S. Popkov & Alexey Yu. Popkov & Yuri A. Dubnov & Dimitri Solomatine, 2020. "Entropy-Randomized Forecasting of Stochastic Dynamic Regression Models," Mathematics, MDPI, vol. 8(7), pages 1-20, July.
    4. Koen W. de Bock & Kristof Coussement & Arno De Caigny & Roman Slowiński & Bart Baesens & Robert N Boute & Tsan-Ming Choi & Dursun Delen & Mathias Kraus & Stefan Lessmann & Sebastián Maldonado & David , 2023. "Explainable AI for Operational Research: A Defining Framework, Methods, Applications, and a Research Agenda," Post-Print hal-04219546, HAL.
    5. David T. Frazier & Gael M. Martin & Ruben Loaiza-Maya, 2022. "Variational Bayes in State Space Models: Inferential and Predictive Accuracy," Monash Econometrics and Business Statistics Working Papers 1/22, Monash University, Department of Econometrics and Business Statistics.
    6. Gunawan, David & Kohn, Robert & Nott, David, 2021. "Variational Bayes approximation of factor stochastic volatility models," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1355-1375.
    7. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    8. Dimitris Korobilis & Davide Pettenuzzo, 2020. "Machine Learning Econometrics: Bayesian algorithms and methods," Working Papers 2020_09, Business School - Economics, University of Glasgow.
    9. Gael M. Martin & David T. Frazier & Christian P. Robert, 2020. "Computing Bayes: Bayesian Computation from 1763 to the 21st Century," Monash Econometrics and Business Statistics Working Papers 14/20, Monash University, Department of Econometrics and Business Statistics.
    10. Ruben Loaiza-Maya & Gael M Martin & David T. Frazier, 2020. "Focused Bayesian Prediction," Monash Econometrics and Business Statistics Working Papers 1/20, Monash University, Department of Econometrics and Business Statistics.
    11. Martin, Gael M. & Frazier, David T. & Maneesoonthorn, Worapree & Loaiza-Maya, Rubén & Huber, Florian & Koop, Gary & Maheu, John & Nibbering, Didier & Panagiotelis, Anastasios, 2024. "Bayesian forecasting in economics and finance: A modern review," International Journal of Forecasting, Elsevier, vol. 40(2), pages 811-839.
    12. Chaya Weerasinghe & Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier, 2023. "ABC-based Forecasting in State Space Models," Monash Econometrics and Business Statistics Working Papers 12/23, Monash University, Department of Econometrics and Business Statistics.
    13. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    14. De Bock, Koen W. & Coussement, Kristof & Caigny, Arno De & Słowiński, Roman & Baesens, Bart & Boute, Robert N. & Choi, Tsan-Ming & Delen, Dursun & Kraus, Mathias & Lessmann, Stefan & Maldonado, Sebast, 2024. "Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda," European Journal of Operational Research, Elsevier, vol. 317(2), pages 249-272.
    15. Gael M. Martin & David T. Frazier & Christian P. Robert, 2021. "Approximating Bayes in the 21st Century," Monash Econometrics and Business Statistics Working Papers 24/21, Monash University, Department of Econometrics and Business Statistics.

  2. Gael M. Martin & Brendan P.M. McCabe & David T. Frazier & Worapree Maneesoonthorn & Christian P. Robert, 2016. "Auxiliary Likelihood-Based Approximate Bayesian Computation in State Space Models," Monash Econometrics and Business Statistics Working Papers 09/16, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Patrick L. McDermott & Christopher K. Wikle & Joshua Millspaugh, 2017. "Hierarchical Nonlinear Spatio-temporal Agent-Based Models for Collective Animal Movement," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(3), pages 294-312, September.
    2. Umberto Picchini & Adeline Samson, 2018. "Coupling stochastic EM and approximate Bayesian computation for parameter inference in state-space models," Computational Statistics, Springer, vol. 33(1), pages 179-212, March.

  3. Gael M. Martin & Brendan P.M. McCabe & Worapree Maneesoonthorn & Christian P. Robert, 2014. "Approximate Bayesian Computation in State Space Models," Monash Econometrics and Business Statistics Working Papers 20/14, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Johan Dahlin & Mattias Villani & Thomas B. Schon, 2015. "Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods," Papers 1506.06975, arXiv.org, revised Jun 2017.
    2. Christian P. Robert, 2016. "Comment on: Reflections on the Probability Space Induced by Moment Conditions with Implications for Bayesian Inference," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 265-271.

  4. Jason Ng & Catherine S. Forbes & Gael M. Martin & Brendan P.M. McCabe, 2011. "Non-Parametric Estimation of Forecast Distributions in Non-Gaussian, Non-linear State Space Models," Monash Econometrics and Business Statistics Working Papers 11/11, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Gael M. Martin & Brendan P.M. McCabe & Worapree Maneesoonthorn & Christian P. Robert, 2014. "Approximate Bayesian Computation in State Space Models," Monash Econometrics and Business Statistics Working Papers 20/14, Monash University, Department of Econometrics and Business Statistics.
    2. Gael M. Martin & Brendan P.M. McCabe & David T. Frazier & Worapree Maneesoonthorn & Christian P. Robert, 2016. "Auxiliary Likelihood-Based Approximate Bayesian Computation in State Space Models," Monash Econometrics and Business Statistics Working Papers 09/16, Monash University, Department of Econometrics and Business Statistics.
    3. Pauwels, Laurent L. & Vasnev, Andrey L., 2016. "A note on the estimation of optimal weights for density forecast combinations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 391-397.
    4. Pauwels, Laurent, 2019. "Predicting China’s Monetary Policy with Forecast Combinations," Working Papers BAWP-2019-07, University of Sydney Business School, Discipline of Business Analytics.
    5. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    6. Patrick Leung & Catherine S. Forbes & Gael M Martin & Brendan McCabe, 2019. "Forecasting Observables with Particle Filters: Any Filter Will Do!," Monash Econometrics and Business Statistics Working Papers 22/19, Monash University, Department of Econometrics and Business Statistics.
    7. Shalini Sharma & Víctor Elvira & Emilie Chouzenoux & Angshul Majumdar, 2021. "Recurrent Dictionary Learning for State-Space Models with an Application in Stock Forecasting," Post-Print hal-03184841, HAL.
    8. Patrick Leung & Catherine S. Forbes & Gael M. Martin & Brendan McCabe, 2016. "Data-driven particle Filters for particle Markov Chain Monte Carlo," Monash Econometrics and Business Statistics Working Papers 17/16, Monash University, Department of Econometrics and Business Statistics.

  5. Brendan P.M. McCabe & Gael M. Martin & David Harris, 2009. "Optimal Probabilistic Forecasts for Counts," Monash Econometrics and Business Statistics Working Papers 7/09, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Barczy, M. & Ispány, M. & Pap, G., 2011. "Asymptotic behavior of unstable INAR(p) processes," Stochastic Processes and their Applications, Elsevier, vol. 121(3), pages 583-608, March.
    2. Dag Tjøstheim, 2012. "Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 413-438, September.
    3. Yousung Park & Hee-Young Kim, 2012. "Diagnostic checks for integer-valued autoregressive models using expected residuals," Statistical Papers, Springer, vol. 53(4), pages 951-970, November.

  6. Ruijun Bu & Kaddour Hadri & Brendan McCabe, 2006. "Conditional Maximum Likelihood Estimation of Higher-Order Integer-Valued Autoregressive Processes," Working Papers 200619, University of Liverpool, Department of Economics.

    Cited by:

    1. Bu, Ruijun & McCabe, Brendan, 2008. "Model selection, estimation and forecasting in INAR(p) models: A likelihood-based Markov Chain approach," International Journal of Forecasting, Elsevier, vol. 24(1), pages 151-162.

  7. Keith Freeland & Brendan McCabe & Gael Martin, 2004. "Testing for Dependence in Non-Gaussian Time Series Data," Econometric Society 2004 Australasian Meetings 313, Econometric Society.

    Cited by:

    1. McCabe, B.P.M. & Martin, G.M., 2005. "Bayesian predictions of low count time series," International Journal of Forecasting, Elsevier, vol. 21(2), pages 315-330.
    2. Ralph D. Snyder & Gael M. Martin & Phillip Gould & Paul D. Feigin, 2007. "An Assessment of Alternative State Space Models for Count Time Series," Monash Econometrics and Business Statistics Working Papers 4/07, Monash University, Department of Econometrics and Business Statistics.
    3. Strickland, Chris M. & Forbes, Catherine S. & Martin, Gael M., 2006. "Bayesian analysis of the stochastic conditional duration model," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2247-2267, May.
    4. Feigin, Paul D. & Gould, Phillip & Martin, Gael M. & Snyder, Ralph D., 2008. "Feasible parameter regions for alternative discrete state space models," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2963-2970, December.

  8. David Harris & Steve Leybourne & Brendan McCabe, 2003. "Panel Stationarity Tests with Cross-sectional Dependence," Econometrics 0311005, University Library of Munich, Germany.

    Cited by:

    1. Lau, Marco Chi Keung & Fung, Ka Wai Terence, 2013. "Convergence in Health Care Expenditure of 14 EU Countries: New Evidence from Non-linear Panel Unit Root Test," MPRA Paper 52871, University Library of Munich, Germany.
    2. Yiannis Karavias & Elias Tzavalis, 2013. "The power performance of fixed-T panel unit root tests allowing for structural breaks," Discussion Papers 13/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    3. Coakley, Jerry & Kellard, Neil & Snaith, Stuart, 2005. "The PPP debate: Price matters!," Economics Letters, Elsevier, vol. 88(2), pages 209-213, August.
    4. Snaith, Stuart, 2012. "The PPP debate: Multiple breaks and cross-sectional dependence," Economics Letters, Elsevier, vol. 115(3), pages 342-344.
    5. Diego Romero-Ávila & Carlos Usabiaga, 2008. "On the persistence of Spanish unemployment rates," Empirical Economics, Springer, vol. 35(1), pages 77-99, August.
    6. Mario Cerrato & Nicholas Sarantis, 2007. "Does purchasing power parity hold in emerging markets? Evidence from a panel of black market exchange rates," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 12(4), pages 427-444.

  9. Brendan McCabe & Stephen Leybourne & David Harris, 2003. "Testing for Stochastic Cointegration and Evidence for Present Value Models," Econometrics 0311009, University Library of Munich, Germany.

    Cited by:

    1. Raj Aggarwal & Brian M. Lucey & Sunil K. Mohanty, 2006. "The Forward Exchange Rate Bias Puzzle: Evidence from New Cointegration Tests," The Institute for International Integration Studies Discussion Paper Series iiisdp123, IIIS.
    2. Schindler, Felix & Voronkova, Svitlana, 2010. "Linkages between international securitized real estate markets: Further evidence from time-varying and stochastic cointegration," ZEW Discussion Papers 10-051, ZEW - Leibniz Centre for European Economic Research.
    3. Lucey, Brian M. & Voronkova, Svitlana, 2008. "Russian equity market linkages before and after the 1998 crisis: Evidence from stochastic and regime-switching cointegration tests," Journal of International Money and Finance, Elsevier, vol. 27(8), pages 1303-1324, December.
    4. Lucey, Brian M. & Voronkova, Svitlana, 2005. "Russian equity market linkages before and after the 1998 crisis: evidence from time-varying and stochastic cointegration tests," BOFIT Discussion Papers 12/2005, Bank of Finland Institute for Emerging Economies (BOFIT).
    5. Abdul Rashid, 2006. "Public-Private Investment Linkage in Pakistan," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, vol. 7(2), pages 219-230, September.
    6. Gawon Yoon, 2006. "A Note on Some Properties of STUR Processes," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(2), pages 253-260, April.
    7. Gawon Yoon, 2005. "Stochastic Unit Roots in the Capital Asset Pricing Model?," Bulletin of Economic Research, Wiley Blackwell, vol. 57(4), pages 369-389, October.

  10. B.P.M. McCabe & G.M. Martin & A.R. Tremayne, 2003. "Persistence and Nonstationary Models," Monash Econometrics and Business Statistics Working Papers 16/03, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. B. P. M. McCabe & G. M. Martin & A. R. Tremayne, 2005. "Assessing Persistence In Discrete Nonstationary Time‐Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(2), pages 305-317, March.

  11. McCabe,B.P.M. & Tremayne,A.R., 1995. "Testing a Time-Series for Difference Stationarity," Cambridge Working Papers in Economics 9420, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Psaradakis, Zacharias & Sola, Martin & Spagnolo, Fabio, 2001. "A simple procedure for detecting periodically collapsing rational bubbles," Economics Letters, Elsevier, vol. 72(3), pages 317-323, September.
    2. Palandri, Alessandro, 2024. "Reconciling interest rates evidence with theory: Rejecting unit roots when the HD(1) is a competing alternative," Journal of Banking & Finance, Elsevier, vol. 161(C).
    3. K Abadir & W Distaso, "undated". "Testing joint hypotheses when one of the alternatives is one-sided," Discussion Papers 05/13, Department of Economics, University of York.
    4. Trapani, Lorenzo, 2021. "A test for strict stationarity in a random coefficient autoregressive model of order 1," Statistics & Probability Letters, Elsevier, vol. 177(C).
    5. Charemza W.W. & M. Lifshits & S. Makarova, 2002. "Conditional testing for unit-root bilinearity in financial time series: some theoretical and empirical results," Computing in Economics and Finance 2002 251, Society for Computational Economics.
    6. Westerlund, Joakim & Larsson, Rolf, 2009. "Testing for a Unit Root in a Random Coefficient Panel Data Model," Working Papers in Economics 383, University of Gothenburg, Department of Economics.
    7. Muriel, Nelson & González-Farías, Graciela, 2018. "Testing the null of difference stationarity against the alternative of a stochastic unit root: A new test based on multivariate STUR," Econometrics and Statistics, Elsevier, vol. 7(C), pages 46-62.
    8. Granger, E.J. & Swanson, N.R., 1996. "An introduction to stochastic Unit Root Processes," Papers 4-96-3, Pennsylvania State - Department of Economics.
    9. Distaso, Walter, 2008. "Testing for unit root processes in random coefficient autoregressive models," Journal of Econometrics, Elsevier, vol. 142(1), pages 581-609, January.
    10. Ha, Jeongcheol & Lee, Sangyeol, 2002. "Coefficient constancy test in AR-ARCH models," Statistics & Probability Letters, Elsevier, vol. 57(1), pages 65-77, March.
    11. Horváth, Lajos & Trapani, Lorenzo, 2019. "Testing for randomness in a random coefficient autoregression model," Journal of Econometrics, Elsevier, vol. 209(2), pages 338-352.
    12. Fong, Pak Wing & Li, Wai Keung, 2003. "On time series with randomized unit root and randomized seasonal unit root," Computational Statistics & Data Analysis, Elsevier, vol. 43(3), pages 369-395, July.
    13. Nagakura, Daisuke, 2009. "Asymptotic theory for explosive random coefficient autoregressive models and inconsistency of a unit root test against a stochastic unit root process," Statistics & Probability Letters, Elsevier, vol. 79(24), pages 2476-2483, December.
    14. Yoon, Gawon, 2016. "Stochastic unit root processes: Maximum likelihood estimation, and new Lagrange multiplier and likelihood ratio tests," Economic Modelling, Elsevier, vol. 52(PB), pages 725-732.

