IDEAS home Printed from https://ideas.repec.org/e/pis25.html
   My authors  Follow this author

Gultekin Isiklar

Personal Details

First Name:Gultekin
Middle Name:
Last Name:Isiklar
Suffix:
RePEc Short-ID:pis25
http://www.albany.edu/~gi7989
Terminal Degree:2005 Department of Economics; State University of New York-Albany (SUNY) (from RePEc Genealogy)

Affiliation

Department of Economics
State University of New York-Albany (SUNY)

Albany, New York (United States)
http://www.albany.edu/econ/
RePEc:edi:dealbus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Kajal Lahiri & Gultekin Isiklar, 2010. "Estimating International Transmission of Shocks Using GDP Forecasts: India and Its Trading Partners," Discussion Papers 10-06, University at Albany, SUNY, Department of Economics.
  2. Isiklar, Gultekin & Lahiri, Kajal & Loungani, Prakash, 2006. "How quickly do forecasters incorporate news? Evidence from cross-country surveys," MPRA Paper 22065, University Library of Munich, Germany.
  3. Kajal Lahiri & Gultekin Isiklar, 2006. "How Far Ahead Can We Forecast? Evidence From Cross-country Surveys," Discussion Papers 06-04, University at Albany, SUNY, Department of Economics.
  4. Gultekin Isiklar, 2005. "Structural VAR identification in asset markets using short-run market inefficiencies," Econometrics 0501001, University Library of Munich, Germany, revised 02 Jan 2005.
  5. Gultekin Isiklar, 2004. "On aggregation bias in fixed-event forecast efficiency tests," Econometrics 0412011, University Library of Munich, Germany, revised 28 Dec 2004.

Articles

  1. Ilker Domac & Gultekin Isiklar & Magda Kandil, 2019. "On the potential and Limitations of monetary policy in Turkey," Middle East Development Journal, Taylor & Francis Journals, vol. 11(2), pages 231-249, July.
  2. Isiklar, Gultekin & Lahiri, Kajal, 2007. "How far ahead can we forecast? Evidence from cross-country surveys," International Journal of Forecasting, Elsevier, vol. 23(2), pages 167-187.
  3. Kajal Lahiri & Gultekin Isiklar & Prakash Loungani, 2006. "How quickly do forecasters incorporate news? Evidence from cross-country surveys," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 703-725.
  4. Isiklar, Gultekin, 2005. "On aggregation bias in fixed-event forecast efficiency tests," Economics Letters, Elsevier, vol. 89(3), pages 312-316, December.

Citations

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

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Kajal Lahiri & Gultekin Isiklar & Prakash Loungani, 2006. "How quickly do forecasters incorporate news? Evidence from cross-country surveys," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 703-725.

    Mentioned in:

    1. How quickly do forecasters incorporate news? Evidence from cross-country surveys (Journal of Applied Econometrics 2006) in ReplicationWiki ()

Working papers

  1. Kajal Lahiri & Gultekin Isiklar, 2010. "Estimating International Transmission of Shocks Using GDP Forecasts: India and Its Trading Partners," Discussion Papers 10-06, University at Albany, SUNY, Department of Economics.

    Cited by:

    1. Ullrich Heilemann & Karsten Müller, 2018. "Wenig Unterschiede – Zur Treffsicherheit Internationaler Prognosen und Prognostiker [Few differences—on the accuracy of international forecasts and forecaster]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 12(3), pages 195-233, December.
    2. Lahiri, Kajal & Zhao, Yongchen, 2019. "International propagation of shocks: A dynamic factor model using survey forecasts," International Journal of Forecasting, Elsevier, vol. 35(3), pages 929-947.
    3. Steffen Henzel & Elisabeth Wieland, 2013. "Synchronization and Changes in International Inflation Uncertainty," CESifo Working Paper Series 4194, CESifo.

