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on Econometric Time Series |
| By: | Roberto Tatiwa Ferreira; Luiz Ivan de Melo Castelar |
| Abstract: | The present study uses linear and non-linear diffusion index models to produce one-stepahead forecast of quarterly Brazilian GDP growth rate. Diffusion index models are like dynamic factors models. The non-linear diffusion index models used in this work are not only parsimonious ones, but also they try to capture economic cycles using for this goal a Threshold diffusion index model and a Markov-Switching diffusion index model. |
| JEL: | E32 E37 |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:anp:en2005:029&r=ets |
| By: | Siem Jan Koopman; André Lucas; Robert J. Daniels |
| Abstract: | We model 19812002 annual default frequencies for a panel of US firms in different rating and age classes from the Standard and Poor's database. The data is decomposed into a systematic and firm-specific risk component, where the systematic component reflects the general economic conditions and default climate. We have to cope with (i) the shared exposure of each age cohort and rating class to the same systematic risk factor; (ii) strongly non-Gaussian features of the individual time series; (iii) possible dynamics of an unobserved common risk factor; (iv) changing default probabilities over the age of the rating, and (v) missing observations. We propose a non-Gaussian ultivariate state space model that deals with all of these issues simultaneously. The model is estimated using importance sampling techniques that have been modified to a multivariate setting. We show in a simulation study that such a multivariate approach improves the performance of the importance sampler. |
| Keywords: | credit risk; multivariate unobserved component models; importance sampling; non-Gaussian state space models. |
| JEL: | C32 G21 |
| Date: | 2005–11 |
| URL: | http://d.repec.org/n?u=RePEc:dnb:dnbwpp:055&r=ets |
| By: | Lawrence J. Christiano; Martin Eichenbaum; Robert J. Vigfusson |
| Abstract: | We show that the standard procedure for estimating long-run identified vector autoregressions uses a particular estimator of the zero-frequency spectral density matrix of the data. We develop alternatives to the standard procedure and evaluate the properties of these alternative procedures using Monte Carlo experiments in which data are generated from estimated real business cycle models. We focus on the properties of estimated impulse response functions. In our examples, the alternative procedures have better small sample properties than the standard procedure, with smaller bias, smaller mean square error and better coverage rates for estimated confidence intervals. |
| Keywords: | Vector analysis ; Vector autoregression ; Econometric models |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedgif:842&r=ets |
| By: | Todd E. Clark; Kenneth D. West |
| Abstract: | Forecast evaluation often compares a parsimonious null model to a larger model that nests the null model. Under the null that the parsimonious model generates the data, the larger model introduces noise into its forecasts by estimating parameters whose population values are zero. We observe that the mean squared prediction error (MSPE) from the parsimonious model is therefore expected to be smaller than that of the larger model. We describe how to adjust MSPEs to account for this noise. We propose applying standard methods (West (1996)) to test whether the adjusted mean squared error difference is zero. We refer to nonstandard limiting distributions derived in Clark and McCracken (2001, 2005a) to argue that use of standard normal critical values will yield actual sizes close to, but a little less than, nominal size. Simulation evidence supports our recommended procedure. |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedkrw:rwp05-05&r=ets |
| By: | Federico Ravenna |
| Keywords: | Vector Autoreregression; Dynamic Stochastic General Equilibrium Model; Kalman Filter; Business Cycle Shocks |
| JEL: | C13 C22 E32 |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:red:sed005:841&r=ets |
| By: | Lawrence Christiano; Martin Eichenbaum |
| JEL: | E32 C15 C52 |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:red:sed005:902&r=ets |
| By: | M. DOSSCHE; G. EVERAERT |
| Abstract: | Using a structural time series approach we measure different sorts of inflation persistence allowing for an unobserved time-varying inflation target. Unobserved components are identified using Kalman filtering and smoothing techniques. Posterior densities of the model parameters and the unobserved components are obtained in a Bayesian framework based on importance sampling. We find that inflation persistence, expressed by the half life of a shock, can range from 1 quarter in case of a cost-push shock to several years for a shock to long-run inflation expectations or the output gap. |