Articles

  1. Brendan P. M. McCabe & Christopher L. Skeels, 2020. "Distributions You Can Count On …But What’s the Point?," Econometrics, MDPI, vol. 8(1), pages 1-36, March.

    Cited by:

    1. Federico Bassetti & Giulia Carallo & Roberto Casarin, 2022. "First-order integer-valued autoregressive processes with Generalized Katz innovations," Papers 2202.02029, arXiv.org.

  2. Frazier, David T. & Maneesoonthorn, Worapree & Martin, Gael M. & McCabe, Brendan P.M., 2019. "Approximate Bayesian forecasting," International Journal of Forecasting, Elsevier, vol. 35(2), pages 521-539.
    See citations under working paper version above.
  3. Harris, David & McCabe, Brendan, 2019. "Semiparametric Independence Testing For Time Series Of Counts And The Role Of The Support," Econometric Theory, Cambridge University Press, vol. 35(6), pages 1111-1145, December.

    Cited by:

    1. Yang Lu, 2021. "The predictive distributions of thinning‐based count processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 42-67, March.

  4. Maria Eduarda Silva & Isabel Pereira & Brendan McCabe, 2019. "Bayesian Outlier Detection in Non‐Gaussian Autoregressive Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 40(5), pages 631-648, September.

    Cited by:

    1. Paolo Gorgi, 2020. "Beta–negative binomial auto‐regressions for modelling integer‐valued time series with extreme observations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(5), pages 1325-1347, December.

  5. Rao, Yao & McCabe, Brendan, 2017. "Is MORE LESS? The role of data augmentation in testing for structural breaks," Economics Letters, Elsevier, vol. 155(C), pages 131-134.

    Cited by:

    1. Yao Rao & Brendan McCabe, 2020. "Structural Change and the Problem of Phantom Break Locations," Manchester School, University of Manchester, vol. 88(1), pages 211-228, January.

  6. Lu Han & Brendan McCabe, 2013. "Testing for parameter constancy in non-Gaussian time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(1), pages 17-29, January.

    Cited by:

    1. Manik Awale & N. Balakrishna & T. V. Ramanathan, 2019. "Testing the constancy of the thinning parameter in a random coefficient integer autoregressive model," Statistical Papers, Springer, vol. 60(5), pages 1515-1539, October.

  7. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
    See citations under working paper version above.
  8. Jiajing Sun & Brendan P. McCabe, 2013. "Score statistics for testing serial dependence in count data," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(3), pages 315-329, May.

    Cited by:

    1. Pedro H. C. Sant’Anna, 2017. "Testing for Uncorrelated Residuals in Dynamic Count Models With an Application to Corporate Bankruptcy," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 349-358, July.
    2. Boris Aleksandrov & Christian H. Weiß, 2020. "Testing the dispersion structure of count time series using Pearson residuals," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(3), pages 325-361, September.
    3. Christian Weiß, 2015. "A Poisson INAR(1) model with serially dependent innovations," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(7), pages 829-851, October.
    4. Mirko Armillotta & Paolo Gorgi, 2023. "Pseudo-variance quasi-maximum likelihood estimation of semi-parametric time series models," Tinbergen Institute Discussion Papers 23-054/III, Tinbergen Institute.
    5. Lucio Palazzo & Riccardo Ievoli, 2022. "A Semiparametric Approach to Test for the Presence of INAR: Simulations and Empirical Applications," Mathematics, MDPI, vol. 10(14), pages 1-18, July.
    6. Luisa Bisaglia & Margherita Gerolimetto, 2019. "Model-based INAR bootstrap for forecasting INAR(p) models," Computational Statistics, Springer, vol. 34(4), pages 1815-1848, December.

  9. Brendan P. M. McCabe & Gael M. Martin & David Harris, 2011. "Efficient probabilistic forecasts for counts," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(2), pages 253-272, March.

    Cited by:

    1. Tianqing Liu & Xiaohui Yuan, 2013. "Random rounded integer-valued autoregressive conditional heteroskedastic process," Statistical Papers, Springer, vol. 54(3), pages 645-683, August.
    2. Maneesoonthorn, Worapree & Martin, Gael M. & Forbes, Catherine S. & Grose, Simone D., 2012. "Probabilistic forecasts of volatility and its risk premia," Journal of Econometrics, Elsevier, vol. 171(2), pages 217-236.
    3. Annika Homburg & Christian H. Weiß & Layth C. Alwan & Gabriel Frahm & Rainer Göb, 2019. "Evaluating Approximate Point Forecasting of Count Processes," Econometrics, MDPI, vol. 7(3), pages 1-28, July.
    4. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    5. Serge Darolles & Gaëlle Le Fol & Yang Lu & Ran Sun, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Post-Print hal-04582262, HAL.
    6. Bisaglia, Luisa & Canale, Antonio, 2016. "Bayesian nonparametric forecasting for INAR models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 70-78.
    7. David Harris & Gael M. Martin & Indeewara Perera & Don S. Poskitt, 2017. "Construction and visualization of optimal confidence sets for frequentist distributional forecasts," Monash Econometrics and Business Statistics Working Papers 9/17, Monash University, Department of Econometrics and Business Statistics.
    8. Wei Wei & Leonhard Held, 2014. "Calibration tests for count data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(4), pages 787-805, December.
    9. Dungey Mardi & Martin Vance L. & Tang Chrismin & Tremayne Andrew, 2020. "A threshold mixed count time series model: estimation and application," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(2), pages 1-18, April.
    10. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
    11. Yang Lu, 2021. "The predictive distributions of thinning‐based count processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 42-67, March.
    12. Giulia Carallo & Roberto Casarin & Christian P. Robert, 2020. "Generalized Poisson Difference Autoregressive Processes," Papers 2002.04470, arXiv.org.
    13. Yao Rao & David Harris & Brendan McCabe, 2022. "A semi‐parametric integer‐valued autoregressive model with covariates," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 495-516, June.
    14. Frazier, David T. & Maneesoonthorn, Worapree & Martin, Gael M. & McCabe, Brendan P.M., 2019. "Approximate Bayesian forecasting," International Journal of Forecasting, Elsevier, vol. 35(2), pages 521-539.
    15. Laurent L. Pauwels & Andrey L. Vasnev, 2017. "Forecast combination for discrete choice models: predicting FOMC monetary policy decisions," Empirical Economics, Springer, vol. 52(1), pages 229-254, February.
    16. Germán Aneiros, 2012. "Comments on: Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 439-441, September.
    17. Vance L. Martin & Andrew R. Tremayne & Robert C. Jung, 2014. "Efficient Method Of Moments Estimators For Integer Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 491-516, November.
    18. Darolles, Serge & Fol, Gaëlle Le & Lu, Yang & Sun, Ran, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 181-203.
    19. Luisa Bisaglia & Margherita Gerolimetto, 2019. "Model-based INAR bootstrap for forecasting INAR(p) models," Computational Statistics, Springer, vol. 34(4), pages 1815-1848, December.

  10. Bu, Ruijun & McCabe, Brendan, 2008. "Model selection, estimation and forecasting in INAR(p) models: A likelihood-based Markov Chain approach," International Journal of Forecasting, Elsevier, vol. 24(1), pages 151-162.

    Cited by:

    1. Yang, Kai & Yu, Xinyang & Zhang, Qingqing & Dong, Xiaogang, 2022. "On MCMC sampling in self-exciting integer-valued threshold time series models," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
    2. Muhammed Rasheed Irshad & Christophe Chesneau & Veena D’cruz & Naushad Mamode Khan & Radhakumari Maya, 2022. "Bivariate Poisson 2Sum-Lindley Distributions and the Associated BINAR(1) Processes," Mathematics, MDPI, vol. 10(20), pages 1-24, October.
    3. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    4. Serge Darolles & Gaëlle Le Fol & Yang Lu & Ran Sun, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Post-Print hal-04582262, HAL.
    5. Ruijun Bu & Brendan McCabe & Kaddour Hadri, 2008. "Maximum likelihood estimation of higher‐order integer‐valued autoregressive processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(6), pages 973-994, November.
    6. Catania, Leopoldo & Di Mari, Roberto, 2021. "Hierarchical Markov-switching models for multivariate integer-valued time-series," Journal of Econometrics, Elsevier, vol. 221(1), pages 118-137.
    7. Haque, M. Ohidul & Haque, Tariq H., 2018. "Evaluating the effects of the road safety system approach in Brunei," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 594-607.
    8. Yousung Park & Hee-Young Kim, 2012. "Diagnostic checks for integer-valued autoregressive models using expected residuals," Statistical Papers, Springer, vol. 53(4), pages 951-970, November.
    9. Kharin, Yuriy & Voloshko, Valeriy, 2021. "Robust estimation for Binomial conditionally nonlinear autoregressive time series based on multivariate conditional frequencies," Journal of Multivariate Analysis, Elsevier, vol. 185(C).
    10. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
    11. Yang Lu, 2021. "The predictive distributions of thinning‐based count processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 42-67, March.
    12. Raju Maiti & Atanu Biswas, 2015. "Coherent forecasting for stationary time series of discrete data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(3), pages 337-365, July.
    13. Masoomeh Forughi & Zohreh Shishebor & Atefeh Zamani, 2022. "Portmanteau tests for generalized integer-valued autoregressive time series models," Statistical Papers, Springer, vol. 63(4), pages 1163-1185, August.
    14. Darolles, Serge & Fol, Gaëlle Le & Lu, Yang & Sun, Ran, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 181-203.
    15. Kai Yang & Yiwei Zhao & Han Li & Dehui Wang, 2023. "On bivariate threshold Poisson integer-valued autoregressive processes," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(8), pages 931-963, November.
    16. Luisa Bisaglia & Margherita Gerolimetto, 2015. "Forecasting integer autoregressive processes of order 1: are simple AR competitive?," Economics Bulletin, AccessEcon, vol. 35(3), pages 1652-1660.
    17. Luisa Bisaglia & Margherita Gerolimetto, 2019. "Model-based INAR bootstrap for forecasting INAR(p) models," Computational Statistics, Springer, vol. 34(4), pages 1815-1848, December.

  11. Harris, David & McCabe, Brendan & Leybourne, Stephen, 2008. "Testing For Long Memory," Econometric Theory, Cambridge University Press, vol. 24(1), pages 143-175, February.

    Cited by:

    1. Bill Russell & Dooruj Rambaccussing, 2016. "Breaks and the Statistical Process of Inflation: The Case of the ‘Modern’ Phillips Curve," Dundee Discussion Papers in Economics 294, Economic Studies, University of Dundee.
    2. Bill Russell & Dooruj Rambaccussing, 2019. "Breaks and the statistical process of inflation: the case of estimating the ‘modern’ long-run Phillips curve," Empirical Economics, Springer, vol. 56(5), pages 1455-1475, May.
    3. Piotr Płuciennik, 2012. "The Impact of the World Financial Crisis on the Polish Interbank Market: A Swap Spread Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(4), pages 269-288, December.
    4. Amsler Christine & Schmidt Peter, 2012. "A Comparison of the Robustness of Several Tests of Short Memory to Autocorrelated Errors," Journal of Econometric Methods, De Gruyter, vol. 1(1), pages 56-66, August.
    5. Kuswanto, Heri & Sibbertsen, Philipp, 2009. "Testing for Long Memory Against ESTAR Nonlinearities," Hannover Economic Papers (HEP) dp-427, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    6. Georgios P. Kouretas & Mark E. Wohar, 2012. "The dynamics of inflation: a study of a large number of countries," Applied Economics, Taylor & Francis Journals, vol. 44(16), pages 2001-2026, June.
    7. Granville, Brigitte & Zeng, Ning, 2019. "Time variation in inflation persistence: New evidence from modelling US inflation," Economic Modelling, Elsevier, vol. 81(C), pages 30-39.
    8. Castano Vélez, Elkin & Gallón Gómez, Santiago Alejandro & Gómez Portilla, Karoll, 2011. "Sesgos en estimación, tamano y potencia de una prueba sobre el parámetro de memoria larga en modelos ARFIMA," Revista Lecturas de Economía, Universidad de Antioquia, CIE, February.
    9. Cho, Cheol-Keun & Amsler, Christine & Schmidt, Peter, 2015. "A test of the null of integer integration against the alternative of fractional integration," Journal of Econometrics, Elsevier, vol. 187(1), pages 217-237.
    10. Lujia Bai & Weichi Wu, 2021. "Detecting long-range dependence for time-varying linear models," Papers 2110.08089, arXiv.org, revised Mar 2023.
    11. Murphy, A. & Izzeldin, M., 2009. "Bootstrapping long memory tests: Some Monte Carlo results," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2325-2334, April.
    12. Ning Zeng, 2015. "Monetary Stability and Stock Returns: A Bivariate Generalized Autoregressive Conditional Heteroscedasticity Modelling Study," Business and Economic Research, Macrothink Institute, vol. 5(2), pages 1-22, December.
    13. Elkin Castaño & Santiago Gallón & Karoll Gómez, 2010. "Estimation Biases, Size and Power of a Test on the Long Memory Parameter in ARFIMA Models," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 73, pages 131-148.

  12. Ruijun Bu & Brendan McCabe & Kaddour Hadri, 2008. "Maximum likelihood estimation of higher‐order integer‐valued autoregressive processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(6), pages 973-994, November.