  2. Isiklar, Gultekin & Lahiri, Kajal & Loungani, Prakash, 2006. "How quickly do forecasters incorporate news? Evidence from cross-country surveys," MPRA Paper 22065, University Library of Munich, Germany.

    Cited by:

    1. Wright, Jonathan H., 2019. "Some observations on forecasting and policy," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1186-1192.
    2. Capistrán, Carlos & López-Moctezuma, Gabriel, 2014. "Forecast revisions of Mexican inflation and GDP growth," International Journal of Forecasting, Elsevier, vol. 30(2), pages 177-191.
    3. Chia-Lin Chang & Bert de Bruijn & Philip Hans Franses & Michael McAleer, 2013. "Analyzing Fixed-event Forecast Revisions," Documentos de Trabajo del ICAE 2013-14, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Apr 2013.
    4. Stekler, H.O., 2007. "The future of macroeconomic forecasting: Understanding the forecasting process," International Journal of Forecasting, Elsevier, vol. 23(2), pages 237-248.
    5. Kajal Lahiri & Gultekin Isiklar, 2010. "Estimating International Transmission of Shocks Using GDP Forecasts: India and Its Trading Partners," Discussion Papers 10-06, University at Albany, SUNY, Department of Economics.
    6. Isiklar, Gultekin & Lahiri, Kajal, 2007. "How far ahead can we forecast? Evidence from cross-country surveys," International Journal of Forecasting, Elsevier, vol. 23(2), pages 167-187.
    7. Jos Jansen & Jasper de Winter, 2016. "Improving model-based near-term GDP forecasts by subjective forecasts: A real-time exercise for the G7 countries," DNB Working Papers 507, Netherlands Central Bank, Research Department.
    8. Yu-chin Chen & Kwok Ping Tsang & Wen Jen Tsay, 2010. "Home Bias in Currency Forecasts," Working Papers 272010, Hong Kong Institute for Monetary Research.
    9. Sinclair, Tara M., 2019. "Characteristics and implications of Chinese macroeconomic data revisions," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1108-1117.
    10. Jonas Dovern & Ulrich Fritsche & Prakash Loungani & Natalia Tamirisa, 2014. "Information Rigidities: Comparing Average And Individual Forecasts For A Large International Panel," Working Papers 2014-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    11. Simionescu, Mihaela, 2014. "New Strategies to Improve the Accuracy of Predictions based on Monte Carlo and Bootstrap Simulations: An Application to Bulgarian and Romanian Inflation || Nuevas estrategias para mejorar la exactitud," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 18(1), pages 112-129, December.
    12. Andrew J. Patton & Allan Timmermann, 2008. "The Resolution of Macroeconomic Uncertainty: Evidence from Survey Forecast," CREATES Research Papers 2008-54, Department of Economics and Business Economics, Aarhus University.
    13. Natsuki Arai, 2016. "Evaluating the Efficiency of the FOMC's New Economic Projections," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(5), pages 1019-1049, August.
    14. Fotis Mouzakis & Dimitrios Papastamos & Simon Stevenson, 2015. "Rationality and Momentum in Real Estate Investment Forecasts," ERES eres2015_297, European Real Estate Society (ERES).
    15. Chen, Qiwei & Costantini, Mauro & Deschamps, Bruno, 2016. "How accurate are professional forecasts in Asia? Evidence from ten countries," International Journal of Forecasting, Elsevier, vol. 32(1), pages 154-167.
    16. António Afonso & João Tovar Jalles & Mina Kazemi, 2019. "The effects of macroeconomic, fiscal and monetary policy announcements on sovereign bond spreads: an event study from the EMU," EconPol Working Paper 22, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    17. Mihaela Simionescu, 2015. "A New Technique based on Simulations for Improving the Inflation Rate Forecasts in Romania," Working Papers of Institute for Economic Forecasting 150206, Institute for Economic Forecasting.
