IDEAS home Printed from https://ideas.repec.org/e/c/ptr191.html
   My authors  Follow this author

Andrew R. Tremayne

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.

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Davies, N & Tremayne, A R, 1994. "Review of STATGRAPHICS," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(3), pages 335-341, July-Sept.

    Mentioned in:

    1. Review of statgraphics (Journal of Applied Econometrics 1994) in ReplicationWiki ()

Working papers

  1. Tena Horrillo, Juan de Dios & Tremayne, A. R., 2006. "Modelling monetary transmission in UK manufacturing industry," DES - Working Papers. Statistics and Econometrics. WS ws062911, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Andrey Sinyakov, 2013. "Declared and actual policy of the Russian Central Bank in 2000–2008: how large is the difference? (in Russian)," Quantile, Quantile, issue 11, pages 91-106, December.
    2. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.
    3. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Fed’s unconventional monetary policy and risk spillover in the US financial markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 42-52.
    4. Tena Horrillo, Juan de Dios & Tremayne, A. R., 2006. "Modelling monetary transmission in UK manufacturing industry," DES - Working Papers. Statistics and Econometrics. WS ws062911, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Roy, Ripon & Bashar, Omar H.N.M. & Bhattacharya, Prasad Sankar, 2023. "The cross-industry effects of monetary policy: New evidence from Bangladesh," Economic Modelling, Elsevier, vol. 127(C).
    6. Bucci, Andrea & Ciciretti, Vito, 2022. "Market regime detection via realized covariances," Economic Modelling, Elsevier, vol. 111(C).
    7. Martin Bruns & Michele Piffer, 2021. "Monetary policy shocks over the business cycle: Extending the Smooth Transition framework," University of East Anglia School of Economics Working Paper Series 2021-07, School of Economics, University of East Anglia, Norwich, UK..
    8. Singh, Sunny Kumar & Rao, D. Tripati, 2014. "Sectoral effects of monetary policy shock: evidence from India," MPRA Paper 62069, University Library of Munich, Germany.
    9. Demetrescu, Matei & Leppin, Julian Sebastian & Reitz, Stefan, 2017. "Homogenous vs. heterogenous transition functions in smooth transition regressions: A LM-type test," Kiel Working Papers 2094, Kiel Institute for the World Economy (IfW Kiel).
    10. Alam, Tasneem & Waheed, Muhammad, 2006. "The monetary transmission mechanism in Pakistan: a sectoral analysis," MPRA Paper 2719, University Library of Munich, Germany, revised 13 Apr 2007.

  2. Tsung Ping Chung & Peter Dolton & Andrew Tremayne, 2004. "The Determinants Of Teacher Supply: Time Series Evidence For The UK, 1962-2001," Royal Economic Society Annual Conference 2004 66, Royal Economic Society.

    Cited by:

    1. Frijters, Paul & Shields, Michael A. & Wheatley Price, Stephen, 2004. "To Teach or Not to Teach? Panel Data Evidence on the Quitting Decision," IZA Discussion Papers 1164, Institute of Labor Economics (IZA).
    2. Leigh, Andrew, 2012. "Teacher pay and teacher aptitude," Economics of Education Review, Elsevier, vol. 31(3), pages 41-53.

  3. 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.

  4. Jung, Robert & Tremayne, Andrew R., 2001. "Testing serial dependence in time series models of counts against some INARMA alternatives," Tübinger Diskussionsbeiträge 204, University of Tübingen, School of Business and Economics.

    Cited by:

    1. Stadler, Manfred & Wapler, Rüdiger, 2001. "Endogenous skilled-biased technological change and matching unemployment," Tübinger Diskussionsbeiträge 220, University of Tübingen, School of Business and Economics.
    2. Pitterle, Ingo & Steffen, Dirk, 2004. "Welfare Effects of Fiscal Policy under Alternative Exchange Rate Regimes : The Role of the Scale Variable of Money Demand," Tübinger Diskussionsbeiträge 284, University of Tübingen, School of Business and Economics.
    3. Köpke, Nikola & Baten, Jörg, 2003. "The biological standard of living in Europe during the last two millennia," Tübinger Diskussionsbeiträge 265, University of Tübingen, School of Business and Economics.
    4. Stadler, Manfred, 2003. "Innovation and growth: The role of labor-force qualification," Tübinger Diskussionsbeiträge 255, University of Tübingen, School of Business and Economics.
    5. Baten, Jörg & Wallusch, Jacek, 2003. "Market integration and disintegration of Poland and Gemany [Germany] in the 18th century," Tübinger Diskussionsbeiträge 268, University of Tübingen, School of Business and Economics.

  5. Robert C. Jung & Andrew R. Tremayne, 2000. "Testing Serial Dependence in Time Series Models of Counts," Econometric Society World Congress 2000 Contributed Papers 1563, Econometric Society, revised 22 Mar 2001.