    Cited by:

    1. Kai Yang & Han Li & Dehui Wang & Chenhui Zhang, 2021. "Random coefficients integer-valued threshold autoregressive processes driven by logistic regression," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(4), pages 533-557, December.
    2. Mohammadipour, Maryam & Boylan, John E., 2012. "Forecast horizon aggregation in integer autoregressive moving average (INARMA) models," Omega, Elsevier, vol. 40(6), pages 703-712.
    3. Christian Weiß, 2015. "A Poisson INAR(1) model with serially dependent innovations," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(7), pages 829-851, October.
    4. Zezhun Chen & Angelos Dassios & George Tzougas, 2023. "INAR approximation of bivariate linear birth and death process," Statistical Inference for Stochastic Processes, Springer, vol. 26(3), pages 459-497, October.
    5. Robert Jung & A. Tremayne, 2011. "Useful models for time series of counts or simply wrong ones?," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 59-91, March.
    6. Chen, Zezhun Chen & Dassios, Angelos & Tzougas, George, 2023. "A first order binomial mixed poisson integer-valued autoregressive model with serially dependent innovations," LSE Research Online Documents on Economics 112222, London School of Economics and Political Science, LSE Library.
    7. Yousung Park & Hee-Young Kim, 2012. "Diagnostic checks for integer-valued autoregressive models using expected residuals," Statistical Papers, Springer, vol. 53(4), pages 951-970, November.
    8. Jentsch, Carsten & Weiß, Christian, 2017. "Bootstrapping INAR models," Working Papers 17-02, University of Mannheim, Department of Economics.
    9. Mirko Armillotta & Paolo Gorgi, 2023. "Pseudo-variance quasi-maximum likelihood estimation of semi-parametric time series models," Tinbergen Institute Discussion Papers 23-054/III, Tinbergen Institute.
    10. Yang Lu, 2021. "The predictive distributions of thinning‐based count processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 42-67, March.
    11. Xanthi Pedeli & Anthony C. Davison & Konstantinos Fokianos, 2015. "Likelihood Estimation for the INAR( p ) Model by Saddlepoint Approximation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 1229-1238, September.
    12. Robert C. Jung & Andrew R. Tremayne, 2020. "Maximum-Likelihood Estimation in a Special Integer Autoregressive Model," Econometrics, MDPI, vol. 8(2), pages 1-15, June.
    13. Luisa Bisaglia & Margherita Gerolimetto, 2019. "Model-based INAR bootstrap for forecasting INAR(p) models," Computational Statistics, Springer, vol. 34(4), pages 1815-1848, December.

  13. Harris, David & Leybourne, Stephen & McCabe, Brendan, 2007. "Modified Kpss Tests For Near Integration," Econometric Theory, Cambridge University Press, vol. 23(2), pages 355-363, April.

    Cited by:

    1. Anton Skrobotov, 2013. "On GLS-detrending for deterministic seasonality testing," Working Papers 0073, Gaidar Institute for Economic Policy, revised 2014.
    2. David O. Cushman, 2012. "Mankiw vs. DeLong and Krugman on the CEA's Real GDP Forecasts in Early 2009: What Might a Time Series Econometrician Have Said?," Econ Journal Watch, Econ Journal Watch, vol. 9(3), pages 309-349, September.
    3. Anton Skrobotov, 2015. "Trend and Initial Condition in Stationarity Tests: The Asymptotic Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(2), pages 254-273, April.
    4. Eiji Kurozumi & Shinya Tanaka, 2010. "Reducing the size distortion of the KPSS test," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(6), pages 415-426, November.
    5. Anton Skrobotov, 2013. "Local Structural Trend Break in Stationarity Testing," Working Papers 0074, Gaidar Institute for Economic Policy, revised 2013.
    6. Cho, Cheol-Keun & Amsler, Christine & Schmidt, Peter, 2015. "A test of the null of integer integration against the alternative of fractional integration," Journal of Econometrics, Elsevier, vol. 187(1), pages 217-237.
    7. Lujia Bai & Weichi Wu, 2021. "Detecting long-range dependence for time-varying linear models," Papers 2110.08089, arXiv.org, revised Mar 2023.
    8. Ferrer-Pérez, H. & Ayuda, M.I. & Aznar, A., 2017. "A comparison of two modified stationarity tests. A Monte Carlo study," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 134(C), pages 28-36.

  14. McCabe, Brendan & Leybourne, Stephen & Harris, David, 2006. "A Residual-Based Test For Stochastic Cointegration," Econometric Theory, Cambridge University Press, vol. 22(3), pages 429-456, June.

    Cited by:

    1. Burak Alparslan Eroğlu & J. Isaac Miller & Taner Yiğit, 2022. "Time-varying cointegration and the Kalman filter," Econometric Reviews, Taylor & Francis Journals, vol. 41(1), pages 1-21, January.
    2. Julio A. Afonso-Rodríguez & María Santana-Gallego, 2018. "Is Spain benefiting from the Arab Spring? On the impact of terrorism on a tourist competitor country," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(3), pages 1371-1408, May.
    3. Lucey, Brian M. & Voronkova, Svitlana, 2008. "Russian equity market linkages before and after the 1998 crisis: Evidence from stochastic and regime-switching cointegration tests," Journal of International Money and Finance, Elsevier, vol. 27(8), pages 1303-1324, December.

  15. McCabe, B.P.M. & Martin, G.M., 2005. "Bayesian predictions of low count time series," International Journal of Forecasting, Elsevier, vol. 21(2), pages 315-330.

    Cited by:

    1. Wooi Chen Khoo & Seng Huat Ong & Biswas Atanu, 2022. "Coherent Forecasting for a Mixed Integer-Valued Time Series Model," Mathematics, MDPI, vol. 10(16), pages 1-15, August.
    2. Aghabazaz, Zeynab & Kazemi, Iraj, 2023. "Under-reported time-varying MINAR(1) process for modeling multivariate count series," Computational Statistics & Data Analysis, Elsevier, vol. 188(C).
    3. Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "Forecasting the intermittent demand for slow-moving inventories: A modelling approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 485-496.
    4. Feike C. Drost & Ramon van den Akker & Bas J. M. Werker, 2009. "Efficient estimation of auto‐regression parameters and innovation distributions for semiparametric integer‐valued AR(p) models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 467-485, April.
    5. Yelland, Phillip M., 2010. "Bayesian forecasting of parts demand," International Journal of Forecasting, Elsevier, vol. 26(2), pages 374-396, April.
    6. Annika Homburg & Christian H. Weiß & Layth C. Alwan & Gabriel Frahm & Rainer Göb, 2019. "Evaluating Approximate Point Forecasting of Count Processes," Econometrics, MDPI, vol. 7(3), pages 1-28, July.
    7. T M Christensen & A S Hurn & K A Lindsay, 2008. "It never rains but it pours: Modelling the persistence of spikes in electricity prices," NCER Working Paper Series 25, National Centre for Econometric Research.
    8. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    9. Serge Darolles & Gaëlle Le Fol & Yang Lu & Ran Sun, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Post-Print hal-04582262, HAL.
    10. Jung, Robert C. & Tremayne, A.R., 2006. "Coherent forecasting in integer time series models," International Journal of Forecasting, Elsevier, vol. 22(2), pages 223-238.
    11. Bisaglia, Luisa & Canale, Antonio, 2016. "Bayesian nonparametric forecasting for INAR models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 70-78.
    12. Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Andres Ramirez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Monash Econometrics and Business Statistics Working Papers 33/20, Monash University, Department of Econometrics and Business Statistics.
    13. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    14. Bu, Ruijun & McCabe, Brendan, 2008. "Model selection, estimation and forecasting in INAR(p) models: A likelihood-based Markov Chain approach," International Journal of Forecasting, Elsevier, vol. 24(1), pages 151-162.
    15. Jonas Andersson & Dimitris Karlis, 2010. "Treating missing values in INAR(1) models: An application to syndromic surveillance data," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(1), pages 12-19, January.
    16. Berry, Lindsay R. & Helman, Paul & West, Mike, 2020. "Probabilistic forecasting of heterogeneous consumer transaction–sales time series," International Journal of Forecasting, Elsevier, vol. 36(2), pages 552-569.
    17. Ralph D. Snyder & Gael M. Martin & Phillip Gould & Paul D. Feigin, 2007. "An Assessment of Alternative State Space Models for Count Time Series," Monash Econometrics and Business Statistics Working Papers 4/07, Monash University, Department of Econometrics and Business Statistics.
    18. T M Christensen & A. S. Hurn & K A Lindsay, 2008. "Discrete time-series models when counts are unobservable," NCER Working Paper Series 35, National Centre for Econometric Research.
    19. Bennedsen, Mikkel & Lunde, Asger & Shephard, Neil & Veraart, Almut E.D., 2023. "Inference and forecasting for continuous-time integer-valued trawl processes," Journal of Econometrics, Elsevier, vol. 236(2).
    20. Wei Wei & Leonhard Held, 2014. "Calibration tests for count data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(4), pages 787-805, December.
    21. Federico Bassetti & Giulia Carallo & Roberto Casarin, 2022. "First-order integer-valued autoregressive processes with Generalized Katz innovations," Papers 2202.02029, arXiv.org.
    22. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    23. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
    24. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2020. "On an integer-valued stochastic intensity model for time series of counts," MPRA Paper 105406, University Library of Munich, Germany.
    25. Claudia Czado & Tilmann Gneiting & Leonhard Held, 2009. "Predictive Model Assessment for Count Data," Biometrics, The International Biometric Society, vol. 65(4), pages 1254-1261, December.
    26. Yang Lu, 2021. "The predictive distributions of thinning‐based count processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 42-67, March.
    27. Giulia Carallo & Roberto Casarin & Christian P. Robert, 2020. "Generalized Poisson Difference Autoregressive Processes," Papers 2002.04470, arXiv.org.
    28. Yelland, Phillip M., 2009. "Bayesian forecasting for low-count time series using state-space models: An empirical evaluation for inventory management," International Journal of Production Economics, Elsevier, vol. 118(1), pages 95-103, March.
    29. Francesco Bravo, 2011. "Comment on: Subsampling weakly dependent time series and application to extremes," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(3), pages 483-486, November.
    30. Raju Maiti & Atanu Biswas & Bibhas Chakraborty, 2018. "Modelling of low count heavy tailed time series data consisting large number of zeros and ones," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(3), pages 407-435, August.
    31. Feigin, Paul D. & Gould, Phillip & Martin, Gael M. & Snyder, Ralph D., 2008. "Feasible parameter regions for alternative discrete state space models," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2963-2970, December.
    32. Annika Homburg & Christian H. Weiß & Layth C. Alwan & Gabriel Frahm & Rainer Göb, 2021. "A performance analysis of prediction intervals for count time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 603-625, July.
    33. Víctor Enciso‐Mora & Peter Neal & T. Subba Rao, 2009. "Efficient order selection algorithms for integer‐valued ARMA processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 1-18, January.
    34. Mohammad Khajehzadeh & Farhad Pazhuheian & Farima Seifi & Rassoul Noorossana & Ali Asli & Niloufar Saeedi, 2022. "Analysis of Factors Affecting Product Sales with an Outlook toward Sale Forecasting in Cosmetic Industry using Statistical Methods," International Review of Management and Marketing, Econjournals, vol. 12(6), pages 55-63, November.
    35. Vance L. Martin & Andrew R. Tremayne & Robert C. Jung, 2014. "Efficient Method Of Moments Estimators For Integer Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 491-516, November.
    36. Brajendra C. Sutradhar, 2008. "On forecasting counts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 109-129.
    37. Darolles, Serge & Fol, Gaëlle Le & Lu, Yang & Sun, Ran, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 181-203.
    38. Andersson, Jonas & Karlis, Dimitris, 2008. "Treating missing values in INAR(1) models," Discussion Papers 2008/14, Norwegian School of Economics, Department of Business and Management Science.

  16. Keith Freeland, R. & McCabe, Brendan, 2005. "Asymptotic properties of CLS estimators in the Poisson AR(1) model," Statistics & Probability Letters, Elsevier, vol. 73(2), pages 147-153, June.

    Cited by:

    1. Feike C. Drost & Ramon van den Akker & Bas J. M. Werker, 2009. "Efficient estimation of auto‐regression parameters and innovation distributions for semiparametric integer‐valued AR(p) models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 467-485, April.
    2. Zeng, Xiaoqiang & Kakizawa, Yoshihide, 2024. "Two-step conditional least squares estimation in ADCINAR(1) process, revisited," Statistics & Probability Letters, Elsevier, vol. 206(C).
    3. Christian Weiß, 2008. "Thinning operations for modeling time series of counts—a survey," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(3), pages 319-341, August.
    4. Boris Aleksandrov & Christian H. Weiß, 2020. "Testing the dispersion structure of count time series using Pearson residuals," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(3), pages 325-361, September.
    5. M. Kachour & J. F. Yao, 2009. "First‐order rounded integer‐valued autoregressive (RINAR(1)) process," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(4), pages 417-448, July.
    6. Mohammadipour, Maryam & Boylan, John E., 2012. "Forecast horizon aggregation in integer autoregressive moving average (INARMA) models," Omega, Elsevier, vol. 40(6), pages 703-712.
    7. Miroslav M. Ristić & Aleksandar S. Nastić & Ana V. Miletić Ilić, 2013. "A geometric time series model with dependent Bernoulli counting series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 466-476, July.
    8. Weiß, Christian H. & Schweer, Sebastian, 2016. "Bias corrections for moment estimators in Poisson INAR(1) and INARCH(1) processes," Statistics & Probability Letters, Elsevier, vol. 112(C), pages 124-130.
    9. Jonas Andersson & Dimitris Karlis, 2010. "Treating missing values in INAR(1) models: An application to syndromic surveillance data," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(1), pages 12-19, January.
    10. Subhankar Chattopadhyay & Raju Maiti & Samarjit Das & Atanu Biswas, 2022. "Change‐point analysis through integer‐valued autoregressive process with application to some COVID‐19 data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 76(1), pages 4-34, February.
    11. Yao Rao & David Harris & Brendan McCabe, 2022. "A semi‐parametric integer‐valued autoregressive model with covariates," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 495-516, June.
    12. Wagner Barreto-Souza & Sokol Ndreca & Rodrigo B. Silva & Roger W. C. Silva, 2023. "Non-linear INAR(1) processes under an alternative geometric thinning operator," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(2), pages 695-725, June.
    13. Zeng, Xiaoqiang & Kakizawa, Yoshihide, 2022. "Bias-correction of some estimators in the INAR(1) process," Statistics & Probability Letters, Elsevier, vol. 187(C).
    14. Christian H. Weiß, 2011. "Detecting mean increases in Poisson INAR(1) processes with EWMA control charts," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(2), pages 383-398, September.
    15. Wagner Barreto-Souza, 2019. "Mixed Poisson INAR(1) processes," Statistical Papers, Springer, vol. 60(6), pages 2119-2139, December.