    18. Lahiri, Kajal & Sheng, Xuguang, 2010. "Learning and heterogeneity in GDP and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 26(2), pages 265-292, April.
    19. Trabelsi, Emna, 2016. "Central bank transparency and the consensus forecast: What does The Economist poll of forecasters tell us?," Research in International Business and Finance, Elsevier, vol. 38(C), pages 338-359.
    20. Joao Tovar Jalles, 2015. "How Quickly is News Incorporated in Fiscal Forecasts?," Economics Bulletin, AccessEcon, vol. 35(4), pages 2802-2812.
    21. Franses, Ph.H.B.F. & Welz, M., 2020. "Does More Expert Adjustment Associate with Less Accurate Professional Forecasts?," Econometric Institute Research Papers EI-1687, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    22. Iregui, Ana María & Núñez, Héctor M. & Otero, Jesús, 2021. "Testing the efficiency of inflation and exchange rate forecast revisions in a changing economic environment," Journal of Economic Behavior & Organization, Elsevier, vol. 187(C), pages 290-314.
    23. Thomas Jobert & Lionel Persyn, 2012. "Quelques constats sur les prévisions conjoncturelles de la croissance française," Revue d'économie politique, Dalloz, vol. 122(6), pages 833-849.
    24. Bruno Deschamps & Christos Ioannidis, 2014. "The Efficiency of Multivariate Macroeconomic Forecasts," Manchester School, University of Manchester, vol. 82(5), pages 509-523, September.
    25. Papastamos, Dimitrios & Matysiak, George & Stevenson, Simon, 2015. "Assessing the accuracy and dispersion of real estate investment forecasts," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 141-152.
    26. Reslow, André, 2019. "Inefficient Use of Competitors’ Forecasts?," Working Paper Series 2019:9, Uppsala University, Department of Economics.
    27. Sun, Yuying & Wang, Shouyang & Zhang, Xun, 2018. "How efficient are China's macroeconomic forecasts? Evidences from a new forecasting evaluation approach," Economic Modelling, Elsevier, vol. 68(C), pages 506-513.
    28. Andrew J. Patton & Allan Timmermann, 2011. "Forecast Rationality Tests Based on Multi-Horizon Bounds," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 1-17, June.
    29. Jalles, João Tovar, 2017. "On the rationality and efficiency of inflation forecasts: Evidence from advanced and emerging market economies," Research in International Business and Finance, Elsevier, vol. 40(C), pages 175-189.
    30. Nibbering, Didier & Paap, Richard & van der Wel, Michel, 2018. "What do professional forecasters actually predict?," International Journal of Forecasting, Elsevier, vol. 34(2), pages 288-311.
    31. Sebastiano Manzan, 2011. "Differential Interpretation in the Survey of Professional Forecasters," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(5), pages 993-1017, August.
    32. Ager, P. & Kappler, M. & Osterloh, S., 2009. "The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach," International Journal of Forecasting, Elsevier, vol. 25(1), pages 167-181.
    33. Jos Jansen, W. & Jin, Xiaowen & Winter, Jasper M. de, 2016. "Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts," Munich Reprints in Economics 43488, University of Munich, Department of Economics.
    34. Maritta Paloviita and Matti Viren, 2012. "Analyzing the relationships between survey forecasts for different variables and countries," Discussion Papers 76, Aboa Centre for Economics.
    35. Heilemann Ullrich & Schnorr-Bäcker Susanne, 2017. "Could the start of the German recession 2008–2009 have been foreseen? Evidence from Real-Time Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(1), pages 29-62, February.
    36. Mr. David Hauner & Ms. Kornelia Krajnyak & Mr. Martin Mühleisen & Mr. Bennett W Sutton & Mr. Stephan Danninger, 2005. "How Do Canadian Budget Forecasts Compare with Those of Other Industrial Countries?," IMF Working Papers 2005/066, International Monetary Fund.
