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Marcus J. Chambers

Citations

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Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Chambers, Marcus J, 1992. "Estimation of a Continuous-Time Dynamic Demand System," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(1), pages 53-64, Jan.-Marc.

    Mentioned in:

    1. Estimation of a continuous-time dynamic demand system (Journal of Applied Econometrics 1992) in ReplicationWiki ()

Working papers

  1. Chambers, Marcus J & Taylor, AM Robert, 2019. "Deterministic Parameter Change Models in Continuous and Discrete Time," Essex Finance Centre Working Papers 24072, University of Essex, Essex Business School.

    Cited by:

    1. Alessandro Casini & Pierre Perron, 2020. "Continuous Record Laplace-based Inference about the Break Date in Structural Change Models," Boston University - Department of Economics - Working Papers Series WP2020-014, Boston University - Department of Economics.

  2. Chambers, MJ, 2018. "Frequency Domain Estimation of Cointegrating Vectors with Mixed Frequency and Mixed Sample Data," Economics Discussion Papers 21144, University of Essex, Department of Economics.

    Cited by:

    1. Cleiton Guollo Taufemback, 2023. "Asymptotic Behavior of Temporal Aggregation in Mixed‐Frequency Datasets," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(4), pages 894-909, August.
    2. Philipp Gersing & Leopold Soegner & Manfred Deistler, 2022. "Retrieval from Mixed Sampling Frequency: Generic Identifiability in the Unit Root VAR," Papers 2204.05952, arXiv.org, revised Jul 2023.

  3. Chambers, MJ & Kyriacou, M, 2016. "Jackknife Bias Reduction in the Presence of a Near-Unit Root," Economics Discussion Papers 17623, University of Essex, Department of Economics.

    Cited by:

    1. Kruse, Robinson & Kaufmann, Hendrik & Wegener, Christoph, 2018. "Bias-corrected estimation for speculative bubbles in stock prices," Economic Modelling, Elsevier, vol. 73(C), pages 354-364.

  4. Chambers, MJ, 2016. "The Estimation of Continuous Time Models with Mixed Frequency Data," Economics Discussion Papers 15988, University of Essex, Department of Economics.

    Cited by:

    1. Thornton, Michael A. & Chambers, Marcus J., 2017. "Continuous time ARMA processes: Discrete time representation and likelihood evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 48-65.
    2. Chambers, Marcus J., 2020. "Frequency domain estimation of cointegrating vectors with mixed frequency and mixed sample data," Journal of Econometrics, Elsevier, vol. 217(1), pages 140-160.
    3. Philipp Gersing & Leopold Soegner & Manfred Deistler, 2022. "Retrieval from Mixed Sampling Frequency: Generic Identifiability in the Unit Root VAR," Papers 2204.05952, arXiv.org, revised Jul 2023.
    4. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    5. Deistler, Manfred & Koelbl, Lukas & Anderson, Brian D.O., 2017. "Non-identifiability of VMA and VARMA systems in the mixed frequency case," Econometrics and Statistics, Elsevier, vol. 4(C), pages 31-38.
    6. Antoine GODIN & Sakir-Devrim YILMAZ, 2020. "Modelling Small Open Developing Economies in a Financialized World: A Stock-Flow Consistent Prototype Growth Model," Working Paper 5eb7e0e8-560f-4ce6-91a5-5, Agence française de développement.
    7. Yaoyuan Zhang & Dewen Xiong, 2023. "Optimal Strategy of the Dynamic Mean-Variance Problem for Pairs Trading under a Fast Mean-Reverting Stochastic Volatility Model," Mathematics, MDPI, vol. 11(9), pages 1-19, May.

  5. Michael Thornton & Marcus Chambers, 2016. "Continuous Time ARMA Processes: Discrete Time Representation and Likelihood Evaluation," Discussion Papers 16/10, Department of Economics, University of York.

    Cited by:

    1. Vicky Fasen-Hartmann & Celeste Mayer, 2022. "Whittle estimation for continuous-time stationary state space models with finite second moments," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(2), pages 233-270, April.
    2. Vicky Fasen‐Hartmann & Sebastian Kimmig, 2020. "Robust estimation of stationary continuous‐time arma models via indirect inference," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(5), pages 620-651, September.
    3. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    4. Sikora, Grzegorz & Michalak, Anna & Bielak, Łukasz & Miśta, Paweł & Wyłomańska, Agnieszka, 2019. "Stochastic modeling of currency exchange rates with novel validation techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1202-1215.
    5. Antoine GODIN & Sakir-Devrim YILMAZ, 2020. "Modelling Small Open Developing Economies in a Financialized World: A Stock-Flow Consistent Prototype Growth Model," Working Paper 5eb7e0e8-560f-4ce6-91a5-5, Agence française de développement.
    6. Fasen-Hartmann, Vicky & Mayer, Celeste, 2023. "Empirical spectral processes for stationary state space models," Stochastic Processes and their Applications, Elsevier, vol. 155(C), pages 319-354.
    7. Szarek, Dawid & Bielak, Łukasz & Wyłomańska, Agnieszka, 2020. "Long-term prediction of the metals’ prices using non-Gaussian time-inhomogeneous stochastic process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
    8. Thornton, Michael A. & Chambers, Marcus J., 2016. "The exact discretisation of CARMA models with applications in finance," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 739-761.
    9. Ralf Korn & Bilgi Yilmaz, 2022. "House Prices as a Result of Trading Activities: A Patient Trader Model," Computational Economics, Springer;Society for Computational Economics, vol. 60(1), pages 281-303, June.

  6. Chambers, MJ, 2013. "The Calculation of Some Limiting Distributions Arising in Near-Integrated Models with GLS Detrending," Economics Discussion Papers 8975, University of Essex, Department of Economics.

    Cited by:

    1. Neil Kellard & Denise Osborn & Jerry Coakley & Marcus J. Chambers, 2015. "Testing for a Unit Root in a Near-Integrated Model with Skip-Sampled Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 630-649, September.
    2. Chambers, MJ, 2016. "The Effects of Sampling Frequency on Detrending Methods for Unit Root Tests," Economics Discussion Papers 16062, University of Essex, Department of Economics.

  7. Chambers, Marcus J. & Kyriacou, Maria, 2012. "Jackknife bias reduction in autoregressive models with a unit root," MPRA Paper 38255, University Library of Munich, Germany.

    Cited by:

    1. Chambers, Marcus J., 2013. "Jackknife estimation of stationary autoregressive models," Journal of Econometrics, Elsevier, vol. 172(1), pages 142-157.
    2. Hendrik Kaufmannz & Robinson Kruse, 2013. "Bias-corrected estimation in potentially mildly explosive autoregressive models," CREATES Research Papers 2013-10, Department of Economics and Business Economics, Aarhus University.

  8. Chambers, MJ, 2010. "Jackknife Estimation of Stationary Autoregressive Models," Economics Discussion Papers 2786, University of Essex, Department of Economics.

    Cited by:

    1. Gareth Liu-Evans, 2021. "Improving the Estimation and Predictions of Small Time Series Models," Working Papers 202106, University of Liverpool, Department of Economics.
    2. Aaron H. Anglin & Aaron F. McKenny & Jeremy C. Short, 2018. "The Impact of Collective Optimism on New Venture Creation and Growth: A Social Contagion Perspective," Entrepreneurship Theory and Practice, , vol. 42(3), pages 390-425, May.
    3. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    4. Chambers, MJ & Kyriacou, M, 2016. "Jackknife Bias Reduction in the Presence of a Near-Unit Root," Economics Discussion Papers 17623, University of Essex, Department of Economics.
    5. Chambers, MJ & Kyriacou, M, 2010. "Jackknife Bias Reduction in the Presence of a Unit Root," Economics Discussion Papers 2785, University of Essex, Department of Economics.
    6. Kanchana Nadarajah & Gael M Martin & Donald S Poskitt, 2019. "Optimal Bias Correction of the Log-periodogram Estimator of the Fractional Parameter: A Jackknife Approach," Monash Econometrics and Business Statistics Working Papers 7/19, Monash University, Department of Econometrics and Business Statistics.
    7. Iglesias, Emma M., 2014. "Testing of the mean reversion parameter in continuous time models," Economics Letters, Elsevier, vol. 122(2), pages 187-189.
    8. Kruse, Yves Robinson & Kaufmann, Hendrik, 2015. "Bias-corrected estimation in mildly explosive autoregressions," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112897, Verein für Socialpolitik / German Economic Association.
    9. Marian Vavra, 2023. "Bias-Correction in Time Series Quantile Regression Models," Working and Discussion Papers WP 3/2023, Research Department, National Bank of Slovakia.
    10. Kruse, Robinson & Kaufmann, Hendrik & Wegener, Christoph, 2018. "Bias-corrected estimation for speculative bubbles in stock prices," Economic Modelling, Elsevier, vol. 73(C), pages 354-364.
    11. Ye Chen & Jun Yu, 2012. "Optimal Jackknife for Discrete Time and Continuous Time Unit Root Models," Working Papers 15-2012, Singapore Management University, School of Economics.
    12. Arturas Juodis & Yiannis Karavias & Vasilis Sarafidis, 2020. "A Homogeneous Approach to Testing for Granger Non-Causality in Heterogeneous Panels," Monash Econometrics and Business Statistics Working Papers 32/20, Monash University, Department of Econometrics and Business Statistics.
    13. 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.
    14. Chen, Ye & Yu, Jun, 2015. "Optimal jackknife for unit root models," Statistics & Probability Letters, Elsevier, vol. 99(C), pages 135-142.
    15. Diana Escandon-Barbosa & David Urbano-Pulido & Andrea Hurtado-Ayala, 2019. "Exploring the Relationship between Formal and Informal Institutions, Social Capital, and Entrepreneurial Activity in Developing and Developed Countries," Sustainability, MDPI, vol. 11(2), pages 1-20, January.
    16. Hendrik Kaufmannz & Robinson Kruse, 2013. "Bias-corrected estimation in potentially mildly explosive autoregressive models," CREATES Research Papers 2013-10, Department of Economics and Business Economics, Aarhus University.
    17. Gourieroux, Christian & Zakoïan, Jean-Michel, 2013. "Estimation-Adjusted Var," Econometric Theory, Cambridge University Press, vol. 29(4), pages 735-770, August.
    18. Marcus J. Chambers, 2015. "A Jackknife Correction to a Test for Cointegration Rank," Econometrics, MDPI, vol. 3(2), pages 1-21, May.
    19. Bork, Lasse & Kaltwasser, Pablo Rovira & Sercu, Piet, 2022. "Aggregation bias in tests of the commodity currency hypothesis," Journal of Banking & Finance, Elsevier, vol. 135(C).
    20. Chambers, Marcus J. & Kyriacou, Maria, 2013. "Jackknife estimation with a unit root," Statistics & Probability Letters, Elsevier, vol. 83(7), pages 1677-1682.
    21. Arturas Juodis & Yiannis Karavias, 2019. "Partially heterogeneous tests for Granger non-causality in panel data," Bank of Lithuania Working Paper Series 59, Bank of Lithuania.
    22. Yong Bao, 2013. "On Sample Skewness and Kurtosis," Econometric Reviews, Taylor & Francis Journals, vol. 32(4), pages 415-448, December.

