1,721,000 research outputs found
Heteroskedastic proxy-SVARs
No full textIdentification strategies are discussed for Structural Vector Autoregressions (SVARs) which combine the use of external instruments, the so-called proxy-SVAR or SVAR-IV approach with the heteroskedasticity found in the data, the so-called identification-via-heteroskedasticity approach. The focus in on the case in which r valid instruments are used to identify g>=1 structural shocks of interest, with r>=g, and there are m structural breaks in the VAR error covariance matrix which give rise to m+1 volatility regimes. It is shown that the combination of the two approaches enhances identification possibilities for practitioners and produce overidentified testable models, denoted HP-SVARs. Two types of heteroskedasticity are considered. In one case, the structural breaks do not affect the on-impact coefficients so that the Impulse Response Functions (IRFs) are constant across volatillity regimes. In the other case, the structural breaks affect the on-impact coefficients and thee IRFs are regime-dependent. General identification results for HP-SVARs are derived for these two cases. Estimation can be carried out through maximum likelihood
Frequentist Evaluation of Small DSGE Models
Full text linkThis paper proposes a new evaluation approach for the class of small-scale `hybrid' New Keynesian Dynamic Stochastic General Equilibrium (NK-DSGE) models typically used in monetary policy and business cycle analysis. The empirical assessment of the NK-DSGE model is based on a conditional sequence of likelihood-based tests conducted in a Vector Autoregressive (VAR) system, in which both the low and high frequency implications of the model are addressed in a coherent framework. If some of the low frequency behavior of the original time series of the model can be approximated by non-stationary processes, stationarity must be imposed by removing the stochastic trends. This gives rise to a set of recoverable unit roots/cointegration restrictions, in addition to the short-run cross-equation restrictions. The procedure is based on the sequence `LR1→LR2→LR3', where LR1 is the cointegration rank test, LR2 the cointegration matrix test and LR3 the cross-equation restrictions test: LR2 is computed conditional on LR1 and LR3 is computed conditional on LR2. The type-I errors of the three tests are set consistently with a pre-fixed overall nominal significance level. A bootstrap analogue of the testing strategy is proposed in small samples. We show that the information stemming from the individual tests can be used constructively to uncover which features of the data are not captured by the theoretical model and thus to rectify, when possible, the specification. We investigate the empirical size properties of the proposed testing strategy by a Monte Carlo experiment and show the empirical usefulness of our approach by estimating and testing a monetary business cycle NK-DSGE model using U.S. quarterly data
Essays on financial stability, credit dynamics and policy challenges
Full text linkOver the last two decades the intensity of credit standards' tightening during economic contractions has exceeded their easing during expansions among euro area banks. This mechanism is fed by the boom-bust cycle of credit that, as much research has shown, is linked to financial instability with large effects on the real economy. We build a small scale nonlinear quadratic (NLQ) model to study how credit feedback can affect the overall adjustment path of the economy towards some steady state, when the central bank solve a infi nite-horizon decision problem where the policy rate is allowed to also be zero or negative. Then, we estimate local projections for a supervisory shock hitting banks' credit standards and propose a new external instrument to identify its dynamic causal impact on the real and fi nancial sector. We find that the regime dependence reveals important information to policy makers to implement macroprudential measures.This paper identi es credit booms in 11 Euro Area countries by tracking private loans from the banking sector. The events are associated with both fi nancial crises and specfii c macro fluctuations, but the standard identifi cation through threshold methods does not allow to catch credit booms in real time data. Thus, an early warning model is employed to predict the explosive dynamics of credit through several macro- financial indicators. The model catches a large part of the in-sample events and signals correctly both the global fi nancial crisis and the sovereign debt crisis in an out-of-sample setting by issuing signals in real-time data. Moreover, while tranquil booms are driven by global dynamics, crisis-booms are related to the resilience of domestic banking systems to adverse financial shocks. The results suggest an ex-ante policy intervention can avoid dangerous credit booms by focusing on the solvency of the domestic banking system and financial market's overheating
Simulation-based tests of forward-looking models under VAR learning dynamics
