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Ching-Kang Ing

Personal Details

First Name:Ching-Kang
Middle Name:
Last Name:Ing
Suffix:
RePEc Short-ID:pin116
http://mx.nthu.edu.tw/~cking/

Affiliation

國立清華大學統計學研究所 (Institute of Statistics, National Tsing Hua University)

http://stat.web.nthu.edu.tw/bin/home.php
Taiwan, Hsinchu

Research output

as
Jump to: Working papers Articles

Working papers

  1. HONDA, Toshio & 本田, 敏雄 & ING, Ching-Kang & WU, Wei-Ying, 2017. "Adaptively weighted group Lasso for semiparametric quantile regression models," Discussion Papers 2017-04, Graduate School of Economics, Hitotsubashi University.
  2. Ching-Kang Ing & Ching-Zong Wei, 2005. "A maximal moment inequality for long range dependent time series with applications to estimation and model selection," Econometrics 0508009, University Library of Munich, Germany.
  3. Ching-Kang Ing, 2005. "Accumulated Prediction Errors, Information Criteria And Optimal Forecasting For Autoregressive Time Series," Econometrics 0503020, University Library of Munich, Germany.

Articles

  1. Ngai Hang Chan & Ching-Kang Ing & Yuanbo Li & Chun Yip Yau, 2017. "Threshold Estimation via Group Orthogonal Greedy Algorithm," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 334-345, April.
  2. Cheng, Tzu-Chang F. & Ing, Ching-Kang & Yu, Shu-Hui, 2015. "Toward optimal model averaging in regression models with time series errors," Journal of Econometrics, Elsevier, vol. 189(2), pages 321-334.
  3. Ching-Kang Ing & Chiao-Yi Yang, 2014. "Predictor Selection for Positive Autoregressive Processes," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 243-253, March.
  4. Ing, Ching-Kang & Sin, Chor-yiu & Yu, Shu-Hui, 2012. "Model selection for integrated autoregressive processes of infinite order," Journal of Multivariate Analysis, Elsevier, vol. 106(C), pages 57-71.
  5. Ing, Ching-Kang & Sin, Chor-yiu & Yu, Shu-Hui, 2010. "Prediction Errors In Nonstationary Autoregressions Of Infinite Order," Econometric Theory, Cambridge University Press, vol. 26(3), pages 774-803, June.
  6. Ing, Ching-Kang & Wei, Ching-Zong, 2003. "On same-realization prediction in an infinite-order autoregressive process," Journal of Multivariate Analysis, Elsevier, vol. 85(1), pages 130-155, April.
  7. Ching‐Kang Ing & Shu‐Hui Yu, 2003. "On Estimating Conditional Mean‐Squared Prediction Error in Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(4), pages 401-422, July.
  8. Ing, Ching-Kang, 2003. "Multistep Prediction In Autoregressive Processes," Econometric Theory, Cambridge University Press, vol. 19(2), pages 254-279, April.

Citations

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

Working papers

  1. HONDA, Toshio & 本田, 敏雄 & ING, Ching-Kang & WU, Wei-Ying, 2017. "Adaptively weighted group Lasso for semiparametric quantile regression models," Discussion Papers 2017-04, Graduate School of Economics, Hitotsubashi University.

    Cited by:

    1. Honda, Toshio & 本田, 敏雄 & Lin, Chien-Tong, 2022. "Forward variable selection for ultra-high dimensional quantile regression models," Discussion Papers 2021-02, Graduate School of Economics, Hitotsubashi University.

  2. Ching-Kang Ing, 2005. "Accumulated Prediction Errors, Information Criteria And Optimal Forecasting For Autoregressive Time Series," Econometrics 0503020, University Library of Munich, Germany.

    Cited by:

    1. Hansen, Bruce E., 2008. "Least-squares forecast averaging," Journal of Econometrics, Elsevier, vol. 146(2), pages 342-350, October.

Articles

  1. Ngai Hang Chan & Ching-Kang Ing & Yuanbo Li & Chun Yip Yau, 2017. "Threshold Estimation via Group Orthogonal Greedy Algorithm," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 334-345, April.