  9. Chambers, MJ & Kyriacou, M, 2010. "Jackknife Bias Reduction in the Presence of a Unit Root," Economics Discussion Papers 2785, University of Essex, Department of Economics.

    Cited by:

    1. Chambers, Marcus J., 2013. "Jackknife estimation of stationary autoregressive models," Journal of Econometrics, Elsevier, vol. 172(1), pages 142-157.
    2. Ye Chen & Jun Yu, 2012. "Optimal Jackknife for Discrete Time and Continuous Time Unit Root Models," Working Papers 15-2012, Singapore Management University, School of Economics.
    3. Marcus J. Chambers, 2015. "A Jackknife Correction to a Test for Cointegration Rank," Econometrics, MDPI, vol. 3(2), pages 1-21, May.
    4. Chambers, Marcus J. & Kyriacou, Maria, 2013. "Jackknife estimation with a unit root," Statistics & Probability Letters, Elsevier, vol. 83(7), pages 1677-1682.

  10. Marcus J. Chambers & Joanne S. Ercolani & A. M. Robert Taylor, 2010. "Testing for seasonal unit roots by frequency domain regression," Discussion Papers 10/02, University of Nottingham, Granger Centre for Time Series Econometrics.

    Cited by:

    1. Atle Oglend & Frank Asche, 2016. "Cyclical non-stationarity in commodity prices," Empirical Economics, Springer, vol. 51(4), pages 1465-1479, December.
    2. Burak Eroglu, 2017. "Wavelet Variance Ratio Test And Wavestrapping For The Determination Of The Cointegration Rank," Working Papers 1706, The Center for Financial Studies (CEFIS), Istanbul Bilgi University.
    3. Eroğlu, Burak Alparslan, 2019. "Wavelet variance ratio cointegration test and wavestrapping," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 298-319.
    4. Burak Eroglu & Kemal Caglar Gogebakan & Mirza Trokic, 2017. "Fractional Seasonal Variance Ratio Unit Root Tests," Working Papers 1707, The Center for Financial Studies (CEFIS), Istanbul Bilgi University.
    5. Sheng-Hung Chen & Song-Zan Chiou-Wei & Zhen Zhu, 2022. "Stochastic seasonality in commodity prices: the case of US natural gas," Empirical Economics, Springer, vol. 62(5), pages 2263-2284, May.

  11. McCrorie, J.R. & Chambers, M.J., 2004. "Granger Causality and the Sampling of Economic Processes," Discussion Paper 2004-39, Tilburg University, Center for Economic Research.

    Cited by:

    1. Salamaliki, Paraskevi K. & Venetis, Ioannis A., 2013. "Energy consumption and real GDP in G-7: Multi-horizon causality testing in the presence of capital stock," Energy Economics, Elsevier, vol. 39(C), pages 108-121.
    2. Chih-Nan Chen & Tsutomu Watanabe & Tomoyoshi Yabu, 2012. "A New Method for Identifying the Effects of Foreign Exchange Interventions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(8), pages 1507-1533, December.
    3. Sentana, Enrique & Diez de los Rios, Antonio, 2007. "Testing Uncovered Interest Parity: A Continuous-Time Approach," CEPR Discussion Papers 6516, C.E.P.R. Discussion Papers.
    4. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    5. Ghysels, Eric & Hill, Jonathan B. & Motegi, Kaiji, 2016. "Testing for Granger causality with mixed frequency data," Journal of Econometrics, Elsevier, vol. 192(1), pages 207-230.
    6. Michael A. Thornton & Marcus J. Chambers, 2013. "Temporal aggregation in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 13, pages 289-310, Edward Elgar Publishing.
    7. Alessandro Gregorio & Francesco Iafrate, 2021. "Regularized bridge-type estimation with multiple penalties," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(5), pages 921-951, October.
    8. Arie ten Cate, 2004. "Refinement of the partial adjustment model using continuous-time econometrics," CPB Discussion Paper 41, CPB Netherlands Bureau for Economic Policy Analysis.
    9. Ghysels, Eric, 2016. "Macroeconomics and the reality of mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 294-314.
    10. Daniel Ventosa-Santaulària & José Eduardo Vera-Valdés, 2008. "Granger-Causality in the presence of structural breaks," Economics Bulletin, AccessEcon, vol. 3(61), pages 1-14.
    11. Petrović, Ljiljana & Dimitrijević, Sladjana, 2012. "Causality with finite horizon of the past in continuous time," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1219-1223.
    12. K. Lebedeva, 2015. "An Empirical Analysis of the Russian Financial Markets’ Liquidity and Returns," Review of Business and Economics Studies // Review of Business and Economics Studies, Финансовый Университет // Financial University, vol. 3(3), pages 5-31.
    13. Ehlers, Stefan & Gürtler, Marc & Olboeter, Sven, 2010. "Financial crises and information transfer: An empirical analysis of the lead-lag relationship between equity and CDS iTraxx Indices," Working Papers IF34V1, Technische Universität Braunschweig, Institute of Finance.

  12. Chambers, M.J. & McCrorie, J.R., 2004. "Identification and Estimation of Exchange Rate Models with Unobservable Fundamentals," Discussion Paper 2004-38, Tilburg University, Center for Economic Research.

    Cited by:

    1. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    2. McCrorie, J.R. & Chambers, M.J., 2004. "Granger Causality and the Sampling of Economic Processes," Discussion Paper 2004-39, Tilburg University, Center for Economic Research.
    3. Jewitt, Giles & Roderick McCrorie, J., 2005. "Computing estimates of continuous time macroeconometric models on the basis of discrete data," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 397-416, April.

  13. Chambers, MJ, 2001. "Testing for Unit Roots with Flow Data and Varying Sampling Frequency," Economics Discussion Papers 2761, University of Essex, Department of Economics.

    Cited by:

    1. Chambers, MJ, 2001. "Testing for Unit Roots with Flow Data and Varying Sampling Frequency," Economics Discussion Papers 2761, University of Essex, Department of Economics.
    2. Theodore Simos & Mike Tsionas, 2018. "Bayesian inference of the fractional Ornstein–Uhlenbeck process under a flow sampling scheme," Computational Statistics, Springer, vol. 33(4), pages 1687-1713, December.
    3. Wu, Xuedong & Dorfman, Jeffrey H. & Karali, Berna, 2015. "The Impact of Data Frequency On Stationarity Tests Of Commodity Futures Prices," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205569, Agricultural and Applied Economics Association.
    4. Wang, Dabin & Tomek, William G., 2004. "Commodity Prices And Unit Root Tests," 2004 Annual meeting, August 1-4, Denver, CO 20141, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Uwe Hassler, 2011. "Estimation of fractional integration under temporal aggregation," Post-Print hal-00815563, HAL.
    6. Wang, Dabin & Tomek, William G., 2004. "Commodity Prices And Unit Root Tests," Working Papers 127145, Cornell University, Department of Applied Economics and Management.
    7. Chambers, MJ, 2016. "The Effects of Sampling Frequency on Detrending Methods for Unit Root Tests," Economics Discussion Papers 16062, University of Essex, Department of Economics.

  14. Chambers, MJ, 2001. "Cointegration and Sampling Frequency," Economics Discussion Papers 2760, University of Essex, Department of Economics.

