Sylvia Kaufmann | Study Center Gerzensee, Foundation of the Swiss National Bank

We combine the factor augmented VAR framework with recently developed estimation and identification procedures for sparse dynamic factor models. Working with a sparse hierarchical prior distribution allows us to discriminate between zero and non-zero factor loadings. The non-zero loadings identify the unobserved factors and provide a meaningful economic interpretation for them. Given that we work with a general covariance matrix of factor innovations, we can implement different strategies for structural shock identification. Applying our methodology to US macroeconomic data (FRED QD) reveals indeed a high degree of sparsity in the data. The proposed identification procedure yields seven unobserved factors that account for about 52 percent of the variation in the data and which can be given an economically meaningful interpretation. We then use the estimated FAVAR to identify a monetary policy shock and study the effect of a shock to the term premium. Factors and specific va! riables show sensible responses to the identified shocks.

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School of Economics seminars are the main academic seminar series held on a Friday. These seminars are presented by guest researchers and enable School of Economics academics to network with other academics from around Australia and internationally.


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