C22 Time-Series Models; Dynamic Quantile Regressions (Updated!)
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I have assessed changes in the monetary policy stance in the euro area since its inception by applying a Bayesian time-varying parameter framework in conjunction with the Hamiltonian Monte Carlo algorithm. I find that the estimated policy response has varied considerably over time. Most of the results suggest that the response weakened after the onset of the financial crisis and while quantitative measures were still in place, although there are also indications that the weakening of the response to the expected inflation gap may have been less pronounced. I also find that the policy response has become more forceful over the course of the recent sharp rise in inflation. Furthermore, it is essential to model the stochastic volatility relating to deviations from the policy rule as it materially influences the results.
Several recent studies have expressed concern that the Haar prior typically imposed in estimating sign-identi.ed VAR models may be unintentionally informative about the implied prior for the structural impulse responses. This question is indeed important, but we show that the tools that have been used in the literature to illustrate this potential problem are invalid. Speci.cally, we show that it does not make sense from a Bayesian point of view to characterize the impulse response prior based on the distribution of the impulse responses conditional on the maximum likelihood estimator of the reduced-form parameters, since the the prior does not, in general, depend on the data. We illustrate that this approach tends to produce highly misleading estimates of the impulse response priors. We formally derive the correct impulse response prior distribution and show that there is no evidence that typical sign-identi.ed VAR models estimated using conventional priors tend to imply unintentionally informative priors for the impulse response vector or that the corre- sponding posterior is dominated by the prior. Our evidence suggests that concerns about the Haar prior for the rotation matrix have been greatly overstated and that alternative estimation methods are not required in typical applications. Finally, we demonstrate that the alternative Bayesian approach to estimating sign-identi.ed VAR models proposed by Baumeister and Hamilton (2015) su¤ers from exactly the same conceptual shortcoming as the conventional approach. We illustrate that this alternative approach may imply highly economically implausible impulse response priors.
We derive the Bayes estimator of vectors of structural VAR impulse responses under a range of alternative loss functions. We also derive joint credible regions for vectors of impulse responses as the lowest posterior risk region under the same loss functions. We show that conventional impulse response estimators such as the posterior median response function or the posterior mean response function are not in general the Bayes estimator of the impulse response vector obtained by stacking the impulse responses of interest. We show that such pointwise estimators may imply response function shapes that are incompatible with any possible parameterization of the underlying model. Moreover, conventional pointwise quantile error bands are not a valid measure of the estimation uncertainty about the impulse response vector because they ignore the mutual dependence of the responses. In practice, they tend to understate substantially the estimation uncertainty about the impulse response vector.
Extending the data set used in Beyer (2009) to 2017, we estimate I(1) and I(2) money demand models for euro area M3. After including two broken trends and a few dummies to account for shifts in the variables following the global financial crisis and the ECB's non-standard monetary policy measures, we find that the money demand and the real wealth relations identified in Beyer (2009) have remained remarkably stable throughout the extended sample period. Testing for price homogeneity in the I(2) model we find that the nominal-to-real transformation is not rejected for the money relation whereas the wealth relation cannot be expressed in real terms.
We develop a state-space model to decompose bid and ask quotes of CDS into two components, fair default premium and liquidity premium. This approach gives a better estimate of the default premium than mid quotes, and it allows to disentangle and compare the liquidity premium earned by the protection buyer and the protection seller. In contrast to other studies, our model is structurally much simpler, while it also allows for correlation between liquidity and default premia, as supported by empirical evidence. The model is implemented and applied to a large data set of 118 CDS for a period ranging from 2004 to 2010. The model-generated output variables are analyzed in a difference-in-difference framework to determine how the default premium, as well as the liquidity premium of protection buyers and sellers, evolved during different periods of the financial crisis and to which extent they differ for financial institutions compared to non-financials.
This paper examines the relationship between oil movements and systemic risk of financial institution in major petroleum-based economies. We estimate ΔCoVaR for those institutions and observe the presence of elevated increases in its levels corresponding to the subprime and global financial crises. The results provide evidence in favor of risk measurement improvements by accounting for oil returns in the risk functions. The spread between the standard CoVaR and the CoVaR that includes oil absorbs in a time range longer than the duration of the oil shock. This indicates that the drop in the oil price has a longer effect on risk and requires more time to be discounted by the financial institutions. To support the analysis, we consider also the other major market-based systemic risk measures.
We build a novel leading indicator (LI) for the EU industrial production (IP). Differently from previous studies, the technique developed in this paper is able to produce an ex-ante LI that is immune to “overlapping information drawbacks”. In addition, the set of variables composing the LI relies on a dynamic and systematic criterion. This ensures that the choice of the variables is not driven by subjective views. Our LI anticipates swings (including the 2007-2008 crisis) in the EU industrial production – on average – by 2 to 3 months. The predictive power improves if the indicator is revised every five or ten years. In a forward-looking framework, via a general-to-specific procedure, we also show that our LI represents the most informative variable in approaching expectations on the EU IP growth.
We examine both the degree and the structural stability of inflation persistence at different quantiles of the conditional inflation distribution. Previous research focused exclusively on persistence at the conditional mean of the inflation rate. As economic theory provides reasons for inflation persistence to differ across conditional quantiles, this is a potentially severe constraint. Conventional studies of inflation persistence cannot identify changes in persistence at selected quantiles that leave persistence at the median of the distribution unchanged. Based on post-war US data we indeed find robust evidence for a structural break in persistence at all quantiles of the inflation process in the early 1980s. While prior to the 1980s inflation was not mean reverting, quantile autoregression based unit root tests suggest that since the end of the Volcker disinflation the unit root can be rejected at every quantile of the conditional inflation distribution.
Using a normalized CES function with factor-augmenting technical progress, we estimate a supply-side system of the US economy from 1953 to 1998. Avoiding potential estimation biases that have occurred in earlier studies and putting a high emphasis on the consistency of the data set, required by the estimated system, we obtain robust results not only for the aggregate elasticity of substitution but also for the parameters of labor and capital augmenting technical change. We find that the elasticity of substitution is significantly below unity and that the growth rates of technical progress show an asymmetrical pattern where the growth of laboraugmenting technical progress is exponential, while that of capital is hyperbolic or logarithmic.
Capturing the zero: a new class of zero-augmented distributions and multiplicative error processes
(2011)
We propose a novel approach to model serially dependent positive-valued variables which realize a non-trivial proportion of zero outcomes. This is a typical phenomenon in financial time series observed at high frequencies, such as cumulated trading volumes. We introduce a flexible point-mass mixture distribution and develop a semiparametric specification test explicitly tailored for such distributions. Moreover, we propose a new type of multiplicative error model (MEM) based on a zero-augmented distribution, which incorporates an autoregressive binary choice component and thus captures the (potentially different) dynamics of both zero occurrences and of strictly positive realizations. Applying the proposed model to high-frequency cumulated trading volumes of both liquid and illiquid NYSE stocks, we show that the model captures the dynamic and distributional properties of the data well and is able to correctly predict future distributions.
