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This paper proposes a joint methodology for the identification and inference of structural vector autoregressive models in the frequency domain. We show that identifying restrictions can be written naturally as an asymptotic least squares problem (Gourieroux, Monfort and Trognon, 1985) in which there is a continuum of nonlinear estimating equations. Following Carrasco and Florens (2000), we then develop a continuum asymptotic least squares estimator (C-ALS) that exploits efficiently the continuum of estimating equations thereby allowing to obtain optimal consistent estimates of impulse responses and reliable confidence intervals. Moreover the identifying restrictions can be formally tested using an appropriate J-stat and the frequency band can be selected with a data-driven procedure. Finally, we provide some new results using Monte Carlo simulations and applications regarding the hours-productivity debate and the impact of news shocks.

In this paper we assess the merits of financial condition indices constructed using simple averages versus a more sophisticated alternative that uses factor models with time varying parameters. Our analysis is based on data for 18 advanced and emerging economies at a monthly frequency covering about 70% of the world's GDP.We assess the performance of these indicators based on their ability to capture tail risk for economic activity and to predict banking and currency crises. We find that averaging across the indicators of interest, using judgmental but intuitive weights, produces financial condition indices that are not inferior to, and actually perform better than, those constructed with more sophisticated statistical methods. An indicator that gives more weight to measures of financial stress, which we term WA-FSI, emerges as the best indicator for anticipating banking crisis, and is therefore better suited for financial stability.

In SVARs, identification of structural shocks can be subject to nonfundamentalness, as the econometrician may have an information set smaller than the economic agents' one. How serious is that problem from a quantitative point of view? In this paper we propose a simple diagnostic for the quantitative importance of nonfundamentalness in structural VARs. The diagnostic is of interest as nonfundamentalness is not an either/or question, and its quantitative implications can be more or less severe. As an illustration, we apply our diagnostic to the identification of TFP news shocks and we find that nonfundamentalness is of little quantitatively importance in that context.

We study the cyclical dynamics of consumption in the euro area (EA) and the large EA countries by distinguishing durable from nondurable expenditures. We adopt a theoretical partial equilibrium framework to justify the identification strategy of our empirical model, a time-varying parameter structural vector autoregression (TVP-SVAR). Following the main insight from the theoretical model, that liquidity constraints induce important interactions between durables and nondurables, we distinguish durable-specific demand and supply shocks, while taking into account monetary and credit conditions. Our main findings are: (i) durables react faster and more strongly than nondurables after monetary shocks in the euro area and in the largest EA countries, a confirmation of an outcome commonly reported for the US; (ii) there is a large degree of cross-country heterogeneity in how different factors (including durable-specific ones) explain consumption; (iii) the strength of spillovers from durable to nondurable consumption, as predicted by theory, is empirically correlated with how much households across countries are likely to be liquidity constrained.

In this paper we discuss general identification results for Structural Vector Autoregressions (SVARs) with external instruments, considering the case in which r valid instruments are used to identify g Ï 1 structural shocks, where r Ï g. We endow the SVAR with an auxiliary statistical model for the external instruments which is a system of reduced form equations. The SVAR and the auxiliary model for the external instruments jointly form a "larger" SVAR characterized by a particularly restricted parametric structure, and are connected by the covariance matrix of their disturbances which incorporates the "relevance" and "exogeneity" conditions. We discuss identification results and likelihood-based estimation methods both in the "multiple shocks" approach, where all structural shocks are of interest, and in the "partial shock" approach, where only a subset of the structural shocks is of interest. Overidentified SVARs with external instruments can be easily tested in our setup. The suggested method is applied to investigate empirically whether commonly employed measures of macroeconomic and financial uncertainty respond on-impact, other than with lags, to business cycle fluctuations in the U.S. in the period after the Global Financial Crisis. To do so, we employ two external instruments to identify the real economic activity shock in a partial shock approach.

Motivated by the increasing use of external instruments to identify structural vector autoregressions (SVARs), we develop algorithms for exact finite sample inference in this class of time series models, commonly known as proxy-SVARs. Our algorithms make independent draws from the normal-generalized-normal family of conjugate posterior distributions over the structural parameterization of a proxy-SVAR. Importantly, our techniques can handle the case of set identification and hence they can be used to relax the additional exclusion restrictions unrelated to the external instruments often imposed to facilitate inference when more than one instrument are used to identify more than one equation, as in Mertens and Montiel-Olea (2018).

