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Automated Discovery in Econometrics

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Abstract

Our subject is the notion of automated discovery in econometrics. Advances in computer power, electronic communication, and data collection processes have all changed the way econometrics is conducted. These advances have helped to elevate the status of empirical research within the economics profession in recent years and they now open up new possibilities for empirical econometric practice. Of particular significance is the ability to build econometric models in an automated way according to an algorithm of decision rules that allow for (what we call here) heteroskedastic and autocorrelation robust (HAR) inference. Computerized search algorithms may be implemented to seek out suitable models, thousands of regressions and model evaluations may be performed in seconds, statistical inference may be automated according to the properties of the data, and policy decisions can be made and adjusted in real time with the arrival of new data. We discuss some aspects and implications of these exciting, emergent trends in econometrics.

Suggested Citation

  • Peter C.B. Phillips, 2004. "Automated Discovery in Econometrics," Cowles Foundation Discussion Papers 1469, Cowles Foundation for Research in Economics, Yale University.
  • Handle: RePEc:cwl:cwldpp:1469
    Note: CFP 1149.
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    Cited by:

    1. Hwang, Jungbin & Sun, Yixiao, 2016. "Simple, Robust, and Accurate F and t Tests in Cointegrated Systems," University of California at San Diego, Economics Working Paper Series qt82k1x4rd, Department of Economics, UC San Diego.
    2. Bernd Brandl & Christian Keber & Matthias Schuster, 2006. "An automated econometric decision support system: forecasts for foreign exchange trades," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 14(4), pages 401-415, December.
    3. Jane E. Ihrig & Mario Marazzi & Alexander D. Rothenberg, 2006. "Exchange-rate pass-through in the G-7 countries," International Finance Discussion Papers 851, Board of Governors of the Federal Reserve System (U.S.).
    4. Marquez, Jaime, 2006. "Estimating elasticities for U.S. trade in services," Economic Modelling, Elsevier, vol. 23(2), pages 276-307, March.
    5. Qin, Duo, 2008. "Uncover Latent PPP by Dynamic Factor Error Correction Model (DF-ECM) Approach: Evidence from Five OECD Countries," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 2, pages 1-26.
    6. Jennifer L. Castle & Xiaochuan Qin & W. Robert Reed, 2013. "Using Model Selection Algorithms To Obtain Reliable Coefficient Estimates," Journal of Economic Surveys, Wiley Blackwell, vol. 27(2), pages 269-296, April.
    7. Dahl, Christian M. & Hansen, Henrik & Smidt, John, 2009. "The cyclical component factor model," International Journal of Forecasting, Elsevier, vol. 25(1), pages 119-127.
    8. Heij, C. & Groenen, P.J.F. & van Dijk, D.J.C., 2006. "Time series forecasting by principal covariate regression," Econometric Institute Research Papers EI 2006-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    More about this item

    Keywords

    Automation; discovery; HAC estimation; HAR inference; model building; online econometrics; policy analysis; prediction; trends;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

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