  17. Harris, David & Leybourne, Stephen & McCabe, Brendan, 2005. "Panel Stationarity Tests for Purchasing Power Parity With Cross-Sectional Dependence," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 395-409, October.

    Cited by:

    1. Hadri, Kaddour & Kurozumi, Eiji, 2012. "A simple panel stationarity test in the presence of serial correlation and a common factor," Economics Letters, Elsevier, vol. 115(1), pages 31-34.
    2. Kaddour Hadri & Eiji Kurozumi & Yao Rao, 2015. "Novel panel cointegration tests emending for cross‐section dependence with N fixed," Econometrics Journal, Royal Economic Society, vol. 18(3), pages 363-411, October.
    3. Donatella Gatti & Anne-Gaël Vaubourg, 2009. "Unemployment and finance: how do financial and labour market factors interact?," Working Papers halshs-00566792, HAL.
    4. Syed A. Basher & Josep Lluis Carrión-i-Silvestre, 2008. "Deconstructing Shocks and Persistence in OECD Real Exchange Rates," Working Papers XREAP2008-06, Xarxa de Referència en Economia Aplicada (XREAP), revised Jun 2008.
    5. Marco Barassi & Matthew Cole & Robert Elliott, 2008. "Stochastic Divergence or Convergence of Per Capita Carbon Dioxide Emissions: Re-examining the Evidence," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 40(1), pages 121-137, May.
    6. Firouz Fallahi & Gabriel Rodríguez, 2011. "Persistence of Unemployment in the Canadian Provinces," International Regional Science Review, , vol. 34(4), pages 438-458, October.
    7. Drakos, Anastassios A. & Kouretas, Georgios P. & Stavroyiannis, Stavros & Zarangas, Leonidas, 2017. "Is the Feldstein-Horioka puzzle still with us? National saving-investment dynamics and international capital mobility: A panel data analysis across EU member countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 47(C), pages 76-88.
    8. David I. Harvey & Stephen J. Leybourne & Bin Xiao, 2007. "A powerful test for linearity when the order of integration is unknown," Discussion Papers 07/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    9. Mariam Camarero & Josep Lluis Carrion-i-Silvestre & Cecilio Tamarit, 2006. "New evidence of the real interest rate parity for OECD countries using panel unit root tests with breaks," Working Papers CREAP2006-14, Xarxa de Referència en Economia Aplicada (XREAP), revised Dec 2006.
    10. Lau, Marco Chi Keung & Fung, Ka Wai Terence, 2013. "Convergence in Health Care Expenditure of 14 EU Countries: New Evidence from Non-linear Panel Unit Root Test," MPRA Paper 52871, University Library of Munich, Germany.
    11. Camarero, Mariam & Carrion-i-Silvestre, Josep Lluís & Tamarit, Cecilio, 2015. "Testing for external sustainability under a monetary integration process. Does the Lawson doctrine apply to Europe?," Economic Modelling, Elsevier, vol. 44(C), pages 343-349.
    12. Sax, Christoph & Gubler, Matthias, 2011. "The Balassa-Samuelson Effect Reversed: New Evidence from OECD Countries," Working papers 2011/09, Faculty of Business and Economics - University of Basel.
    13. Mark J. Holmes & Jesús Otero & Theodore Panagiotidis, 2011. "PPP in OECD Countries: An Analysis of Real Exchange Rate Stationarity, cross-Sectional Dependency and Structural Breaks," Working Paper series 51_11, Rimini Centre for Economic Analysis.
    14. Skare, Marinko & PORADA-ROCHON, Małgorzata, 2022. "The role of innovation in sustainable growth: A dynamic panel study on micro and macro levels 1990–2019," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    15. Giorgio Canarella & Stephen M. Miller & Stephen K. Pollard, 2012. "Purchasing Power Parity between the UK and the Euro Area," Working papers 2012-46, University of Connecticut, Department of Economics.
    16. Joerg Breitung & M. Hashem Pesaran, 2005. "Unit Roots and Cointegration in Panels," CESifo Working Paper Series 1565, CESifo.
    17. Joakim Westerlund & David L. Edgerton, 2008. "A Simple Test for Cointegration in Dependent Panels with Structural Breaks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(5), pages 665-704, October.
    18. Giorgio Canarella & Stephen Miller & Stephen Pollard, 2014. "Purchasing Power Parity Between the UK and Germany: The Euro Era," Open Economies Review, Springer, vol. 25(4), pages 677-699, September.
    19. Yiannis Karavias & Elias Tzavalis, 2013. "The power performance of fixed-T panel unit root tests allowing for structural breaks," Discussion Papers 13/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    20. Matei Demetrescu & Uwe Hassler & Adina Tarcolea, 2010. "Testing for stationarity in large panels with cross-dependence, and US evidence on unit labor cost," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(8), pages 1381-1397.
    21. Shiu-Sheng Chen, 2012. "Does extracting inflation from stock returns solve the purchasing power parity puzzle?," Empirical Economics, Springer, vol. 42(3), pages 1097-1105, June.
    22. Basher Syed A. & Carrion-i-Silvestre Josep Lluís, 2009. "Price Level Convergence, Purchasing Power Parity and Multiple Structural Breaks in Panel Data Analysis: An Application to U.S. Cities," Journal of Time Series Econometrics, De Gruyter, vol. 1(1), pages 1-38, April.
    23. Kaddour Hadri & Eiji Kurozumi, 2009. "A Simple Panel Stationarity Test in the Presence of Cross-Sectional Dependence," Economics Working Papers 09-01, Queen's Management School, Queen's University Belfast.
    24. Yiannis Karavias & Elias Tzavalis, 2014. "Testing for unit roots in panels with structural changes, spatial and temporal dependence when the time dimension is finite," Discussion Papers 14/03, University of Nottingham, Granger Centre for Time Series Econometrics.
    25. Hadri, Kaddour & Kurozumi, Eiji, 2011. "A Locally Optimal Test for No Unit Root in Cross-sectionally Dependent Panel Data," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 52(2), pages 165-184, December.
    26. Georgescu, Irina Alexandra & Oprea, Simona-Vasilica & Bâra, Adela, 2024. "Investigating the relationship between macroeconomic indicators, renewables and pollution across diverse regions in the globalization era," Applied Energy, Elsevier, vol. 363(C).
    27. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    28. Eleftherios Thalassinos & Marta Kadłubek & Le Minh Thong & Tran Van Hiep & Erginbay Ugurlu, 2022. "Managerial Issues Regarding the Role of Natural Gas in the Transition of Energy and the Impact of Natural Gas Consumption on the GDP of Selected Countries," Resources, MDPI, vol. 11(5), pages 1-22, April.
    29. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2011. "Unit-root and stationarity testing with empirical application on industrial production of CEE-4 countries," MPRA Paper 29648, University Library of Munich, Germany.
    30. Yiannis Karavias & Elias Tzavalis, 2017. "Local power of panel unit root tests allowing for structural breaks," Econometric Reviews, Taylor & Francis Journals, vol. 36(10), pages 1123-1156, November.
    31. Chia-Cheng Ho & Su-Yin Cheng & Han Hou, 2009. "Purchasing Power Parity and Country Characteristics: Evidence from Time Series Analysis," Economics Bulletin, AccessEcon, vol. 29(1), pages 444-456.
    32. Syed A. Basher & Josep Lluís Carrion-i-Silvestre, 2007. "Another Look at the Null of Stationary RealExchange Rates. Panel Data with Structural Breaks and Cross-section Dependence," IREA Working Papers 200710, University of Barcelona, Research Institute of Applied Economics, revised May 2007.
    33. Lin, Pei-Chien & Huang, Ho-Chuan (River), 2012. "Inequality convergence revisited: Evidence from stationarity panel tests with breaks and cross correlation," Economic Modelling, Elsevier, vol. 29(2), pages 316-325.
    34. Kaddour Hadri & Eiji Kurozumi & Daisuke Yamazaki, 2015. "Synergy between an Improved Covariate Unit Root Test and Cross-sectionally Dependent Panel Data Unit Root Tests," Manchester School, University of Manchester, vol. 83(6), pages 676-700, December.
    35. Syed A. Basher & Josep Lluis Carrión-i-Silvestre, 2008. "Price level convergence, purchasing power parity and multiple structural breaks: An application to US cities," Working Papers XREAP2008-08, Xarxa de Referència en Economia Aplicada (XREAP), revised Jul 2008.
    36. Mohsen Bahmani‐Oskooee & Scott W. Hegerty, 2009. "Purchasing Power Parity In Less‐Developed And Transition Economies: A Review Paper," Journal of Economic Surveys, Wiley Blackwell, vol. 23(4), pages 617-658, September.
    37. Basher, Syed A. & Westerlund, Joakim, 2009. "Panel cointegration and the monetary exchange rate model," Economic Modelling, Elsevier, vol. 26(2), pages 506-513, March.
    38. Eshagh Mansourkiaee, 2023. "Estimating energy demand elasticities for gas exporting countries: a dynamic panel data approach," SN Business & Economics, Springer, vol. 3(1), pages 1-28, January.
    39. Eiji Kurozumi & Daisuke Yamazaki & Kaddour Hadri, 2013. "Covariate Unit Root Test for Cross-Sectionally Dependent Panel Data," Economics Working Papers 13-01, Queen's Management School, Queen's University Belfast.
    40. Pope, Robin & Selten, Reinhard & Kaiser, Johannes & von Hagen, Jürgen, 2006. "The Underlying Cause of Unpredictability in Exchange Rates and Good Models of Exchange Rate Regime Selection: Field and Laboratory Evidence," Bonn Econ Discussion Papers 27/2006, University of Bonn, Bonn Graduate School of Economics (BGSE).
    41. Diego Romero-Ávila & Carlos Usabiaga, 2008. "On the persistence of Spanish unemployment rates," Empirical Economics, Springer, vol. 35(1), pages 77-99, August.
    42. Norman Gemmell & Richard Kneller & Ismael Sanz, 2011. "The Timing and Persistence of Fiscal Policy Impacts on Growth: Evidence from OECD Countries," Economic Journal, Royal Economic Society, vol. 121(550), pages 33-58, February.
    43. Mariam Camarero & Josep Lluís Carrion‐i‐Silvestre & Cecilio Tamarit, 2010. "Does Real Interest Rate Parity Hold For Oecd Countries? New Evidence Using Panel Stationarity Tests With Cross‐Section Dependence And Structural Breaks," Scottish Journal of Political Economy, Scottish Economic Society, vol. 57(5), pages 568-590, November.
    44. Mariam Camarero & Josep Lluis Carrion‐I‐Silvestre & Cecilio Tamarit, 2009. "Testing For Real Interest Rate Parity Using Panel Stationarity Tests With Dependence: A Note," Manchester School, University of Manchester, vol. 77(1), pages 112-126, January.
    45. Yagmur Saglam & Apostolos Ampountolas, 2021. "The effects of shocks on Turkish tourism demand: Evidence using panel unit root test," Tourism Economics, , vol. 27(4), pages 859-866, June.
    46. Gemmell, Norman & Kneller, Richard & Sanz, Ismael, 2008. "Foreign investment, international trade and the size and structure of public expenditures," European Journal of Political Economy, Elsevier, vol. 24(1), pages 151-171, March.

  18. R. K. Freeland & B. P. M. McCabe, 2004. "Analysis of low count time series data by poisson autoregression," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(5), pages 701-722, September.