    Cited by:

    1. Chih‐Hao Chang & Kam‐Fai Wong & Wei‐Yee Lim, 2023. "Threshold estimation for continuous three‐phase polynomial regression models with constant mean in the middle regime," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 77(1), pages 4-47, February.
    2. Muhammad Jaffri Mohd Nasir & Ramzan Nazim Khan & Gopalan Nair & Darfiana Nur, 2024. "Active-set based block coordinate descent algorithm in group LASSO for self-exciting threshold autoregressive model," Statistical Papers, Springer, vol. 65(5), pages 2973-3006, July.

  2. Cheng, Tzu-Chang F. & Ing, Ching-Kang & Yu, Shu-Hui, 2015. "Toward optimal model averaging in regression models with time series errors," Journal of Econometrics, Elsevier, vol. 189(2), pages 321-334.

    Cited by:

    1. Yicong Lin & Hanno Reuvers, 2019. "Efficient Estimation by Fully Modified GLS with an Application to the Environmental Kuznets Curve," Papers 1908.02552, arXiv.org, revised Aug 2020.
    2. Shiqing Ling & Michael McAleer & Howell Tong, 2015. "Frontiers in Time Series and Financial Econometrics: An Overview," Documentos de Trabajo del ICAE 2015-04, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    3. Michael Schomaker & Christian Heumann, 2020. "When and when not to use optimal model averaging," Statistical Papers, Springer, vol. 61(5), pages 2221-2240, October.
    4. Liao, Jun & Wan, Alan T.K. & He, Shuyuan & Zou, Guohua, 2022. "Optimal model averaging for multivariate regression models," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    5. Yan Gao & Xinyu Zhang & Shouyang Wang & Terence Tai-leung Chong & Guohua Zou, 2019. "Frequentist model averaging for threshold models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(2), pages 275-306, April.
    6. Wei Qian & Craig A. Rolling & Gang Cheng & Yuhong Yang, 2019. "On the Forecast Combination Puzzle," Econometrics, MDPI, vol. 7(3), pages 1-26, September.
    7. Rongjie Jiang & Liming Wang & Yang Bai, 2021. "Optimal model averaging estimator for semi-functional partially linear models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(2), pages 167-194, February.
    8. Chu-An Liu & Biing-Shen Kuo & Wen-Jen Tsay, 2017. "Autoregressive Spectral Averaging Estimator," IEAS Working Paper : academic research 17-A013, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    9. Liao, Jun & Zou, Guohua & Gao, Yan & Zhang, Xinyu, 2021. "Model averaging prediction for time series models with a diverging number of parameters," Journal of Econometrics, Elsevier, vol. 223(1), pages 190-221.
    10. Liao, Jun & Zong, Xianpeng & Zhang, Xinyu & Zou, Guohua, 2019. "Model averaging based on leave-subject-out cross-validation for vector autoregressions," Journal of Econometrics, Elsevier, vol. 209(1), pages 35-60.
    11. Muriel Fadairo & Cintya Lanchimba & Josef Windsperger, 2018. "Entrepreneurial orientation, risk and incentives: the case of franchising," Post-Print halshs-01611633, HAL.
    12. Peng, Jingfu & Yang, Yuhong, 2022. "On improvability of model selection by model averaging," Journal of Econometrics, Elsevier, vol. 229(2), pages 246-262.
    13. Verdejo, Humberto & Awerkin, Almendra & Becker, Cristhian & Olguin, Gabriel, 2017. "Statistic linear parametric techniques for residential electric energy demand forecasting. A review and an implementation to Chile," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 512-521.
    14. Zhang, Xiaomeng & Zhang, Xinyu, 2023. "Optimal model averaging based on forward-validation," Journal of Econometrics, Elsevier, vol. 237(2).
    15. Ling, S. & McAleer, M.J. & Tong, H., 2015. "Frontiers in Time Series and Financial Econometrics," Econometric Institute Research Papers EI 2015-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. Chor-yiu Sin & Shu-Hui Yu, 2019. "Order selection for possibly infinite-order non-stationary time series," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(2), pages 187-216, June.

