Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks
American Economic Review,
Traditional approaches to structural vector autoregressions (VARs) can be viewed as special cases of Bayesian inference arising from very strong prior beliefs. These methods can be generalized with a less restrictive formulation that incorporates uncertainty about the identifying assumptions themselves. We use this approach to revisit the importance of shocks to oil supply and demand. Supply disruptions turn out to be a bigger factor in historical oil price movements and inventory accumulation a smaller factor than implied by earlier estimates. Supply shocks lead to a reduction in global economic activity after a significant lag, whereas shocks to oil demand do not.
Inference in Structural Vector Autoregressions when the Identifying Assumptions are not Fully Believed: Re-evaluating the Role of Monetary Policy in Economic Fluctuations
Journal of Monetary Economics,
Point estimates and error bands for SVARs that are set identified are only justified if the researcher is persuaded that some parameter values are a priori more plausible than others. When such prior information exists, traditional approaches can be generalized to allow for doubts about the identifying assumptions. We use information about both structural coefficients and impacts of shocks and propose a new asymmetric t-distribution for incorporating information about signs in a nondogmatic way. We apply these methods to a three-variable macroeconomic model and conclude that monetary policy shocks are not the major driver of output, inflation, or interest rates.
Time-varying Volatility, Financial Intermediation and Monetary Policy
IWH Discussion Papers,
We document that expansionary monetary policy shocks are less effective at stimulating output and investment in periods of high volatility compared to periods of low volatility, using a regime-switching vector autoregression. Exogenous policy changes are identified by adapting an external instruments approach to the non-linear model. The lower effectiveness of monetary policy can be linked to weaker responses of credit costs, suggesting a financial accelerator mechanism that is weaker in high volatility periods. To rationalize our robust empirical results, we use a macroeconomic model in which financial intermediaries endogenously choose their capital structure. In the model, the leverage choice of banks depends on the volatility of aggregate shocks. In low volatility periods, financial intermediaries lever up, which makes their balance sheets more sensitive to aggregate shocks and the financial accelerator more effective. On the contrary, in high volatility periods, banks decrease leverage, which renders the financial accelerator less effective; this in turn decreases the ability of monetary policy to improve funding conditions and credit supply, and thereby to stimulate the economy. Hence, we provide a novel explanation for the non-linear effects of monetary stimuli observed in the data, linking the effectiveness of monetary policy to the procyclicality of leverage.
On the Low-frequency Relationship Between Public Deficits and Inflation
Journal of Applied Econometrics,
We estimate the low-frequency relationship between fiscal deficits and inflation and pay special attention to its potential time variation by estimating a time-varying vector autoregression model for US data from 1900 to 2011. We find the strongest relationship neither in times of crisis nor in times of high public deficits, but from the mid 1960s up to 1980. Employing a structural decomposition of the low-frequency relationship and further narrative evidence, we interpret our results such that the low-frequency relationship between fiscal deficits and inflation is strongly related to the conduct of monetary policy and its interaction with fiscal policy after World War II.
Sign Restrictions, Structural Vector Autoregressions, and Useful Prior Information
This paper makes the following original contributions to the literature. (i) We develop a simpler analytical characterization and numerical algorithm for Bayesian inference in structural vector autoregressions (VARs) that can be used for models that are overidentified, just‐identified, or underidentified. (ii) We analyze the asymptotic properties of Bayesian inference and show that in the underidentified case, the asymptotic posterior distribution of contemporaneous coefficients in an n‐variable VAR is confined to the set of values that orthogonalize the population variance–covariance matrix of ordinary least squares residuals, with the height of the posterior proportional to the height of the prior at any point within that set. For example, in a bivariate VAR for supply and demand identified solely by sign restrictions, if the population correlation between the VAR residuals is positive, then even if one has available an infinite sample of data, any inference about the demand elasticity is coming exclusively from the prior distribution. (iii) We provide analytical characterizations of the informative prior distributions for impulse‐response functions that are implicit in the traditional sign‐restriction approach to VARs, and we note, as a special case of result (ii), that the influence of these priors does not vanish asymptotically. (iv) We illustrate how Bayesian inference with informative priors can be both a strict generalization and an unambiguous improvement over frequentist inference in just‐identified models. (v) We propose that researchers need to explicitly acknowledge and defend the role of prior beliefs in influencing structural conclusions and we illustrate how this could be done using a simple model of the U.S. labor market.
Business Cycle Volatility in Germany
German Economic Review,
Stylized facts suggest that output volatility in OECD countries has declined in recent years. The causes and the nature of this decline have so far been analyzed mainly for the United States. In this paper, we analyze whether structural changes in output volatility in Germany can be detected. We report evidence that output volatility has declined in Germany. It is difficult to answer the question whether this decline in output volatility reflects good economic and monetary policy or merely ‘good luck’.