    37. Lahiri, Kajal & Zhao, Yongchen, 2019. "International propagation of shocks: A dynamic factor model using survey forecasts," International Journal of Forecasting, Elsevier, vol. 35(3), pages 929-947.
    38. Jonas Dovern & Ulrich Fritsche & Jiri Slacalek, 2012. "Disagreement Among Forecasters in G7 Countries," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1081-1096, November.
    39. Jan-Egbert Sturm & Timo Wollmershäuser, 2008. "The Stress of Having a Single Monetary Policy in Europe," KOF Working papers 08-190, KOF Swiss Economic Institute, ETH Zurich.
    40. Franses, Ph.H.B.F., 2019. "Professional Forecasters and January," Econometric Institute Research Papers EI2019-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    41. Cepparulo, Alessandra & Gastaldi, Francesca & Giuriato, Luisa & Sacchi, Agnese, 2011. "Budgeting versus implementing fiscal policy:the Italian case," MPRA Paper 32474, University Library of Munich, Germany.
    42. Ulrich Heilemann & Susanne Schnorr-Bäcker, 2016. "Could The Start Of The German Recession 2008-2009 Have Been Foreseen? Evidence From Real-Time Data," Working Papers 2016-003, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    43. Loungani, Prakash & Stekler, Herman & Tamirisa, Natalia, 2013. "Information rigidity in growth forecasts: Some cross-country evidence," International Journal of Forecasting, Elsevier, vol. 29(4), pages 605-621.
    44. Klaus-Peter Hellwig, 2018. "Overfitting in Judgment-based Economic Forecasts: The Case of IMF Growth Projections," IMF Working Papers 2018/260, International Monetary Fund.
    45. Döhrn Roland & Schmidt Christoph M., 2011. "Information or Institution?: On the Determinants of Forecast Accuracy," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 9-27, February.
    46. Jonas Dovern & Johannes Weisser, 2009. "Accuracy, Unbiasedness and Efficiency of Professional Macroeconomic Forecasts: An empirical Comparison for the G7," Jena Economic Research Papers 2009-091, Friedrich-Schiller-University Jena.
    47. Alfredo Pistelli M., 2012. "Análisis de Sesgos y Eficiencia en Proyecciones de Consensus Forecasts," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 15(1), pages 98-104, April.
    48. Sheng, Xuguang (Simon), 2015. "Evaluating the economic forecasts of FOMC members," International Journal of Forecasting, Elsevier, vol. 31(1), pages 165-175.
    49. Bruno Deschamps & Christos Ioannidis & Kook Ka, 2019. "High-Frequency Credit Spread Information and Macroeconomic Forecast Revision," Working Papers 2019-17, Economic Research Institute, Bank of Korea.
    50. Peter Tillmann, 2011. "Reputation and Forecast Revisions: Evidence from the FOMC," MAGKS Papers on Economics 201128, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    51. Philip Hans Franses, 2020. "Correcting the January optimism effect," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 927-933, September.
    52. Deschamps, Bruno & Ioannidis, Christos & Ka, Kook, 2020. "High-frequency credit spread information and macroeconomic forecast revision," International Journal of Forecasting, Elsevier, vol. 36(2), pages 358-372.
    53. Frenkel, Michael & Rülke, Jan-Christoph & Zimmermann, Lilli, 2013. "Do private sector forecasters chase after IMF or OECD forecasts?," Journal of Macroeconomics, Elsevier, vol. 37(C), pages 217-229.
    54. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.
    55. Franses, Ph.H.B.F. & Maassen, N.R., 2015. "Consensus forecasters: How good are they individually and why?," Econometric Institute Research Papers EI2015-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  3. Kajal Lahiri & Gultekin Isiklar, 2006. "How Far Ahead Can We Forecast? Evidence From Cross-country Surveys," Discussion Papers 06-04, University at Albany, SUNY, Department of Economics.