    Cited by:

    1. Šárka Hudecová & Marie Hušková & Simos G. Meintanis, 2021. "Goodness–of–Fit Tests for Bivariate Time Series of Counts," Econometrics, MDPI, vol. 9(1), pages 1-20, March.
    2. Christian H. Weiß, 2012. "Fully observed INAR(1) processes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(3), pages 581-598, July.
    3. Feike C. Drost & Ramon van den Akker & Bas J. M. Werker, 2009. "Efficient estimation of auto‐regression parameters and innovation distributions for semiparametric integer‐valued AR(p) models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 467-485, April.
    4. Isabel Silva & M. Eduarda Silva & Isabel Pereira & Nélia Silva, 2005. "Replicated INAR(1) Processes," Methodology and Computing in Applied Probability, Springer, vol. 7(4), pages 517-542, December.
    5. B.P.M. McCabe & G.M. Martin, 2003. "Coherent Predictions of Low Count Time Series," Monash Econometrics and Business Statistics Working Papers 8/03, Monash University, Department of Econometrics and Business Statistics.
    6. Christian Weiß, 2008. "Thinning operations for modeling time series of counts—a survey," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(3), pages 319-341, August.
    7. Kai Yang & Han Li & Dehui Wang & Chenhui Zhang, 2021. "Random coefficients integer-valued threshold autoregressive processes driven by logistic regression," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(4), pages 533-557, December.
    8. Borges, Patrick & Molinares, Fabio Fajardo & Bourguignon, Marcelo, 2016. "A geometric time series model with inflated-parameter Bernoulli counting series," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 264-272.
    9. Feike C. Drost & Ramon Van Den Akker & Bas J. M. Werker, 2008. "Local asymptotic normality and efficient estimation for INAR(p) models," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(5), pages 783-801, September.
    10. T M Christensen & A S Hurn & K A Lindsay, 2008. "It never rains but it pours: Modelling the persistence of spikes in electricity prices," NCER Working Paper Series 25, National Centre for Econometric Research.
    11. M. Kachour & J. F. Yao, 2009. "First‐order rounded integer‐valued autoregressive (RINAR(1)) process," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(4), pages 417-448, July.
    12. Muhammed Rasheed Irshad & Christophe Chesneau & Veena D’cruz & Naushad Mamode Khan & Radhakumari Maya, 2022. "Bivariate Poisson 2Sum-Lindley Distributions and the Associated BINAR(1) Processes," Mathematics, MDPI, vol. 10(20), pages 1-24, October.
    13. Christian Weiß, 2015. "A Poisson INAR(1) model with serially dependent innovations," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(7), pages 829-851, October.
    14. Bisaglia, Luisa & Canale, Antonio, 2016. "Bayesian nonparametric forecasting for INAR models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 70-78.
    15. Weiß Christian & Scherer Lukas & Aleksandrov Boris & Feld Martin, 2020. "Checking Model Adequacy for Count Time Series by Using Pearson Residuals," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-15, January.
    16. Ruijun Bu & Brendan McCabe & Kaddour Hadri, 2008. "Maximum likelihood estimation of higher‐order integer‐valued autoregressive processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(6), pages 973-994, November.
    17. McCabe, B.P.M. & Martin, G.M., 2005. "Bayesian predictions of low count time series," International Journal of Forecasting, Elsevier, vol. 21(2), pages 315-330.
    18. Huaping Chen & Fukang Zhu & Xiufang Liu, 2022. "A New Bivariate INAR(1) Model with Time-Dependent Innovation Vectors," Stats, MDPI, vol. 5(3), pages 1-22, August.
    19. Miroslav M. Ristić & Aleksandar S. Nastić & Ana V. Miletić Ilić, 2013. "A geometric time series model with dependent Bernoulli counting series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 466-476, July.
    20. Aleksandar S. Nastić & Petra N. Laketa & Miroslav M. Ristić, 2016. "Random environment integer-valued autoregressive process," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(2), pages 267-287, March.
    21. Han Li & Zijian Liu & Kai Yang & Xiaogang Dong & Wenshan Wang, 2024. "A pth-order random coefficients mixed binomial autoregressive process with explanatory variables," Computational Statistics, Springer, vol. 39(5), pages 2581-2604, July.
    22. Bu, Ruijun & McCabe, Brendan, 2008. "Model selection, estimation and forecasting in INAR(p) models: A likelihood-based Markov Chain approach," International Journal of Forecasting, Elsevier, vol. 24(1), pages 151-162.
    23. Ralph D. Snyder & Gael M. Martin & Phillip Gould & Paul D. Feigin, 2007. "An Assessment of Alternative State Space Models for Count Time Series," Monash Econometrics and Business Statistics Working Papers 4/07, Monash University, Department of Econometrics and Business Statistics.
    24. T M Christensen & A. S. Hurn & K A Lindsay, 2008. "Discrete time-series models when counts are unobservable," NCER Working Paper Series 35, National Centre for Econometric Research.
    25. Christian H. Weiß & Martin H.-J. M. Feld & Naushad Mamode Khan & Yuvraj Sunecher, 2019. "INARMA Modeling of Count Time Series," Stats, MDPI, vol. 2(2), pages 1-37, June.
    26. Federico Bassetti & Giulia Carallo & Roberto Casarin, 2022. "First-order integer-valued autoregressive processes with Generalized Katz innovations," Papers 2202.02029, arXiv.org.
    27. Wagner Barreto-Souza, 2015. "Zero-Modified Geometric INAR(1) Process for Modelling Count Time Series with Deflation or Inflation of Zeros," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(6), pages 839-852, November.
    28. Ruijun Bu & Kaddour Hadri & Brendan McCabe, 2006. "Conditional Maximum Likelihood Estimation of Higher-Order Integer-Valued Autoregressive Processes," Working Papers 200619, University of Liverpool, Department of Economics.
    29. Baena-Mirabete, S. & Puig, P., 2020. "Computing probabilities of integer-valued random variables by recurrence relations," Statistics & Probability Letters, Elsevier, vol. 161(C).
    30. Giulia Carallo & Roberto Casarin & Christian P. Robert, 2020. "Generalized Poisson Difference Autoregressive Processes," Papers 2002.04470, arXiv.org.
    31. Manik Awale & N. Balakrishna & T. V. Ramanathan, 2019. "Testing the constancy of the thinning parameter in a random coefficient integer autoregressive model," Statistical Papers, Springer, vol. 60(5), pages 1515-1539, October.
    32. Francesco Bravo, 2011. "Comment on: Subsampling weakly dependent time series and application to extremes," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(3), pages 483-486, November.
    33. Jowaheer, Vandna & Sutradhar, Brajendra, 2009. "GMM versus GQL inferences for panel count data," Statistics & Probability Letters, Elsevier, vol. 79(18), pages 1928-1934, September.
    34. Feigin, Paul D. & Gould, Phillip & Martin, Gael M. & Snyder, Ralph D., 2008. "Feasible parameter regions for alternative discrete state space models," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2963-2970, December.
    35. Moizes Melo & Airlane Alencar, 2020. "Conway–Maxwell–Poisson Autoregressive Moving Average Model for Equidispersed, Underdispersed, and Overdispersed Count Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(6), pages 830-857, November.
    36. Layth C. Alwan & Christian H. Weiß, 2017. "INAR implementation of newsvendor model for serially dependent demand counts," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 1085-1099, February.
    37. Zezhun Chen & Angelos Dassios & George Tzougas, 2023. "Multivariate mixed Poisson Generalized Inverse Gaussian INAR(1) regression," Computational Statistics, Springer, vol. 38(2), pages 955-977, June.
    38. Shengqi Tian & Dehui Wang & Shuai Cui, 2020. "A seasonal geometric INAR process based on negative binomial thinning operator," Statistical Papers, Springer, vol. 61(6), pages 2561-2581, December.
    39. Brajendra C. Sutradhar, 2008. "On forecasting counts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 109-129.
    40. Wagner Barreto‐Souza & Hernando Ombao, 2022. "The negative binomial process: A tractable model with composite likelihood‐based inference," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(2), pages 568-592, June.
    41. Bu Hyoung Lee, 2022. "Bootstrap Prediction Intervals of Temporal Disaggregation," Stats, MDPI, vol. 5(1), pages 1-13, February.
    42. Chigozie E. Utazi, 2017. "Bayesian Single Changepoint Estimation in a Parameter-driven Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(3), pages 765-779, September.
    43. Feilong Lu & Dehui Wang, 2022. "A new estimation for INAR(1) process with Poisson distribution," Computational Statistics, Springer, vol. 37(3), pages 1185-1201, July.
    44. José M. R. Murteira & Mário A. G. Augusto, 2017. "Hurdle models of repayment behaviour in personal loan contracts," Empirical Economics, Springer, vol. 53(2), pages 641-667, September.

  19. Freeland, R. K. & McCabe, B. P. M., 2004. "Forecasting discrete valued low count time series," International Journal of Forecasting, Elsevier, vol. 20(3), pages 427-434.

    Cited by:

    1. Dimitris Karlis & Naushad Mamode Khan & Yuvraj Sunecher, 2024. "The Negative Binomial INAR(1) Process under Different Thinning Processes: Can We Separate between the Different Models?," Stats, MDPI, vol. 7(3), pages 1-15, July.
    2. Wooi Chen Khoo & Seng Huat Ong & Biswas Atanu, 2022. "Coherent Forecasting for a Mixed Integer-Valued Time Series Model," Mathematics, MDPI, vol. 10(16), pages 1-15, August.
    3. Raju Maiti & Atanu Biswas & Samarjit Das, 2016. "Coherent forecasting for count time series using Box–Jenkins's AR(p) model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(2), pages 123-145, May.
    4. Azam, Kazim & Pitt, Michael, 2014. "Bayesian Inference for a Semi-Parametric Copula-based Markov Chain," Economic Research Papers 270232, University of Warwick - Department of Economics.
    5. Christian H. Weiß, 2012. "Fully observed INAR(1) processes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(3), pages 581-598, July.
    6. Annika Homburg & Christian H. Weiß & Layth C. Alwan & Gabriel Frahm & Rainer Göb, 2019. "Evaluating Approximate Point Forecasting of Count Processes," Econometrics, MDPI, vol. 7(3), pages 1-28, July.
    7. B.P.M. McCabe & G.M. Martin, 2003. "Coherent Predictions of Low Count Time Series," Monash Econometrics and Business Statistics Working Papers 8/03, Monash University, Department of Econometrics and Business Statistics.
    8. T M Christensen & A S Hurn & K A Lindsay, 2008. "It never rains but it pours: Modelling the persistence of spikes in electricity prices," NCER Working Paper Series 25, National Centre for Econometric Research.
    9. Axel Groß-Klußmann & Nikolaus Hautsch, 2011. "Predicting Bid-Ask Spreads Using Long Memory Autoregressive Conditional Poisson Models," SFB 649 Discussion Papers SFB649DP2011-044, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    11. Jung, Robert C. & Tremayne, A.R., 2006. "Coherent forecasting in integer time series models," International Journal of Forecasting, Elsevier, vol. 22(2), pages 223-238.
    12. Mohammadipour, Maryam & Boylan, John E., 2012. "Forecast horizon aggregation in integer autoregressive moving average (INARMA) models," Omega, Elsevier, vol. 40(6), pages 703-712.
    13. Aliou DIAGNE, 2006. "Diffusion And Adoption Of Nerica Rice Varieties In Côte D’Ivoire," The Developing Economies, Institute of Developing Economies, vol. 44(2), pages 208-231, June.
    14. Bisaglia, Luisa & Canale, Antonio, 2016. "Bayesian nonparametric forecasting for INAR models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 70-78.
    15. Christian H. Weiß, 2018. "Goodness-of-fit testing of a count time series’ marginal distribution," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(6), pages 619-651, August.
    16. Simon Nik & Christian H. Weiß, 2020. "CLAR(1) point forecasting under estimation uncertainty," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(4), pages 489-516, November.
    17. Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Andres Ramirez Hassan, 2020. "Optimal probabilistic forecasts: When do they work?," Monash Econometrics and Business Statistics Working Papers 33/20, Monash University, Department of Econometrics and Business Statistics.
    18. Ruijun Bu & Brendan McCabe & Kaddour Hadri, 2008. "Maximum likelihood estimation of higher‐order integer‐valued autoregressive processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(6), pages 973-994, November.
    19. McCabe, B.P.M. & Martin, G.M., 2005. "Bayesian predictions of low count time series," International Journal of Forecasting, Elsevier, vol. 21(2), pages 315-330.
    20. David Harris & Gael M. Martin & Indeewara Perera & Don S. Poskitt, 2017. "Construction and visualization of optimal confidence sets for frequentist distributional forecasts," Monash Econometrics and Business Statistics Working Papers 9/17, Monash University, Department of Econometrics and Business Statistics.
    21. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    22. Miroslav M. Ristić & Aleksandar S. Nastić & Ana V. Miletić Ilić, 2013. "A geometric time series model with dependent Bernoulli counting series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 466-476, July.
    23. Azam, Kazim & Pitt, Michael, 2014. "Bayesian Inference for a Semi-Parametric Copula-based Markov Chain," The Warwick Economics Research Paper Series (TWERPS) 1051, University of Warwick, Department of Economics.
    24. R. Freeland, 2010. "True integer value time series," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 94(3), pages 217-229, September.
    25. Han Li & Zijian Liu & Kai Yang & Xiaogang Dong & Wenshan Wang, 2024. "A pth-order random coefficients mixed binomial autoregressive process with explanatory variables," Computational Statistics, Springer, vol. 39(5), pages 2581-2604, July.
    26. Bu, Ruijun & McCabe, Brendan, 2008. "Model selection, estimation and forecasting in INAR(p) models: A likelihood-based Markov Chain approach," International Journal of Forecasting, Elsevier, vol. 24(1), pages 151-162.
    27. Christoph Jeßberger, 2011. "Multilateral Environmental Agreements up to 2050: Are They Sustainable Enough?," ifo Working Paper Series 98, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    28. Rostami-Tabar, Bahman & Disney, Stephen M., 2023. "On the order-up-to policy with intermittent integer demand and logically consistent forecasts," International Journal of Production Economics, Elsevier, vol. 257(C).
    29. Ralph D. Snyder & Gael M. Martin & Phillip Gould & Paul D. Feigin, 2007. "An Assessment of Alternative State Space Models for Count Time Series," Monash Econometrics and Business Statistics Working Papers 4/07, Monash University, Department of Econometrics and Business Statistics.
    30. Christian H. Weiß & Annika Homburg & Pedro Puig, 2019. "Testing for zero inflation and overdispersion in INAR(1) models," Statistical Papers, Springer, vol. 60(3), pages 823-848, June.
    31. T M Christensen & A. S. Hurn & K A Lindsay, 2008. "Discrete time-series models when counts are unobservable," NCER Working Paper Series 35, National Centre for Econometric Research.
    32. Bennedsen, Mikkel & Lunde, Asger & Shephard, Neil & Veraart, Almut E.D., 2023. "Inference and forecasting for continuous-time integer-valued trawl processes," Journal of Econometrics, Elsevier, vol. 236(2).
    33. Dungey Mardi & Martin Vance L. & Tang Chrismin & Tremayne Andrew, 2020. "A threshold mixed count time series model: estimation and application," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(2), pages 1-18, April.
    34. Subhankar Chattopadhyay & Raju Maiti & Samarjit Das & Atanu Biswas, 2022. "Change‐point analysis through integer‐valued autoregressive process with application to some COVID‐19 data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 76(1), pages 4-34, February.
    35. Wagner Barreto-Souza, 2015. "Zero-Modified Geometric INAR(1) Process for Modelling Count Time Series with Deflation or Inflation of Zeros," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(6), pages 839-852, November.
    36. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    37. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
    38. Azaare Jacob & Zhao Wu, 2020. "An Alternative Pricing System through Bayesian Estimates and Method of Moments in a Bonus-Malus Framework for the Ghanaian Auto Insurance Market," JRFM, MDPI, vol. 13(7), pages 1-15, July.
    39. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2020. "On an integer-valued stochastic intensity model for time series of counts," MPRA Paper 105406, University Library of Munich, Germany.
    40. Schweer, Sebastian & Weiß, Christian H., 2014. "Compound Poisson INAR(1) processes: Stochastic properties and testing for overdispersion," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 267-284.
    41. Brajendra C. Sutradhar & Vandna Jowaheer & Gary Sneddon, 2008. "On a Unified Generalized Quasi–likelihood Approach for Familial–Longitudinal Non‐Stationary Count Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(4), pages 597-612, December.
    42. Annika Homburg & Christian H. Weiß & Gabriel Frahm & Layth C. Alwan & Rainer Göb, 2021. "Analysis and Forecasting of Risk in Count Processes," JRFM, MDPI, vol. 14(4), pages 1-25, April.
    43. Han Li & Kai Yang & Shishun Zhao & Dehui Wang, 2018. "First-order random coefficients integer-valued threshold autoregressive processes," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(3), pages 305-331, July.
    44. Yao Rao & David Harris & Brendan McCabe, 2022. "A semi‐parametric integer‐valued autoregressive model with covariates," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 495-516, June.
    45. Euán, Carolina & Sun, Ying, 2020. "Bernoulli vector autoregressive model," Journal of Multivariate Analysis, Elsevier, vol. 177(C).
    46. Dunsmuir, William T. M. & Scott, David J., 2015. "The glarma Package for Observation-Driven Time Series Regression of Counts," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i07).
    47. Raju Maiti & Atanu Biswas & Bibhas Chakraborty, 2018. "Modelling of low count heavy tailed time series data consisting large number of zeros and ones," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(3), pages 407-435, August.
    48. Feigin, Paul D. & Gould, Phillip & Martin, Gael M. & Snyder, Ralph D., 2008. "Feasible parameter regions for alternative discrete state space models," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2963-2970, December.
    49. Annika Homburg & Christian H. Weiß & Layth C. Alwan & Gabriel Frahm & Rainer Göb, 2021. "A performance analysis of prediction intervals for count time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 603-625, July.
    50. Víctor Enciso‐Mora & Peter Neal & T. Subba Rao, 2009. "Efficient order selection algorithms for integer‐valued ARMA processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 1-18, January.
    51. Wooi Chen Khoo & Seng Huat Ong & Atanu Biswas, 2017. "Modeling time series of counts with a new class of INAR(1) model," Statistical Papers, Springer, vol. 58(2), pages 393-416, June.
    52. Raju Maiti & Atanu Biswas, 2015. "Coherent forecasting for stationary time series of discrete data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(3), pages 337-365, July.
    53. Alwell J. Oyet & Brajendra C. Sutradhar, 2021. "Analyzing Unevenly Spaced Longitudinal Count Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 342-373, November.
    54. Yao Kang & Dehui Wang & Kai Yang, 2021. "A new INAR(1) process with bounded support for counts showing equidispersion, underdispersion and overdispersion," Statistical Papers, Springer, vol. 62(2), pages 745-767, April.
    55. Yao Kang & Shuhui Wang & Dehui Wang & Fukang Zhu, 2023. "Analysis of zero-and-one inflated bounded count time series with applications to climate and crime data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(1), pages 34-73, March.
    56. Layth C. Alwan & Christian H. Weiß, 2017. "INAR implementation of newsvendor model for serially dependent demand counts," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 1085-1099, February.
    57. Hee-Young Kim & Yousung Park, 2008. "A non-stationary integer-valued autoregressive model," Statistical Papers, Springer, vol. 49(3), pages 485-502, July.
    58. Cattivelli, Luca & Pirino, Davide, 2019. "A SHARP model of bid–ask spread forecasts," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1211-1225.
    59. Vance L. Martin & Andrew R. Tremayne & Robert C. Jung, 2014. "Efficient Method Of Moments Estimators For Integer Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 491-516, November.
    60. Brajendra C. Sutradhar, 2008. "On forecasting counts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 109-129.
    61. Scotto, Manuel G. & Weiß, Christian H. & Silva, Maria Eduarda & Pereira, Isabel, 2014. "Bivariate binomial autoregressive models," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 233-251.
    62. Kai Yang & Yiwei Zhao & Han Li & Dehui Wang, 2023. "On bivariate threshold Poisson integer-valued autoregressive processes," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(8), pages 931-963, November.
    63. Andersson, Jonas & Karlis, Dimitris, 2008. "Treating missing values in INAR(1) models," Discussion Papers 2008/14, Norwegian School of Economics, Department of Business and Management Science.
    64. Christian H. Weiß & Philip K. Pollett, 2012. "Chain Binomial Models and Binomial Autoregressive Processes," Biometrics, The International Biometric Society, vol. 68(3), pages 815-824, September.

