IDEAS home Printed from https://ideas.repec.org/p/cpr/ceprdp/10201.html
   My bibliography  Save this paper

Economic theory and forecasting: lessons from the literature

Author

Listed:
  • Giacomini, Raffaella

Abstract

Does economic theory help in forecasting key macroeconomic variables? This article aims to provide some insight into the question by drawing lessons from the literature. The definition of "economic theory" includes a broad range of examples, such as accounting identities, disaggregation and spatial restrictions when forecasting aggregate variables, cointegration and forecasting with Dynamic Stochastic General Equilibrium (DSGE) models. We group the lessons into three themes. The first discusses the importance of using the correct econometric tools when answering the question. The second presents examples of theory-based forecasting that have not proven useful, such as theory-driven variable selection and some popular DSGE models. The third set of lessons discusses types of theoretical restrictions that have shown some usefulness in forecasting, such as accounting identities, disaggregation and spatial restrictions, and cointegrating relationships. We conclude by suggesting that economic theory might help in overcoming the widespread instability that affects the forecasting performance of econometric models by guiding the search for stable relationships that could be usefully exploited for forecasting.

Suggested Citation

  • Giacomini, Raffaella, 2014. "Economic theory and forecasting: lessons from the literature," CEPR Discussion Papers 10201, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:10201
    as

