Optimal Autoregressive Predictions
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Choi,In, 2015.
"Almost All about Unit Roots,"
Cambridge Books,
Cambridge University Press, number 9781107482500, November.
- Choi,In, 2015. "Almost All about Unit Roots," Cambridge Books, Cambridge University Press, number 9781107097339, January.
- Phillips, Peter C B, 1988.
"Regression Theory for Near-Integrated Time Series,"
Econometrica, Econometric Society, vol. 56(5), pages 1021-1043, September.
- Peter C.B. Phillips, 1986. "Regression Theory for Near-Integrated Time Series," Cowles Foundation Discussion Papers 781R, Cowles Foundation for Research in Economics, Yale University, revised Jan 1987.
- G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
- G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
- Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 25(Win), pages 2-11.
- Choi, In, 1993. "Asymptotic Normality of the Least-Squares Estimates for Higher Order Autoregressive Integrated Processes with Some Applications," Econometric Theory, Cambridge University Press, vol. 9(2), pages 263-282, April.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Szafranek, Karol, 2019.
"Bagged neural networks for forecasting Polish (low) inflation,"
International Journal of Forecasting, Elsevier, vol. 35(3), pages 1042-1059.
- Karol Szafranek, 2017. "Bagged artificial neural networks in forecasting inflation: An extensive comparison with current modelling frameworks," NBP Working Papers 262, Narodowy Bank Polski.
- Baumeister, Christiane & Kilian, Lutz & Lee, Thomas K., 2014.
"Are there gains from pooling real-time oil price forecasts?,"
Energy Economics, Elsevier, vol. 46(S1), pages 33-43.
- Christiane Baumeister & Lutz Kilian & Thomas K. Lee, 2014. "Are There Gains from Pooling Real-Time Oil Price Forecasts?," Staff Working Papers 14-46, Bank of Canada.
- Kilian, Lutz & Baumeister, Christiane & Lee, Thomas K, 2014. "Are there Gains from Pooling Real-Time Oil Price Forecasts?," CEPR Discussion Papers 10075, C.E.P.R. Discussion Papers.
- Marco Del Negro & Michele Lenza & Giorgio E. Primiceri & Andrea Tambalotti, 2020.
"What's Up with the Phillips Curve?,"
Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 51(1 (Spring), pages 301-373.
- Marco Del Negro & Michele Lenza & Giorgio E. Primiceri & Andrea Tambalotti, 2020. "What’s up with the Phillips Curve?," NBER Working Papers 27003, National Bureau of Economic Research, Inc.
- Del Negro, Marco & Lenza, Michele & Primiceri, Giorgio E. & Tambalotti, Andrea, 2020. "What’s up with the Phillips Curve?," Working Paper Series 2435, European Central Bank.
- Primiceri, Giorgio & Del Negro, Marco & Lenza, Michele & Tambalotti, Andrea, 2020. "What's up with the Phillips Curve?," CEPR Discussion Papers 14583, C.E.P.R. Discussion Papers.
- William Chen & Marco Del Negro & Michele Lenza & Giorgio E. Primiceri & Andrea Tambalotti, 2020. "What’s Up with the Phillips Curve?," Liberty Street Economics 20200918a, Federal Reserve Bank of New York.
- Barbara Rossi, 2013.
"Exchange Rate Predictability,"
Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
- Rossi, Barbara, 2013. "Exchange Rate Predictability," CEPR Discussion Papers 9575, C.E.P.R. Discussion Papers.
- Barbara Rossi, 2015. "Exchange Rate Predictability," Working Papers 690, Barcelona School of Economics.
- Barbara Rossi, 2013. "Exchange rate predictability," Economics Working Papers 1369, Department of Economics and Business, Universitat Pompeu Fabra.
- Norman R. Swanson & Weiqi Xiong, 2018.
"Big data analytics in economics: What have we learned so far, and where should we go from here?,"
Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 51(3), pages 695-746, August.
- Norman R. Swanson & Weiqi Xiong, 2018. "Big data analytics in economics: What have we learned so far, and where should we go from here?," Canadian Journal of Economics, Canadian Economics Association, vol. 51(3), pages 695-746, August.
- Kinda Hachem & Jing Cynthia Wu, 2017.
"Inflation Announcements and Social Dynamics,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(8), pages 1673-1713, December.
- Jing Cynthia Wu & Kinda Hachem, 2013. "Inflation Announcements and Social Dynamics," 2013 Meeting Papers 238, Society for Economic Dynamics.