| Keywords: | Inflation Target, State Space Model, Kalman Filter, Bayesian Analysis |
| JEL: | C11 C22 C32 E31 |
| Date: | 2005–11 |
| URL: | http://d.repec.org/n?u=RePEc:rug:rugwps:05/340&r=ets |
| By: | Derek Bond (University of Ulster); Michael J. Harrison (Department of Economics, Trinity College); Edward J. O'Brien (Department of Economics, Trinity College and Central Bank of Ireland) |
| Abstract: | This paper draws attention to the limitations of the standard unit root/cointegration approach to economic and financial modelling, and to some of the alternatives based on the idea of fractional integration, long memory models, and the random field regression approach to nonlinearity. Following brief explanations of fractional integration and random field regression, and the methods of applying them, selected techniques are applied to a demand for money dataset. Comparisons of the results from this illustrative case study are presented, and conclusions are drawn that should aid practitioners in applied time-series econometrics. |
| JEL: | C22 C52 E41 |
| Date: | 2005–10 |
| URL: | http://d.repec.org/n?u=RePEc:tcd:tcduee:tep20021&r=ets |
| By: | Francesco Bravo |
| Abstract: | This paper develops a new test for a unit root in autoregressive models with serially correlated errors. The test is based on the ``empirical'' Cressie-Read statistic and uses a sieve approximation to eliminate the bias in the asymptotic distribution of the test due to presence of serial correlation. The paper derives the asymptotic distributions of the sieve empirical Cressie-Read statistic under the null hypothesis of a unit root and under a local-to-unity alternative hypothesis. The paper uses a Monte Carlo study to assess the finite sample properties of two well-known members of the proposed test statistic: the empirical likelihood ratio and the Kullback-Liebler distance statistic. The results of the simulations seem to suggest that these two statistics have, in general, similar size and in most cases better power properties than those of standard Augmented Dickey-Fuller tests of a unit root. The paper also analyses the finite sample properties of a sieve bootstrap version of the (square of) the standard Augmented Dickey-Fuller test for a unit root. The results of the simulations seem to indicate that the bootstrap does solve almost completely the size distortion problem, yet at the same time produces a test statistic that has considerably less power than either that of the empirical likelihood or of the Kullback-Liebler distance statistic. |
| Keywords: | Autogregressive approximation; bootstrap; empirical Cressie-Read statistic; generalized empirical likelihood; linear process; unit root test. |
| URL: | http://d.repec.org/n?u=RePEc:yor:yorken:05/33&r=ets |
| By: | Saadet Kýrbaþ Kasman (Department of Economics, Faculty of Business, Dokuz Eylül University); Adnan Kasman (Department of Economics, Faculty of Business, Dokuz Eylül University); Evrim Turgutlu (Department of Economics, Faculty of Business, Dokuz Eylül University) |
| Abstract: | This paper investigates the validity of the Fisher hypothesis using data from 33 developed and developing countries. Conventional cointegration tests do not provide strong evidence on the relationship between nominal interest rates and inflation. Therefore, we use fractional cointegration analysis to test the long-run relationship between the two variables. The results indicate that the long-run relationship between nominal interest rates and inflation do not exist for most countries in the sample when conventional cointegration test is employed. However, fractional cointegration between the two variables is found for a large majority of countries, implying the validity of the Fisher hypothesis. The results also indicate that the equilibrium errors display long memory. |
| Keywords: | Fisher hypothesis, interest rates, fractional cointegration, long memory |
| JEL: | E43 C22 |
| URL: | http://d.repec.org/n?u=RePEc:deu:dpaper:0405&r=ets |
| By: | Zsolt Darvas (Corvinus University, Budapest); Gabor Vadas (Magyar Nemzeti Bank) |
| Abstract: | Decomposing output into trend and cyclical components is an uncertain exercise and depends on the method applied. It is an especially dubious task for countries undergoing large structural changes, such as transition countries. Despite their deficiencies, however, univariate detrending methods are frequently adopted for both policy oriented and academic research. This paper proposes a new procedure for combining univariate detrending techniques which is based on revisions of the estimated output gaps adjusted by the variance of and the correlation among output gaps. The procedure is applied to the study of the similarity of business cycles between the euro area and new EU Member States. |
| Keywords: | combination, detrending, new EU members, OCA, output gap, revision |
| JEL: | C22 E32 |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:mnb:wpaper:2005/05&r=ets |