    Cited by:

    1. Stadler, Manfred & Wapler, Rüdiger, 2001. "Endogenous skilled-biased technological change and matching unemployment," Tübinger Diskussionsbeiträge 220, University of Tübingen, School of Business and Economics.
    2. Pitterle, Ingo & Steffen, Dirk, 2004. "Welfare Effects of Fiscal Policy under Alternative Exchange Rate Regimes : The Role of the Scale Variable of Money Demand," Tübinger Diskussionsbeiträge 284, University of Tübingen, School of Business and Economics.
    3. Köpke, Nikola & Baten, Jörg, 2003. "The biological standard of living in Europe during the last two millennia," Tübinger Diskussionsbeiträge 265, University of Tübingen, School of Business and Economics.
    4. Stadler, Manfred, 2003. "Innovation and growth: The role of labor-force qualification," Tübinger Diskussionsbeiträge 255, University of Tübingen, School of Business and Economics.
    5. Baten, Jörg & Wallusch, Jacek, 2003. "Market integration and disintegration of Poland and Gemany [Germany] in the 18th century," Tübinger Diskussionsbeiträge 268, University of Tübingen, School of Business and Economics.

  6. 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. 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.
    3. Trapani, Lorenzo, 2021. "A test for strict stationarity in a random coefficient autoregressive model of order 1," Statistics & Probability Letters, Elsevier, vol. 177(C).
    4. 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.
    5. 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.
    6. 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.
    7. Granger, E.J. & Swanson, N.R., 1996. "An introduction to stochastic Unit Root Processes," Papers 4-96-3, Pennsylvania State - Department of Economics.
    8. Distaso, Walter, 2008. "Testing for unit root processes in random coefficient autoregressive models," Journal of Econometrics, Elsevier, vol. 142(1), pages 581-609, January.
    9. Ha, Jeongcheol & Lee, Sangyeol, 2002. "Coefficient constancy test in AR-ARCH models," Statistics & Probability Letters, Elsevier, vol. 57(1), pages 65-77, March.
    10. Horváth, Lajos & Trapani, Lorenzo, 2019. "Testing for randomness in a random coefficient autoregression model," Journal of Econometrics, Elsevier, vol. 209(2), pages 338-352.
    11. 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.
    12. 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.
    13. 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. 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.

    Cited by:

    1. 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.
    2. Malte Jahn, 2023. "Artificial neural networks and time series of counts: A class of nonlinear INGARCH models," Papers 2304.01025, arXiv.org.

  2. 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.

    Cited by:

    1. Vladica S. Stojanović & Hassan S. Bakouch & Eugen Ljajko & Najla Qarmalah, 2023. "Zero-and-One Integer-Valued AR(1) Time Series with Power Series Innovations and Probability Generating Function Estimation Approach," Mathematics, MDPI, vol. 11(8), pages 1-25, April.
    2. 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.
    3. Frazier, David T. & Oka, Tatsushi & Zhu, Dan, 2019. "Indirect inference with a non-smooth criterion function," Journal of Econometrics, Elsevier, vol. 212(2), pages 623-645.
    4. Gareth Liu-Evans, 2021. "Improving the Estimation and Predictions of Small Time Series Models," Working Papers 202106, University of Liverpool, Department of Economics.
    5. 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.

  3. Robert C. Jung & A. R. Tremayne, 2011. "Convolution‐closed models for count time series with applications," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(3), pages 268-280, May.

    Cited by:

    1. Bisaglia, Luisa & Canale, Antonio, 2016. "Bayesian nonparametric forecasting for INAR models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 70-78.
    2. Shirozhan, M. & Bakouch, Hassan S. & Mohammadpour, M., 2023. "A flexible INAR(1) time series model with dependent zero-inflated count series and medical contagious cases," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 206(C), pages 216-230.
    3. Nisreen Shamma & Mehrnaz Mohammadpour & Masoumeh Shirozhan, 2020. "A time series model based on dependent zero inflated counting series," Computational Statistics, Springer, vol. 35(4), pages 1737-1757, December.
    4. Jentsch, Carsten & Weiß, Christian, 2017. "Bootstrapping INAR models," Working Papers 17-02, University of Mannheim, Department of Economics.
    5. 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.
    6. 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.

  4. 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.

    Cited by:

    1. Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2017. "Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers," ETA: Economic Theory and Applications 253725, Fondazione Eni Enrico Mattei (FEEM).
    2. Christian H. Weiß & Esmeralda Gonçalves & Nazaré Mendes Lopes, 2017. "Testing the compounding structure of the CP-INARCH model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(5), pages 571-603, July.
    3. Šárka Hudecová & Marie Hušková & Simos G. Meintanis, 2017. "Tests for Structural Changes in Time Series of Counts," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(4), pages 843-865, December.
    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. Chen, Cathy W.S. & Lee, Sangyeol, 2016. "Generalized Poisson autoregressive models for time series of counts," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 51-67.
    6. Jiwon Kang & Sangyeol Lee, 2014. "Parameter Change Test for Poisson Autoregressive Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(4), pages 1136-1152, December.
    7. Veraart, Almut E.D., 2019. "Modeling, simulation and inference for multivariate time series of counts using trawl processes," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 110-129.
    8. Andrea BASTIANIN & Marzio GALEOTTI & Matteo MANERA, 2011. "Forecast evaluation in call centers: combined forecasts, flexible loss functions and economic criteria," Departmental Working Papers 2011-08, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    9. 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.
    10. 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.
    11. Marcelo Bourguignon & Christian H. Weiß, 2017. "An INAR(1) process for modeling count time series with equidispersion, underdispersion and overdispersion," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(4), pages 847-868, December.
    12. 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.
    13. Ole E. Barndorff-Nielsen & Asger Lunde & Neil Shephard & Almut E.D. Veraart, 2014. "Integer-valued Trawl Processes: A Class of Stationary Infinitely Divisible Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(3), pages 693-724, September.
    14. Robert C. Jung & Stephanie Glaser, 2022. "Modelling and Diagnostics of Spatially Autocorrelated Counts," Econometrics, MDPI, vol. 10(3), pages 1-17, September.
    15. Stephanie Glaser & Robert C. Jung & Karsten Schweikert, 2022. "Spatial panel count data: modeling and forecasting of urban crimes," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-29, December.
    16. 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.
    17. Christian Weiß & Hee-Young Kim, 2013. "Parameter estimation for binomial AR(1) models with applications in finance and industry," Statistical Papers, Springer, vol. 54(3), pages 563-590, August.
    18. 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).
    19. Christian H. Weiß & Sebastian Schweer, 2015. "Detecting overdispersion in INARCH(1) processes," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(3), pages 281-297, August.
    20. Li, Qi & Lian, Heng & Zhu, Fukang, 2016. "Robust closed-form estimators for the integer-valued GARCH (1,1) model," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 209-225.
    21. 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.
    22. Lívio Tito & Bourguignon Marcelo & Nascimento Fernando, 2020. "INAR(1) Processes with Inflated-parameter Generalized Power Series Innovations," Journal of Time Series Econometrics, De Gruyter, vol. 12(2), pages 1-27, July.
    23. 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.
    24. 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.
    25. 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.
    26. Wagner Barreto-Souza, 2019. "Mixed Poisson INAR(1) processes," Statistical Papers, Springer, vol. 60(6), pages 2119-2139, December.

  5. Tena, Juan de Dios & Tremayne, A.R., 2009. "Modelling monetary transmission in UK manufacturing industry," Economic Modelling, Elsevier, vol. 26(5), pages 1053-1066, September.
    See citations under working paper version above.
  6. S. de Silva & K. Hadri & A. R. Tremayne, 2009. "Panel unit root tests in the presence of cross-sectional dependence: finite sample performance and an application," Econometrics Journal, Royal Economic Society, vol. 12(2), pages 340-366, July.

    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. Amélie Charles & Olivier Darné & Jean-François Hoarau, 2010. "Does the real GDP per capita convergence hold in the Common Market for Eastern and Southern Africa?," Post-Print hal-00797485, HAL.
    3. Mitze, Timo & Reinkowski, Janina, 2010. "Testing the Neoclassical Migration Model: Overall and Age-Group Specific Results for German Regions," Ruhr Economic Papers 226, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    4. Özyurt, Selin & Mitze, Timo, 2012. "The Spatial Dimension of Trade- and FDI-driven Productivity Growth in Chinese Provinces – A Global Cointegration Approach," Ruhr Economic Papers 308, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    5. HASHIGUCHI, Yoshihiro & HAMORI, Shigeyuki, 2010. "Small sample properties of CIPS panel unit root test under conditional and unconditional heteroscedasticity," MPRA Paper 24053, University Library of Munich, Germany.
    6. Amélie Charles & Olivier Darne & Jean-François Hoarau, 2012. "Convergence of real per capita GDP within COMESA countries: A panel unit root evidence," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 49(1), pages 53-71, August.
    7. Juan Aquino-Chávez & N.R. Ramírez-Rondán, 2017. "Estimating Factor Shares from Nonstationary Panel Data," Working Papers 89, Peruvian Economic Association.
    8. Robertson, Donald & Sarafidis, Vasilis & Westerlund, Joakim, 2014. "GMM Unit Root Inference in Generally Trending and Cross-Correlated Dynamic Panels," MPRA Paper 53419, University Library of Munich, Germany.
    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. Chingnun Lee & Jyh-Lin Wu & Lixiong Yang, 2016. "A Simple Panel Unit-Root Test with Smooth Breaks in the Presence of a Multifactor Error Structure," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(3), pages 365-393, June.
    11. Munir, Qaiser & Lean, Hooi Hooi & Smyth, Russell, 2020. "CO2 emissions, energy consumption and economic growth in the ASEAN-5 countries: A cross-sectional dependence approach," Energy Economics, Elsevier, vol. 85(C).
    12. Becheri, I.G., 2012. "Limiting experiments for panel-data and jump-diffusion models," Other publications TiSEM 7e53f6cf-fab1-4f86-9e5d-b, Tilburg University, School of Economics and Management.
    13. 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.
    14. Mitze, Timo & Reinkowski, Janina, 2010. "Testing the Validity of the Neoclassical Migration Model: Overall and Age-Group Specific Estimation Results for German Spatial Planning Regions," MPRA Paper 23616, University Library of Munich, Germany.
    15. Shuddhasattwa Rafiq & Ruhul Salim, 2014. "Does oil price volatility matter for Asian emerging economies?," Economic Analysis and Policy, Elsevier, vol. 44(4), pages 417-441.
    16. Honoré Tekam Oumbé & Ronald Djeunankan & Alain Mekia Ndzana, 2023. "Does information and communication technologies affect economic complexity?," SN Business & Economics, Springer, vol. 3(4), pages 1-25, April.

  7. 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.