    Download full text from publisher

    File URL: https://cepr.org/publications/DP10201
    Download Restriction: CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Carlo Altavilla & Raffaella Giacomini & Riccardo Costantini, 2014. "Bond Returns and Market Expectations," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 12(4), pages 708-729.
    2. Hendry, David & Hubrich, Kirstin, 2006. "Forecasting Economic Aggregates by Disaggregates," CEPR Discussion Papers 5485, C.E.P.R. Discussion Papers.
    3. Fabio Canova & Filippo Ferroni, 2011. "Multiple filtering devices for the estimation of cyclical DSGE models," Quantitative Economics, Econometric Society, vol. 2(1), pages 73-98, March.
    4. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
    5. Faust, Jon & Gupta, Abhishek, 2010. "Posterior Predictive Analysis for Evaluating DSGE Models," MPRA Paper 26721, University Library of Munich, Germany.
    6. Hashem M. Pesaran & Ron P. Smith, 2011. "Beyond the DSGE Straitjacket," CESifo Working Paper Series 3447, CESifo.
    7. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
    8. Raffaella Giacomini & Barbara Rossi, 2009. "Detecting and Predicting Forecast Breakdowns," Review of Economic Studies, Oxford University Press, vol. 76(2), pages 669-705.
    9. Robertson, John C & Tallman, Ellis W & Whiteman, Charles H, 2005. "Forecasting Using Relative Entropy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 383-401, June.
    10. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-1084, September.
    11. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    12. Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
    13. Pastor, Lubos & Stambaugh, Robert F., 2002. "Investing in equity mutual funds," Journal of Financial Economics, Elsevier, vol. 63(3), pages 351-380, March.
    14. Carriero, Andrea & Giacomini, Raffaella, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Journal of Econometrics, Elsevier, vol. 164(1), pages 21-34, September.
    15. Nikita Perevalov & Philipp Maier, 2010. "On the Advantages of Disaggregated Data: Insights from Forecasting the U.S. Economy in a Data-Rich Environment," Staff Working Papers 10-10, Bank of Canada.
    16. M. Hashem Pesaran & Ron P. Smith, 2011. "BEYOND THE DSGE STRAITJACKET-super-1," Manchester School, University of Manchester, vol. 79(s2), pages 5-16, September.
    17. Carlo Altavilla & Raffaella Giacomini & Giuseppe Ragusa, 2017. "Anchoring the yield curve using survey expectations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(6), pages 1055-1068, September.
    18. Raffaella Giacomini & Barbara Rossi, 2016. "Model Comparisons In Unstable Environments," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57(2), pages 369-392, May.
    19. Banegas, Ayelen & Gillen, Ben & Timmermann, Allan & Wermers, Russ, 2013. "The cross section of conditional mutual fund performance in European stock markets," Journal of Financial Economics, Elsevier, vol. 108(3), pages 699-726.
    20. Carson, Richard T. & Cenesizoglu, Tolga & Parker, Roger, 2011. "Forecasting (aggregate) demand for US commercial air travel," International Journal of Forecasting, Elsevier, vol. 27(3), pages 923-941, July.
    21. Clements, Michael P & Hendry, David F, 1995. "Forecasting in Cointegration Systems," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 127-146, April-Jun.
    22. Colin Bermingham & Antonello D’Agostino, 2014. "Understanding and forecasting aggregate and disaggregate price dynamics," Empirical Economics, Springer, vol. 46(2), pages 765-788, March.
    23. repec:hal:journl:peer-00844809 is not listed on IDEAS
    24. De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2006. "Forecasting using a large number of predictors: is Bayesian regression a valid alternative to principal components?," Discussion Paper Series 1: Economic Studies 2006,32, Deutsche Bundesbank.
    25. Schnatz, Bernd & D'Agostino, Antonello, 2012. "Survey-based nowcasting of US growth: a real-time forecast comparison over more than 40 years," Working Paper Series 1455, European Central Bank.
    26. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    27. Stock, James H. & Watson, Mark W., 2006. "Forecasting with Many Predictors," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 10, pages 515-554, Elsevier.
    28. Amisano, Gianni & Giacomini, Raffaella, 2007. "Comparing Density Forecasts via Weighted Likelihood Ratio Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 177-190, April.
    29. Bouakez, Hafedh & Cardia, Emanuela & Ruge-Murcia, Francisco, 2014. "Sectoral price rigidity and aggregate dynamics," European Economic Review, Elsevier, vol. 65(C), pages 1-22.
    30. Del Negro, Marco & Schorfheide, Frank & Smets, Frank & Wouters, Rafael, 2007. "On the Fit of New Keynesian Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 123-143, April.
    31. Deschamps, Bruno & Ioannidis, Christos, 2013. "Can rational stubbornness explain forecast biases?," Journal of Economic Behavior & Organization, Elsevier, vol. 92(C), pages 141-151.
    32. Groen, Jan J.J. & Kapetanios, George & Price, Simon, 2009. "A real time evaluation of Bank of England forecasts of inflation and growth," International Journal of Forecasting, Elsevier, vol. 25(1), pages 74-80.
    33. Rochelle M. Edge & Michael T. Kiley & Jean-Philippe Laforte, 2010. "A comparison of forecast performance between Federal Reserve staff forecasts, simple reduced-form models, and a DSGE model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 720-754.
    34. Adolfson, Malin & Laséen, Stefan & Lindé, Jesper & Villani, Mattias, 2008. "Evaluating an estimated new Keynesian small open economy model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(8), pages 2690-2721, August.
    35. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    36. Marco Del Negro & Frank Schorfheide, 2004. "Priors from General Equilibrium Models for VARS," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(2), pages 643-673, May.
    37. Giacomini, Raffaella & Granger, Clive W. J., 2004. "Aggregation of space-time processes," Journal of Econometrics, Elsevier, vol. 118(1-2), pages 7-26.
    38. Negro, Marco Del & Schorfheide, Frank, 2013. "DSGE Model-Based Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 57-140, Elsevier.
    39. Marc P. Giannoni & Jean Boivin, 2005. "DSGE Models in a Data-Rich Environment," Computing in Economics and Finance 2005 431, Society for Computational Economics.
    40. Granger, Clive W.J. & Machina, Mark J., 2006. "Forecasting and Decision Theory," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 2, pages 81-98, Elsevier.
    41. David H. Romer & Christina D. Romer, 2000. "Federal Reserve Information and the Behavior of Interest Rates," American Economic Review, American Economic Association, vol. 90(3), pages 429-457, June.
    42. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
    43. Raffaella Giacomini & Barbara Rossi, 2010. "Forecast comparisons in unstable environments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 595-620.