Long-run restrictions are a very popular method for identifying structural vector autoregressions, but they suffer from weak identification when the data is very persistent, i.e., when the highest autoregressive roots are near unity. Near unit roots introduce additional nuisance parameters and make standard weak-instrument-robust methods of inference inapplicable. We develop a method of inference that is robust to both weak identification and strong persistence. The method is based on a combination of the Anderson-Rubin test with instruments derived by filtering potentially non-stationary variables to make them near stationary. We apply our method to obtain robust confidence bands on impulse responses in two leading applications in the literature.

We identify structural vector autoregressions using narrative sign restrictions. Narrative sign restrictions constrain the structural shocks and the historical decomposition around key historical events, ensuring that they agree with the established narrative account of these episodes. Using models of the oil market and monetary policy, we show that narrative sign restrictions are highly informative. We highlight that adding a single narrative sign restriction dramatically sharpens and even changes the inference of SVARs originally identified via traditional sign restrictions. Our approach combines the appeal of narrative methods with the popularized usage of traditional sign restrictions.

This paper studies the effects of monetary policy shocks using structural vector autoregressions (SVARs). We achieve identification by imposing sign and zero restrictions on the systematic component of monetary policy. We consistently find that an increase in the fed funds rate induces a contraction in output. We also show that the identification strategy in Uhlig (2005), which imposes sign restrictions on the impulse responses to a monetary shock, does not satisfy our restrictions on the systematic component of monetary policy with high posterior probability. This finding accounts for the difference in results with Uhlig (2005), who found that contractionary monetary policy shocks have no clear effect on output. When we reconcile the two approaches by combining both sets of restrictions, monetary policy shocks remain contractionary.

In this paper, we identify monetary policy shocks in structural vector autoregressions (SVARs) by imposing sign and zero restrictions on the systematic component of monetary policy while leaving the remaining equations in the system unrestricted. As in Uhlig (2005), no restrictions are imposed on the response of output to a monetary policy shock. We find that an exogenous increase in the federal funds rate leads to a persistent decline in output and prices. Our results show that the contractionary effects of monetary policy shocks do not hinge on questionable exclusion restrictions, but are instead consistent with agnostic identification schemes. The analysis is robust to various specifications of the systematic component of monetary policy widely used in the literature.

Are optimism shocks an important source of business cycle fluctuations? Are deficit-financed tax cuts better than deficit-financed spending to increase output? These questions have been previously studied using SVARs identified with sign and zero restrictions and the answers have been positive and definite in both cases. While the identification of SVARs with sign and zero restrictions is theoretically attractive because it allows the researcher to remain agnostic with respect to the responses of the key variables of interest, we show that current implementation of these techniques does not respect the agnosticism of the theory. These algorithms impose additional sign restrictions on variables that are seemingly unrestricted that bias the results and produce misleading confidence intervals. We provide an alternative and efficient algorithm that does not introduce any additional sign restriction, hence preserving the agnosticism of the theory. Without the additional restrictions, it is hard to support the claim that either optimism shocks are an important source of business cycle fluctuations or deficit-financed tax cuts work best at improving output. Our algorithm is not only correct but also faster than current ones.

Shocks to bank lending, risk-taking and securitization activities that are orthogonal to real economy and monetary policy innovations account for more than 30 percent of U.S. output variation. The dynamic effects, however, depend on the type of shock. Expansionary securitization shocks lead to a permanent rise in real GDP and a fall in inflation. Bank lending and risktaking shocks, in contrast, have only a temporary effect on real GDP and tend to lead to a (moderate) rise in the price level.Furthermore, there is evidence for a strong search-for-yield effect on the side of investors in the transmission mechanism of monetary policy. These effects are estimated with a structural VAR model, where the shocks are identified using a model of bank risk-taking and securitization.

Shocks to bank lending, risk-taking and securitization activities that are orthogonal to real economy and monetary policy innovations account for more than 30 percent of U.S. output variation. The dynamic effects, however, depend on the type of shock. Expansionary securitization shocks lead to a permanent rise in real GDP and a fall in inflation. Bank lending and risk-taking shocks, in contrast, have only a temporary effect on real GDP and tend to lead to a (moderate) rise in the price level. Furthermore, there is evidence for a strong search-for-yield effect on the side of investors in the transmission mechanism of monetary policy. These effects are estimated with a structural VAR model, where the shocks are identified using a model of bank risk-taking and securitization.