- Kinda Hachem & Jing Cynthia Wu, 2014. "Inflation Announcements and Social Dynamics," NBER Working Papers 20161, National Bureau of Economic Research, Inc.
- Ang, Andrew & Bekaert, Geert & Wei, Min, 2007.
"Do macro variables, asset markets, or surveys forecast inflation better?,"
Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
- Andrew Ang & Geert Bekaert & Min Wei, 2005. "Do Macro Variables, Asset Markets or Surveys Forecast Inflation Better?," NBER Working Papers 11538, National Bureau of Economic Research, Inc.
- Andrew Ang & Geert Bekaert & Min Wei, 2006. "Do macro variables, asset markets, or surveys forecast inflation better?," Finance and Economics Discussion Series 2006-15, Board of Governors of the Federal Reserve System (U.S.).
- Christiane Baumeister & Lutz Kilian & Thomas K. Lee, 2017.
"Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 275-295, March.
- Baumeister, Christiane & Kilian, Lutz & Lee, Thomas K., 2015. "Inside the crystal ball: New approaches to predicting the gasoline price at the pump," CFS Working Paper Series 500, Center for Financial Studies (CFS).
- Kilian, Lutz & Baumeister, Christiane & Lee, Thomas K, 2015. "Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump," CEPR Discussion Papers 10362, C.E.P.R. Discussion Papers.
- Christiane Baumeister & Lutz Kilian & Thomas K. Lee, 2016. "Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump," CESifo Working Paper Series 5759, CESifo.
- Barkan, Oren & Benchimol, Jonathan & Caspi, Itamar & Cohen, Eliya & Hammer, Allon & Koenigstein, Noam, 2023.
"Forecasting CPI inflation components with Hierarchical Recurrent Neural Networks,"
International Journal of Forecasting, Elsevier, vol. 39(3), pages 1145-1162.
- Oren Barkan & Jonathan Benchimol & Itamar Caspi & Eliya Cohen & Allon Hammer & Noam Koenigstein, 2020. "Forecasting CPI Inflation Components with Hierarchical Recurrent Neural Networks," Papers 2011.07920, arXiv.org, revised Feb 2022.
- Oren Barkan & Jonathan Benchimol & Itamar Caspi & Eliya Cohen & Allon Hammer & Noam Koenigstein, 2023. "Forecasting CPI inflation components with Hierarchical Recurrent Neural Networks," Post-Print emse-04624940, HAL.
- Oren Barkan & Jonathan Benchimol & Itamar Caspi & Allon Hammer & Noam Koenigstein, 2021. "Forecasting CPI Inflation Components with Hierarchical Recurrent Neural Networks," Bank of Israel Working Papers 2021.06, Bank of Israel.
- Rossi, Barbara & Sekhposyan, Tatevik, 2014.
"Evaluating predictive densities of US output growth and inflation in a large macroeconomic data set,"
International Journal of Forecasting, Elsevier, vol. 30(3), pages 662-682.
- Barbara Rossi & Tatevik Sekhposyan, 2013. "Evaluating predictive densities of U.S. output growth and inflation in a large macroeconomic data set," Economics Working Papers 1370, Department of Economics and Business, Universitat Pompeu Fabra.
- Barbara Rossi, 2015. "Evaluating Predictive Densities of US Output Growth and Inflation in a Large Macroeconomic Data Set," Working Papers 689, Barcelona School of Economics.
- Hännikäinen Jari, 2017.
"Selection of an Estimation Window in the Presence of Data Revisions and Recent Structural Breaks,"
Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-22, January.
- Hännikäinen, Jari, 2015. "Selection of an estimation window in the presence of data revisions and recent structural breaks," MPRA Paper 66759, University Library of Munich, Germany.
- Jari Hännikäinen, 2016. "Selection of an Estimation Window in the Presence of Data Revisions and Recent Structural Breaks," Working Papers 1692, Tampere University, Faculty of Management and Business, Economics.
- Malte Knüppel & Fabian Krüger, 2022.
"Forecast uncertainty, disagreement, and the linear pool,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 23-41, January.
- Knüppel, Malte & Krüger, Fabian, 2017. "Forecast Uncertainty, Disagreement, and Linear Pools of Density Forecasts," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168294, Verein für Socialpolitik / German Economic Association.