    44. Dario Caldara & Richard Harrison & Anna Lipinska, 2012. "Practical tools for policy analysis in DSGE models with missing channels," Finance and Economics Discussion Series 2012-72, Board of Governors of the Federal Reserve System (U.S.).
    45. De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2008. "Forecasting using a large number of predictors: Is Bayesian shrinkage a valid alternative to principal components?," Journal of Econometrics, Elsevier, vol. 146(2), pages 318-328, October.
    46. Gianluca Moretti & Giulio Nicoletti, 2010. "Estimating DSGE models with unknown data persistence," Temi di discussione (Economic working papers) 750, Bank of Italy, Economic Research and International Relations Area.
    47. Eric Girardin & Konstantin A. Kholodilin, 2011. "How helpful are spatial effects in forecasting the growth of Chinese provinces?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(7), pages 622-643, November.
    48. Giacomini, Raffaella & Ragusa, Giuseppe, 2014. "Theory-coherent forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 145-155.
    49. Edge, Rochelle M. & Kiley, Michael T. & Laforte, Jean-Philippe, 2008. "Natural rate measures in an estimated DSGE model of the U.S. economy," Journal of Economic Dynamics and Control, Elsevier, vol. 32(8), pages 2512-2535, August.
    50. Hernandez-Murillo, Ruben & Owyang, Michael T., 2006. "The information content of regional employment data for forecasting aggregate conditions," Economics Letters, Elsevier, vol. 90(3), pages 335-339, March.
    51. Jon Faust, 2012. "DSGE Models: I Smell a Rat (and It Smells Good)," International Journal of Central Banking, International Journal of Central Banking, vol. 8(1), pages 53-64, March.
    52. Rochelle M. Edge & Refet S. Gurkaynak, 2010. "How Useful Are Estimated DSGE Model Forecasts for Central Bankers?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 41(2 (Fall)), pages 209-259.
    53. Elliott, Graham, 2006. "Forecasting with Trending Data," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 11, pages 555-604, Elsevier.
    54. Raffaella Giacomini, 2013. "The relationship between DSGE and VAR models," CeMMAP working papers CWP21/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Petar Soric & Enric Monte & Salvador Torra & Oscar Claveria, 2022. "“Density forecasts of inflation using Gaussian process regression models”," AQR Working Papers 202207, University of Barcelona, Regional Quantitative Analysis Group, revised Jul 2022.
    2. Nuttanan Wichitaksorn, 2020. "Analyzing and Forecasting Thai Macroeconomic Data using Mixed-Frequency Approach," PIER Discussion Papers 146, Puey Ungphakorn Institute for Economic Research.
    3. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Papers 1805.03807, arXiv.org.
    4. Lee Tae-Hwy & Wang He & Xi Zhou & Zhang Ru, 2023. "Density Forecast of Financial Returns Using Decomposition and Maximum Entropy," Journal of Econometric Methods, De Gruyter, vol. 12(1), pages 57-83, January.
    5. Muhammad Nadim Hanif & Muhammad Jahanzeb Malik, 2015. "Evaluating the Performance of Inflation Forecasting Models of Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 11, pages 43-78.
    6. Choy Keen Meng, 2016. "The inflation process and expectations in Singapore," BIS Papers chapters, in: Bank for International Settlements (ed.), Inflation mechanisms, expectations and monetary policy, volume 89, pages 335-343, Bank for International Settlements.
    7. EMERSON Abraham Jackson, 2018. "Comparison Between Static And Dynamic Forecast In Autoregressive Integrated Moving Average For Seasonally Adjusted Headline Consumer Price Index," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 70(1), pages 53-65, August.
    8. Alessandro Casini, 2018. "Tests for Forecast Instability and Forecast Failure under a Continuous Record Asymptotic Framework," Papers 1803.10883, arXiv.org, revised Dec 2018.
    9. 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.
    10. Fritz Breuss, 2018. "Would DSGE Models Have Predicted the Great Recession in Austria?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 105-126, April.
    11. Ca’ Zorzi, Michele & Kolasa, Marcin & Rubaszek, Michał, 2017. "Exchange rate forecasting with DSGE models," Journal of International Economics, Elsevier, vol. 107(C), pages 127-146.
    12. Luca Fanelli & Marco M. Sorge, 2015. "Indeterminacy, Misspecification and Forecastability: Good Luck in Bad Policy?," CSEF Working Papers 402, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    13. Elshurafa, Amro M. & Alatawi, Hatem & Hasanov, Fakhri J. & Algahtani, Goblan J. & Felder, Frank A., 2022. "Cost, emission, and macroeconomic implications of diesel displacement in the Saudi agricultural sector: Options and policy insights," Energy Policy, Elsevier, vol. 168(C).
    14. Fakhri J. Hasanov & Noha Razek, 2023. "Oil and Non-Oil Determinants of Saudi Arabia’s International Competitiveness: Historical Analysis and Policy Simulations," Sustainability, MDPI, vol. 15(11), pages 1-39, June.
    15. Fritz Breuss, 2016. "Would DSGE Models have Predicted the Great Recession in Austria?," WIFO Working Papers 530, WIFO.
    16. Job Nmadu & Ezekiel Yisa & Usman Mohammed & Halima Sallawu & Yebosoko Nmadu & Sokoyami Nmadu, 2022. "Structural Analysis and Forecast of Nigerian Monthly Inflation Movement between 1996 and 2022," RAIS Conference Proceedings 2022-2023 0211, Research Association for Interdisciplinary Studies.
    17. Ginanneschi, Marco, 2021. "Long-term strategic thinking, the Themis method and the future of food," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    18. Lillian R. Gaeto & Sandeep Mazumder, 2019. "Measuring the Accuracy of Federal Reserve Forecasts," Southern Economic Journal, John Wiley & Sons, vol. 85(3), pages 960-984, January.
    19. Ozana Nadoveza Jelić & Rafael Ravnik, 2021. "Introducing Policy Analysis Croatian MAcroecoNometric Model (PACMAN)," Surveys 41, The Croatian National Bank, Croatia.
    20. Lake, A., 2020. "Optimal Feasible Expectations in Economics and Finance," Cambridge Working Papers in Economics 20105, Faculty of Economics, University of Cambridge.
    21. Wichitaksorn, Nuttanan, 2022. "Analyzing and forecasting Thai macroeconomic data using mixed-frequency approach," Journal of Asian Economics, Elsevier, vol. 78(C).
    22. Diogo de Prince & Emerson Fernandes Marçal & Pedro L. Valls Pereira, 2022. "Forecasting Industrial Production Using Its Aggregated and Disaggregated Series or a Combination of Both: Evidence from One Emerging Market Economy," Econometrics, MDPI, vol. 10(2), pages 1-34, June.
    23. Ran Spiegler, 2021. "A Simple Model of Monetary Policy under Phillips-Curve Causal Disagreements," Papers 2105.08988, arXiv.org.
    24. Fanelli, Luca & Sorge, Marco M., 2017. "Indeterminate forecast accuracy under indeterminacy," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 57-70.

