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on Econometric Time Series |
| By: | Juan Manuel Julio; Norberto Rodríguez; Héctor Manuel Zárate |
| Abstract: | In this paper we estimated a volatility model for COP/US under two different samples, one containing the information before the “discretional interventions” started, and the other using the whole sample. We use a nonparametric approach to estimate the mean and “volatility smile” return functions using daily data. For the pre-interventions sample, we found a nonlinear expected return function and, surprisingly, a nonsymmetric “volatility smile”. These lack of linearity and symmetry are related to absolute returns above 1,5% and 1,0%, respectively. We also found that the “discretional interventions” did not shift the mean response function, but moved the expected returns along the line towards the required levels. In contrast, the “volatility smile” tends to increase in a non-symmetric way after accounting for “discretional interventions”. The Sep/29/2004 announcement does not seem to have had any effect on the expected conditional mean or variance functions, but the Dec/17/2004 announcement seems to be related to non-symmetric effects on the volatility smile. We concluded that the announcement of discretional intervention by the monetary authority was more efficient when time and amount were unannounced. |
| Keywords: | Volatility Smile, |
| JEL: | C14 |
| Date: | 2005–07–30 |
| URL: | http://d.repec.org/n?u=RePEc:col:000070:001226&r=ets |
| By: | Marco Avarucci; Domenico Marinucci |
| Abstract: | In this paper we consider polynomial cointegrating relationships among stationary processes with long range dependence. We express the regression functions in terms of Hermite polynomials and we consider a form of spectral regression around frequency zero. For these estimates, we establish consistency by means of a more general result on continuously averaged estimates of the spectral density matrix at frequency zero. |
| Date: | 2005–09 |
| URL: | http://d.repec.org/n?u=RePEc:cte:werepe:we055123&r=ets |
| By: | Wenceslao Gonzalez-Manteiga; Maria J. Lombardia; Isabel Molina; Domingo Morales; Laureano Santamaria |
| Abstract: | A Multivariate Fay-Herriot model is used to aid the prediction of small area parameters of dependent variables with sample data aggregated to area level. The empirical best linear unbiased predictor of the parameter vector is used, and an approximation of the elements of the mean cross product error matrix is obtained by an extension of the results of Prasad and Rao (1990) to the multiparameter case. Three different bootstrap approximations of those elements are introduced, and a simulation study is developed in order to compare the efficiency of all presented approximations, including a comparison under lack of normality. Further, the number of replications needed for the bootstrap procedures to get stabilized are studied. |
| Date: | 2005–09 |
| URL: | http://d.repec.org/n?u=RePEc:cte:wsrepe:ws054910&r=ets |
| By: | Meitz, Mika (Dept. of Economic Statistics, Stockholm School of Economics) |
| Abstract: | We consider a family of GARCH(1,1) processes introduced in He and Teräsvirta (1999a). This family contains various popular GARCH models as special cases. A necessary and sufficient condition for the existence of a strictly stationary solution is given. |
| Keywords: | GARCH; strict stationarity; Lyapunov exponent |
| JEL: | C22 |
| Date: | 2005–07–23 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:hastef:0601&r=ets |
| By: | González, Andrés (Dept. of Economic Statistics, Stockholm School of Economics); Teräsvirta, Timo (Dept. of Economic Statistics, Stockholm School of Economics) |
| Abstract: | In this paper we use Monte Carlo testing techniques for testing linearity against the smooth transition models. The Monte Carlo approach allows us to introduce a new test that differs from the tests existing in the literature in two respects. First, the test is exact in the sense that the probability of rejecting the null when it is true is always less that or equal to the nominal size of the test. Second, the test is not based on an auxiliary regression obtained by replacing the model under the alternative by approximations based on a Taylor expansion. We also apply Monte Carlo testing methods for size-correcting the test proposed by Luukkonen Saikkonen and Teräsvirta (1988). Simulated annealing is used in computing values of the test statistics. The results show that the power loss implied by the auxiliary regression based test is nonexistent compared to a supremum-based test but is more substantial when compared to the other three tests under consideration. |