    Cited by:

    1. Capistrán, Carlos & López-Moctezuma, Gabriel, 2014. "Forecast revisions of Mexican inflation and GDP growth," International Journal of Forecasting, Elsevier, vol. 30(2), pages 177-191.
    2. Batchelor, Roy, 2007. "Bias in macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 23(2), pages 189-203.
    3. Kajal Lahiri & Gultekin Isiklar, 2010. "Estimating International Transmission of Shocks Using GDP Forecasts: India and Its Trading Partners," Discussion Papers 10-06, University at Albany, SUNY, Department of Economics.
    4. Breitung, Jörg & Knüppel, Malte, 2018. "How far can we forecast? Statistical tests of the predictive content," Discussion Papers 07/2018, Deutsche Bundesbank.
    5. Mr. Ken Miyajima & James Yetman, 2018. "Inflation Expectations Anchoring Across Different Types of Agents: the Case of South Africa," IMF Working Papers 2018/177, International Monetary Fund.
    6. Carlos Diaz Vela, 2016. "Extracting the Information Shocks from the Bank of England Inflation Density Forecasts," Discussion Papers in Economics 16/13, Division of Economics, School of Business, University of Leicester.
    7. Sinclair, Tara M., 2019. "Characteristics and implications of Chinese macroeconomic data revisions," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1108-1117.
    8. Jonas Dovern & Ulrich Fritsche & Prakash Loungani & Natalia Tamirisa, 2014. "Information Rigidities: Comparing Average And Individual Forecasts For A Large International Panel," Working Papers 2014-001, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    9. António Brandão Moniz, 2008. "Assessing scenarios on the future of work," Enterprise and Work Innovation Studies, Universidade Nova de Lisboa, IET/CICS.NOVA-Interdisciplinary Centre on Social Sciences, Faculty of Science and Technology, vol. 4(4), pages 91-106, November.
    10. Garratt, Anthony & Lee, Kevin & Shields, Kalvinder, 2016. "Forecasting global recessions in a GVAR model of actual and expected output," International Journal of Forecasting, Elsevier, vol. 32(2), pages 374-390.
    11. Patton, Andrew J & Timmermann, Allan G, 2007. "Learning in Real Time: Theory and Empirical Evidence from the Term Structure of Survey Forecasts," CEPR Discussion Papers 6526, C.E.P.R. Discussion Papers.
    12. Heilemann, Ullrich & Stekler, Herman, 2007. "Introduction to "The future of macroeconomic forecasting"," International Journal of Forecasting, Elsevier, vol. 23(2), pages 159-165.
    13. Stefan Günnel & Karl-Heinz Tödter, 2009. "Does Benford’s Law hold in economic research and forecasting?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 36(3), pages 273-292, August.
    14. Chen, Qiwei & Costantini, Mauro & Deschamps, Bruno, 2016. "How accurate are professional forecasts in Asia? Evidence from ten countries," International Journal of Forecasting, Elsevier, vol. 32(1), pages 154-167.
    15. Lahiri, Kajal & Sheng, Xuguang, 2010. "Learning and heterogeneity in GDP and inflation forecasts," International Journal of Forecasting, Elsevier, vol. 26(2), pages 265-292, April.
    16. Abad, Jorge & Suarez, Javier, 2018. "The Procyclicality of Expected Credit Loss Provisions," CEPR Discussion Papers 13135, C.E.P.R. Discussion Papers.
    17. Roberts Bryan W, 2009. "The Macroeconomic Impacts of the 9/11 Attack: Evidence from Real-Time Forecasting," Peace Economics, Peace Science, and Public Policy, De Gruyter, vol. 15(2), pages 1-29, July.
    18. Lahiri, Kajal & Wang, J. George, 2013. "Evaluating probability forecasts for GDP declines using alternative methodologies," International Journal of Forecasting, Elsevier, vol. 29(1), pages 175-190.
    19. Goodwin, Thomas & Tian, Jing, 2017. "A state space approach to evaluate multi-horizon forecasts," Working Papers 2017-15, University of Tasmania, Tasmanian School of Business and Economics.
    20. Sun, Yuying & Wang, Shouyang & Zhang, Xun, 2018. "How efficient are China's macroeconomic forecasts? Evidences from a new forecasting evaluation approach," Economic Modelling, Elsevier, vol. 68(C), pages 506-513.
    21. Herman O. Stekler & Raj M. Talwar, 2011. "Economic Forecasting in the Great Recession," Working Papers 2011-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    22. Roy Batchelor, 2007. "Forecaster Behaviour and Bias in Macroeconomic Forecasts," ifo Working Paper Series 39, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    23. Galimberti, Jaqueson K. & Moura, Marcelo L., 2010. "Taylor Rules and Exchange Rate Predictability in Emerging Economies," Insper Working Papers wpe_214, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    24. Ager, P. & Kappler, M. & Osterloh, S., 2009. "The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach," International Journal of Forecasting, Elsevier, vol. 25(1), pages 167-181.