    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. 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.
    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. 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. Mohammadipour, Maryam & Boylan, John E., 2012. "Forecast horizon aggregation in integer autoregressive moving average (INARMA) models," Omega, Elsevier, vol. 40(6), pages 703-712.
    6. Chen Xi & Wang Lihong, 2013. "Conditional L1 estimation for random coefficient integer-valued autoregressive processes," Statistics & Risk Modeling, De Gruyter, vol. 30(3), pages 221-235, August.
    7. Bisaglia, Luisa & Canale, Antonio, 2016. "Bayesian nonparametric forecasting for INAR models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 70-78.
    8. 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.
    9. 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.
    10. Shirozhan, M. & Bakouch, Hassan S. & Mohammadpour, M., 2023. "A flexible INAR(1) time series model with dependent zero-inflated count series and medical contagious cases," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 206(C), pages 216-230.
    11. 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.
    12. 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.
    13. Christian H. Weiß, 2013. "Integer-valued autoregressive models for counts showing underdispersion," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(9), pages 1931-1948, September.
    14. Jentsch, Carsten & Weiß, Christian, 2017. "Bootstrapping INAR models," Working Papers 17-02, University of Mannheim, Department of Economics.
    15. 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.
    16. 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.
    17. 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.
    18. Xinyang Wang & Dehui Wang & Kai Yang, 2021. "Integer-valued time series model order shrinkage and selection via penalized quasi-likelihood approach," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(5), pages 713-750, July.
    19. Jung, Robert C. & Kukuk, Martin & Liesenfeld, Roman, 2006. "Time series of count data: modeling, estimation and diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2350-2364, December.
    20. 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.
    21. 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.
    22. Maia, Gisele de Oliveira & Barreto-Souza, Wagner & Bastos, Fernando de Souza & Ombao, Hernando, 2021. "Semiparametric time series models driven by latent factor," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1463-1479.
    23. Hee-Young Kim & Yousung Park, 2008. "A non-stationary integer-valued autoregressive model," Statistical Papers, Springer, vol. 49(3), pages 485-502, July.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. Luisa Bisaglia & Margherita Gerolimetto, 2019. "Model-based INAR bootstrap for forecasting INAR(p) models," Computational Statistics, Springer, vol. 34(4), pages 1815-1848, December.

  8. Robert Jung & Gerd Ronning & A. Tremayne, 2005. "Estimation in conditional first order autoregression with discrete support," Statistical Papers, Springer, vol. 46(2), pages 195-224, April.

    Cited by:

    1. Christian H. Weiß, 2012. "Fully observed INAR(1) processes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(3), pages 581-598, July.
    2. 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.
    3. Vladica S. Stojanović & Hassan S. Bakouch & Eugen Ljajko & Najla Qarmalah, 2023. "Zero-and-One Integer-Valued AR(1) Time Series with Power Series Innovations and Probability Generating Function Estimation Approach," Mathematics, MDPI, vol. 11(8), pages 1-25, April.
    4. 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.
    5. 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.
    6. Chen Xi & Wang Lihong, 2013. "Conditional L1 estimation for random coefficient integer-valued autoregressive processes," Statistics & Risk Modeling, De Gruyter, vol. 30(3), pages 221-235, August.
    7. Bisaglia, Luisa & Canale, Antonio, 2016. "Bayesian nonparametric forecasting for INAR models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 70-78.
    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. Christian H. Weiß, 2013. "Integer-valued autoregressive models for counts showing underdispersion," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(9), pages 1931-1948, September.
    11. Sebastian Schweer & Christian H. Weiß, 2016. "Testing for Poisson arrivals in INAR(1) processes," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(3), pages 503-524, September.
    12. 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.
    13. 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.
    14. Kai Yang & Dehui Wang & Boting Jia & Han Li, 2018. "An integer-valued threshold autoregressive process based on negative binomial thinning," Statistical Papers, Springer, vol. 59(3), pages 1131-1160, September.
    15. 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.
    16. Sebastian Schweer, 2016. "A Goodness-of-Fit Test for Integer-Valued Autoregressive Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(1), pages 77-98, January.
    17. 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.
    18. 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.
    19. Christian Weiß & Hee-Young Kim, 2013. "Parameter estimation for binomial AR(1) models with applications in finance and industry," Statistical Papers, Springer, vol. 54(3), pages 563-590, August.
    20. Maxime Faymonville & Carsten Jentsch & Christian H. Weiß & Boris Aleksandrov, 2023. "Semiparametric estimation of INAR models using roughness penalization," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(2), pages 365-400, June.
    21. 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.
    22. Predrag M. Popović & Miroslav M. Ristić & Aleksandar S. Nastić, 2016. "A geometric bivariate time series with different marginal parameters," Statistical Papers, Springer, vol. 57(3), pages 731-753, September.
    23. Zeng, Xiaoqiang & Kakizawa, Yoshihide, 2022. "Bias-correction of some estimators in the INAR(1) process," Statistics & Probability Letters, Elsevier, vol. 187(C).
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.

  9. Godfrey, L.G. & Tremayne, A.R., 2005. "The wild bootstrap and heteroskedasticity-robust tests for serial correlation in dynamic regression models," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 377-395, April.