  20. Harris, David & McCabe, Brendan & Leybourne, Stephen, 2003. "Some Limit Theory For Autocovariances Whose Order Depends On Sample Size," Econometric Theory, Cambridge University Press, vol. 19(5), pages 829-864, October.

    Cited by:

    1. Kaddour Hadri & Eiji Kurozumi & Yao Rao, 2015. "Novel panel cointegration tests emending for cross‐section dependence with N fixed," Econometrics Journal, Royal Economic Society, vol. 18(3), pages 363-411, October.
    2. Ghassan, Hassan & Boulanouar, Zakaria & Hassan, Kabir Mohammed, 2020. "Revisiting Banking Stability Using a New Panel Cointegration Test," MPRA Paper 107085, University Library of Munich, Germany, revised 2020.
    3. David I. Harvey & Stephen J. Leybourne & Bin Xiao, 2007. "A powerful test for linearity when the order of integration is unknown," Discussion Papers 07/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    4. Brendan McCabe & Stephen Leybourne & David Harris, 2003. "Testing for Stochastic Cointegration and Evidence for Present Value Models," Econometrics 0311009, University Library of Munich, Germany.
    5. Kyung So Im & Junsoo Lee & Vladimir Arcabic & Mansik Hur, 2018. "DF-IV Unit Root Tests Using Stationary Instrument Variables," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 7(1), pages 1-1.
    6. Ayesh Ariyasinghe & N. S. Cooray, 2021. "The Nexus Of Foreign Reserves, Exchange Rate And Inflation: Recent Empirical Evidence From Sri Lanka," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, vol. 22(1), pages 29-72, March.
    7. Jirak, Moritz, 2011. "On the maximum of covariance estimators," Journal of Multivariate Analysis, Elsevier, vol. 102(6), pages 1032-1046, July.
    8. Gawon Yoon, 2010. "Nonlinearity in real exchange rates: an approach with disaggregated data and a new linearity test," Applied Economics Letters, Taylor & Francis Journals, vol. 17(11), pages 1125-1132.
    9. Kaddour Hadri & Eiji Kurozumi, 2009. "A Simple Panel Stationarity Test in the Presence of Cross-Sectional Dependence," Economics Working Papers 09-01, Queen's Management School, Queen's University Belfast.
    10. Yoon, Gawon, 2009. "It's all the miners' fault: On the nonlinearity in U.S. unemployment rates," Economic Modelling, Elsevier, vol. 26(6), pages 1449-1454, November.
    11. Bob Nobay & Ivan Paya & David A. Peel, 2010. "Inflation Dynamics in the U.S.: Global but Not Local Mean Reversion," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(1), pages 135-150, February.
    12. Bob Nobay & Ivan Paya & David A. Peel, 2007. "Inflation Dynamics in the US -A Nonlinear Perspective," FMG Discussion Papers dp601, Financial Markets Group.
    13. Khraief, Naceur & Shahbaz, Muhammad & Heshmati, Almas & Azam, Muhammad, 2015. "Are Unemployment Rates in OECD Countries Stationary? Evidence from Univariate and Panel Unit Root Tests," IZA Discussion Papers 9571, Institute of Labor Economics (IZA).
    14. Harris, David & McCabe, Brendan & Leybourne, Stephen, 2002. "Stochastic cointegration: estimation and inference," Journal of Econometrics, Elsevier, vol. 111(2), pages 363-384, December.
    15. Erdas Mehmet Levent, 2019. "Validity of Weak-Form Market Efficiency in Central and Eastern European Countries (CEECs): Evidence from Linear and Nonlinear Unit Root Tests," Review of Economic Perspectives, Sciendo, vol. 19(4), pages 399-428, December.
    16. Syed A. Basher & Josep Lluís Carrion-i-Silvestre, 2007. "Another Look at the Null of Stationary RealExchange Rates. Panel Data with Structural Breaks and Cross-section Dependence," IREA Working Papers 200710, University of Barcelona, Research Institute of Applied Economics, revised May 2007.
    17. Neifar, Malika, 2020. "Multivariate GARCH Approaches: case of major sectorial Tunisian stock markets," MPRA Paper 99658, University Library of Munich, Germany.
    18. Yavuz, Nilgün Çil & Yilanci, Veli, 2012. "Testing For Nonlinearity In G7 Macroeconomic Time Series," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 69-79, September.
    19. Ghassan, Hassan & Abdullah, Abdelgader, 2009. "Does the entry of foreign investors influence the volatility of Doha Securities Market?," MPRA Paper 95620, University Library of Munich, Germany, revised 2010.
    20. Malika Neifar & Leila Gharbi, 2022. "Weak EMH and Canadian stock markets: evidence from linear and nonlinear unit root tests," Journal of Islamic Accounting and Business Research, Emerald Group Publishing Limited, vol. 14(4), pages 629-651, December.
    21. David Harris & Steve Leybourne & Brendan McCabe, 2003. "Panel Stationarity Tests with Cross-sectional Dependence," Econometrics 0311005, University Library of Munich, Germany.
    22. neifar, malika, 2020. "Efficient Markets Hypothesis in Canada:‎ a comparative study between Islamic and Conventional stock markets ‎," MPRA Paper 103175, University Library of Munich, Germany.
    23. Wu, Wei Biao, 2009. "An asymptotic theory for sample covariances of Bernoulli shifts," Stochastic Processes and their Applications, Elsevier, vol. 119(2), pages 453-467, February.

  21. Harris, David & McCabe, Brendan & Leybourne, Stephen, 2002. "Stochastic cointegration: estimation and inference," Journal of Econometrics, Elsevier, vol. 111(2), pages 363-384, December.

    Cited by:

    1. Raj Aggarwal & Brian M. Lucey & Sunil K. Mohanty, 2006. "The Forward Exchange Rate Bias Puzzle: Evidence from New Cointegration Tests," The Institute for International Integration Studies Discussion Paper Series iiisdp123, IIIS.
    2. Brendan McCabe & Stephen Leybourne & David Harris, 2003. "Testing for Stochastic Cointegration and Evidence for Present Value Models," Econometrics 0311009, University Library of Munich, Germany.
    3. Chen, Haiqiang & Fang, Ying & Li, Yingxing, 2015. "Estimation And Inference For Varying-Coefficient Models With Nonstationary Regressors Using Penalized Splines," Econometric Theory, Cambridge University Press, vol. 31(4), pages 753-777, August.
    4. Schindler, Felix & Voronkova, Svitlana, 2010. "Linkages between international securitized real estate markets: Further evidence from time-varying and stochastic cointegration," ZEW Discussion Papers 10-051, ZEW - Leibniz Centre for European Economic Research.
    5. Miller, Stephen M. & Martins, Luis Filipe & Gupta, Rangan, 2019. "A Time-Varying Approach Of The Us Welfare Cost Of Inflation," Macroeconomic Dynamics, Cambridge University Press, vol. 23(2), pages 775-797, March.
    6. Burak Alparslan Eroğlu & J. Isaac Miller & Taner Yiğit, 2022. "Time-varying cointegration and the Kalman filter," Econometric Reviews, Taylor & Francis Journals, vol. 41(1), pages 1-21, January.
    7. Xiao, Zhijie, 2009. "Functional-coefficient cointegration models," Journal of Econometrics, Elsevier, vol. 152(2), pages 81-92, October.
    8. Gasmi, Farid & Laourari, Imène, 2017. "Has Algeria suffered from the dutch disease?: Evidence from 1960–2013 data," TSE Working Papers 17-780, Toulouse School of Economics (TSE).
    9. B. P. M. McCabe & G. M. Martin & A. R. Tremayne, 2005. "Assessing Persistence In Discrete Nonstationary Time‐Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(2), pages 305-317, March.
    10. Brian M Lucey & Cal Muckley, 2011. "Robust Global Stock Market Interdependencies," The Institute for International Integration Studies Discussion Paper Series iiisdp353, IIIS.
    11. Lucey, Brian M. & Voronkova, Svitlana, 2008. "Russian equity market linkages before and after the 1998 crisis: Evidence from stochastic and regime-switching cointegration tests," Journal of International Money and Finance, Elsevier, vol. 27(8), pages 1303-1324, December.
    12. Lucey, Brian M. & Voronkova, Svitlana, 2005. "Russian equity market linkages before and after the 1998 crisis: evidence from time-varying and stochastic cointegration tests," BOFIT Discussion Papers 12/2005, Bank of Finland Institute for Emerging Economies (BOFIT).
    13. Thomas Lagoarde-Segot & Brian M. Lucey, 2007. "Capital Market Integration in the Middle East and North Africa," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 43(3), pages 34-57, June.
    14. Chiquiar Daniel & Ramos Francia Manuel, 2004. "Bilateral Trade and Business Cycle Synchronization: Evidence from Mexico and United States Manufacturing Industries," Working Papers 2004-05, Banco de México.

  22. Leybourne, S J & McCabe, B P M, 1999. "Modified Stationarity Tests with Data-Dependent Model-Selection Rules," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(2), pages 264-270, April.