    Cited by:

    1. Partha Ray & Vinodh Madhavan, 2014. "Price and Volatility Linkages between Indian Stocks and their European GDRs," Proceedings of International Academic Conferences 0300812, International Institute of Social and Economic Sciences.
    2. Dierk Herzer & Holger Strulik, 2017. "Religiosity and income: a panel cointegration and causality analysis," Applied Economics, Taylor & Francis Journals, vol. 49(30), pages 2922-2938, June.
    3. J. Isaac Miller, 2018. "Testing Cointegrating Relationships Using Irregular and Non-Contemporaneous Series with an Application to Paleoclimate Data," Working Papers 1809, Department of Economics, University of Missouri.
    4. Thornton, Michael A. & Chambers, Marcus J., 2017. "Continuous time ARMA processes: Discrete time representation and likelihood evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 48-65.
    5. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    6. Herzer, Dierk, 2009. "Cross-country heterogeneity and the trade-income relationship," Proceedings of the German Development Economics Conference, Frankfurt a.M. 2009 13, Verein für Socialpolitik, Research Committee Development Economics.
    7. J. Isaac Miller, 2016. "Conditionally Efficient Estimation of Long-Run Relationships Using Mixed-Frequency Time Series," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1142-1171, June.
    8. Herzer, Dierk & Nunnenkamo, Peter, 2014. "Income Inequality and Health: Evidence from Developed and Developing Countries," Working Paper 141/2014, Helmut Schmidt University, Hamburg.
    9. Herzer, Dierk & Strulik, Holger & Vollmer, Sebastian, 2010. "The Long-run Determinants of Fertility: One Century of Demographic Change 1900-1999," Hannover Economic Papers (HEP) dp-456, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    10. Eric Ghysels & J. Isaac Miller, 2013. "Testing for Cointegration with Temporally Aggregated and Mixed-frequency Time Series," Working Papers 1307, Department of Economics, University of Missouri, revised 07 May 2014.
    11. J. Isaac Miller & Xi Wang, 2016. "Implementing Residual-Based KPSS Tests for Cointegration with Data Subject to Temporal Aggregation and Mixed Sampling Frequencies," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(6), pages 810-824, November.
    12. Nicole Grunewald & Inmaculada Martínez-Zarzoso, 2014. "Green Growth in Mexico, Brazil and Chile: Policy strategies and future prospects," Ibero America Institute for Econ. Research (IAI) Discussion Papers 229, Ibero-America Institute for Economic Research.
    13. Chambers, MJ, 2016. "The Estimation of Continuous Time Models with Mixed Frequency Data," Economics Discussion Papers 15988, University of Essex, Department of Economics.
    14. Gustavo Fruet Dias & Karsten Schweiker, 2024. "Integrated Variance Estimation for Assets Traded in Multiple Venues," University of East Anglia School of Economics Working Paper Series 2024-04, School of Economics, University of East Anglia, Norwich, UK..
    15. Milena Hoyos, 2020. "Mixed First‐ and Second‐Order Cointegrated Continuous Time Models with Mixed Stock and Flow Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(2), pages 249-267, March.
    16. Chambers, MJ, 2016. "The Effects of Sampling Frequency on Detrending Methods for Unit Root Tests," Economics Discussion Papers 16062, University of Essex, Department of Economics.

  15. Chambers, MJ, 1998. "Gaussian estimation of temporally aggregated cointegrated systems," Economics Discussion Papers 2763, University of Essex, Department of Economics.

    Cited by:

    1. Chambers, Marcus J., 1999. "Discrete time representation of stationary and non-stationary continuous time systems," Journal of Economic Dynamics and Control, Elsevier, vol. 23(4), pages 619-639, February.

  16. Chambers, MJ, 1995. "The Estimation of Systems of Joint Differential-Difference Equations," Economics Discussion Papers 2764, University of Essex, Department of Economics.

    Cited by:

    1. Joanne S. McGarry & Marcus J. Chambers, 2004. "Party formation and coalitional bargaining in a model of proportional representation," Discussion Papers 04-07, Department of Economics, University of Birmingham.
    2. Chambers, M.J. & McCrorie, J.R., 2004. "Frequency Domain Gaussian Estimation of Temporally Aggregated Cointegrated Systems," Discussion Paper 2004-40, Tilburg University, Center for Economic Research.
    3. Chambers, MJ, 2016. "The Estimation of Continuous Time Models with Mixed Frequency Data," Economics Discussion Papers 15988, University of Essex, Department of Economics.
    4. Chambers, Marcus J. & Roderick McCrorie, J., 2007. "Frequency domain estimation of temporally aggregated Gaussian cointegrated systems," Journal of Econometrics, Elsevier, vol. 136(1), pages 1-29, January.

  17. Chambers, MJ, 1995. "Long Memory and Aggregation in Macroeconomic Time Series," Economics Discussion Papers 2766, University of Essex, Department of Economics.

    Cited by:

    1. Man, K.S. & Tiao, G.C., 2006. "Aggregation effect and forecasting temporal aggregates of long memory processes," International Journal of Forecasting, Elsevier, vol. 22(2), pages 267-281.
    2. Haldrup, Niels & Vera Valdés, J. Eduardo, 2017. "Long memory, fractional integration, and cross-sectional aggregation," Journal of Econometrics, Elsevier, vol. 199(1), pages 1-11.
    3. Fischer, Christian & Gil-Alana, Luis A., 2006. "The Nature of the Relationship between International Tourism and International Trade: The Case of German Imports of Spanish Wine," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25341, International Association of Agricultural Economists.
    4. Chevillon, Guillaume & Mavroeidis, Sophocles, 2017. "Learning can generate long memory," Journal of Econometrics, Elsevier, vol. 198(1), pages 1-9.
    5. Leschinski, Christian, 2016. "On the Memory of Products of Long Range Dependent Time Series," Hannover Economic Papers (HEP) dp-569, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    6. Karim M. Abadir & Gabriel Talmain & Giovanni Caggiano, 2008. "Nelson-Plosser revisited: the ACF approach," Working Paper series 18_08, Rimini Centre for Economic Analysis.
    7. Souza, Leonardo Rocha, 2003. "A note on Chambers's 'long memory and aggregation in macroeconomic time series'," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 503, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    8. Gil-Alana, L.A., 2006. "Fractional integration in daily stock market indexes," Review of Financial Economics, Elsevier, vol. 15(1), pages 28-48.
    9. Juncal Cunado & Luis A. Gil-Alana & Fernando Pérez de Gracia, 2003. "Additional Empirical Evidence on Real Convergence: A Fractionally Integrated Approach," Faculty Working Papers 01/03, School of Economics and Business Administration, University of Navarra.
    10. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2009. "Long Memory in US Real Output per Capita," CESifo Working Paper Series 2671, CESifo.
    11. Luis A. Gil-Alana, 2004. "Modelling the Japanese Exchange Rate in Terms of I(d) Statistical Models with Parametric and Semiparametric Techniques," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 3(2), pages 123-138, August.
    12. Souza, Leonardo Rocha & Smith, Jeremy & Souza, Reinaldo Castro, 2003. "Convex combinations of long memory estimates from different sampling rates," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 489, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    13. Carlos Barros & Luis Gil-Alana, 2012. "Inflation forecasting in Angola: a fractional approach," CEsA Working Papers 103, CEsA - Centre for African and Development Studies.
    14. Davidson James & Rambaccussing Dooruj, 2015. "A Test of the Long Memory Hypothesis Based on Self-Similarity," Journal of Time Series Econometrics, De Gruyter, vol. 7(2), pages 115-141, July.
    15. McHale, I.G. & Peel, D.A., 2010. "Habit and long memory in UK lottery sales," Economics Letters, Elsevier, vol. 109(1), pages 7-10, October.
    16. Diebold, Francis X. & Inoue, Atsushi, 2001. "Long memory and regime switching," Journal of Econometrics, Elsevier, vol. 105(1), pages 131-159, November.
    17. L. A. Gil-Alana, 2003. "A fractional integration analysis of the population in some OECD countries," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(10), pages 1147-1159.
    18. Yunus Emre Ergemen, 2016. "System Estimation of Panel Data Models under Long-Range Dependence," CREATES Research Papers 2016-02, Department of Economics and Business Economics, Aarhus University.
    19. Pierre Perron & Wendong Shi, 2020. "Temporal Aggregation and Long Memory for Asset Price Volatility," JRFM, MDPI, vol. 13(8), pages 1-18, August.
    20. Barros, Carlos P. & Gil-Alana, Luis A. & Wanke, Peter, 2016. "Energy production in Brazil: Empirical facts based on persistence, seasonality and breaks," Energy Economics, Elsevier, vol. 54(C), pages 88-95.
    21. Gil-Alana, Luis A., 2004. "Modelling the U.S. interest rate in terms of I(d) statistical models," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(4), pages 475-486, September.
    22. Maria Caporale, Guglielmo & A. Gil-Alana, Luis, 2011. "Multi-Factor Gegenbauer Processes and European Inflation Rates," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 26, pages 386-409.
    23. Manmohan S. Kumar & Tatsuyoshi Okimoto, 2007. "Dynamics of Persistence in International Inflation Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(6), pages 1457-1479, September.
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    75. Li, Huiyu & Stachurski, John, 2014. "Solving the income fluctuation problem with unbounded rewards," Journal of Economic Dynamics and Control, Elsevier, vol. 45(C), pages 353-365.
    76. Marcus J. Chambers & Roy E. Bailey, 1999. "A Statistical Analysis of Wheat Price Fluctuations in England: 1685–1850," Journal of Agricultural Economics, Wiley Blackwell, vol. 50(3), pages 564-588, September.
    77. Symeonidis, Lazaros & Prokopczuk, Marcel & Brooks, Chris & Lazar, Emese, 2012. "Futures basis, inventory and commodity price volatility: An empirical analysis," MPRA Paper 39903, University Library of Munich, Germany.
    78. Ye, Michael & Zyren, John & Shore, Joanne, 2006. "Forecasting short-run crude oil price using high- and low-inventory variables," Energy Policy, Elsevier, vol. 34(17), pages 2736-2743, November.
    79. Hu, Min & Zhang, Dayong & Ji, Qiang & Wei, Lijian, 2020. "Macro factors and the realized volatility of commodities: A dynamic network analysis," Resources Policy, Elsevier, vol. 68(C).
    80. Anna Creti & Bertrand Villeneuve, 2013. "Commodity storage with durable shocks : A simple Markovian model," Post-Print hal-01517436, HAL.
    81. Chi Truong, 2012. "An Analysis of Storage Capacity Reallocation Impacts on the Irrigation Sector," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 51(1), pages 141-159, January.
    82. Seifert, Ralf W. & Thonemann, Ulrich W. & Hausman, Warren H., 2004. "Optimal procurement strategies for online spot markets," European Journal of Operational Research, Elsevier, vol. 152(3), pages 781-799, February.
    83. Ivar Ekeland & Delphine Lautier & Bertrand Villeneuve, 2019. "Hedging pressure and speculation in commodity markets," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 68(1), pages 83-123, July.
    84. Rhys ap Gwilym & M. Shahid Ebrahim & Abdelkader O. El Alaoui & Hamid Rahman & Abderrahim Taamouti, 2019. "Financial Frictions and the Futures Pricing Puzzle," Working Papers 2019_07, Durham University Business School.
    85. Hélyette Geman & Vu-Nhat Nguyen, 2005. "Soybean Inventory and Forward Curve Dynamics," Management Science, INFORMS, vol. 51(7), pages 1076-1091, July.
    86. Yu-Hong Liu & I-Ming Jiang & Shih-Cheng Lee & Yu-Ting Chen, 2011. "The Valuation Of Reset Options When Underlying Assets Are Autocorrelated," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 5(2), pages 95-114.
    87. Ruijs, Arjan & Schweigman, Caspar & Lutz, Clemens, 2004. "The impact of transport- and transaction-cost reductions on food markets in developing countries: evidence for tempered expectations for Burkina Faso," Agricultural Economics, Blackwell, vol. 31(2-3), pages 219-228, December.
    88. Kleppe, Tore Selland & Oglend, Atle, 2017. "Estimating the competitive storage model: A simulated likelihood approach," Econometrics and Statistics, Elsevier, vol. 4(C), pages 39-56.
    89. Ren'e Aid & Luciano Campi & Delphine Lautier, 2015. "On the spot-futures no-arbitrage relations in commodity markets," Papers 1501.00273, arXiv.org, revised Feb 2018.
    90. Tomek, William G., 2000. "Commodity Prices Revisited," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 29(2), pages 1-13, October.
    91. Chitose, Atsushi & Weaver, Robert D., 2007. "Dynamics of Slaughter Weight Response to Market Price Changes for Japanese Beef Cattle," Japanese Journal of Agricultural Economics (formerly Japanese Journal of Rural Economics), Agricultural Economics Society of Japan (AESJ), vol. 9, pages 1-14.
    92. Delphine Lautier & Yves Simon, 2004. "La volatilité des prix des matières premières," Revue d'Économie Financière, Programme National Persée, vol. 74(1), pages 45-84.
    93. Anders B. Trolle & Eduardo S. Schwartz, 2006. "Unspanned Stochastic Volatility and the Pricing of Commodity Derivatives," NBER Working Papers 12744, National Bureau of Economic Research, Inc.
    94. Rabault, Guillaume, 2002. "When do borrowing constraints bind? Some new results on the income fluctuation problem," Journal of Economic Dynamics and Control, Elsevier, vol. 26(2), pages 217-245, February.
    95. Shafiqur Rahman & M. Shahid Ebrahim, 2005. "The Futures Pricing Puzzle," Computing in Economics and Finance 2005 35, Society for Computational Economics.
    96. Frode Brevik & Axel Kind, 2004. "What is going on in the oil market?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 18(4), pages 442-457, December.
    97. Considine, Timothy J. & Larson, Donald F., 2001. "Uncertainty and the convenience yield in crude oil price backwardations," Energy Economics, Elsevier, vol. 23(5), pages 533-548, September.
    98. Chaudhry, Muhammad Imran & Katchova, Ani & Miranda, Mario Javier, 2016. "Examining pricing mechanics in the poultry value chain - empirical evidence from Pakistan," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235953, Agricultural and Applied Economics Association.
    99. Ivar Ekeland & Delphine Lautier & Bertrand Villeneuve, 2013. "A simple equilibrium model for a commodity market with spot trades and futures contracts," Post-Print hal-01655807, HAL.
    100. Gleich, Benedikt & Achzet, Benjamin & Mayer, Herbert & Rathgeber, Andreas, 2013. "An empirical approach to determine specific weights of driving factors for the price of commodities—A contribution to the measurement of the economic scarcity of minerals and metals," Resources Policy, Elsevier, vol. 38(3), pages 350-362.
    101. Li, Shanling & Murat, Alper & Huang, Wanzhen, 2009. "Selection of contract suppliers under price and demand uncertainty in a dynamic market," European Journal of Operational Research, Elsevier, vol. 198(3), pages 830-847, November.
    102. Chatrath, Arjun & Adrangi, Bahram & Dhanda, Kanwalroop Kathy, 2002. "Are commodity prices chaotic?," Agricultural Economics, Blackwell, vol. 27(2), pages 123-137, August.
    103. Coleman, Andrew, 2005. "Storage, transport and the law of one price: evidence from nineteenth century U.S. corn markets," 46th Annual Transportation Research Forum, Washington, D.C., March 6-8, 2005 208149, Transportation Research Forum.

Articles

  1. Marcus J. Chambers & A. M. Robert Taylor, 2020. "Deterministic Parameter Change Models in Continuous and Discrete Time," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(1), pages 134-145, January.
    See citations under working paper version above.
  2. Chambers, Marcus J., 2020. "Frequency domain estimation of cointegrating vectors with mixed frequency and mixed sample data," Journal of Econometrics, Elsevier, vol. 217(1), pages 140-160.
    See citations under working paper version above.
  3. Marcus J. Chambers, 2019. "Frequency Domain Estimation of Continuous Time Cointegrated Models with Mixed Frequency and Mixed Sample Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 40(6), pages 887-913, November.

    Cited by:

    1. Chambers, Marcus J., 2020. "Frequency domain estimation of cointegrating vectors with mixed frequency and mixed sample data," Journal of Econometrics, Elsevier, vol. 217(1), pages 140-160.

  4. Marcus J. Chambers & Maria Kyriacou, 2018. "Jackknife Bias Reduction in the Presence of a Near-Unit Root," Econometrics, MDPI, vol. 6(1), pages 1-28, March.
    See citations under working paper version above.
  5. Thornton, Michael A. & Chambers, Marcus J., 2017. "Continuous time ARMA processes: Discrete time representation and likelihood evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 48-65.
    See citations under working paper version above.
  6. Chambers, Marcus J., 2016. "The estimation of continuous time models with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 390-404.
    See citations under working paper version above.
  7. Thornton, Michael A. & Chambers, Marcus J., 2016. "The exact discretisation of CARMA models with applications in finance," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 739-761.

    Cited by:

    1. Thornton, Michael A. & Chambers, Marcus J., 2017. "Continuous time ARMA processes: Discrete time representation and likelihood evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 48-65.
    2. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.

  8. Abouwafia, Hashem E. & Chambers, Marcus J., 2015. "Monetary policy, exchange rates and stock prices in the Middle East region," International Review of Financial Analysis, Elsevier, vol. 37(C), pages 14-28.

    Cited by:

    1. Renata Legenzova & Otilija Jurakovaite & Agne Galinskaite, 2017. "The Analysis of Dividend Announcement Impact on Stock Prices of Baltic Companies," Central European Business Review, Prague University of Economics and Business, vol. 2017(1), pages 61-76.
    2. Yip, Pick Schen & Brooks, Robert & Do, Hung Xuan & Vo, Xuan Vinh, 2022. "What drives cross-market correlations during the United States Q.E.?," International Review of Financial Analysis, Elsevier, vol. 83(C).
    3. Sanjeev Parmanand, 2022. "The impact of Philippine monetary policy on domestic prices and output: evaluating the country’s transmission channels," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 59(1), pages 46-76, June.
    4. Sakshi Saini & Sanjay Sehgal & Florent Deisting, 2020. "Monetary Policy, Risk Aversion and Uncertainty in an International Context," Multinational Finance Journal, Multinational Finance Journal, vol. 24(3-4), pages 211-266, September.
    5. Prabheesh, K.P. & Anglingkusumo, Reza & Juhro, Solikin M., 2021. "The dynamics of global financial cycle and domestic economic cycles: Evidence from India and Indonesia," Economic Modelling, Elsevier, vol. 94(C), pages 831-842.
    6. Yang, Sheng-Ping, 2017. "Exchange rate dynamics and stock prices in small open economies: Evidence from Asia-Pacific countries," Pacific-Basin Finance Journal, Elsevier, vol. 46(PB), pages 337-354.
    7. Chikashi Tsuji, 2015. "Exchange Rate Effects on Equity Prices: The Recent Case from Japan," Business and Management Research, Business and Management Research, Sciedu Press, vol. 4(4), pages 1-12, December.
    8. Abdullah M. H. Alharbi, 2023. "Oil Shocks, Monetary Policy, and Stock Returns: A Case of Oil-based Economy," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 56-63, November.
    9. Arash Habibi & Chin Lee, 2019. "Asymmetric Effects of Exchange Rates on Stock Prices in G7 Countries," Capital Markets Review, Malaysian Finance Association, vol. 27(1), pages 19-33.
    10. Prabheesh, K.P. & Vidya, C.T., 2018. "Do business cycles, investment-specific technology shocks matter for stock returns?," Economic Modelling, Elsevier, vol. 70(C), pages 511-524.