    Cited by:

    1. Frauke Schleer & Willi Semmler, 2014. "Financial Sector and Output Dynamics in the Euro Area: Non-linearities Reconsidered," SCEPA working paper series. 2014-5, Schwartz Center for Economic Policy Analysis (SCEPA), The New School.
    2. Godfrey, L.G., 2007. "Alternative approaches to implementing Lagrange multiplier tests for serial correlation in dynamic regression models," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3282-3295, April.
    3. Asai, Manabu & Brugal, Ivan, 2013. "Forecasting volatility via stock return, range, trading volume and spillover effects: The case of Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 202-213.
    4. Erdenebat Bataa & Denise R. Osborn & Marianne Sensier & Dick van Dijk, 2009. "Changes in International Business Cycle Affiliations," Economics Discussion Paper Series 0924, Economics, The University of Manchester.
    5. Pavlidis Efthymios G & Paya Ivan & Peel David A, 2010. "Specifying Smooth Transition Regression Models in the Presence of Conditional Heteroskedasticity of Unknown Form," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(3), pages 1-40, May.
    6. Boswijk, H. Peter & Cavaliere, Giuseppe & Rahbek, Anders & Taylor, A.M. Robert, 2016. "Inference on co-integration parameters in heteroskedastic vector autoregressions," Journal of Econometrics, Elsevier, vol. 192(1), pages 64-85.
    7. Andreea Halunga & Chris D. Orme & Takashi Yamagata, 2011. "A Heteroskedasticity Robust Breusch-Pagan Test for Contemporaneous Correlation in Dynamic Panel Data Models," Economics Discussion Paper Series 1118, Economics, The University of Manchester.
    8. David Harris & Hsein Kew, 2014. "Portmanteau Autocorrelation Tests Under Q-Dependence And Heteroskedasticity," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(3), pages 203-217, May.
    9. Erdenebat Bataa & Dong H. Kim & Denise R. Osborn, 2006. "A Further Examination of the Expectations Hypothesis for the Term Structure," Economics Discussion Paper Series 0611, Economics, The University of Manchester.
    10. Jeong, Jinook & Kang, Byunguk, 2006. "Wild-Bootstrapped Variance Ratio Test for Autocorrelation in the Presence of Heteroskedasticity," MPRA Paper 9791, University Library of Munich, Germany, revised May 2008.
    11. Niklas Ahlgren & Paul Catani, 2017. "Wild bootstrap tests for autocorrelation in vector autoregressive models," Statistical Papers, Springer, vol. 58(4), pages 1189-1216, December.
    12. Schleer, Frauke & Semmler, Willi, 2013. "Financial sector-output dynamics in the euro area: Non-linearities reconsidered," ZEW Discussion Papers 13-068, ZEW - Leibniz Centre for European Economic Research.
    13. O'Reilly, Gerard & Whelan, Karl, 2005. "Testing Parameter Stability: A Wild Bootstrap Approach," Research Technical Papers 8/RT/05, Central Bank of Ireland.
    14. Erdenebat Bataa & Dong H. Kim & Denise R. Osborn, 2007. "Expectations Hypothesis Tests in the Presence of Model Uncertainty," Discussion Paper Series 0703, Institute of Economic Research, Korea University.
    15. Klaus Grobys, 2015. "Size distortions of the wild bootstrapped HCCME-based LM test for serial correlation in the presence of asymmetric conditional heteroskedasticity," Empirical Economics, Springer, vol. 48(3), pages 1189-1202, May.
    16. Godfrey, L.G., 2006. "Tests for regression models with heteroskedasticity of unknown form," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2715-2733, June.
    17. Francesco Bravo & Federico Crudu, 2012. "Efficient bootstrap with weakly dependent processes," Discussion Papers 12/08, Department of Economics, University of York.
    18. Liu-Evans Gareth D. & Phillips Garry D. A., 2012. "Bootstrap, Jackknife and COLS: Bias and Mean Squared Error in Estimation of Autoregressive Models," Journal of Time Series Econometrics, De Gruyter, vol. 4(2), pages 1-35, November.
    19. Soo-Bin Jeong & Bong-Hwan Kim & Tae-Hwan Kim & Hyung-Ho Moon, 2017. "Unit Root Tests In The Presence Of Multiple Breaks In Variance," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 62(02), pages 345-361, June.
    20. Erdenebat Bataa & Denise R. Osborn & Marianne Sensier & Dick van Dijk, 2009. "Structural Breaks in the International Transmission of Inflation," Centre for Growth and Business Cycle Research Discussion Paper Series 119, Economics, The University of Manchester.
    21. Pavlidis Efthymios G. & Paya Ivan & Peel David A., 2013. "Nonlinear causality tests and multivariate conditional heteroskedasticity: a simulation study," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(3), pages 297-312, May.

  10. Paulo M. M. Rodrigues & Andrew Tremayne, 2004. "F versus t tests for unit roots: a comment," Economics Bulletin, AccessEcon, vol. 3(12), pages 1-7.

    Cited by:

    1. Peter E. Kennedy & John Elder, 2004. "More on F versus t tests for unit roots when there is no trend," Economics Bulletin, AccessEcon, vol. 3(37), pages 1-6.

  11. A Stewart Fotheringham & Phil Rees & Tony Champion & Stamatis Kalogirou & Andy R Tremayne, 2004. "The Development of a Migration Model for England and Wales: Overview and Modelling Out-Migration," Environment and Planning A, , vol. 36(9), pages 1633-1672, September.