    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.
    1. Raffaella Giacomini, 2014. "Economic theory and forecasting: lessons from the literature," CeMMAP working papers 41/14, Institute for Fiscal Studies.
    2. 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.
    3. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    4. Raffaella Giacomini & Barbara Rossi, 2013. "Forecasting in macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 17, pages 381-408, Edward Elgar Publishing.
    5. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    6. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    7. Andrew Martinez, 2017. "Testing for Differences in Path Forecast Accuracy: Forecast-Error Dynamics Matter," Working Papers (Old Series) 1717, Federal Reserve Bank of Cleveland.
    8. Giacomini, Raffaella & Ragusa, Giuseppe, 2014. "Theory-coherent forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 145-155.
    9. Cai, Michael & Del Negro, Marco & Giannoni, Marc P. & Gupta, Abhi & Li, Pearl & Moszkowski, Erica, 2019. "DSGE forecasts of the lost recovery," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1770-1789.
    10. 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.
    11. Stelios Bekiros & Alessia Paccagnini, 2013. "On the predictability of time-varying VAR and DSGE models," Empirical Economics, Springer, vol. 45(1), pages 635-664, August.
    12. Giacomini, Raffaella & Ragusa, Giuseppe, 2011. "Incorporating theoretical restrictions into forecasting by projection methods," CEPR Discussion Papers 8604, C.E.P.R. Discussion Papers.
    13. Negro, Marco Del & Schorfheide, Frank, 2013. "DSGE Model-Based Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 57-140, Elsevier.
    14. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2015. "Prior Selection for Vector Autoregressions," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 436-451, May.
    15. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
    16. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    17. Bekiros Stelios & Paccagnini Alessia, 2015. "Estimating point and density forecasts for the US economy with a factor-augmented vector autoregressive DSGE model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(2), pages 107-136, April.
    18. Kolasa, Marcin & Rubaszek, Michał, 2015. "Forecasting using DSGE models with financial frictions," International Journal of Forecasting, Elsevier, vol. 31(1), pages 1-19.
    19. Mu-Chun Wang, 2009. "Comparing the DSGE model with the factor model: an out-of-sample forecasting experiment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(2), pages 167-182.
    20. Maik H. Wolters, 2015. "Evaluating Point and Density Forecasts of DSGE Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 74-96, January.

    More about this item

    Keywords

    Bayesian methods; Dsge models; Exponential tilting;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    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:cpr:ceprdp:10201. 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: the person in charge (email available below). General contact details of provider: https://www.cepr.org .

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

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