  9. Marcus J. Chambers, 2015. "A Jackknife Correction to a Test for Cointegration Rank," Econometrics, MDPI, vol. 3(2), pages 1-21, May.

    Cited by:

    1. Chambers, MJ & Kyriacou, M, 2016. "Jackknife Bias Reduction in the Presence of a Near-Unit Root," Economics Discussion Papers 17623, University of Essex, Department of Economics.

  10. Marcus J. Chambers, 2015. "The Calculation of Some Limiting Distributions Arising in Near-Integrated Models with GLS Detrending," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(4), pages 562-586, July.
    See citations under working paper version above.
  11. Neil Kellard & Denise Osborn & Jerry Coakley & Marcus J. Chambers, 2015. "Testing for a Unit Root in a Near-Integrated Model with Skip-Sampled Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 630-649, September.

    Cited by:

    1. Miller, J. Isaac, 2018. "Simple robust tests for the specification of high-frequency predictors of a low-frequency series," Econometrics and Statistics, Elsevier, vol. 5(C), pages 45-66.
    2. Chambers, MJ, 2016. "The Effects of Sampling Frequency on Detrending Methods for Unit Root Tests," Economics Discussion Papers 16062, University of Essex, Department of Economics.

  12. Chambers, Marcus J. & Ercolani, Joanne S. & Taylor, A.M. Robert, 2014. "Testing for seasonal unit roots by frequency domain regression," Journal of Econometrics, Elsevier, vol. 178(P2), pages 243-258.
    See citations under working paper version above.
  13. Chambers, Marcus J. & Kyriacou, Maria, 2013. "Jackknife estimation with a unit root," Statistics & Probability Letters, Elsevier, vol. 83(7), pages 1677-1682.

    Cited by:

    1. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    2. Chambers, MJ & Kyriacou, M, 2016. "Jackknife Bias Reduction in the Presence of a Near-Unit Root," Economics Discussion Papers 17623, University of Essex, Department of Economics.
    3. Kruse, Yves Robinson & Kaufmann, Hendrik, 2015. "Bias-corrected estimation in mildly explosive autoregressions," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112897, Verein für Socialpolitik / German Economic Association.
    4. Kruse, Robinson & Kaufmann, Hendrik & Wegener, Christoph, 2018. "Bias-corrected estimation for speculative bubbles in stock prices," Economic Modelling, Elsevier, vol. 73(C), pages 354-364.
    5. Chen, Ye & Yu, Jun, 2015. "Optimal jackknife for unit root models," Statistics & Probability Letters, Elsevier, vol. 99(C), pages 135-142.
    6. Marcus J. Chambers, 2015. "A Jackknife Correction to a Test for Cointegration Rank," Econometrics, MDPI, vol. 3(2), pages 1-21, May.

  14. Michael A. Thornton & Marcus J. Chambers, 2013. "Continuous-time autoregressive moving average processes in discrete time: representation and embeddability," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(5), pages 552-561, September.

    Cited by:

    1. Neil Kellard & Denise Osborn & Jerry Coakley & Marcus J. Chambers, 2015. "Testing for a Unit Root in a Near-Integrated Model with Skip-Sampled Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 630-649, September.
    2. P. Brockwell, 2014. "Recent results in the theory and applications of CARMA processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(4), pages 647-685, August.

  15. Chambers, Marcus J., 2013. "Jackknife estimation of stationary autoregressive models," Journal of Econometrics, Elsevier, vol. 172(1), pages 142-157.
    See citations under working paper version above.
  16. Chambers, Marcus J. & Thornton, Michael A., 2012. "Discrete Time Representation Of Continuous Time Arma Processes," Econometric Theory, Cambridge University Press, vol. 28(1), pages 219-238, February.

    Cited by:

    1. Thornton, Michael A. & Chambers, Marcus J., 2017. "Continuous time ARMA processes: Discrete time representation and likelihood evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 48-65.
    2. D. Stephen G. Pollock, 2020. "Linear Stochastic Models in Discrete and Continuous Time," Econometrics, MDPI, vol. 8(3), pages 1-22, September.
    3. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    4. Gabriele Fiorentini & Alessandro Galesi & Enrique Sentana, 2016. "A spectral EM algorithm for dynamic factor models," Working Papers 1619, Banco de España.
    5. Neil Kellard & Denise Osborn & Jerry Coakley & Marcus J. Chambers, 2015. "Testing for a Unit Root in a Near-Integrated Model with Skip-Sampled Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 630-649, September.
    6. Michael A. Thornton & Marcus J. Chambers, 2013. "Temporal aggregation in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 13, pages 289-310, Edward Elgar Publishing.
    7. Chambers, MJ, 2016. "The Estimation of Continuous Time Models with Mixed Frequency Data," Economics Discussion Papers 15988, University of Essex, Department of Economics.
    8. Thornton, Michael A. & Chambers, Marcus J., 2016. "The exact discretisation of CARMA models with applications in finance," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 739-761.
    9. Michael A. Thornton & Marcus J. Chambers, 2013. "Continuous-time autoregressive moving average processes in discrete time: representation and embeddability," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(5), pages 552-561, September.
    10. Chambers, MJ, 2016. "The Effects of Sampling Frequency on Detrending Methods for Unit Root Tests," Economics Discussion Papers 16062, University of Essex, Department of Economics.

  17. Marcus J. Chambers, 2011. "Cointegration and sampling frequency," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 156-185, July.
    See citations under working paper version above.
  18. Chambers, Marcus J., 2009. "Discrete Time Representations Of Cointegrated Continuous Time Models With Mixed Sample Data," Econometric Theory, Cambridge University Press, vol. 25(4), pages 1030-1049, August.

    Cited by:

    1. Thornton, Michael A. & Chambers, Marcus J., 2017. "Continuous time ARMA processes: Discrete time representation and likelihood evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 48-65.
    2. J. Isaac Miller, 2014. "Mixed-frequency Cointegrating Regressions with Parsimonious Distributed Lag Structures," Journal of Financial Econometrics, Oxford University Press, vol. 12(3), pages 584-614.
    3. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    4. Michael A. Thornton & Marcus J. Chambers, 2013. "Temporal aggregation in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 13, pages 289-310, Edward Elgar Publishing.
    5. Chambers, MJ, 2016. "The Estimation of Continuous Time Models with Mixed Frequency Data," Economics Discussion Papers 15988, University of Essex, Department of Economics.
    6. Michael A. Thornton & Marcus J. Chambers, 2013. "Continuous-time autoregressive moving average processes in discrete time: representation and embeddability," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(5), pages 552-561, September.
    7. Milena Hoyos, 2020. "Mixed First‐ and Second‐Order Cointegrated Continuous Time Models with Mixed Stock and Flow Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(2), pages 249-267, March.
    8. Hernández Juan R., 2016. "Unit Root Testing in ARMA Models: A Likelihood Ratio Approach," Working Papers 2016-03, Banco de México.
    9. Hernández, Juan R., 2016. "Unit Root Testing in ARMA Models: A Likelihood Ratio Approach," MPRA Paper 100857, University Library of Munich, Germany.

  19. Chambers, Marcus J., 2008. "Corrigendum to: "Testing for unit roots with flow data and varying sampling frequency" [J. Econom. 119 (1) (2004) 1-18]," Journal of Econometrics, Elsevier, vol. 144(2), pages 524-525, June.

    Cited by:

    1. Chambers, MJ, 2016. "The Effects of Sampling Frequency on Detrending Methods for Unit Root Tests," Economics Discussion Papers 16062, University of Essex, Department of Economics.

  20. Chambers, Marcus J. & Roderick McCrorie, J., 2007. "Frequency domain estimation of temporally aggregated Gaussian cointegrated systems," Journal of Econometrics, Elsevier, vol. 136(1), pages 1-29, January.

    Cited by:

    1. Vicky Fasen‐Hartmann & Sebastian Kimmig, 2020. "Robust estimation of stationary continuous‐time arma models via indirect inference," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(5), pages 620-651, September.
    2. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    3. J. Isaac Miller, 2016. "Conditionally Efficient Estimation of Long-Run Relationships Using Mixed-Frequency Time Series," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1142-1171, June.
    4. Marcus J. Chambers & Joanne S. Ercolani & A. M. Robert Taylor, 2010. "Testing for seasonal unit roots by frequency domain regression," Discussion Papers 10/02, University of Nottingham, Granger Centre for Time Series Econometrics.
    5. Chambers, MJ, 2016. "The Estimation of Continuous Time Models with Mixed Frequency Data," Economics Discussion Papers 15988, University of Essex, Department of Economics.
    6. Hernández Juan R., 2016. "Unit Root Testing in ARMA Models: A Likelihood Ratio Approach," Working Papers 2016-03, Banco de México.
    7. Hernández, Juan R., 2016. "Unit Root Testing in ARMA Models: A Likelihood Ratio Approach," MPRA Paper 100857, University Library of Munich, Germany.

