Research Topics

Publications on Structural vector autoregression (SVAR)

There are 3 publications for Structural vector autoregression (SVAR).
  • Causal Linkages between Work and Life Satisfaction and Their Determinants in a Structural VAR Approach

    Working Paper No. 809 | June 2014

    Work and life satisfaction depends on a number of pecuniary and nonpecuniary factors at the workplace and determines these in turn. We analyze these causal linkages using a structural vector autoregression approach for a sample of the German working populace collected from 1984 to 2008, finding that workplace autonomy plays an important causal role in determining well-being.

    Associated Program:
    Alex Coad Martin Binder

  • The Household Sector Financial Balance, Financing Gap, Financial Markets, and Economic Cycles in the US Economy

    Working Paper No. 632 | November 2010
    A Structural VAR Analysis

    This paper investigates private net saving in the US economy—divided into its principal components, households and (nonfinancial) corporate financial balances—and its impact on the GDP cycle from the 1980s to the present. Furthermore, we investigate whether the financial markets (stock prices, BAA spread, and long-term interest rates) have a role in explaining the cyclical pattern of the two private financial balances. We analyze all these aspects estimating a VAR—between household and (nonfinancial) corporate financial balances (also known as the corporate financing gap), financial markets, and the economic cycle—and imposing restrictions on the matrix A to identify the structural shocks. We find that households and corporate balances react to financial markets as theoretically expected, and that the economic cycle reacts positively to corporate balance, in accordance with the Minskyan view of the operation of the economy that we have embraced.

    Associated Programs:
    Paolo Casadio Antonio Paradiso

  • Infinite-variance, Alpha-stable Shocks in Monetary SVAR

    Working Paper No. 596 | May 2010
    The process of constructing impulse-response functions (IRFs) and forecast-error variance decompositions (FEVDs) for a structural vector autoregression (SVAR) usually involves a factorization of an estimate of the error-term variance-covariance matrix V. Examining residuals from a monetary VAR, this paper finds evidence suggesting that all of the variances in V are infinite. Specifically, this study estimates alpha-stable distributions for the reduced-form error terms. The ML estimates of the residuals’ characteristic exponents α range from 1.5504 to 1.7734, with the Gaussian case lying outside 95 percent asymptotic confidence intervals for all six equations of the VAR. Variance-stabilized P-P plots show that the estimated distributions fit the residuals well. Results for subsamples are varied, while GARCH(1,1) filtering yields standardized shocks that are also all likely to be non-Gaussian alpha stable. When one or more error terms have infinite variance, V cannot be factored. Moreover, by Proposition 1, the reduced-form DGP cannot be transformed, using the required nonsingular matrix, into an appropriate system of structural equations with orthogonal, or even finite-variance, shocks. This result holds with arbitrary sets of identifying restrictions, including even the null set. Hence, with one or more infinite-variance error terms, structural interpretation of the reduced-form VAR within the standard SVAR model is impossible.

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