    25. Jones, Jacob T. & Sinclair, Tara M. & Stekler, Herman O., 2020. "A textual analysis of Bank of England growth forecasts," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1478-1487.
    26. Dovern, Jonas & Jannsen, Nils, 2017. "Systematic errors in growth expectations over the business cycle," International Journal of Forecasting, Elsevier, vol. 33(4), pages 760-769.
    27. Marc-Oliver Pohle, 2020. "The Murphy Decomposition and the Calibration-Resolution Principle: A New Perspective on Forecast Evaluation," Papers 2005.01835, arXiv.org.
    28. Anthony Garratt & Kevin Lee & Kalvinder Shields, 2014. "Forecasting Global Recessions in a GVAR Model of Actual and Expected Output in the G7," Discussion Papers 2014/06, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
    29. Ken Miyajima & James Yetman, 2019. "Assessing inflation expectations anchoring for heterogeneous agents: analysts, businesses and trade unions," Applied Economics, Taylor & Francis Journals, vol. 51(41), pages 4499-4515, September.
    30. Oller, Lars-Erik & Teterukovsky, Alex, 2007. "Quantifying the quality of macroeconomic variables," International Journal of Forecasting, Elsevier, vol. 23(2), pages 205-217.
    31. Kappler, Marcus, 2007. "Projecting the Medium-Term: Outcomes and Errors for GDP Growth," ZEW Discussion Papers 07-068, ZEW - Leibniz Centre for European Economic Research.
    32. Lahiri, Kajal & Zhao, Yongchen, 2019. "International propagation of shocks: A dynamic factor model using survey forecasts," International Journal of Forecasting, Elsevier, vol. 35(3), pages 929-947.
    33. Mehrotra, Aaron & Yetman, James, 2018. "Are inflation targets credible? A novel test," Economics Letters, Elsevier, vol. 167(C), pages 67-70.
    34. Tian, Jing & Goodwin, Thomas, 2018. "An unobserved component modeling approach to evaluate multi-horizon forecasts," Working Papers 2018-04, University of Tasmania, Tasmanian School of Business and Economics.
    35. Galimberti, Jaqueson K. & Moura, Marcelo L., 2016. "Improving the reliability of real-time output gap estimates using survey forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 358-373.
    36. Jörg Breitung & Malte Knüppel, 2021. "How far can we forecast? Statistical tests of the predictive content," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(4), pages 369-392, June.
    37. Mr. Ulrich Fritsche & Jonas Dovern & Mr. Prakash Loungani & Ms. Natalia T. Tamirisa, 2013. "Information Rigidities in Economic Growth Forecasts: Evidence from a Large International Panel," IMF Working Papers 2013/056, International Monetary Fund.
    38. Konstantin A. Kholodilin & Boriss Siliverstovs, 2009. "Do forecasters inform or reassure?," KOF Working papers 09-215, KOF Swiss Economic Institute, ETH Zurich.
    39. Döhrn Roland & Schmidt Christoph M., 2011. "Information or Institution?: On the Determinants of Forecast Accuracy," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 9-27, February.
    40. Kajal Lahiri, 2012. "Comment on "Forecast Rationality Tests Based on Multi-Horizon Bounds" by Andrew Patton and Allan Timmermann. Journal of Business and Economic Statistics, No. 1, Vol. 30, 2012, pp.1-17," Discussion Papers 12-10, University at Albany, SUNY, Department of Economics.
    41. Jaqueson K. Galimberti & Marcelo L. Moura, 2011. "Improving the reliability of real-time Hodrick-Prescott filtering using survey forecasts," Centre for Growth and Business Cycle Research Discussion Paper Series 159, Economics, The University of Manchester.
    42. Herman O. Stekler, 2008. "What Do We Know About G-7 Macro Forecasts?," Working Papers 2008-009, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    43. Alfredo Pistelli M., 2012. "Análisis de Sesgos y Eficiencia en Proyecciones de Consensus Forecasts," Notas de Investigación Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 15(1), pages 98-104, April.
    44. H.O. Stekler & Huixia Zhang, 2013. "An evaluation of Chinese economic forecasts," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 11(4), pages 251-259, November.
    45. Ullrich Heilemann & Herman Stekler, 2010. "Perspectives on Evaluating Macroeconomic Forecasts," Working Papers 2010-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    46. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.
    47. Franses, Ph.H.B.F. & Maassen, N.R., 2015. "Consensus forecasters: How good are they individually and why?," Econometric Institute Research Papers EI2015-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  4. Gultekin Isiklar, 2004. "On aggregation bias in fixed-event forecast efficiency tests," Econometrics 0412011, University Library of Munich, Germany, revised 28 Dec 2004.