- Knüppel, Malte & Krüger, Fabian, 2019. "Forecast uncertainty, disagreement, and the linear pool," Discussion Papers 28/2019, Deutsche Bundesbank.
- Rui Liu, 2019. "Forecasting Bond Risk Premia with Unspanned Macroeconomic Information," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 9(01), pages 1-62, March.
- Raffaella Giacomini & Barbara Rossi, 2015.
"Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models,"
Annual Review of Economics, Annual Reviews, vol. 7(1), pages 207-229, August.
- Raffaella Giacomini & Barbara Rossi, 2014. "Forecasting in nonstationary environments: What works and what doesn't in reduced-form and structural models," Economics Working Papers 1476, Department of Economics and Business, Universitat Pompeu Fabra.
- Raffaella Giacomini & Barbara Rossi, 2015. "Forecasting in Nonstationary Environments: What Works and What Doesn’t in Reduced-Form and Structural Models," Working Papers 819, Barcelona School of Economics.
- Bennedsen, Mikkel & Hillebrand, Eric & Koopman, Siem Jan, 2021.
"Modeling, forecasting, and nowcasting U.S. CO2 emissions using many macroeconomic predictors,"
Energy Economics, Elsevier, vol. 96(C).
- Mikkel Bennedsen & Eric Hillebrand & Siem Jan Koopman, 2019. "Modeling, Forecasting, and Nowcasting U.S. CO2 Emissions Using Many Macroeconomic Predictors," CREATES Research Papers 2019-21, Department of Economics and Business Economics, Aarhus University.
- Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018.
"Risk Everywhere: Modeling and Managing Volatility,"
The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2729-2773.
- Pedersen, Lasse Heje & Bollerslev, Tim & Hood, Benjamin & Huss, John, 2018. "Risk Everywhere: Modeling and Managing Volatility," CEPR Discussion Papers 12687, C.E.P.R. Discussion Papers.
- Manzan, Sebastiano & Zerom, Dawit, 2013.
"Are macroeconomic variables useful for forecasting the distribution of U.S. inflation?,"
International Journal of Forecasting, Elsevier, vol. 29(3), pages 469-478.
- Manzan, Sebastiano & Zerom, Dawit, 2009. "Are Macroeconomic Variables Useful for Forecasting the Distribution of U.S. Inflation?," MPRA Paper 14387, University Library of Munich, Germany.
- Jiahan Li & Ilias Tsiakas & Wei Wang, 2015.
"Predicting Exchange Rates Out of Sample: Can Economic Fundamentals Beat the Random Walk?,"
Journal of Financial Econometrics, Oxford University Press, vol. 13(2), pages 293-341.
- Jiahan Li & Ilias Tsiakas & Wei Wang, 2014. "Predicting Exchange Rates Out of Sample: Can Economic Fundamentals Beat the Random Walk?," Working Paper series 05_14, Rimini Centre for Economic Analysis.
- Barbara Rossi, 2019.
"Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them,"
Economics Working Papers
1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
- Barbara Rossi, 2020. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," Working Papers 1162, Barcelona School of Economics.
- Rossi, Barbara, 2020. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," CEPR Discussion Papers 14472, C.E.P.R. Discussion Papers.
- M. Hashem Pesaran & Andreas Pick & Allan Timmermann, 2022.
"Forecasting With Panel Data: Estimation Uncertainty Versus Parameter Heterogeneity,"
CESifo Working Paper Series
9690, CESifo.
- Pesaran, M. Hashem & Pick, Andreas & Timmermann, Allan, 2022. "Forecasting with panel data: estimation uncertainty versus parameter heterogeneity," CEPR Discussion Papers 17123, C.E.P.R. Discussion Papers.
- Pesaran, M. H. & Pick, A. & Timmermann, A., 2022. "Forecasting with panel data: estimation uncertainty versus parameter heterogeneity," Cambridge Working Papers in Economics 2219, Faculty of Economics, University of Cambridge.
- M. Hashem Pesaran & Andreas Pick & Allan Timmermann, 2024. "Forecasting with panel data: Estimation uncertainty versus parameter heterogeneity," Papers 2404.11198, arXiv.org.
More about this item
Keywords
Autoregressive model; prediction; near unit root;All these keywords.
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2016-07-30 (Econometrics)
- NEP-ETS-2016-07-30 (Econometric Time Series)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sgo:wpaper:1607. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Jung Hur (email available below). General contact details of provider: https://edirc.repec.org/data/risogkr.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.