  3. Ing, Ching-Kang & Sin, Chor-yiu & Yu, Shu-Hui, 2012. "Model selection for integrated autoregressive processes of infinite order," Journal of Multivariate Analysis, Elsevier, vol. 106(C), pages 57-71.

    Cited by:

    1. Gang Cheng & Sicong Wang & Yuhong Yang, 2015. "Forecast Combination under Heavy-Tailed Errors," Econometrics, MDPI, vol. 3(4), pages 1-28, November.
    2. Liao, Jun & Zou, Guohua & Gao, Yan & Zhang, Xinyu, 2021. "Model averaging prediction for time series models with a diverging number of parameters," Journal of Econometrics, Elsevier, vol. 223(1), pages 190-221.
    3. Costantini, Mauro & Kunst, Robert M., 2021. "On using predictive-ability tests in the selection of time-series prediction models: A Monte Carlo evaluation," International Journal of Forecasting, Elsevier, vol. 37(2), pages 445-460.
    4. William Kengne, 2023. "On consistency for time series model selection," Statistical Inference for Stochastic Processes, Springer, vol. 26(2), pages 437-458, July.
    5. Chor-yiu Sin & Shu-Hui Yu, 2019. "Order selection for possibly infinite-order non-stationary time series," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(2), pages 187-216, June.

  4. Ing, Ching-Kang & Sin, Chor-yiu & Yu, Shu-Hui, 2010. "Prediction Errors In Nonstationary Autoregressions Of Infinite Order," Econometric Theory, Cambridge University Press, vol. 26(3), pages 774-803, June.

    Cited by:

    1. Yi-Ting Chen & Chu-An Liu, 2021. "Model Averaging for Asymptotically Optimal Combined Forecasts," IEAS Working Paper : academic research 21-A002, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    2. Chor-yiu Sin & Shu-Hui Yu, 2019. "Order selection for possibly infinite-order non-stationary time series," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(2), pages 187-216, June.
    3. Ing, Ching-Kang & Sin, Chor-yiu & Yu, Shu-Hui, 2012. "Model selection for integrated autoregressive processes of infinite order," Journal of Multivariate Analysis, Elsevier, vol. 106(C), pages 57-71.

  5. Ing, Ching-Kang & Wei, Ching-Zong, 2003. "On same-realization prediction in an infinite-order autoregressive process," Journal of Multivariate Analysis, Elsevier, vol. 85(1), pages 130-155, April.

    Cited by:

    1. Hansen, Bruce E., 2010. "Averaging estimators for autoregressions with a near unit root," Journal of Econometrics, Elsevier, vol. 158(1), pages 142-155, September.
    2. Liu, Chu-An & Tao, Jing, 2016. "Model selection and model averaging in nonparametric instrumental variables models," MPRA Paper 69492, University Library of Munich, Germany.
    3. Luisa Bisaglia & Matteo Grigoletto, 2021. "A new time-varying model for forecasting long-memory series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 139-155, March.
    4. Hwang, Eunju & Shin, Dong Wan, 2014. "Infinite-order, long-memory heterogeneous autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 339-358.
    5. Yongmiao Hong & Tae-Hwy Lee & Yuying Sun & Shouyang Wang & Xinyu Zhang, 2017. "Time-varying Model Averaging," Working Papers 202001, University of California at Riverside, Department of Economics.
    6. Massimo Guidolin & Manuela Pedio, 2020. "Distilling Large Information Sets to Forecast Commodity Returns: Automatic Variable Selection or HiddenMarkov Models?," BAFFI CAREFIN Working Papers 20140, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    7. Jirak, Moritz, 2014. "Simultaneous confidence bands for sequential autoregressive fitting," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 130-149.
    8. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Selecting a Model for Forecasting," Econometrics, MDPI, vol. 9(3), pages 1-35, June.
    9. Greenaway-McGrevy, Ryan, 2015. "Evaluating panel data forecasts under independent realization," Journal of Multivariate Analysis, Elsevier, vol. 136(C), pages 108-125.
    10. Zhang, Xinyu & Wan, Alan T.K. & Zou, Guohua, 2013. "Model averaging by jackknife criterion in models with dependent data," Journal of Econometrics, Elsevier, vol. 174(2), pages 82-94.
    11. Cheng, Tzu-Chang F. & Ing, Ching-Kang & Yu, Shu-Hui, 2015. "Toward optimal model averaging in regression models with time series errors," Journal of Econometrics, Elsevier, vol. 189(2), pages 321-334.
    12. Kare Kamila, 2023. "Data-driven model selection for same-realization predictions in autoregressive processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(4), pages 567-592, August.
    13. Hansen, Bruce E., 2008. "Least-squares forecast averaging," Journal of Econometrics, Elsevier, vol. 146(2), pages 342-350, October.
    14. Chu-An Liu & Biing-Shen Kuo & Wen-Jen Tsay, 2017. "Autoregressive Spectral Averaging Estimator," IEAS Working Paper : academic research 17-A013, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    15. Liao, Jun & Zou, Guohua & Gao, Yan & Zhang, Xinyu, 2021. "Model averaging prediction for time series models with a diverging number of parameters," Journal of Econometrics, Elsevier, vol. 223(1), pages 190-221.
    16. Moiseev, Nikita & Volodin, Andrei, 2019. "Increasing the accuracy of macroeconomic time series forecast by incorporating functional and correlational dependencies between them," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 53, pages 119-137.
    17. Ng, Serena, 2013. "Variable Selection in Predictive Regressions," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 752-789, Elsevier.
    18. Schorfheide, Frank, 2005. "VAR forecasting under misspecification," Journal of Econometrics, Elsevier, vol. 128(1), pages 99-136, September.
    19. Greenaway-McGrevy, Ryan, 2022. "Forecast combination for VARs in large N and T panels," International Journal of Forecasting, Elsevier, vol. 38(1), pages 142-164.
    20. Ing, Ching-Kang & Sin, Chor-yiu & Yu, Shu-Hui, 2012. "Model selection for integrated autoregressive processes of infinite order," Journal of Multivariate Analysis, Elsevier, vol. 106(C), pages 57-71.

  6. Ching‐Kang Ing & Shu‐Hui Yu, 2003. "On Estimating Conditional Mean‐Squared Prediction Error in Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(4), pages 401-422, July.

    Cited by:

    1. Ng, Serena, 2013. "Variable Selection in Predictive Regressions," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 752-789, Elsevier.

  7. Ing, Ching-Kang, 2003. "Multistep Prediction In Autoregressive Processes," Econometric Theory, Cambridge University Press, vol. 19(2), pages 254-279, April.

    Cited by:

    1. Fearghal Kearney & Han Lin Shang & Lisa Sheenan, 2019. "Implied volatility surface predictability: the case of commodity markets," Papers 1909.11009, arXiv.org.
    2. Stock, James & Watson, Mark & Marcellino, Massimiliano, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," CEPR Discussion Papers 4976, C.E.P.R. Discussion Papers.
    3. Hansen, Bruce E., 2010. "Averaging estimators for autoregressions with a near unit root," Journal of Econometrics, Elsevier, vol. 158(1), pages 142-155, September.
    4. Pincheira, Pablo M. & West, Kenneth D., 2016. "A comparison of some out-of-sample tests of predictability in iterated multi-step-ahead forecasts," Research in Economics, Elsevier, vol. 70(2), pages 304-319.
    5. Rebecca Stuart, 2020. "Monetary regimes, the term structure and business cycles in Ireland, 1972–2018," Manchester School, University of Manchester, vol. 88(5), pages 731-748, September.
    6. Alfred A. Haug & Christie Smith, 2007. "Local linear impulse responses for a small open economy," Working Papers 0707, University of Otago, Department of Economics, revised Apr 2007.
    7. Clark, Todd E. & West, Kenneth D., 2006. "Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 155-186.
    8. M. Hashem Pesaran & Andreas Pick & Allan Timmermann, 2009. "Variable Selection and Inference for Multi-period Forecasting Problems," CESifo Working Paper Series 2543, CESifo.
    9. Òscar Jordà, 2005. "Estimation and Inference of Impulse Responses by Local Projections," American Economic Review, American Economic Association, vol. 95(1), pages 161-182, March.
    10. Patricia Toledo & Roberto Duncan, 2024. "Forecasting food price inflation during global crises," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 1087-1113, July.
    11. Hännikäinen, Jari, 2014. "Multi-step forecasting in the presence of breaks," MPRA Paper 55816, University Library of Munich, Germany.
    12. Proietti, Tommaso, 2011. "Direct and iterated multistep AR methods for difference stationary processes," International Journal of Forecasting, Elsevier, vol. 27(2), pages 266-280, April.
    13. Hitesh Doshi & Kris Jacobs & Rui Liu, 2021. "Information in the Term Structure: A Forecasting Perspective," Management Science, INFORMS, vol. 67(8), pages 5255-5277, August.
    14. Kenneth D. West & Todd Clark, 2006. "Approximately Normal Tests for Equal Predictive Accuracy in Nested Models," NBER Technical Working Papers 0326, National Bureau of Economic Research, Inc.
    15. Tommaso Proietti, 2016. "The Multistep Beveridge--Nelson Decomposition," Econometric Reviews, Taylor & Francis Journals, vol. 35(3), pages 373-395, March.
    16. Francis X. Diebold & Maximilian Gobel, 2022. "A Benchmark Model for Fixed-Target Arctic Sea Ice Forecasting," PIER Working Paper Archive 22-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    17. Alexander Chudik & Valerie Grossman & M. Hashem Pesaran, 2014. "A multi-country approach to forecasting output growth using PMIs," Globalization Institute Working Papers 213, Federal Reserve Bank of Dallas.
    18. Diebold, Francis X. & Göbel, Maximilian & Goulet Coulombe, Philippe, 2023. "Assessing and comparing fixed-target forecasts of Arctic sea ice: Glide charts for feature-engineered linear regression and machine learning models," Energy Economics, Elsevier, vol. 124(C).
    19. João Henrique Gonçalves Mazzeu & Esther Ruiz & Helena Veiga, 2018. "Uncertainty And Density Forecasts Of Arma Models: Comparison Of Asymptotic, Bayesian, And Bootstrap Procedures," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 388-419, April.
    20. David Hendry & Guillaume Chevillon, 2004. "Non-Parametric Direct Multi-step Estimation for Forecasting Economic Processes," Economics Series Working Papers 196, University of Oxford, Department of Economics.
    21. Guillaume Chevillon, 2007. "Direct Multi‐Step Estimation And Forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 746-785, September.
    22. Greenaway-McGrevy, Ryan, 2015. "Evaluating panel data forecasts under independent realization," Journal of Multivariate Analysis, Elsevier, vol. 136(C), pages 108-125.
    23. Ching-Kang Ing, 2005. "Accumulated Prediction Errors, Information Criteria And Optimal Forecasting For Autoregressive Time Series," Econometrics 0503020, University Library of Munich, Germany.
    24. Pesaran, M. Hashem & Pick, Andreas & Timmermann, Allan, 2011. "Variable selection, estimation and inference for multi-period forecasting problems," Journal of Econometrics, Elsevier, vol. 164(1), pages 173-187, September.
    25. Hansen, Bruce E., 2006. "Interval forecasts and parameter uncertainty," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 377-398.