    Cited by:

    1. Judith Giles & Cara Williams, 2001. "Export-led growth: a survey of the empirical literature and some non-causality results. Part 2," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 9(4), pages 445-470.
    2. Alexandru Minea & Christophe Rault, 2011. "External Monetary Shocks and Monetary Integration: Evidence from the Bulgarian Currency Board," CESifo Working Paper Series 3409, CESifo.
    3. Joseph Ross, 2021. "Stationarity Statistics on Rolling Windows," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 655-691, February.
    4. Norman J. Morin & John M. Roberts, 1999. "Is hysteresis important for U.S. unemployment?," Finance and Economics Discussion Series 1999-56, Board of Governors of the Federal Reserve System (U.S.).
    5. Aepli, Matthias D. & Füss, Roland & Henriksen, Tom Erik S. & Paraschiv, Florentina, 2017. "Modeling the multivariate dynamic dependence structure of commodity futures portfolios," Journal of Commodity Markets, Elsevier, vol. 6(C), pages 66-87.
    6. Amsler Christine & Schmidt Peter, 2012. "A Comparison of the Robustness of Several Tests of Short Memory to Autocorrelated Errors," Journal of Econometric Methods, De Gruyter, vol. 1(1), pages 56-66, August.
    7. Róbert Csalódi & Tímea Czvetkó & Viktor Sebestyén & János Abonyi, 2022. "Sectoral Analysis of Energy Transition Paths and Greenhouse Gas Emissions," Energies, MDPI, vol. 15(21), pages 1-26, October.
    8. Amsler Christine & Schmidt Peter & Vogelsang Timothy J, 2009. "The KPSS Test Using Fixed-b Critical Values: Size and Power in Highly Autocorrelated Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 1(1), pages 1-44, December.
    9. Kurozumi, Eiji, 2009. "Construction of Stationarity Tests with Less Size Distortions," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 50(1), pages 87-105, June.
    10. Vasco J. Gabriel & Luis F. Martins, 2010. "Cointegration Tests Under Multiple Regime Shifts: An Application to the Stock Price-Dividend Relationship," NIPE Working Papers 28/2010, NIPE - Universidade do Minho.
    11. Judith Giles & Cara Williams, 2001. "Export-led growth: a survey of the empirical literature and some non-causality results. Part 1," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 9(3), pages 261-337.
    12. Ana Iregui & Jesús Otero, 2011. "Testing the law of one price in food markets: evidence for Colombia using disaggregated data," Empirical Economics, Springer, vol. 40(2), pages 269-284, April.
    13. Franco Bevilacqua & Adriaan van Zon, 2004. "Random walks and non-linear paths in macroeconomic time series: some evidence and implications," Chapters, in: John Foster & Werner Hölzl (ed.), Applied Evolutionary Economics and Complex Systems, chapter 3, Edward Elgar Publishing.
    14. Eiji Kurozumi & Shinya Tanaka, 2010. "Reducing the size distortion of the KPSS test," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(6), pages 415-426, November.
    15. Newbold, Paul & Leybourne, Stephen & Wohar, Mark E., 2001. "Trend-stationarity, difference-stationarity, or neither: further diagnostic tests with an application to U.S. Real GNP, 1875-1993," Journal of Economics and Business, Elsevier, vol. 53(1), pages 85-102.
    16. Jönsson, Kristian, 2006. "Finite-Sample Stability of the KPSS Test," Working Papers 2006:23, Lund University, Department of Economics.
    17. Slade, Margaret E., 2001. "Valuing Managerial Flexibility: An Application of Real-Option Theory to Mining Investments," Journal of Environmental Economics and Management, Elsevier, vol. 41(2), pages 193-233, March.
    18. Raul Crespo, 2005. "Total Factor Productivity: An Unobserved Components Approach," Bristol Economics Discussion Papers 05/579, School of Economics, University of Bristol, UK.
    19. Judith A. Giles & Sadaf Mirza, 1999. "Some Pretesting Issues on Testing for Granger Noncausality," Econometrics Working Papers 9914, Department of Economics, University of Victoria.
    20. Aepli, Matthias D. & Frauendorfer, Karl & Fuess, Roland & Paraschiv, Florentina, 2015. "Multivariate Dynamic Copula Models: Parameter Estimation and Forecast Evaluation," Working Papers on Finance 1513, University of St. Gallen, School of Finance.
    21. Gabriel, Vasco J., 2003. "Cointegration and the joint confirmation hypothesis," Economics Letters, Elsevier, vol. 78(1), pages 17-25, January.
    22. Muller, Ulrich K., 2005. "Size and power of tests of stationarity in highly autocorrelated time series," Journal of Econometrics, Elsevier, vol. 128(2), pages 195-213, October.
    23. Martins, Luis F. & Gabriel, Vasco J., 2014. "Modelling long run comovements in equity markets: A flexible approach," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 288-295.
    24. Paul Newbold & Tony Rayner & Neil Kellard, 2000. "Long‐Run Drift, Co‐Movement and Persistence in Real Wheat and Maize Prices," Journal of Agricultural Economics, Wiley Blackwell, vol. 51(1), pages 106-121, January.
    25. Josep Carrion-i-Silvestre & Andreu Sansó, 2006. "A guide to the computation of stationarity tests," Empirical Economics, Springer, vol. 31(2), pages 433-448, June.
    26. Vasco J. Gabriel & Martin Sola & Zacharias Psaradakis, 2002. "Residual-based tests for cointegration and multiple regime shifts," NIPE Working Papers 7/2002, NIPE - Universidade do Minho.

  23. McCabe, B.P.M. & Leybourne, S.J., 1998. "On Estimating An Arma Model With An Ma Unit Root," Econometric Theory, Cambridge University Press, vol. 14(3), pages 326-338, June.

    Cited by:

    1. Tae‐Hwan Kim & Stephan Pfaffenzeller & Tony Rayner & Paul Newbold, 2003. "Testing for Linear Trend with Application to Relative Primary Commodity Prices," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(5), pages 539-551, September.
    2. Yongcheol Shin & Andy Snell, 2006. "Mean group tests for stationarity in heterogeneous panels," Econometrics Journal, Royal Economic Society, vol. 9(1), pages 123-158, March.
    3. Kurozumi, Eiji, 2009. "Construction of Stationarity Tests with Less Size Distortions," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 50(1), pages 87-105, June.
    4. Josep Carrion-i-Silvestre & Andreu Sansó, 2006. "A guide to the computation of stationarity tests," Empirical Economics, Springer, vol. 31(2), pages 433-448, June.

  24. B. P. M. McCabe & S. J. Leybourne & Y. Shin, 1997. "A Parametric approach to testing the null of cointegration," Journal of Time Series Analysis, Wiley Blackwell, vol. 18(4), pages 395-413, July.

    Cited by:

    1. Judith Giles & Cara Williams, 2001. "Export-led growth: a survey of the empirical literature and some non-causality results. Part 2," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 9(4), pages 445-470.
    2. Matteo Mogliani, 2010. "Residual-based tests for cointegration and multiple deterministic structural breaks: A Monte Carlo study," PSE Working Papers halshs-00564897, HAL.
    3. Hassler, Uwe, 2009. "The Effect of Linear Time Trends on Cointegration Testing in Single Equations," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77573, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    4. Vasco J. Gabriel, 2001. "Tests for the Null Hypothesis of Cointegration: a Monte Carlo Comparison," NIPE Working Papers 7/2001, NIPE - Universidade do Minho.
    5. Josep Lluís Carrion‐i‐Silvestre & Andreu Sansó, 2006. "Testing the Null of Cointegration with Structural Breaks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(5), pages 623-646, October.
    6. Gabriel, Vasco J. & Psaradakis, Zacharias & Sola, Martin, 2002. "A simple method of testing for cointegration subject to multiple regime changes," Economics Letters, Elsevier, vol. 76(2), pages 213-221, July.
    7. Vasco J. Gabriel & Luis F. Martins, 2010. "Cointegration Tests Under Multiple Regime Shifts: An Application to the Stock Price-Dividend Relationship," NIPE Working Papers 28/2010, NIPE - Universidade do Minho.
    8. Christoph Hanck & Till Massing, 2021. "Testing for Nonlinear Cointegration under Heteroskedasticity," Papers 2102.08809, arXiv.org, revised Oct 2024.
    9. Judith Giles & Cara Williams, 2001. "Export-led growth: a survey of the empirical literature and some non-causality results. Part 1," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 9(3), pages 261-337.
    10. Caner, M. & Kilian, L., 2001. "Size distortions of tests of the null hypothesis of stationarity: evidence and implications for the PPP debate," Journal of International Money and Finance, Elsevier, vol. 20(5), pages 639-657, October.
    11. Vasco J. Gabriel & Martin Sola & Zacharias Psaradakis, 2001. "A simple method for testing cointegration subject to regime changes," NIPE Working Papers 15/2001, NIPE - Universidade do Minho.
    12. Judith A. Clarke & Sadaf Mirza, 2003. "Some Finite Sample Results On Testing For Granger Noncausality," Econometrics Working Papers 0305, Department of Economics, University of Victoria.
    13. Ching-Chuan Tsong & Cheng-Feng Lee & Li-Ju Tsai & Te-Chung Hu, 2016. "The Fourier approximation and testing for the null of cointegration," Empirical Economics, Springer, vol. 51(3), pages 1085-1113, November.
    14. Judith A. Giles & Sadaf Mirza, 1999. "Some Pretesting Issues on Testing for Granger Noncausality," Econometrics Working Papers 9914, Department of Economics, University of Victoria.
    15. Gabriel, Vasco J., 2003. "Cointegration and the joint confirmation hypothesis," Economics Letters, Elsevier, vol. 78(1), pages 17-25, January.
    16. Martins, Luis F. & Gabriel, Vasco J., 2014. "Modelling long run comovements in equity markets: A flexible approach," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 288-295.
    17. Nicoleta ISAC & Cosmin DOBRIN & Mehmood HUSSAN & Asad ul Islam KHAN & Alina- Andreea MARIN, 2020. "On The Ranks Of Tests Having Null Of Cointegration: A Monte Carlo Comparison," Management Research and Practice, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 12(2), pages 58-69, June.

  25. Leybourne, S J & McCabe, B P M & Tremayne, A R, 1996. "Can Economic Time Series Be Differenced to Stationarity?," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 435-446, October.

    Cited by:

    1. Offer Lieberman & Peter C.B. Phillips, 2018. "Understanding Temporal Aggregation Effects on Kurtosis in Financial Indices," Cowles Foundation Discussion Papers 2151, Cowles Foundation for Research in Economics, Yale University.
    2. Francisco de Castro & José M. González-Páramo & Pablo Hernández de Cos, 2001. "Evaluating the dynamics of fiscal policy in Spain: patterns of interdependence and consistency of public expenditure and revenues," Working Papers 0103, Banco de España.
    3. Psaradakis, Zacharias & Sola, Martin & Spagnolo, Fabio, 2001. "A simple procedure for detecting periodically collapsing rational bubbles," Economics Letters, Elsevier, vol. 72(3), pages 317-323, September.
    4. Offer Lieberman & Peter C.B. Phillips, 2013. "Norming Rates and Limit Theory for Some Time-Varying Coefficient Autoregressions," Cowles Foundation Discussion Papers 1916, Cowles Foundation for Research in Economics, Yale University.
    5. Yoon, Gawon, 2004. "On the existence of expected utility with CRRA under STUR," Economics Letters, Elsevier, vol. 83(2), pages 219-224, May.
    6. W. K. Li & Shiqing Ling & Michael McAleer, 2001. "A Survey of Recent Theoretical Results for Time Series Models with GARCH Errors," ISER Discussion Paper 0545, Institute of Social and Economic Research, Osaka University.
    7. Brendan McCabe & Stephen Leybourne & David Harris, 2003. "Testing for Stochastic Cointegration and Evidence for Present Value Models," Econometrics 0311009, University Library of Munich, Germany.
    8. Amaze Lusompa, 2021. "Local Projections, Autocorrelation, and Efficiency," Research Working Paper RWP 21-01, Federal Reserve Bank of Kansas City.
    9. Angelos Kanas, 2009. "Real exchange rate, stationarity, and economic fundamentals," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 33(4), pages 393-409, October.
    10. Palandri, Alessandro, 2024. "Reconciling interest rates evidence with theory: Rejecting unit roots when the HD(1) is a competing alternative," Journal of Banking & Finance, Elsevier, vol. 161(C).
    11. K Abadir & W Distaso, "undated". "Testing joint hypotheses when one of the alternatives is one-sided," Discussion Papers 05/13, Department of Economics, University of York.
    12. Lajos Horvath & Lorenzo Trapani, 2021. "Changepoint detection in random coefficient autoregressive models," Papers 2104.13440, arXiv.org.
    13. Yoon, Gawon, 2005. "An introduction to I([infinity]) processes," Economic Modelling, Elsevier, vol. 22(3), pages 473-483, May.
    14. Trapani, Lorenzo, 2021. "A test for strict stationarity in a random coefficient autoregressive model of order 1," Statistics & Probability Letters, Elsevier, vol. 177(C).
    15. Charemza W.W. & M. Lifshits & S. Makarova, 2002. "Conditional testing for unit-root bilinearity in financial time series: some theoretical and empirical results," Computing in Economics and Finance 2002 251, Society for Computational Economics.
    16. Lorenzo Trapani, 2021. "Testing for strict stationarity in a random coefficient autoregressive model," Econometric Reviews, Taylor & Francis Journals, vol. 40(3), pages 220-256, April.
    17. Westerlund, Joakim & Larsson, Rolf, 2009. "Testing for a Unit Root in a Random Coefficient Panel Data Model," Working Papers in Economics 383, University of Gothenburg, Department of Economics.
    18. Muriel, Nelson & González-Farías, Graciela, 2018. "Testing the null of difference stationarity against the alternative of a stochastic unit root: A new test based on multivariate STUR," Econometrics and Statistics, Elsevier, vol. 7(C), pages 46-62.
    19. Daisuke Nagakura, 2007. "Testing for Coefficient Stability of AR(1) Model When the Null is an Integrated or a Stationary Process," IMES Discussion Paper Series 07-E-20, Institute for Monetary and Economic Studies, Bank of Japan.
    20. Fong, P.W. & Li, W.K. & An, Hong-Zhi, 2006. "A simple multivariate ARCH model specified by random coefficients," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1779-1802, December.
    21. Zacharias Psaradakis & Martin Sola & Fabio Spagnolo, 2004. "On Markov error-correction models, with an application to stock prices and dividends," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(1), pages 69-88.
    22. Franco Bevilacqua & Adriaan van Zon, 2004. "Random walks and non-linear paths in macroeconomic time series: some evidence and implications," Chapters, in: John Foster & Werner Hölzl (ed.), Applied Evolutionary Economics and Complex Systems, chapter 3, Edward Elgar Publishing.
    23. Hwa-Taek Lee & Gawon Yoon, 2013. "Does purchasing power parity hold sometimes? Regime switching in real exchange rates," Applied Economics, Taylor & Francis Journals, vol. 45(16), pages 2279-2294, June.
    24. Angelos Kanas, 2009. "Real exchange rates and developing countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 14(3), pages 280-299.
    25. Ruey Yau & C. James Hueng, 2007. "Output convergence revisited: new time series results on industrialized countries," Applied Economics Letters, Taylor & Francis Journals, vol. 14(1), pages 75-77.
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    103. Gil-Alana, L. A. & Robinson, P. M., 1997. "Testing of unit root and other nonstationary hypotheses in macroeconomic time series," Journal of Econometrics, Elsevier, vol. 80(2), pages 241-268, October.
    104. María Presno & Manuel Landajo, 2010. "Computation of limiting distributions in stationarity testing with a generic trend," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 71(2), pages 165-183, March.
    105. Manuel Landajo & María José Presno, 2010. "Stationarity testing under nonlinear models. Some asymptotic results," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(5), pages 392-405, September.
    106. Chang, Koying & Filer, Larry & Ying, Yung-Hsiang, 2002. "A structural decomposition of business cycles in Taiwan," China Economic Review, Elsevier, vol. 13(1), pages 53-64.
    107. Luciano Gutierrez, 2005. "Tests for cointegration in panels with regime shifts," Econometrics 0505007, University Library of Munich, Germany.
    108. Amano, Robert A., 1998. "On the Optimal Seigniorage Hypothesis," Journal of Macroeconomics, Elsevier, vol. 20(2), pages 295-308, April.
    109. Pascalau, Razvan, 2008. "Unit Roots Tests with Smooth Breaks: An Application to the Nelson-Plosser Data Set," MPRA Paper 7220, University Library of Munich, Germany.
    110. Deb, Surajit, 2004. "Terms of Trade and Investment Behaviour in Indian Agriculture: A Cointegration Analysis," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 59(2), pages 1-22.
    111. Michael Bleaney, 1998. "Market Efficiency and Apparent Unit Roots: An Application to Exchange Rates," The Economic Record, The Economic Society of Australia, vol. 74(225), pages 139-144, June.
    112. Fabio Busetti & Silvestro di Sanzo, 2011. "Bootstrap LR tests of stationarity, common trends and cointegration," Temi di discussione (Economic working papers) 799, Bank of Italy, Economic Research and International Relations Area.
    113. Lee, Junsoo, 1996. "On the power of stationarity tests using optimal bandwidth estimates," Economics Letters, Elsevier, vol. 51(2), pages 131-137, May.

