Browsing by Subject "Factor models"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Publication
    Open Access
    Factor models for large and incomplete data sets with unknown group structure
    (Elsevier B.V. on behalf of International Institute of Forecasters., 2023-07) Camacho, Maximo; Lopez-Buenache, German; Métodos Cuantitativos para la Economía y la Empresa
    Most economic applications rely on a large number of time series, which typically have a remarkable clustering structure and they are available over different spans. To handle these databases, we combined the expectation–maximization (EM) algorithm outlined by Stock and Watson (JBES, 2002) and the estimation algorithm for large factor models with an unknown number of group structures and unknown membership described by Ando and Bai (JAE, 2016; JASA, 2017) . Several Monte Carlo experiments demonstrated the good performance of the proposed method at determining the correct number of clusters, providing the appropriate number of group-specific factors, identifying error-free group membership, and obtaining accurate estimates of unobserved missing data. In addition, we found that our proposed method performed substantially better than the standard EM algorithm when the data had a grouped factor structure. Using the Federal Reserve Economic Data FRED-QD, our method detected two distinct groups of macroeconomic indicators comprising the real activity indicators and nominal indicators. Thus, we demonstrated the usefulness of our group-specific factor model for studies of business cycle chronology and for forecasting purposes.
  • Thumbnail Image
    Publication
    Open Access
    Forecast Accuracy of Small and Large Scale Dynamic Factor Models in Developing Economies
    (2018) López Buenache, Germán; Métodos Cuantitativos para la Economía y la Empresa
    Developing economies usually present limitations in the availability of economic data. This constraint may affect the capacity of Dynamic Factor Models to summarize large amounts of information into latent factors that reflect macroeconomic performance. This paper addresses this issue by comparing the accuracy of two kinds of Dynamic Factor Models at GDP forecasting for six Latin American countries. Each model is based on a dataset of different dimensions: a large dataset composed of series belonging to several macroeconomic categories (Large Scale Dynamic Factor Model) and a small dataset with a few prescreened variables considered as the most representative ones (Small Scale Dynamic Factor Model). Short- term pseudo real time out-of-sample forecast of GDP growth is carried out with both models reproducing the real time situation of data accessibility derived from the publication lags of the series in each country. Results i) confirm the important role of the inclusion of latest released data in the forecast accuracy of both models, ii) show better precision of predictions based on factors with respect to autoregressive models and iii) identify the most adequate model for each country according to availability of the observed data.
  • Thumbnail Image
    Publication
    Open Access
    The evolution of monetary policy effectiveness under macroeconomic instability
    (2019) López Buenache, Germán; Métodos Cuantitativos para la Economía y la Empresa
    This paper studies the evolution of the monetary policy transmission mechanisms in the US following the Great Recession. The implementation of a modified Dynamic Factor Model enables the identification of two different structural scenarios based on the information contained in a large dataset of 110 variables. Impulse Response Functions to an increase of official interest rate for this large dataset are estimated for each structural context. Three techniques are combined to deal with the dimensionality problems which emerge from an estimation procedure of this magnitude: (i) factor decomposition, (ii) an identification strategy independent of the number of variables included in the dataset and (iii) a blockwise optimization algorithm for the correct selection of the Bayesian priors. Results show the presence of a structural break in 2008 and the higher responsiveness of the economy to monetary policy after that date.