    26. Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe, 2022. "Assessing and Comparing Fixed-Target Forecasts of Arctic Sea Ice: Glide Charts for Feature-Engineered Linear Regression and Machine Learning Models," Working Papers 22-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    27. Dées, Stéphane & Burgert, Matthias, 2008. "Forecasting world trade: direct versus "bottom-up" approaches," Working Paper Series 882, European Central Bank.
    28. Hansen, Bruce E., 2008. "Least-squares forecast averaging," Journal of Econometrics, Elsevier, vol. 146(2), pages 342-350, October.
    29. Eliana González Molano & Luis Fernando Melo Velnadia & Anderson Grajales Olarte, 2007. "Pronósticos directos de la inflación colombiana," Borradores de Economia 4246, Banco de la Republica.
    30. Todd E. Clark & Kenneth D. West, 2005. "Using Out-of-Sample Mean Squared Prediction Errors to Test the Martingale Difference," NBER Technical Working Papers 0305, National Bureau of Economic Research, Inc.
    31. Moiseev, Nikita & Volodin, Andrei, 2019. "Increasing the accuracy of macroeconomic time series forecast by incorporating functional and correlational dependencies between them," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 53, pages 119-137.
    32. West, Kenneth D., 2006. "Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 3, pages 99-134, Elsevier.
    33. Kauppi, Heikki & Virtanen, Timo, 2021. "Boosting nonlinear predictability of macroeconomic time series," International Journal of Forecasting, Elsevier, vol. 37(1), pages 151-170.
    34. Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe, 2022. "Assessing and Comparing Fixed-Target Forecasts of Arctic Sea Ice:Glide Charts for Feature-Engineered Linear Regression and Machine Learning Models," PIER Working Paper Archive 22-028, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    35. Nicholas Apergis & Panagiotis G. Artikis, 2016. "Foreign Exchange Risk, Equity Risk Factors and Economic Growth," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 44(4), pages 425-445, December.
    36. Ching-Kang Ing & Chiao-Yi Yang, 2014. "Predictor Selection for Positive Autoregressive Processes," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 243-253, March.
    37. Thomas Flavin & Ekaterini Panopoulou & Theologos Pantelidis, 2009. "Forecasting growth and inflation in an enlarged euro area," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(5), pages 405-425.
    38. Euler Pereira G. de Mello & Francisco Marcos R. Figueiredo, 2014. "Assessing the Short-term Forecasting Power of Confidence Indices," Working Papers Series 371, Central Bank of Brazil, Research Department.
    39. Chevillon, Guillaume, 2016. "Multistep forecasting in the presence of location shifts," International Journal of Forecasting, Elsevier, vol. 32(1), pages 121-137.
    40. Chevillon, Guillaume, 2017. "Robustness of Multistep Forecasts and Predictive Regressions at Intermediate and Long Horizons," ESSEC Working Papers WP1710, ESSEC Research Center, ESSEC Business School.
    41. Wu, Jyh-Lin & Lee, Chingnun & Wang, Tzu-Wei, 2011. "A re-examination on dissecting the purchasing power parity puzzle," Journal of International Money and Finance, Elsevier, vol. 30(3), pages 572-586, April.
    42. Chevillon, Guillaume, 2009. "Multi-step forecasting in emerging economies: An investigation of the South African GDP," International Journal of Forecasting, Elsevier, vol. 25(3), pages 602-628, July.
    43. Elena Ivona Dumitrescu & Peter Hansen, 2020. "How Should Parameter Estimation Be Tailored to the Objective?," Post-Print hal-03331109, HAL.
    44. Schorfheide, Frank, 2005. "VAR forecasting under misspecification," Journal of Econometrics, Elsevier, vol. 128(1), pages 99-136, September.
    45. White, Halbert, 2006. "Time-series estimation of the effects of natural experiments," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 527-566.
    46. Roberto Duncan & Enrique Martínez‐García, 2023. "Forecasting inflation in open economies: What can a NOEM model do?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 481-513, April.
    47. Ing, Ching-Kang & Wei, Ching-Zong, 2003. "On same-realization prediction in an infinite-order autoregressive process," Journal of Multivariate Analysis, Elsevier, vol. 85(1), pages 130-155, April.
    48. John Haywood & Granville Tunnicliffe Wilson, 2009. "A test for improved multi‐step forecasting," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(6), pages 682-707, November.

More information

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Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (3) 2005-04-16 2005-11-09 2017-04-16
  2. NEP-ETS: Econometric Time Series (2) 2005-04-16 2005-11-09

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