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Preface to Econometric Modeling: A Likelihood Approach

In: Econometric Modeling: A Likelihood Approach

Author

Listed:
  • David F. Hendry

    (University of Oxford, Nuffield College.)

  • Bent Nielsen

    (University of Oxford, Nuffield College)

Abstract

Econometric Modeling provides a new and stimulating introduction to econometrics, focusing on modeling. The key issue confronting empirical economics is to establish sustainable relationships that are both supported by data and interpretable from economic theory. The unified likelihood-based approach of this book gives students the required statistical foundations of estimation and inference, and leads to a thorough understanding of econometric techniques. David Hendry and Bent Nielsen introduce modeling for a range of situations, including binary data sets, multiple regression, and cointegrated systems. In each setting, a statistical model is constructed to explain the observed variation in the data, with estimation and inference based on the likelihood function. Substantive issues are always addressed, showing how both statistical and economic assumptions can be tested and empirical results interpreted. Important empirical problems such as structural breaks, forecasting, and model selection are covered, and Monte Carlo simulation is explained and applied. Econometric Modeling is a self-contained introduction for advanced undergraduate or graduate students. Throughout, data illustrate and motivate the approach, and are available for computer-based teaching. Technical issues from probability theory and statistical theory are introduced only as needed. Nevertheless, the approach is rigorous, emphasizing the coherent formulation, estimation, and evaluation of econometric models relevant for empirical research.

Suggested Citation

  • David F. Hendry & Bent Nielsen, 2007. "Preface to Econometric Modeling: A Likelihood Approach," Introductory Chapters,in: Econometric Modeling: A Likelihood Approach Princeton University Press.
  • Handle: RePEc:pup:chapts:8352-p
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    Citations

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    Cited by:

    1. Camila Epprecht & Dominique Guegan & Álvaro Veiga & Joel Correa da Rosa, 2017. "Variable selection and forecasting via automated methods for linear models: LASSO/adaLASSO and Autometrics," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00917797, HAL.
    2. Ahumada, Hildegart A. & Garegnani, Maria Lorena, 2012. "Forecasting a monetary aggregate under instability: Argentina after 2001," International Journal of Forecasting, Elsevier, vol. 28(2), pages 412-427.
    3. Camila Epprecht & Dominique Guegan & Álvaro Veiga, 2013. "Comparing variable selection techniques for linear regression: LASSO and Autometrics," Documents de travail du Centre d'Economie de la Sorbonne 13080, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    4. Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2012. "Model selection when there are multiple breaks," Journal of Econometrics, Elsevier, vol. 169(2), pages 239-246.
    5. Andrew J Swiston, 2011. "Official Dollarization As a Monetary Regime; Its Effectson El Salvador," IMF Working Papers 11/129, International Monetary Fund.
    6. Bec, Frédérique & Mogliani, Matteo, 2015. "Nowcasting French GDP in real-time with surveys and “blocked” regressions: Combining forecasts or pooling information?," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1021-1042.
    7. David Hendry & Jurgen A. Doornik, 2014. "Statistical Model Selection with 'Big Data'," Economics Series Working Papers 735, University of Oxford, Department of Economics.
    8. Tian Xie, 2012. "Least Squares Model Averaging by Prediction Criterion," Working Papers 1299, Queen's University, Department of Economics.
    9. Soyer, Emre & Hogarth, Robin M., 2012. "The illusion of predictability: How regression statistics mislead experts," International Journal of Forecasting, Elsevier, vol. 28(3), pages 695-711.
    10. Monique Reid & Gideon Rand, 2015. "A Sticky Information Phillips Curve for South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 83(4), pages 506-526, December.
    11. Durevall, Dick & Loening, Josef L. & Ayalew Birru, Yohannes, 2013. "Inflation dynamics and food prices in Ethiopia," Journal of Development Economics, Elsevier, vol. 104(C), pages 89-106.
    12. repec:gam:jecnmx:v:5:y:2017:i:3:p:38-:d:110889 is not listed on IDEAS
    13. Willem H. Boshoff, 2011. "Gasoline, diesel fuel and jet fuel demand in South Africa," Working Papers 226, Economic Research Southern Africa.
    14. repec:eee:energy:v:137:y:2017:i:c:p:1054-1065 is not listed on IDEAS
    15. Swarnali Ahmed, 2015. "If the Fed Acts, How Do You React? The Liftoff Effect on Capital Flows," IMF Working Papers 15/256, International Monetary Fund.
    16. Hendry, David F. & Martinez, Andrew B., 2017. "Evaluating multi-step system forecasts with relatively few forecast-error observations," International Journal of Forecasting, Elsevier, vol. 33(2), pages 359-372.
    17. Francesco Grigoli & José M. Mota, 2017. "Interest rate pass-through in the Dominican Republic," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 26(1), pages 1-25, December.
    18. Hikaru Saijo & Cosmin Ilut, 2015. "Learning, Confidence, and Business Cycles," 2015 Meeting Papers 917, Society for Economic Dynamics.
    19. Fullerton, Thomas M., Jr. & Ceballos, Alejandro & Walke, Adam G., 2015. "Short-Term Forecasting Analysis for Municipal Water Demand," MPRA Paper 78259, University Library of Munich, Germany, revised 04 Aug 2015.
    20. Matteo G. Richiardi, 2015. "The future of agent-based modelling," LABORatorio R. Revelli Working Papers Series 141, LABORatorio R. Revelli, Centre for Employment Studies.
    21. Clements Michael P. & Hendry David F., 2008. "Economic Forecasting in a Changing World," Capitalism and Society, De Gruyter, pages 1-20.
    22. Owen, Dorian, 2017. "Replication to assess statistical adequacy," Economics Discussion Papers 2017-73, Kiel Institute for the World Economy (IfW).

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