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On Identification Issues in Business Cycle Accounting Models

In: Essays in Honour of Fabio Canova

Author

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  • Pedro Brinca
  • Nikolay Iskrev
  • Francesca Loria

Abstract

Since its introduction by Chari, Kehoe, and McGrattan (2007), Business Cycle Accounting (BCA) exercises have become widespread. Much attention has been devoted to the results of such exercises and to methodological departures from the baseline methodology. Little attention has been paid to identification issues within these classes of models. In this chapter, the authors investigate whether such issues are of concern in the original methodology and in an extension proposed by Šustek (2011) called Monetary Business Cycle Accounting. The authors resort to two types of identification tests in population. One concerns strict identification as theorized by Komunjer and Ng (2011) while the other deals both with strict and weak identification as in Iskrev (2010). Most importantly, the authors explore the extent to which these weak identification problems affect the main economic takeaways and find that the identification deficiencies are not relevant for the standard BCA model. Finally, the authors compute some statistics of interest to practitioners of the BCA methodology.

Suggested Citation

  • Pedro Brinca & Nikolay Iskrev & Francesca Loria, 2022. "On Identification Issues in Business Cycle Accounting Models," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 55-138, Emerald Group Publishing Limited.
  • Handle: RePEc:eme:aecozz:s0731-90532022000044a004
    DOI: 10.1108/S0731-90532022000044A004
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    Cited by:

    1. Kshitiz Mishra & Partha Chatterjee, 2021. "Monetary Business Cycle Accounting Analysis of Indian Economy," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(3), pages 471-491, September.
    2. Daniel Fehrle & Johannes Huber, 2020. "Business cycle accounting for the German fiscal stimulus program during the Great Recession," Discussion Paper Series 339, Universitaet Augsburg, Institute for Economics.
    3. Brinca, Pedro & Costa-Filho, João & Loria, Francesca, 2020. "Business Cycle Accounting: what have we learned so far?," MPRA Paper 100180, University Library of Munich, Germany.
    4. Fernandes, Daniel, 2022. "Business Cycle Accounting for the COVID-19 Recession," MPRA Paper 111577, University Library of Munich, Germany.
    5. Scholl, Christoph, 2022. "COVID-19 and the GDP fall in Germany: A Business Cycle Accounting Approach," MPRA Paper 111570, University Library of Munich, Germany.

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    More about this item

    Keywords

    Business cycle accounting; identification; maximum likelihood estimation; C32; C51; C52; E27; E32; E37;
    All these keywords.

    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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