Shocks to bank lending, risk-taking and securitization activities that are orthogonal to real economy and monetary policy innovations account for more than 30 percent of U.S. output variation. The dynamic effects, however, depend on the type of shock. Expansionary securitization shocks lead to a permanent rise in real GDP and a fall in inflation. Bank lending and risktaking shocks, in contrast, have only a temporary effect on real GDP and tend to lead to a (moderate) rise in the price level. Furthermore, there is evidence for a strong search-for-yield effect on the side of investors in the transmission mechanism of monetary policy. These effects are estimated with a structural VAR model, where the shocks are identified using a model of bank risk-taking and securitization.

This paper assesses SVARs as relevant tools at identifying the dynamic effects or news shocks, Because of the misalignment between the econometrician and private agents' information sets resulting from foresight the dynamic responses identified from SVARs using either long-run and short-run restrictions are biased. However the bias vanishes when news shocks account for the bulk of fluctuations in the economy. Furthermore under this condition. he two identified shocks have a correlation close to unity validating the sequential identification approach adopted by BEAUDRY and PORTIER (2006)

Shocks to bank lending, risk-taking and securitization activities that are orthogonal to real economy and monetary policy innovations account for more than 30 percent of U.S. output variation. The dynamic effects, however, depend on the type of shock. Expansionary securitization shocks lead to a permanent rise in real GDP and a fall in inflation. Bank lending and risktaking shocks, in contrast, have only a temporary effect on real GDP and tend to lead to a (moderate) rise in the price level. Furthermore, there is evidence for a strong search-for-yield effect on the side of investors in the transmission mechanism of monetary policy. These effects are estimated with a structural VAR model, where the shocks are identified using a model of bank risk-taking and securitization.

Shocks to bank lending, risk-taking and securitization activities that are orthogonal to real economy and monetary policy innovations account for more than 30 percent of U.S. output variation. The dynamic effects, however, depend on the type of shock. Expansionary securitization shocks lead to a permanent rise in real GDP and a fall in inflation. Bank lending and risktaking shocks, in contrast, have only a temporary effect on real GDP and tend to lead to a (moderate) rise in the price level. Furthermore, there is evidence for a strong search-for-yield effect on the side of investors in the transmission mechanism of monetary policy. These effects are estimated with a structural VAR model, where the shocks are identified using a model of bank risk-taking and securitization.

Shocks to bank lending, risk-taking and securitization activities that are orthogonal to real economy and monetary policy innovations account for more than 30 percent of U.S. output variation. The dynamic effects, however, depend on the type of shock. Expansionary securitization shocks lead to a permanent rise in real GDP and a fall in inflation. Bank lending and risktaking shocks, in contrast, have only a temporary effect on real GDP and tend to lead to a (moderate) rise in the price level.Furthermore, there is evidence for a strong search-for-yield effect on the side of investors in the transmission mechanism of monetary policy. These effects are estimated with a structural VAR model, where the shocks are identified using a model of bank risk-taking and securitization.

This paper studies the statistical properties of impulse response functions in structural vector autoregressions (SVARs) with a highly persistent variable as hours worked and long-run identifying restrictions. The highly persistent variable is specified as a nearly stationary persistent process. Such process appears particularly well suited to characterized the dynamics of hours worked because it implies a unit root in finite sample but is asymptotically stationary and persistent. This is typically the case for per capita hours worked which are included in SVARs. Theoretical results derived from this specification allow to explain most of the empirical findings from SVARs which include U.S. hours worked. Simulation experiments from an estimated DSGE model confirm theoretical results.

This paper investigates the reliability of SVARs to identify the dynamic effects of news shocks. We show analytically that the dynamics implied by SVARs, using both long–run and short–run restrictions, are biased. However, the bias vanishes as long as news shocks account for most of the variability of the endogenous variable and the economy exhibits strong forward–looking behavior. Our simulation experiments confirm these findings and further suggest that the number of lags is a key ingredient for the success of the VAR setup. Furthermore, a simple correlation diagnostic test shows that news shocks identified using both restrictions are found to exhibit a correlation close to unity, provided that news shocks drive an overwhelming part of aggregate fluctuations.

