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The perils of aggregating foreign variables in panel data models

  • Michele Ca' Zorzi
  • Alexander Chudik
  • Alistair Dieppe

The curse of dimensionality refers to the difficulty of including all relevant variables in empirical applications due to the lack of sufficient degrees of freedom. A common solution to alleviate the problem in the context of open economy models is to aggregate foreign variables by constructing trade-weighted cross-sectional averages. This paper provides two key contributions in the context of static panel data models. The first is to show under what conditions the aggregation of foreign variables (AFV) leads to consistent estimates (as the time dimension T is fixed and the cross section dimension N 8). The second is to design a formal test to assess the admissibility of the AFV restriction and to evaluate the small sample properties of the test by undertaking Monte Carlo experiments. Finally, we illustrate an application in the context of the current account empirical literature where the AFV restriction is rejected.

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Paper provided by Federal Reserve Bank of Dallas in its series Globalization and Monetary Policy Institute Working Paper with number 111.

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Date of creation: 2012
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Handle: RePEc:fip:feddgw:111
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  1. Menzie David Chinn & Eswar Prasad, 2000. "Medium-Term Determinants of Current Accounts in Industrial and Developing Countries: An Empirical Exploration," IMF Working Papers 00/46, International Monetary Fund.
  2. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2004. "The generalized dynamic factor model consistency and rates," Journal of Econometrics, Elsevier, vol. 119(2), pages 231-255, April.
  3. Marco Del Negro & Frank Schorfheide, 2002. "Priors from general equilibrium models for VARs," FRB Atlanta Working Paper 2002-14, Federal Reserve Bank of Atlanta.
  4. Alexander Chudik & M. Hashem Pesaran, 2007. "Infinite Dimensional VARs and Factor Models," CESifo Working Paper Series 2176, CESifo Group Munich.
  5. Ca’ Zorzi, Michele & Chudik, Alexander & Dieppe, Alistair, 2012. "Thousands of models, one story: Current account imbalances in the global economy," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1319-1338.
  6. Alexander Chudik & M. Hashem Pesaran & Elisa Tosetti, 2011. "Weak and strong cross‐section dependence and estimation of large panels," Econometrics Journal, Royal Economic Society, vol. 14(1), pages C45-C90, February.
  7. Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
  8. Pesaran, M.H. & Chudik, A., 2010. "Econometric Analysis of High Dimensional VARs Featuring a Dominant Unit," Cambridge Working Papers in Economics 1024, Faculty of Economics, University of Cambridge.
  9. Jesmin Rahman, 2008. "Current Account Developments in New Member States of the European Union: Equilibrium, Excess, and EU-Phoria," IMF Working Papers 08/92, International Monetary Fund.
  10. Ca' Zorzi, Michele & Chudik, Alexander & Dieppe, Alistair, 2009. "Current account benchmarks for central and eastern Europe: a desperate search?," Working Paper Series 0995, European Central Bank.
  11. Bussière, Matthieu & Ca' Zorzi, Michele & Chudik, Alexander & Dieppe, Alistair, 2010. "Methodological advances in the assessment of equilibrium exchange rates," Working Paper Series 1151, European Central Bank.
  12. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
  13. Forni, Mario & Lippi, Marco, 2001. "The Generalized Dynamic Factor Model: Representation Theory," Econometric Theory, Cambridge University Press, vol. 17(06), pages 1113-1141, December.
  14. Bussière, Matthieu & Fratzscher, Marcel, 2006. "Current Account Dynamics in OECD Countries and in the New EU Member States: An Intertemporal Approach," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 21, pages 593-618.
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