  21. Ercolani, Joanne S. & Chambers, Marcus J., 2006. "Estimation Of Differential-Difference Equation Systems With Unknown Lag Parameters," Econometric Theory, Cambridge University Press, vol. 22(3), pages 483-498, June.

    Cited by:

    1. Joanne S. Ercolani, 2010. "On the Asymptotic Properties of a Feasible Estimator of the Continuous Time Long Memory Parameter," Discussion Papers 10-09, Department of Economics, University of Birmingham.
    2. Joanne S. Ercolani, 2007. "Cyclical Trends in Continuous Time Models," Discussion Papers 07-13, Department of Economics, University of Birmingham.
    3. Joanne S. Ercolani, 2014. "Cyclical Activity and Gestation Lags in Investment," Manchester School, University of Manchester, vol. 82(5), pages 620-630, September.

  22. McCrorie, J. Roderick & Chambers, Marcus J., 2006. "Granger causality and the sampling of economic processes," Journal of Econometrics, Elsevier, vol. 132(2), pages 311-336, June.
    See citations under working paper version above.
  23. Marcus J. Chambers & J. Roderick McCrorie, 2006. "Identification And Estimation Of Exchange Rate Models With Unobservable Fundamentals," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 573-582, May.
    See citations under working paper version above.
  24. Chambers, Marcus J., 2005. "The purchasing power parity puzzle, temporal aggregation, and half-life estimation," Economics Letters, Elsevier, vol. 86(2), pages 193-198, February.

    Cited by:

    1. Clements, Kenneth & Lan, Yihui & Roberts, John, 2008. "Exchange-rate economics for the resources sector," Resources Policy, Elsevier, vol. 33(2), pages 102-117, June.
    2. Michael Frömmel & Darko B. Vukovic & Jinyuan Wu, 2022. "The Dollar Exchange Rate, Adjustment to the Purchasing Power Parity, and the Interest Rate Differential," Mathematics, MDPI, vol. 10(23), pages 1-17, November.
    3. Andres Elberg, 2014. "Temporal Aggregation and Convergence to the Law of One Price: Evidence from Micro Data," Working Papers 53, Facultad de Economía y Empresa, Universidad Diego Portales.
    4. Ca' Zorzi, Michele & Chudik, Alexander, 2013. "Spatial considerations on the PPP debate," Working Paper Series 1534, European Central Bank.
    5. Mamingi Nlandu, 2017. "Beauty and Ugliness of Aggregation over Time: A Survey," Review of Economics, De Gruyter, vol. 68(3), pages 205-227, December.
    6. Seong, Byeongchan & Mahbub Morshed, A.K.M. & Ahn, Sung K., 2006. "Additional sources of bias in half-life estimation," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 2056-2064, December.
    7. Chambers, MJ, 2016. "The Effects of Sampling Frequency on Detrending Methods for Unit Root Tests," Economics Discussion Papers 16062, University of Essex, Department of Economics.

  25. Chambers, Marcus J., 2004. "Testing for unit roots with flow data and varying sampling frequency," Journal of Econometrics, Elsevier, vol. 119(1), pages 1-18, March.
    See citations under working paper version above.
  26. Chambers, Marcus J., 2003. "The Asymptotic Efficiency Of Cointegration Estimators Under Temporal Aggregation," Econometric Theory, Cambridge University Press, vol. 19(1), pages 49-77, February.

    Cited by:

    1. J. Isaac Miller, 2018. "Testing Cointegrating Relationships Using Irregular and Non-Contemporaneous Series with an Application to Paleoclimate Data," Working Papers 1809, Department of Economics, University of Missouri.
    2. Sentana, Enrique & Diez de los Rios, Antonio, 2007. "Testing Uncovered Interest Parity: A Continuous-Time Approach," CEPR Discussion Papers 6516, C.E.P.R. Discussion Papers.
    3. Hecq, A.W. & Götz, T.B. & Urbain, J.R.Y.J., 2012. "Forecasting Mixed Frequency Time Series with ECM-MIDAS Models," Research Memorandum 012, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    4. Chambers, Marcus J., 2020. "Frequency domain estimation of cointegrating vectors with mixed frequency and mixed sample data," Journal of Econometrics, Elsevier, vol. 217(1), pages 140-160.
    5. Philipp Gersing & Leopold Soegner & Manfred Deistler, 2022. "Retrieval from Mixed Sampling Frequency: Generic Identifiability in the Unit Root VAR," Papers 2204.05952, arXiv.org, revised Jul 2023.
    6. J. Isaac Miller, 2014. "Mixed-frequency Cointegrating Regressions with Parsimonious Distributed Lag Structures," Journal of Financial Econometrics, Oxford University Press, vol. 12(3), pages 584-614.
    7. Eric Ghysels & J. Isaac Miller, 2014. "On the Size Distortion from Linearly Interpolating Low-frequency Series for Cointegration Tests," Working Papers 1403, Department of Economics, University of Missouri.
    8. Herzer, Dierk & Strulik, Holger & Vollmer, Sebastian, 2010. "The Long-run Determinants of Fertility: One Century of Demographic Change 1900-1999," Hannover Economic Papers (HEP) dp-456, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    9. Eric Ghysels & J. Isaac Miller, 2013. "Testing for Cointegration with Temporally Aggregated and Mixed-frequency Time Series," Working Papers 1307, Department of Economics, University of Missouri, revised 07 May 2014.
    10. Chambers, M.J. & McCrorie, J.R., 2004. "Frequency Domain Gaussian Estimation of Temporally Aggregated Cointegrated Systems," Discussion Paper 2004-40, Tilburg University, Center for Economic Research.
    11. J. Isaac Miller & Xi Wang, 2016. "Implementing Residual-Based KPSS Tests for Cointegration with Data Subject to Temporal Aggregation and Mixed Sampling Frequencies," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(6), pages 810-824, November.
    12. Chambers, Marcus J. & Roderick McCrorie, J., 2007. "Frequency domain estimation of temporally aggregated Gaussian cointegrated systems," Journal of Econometrics, Elsevier, vol. 136(1), pages 1-29, January.
    13. Chambers, MJ, 2016. "The Effects of Sampling Frequency on Detrending Methods for Unit Root Tests," Economics Discussion Papers 16062, University of Essex, Department of Economics.

  27. Chambers, Marcus J. & McGarry, Joanne S., 2002. "Modeling Cyclical Behavior With Differential-Difference Equations In An Unobserved Components Framework," Econometric Theory, Cambridge University Press, vol. 18(2), pages 387-419, April.

    Cited by:

    1. Joanne S. McGarry & Marcus J. Chambers, 2004. "Party formation and coalitional bargaining in a model of proportional representation," Discussion Papers 04-07, Department of Economics, University of Birmingham.
    2. Eliana González & Luis F. Melo & Luis E. Rojas & Brayan Rojas, 2011. "Estimations of the Natural Rate of Interest in Colombia," Money Affairs, CEMLA, vol. 0(1), pages 33-75, January-J.
    3. Joanne S. Ercolani, 2010. "On the Asymptotic Properties of a Feasible Estimator of the Continuous Time Long Memory Parameter," Discussion Papers 10-09, Department of Economics, University of Birmingham.
    4. Joanne S. Ercolani, 2007. "Cyclical Trends in Continuous Time Models," Discussion Papers 07-13, Department of Economics, University of Birmingham.
    5. Tucker S. McElroy & Thomas M. Trimbur, 2007. "Continuous time extraction of a nonstationary signal with illustrations in continuous low-pass and band-pass filtering," Finance and Economics Discussion Series 2007-68, Board of Governors of the Federal Reserve System (U.S.).
    6. Joanne S. Ercolani, 2014. "Cyclical Activity and Gestation Lags in Investment," Manchester School, University of Manchester, vol. 82(5), pages 620-630, September.
    7. Webel, Karsten, 2022. "A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series," Discussion Papers 31/2022, Deutsche Bundesbank.

  28. Chambers, Marcus J., 2001. "Temporal Aggregation And The Finite Sample Performance Of Spectral Regression Estimators In Cointegrated Systems," Econometric Theory, Cambridge University Press, vol. 17(3), pages 591-607, June.

    Cited by:

    1. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    2. Marcus J. Chambers, 2011. "Cointegration and sampling frequency," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 156-185, July.
    3. Chambers, Marcus J. & Roderick McCrorie, J., 2007. "Frequency domain estimation of temporally aggregated Gaussian cointegrated systems," Journal of Econometrics, Elsevier, vol. 136(1), pages 1-29, January.

  29. Marcus J. Chambers & Roy E. Bailey, 1999. "A Statistical Analysis of Wheat Price Fluctuations in England: 1685–1850," Journal of Agricultural Economics, Wiley Blackwell, vol. 50(3), pages 564-588, September.

    Cited by:

    1. David Stead, 2004. "Risk and risk management in English agriculture, c. 1750–1850," Economic History Review, Economic History Society, vol. 57(2), pages 334-361, May.

  30. Chambers, Marcus J., 1999. "Discrete time representation of stationary and non-stationary continuous time systems," Journal of Economic Dynamics and Control, Elsevier, vol. 23(4), pages 619-639, February.