I find that the Eurosystem can stimulate the economy beyond the policy rate by increasing the size of its balance sheet or the monetary base. The transmission mechanism turns out to be different compared to traditional interest rate innovations: (i) whilst the effects on economic activity and consumer prices reach a peak after about one year for an interest rate innovation, this is more than six months later for a shift in the monetary base that is orthogonal to the policy rate (ii) interest rate spreads charged by banks decline persistently after a rise in the monetary base, whereas the spreads increase significantly after a fall in the policy rate (iii) there is no significant short-run liquidity effect after an interest rate innovation, that is additional bank loans are generated by a greater credit multiplier. In contrast, the multiplier declines considerably after an expansion of the Eurosystem’s balance sheet. JEL Classification: C32, E30, E44, E51, E52

I find that the Eurosystem can stimulate the economy beyond the policy rate by increasing the size of its balance sheet or the monetary base, that is so-called quantitative easing. The transmission mechanism turns out to be different compared to traditional interest rate innovations: (i) whilst the effects on economic activity and consumer prices reach a peak after about one year for an interest rate innovation, this is more than six months later for a shift in the monetary base that is orthogonal to the policy rate (ii) interest rate spreads charged by banks decline persistently after quantitative easing policies, whereas the spreads increase significantly after a fall in the policy rate (iii) there is no significant short-run liquidity effect after an interest rate innovation, that is additional bank loans are generated by a greater credit multiplier. In contrast, the multiplier declines considerably after an expansion of the Eurosystem's balance sheet.

This article re-examines the VAR evidence on the price puzzle and proposes a new theoretical interpretation. Using actual data and two identification strategies based on zero restrictions and model-consistent sign restrictions, we find that the positive response of prices to a monetary policy shock is historically limited to the sub-samples that are typically associated with a weak interest rate response to inflation. Using pseudo data generated by a sticky price model of the US economy, we then show that the structural VARs are capable of reproducing the price puzzle only when monetary policy is passive. The omission in the VARs of a variable capturing expected inflation is found to account for the price puzzle observed in simulated and actual data. Structural vector autoregressions (SVARs) are widely used for measuring and understanding the effects of monetary policy innovations on the aggregate economy. While most results in the VAR literature are consistent with economic intuition and macroeconomic theory, the typically found positive and significant reaction of the price level on impact to a monetary policy shock is a fact that most monetary models

An important question in empirical macroeconomics is whether structural vector autoregressions (SVARs) can reliably discriminate between competing DSGE models. Several recent papers have sug- gested that one reason SVARs may fail to do so is because they are finite-order approximations to infinite-order processes. In this context, we investigate the performance of models that do not suffer from this type of misspecification. We estimate VARMA and state space models using simulated data from a standard economic model and compare true with estimated impulse responses. For our examples, we find that one cannot gain much by using algorithms based on a VARMA rep- resentation. However, algorithms that are based on the state space representation do outperform VARs. Unfortunately, these alternative estimates remain heavily biased and very imprecise. The findings of this paper suggest that the reason SVARs perform weakly in these types of simulation studies is not because they are simple finite-order approximations. Given the properties of the generated data, their fail- ure seems almost entirely due to the use of small samples.

The recent empirical literature that uses Structural Vector Autoregressions (SVAR) has shown that productivity shocks identified using long--run restrictions lead to a persistent and significant decline in hours worked. This evidence calls into question standard RBC models in which a positive technology shock leads to a rise in hours. In this paper, we estimate and test a standard RBC model using Indirect Inference on impulse responses of hours worked after technology and non-technology shocks. We find that this model is not rejected by the data and is able to produce impulse responses in SVAR from simulated data similar to impulse responses in SVAR from actual data. Moreover, technology shocks represent the main contribution to the variance of the business cycle component of output under the estimated DSGE model. Our results suggest that we do not necessarily need DSGE models with a fall in hours to reproduce the results deriving from SVAR models.

The paper examines the macroeconomic consequences of selecting alternative exchange rate regimes of countries in three regions. In particular, it studies whether Austria, the Netherlands, Canada and New Zealand made the right monetary regime choices between 1970 and 2000. We focus on the role of asymmetric shocks as a core determinant for the evaluation of various monetary regimes by studying the impact of a hard peg, a full monetary union, or floating exchange rates (with or without inflation targeting) on selected macroeconomic variables. Estimates of structural VARs are used to ascertain if the countries under review meet the essential ingredients of an optimum currency area (OCA) and thus are candidates for a monetary union. Counterfactual experiments help to study economic outcomes had these countries pursued alternative monetary strategies. We conclude that a floating regime with inflation targeting is best for Canada, a monetary union with Australia is the best course of action for New Zealand, and monetary union is the appropriate choice for the Netherlands while there are reasons to believe that Austria might have been better off with a floating regime, at least for a time. We also find that good monetary policy is not confined to any particular exchange rate regime and that political and institutional factors weigh heavily in this decision.