    Cited by:

    1. Ioannis Kaplanis & Vassilis Monastiriotis, 2012. "Flexible Employment and Cross-Regional Adjustment," SERC Discussion Papers 0100, Centre for Economic Performance, LSE.
    2. Leo JG Van Wissen & Nicole Gaag & Phil Rees & John Stillwell, 2005. "In search of a modelling strategy for projecting internal migration in European countries - Demographic versus economic-geographical approaches," ERSA conference papers ersa05p787, European Regional Science Association.
    3. Thomas Niedomysl, 2008. "Residential Preferences for Interregional Migration in Sweden: Demographic, Socioeconomic, and Geographical Determinants," Environment and Planning A, , vol. 40(5), pages 1109-1131, May.
    4. Oshan, Taylor M., 2020. "The spatial structure debate in spatial interaction modeling: 50 years on," OSF Preprints 42vxn, Center for Open Science.
    5. Muellbauer, John & Murphy, Anthony & Cameron, Gavin, 2006. "Housing Market Dynamics and Regional Migration in Britain," CEPR Discussion Papers 5832, C.E.P.R. Discussion Papers.
    6. Ian Smith & Rob Atkinson, 2011. "Mobility and the smart, green and inclusive Europe," Local Economy, London South Bank University, vol. 26(6-7), pages 562-576, September.
    7. Adam Dennett & Alan Wilson, 2013. "A Multilevel Spatial Interaction Modelling Framework for Estimating Interregional Migration in Europe," Environment and Planning A, , vol. 45(6), pages 1491-1507, June.

  12. Robert C. Jung & A. R. Tremayne, 2003. "Testing for serial dependence in time series models of counts," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(1), pages 65-84, January.

    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Alfredo García-Hiernaux, 2009. "Diagnostic checking using subspace methods," Documentos de Trabajo del ICAE 2009-03, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    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. Khan Naushad Mamode & Sunecher Yuvraj & Jowaheer Vandna, 2017. "Analyzing the Full BINMA Time Series Process Using a Robust GQL Approach," Journal of Time Series Econometrics, De Gruyter, vol. 9(2), pages 1-12, July.
    10. Franklin E. Zimring & Jeffrey Fagan & David T. Johnson, 2010. "Executions, Deterrence, and Homicide: A Tale of Two Cities," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 7(1), pages 1-29, March.
    11. 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.
    12. 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.
    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. 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.
    15. Robert Jung & Gerd Ronning & A. Tremayne, 2005. "Estimation in conditional first order autoregression with discrete support," Statistical Papers, Springer, vol. 46(2), pages 195-224, April.

  13. J. M. Marriott & J. C. Naylor & A. R. Tremayne, 2003. "Exploring economic time series: a Bayesian graphical approach," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 124-145, June.

    Cited by:

    1. Kelvin Balcombe & Iain Fraser & Abhijit Sharma, 2011. "Bayesian model averaging and identification of structural breaks in time series," Applied Economics, Taylor & Francis Journals, vol. 43(26), pages 3805-3818.
    2. Naylor, J.C. & Tremayne, A.R. & Marriott, J.M., 2010. "Exploratory data analysis and model criticism with posterior plots," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2707-2720, November.
    3. Iolanda Lo Cascio & Stephen Pollock, 2007. "Comparative Economic Cycles," Working Papers 599, Queen Mary University of London, School of Economics and Finance.
    4. Yoon, Gawon, 2005. "Has the U.S. economy really become less correlated with that of the rest of the world?," Economic Modelling, Elsevier, vol. 22(1), pages 147-158, January.
    5. 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.

