
on Econometric Time Series 
By:  Richard Y. Chen 
Abstract:  This paper presents the nonparametric inference for nonlinear volatility functionals of general multivariate It\^o semimartingales, in highfrequency and noisy setting. Preaveraging and truncation enable simultaneous handling of noise and jumps. Secondorder expansion reveals explicit biases and a pathway to bias correction. Estimators based on this framework achieve the optimal convergence rate. A class of stable central limit theorems are attained with estimable asymptotic covariance matrices. This paper form a basis for infill asymptotic results of, for example, the realized Laplace transform, the realized principal component analysis, the continuoustime linear regression, and the generalized method of integrated moments, hence helps to extend the application scopes to more frequently sampled noisy data. 
Date:  2018–10 
URL:  http://d.repec.org/n?u=RePEc:arx:papers:1810.04725&r=all 
By:  Fabio Franco (University of Rome "Tor Vergata") 
Abstract:  Particle Markov Chain Monte Carlo (PMCMC) is a widely used method to handle estimation problem in the context of nonlinear structural dynamic models whose likelihood function is analytically intractable. PMCMC can be constructed upon a GMM likelihood representation when one does not want to rely on the structural form of the measurement equation (Gallant et al 2016). It only requires to compute moment conditions available from the structural model. However, particle filter with GMM may suffer from high degeneracy of particle weights which severely affects the accuracy of Monte Carlo approximations and in turn Markov Chain Monte Carlo estimates. This work is concerned with revising particle GMM algorithm as proposed in Gallant et al in order to reduce the depletion problem. Estimation results of stochastic volatility models show that the efficient block sampling strategy as proposed in Doucet et al (2006) can outperform particle GMM and in turn deliver more reliable MCMC estimates. Auxiliary particle filter (Doucet et al, 2011) is also proposed as an alternative strategy to the block sampling approach. However, in the intended experiments it does not seem to be very effective. Thus some of the assumptions needed to estimate structural nonlinear state space models can be weakened and requiring only available moment conditions without affecting dramatically the conclusions. 
Keywords:  Particle filter, Kalman filter, MCMC, Generalized Method of Moments, State Space, nonlinear Structural Dynamic model, Stochastic Volatility 
JEL:  C4 C8 
Date:  2019–11–18 
URL:  http://d.repec.org/n?u=RePEc:rtv:ceisrp:473&r=all 
By:  António Afonso; Florence Huart; João Tovar Jalles; Piotr Stanek 
Abstract:  We assessthe sustainability of external imbalances for EUcountriesusing panel stationarity tests of Current Account(CA) balancetoGDP ratiosand panel cointegration of exports and imports of goods and services, for the period 1970Q12015Q4. We find that: i) the country panel isnonstationary; ii) crosssectional dependence plays an important role; iii) there is nonstationarity of the CA, imports, and exportswith crosssectional panel dependenceand multiple structural breaks; iv) however, there is a stable longrun relationship between exports and imports in the panel.Hence, trade imbalances can be less unsustainable but this is not sufficient to make current account imbalances sustainable. 
Keywords:  current account, exports, imports, unit roots, cointegration 
JEL:  C23 F32 F41 
Date:  2019–11 
URL:  http://d.repec.org/n?u=RePEc:ise:remwps:wp0992019&r=all 
By:  Juan Carlos Cuestas (Department of Economics, Universitat Jaume I, Castellón, Spain) 
Abstract:  In this paper we aim to analyse the evolution of the current account as percentage of the GDP for a group of Central and Eastern European Countries. Instead of only analysing the variable for unit roots, we go a step further and test for different speeds of mean reversion dependent on break dates endogenously determined. We apply the Bai and Perron method to find that although most countries have managed to balance their current account but some of them should keep an eye on a low speed of mean reversion and deviating time trend from balance. 
Keywords:  debt, Central and Eastern Europe, structural breaks, European integration 
JEL:  C22 F15 F32 
Date:  2019 
URL:  http://d.repec.org/n?u=RePEc:jau:wpaper:2019/10&r=all 
By:  Chavleishvili, Sulkhan; Manganelli, Simone 
Abstract:  We introduce a structural quantile vector autoregressive (VAR) model. Unlike standard VAR which models only the average interaction of the endogenous variables, quantile VAR models their interaction at any quantile. We show how to estimate and forecast multivariate quantiles within a recursive structural system. The model is estimated using real and financial variables. The dynamic properties of the system change across quantiles. This is relevant for stress testing exercises, whose goal is to forecast the tail behavior of the economy when hit by large financial and real shocks. JEL Classification: C32, C53, E17, E32, E44 
Keywords:  growth at risk, regression quantiles, structural VAR 
Date:  2019–11 
URL:  http://d.repec.org/n?u=RePEc:ecb:ecbwps:20192330&r=all 
By:  Guglielmo Maria Caporale; Luis A. GilAlana; Carlos Poza 
Abstract:  This paper uses a modelling framework which includes two singularities (or poles) in the spectral density function, one corresponding to the longrun (zero) frequency and the other to the cyclical (nonzero) frequency. The adopted specification is very general, since it allows for fractional integration with stochastic patterns at the zero and cyclical frequencies and includes both long and short memory components. The cyclical patterns are modelled using Gegenbauer processes. This model is estimated using monthly data for five European stock market indices (DAX30, FTSE100, CAC40, FTSE MIB40, IBEX35) from January 2009 to January 2019. The results indicate that the series are highly persistent at the longrun frequency, but they are not supportive of the existence of cyclical stochastic structures in the European financial markets. The only clear evidence of a stochastic cycle is obtained in the case of France under the assumption of white noise disturbances; in all other cases, there is no evidence of cycles. 
