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on Econometric Time Series |
| By: | Dominique Guegan (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris); Patrick Rakotomarolahy (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I) |
| Abstract: | An empirical forecast accuracy comparison of the non-parametric method, known as multivariate Nearest Neighbor method, with parametric VAR modelling is conducted on the euro area GDP. Using both methods for nowcasting and forecasting the GDP, through the estimation of economic indicators plugged in the bridge equations, we get more accurate forecasts when using nearest neighbor method. We prove also the asymptotic normality of the multivariate k-nearest neighbor regression estimator for dependent time series, providing confidence intervals for point forecast in time series. |
| Keywords: | Forecast, economic indicators, GDP, Euro area, VAR, multivariate k-nearest neighbor regression, asymptotic normality. |
| Date: | 2010–07 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-00505165_v1&r=ets |
| By: | Dominique Guegan (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris); Zhiping Lu (ECNU - East China Normal University) |
| Abstract: | Foreign exchange rate plays an important role in international finance. This paper examines unit roots and the long range dependence of 23 foreign exchange rates using Robinson's (1994) test, which is one of the most efficient tests when testing fractional orders of seasonal/cyclical long memory processes. Monte Carlo simulations are carried out to explore the accuracy of the test before implementing the empirical applications. |
| Keywords: | Long memory processes ; test ; Monte Carlo Simulations ; unit roots ; exchange rate |
| Date: | 2010–06 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-00505117_v1&r=ets |
| By: | António Rua |
| Abstract: | It has been acknowledged that wavelets can constitute a useful tool for forecasting in economics. Through a wavelet multiresolution analysis, a time series can be decomposed into different time-scale components and a model can be fitted to each component to improve the forecast accuracy of the series as a whole. Up to now, the literature on forecasting with wavelets has mainly focused on univariate modelling. On the other hand, in a context of growing data availability, a line of research has emerged on forecasting with large datasets. In particular, the use of factor-augmented models have become quite widespread in the literature and among practitioners. The aim of this paper is to bridge the two strands of the literature. A wavelet approach for factor-augmented forecasting is proposed and put to test for forecasting GDP growth for the major euro area countries. The results show that the forecasting performance is enhanced when wavelets and factor-augmented models are used together. |
| JEL: | C22 C40 C53 |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:ptu:wpaper:w201007&r=ets |
| By: | Paulo M.M. Rodrigues; Antonio Rubia |
| Abstract: | This paper discusses the asymptotic and finite-sample properties of CUSUM-based tests for detecting structural breaks in volatility in the presence of stochastic contamination, such as additive outliers or measurement errors. This analysis is particularly relevant for financial data, on which these tests are commonly used to detect variance breaks. In particular, we focus on the tests by Inclán and Tiao [IT] (1994) and Kokoszka and Leipus [KL] (1998, 2000), which have been intensively used in the applied literature. Our results are extensible to related procedures. We show that the asymptotic distribution of the IT test can largely be affected by sample contamination, whereas the distribution of the KL test remains invariant. Furthermore, the break-point estimator of the KL test renders consistent estimates. In spite of the good large-sample properties of this test, large additive outliers tend to generate power distortions or wrong break-date estimates in small samples. |
| JEL: | C12 C15 C52 |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:ptu:wpaper:w201011&r=ets |
| By: | Miguel de Carvalho; K. Feridum Turkman; António Rua |
| Abstract: | Considerable attention has been devoted to the statistical analysis of extreme events. Classical peaks over threshold methods are a popular modelling strategy for extreme value statistics of stationary data. For nonstationary series a variant of the peaks over threshold analysis is routinely applied using covariates as a means to overcome the lack of stationarity in the series of interest. In this paper we concern ourselves with extremes of possibly nonstationary processes. Given that our approach is, in some way, linked to the celebrated Box-Jenkins method, we refer to the procedure proposed and applied herein as Box-Jenkins-Pareto. Our procedure is particularly appropriate for settings where the parameter covariate model is non-trivial or when well qualified covariates are simply unavailable. We apply the Box-Jenkins-Pareto approach to the weekly number of unemployment insurance claims in the US and exploit the connection between threshold exceedances and the US business cycle. |
| JEL: | C16 C50 E32 |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:ptu:wpaper:w201003&r=ets |
| By: | António Rua |
| Abstract: | The measurement of comovement among variables has a long tradition in the economic and financial literature. Traditionally, comovement is assessed in the time domain through the well-known correlation coefficient while the evolving properties are investigated either through a rolling window or by considering non-overlapping periods. More recently, Croux, Forni and Reichlin [Review of Economics and Statistics 83 (2001)] have proposed a measure of comovement in the frequency domain. While it allows to quantify the comovement at the frequency level, such a measure disregards the fact that the strength of the comovement may vary over time. Herein, it is proposed a new measure of comovement resorting to wavelet analysis. This wavelet-based measure allows one to assess simultaneously the comovement at the frequency level and over time. In this way, it is possible to capture the time and frequency varying features of comovement within a unified framework which constitutes a refinement to previous approaches. |
| JEL: | C40 E32 |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:ptu:wpaper:w201001&r=ets |