    Cited by:

    1. Thornton, Michael A. & Chambers, Marcus J., 2017. "Continuous time ARMA processes: Discrete time representation and likelihood evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 48-65.
    2. Theodore Simos, 2008. "The exact discrete model of a system of linear stochastic differential equations driven by fractional noise," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(6), pages 1019-1031, November.
    3. D. Stephen G. Pollock, 2020. "Linear Stochastic Models in Discrete and Continuous Time," Econometrics, MDPI, vol. 8(3), pages 1-22, September.
    4. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    5. Chen, Baoline & Zadrozny, Peter A., 2001. "Analytic derivatives of the matrix exponential for estimation of linear continuous-time models1," Journal of Economic Dynamics and Control, Elsevier, vol. 25(12), pages 1867-1879, December.
    6. J. McCrorie, 2002. "The Likelihood of the Parameters of a Continuous Time Vector Autoregressive Model," Statistical Inference for Stochastic Processes, Springer, vol. 5(3), pages 273-286, October.
    7. J. Roderick McCrorie, 2000. "The Likelihood of a Continuous-time Vector Autoregressive Model," Working Papers 419, Queen Mary University of London, School of Economics and Finance.
    8. McCrorie, J.R. & Chambers, M.J., 2004. "Granger Causality and the Sampling of Economic Processes," Discussion Paper 2004-39, Tilburg University, Center for Economic Research.
    9. Marcus J. Chambers, 2011. "Cointegration and sampling frequency," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 156-185, July.
    10. Michael A. Thornton & Marcus J. Chambers, 2013. "Temporal aggregation in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 13, pages 289-310, Edward Elgar Publishing.
    11. Chambers, M.J. & McCrorie, J.R., 2004. "Frequency Domain Gaussian Estimation of Temporally Aggregated Cointegrated Systems," Discussion Paper 2004-40, Tilburg University, Center for Economic Research.
    12. Arie ten Cate, 2004. "Refinement of the partial adjustment model using continuous-time econometrics," CPB Discussion Paper 41, CPB Netherlands Bureau for Economic Policy Analysis.
    13. Jewitt, Giles & Roderick McCrorie, J., 2005. "Computing estimates of continuous time macroeconometric models on the basis of discrete data," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 397-416, April.
    14. Tilak Abeysinghe & Gulasekaran Rajaguru, 2004. "Temporal aggregation, causality distortions and a sign rule," Econometric Society 2004 Australasian Meetings 73, Econometric Society.
    15. Roderick McCrorie, J., 2001. "Interpolating exogenous variables in continuous time dynamic models," Journal of Economic Dynamics and Control, Elsevier, vol. 25(9), pages 1399-1427, September.
    16. Chambers, Marcus J. & Roderick McCrorie, J., 2007. "Frequency domain estimation of temporally aggregated Gaussian cointegrated systems," Journal of Econometrics, Elsevier, vol. 136(1), pages 1-29, January.
    17. Michael A. Thornton & Marcus J. Chambers, 2013. "Continuous-time autoregressive moving average processes in discrete time: representation and embeddability," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(5), pages 552-561, September.

  31. Marcus J. Chambers, 1999. "A Note on Modelling Seasonal Processes in Continuous Time," Journal of Time Series Analysis, Wiley Blackwell, vol. 20(2), pages 139-143, March.

    Cited by:

    1. Webel, Karsten, 2022. "A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series," Discussion Papers 31/2022, Deutsche Bundesbank.

  32. Chambers, Marcus J, 1998. "Long Memory and Aggregation in Macroeconomic Time Series," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 1053-1072, November.
    See citations under working paper version above.
  33. Chambers, Marcus J., 1998. "The estimation of systems of joint differential-difference equations," Journal of Econometrics, Elsevier, vol. 85(1), pages 1-31, July.
    See citations under working paper version above.
  34. Roy E. Bailey & Marcus J. Chambers, 1998. "The impact of real wage and mortality fluctuations on fertility and nuptiality in precensus England," Journal of Population Economics, Springer;European Society for Population Economics, vol. 11(3), pages 413-434.

    Cited by:

    1. George Hondroyiannis, 2009. "Fertility Determinants and Economic Uncertainty:An Assessment Using European Panel Data," Working Papers 96, Bank of Greece.
    2. Peter Grajzl & Peter Murrell, 2022. "Did Caselaw Foster England’s Economic Development during the Industrial Revolution? Data and Evidence," CESifo Working Paper Series 10088, CESifo.
    3. Francisco Climent Diranzo & Robert Meneu Gaya, "undated". "Relaciones de equilibrio entre demografía y crecimiento económico en Espana," Studies on the Spanish Economy 163, FEDEA.
    4. Marcus J. Chambers & Roy E. Bailey, 1999. "A Statistical Analysis of Wheat Price Fluctuations in England: 1685–1850," Journal of Agricultural Economics, Wiley Blackwell, vol. 50(3), pages 564-588, September.
    5. Alam, Shamma Adeeb & Pörtner, Claus C., 2018. "Income shocks, contraceptive use, and timing of fertility," Journal of Development Economics, Elsevier, vol. 131(C), pages 96-103.

  35. Marcus Chambers & K. Ben Nowman, 1997. "Forecasting with the almost ideal demand system: evidence from some alternative dynamic specifications," Applied Economics, Taylor & Francis Journals, vol. 29(7), pages 935-943.

    Cited by:

    1. Balcombe, Kelvin & Bailey, Alastair, 2006. "Bayesian inference of a smooth transition dynamic almost ideal model of food demand in the US," MPRA Paper 17305, University Library of Munich, Germany.
    2. Li, Gang & Song, Haiyan & Witt, Stephen F., 2006. "Time varying parameter and fixed parameter linear AIDS: An application to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 22(1), pages 57-71.
    3. Cranfield, John A.L. & Preckel, Paul V. & Hertel, Thomas W., 2005. "A Modified, Implicit, Directly Additive Demand System," Working Papers 34145, University of Guelph, Department of Food, Agricultural and Resource Economics.
    4. Chang, C-L. & Khamkaew, T. & McAleer, M.J., 2010. "Estimating Price Effects in an Almost Ideal Demand Model of Outbound Thai Tourism to East Asia," Econometric Institute Research Papers EI 2010-29, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Mohammad Hashem Pesaran & Yongcheol Shin, 1999. "Long-Run Structural Modelling," Edinburgh School of Economics Discussion Paper Series 44, Edinburgh School of Economics, University of Edinburgh.
    6. Erkan Erdil, 2006. "Demand systems for agricultural products in OECD countries," Applied Economics Letters, Taylor & Francis Journals, vol. 13(3), pages 163-169.
    7. Dogbe, Wisdom, 2022. "Implications of increasing fruits and vegetable consumption in Scotland," 96th Annual Conference, April 4-6, 2022, K U Leuven, Belgium 321232, Agricultural Economics Society - AES.
    8. Chang, Hui-Shung (Christie), 2000. "An econometric analysis of the competitive position of Australian cotton in the Japanese market," Working Papers 12940, University of New England, School of Economics.
    9. Chang, Hui-Shung (Christie) & Nguyen, Chi, 1997. "The elasticity of demand for Australian cotton in Japan," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 46(1), pages 1-15.
    10. Chang, Hui-Shung (Christie) & Bettington, Nicholas, 2001. "Demand for Wine in Australia: Systems Versus Single Equation Approach," Working Papers 12923, University of New England, School of Economics.
    11. Wang, Zijun & Bessler, David A, 2002. "The Homogeneity Restriction and Forecasting Performance of VAR-Type Demand Systems: An Empirical Examination of US Meat Consumption," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(3), pages 193-206, April.
    12. Byers, S. L. & Nowman, K. B., 1998. "Forecasting U.K. and U.S. interest rates using continuous time term structure models," International Review of Financial Analysis, Elsevier, vol. 7(3), pages 191-206.
    13. Chang, Hui-Shung & Griffith, Garry & Bettington, Nicholas, 2002. "The Demand for Wine in Australia Using a Systems Approach: Industry Implications," Australasian Agribusiness Review, University of Melbourne, Department of Agriculture and Food Systems, vol. 10, pages 1-12, September.
    14. J. M. Gil & B. Dhehibi & M. Ben Kaabia & A. M. Angulo, 2004. "Non-stationarity and the import demand for virgin olive oil in the European Union," Applied Economics, Taylor & Francis Journals, vol. 36(16), pages 1859-1869.
    15. Tonsor, Glynn T. & Marsh, Thomas L., 2005. "Comparing Heterogeneous Consumption in US and Japanese Meat and Fish Demand," 2005 Annual meeting, July 24-27, Providence, RI 19567, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    16. Athanasopoulos, George & Deng, Minfeng & Li, Gang & Song, Haiyan, 2014. "Modelling substitution between domestic and outbound tourism in Australia: A system-of-equations approach," Tourism Management, Elsevier, vol. 45(C), pages 159-170.

  36. Chambers, Marcus J., 1996. "Fractional integration, trend stationarity and difference stationarity Evidence from some U.K. macroeconomic time series," Economics Letters, Elsevier, vol. 50(1), pages 19-24, January.

    Cited by:

    1. Marmol, Francesc, 1997. "Fractional integration versus trend stationary in time series analysis," DES - Working Papers. Statistics and Econometrics. WS 10498, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Marmol, Francesc & Velasco, Carlos, 2002. "Trend stationarity versus long-range dependence in time series analysis," Journal of Econometrics, Elsevier, vol. 108(1), pages 25-42, May.

  37. Chambers, Marcus J., 1996. "The Estimation of Continuous Parameter Long-Memory Time Series Models," Econometric Theory, Cambridge University Press, vol. 12(2), pages 374-390, June.