Keywords:  European stock markets, long run behavior, cycles, persistence 
JEL:  C22 C58 
Date:  2019 
URL:  http://d.repec.org/n?u=RePEc:ces:ceswps:_7943&r=all 
By:  Mirela Miescu; Haroon Mumtaz 
Abstract:  We show that the contemporaneous and longer horizon impulse responses estimated using smallscale Proxy structural vector autoregressions (SVARs) can be severely biased in the presence of information insufficiency. Instead, we recommend the use of a Proxy Factor Augmented VAR (FAVAR) model that remains robust in the presence of this problem. In an empirical exercise, we demonstrate that this issue has important consequences for the estimated impact of monetary policy shocks in the US. We find that the impulse responses of real activity and prices estimated using a Proxy FAVAR are substantially larger and more persistent than those suggested by a smallscale Proxy SVAR. 
Keywords:  information sufficiency, dynamic factor models, instrumental variables, monetary policy, structural VAR 
JEL:  C36 C38 E52 
Date:  2019 
URL:  http://d.repec.org/n?u=RePEc:lan:wpaper:280730188&r=all 
By:  Martin Bruns (University of East Anglia) 
Abstract:  Structural VAR models require two ingredients: (i) Informational sufficiency, and (ii) a valid identification strategy. These conditions are unlikely to be met by smallscale recursively identified VAR models. I propose a Bayesian Proxy FactorAugmented VAR (BPFAVAR) to combine a large information set with an identification scheme based on an external instrument. In an application to monetary policy shocks I find that augmenting a standard smallscale Proxy VAR by factors from a large set of financial variables changes the model dynamics and delivers price responses which are more in line with economic theory. A second application shows that an exogenous increase in uncertainty affects disaggregated investment series more negatively than consumption series. 
Keywords:  Dynamic factor models, external instruments, monetary policy, uncertainty shocks 
JEL:  C38 E60 
Date:  2019–08–16 
URL:  http://d.repec.org/n?u=RePEc:uea:ueaeco:2019_03&r=all 
By:  Federico Bassi (CEPN  Centre d'Economie de l'Université Paris Nord  UP13  Université Paris 13  USPC  Université Sorbonne Paris Cité  CNRS  Centre National de la Recherche Scientifique) 
Abstract:  Most empirical studies provide evidence that the rate of capacity utilization is stable around a constant Nonaccelerating inflation rate of capacity utilization (NAIRCU). Nevertheless , available statistical series of the rate of capacity utilization, which is unobservable, are constructed by assuming that it is stable over time. Hence, the stability of the NAIRCU is an artificial artefact. In this paper, we develop a method to estimate the rate of capacity utilization without imposing stability constraints. Partially inspired to the Production function methodology (PFM), we estimate the parameters of a production function by imposing aggregate correlations between the rate of capacity utilization and a set of macroeconomic variables, namely investment , labor productivity and unemployment. Our results show that the NAIRCU is not a constant rate but a nonstationary timevarying trend, and that chronicle underutilization of capacity with stable inflation is a plausible equilibrium. Hence, persistent deviations of GDP might reflect persistent shocks to capacity utilization rather than exogenous shocks to total factor productivity. As a corollary, expansionary demand policies do not necessarily create permanent inflationary pressures if the NAIRCU is below fullcapacity output, namely in postcrisis periods. Abstract Most empirical studies provide evidence that the rate of capacity utilization is stable around a constant Nonaccelerating inflation rate of capacity utilization (NAIRCU). Nevertheless, available statistical series of the rate of capacity utilization, which is unobservable, are constructed by assuming that it is stable over time. Hence, the stability of the NAIRCU is an artificial artefact. In this paper, we develop a method to estimate the rate of capacity utilization without imposing stability constraints. Partially inspired to the Production function methodology (PFM), we estimate the parameters of a production function by imposing aggregate correlations between the rate of capacity utilization and a set of macroeconomic variables, namely investment, labor productivity and unemployment. Our results show that the NAIRCU is not a constant rate but a nonstationary timevarying trend, and that chronicle underutilization of capacity with stable inflation is a plausible equilibrium. Hence, persistent deviations of GDP might reflect persistent shocks to capacity utilization rather than exogenous shocks to total factor productivity. As a corollary, expansionary demand policies do not necessarily create permanent inflationary pressures if the NAIRCU is below fullcapacity output, namely in postcrisis periods. 
Keywords:  Capacity utilization,NAIRCU,Potential GDP,Hysteresis,Secular stagnation 
Date:  2019–11–12 
URL:  http://d.repec.org/n?u=RePEc:hal:cepnwp:hal02360456&r=all 