• Maddalena CAVICCHIOLI University of Venice, Italy Advanced School of Economics


We review some recent papers on a large dynamic factor model (LDFM) and its applications to structural macroeconomic analysis. Then we prove some convergence results concerning with the stochastic variables which define such a model.


[1] Bai, J., and Ng, S., 2002. Determining the number of factors in approximate factor models, Econometrica 70(1):191-221.
[2] Bai, J., and Ng, S., 2007. Determining the number of primitive shocks in factor models, Journal of Business and Economic Statistics, 25: 52-60.
[3] Chamberlain, G., and Rothschild, M., 1983. Arbitrage, factor structure and mean-variance analysis in large asset markets, Econometrics, 51: 1305-1324.
[4] Forni, M., Giannone, D., Lippi, M., and Reichlin, L. 2009. Opening the black box: structural factor models with large cross-sections, Econometric Theory, 25: 1319-1347.
[5] Forni, M., and Gambetti, L., 2010. The dynamic effects of monetary policy: a structural factor model approach, Journal of Monetary Economics, 57: 203-216.
[6] Forni, M., Hallin, M., Lippi, M., and Reichlin, L. 2000. The generalized dynamic factor model: identification and estimation, The Review of Economics and Statistics, 82: 540-554.
[7] Forni, M., and Lippi, M., 2001. The generalized dynamic factor model: representation theory, Econometric Theory, 17: 1113-1141.
[8] Onastski, A., 2009. Testing hypotheses about the number of factors in large factor models, manuscript, Columbia University, 2009.
[9] Rozanov, Y., Stationary Random Process, Holden Day, San Francisco, USA, 1967.
[10] Stock, J., and Watson, M. 2005. Implications of dynamic factor models for VAR analysis, NBER Working Papers, No.11467.
How to Cite
CAVICCHIOLI, Maddalena. SOME CONVERGENCE RESULTS ON DYNAMIC FACTOR MODELS. Theoretical and Practical Research in the Economic Fields, [S.l.], v. 2, n. 2, p. 120-131, may 2017. ISSN 2068-7710. Available at: <>. Date accessed: 25 apr. 2019.