    Cited by:

    1. Kajal Lahiri & Yongchen Zhao, 2020. "The Nordhaus Test with Many Zeros," Working Papers 2020-05, Towson University, Department of Economics, revised Jun 2020.
    2. Natsuki Arai, 2016. "Evaluating the Efficiency of the FOMC's New Economic Projections," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(5), pages 1019-1049, August.
    3. Ager, P. & Kappler, M. & Osterloh, S., 2009. "The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach," International Journal of Forecasting, Elsevier, vol. 25(1), pages 167-181.
    4. Bruno Deschamps, 2015. "Are aggregate corporate earnings forecasts unbiased and efficient?," Review of Quantitative Finance and Accounting, Springer, vol. 45(4), pages 803-818, November.

Articles

  1. Isiklar, Gultekin & Lahiri, Kajal, 2007. "How far ahead can we forecast? Evidence from cross-country surveys," International Journal of Forecasting, Elsevier, vol. 23(2), pages 167-187.
    See citations under working paper version above.
  2. Kajal Lahiri & Gultekin Isiklar & Prakash Loungani, 2006. "How quickly do forecasters incorporate news? Evidence from cross-country surveys," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 703-725.
    See citations under working paper version above.
  3. Isiklar, Gultekin, 2005. "On aggregation bias in fixed-event forecast efficiency tests," Economics Letters, Elsevier, vol. 89(3), pages 312-316, December.
    See citations under working paper version above.Sorry, no citations of articles recorded.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Featured entries

This author is featured on the following reading lists, publication compilations, Wikipedia, or ReplicationWiki entries:
  1. Turkish Economists

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 (2) 2005-01-02 2005-01-09
  2. NEP-CFN: Corporate Finance (1) 2005-01-09
  3. NEP-CWA: Central & Western Asia (1) 2010-06-18
  4. NEP-EEC: European Economics (1) 2005-01-09
  5. NEP-ETS: Econometric Time Series (1) 2005-01-09
  6. NEP-FMK: Financial Markets (1) 2005-01-09
  7. NEP-FOR: Forecasting (1) 2010-06-18
  8. NEP-MAC: Macroeconomics (1) 2010-06-18
  9. NEP-OPM: Open Economy Macroeconomics (1) 2010-06-18
  10. NEP-RMG: Risk Management (1) 2005-01-09
  11. NEP-SEA: South East Asia (1) 2010-06-18

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Gultekin Isiklar should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.