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on Econometric Time Series |
| By: | Shu-Ping Shi (The Australian National University); Peter C. B. Phillips (Yale University, University of Auckland, University of Southampton and Singapore Management University); Jun Yu (Singapore Management University and Hong Kong Institute for Monetary Research) |
| Abstract: | Right-tailed unit root tests have proved promising for detecting exuberance in economic and financial activities. Like left-tailed tests, the limit theory and test performance are sensitive to the null hypothesis and the model specification used in parameter estimation. This paper aims to provide some empirical guidelines for the practical implementation of right-tailed unit root tests, focusing on the sup ADF test of Phillips, Wu and Yu (2011), which implements a right-tailed ADF test repeatedly on a sequence of forward sample recursions. We analyze and compare the limit theory of the sup ADF test under different hypotheses and model specifications. The size and power properties of the test under various scenarios are examined in simulations and some recommendations for empirical practice are given. An empirical application to Nasdaq data reveals the practical importance of model specification on test outcomes. |
| Keywords: | Unit Root Test, Mildly Explosive Process, Recursive Regression, Size and Power |
| JEL: | C15 C22 |
| Date: | 2011–06 |
| URL: | http://d.repec.org/n?u=RePEc:hkm:wpaper:172011&r=ets |
| By: | Luc Bauwens (Université catholique de Louvain, CORE); Gary Koop (University of Strathclyde); Dimitris Korobilis (Université catholique de Louvain, CORE); Jeroen V.K. Rombouts (Institute of Applied Economics at HEC Montréal, CIRANO, CIRPEE; Université catholique de Louvain, CORE) |
| Abstract: | This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. We find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling window based forecasts perform well. |
| Keywords: | Forecasting, change-points, Markov switching, Bayesian inference |
| JEL: | C11 C22 C53 |
| Date: | 2011–07 |
| URL: | http://d.repec.org/n?u=RePEc:rim:rimwps:38_11&r=ets |
| By: | Thanasis Stengos (University of Guelph); M. Ege Yazgan (Istanbul Bilgi University) |
| Abstract: | In this paper, we examine the convergence hypothesis using a long memory framework that allows for structural breaks and the non reliance on a benchmark country. We find that even though the long memory framework of analysis is much richer than the simple I(1)=I(0) alternative, a simple absolute divergence and rapid convergence dichotomy produced by the latter is sufficient to capture the behavior of the gaps in per capita GDP levels and growth rates results respectively. This is in contrast to the findings of Dufrénot, Mignon and Naccache (2009) who found strong evidence of long memory for output gaps. The speed of convergence captured by the estimated long memory parameter d, is explained by differences in physical and human capital as well as fiscal discipline characteristics of economic policies pursued by different countries. |
| Keywords: | growth convergence, long memory |
| JEL: | C32 O47 |
| Date: | 2011–07 |
| URL: | http://d.repec.org/n?u=RePEc:rim:rimwps:34_11&r=ets |
| By: | Miguel A. G. Belmonte (University of Strathclyde); Gary Koop (University of Strathclyde); Dimitris Korobilis (Université Catholique de Louvain) |
| Abstract: | In this paper, we forecast EU-area inflation with many predictors using time-varying parameter models. The facts that time-varying parameter models are parameter-rich and the time span of our data is relatively short motivate a desire for shrinkage. In constant coefficient regression models, the Bayesian Lasso is gaining increasing popularity as an effective tool for achieving such shrinkage. In this paper, we develop econometric methods for using the Bayesian Lasso with time-varying parameter models. Our approach allows for the coefficient on each predictor to be: i) time varying, ii) constant over time or iii) shrunk to zero. The econometric methodology decides automatically which category each coefficient belongs in. Our empirical results indicate the benefits of such an approach. |
| Keywords: | hierarchical prior; time-varying parameters; Bayesian Lasso |
| JEL: | C11 C52 E37 E47 |
| Date: | 2011–07 |
| URL: | http://d.repec.org/n?u=RePEc:rim:rimwps:35_11&r=ets |
| By: | Fossati, Sebastian (University of Alberta, Department of Economics) |
| Abstract: | The issue of testing for a unit root allowing for a structural break in the trend function is considered. The focus is on the construction of more powerful tests using the information in relevant multivariate data sets. The proposed test adopts the GLS detrending approach and uses correlated stationary covariates to improve power. As it is standard in the literature, the break date is treated as unknown. Asymptotic distributions are derived and a set of asymptotic and nite sample critical values are tabulated. Asymptotic local power functions show that power gains can be large. Finite sample results show that the test exhibits small size distortions and power that can be far beyond what is achievable by univariate tests. |
| Keywords: | unit root test; CLS detrending; structural break |
| JEL: | C22 C32 |
| Date: | 2011–05–01 |
| URL: | http://d.repec.org/n?u=RePEc:ris:albaec:2011_010&r=ets |
| By: | Axel Groß-Klußmann; Nikolaus Hautsch |
| Abstract: | We introduce a long memory autoregressive conditional Poisson (LMACP) model to model highly persistent time series of counts. The model is applied to forecast quoted bid-ask spreads, a key parameter in stock trading operations. It is shown that the LMACP nicely captures salient features of bid-ask spreads like the strong autocorrelation and discreteness of observations. We discuss theoretical properties of LMACP models and evaluate rolling window forecasts of quoted bid-ask spreads for stocks traded at NYSE and NASDAQ. We show that Poisson time series models significantly outperform forecasts from ARMA, ARFIMA, ACD and FIACD models. The economic significance of our results is supported by the evaluation of a trade schedule. Scheduling trades according to spread forecasts we realize cost savings of up to 13 % of spread transaction costs. |
| Keywords: | Bid-ask spreads, forecasting, high-frequency data, stock market liquidity, count data time series, long memory Poisson autoregression |
| JEL: | G14 C32 |
| Date: | 2011–07 |
| URL: | http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2011-044&r=ets |
| By: | Marek Jarocinski; Albert Marcet |
| Abstract: | We propose a benchmark prior for the estimation of vector autoregressions: a prior about initial growth rates of the modelled series. We first show that the Bayesian vs frequentist small sample bias controversy is driven by different default initial conditions. These initial conditions are usually arbitrary and our prior serves to replace them in an intuitive way. To implement this prior we develop a technique for translating priors about observables into priors about parameters. We find that our prior makes a big difference for the estimated persistence of output responses to monetary policy shocks in the United States. |
| Keywords: | Vector autoregression, initial condition, bayesian estimation, prior about growthrate, monetary policy shocks, small sample distribution, bias correction |
| JEL: | C11 C22 C32 |
| Date: | 2011–07 |
| URL: | http://d.repec.org/n?u=RePEc:cep:cepdps:dp1061&r=ets |