| Keywords: | Exact test; Monte Carlo test; Sequential Monte Carlo test; Nonlinear modelling; Panel smooth transition regression |
| JEL: | C12 C15 C52 |
| Date: | 2005–08–17 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:hastef:0603&r=ets |
| By: | González, Andrés (Dept. of Economic Statistics, Stockholm School of Economics); Teräsvirta, Timo (Dept. of Economic Statistics, Stockholm School of Economics); van Dijk, Dick (Econometric Institute, Erasmus University Rotterdam) |
| Abstract: | We develop a non-dynamic panel smooth transition regression model with fixed individual effects. The model is useful for describing heterogenous panels, with regression coefficients that vary across individuals and over time. Heterogeneity is allowed for by assuming that these coefficients are continuous functions of an observable variable through a bounded function of this variable and fluctuate between a limited number (often two) of “extreme regimes”. The model can be viewed as a generalization of the threshold panel model of Hansen (1999). We extend the modelling strategy for univariate smooth transition regression models to the panel context. This comprises of model specification based on homogeneity tests, parameter estimation, and diagnostic checking, including tests for parameter constancy and no remaining nonlinearity. The new model is applied to describe firms' investment decisions in the presence of capital market imperfections. |
| Keywords: | financial constraints; heterogeneous panel; invesatment; misspecification test; nonlinear modelling panel data; smooth transition model |
| JEL: | C12 C23 C52 G31 G32 |
| Date: | 2005–08–17 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:hastef:0604&r=ets |
| By: | Heather M. Anderson; Chin Nam Low; Ralph Snyder |
| Abstract: | A well known property of the Beveridge Nelson decomposition is that the innovations in the permanent and transitory components are perfectly correlated. We use a single source of error state space model to exploit this property and perform a Beveridge Nelson decomposition. The single source of error state space approach to the decomposition is computationally simple and it incorporates the direct estimation of the long-run multiplier. |
| JEL: | C22 C51 E32 |
| Date: | 2005–05 |
| URL: | http://d.repec.org/n?u=RePEc:pas:camaaa:2005-11&r=ets |
| By: | Graham Elliott; Ivana Komunjer; Allan Timmermann |
| Abstract: | Empirical studies using survey data on expectations have frequently observed that forecasts are biased and have concluded that agents are not rational. We establish that existing rationality tests are not robust to even small deviations from symmetric loss and hence have little ability to tell whether the forecaster is irrational or the loss function is asymmetric. We quantify the exact trade-off between forecast inefficiency and asymmetric loss leading to identical outcomes of standard rationality tests and explore new and more general methods for testing forecast rationality jointly with flexible families of loss functions that embed quadratic loss as a special case. An empirical application to survey data on forecasts of nominal output growth demonstrates the empirical significance of our results and finds that rejections of rationality may largely have been driven by the assumption of symmetric loss. |
| Date: | 2005–05 |
| URL: | http://d.repec.org/n?u=RePEc:pas:camaaa:2005-14&r=ets |
| By: | Shrestha, Min B. (University of Wollongong); Chowdhury, Khorshed (University of Wollongong) |
| Abstract: | Testing for unit roots has special significance in terms of both economic theory and the interpretation of estimation results. As there are several methods available, researchers face method selection problem while conducting the unit root test on time series data in the presence of structural break. This paper proposes a sequential search procedure to determine the best test method for each time series. Different test methods or models may be appropriate for different time series. Therefore, instead of sticking to one particular test method for all the time series under consideration, selection of a set of mixed methods is recommended for obtaining better results. |
| Keywords: | Time Series, Stationarity, Unit Root Test, Structural Break, Sequential Procedure |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:uow:depec1:wp05-06&r=ets |