  27. Leybourne, S J & McCabe, B P M, 1994. "A Simple Test for Cointegration," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 56(1), pages 97-103, February.

    Cited by:

    1. Hassler, Uwe, 2009. "The Effect of Linear Time Trends on Cointegration Testing in Single Equations," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77573, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    2. Josep Lluís Carrion‐i‐Silvestre & Andreu Sansó, 2006. "Testing the Null of Cointegration with Structural Breaks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(5), pages 623-646, October.
    3. Villanueva, O. Miguel, 2007. "Spot-forward cointegration, structural breaks and FX market unbiasedness," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 17(1), pages 58-78, February.
    4. G. Everaert, 2007. "Estimating Long-Run Relationships between Observed Integrated Variables by Unobserved Component Methods," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/452, Ghent University, Faculty of Economics and Business Administration.
    5. Christoph Hanck & Till Massing, 2021. "Testing for Nonlinear Cointegration under Heteroskedasticity," Papers 2102.08809, arXiv.org, revised Oct 2024.
    6. Andy Snell, "undated". "Testing For R Versus R-1 Cointegrating Vectors," Discussion Papers 1995-10, Edinburgh School of Economics, University of Edinburgh.
    7. David E.A. Giles & Gugsa T. Werkneh & Betty J. Johnson, 2001. "Asymmetric Responses of the Underground Economy to Tax Changes: Evidence From New Zealand Data," The Economic Record, The Economic Society of Australia, vol. 77(237), pages 148-159, June.
    8. D. Schimmelpfennig & C. Thirtle, 1994. "Cointegration, And Causality: Exploring The Relationship Between Agricultural And Productivity," Journal of Agricultural Economics, Wiley Blackwell, vol. 45(2), pages 220-231, May.
    9. Javier Fernandez-Macho, 2013. "A wavelet approach to multiple cointegration testing," Economics Series Working Papers 668, University of Oxford, Department of Economics.
    10. Judith A. Giles & Sadaf Mirza, 1999. "Some Pretesting Issues on Testing for Granger Noncausality," Econometrics Working Papers 9914, Department of Economics, University of Victoria.
    11. David E. A. Giles & Betty J. Johnson, 1999. "Taxes, Risk-Aversion, and the Size of the Underground Economy: A Nonparametric Analysis With New Zealand Data," Econometrics Working Papers 9910, Department of Economics, University of Victoria.
    12. Erik Hjalmarsson & Pär Österholm, 2007. "A residual-based cointegration test for near unit root variables," International Finance Discussion Papers 907, Board of Governors of the Federal Reserve System (U.S.).
    13. David Harvey & Stephen Leybourne & Paul Newbold, 2003. "How great are the great ratios?," Applied Economics, Taylor & Francis Journals, vol. 35(2), pages 163-177.
    14. Javier Fernandez-Macho, 2013. "A Test for the Null of Multiple Cointegrating Vectors," Economics Series Working Papers 657, University of Oxford, Department of Economics.

  28. McCabe, B. P. M., 1989. "Misspecification tests in econometrics based on ranks," Journal of Econometrics, Elsevier, vol. 40(2), pages 261-278, February.

    Cited by:

    1. Andrews, Donald W.K. & Marmer, Vadim, 2008. "Exactly distribution-free inference in instrumental variables regression with possibly weak instruments," Journal of Econometrics, Elsevier, vol. 142(1), pages 183-200, January.
    2. Mazzi, Francesco & Slack, Richard & Tsalavoutas, Ioannis, 2018. "The effect of corruption and culture on mandatory disclosure compliance levels: Goodwill reporting in Europe," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 31(C), pages 52-73.
    3. Michail Nerantzidis, 2018. "The role of weighting in corporate governance ratings," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 22(3), pages 589-628, September.
    4. Breitung, Jorg & Gourieroux, Christian, 1997. "Rank tests for unit roots," Journal of Econometrics, Elsevier, vol. 81(1), pages 7-27, November.
    5. Luger, Richard, 2006. "Exact permutation tests for non-nested non-linear regression models," Journal of Econometrics, Elsevier, vol. 133(2), pages 513-529, August.
    6. Maria Baldini & Lorenzo Dal Maso & Giovanni Liberatore & Francesco Mazzi & Simone Terzani, 2018. "Role of Country- and Firm-Level Determinants in Environmental, Social, and Governance Disclosure," Journal of Business Ethics, Springer, vol. 150(1), pages 79-98, June.
    7. Francesco Mazzi & Paul André & Dionysia Dionysiou & Ioannis Tsalavoutas, 2017. "Compliance with goodwill-related mandatory disclosure requirements and the cost of equity capital," Accounting and Business Research, Taylor & Francis Journals, vol. 47(3), pages 268-312, April.

  29. Leybourne, S J & McCabe, B P M, 1989. "Testing for Coefficient Constancy in Random Walk Models with Particular Reference to the Initial Value Problem," Empirical Economics, Springer, vol. 14(2), pages 105-112.

    Cited by:

    1. Sahbi FARHANI, 2012. "Tests of Parameters Instability: Theoretical Study and Empirical Analysis on Two Types of Models (ARMA Model and Market Model)," International Journal of Economics and Financial Issues, Econjournals, vol. 2(3), pages 246-266.

  30. McCabe, B.P.M., 1988. "A Multiple Decision Theory Analysis of Structural Stability in Regression," Econometric Theory, Cambridge University Press, vol. 4(3), pages 499-508, December.

    Cited by:

    1. Lajos Horváth & William Pouliot & Shixuan Wang, 2017. "Detecting at-Most-m Changes in Linear Regression Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(4), pages 552-590, July.
    2. Olmo Jose & Pouliot William, 2011. "Early Detection Techniques for Market Risk Failure," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(4), pages 1-55, September.

  31. Phillips, G. D. A. & McCabe, B. P., 1983. "The independence of tests for structural change in regression models," Economics Letters, Elsevier, vol. 12(3-4), pages 283-287.

    Cited by:

    1. MacKinnon, J G, 1989. "Heteroskedasticity-Robust Tests for Structural Change," Empirical Economics, Springer, vol. 14(2), pages 77-92.
    2. Tzavalis, E. & Wickens, M.R., 1994. "The Persistence in Volatility of the US Term Premium 1970-1986," Discussion Papers 9409, University of Exeter, Department of Economics.
    3. Maasoumi, Esfandiar & Zaman, Asad & Ahmed, Mumtaz, 2010. "Tests for structural change, aggregation, and homogeneity," Economic Modelling, Elsevier, vol. 27(6), pages 1382-1391, November.
    4. Tucci, Marco P., 1995. "Time-varying parameters: a critical introduction," Structural Change and Economic Dynamics, Elsevier, vol. 6(2), pages 237-260, June.
    5. John J. Beggs, 1988. "Diagnostic Testing in Applied Econometrics," The Economic Record, The Economic Society of Australia, vol. 64(2), pages 81-101, June.
    6. Tarek Ibrahim Eldomiaty & Marwa Anwar & Nebal Magdy & Mohamed Nabil Hakam, 2020. "Robust examination of political structural breaks and abnormal stock returns in Egypt," Future Business Journal, Springer, vol. 6(1), pages 1-9, December.
    7. Ozcam, Ahmet & Judge, George, 1988. "The Analytical Risk of a Two Stage Pretest Estimator in the Case of Possible Heteroscedasticity," CUDARE Working Papers 198478, University of California, Berkeley, Department of Agricultural and Resource Economics.

  32. B. P. M. McCabe & M. J. Harrison, 1980. "Testing the Constancy of Regression Relationships Over Time Using Least Squares Residuals," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(2), pages 142-148, June.

    Cited by:

    1. Olmo, Jose & Pilbeam, Keith & Pouliot, William, 2011. "Detecting the presence of insider trading via structural break tests," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2820-2828, November.
    2. Olmo, J. & Pilbeam, K. & Pouliot, W., 2009. "Detecting the Presence of Informed Price Trading Via Structural Break Tests," Working Papers 09/10, Department of Economics, City University London.
    3. Deng, Ai & Perron, Pierre, 2008. "The Limit Distribution Of The Cusum Of Squares Test Under General Mixing Conditions," Econometric Theory, Cambridge University Press, vol. 24(3), pages 809-822, June.
    4. Anders Westlund, 1984. "Sequential moving sums of squares of OLS residuals in parameter stability testing," Quality & Quantity: International Journal of Methodology, Springer, vol. 18(3), pages 261-273, May.
    5. Deng, Ai & Perron, Pierre, 2008. "A non-local perspective on the power properties of the CUSUM and CUSUM of squares tests for structural change," Journal of Econometrics, Elsevier, vol. 142(1), pages 212-240, January.
    6. Lee, B.M.S. & Bui-Lan, Anh, 1982. "Use Of Errors Of Prediction In Improving Forecast Accuracy: An Application To Wool In Australia," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 26(1), pages 1-14, April.
    7. Rao, Yao & McCabe, Brendan, 2017. "Is MORE LESS? The role of data augmentation in testing for structural breaks," Economics Letters, Elsevier, vol. 155(C), pages 131-134.
    8. Nielsen, Bent & Sohkanen, Jouni S., 2011. "Asymptotic Behavior Of The Cusum Of Squares Test Under Stochastic And Deterministic Time Trends," Econometric Theory, Cambridge University Press, vol. 27(4), pages 913-927, August.
    9. Pierre Perron & Tomoyoshi Yabu, 2007. "Estimating Deterministic Trend with an Integrated or Stationary Noise Component," Boston University - Department of Economics - Working Papers Series WP2007-020, Boston University - Department of Economics.
    10. Vanessa Berenguer-Rico & Bent Nielsen, 2015. "Cumulated sum of squares statistics for non-linear and non-stationary regressions," Economics Papers 2015-W09, Economics Group, Nuffield College, University of Oxford.
    11. Yao Rao & Brendan McCabe, 2020. "Structural Change and the Problem of Phantom Break Locations," Manchester School, University of Manchester, vol. 88(1), pages 211-228, January.
    12. Watson, G. S., 1995. "Detecting a change in the intercept in multiple regression," Statistics & Probability Letters, Elsevier, vol. 23(1), pages 69-72, April.
    13. Saima Siddiqui & Sameena Zehra & Sadia Majeed & Muhammad Sabihuddin Butt, 2008. "Export-Led Growth Hypothesis in Pakistan: A Reinvestigation Using the Bounds Test," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 13(2), pages 59-80, Jul-Dec.
    14. Banerjee, Anindya & Lumsdaine, Robin L & Stock, James H, 1992. "Recursive and Sequential Tests of the Unit-Root and Trend-Break Hypotheses: Theory and International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 271-287, July.
    15. Ai Deng & Pierre Perron, 2005. "The Limit Distribution of the CUSUM of Square Test Under Genreal MIxing Conditions," Boston University - Department of Economics - Working Papers Series WP2005-046, Boston University - Department of Economics.
    16. Shujaat Naeem Azmi & Shakeb Akhtar, 2023. "Interactions of services export, financial development and growth: evidence from India," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(5), pages 4709-4724, October.

  33. O'Hagan, John W & McCabe, Brendan, 1975. "Tests for the Severity of Multicollinearity in Regression Analysis: A Comment," The Review of Economics and Statistics, MIT Press, vol. 57(3), pages 368-370, August.

    Cited by:

    1. David A. Belsley, 1976. "Multicollinearity: Diagnosing its Presence and Assessing the Potential Damage It Causes Least Squares Estimation," NBER Working Papers 0154, National Bureau of Economic Research, Inc.
    2. Emilian Dobrescu, 2018. "Functional trinity of public finance in an emerging economy," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 7(1), pages 1-27, December.
    3. Valmor Comim Junior, 2021. "Literature review on Drivers of Chinese Outward Foreign Direct Investment," International Journal of Science and Business, IJSAB International, vol. 5(4), pages 143-157.
    4. Jørgen Lauridsen & Jesùs Mur, 2006. "Multicollinearity in cross-sectional regressions," Journal of Geographical Systems, Springer, vol. 8(4), pages 317-333, October.

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