    Cited by:

    1. Henghsiu Tsai & K. S. Chan, 2005. "Quasi‐Maximum Likelihood Estimation for a Class of Continuous‐time Long‐memory Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(5), pages 691-713, September.
    2. Theodore Simos & Mike Tsionas, 2018. "Bayesian inference of the fractional Ornstein–Uhlenbeck process under a flow sampling scheme," Computational Statistics, Springer, vol. 33(4), pages 1687-1713, December.
    3. Theodore Simos, 2008. "The exact discrete model of a system of linear stochastic differential equations driven by fractional noise," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(6), pages 1019-1031, November.
    4. Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Estimation of Long Memory in Integrated Variance," Econometric Reviews, Taylor & Francis Journals, vol. 33(7), pages 785-814, October.
    5. Henghsiu Tsai & K. S. Chan, 2005. "Temporal Aggregation of Stationary And Nonstationary Discrete‐Time Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(4), pages 613-624, July.
    6. Anne Philippe & Caroline Robet & Marie-Claude Viano, 2021. "Random discretization of stationary continuous time processes," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(3), pages 375-400, April.
    7. Comte, F., 1998. "Discrete and continuous time cointegration," Journal of Econometrics, Elsevier, vol. 88(2), pages 207-226, November.
    8. Joanne S. Ercolani, 2010. "On the Asymptotic Properties of a Feasible Estimator of the Continuous Time Long Memory Parameter," Discussion Papers 10-09, Department of Economics, University of Birmingham.
    9. Wymer Clifford R., 2012. "Continuous-Tme Econometrics of Structural Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(2), pages 1-28, April.
    10. Leonenko, Nikolai N. & Sharapov, Michail M. & El-Bassiouny, Ahmed H., 2000. "On the exactness of normal approximation of LSE of regression coefficient of long-memory random fields," Statistics & Probability Letters, Elsevier, vol. 48(2), pages 121-130, June.
    11. Uwe Hassler, 2011. "Estimation of fractional integration under temporal aggregation," Post-Print hal-00815563, HAL.
    12. Souza, Leonardo R. & Smith, Jeremy, 2002. "Bias in the memory parameter for different sampling rates," International Journal of Forecasting, Elsevier, vol. 18(2), pages 299-313.

  38. Chambers, Marcus J & Bailey, Roy E, 1996. "A Theory of Commodity Price Fluctuations," Journal of Political Economy, University of Chicago Press, vol. 104(5), pages 924-957, October.
    See citations under working paper version above.
  39. R. E. Bailey & M. J. Chambers, 1993. "Long‐Term Demographic Interactions in Precensus England," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 156(3), pages 339-362, May.

    Cited by:

    1. Crafts, Nicholas & Mills, Terence C., 2020. "Considering the counterfactual: Real wages in the First Industrial Revolution," CAGE Online Working Paper Series 502, Competitive Advantage in the Global Economy (CAGE).
    2. Crafts, Nicholas & Mills, Terence C., 2020. "The Race between Population and Technology : Real Wages in the First Industrial Revolution," The Warwick Economics Research Paper Series (TWERPS) 1298, University of Warwick, Department of Economics.
    3. Robert McNown, 2003. "A Cointegration Model of Age‐Specific Fertility and Female Labor Supply in the United States," Southern Economic Journal, John Wiley & Sons, vol. 70(2), pages 344-358, October.
    4. Peter Grajzl & Peter Murrell, 2023. "Of families and inheritance: law and development in England before the Industrial Revolution," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 17(3), pages 387-432, September.
    5. Ulrich Pfister & Georg Fertig, 2020. "From Malthusian Disequilibrium to the Post-Malthusian Era: The Evolution of the Preventive and Positive Checks in Germany, 1730–1870," Demography, Springer;Population Association of America (PAA), vol. 57(3), pages 1145-1170, June.
    6. Jacob B. Madsen & Peter E. Robertson & Longfeng Ye, 2019. "Malthus Was Right: Explaining a Millennium of Stagnation," Economics Discussion / Working Papers 19-16, The University of Western Australia, Department of Economics.
    7. Maja Pedersen & Claudia Riani & Paul Sharp, 2021. "Malthus in preindustrial Northern Italy?," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(3), pages 1003-1026, July.
    8. Maja Pedersen & Claudia Riani & Paul Sharp, 2019. "Malthus in Pre-industrial Northern Italy? A Cointegration Approach," Working Papers 0156, European Historical Economics Society (EHES).

  40. Chambers, Marcus J, 1992. "Estimation of a Continuous-Time Dynamic Demand System," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(1), pages 53-64, Jan.-Marc.

    Cited by:

    1. Chambers, MJ & McCrorie, JR & Thornton, MA, 2017. "Continuous Time Modelling Based on an Exact Discrete Time Representation," Economics Discussion Papers 20497, University of Essex, Department of Economics.
    2. Anton Bondarev, 2008. "Evaluation of Demand Functions for foodstuffs in Russian Economy in 1999–2004," Research Paper Series, Gaidar Institute for Economic Policy, issue 118P, pages 166-166.

  41. Chambers, Marcus J., 1991. "Discrete Models for Estimating General Linear Continuous Time Systems," Econometric Theory, Cambridge University Press, vol. 7(4), pages 531-542, December.

    Cited by:

    1. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," CIRANO Working Papers 2004s-20, CIRANO.
    2. Roderick McCrorie, J., 2001. "Interpolating exogenous variables in continuous time dynamic models," Journal of Economic Dynamics and Control, Elsevier, vol. 25(9), pages 1399-1427, September.
    3. Byers, S. L. & Nowman, K. B., 1998. "Forecasting U.K. and U.S. interest rates using continuous time term structure models," International Review of Financial Analysis, Elsevier, vol. 7(3), pages 191-206.

  42. Chambers, Marcus J., 1990. "Forecasting with demand systems : A comparative study," Journal of Econometrics, Elsevier, vol. 44(3), pages 363-376, June.

    Cited by:

    1. Shashika D. Rathnayaka & Saroja Selvanathan & E. A. Selvanathan, 2021. "Demand for animal‐derived food in selected Asian countries: A system‐wide analysis," Agricultural Economics, International Association of Agricultural Economists, vol. 52(1), pages 97-122, January.
    2. Mu, Jianhong E. & McCarl, Bruce A. & Bessler, David A., 2013. "Impacts of BSE and Avian Influenza on U.S. Meat Demand," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150392, Agricultural and Applied Economics Association.
    3. Li, Gang & Song, Haiyan & Witt, Stephen F., 2006. "Time varying parameter and fixed parameter linear AIDS: An application to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 22(1), pages 57-71.
    4. Toshinobu Matsuda, 2006. "Linear approximations to the quadratic almost ideal demand system," Empirical Economics, Springer, vol. 31(3), pages 663-675, September.
    5. Chambers, Marcus J, 1992. "Estimation of a Continuous-Time Dynamic Demand System," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(1), pages 53-64, Jan.-Marc.
    6. Arsenault, E. & Bernard, J.T. & Carr, C.W. & Genest-Laplante, E., 1993. "A Total Energy Demand Model of Quebec: Forecasting Properties," Papers 9329, Laval - Recherche en Energie.
    7. Kostas Bithas & Chrysostomos Stoforos, 2006. "Estimating Urban Residential Water Demand Determinants and Forecasting Water Demand for Athens Metropolitan Area, 2000-2010," South-Eastern Europe Journal of Economics, Association of Economic Universities of South and Eastern Europe and the Black Sea Region, vol. 4(1), pages 47-59.
    8. Ingco, Merlinda D., 1991. "Is rice becoming an inferior good? Food demand in the Philippines," Policy Research Working Paper Series 722, The World Bank.
    9. Zijun Wang & David A. Bessler, 2003. "Forecast evaluations in meat demand analysis," Agribusiness, John Wiley & Sons, Ltd., vol. 19(4), pages 505-523.
    10. Rapanos, Vassilis T. & Polemis, Michael L., 2006. "The structure of residential energy demand in Greece," Energy Policy, Elsevier, vol. 34(17), pages 3137-3143, November.
    11. Toshinobu Matsuda, 2007. "Linearizing the inverse quadratic almost ideal demand system," Applied Economics, Taylor & Francis Journals, vol. 39(3), pages 381-396.
    12. Cranfield, J. A. L. & Pellow, Scott, 2004. "The role of global vs. local negativity in functional form selection: an application to Canadian consumer demands," Economic Modelling, Elsevier, vol. 21(2), pages 345-360, March.
    13. Wang, Zijun & Bessler, David A, 2002. "The Homogeneity Restriction and Forecasting Performance of VAR-Type Demand Systems: An Empirical Examination of US Meat Consumption," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(3), pages 193-206, April.
    14. Tridimas, George, 2000. "The analysis of consumer demand in Greece. Model selection and dynamic specification," Economic Modelling, Elsevier, vol. 17(4), pages 455-471, December.

Chapters

  1. Michael A. Thornton & Marcus J. Chambers, 2013. "Temporal aggregation in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 13, pages 289-310, Edward Elgar Publishing.

    Cited by:

    1. Du, Yingxin & Ju, Jiandong & Ramirez, Carlos D. & Yao, Xi, 2017. "Bilateral trade and shocks in political relations: Evidence from China and some of its major trading partners, 1990–2013," Journal of International Economics, Elsevier, vol. 108(C), pages 211-225.
    2. Bartsch, Zachary, 2019. "Economic policy uncertainty and dollar-pound exchange rate return volatility," Journal of International Money and Finance, Elsevier, vol. 98(C), pages 1-1.

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