  14. 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. 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.
    11. Lajos Horvath & Lorenzo Trapani, 2021. "Changepoint detection in random coefficient autoregressive models," Papers 2104.13440, arXiv.org.
    12. Yoon, Gawon, 2005. "An introduction to I([infinity]) processes," Economic Modelling, Elsevier, vol. 22(3), pages 473-483, May.
    13. Trapani, Lorenzo, 2021. "A test for strict stationarity in a random coefficient autoregressive model of order 1," Statistics & Probability Letters, Elsevier, vol. 177(C).
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. Angelos Kanas, 2009. "Real exchange rates and developing countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 14(3), pages 280-299.
    24. 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.
    25. Michael F. Bleaney & Stephen J. Leybourne & Paul Mizen, 1999. "Mean Reversion of Real Exchange Rates in High‐Inflation Countries," Southern Economic Journal, John Wiley & Sons, vol. 65(4), pages 839-854, April.
    26. Ou, Shiqi & Lin, Zhenhong & Xu, Guoquan & Hao, Xu & Li, Hongwei & Gao, Zhiming & He, Xin & Przesmitzki, Steven & Bouchard, Jessey, 2020. "The retailed gasoline price in China: Time-series analysis and future trend projection," Energy, Elsevier, vol. 191(C).
    27. Magdalena Osińska & Aleksandra Matuszewska, 2006. "Detecting Some Dynamic Properties of the Euro/Dollar Exchange Rate," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 12(3), pages 327-341, August.
    28. Francq, Christian & Makarova, Svetlana & Zakoi[diaeresis]an, Jean-Michel, 2008. "A class of stochastic unit-root bilinear processes: Mixing properties and unit-root test," Journal of Econometrics, Elsevier, vol. 142(1), pages 312-326, January.
    29. 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.
    30. Granger, E.J. & Swanson, N.R., 1996. "An introduction to stochastic Unit Root Processes," Papers 4-96-3, Pennsylvania State - Department of Economics.
    31. Offer Lieberman & Peter C.B. Phillips, 2017. "Hybrid Stochastic Local Unit Roots," Cowles Foundation Discussion Papers 2113, Cowles Foundation for Research in Economics, Yale University.
    32. Lee, Hwa-Taek & Yoon, Gawon, 2007. "Does Purchasing Power Parity Hold Sometimes? Regime Switching in Real Exchange Rates," Economics Working Papers 2007-24, Christian-Albrechts-University of Kiel, Department of Economics.
    33. Jacek Kwiatkowski, 2006. "A Bayesian Estimation and Testing of STUR Models with Application to Polish Financial Time Series," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 7, pages 151-160.
    34. P. W. Fong & W. K. Li, 2004. "Some Results on Cointegration with Random Coefficients in the Error Correction Form: Estimation and Testing," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(3), pages 419-441, May.
    35. Wu, Jyh-Lin & Chen, Show-Lin, 1997. "Can nominal exchange rates be differenced to stationarity?," Economics Letters, Elsevier, vol. 55(3), pages 397-402, September.
    36. Distaso, Walter, 2008. "Testing for unit root processes in random coefficient autoregressive models," Journal of Econometrics, Elsevier, vol. 142(1), pages 581-609, January.
    37. Mehmet Hanefi Topal, 2020. "The Middle Income Trap: Theory and Empirical Evidence," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 34(1), pages 51-75.
    38. 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.
    39. Gawon Yoon, 2010. "Nonlinear mean-reversion to purchasing power parity: exponential smooth transition autoregressive models and stochastic unit root processes," Applied Economics, Taylor & Francis Journals, vol. 42(4), pages 489-496.
    40. Gawon Yoon, 2010. "Nonlinear mean reversion in real exchange rates: threshold autoregressive models and stochastic unit root processes," Applied Economics Letters, Taylor & Francis Journals, vol. 17(8), pages 797-804.
    41. Mikihito Nishi, 2023. "Testing for Coefficient Randomness in Local-to-Unity Autoregressions," Papers 2301.04853, arXiv.org, revised Jan 2023.
    42. Chowdhury, Khorshed & Mallik, Girijasankar, 2007. "SPair-Wise Output Convergence in East Asia and the Pacific: An Application of Stochastic Unit Root Test," Economics Working Papers wp07-07, School of Economics, University of Wollongong, NSW, Australia.
    43. Granger, Clive W.J., 2005. "The past and future of empirical finance: some personal comments," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 35-40.
    44. Kanas, Angelos, 2006. "Purchasing Power Parity and Markov Regime Switching," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(6), pages 1669-1687, September.
    45. Magdalena Osinska & Joanna Górka, 2006. "Identification of Non-linearity in Economic Time Series," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 7, pages 83-92.
    46. Gawon Yoon, 2005. "Correlation Coefficients, Heteroskedasticity And Contagion Of Financial Crises," Manchester School, University of Manchester, vol. 73(1), pages 92-100, January.
    47. Horváth, Lajos & Trapani, Lorenzo, 2019. "Testing for randomness in a random coefficient autoregression model," Journal of Econometrics, Elsevier, vol. 209(2), pages 338-352.
    48. Yoon, Gawon, 2005. "Has the U.S. economy really become less correlated with that of the rest of the world?," Economic Modelling, Elsevier, vol. 22(1), pages 147-158, January.
    49. A. M. Robert Taylor & Dick van Dijk, 2002. "Can Tests for Stochastic Unit Roots Provide Useful Portmanteau Tests for Persistence?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(4), pages 381-397, September.
    50. Zacharias Psaradakis & Fabio Spagnolo, 2005. "Forecast performance of nonlinear error-correction models with multiple regimes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(2), pages 119-138.
    51. 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.
    52. Berenguer Rico, Vanessa & Gonzalo, Jesús, 2011. "Summability of stochastic processes: a generalization of integration and co-integration valid for non-linear processes," UC3M Working papers. Economics we1115, Universidad Carlos III de Madrid. Departamento de Economía.
    53. Berenguer-Rico, Vanessa & Gonzalo, Jesús, 2014. "Summability of stochastic processes—A generalization of integration for non-linear processes," Journal of Econometrics, Elsevier, vol. 178(P2), pages 331-341.
    54. Abadir, Karim & Larsson, R., 1994. "Cointegration Theory, Equilibrium and Disequilibrium Economics," Discussion Papers 9407, University of Exeter, Department of Economics.
    55. Francisco De Castro & Pablo Hernández De Cos, 2002. "On the sustainability of the Spanish public budget performance," Hacienda Pública Española / Review of Public Economics, IEF, vol. 160(1), pages 9-28, march.
    56. 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.
    57. Franses, Philip Hans & Paap, Richard & Vroomen, Bjorn, 2004. "Forecasting unemployment using an autoregression with censored latent effects parameters," International Journal of Forecasting, Elsevier, vol. 20(2), pages 255-271.
    58. Andreas Hetland, 2018. "The Stochastic Stationary Root Model," Econometrics, MDPI, vol. 6(3), pages 1-33, August.
    59. Asmaa Ahmed, 2005. "Random Walks in the Economic Dynamic Series," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 78-100.
    60. Franses, Ph.H.B.F. & Paap, R., 1998. "Modelling asymmetric persistence over the business cycle," Econometric Institute Research Papers EI 9852, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    61. 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.