No full textIn this paper we propose simulation-based techniques to investigate the finite sample performance of likelihood ratio (LR) tests for the nonlinear restrictions that arise when a class of forward-looking (FL) models, typically used in monetary policy analysis, is evaluated with Vector Autoregressive (VAR) models. We consider both `one-shot' tests and sequences of tests under a particular form of adaptive learning dynamics, where `boundedly rational' agents use VARs recursively to update their beliefs. The analysis is based on the comparison of the likelihood of the unrestricted and restricted VAR, and the p-values associated with the LR statistics are computed by Monte Carlo simulation. We also address the case where the variables of the FL model are approximated as non-stationary cointegrated processes. Application to the New Keynesian Phillips Curve in the euro area shows that the FL model of inflation dynamics is not rejected once the suggested simulation-based tests are applied. The result is robust to specification of the VAR as a stationary (albeit highly persistent) or cointegrated system. However, in the second case the imposition of cointegration restrictions changes the estimated degree of price stickiness
Evaluating the New Keynesian Phillips Curve under VAR-based learning
Full text linkThis paper proposes the evaluation of the New Keynesian Phillips Curve (NKPC) under a new learning mechanism where VAR learning dynamics is combined with the idea of testing the validity of the forward-looking model of inflation dynamics. The key assumption is that agents’ perceived law of motion is a VAR whose parameters are updated by recursive
least squares. Differently from standard adaptive learning methods, agents test sequentially the cross-equation restrictions that the NKPC imposes on the VAR as the information set increases. When the restrictions are not rejected agents learn under the restricted system and exploit the cross-equation restrictions to forecast inflation. It is thus possible to check how much and in which periods agents’ beliefs are consistent with the restrictions of the theory. The empirical analysis on quarterly data on the euro area shows that the NKPC with negligible backward-looking parameter is not rejected when the model is evaluated over the period 1984-2005 under the proposed learning mechanism. The result, however, is not fully robust to specifications based on non stationary variables and points out that learning may represent a remarkable source of euro area inflation persistence but not its only determinant
Simulation-based tests of forward-looking models under VAR learning dynamics
No full textIn this paper we propose a simulation-based technique to investigate the finite sample performance of likelihood ratio (LR) tests for the nonlinear restrictions that arise when a class of forward-looking (FL) models typically used in monetary policy analysis is evaluated with vector autoregressive (VAR) models. We consider ‘one-shot’ tests to evaluate the FL model under the rational expectations hypothesis and sequences of tests obtained under the adaptive learning hypothesis. The analysis is based on a comparison between the unrestricted and restricted VAR likelihoods, and the p-values associated with the LR test statistics are computed by Monte Carlo simulation. We also address the case where the variables of the FL model can be approximated as non-stationary cointegrated processes. Application to the ‘hybrid’ New Keynesian Phillips Curve (NKPC) in the euro area shows that (i) the forward-looking component of inflation dynamics is much larger than the backward-looking component and (ii) the sequence of restrictions implied by the cointegrated NKPC under learning dynamics is not rejected over the monitoring period 1984–2005
Co-integration rank determination in partial systems using information criteria
Full text linkWe investigate the asymptotic and finite sample properties of the most widely used information criteria for co-integration rank determination in ‘partial’ systems, i.e. in co-integrated Vector Autoregressive (VAR) models where a sub-set of variables of interest is modeled conditional on another sub-set of variables. The asymptotic properties of the Akaike Information Criterion (AIC), the Bayesian Information Criterion (BIC) and the Hannan-Quinn Information Criterion (HQC) are established, and consistency of BIC and HQC is proved. No- tably, consistency of BIC and HQC is robust to violations of the hypothesis of weak exogeneity of the conditioning variables with respect to the co-integration parameters. More precisely, BIC and HQC recover the true co-integration rank from the partial system analysis also when the conditional model does not convey all information about the co-integration parameters. This result opens up interesting possibilities for practitioners who can determine the co-integration rank in partial systems without being concerned with the weak exogeneity of the conditioning variables. A Monte Carlo experiment which considers large systems as data generating process shows that BIC and HQC applied in partial systems perform reasonably well in small samples and comparatively better than ‘traditional’ approaches for co-integration rank determination. We further show the usefulness of our approach and the benefits of the conditional system anal- ysis to co-integration rank determination with two empirical illustrations, both based on the estimation of VAR systems on U.S. quarterly data. Overall, our analysis clearly shows that the gains of combining information criteria with partial systems analysis are indisputable
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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