  15. S. P. Burke & L. G. Godfrey & A. R. Tremayne, 1990. "Testing AR(1) Against MA(1) Disturbances in the Linear Regression Model: An Alternative Procedure," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 57(1), pages 135-145.

    Cited by:

    1. Mckensi, C.R. & Mcaleer, M. & Gill, L., 1990. "Simple Procedures For Testing Autoregressive Versus Moving Average Errors In Regression Models," Papers 210, Australian National University - Department of Economics.
    2. C. R. McKenzie & Michael McAleer, 2001. "Comparing Tests of Autoregressive Versus Moving Average Errors in Regression Models Using Bahadur's Asymptotic Relative Efficiency," ISER Discussion Paper 0537, Institute of Social and Economic Research, Osaka University.
    3. Baltagi, Badi H. & Li, Qi, 1995. "Testing AR(1) against MA(1) disturbances in an error component model," Journal of Econometrics, Elsevier, vol. 68(1), pages 133-151, July.
    4. Silvapulle, Paramsothy & King, Maxwell L., 1993. "Nonnested testing for autocorrelation in the linear regression model," Journal of Econometrics, Elsevier, vol. 58(3), pages 295-314, August.
    5. Andrea Vaona, 2011. "A panel data approach to price-value correlations," Working Papers 14/2011, University of Verona, Department of Economics.
    6. James F. Ragan & Bernt Bratsberg, 2000. "Un‐COLA: Why Have Cost‐of‐Living Clauses Disappeared from Union Contracts and Will They Return?," Southern Economic Journal, John Wiley & Sons, vol. 67(2), pages 304-324, October.

  16. Poskitt, D. S. & Tremayne, A. R., 1986. "The selection and use of linear and bilinear time series models," International Journal of Forecasting, Elsevier, vol. 2(1), pages 101-114.

    Cited by:

    1. Rossen, Anja, 2014. "On the predictive content of nonlinear transformations of lagged autoregression residuals and time series observations," HWWI Research Papers 157, Hamburg Institute of International Economics (HWWI).
    2. Philip Hans Franses, 2019. "Model‐based forecast adjustment: With an illustration to inflation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(2), pages 73-80, March.
    3. 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.
    4. Liu, Yamei, 2000. "Overfitting and forecasting: linear versus non-linear time series models," ISU General Staff Papers 2000010108000014914, Iowa State University, Department of Economics.
    5. Filelis - Papadopoulos, Christos K. & Kyziropoulos, Panagiotis E. & Morrison, John P. & O‘Reilly, Philip, 2022. "Modelling and forecasting based on recursive incomplete pseudoinverse matrices," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 197(C), pages 358-376.
    6. Zaher Mundher Yaseen & Mazen Ismaeel Ghareb & Isa Ebtehaj & Hossein Bonakdari & Ridwan Siddique & Salim Heddam & Ali A. Yusif & Ravinesh Deo, 2018. "Rainfall Pattern Forecasting Using Novel Hybrid Intelligent Model Based ANFIS-FFA," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(1), pages 105-122, January.
    7. 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.

  17. D. S. Poskitt & A. R. Tremayne, 1986. "Some Aspects Of The Performance Of Diagnostic Checks In Bivariate Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 7(3), pages 217-233, May.

    Cited by:

    1. Robert C. Jung & A. R. Tremayne, 2003. "Testing for serial dependence in time series models of counts," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(1), pages 65-84, January.
    2. D. S. Poskitt, 2005. "A Note on the Specification and Estimation of ARMAX Systems," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(2), pages 157-183, March.
    3. D. S. Poskitt & M. O. Salau, 1995. "On The Relationship Between Generalized Least Squares And Gaussian Estimation Of Vector Arma Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 16(6), pages 617-645, November.
    4. D.S. Poskitt, 2004. "Some Results on the Identification and Estimation of Vector ARMAX Processes," Monash Econometrics and Business Statistics Working Papers 12/04, Monash University, Department of Econometrics and Business Statistics.

  18. D. S. Poskitt & A. R. Tremayne, 1981. "A Time Series Application Of The Use Of Monte Carlo Methods To Compare Statistical Tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 2(4), pages 263-277, July.

    Cited by:

    1. Neil R. Ericsson, 1987. "Monte Carlo methodology and the finite sample properties of statistics for testing nested and non-nested hypotheses," International Finance Discussion Papers 317, Board of Governors of the Federal Reserve System (U.S.).

  19. Hendry, David F & Tremayne, Andrew R, 1976. "Estimating Systems of Dynamic Reduced Form Equations with Vector Autoregressive Errors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 17(2), pages 463-471, June.

    Cited by:

    1. David F. Hendry & Gordon J. Anderson, 1975. "Testing Dynamic Specification in Small Simultaneous Systems: An Application to a Model of Building Society Behavior in the United Kingdom," Cowles Foundation Discussion Papers 398, Cowles Foundation for Research in Economics, Yale University.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.