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on Econometric Time Series |
| By: | Luis F. Martins; Paulo M.M. Rodrigues |
| Abstract: | In this paper we propose an approach to detect persistence changes in fractionally integrated models based on recursive forward and backward estimation of the Breitung and Hassler (2002) test. This procedure generalises to fractionally integrated processes the approaches of Leybourne, Kim, Smith and Newbold (2003) and Leybourne and Taylor (2003),which are ADF and seasonal unit root type tests, respectively, for the conventional intenger value context. Asymptotic results are derived and the performance of the new procedures evaluated in a Monte Carlo exercise. The ?nite sample size and power performance of the procedures are very encouraging and compare very favourably to available tests, such as those recently proposed by Hassler and Sheithauer (2009) and Sibbertsen and Kruse (2007).We also apply the test statistics introduced to several world inflation rates and and evidence of change in persistence in most series.<br> |
| JEL: | C20 C22 |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:ptu:wpaper:w201030&r=ets |
| By: | Anthony Garratt; James Mitchell; Shaun P. Vahey; Elizabeth C. Wakerly |
| Abstract: | We examine the effectiveness of recursive-weight and equal-weight combination strategies for forecasting using many time-varying models of the relationship be- tween inflation and the output gap. The forecast densities for inflation reflect the uncertainty across models using many statistical measures of the output gap, and allow for time-variation in the ensemble Phillips curves. Using real-time data for the US, Australia, New Zealand and Norway, we find that the recursive-weight strategy performs well, consistently giving well-calibrated forecast densities. The equal-weight strategy generates poorly-calibrated forecast densities for the US and Australian samples. There is little difference between the two strategies for our New Zealand and Norwegian data. We also find that the ensemble modelling approach performs more consistently with real-time data than with revised data in all four countries. |
| JEL: | C32 C53 E37 |
| Date: | 2010–12 |
| URL: | http://d.repec.org/n?u=RePEc:acb:camaaa:2010-34&r=ets |
| By: | Tilak Abeysinghe; Gulasekaran Rajaguru (Singapore Centre for Applied and Policy Economics) |
| Abstract: | We use a mixed-frequency regression technique to develop a test for cointegration under the null of stationarity of the deviations from a long-run relationship. What is noteworthy about this MA unit root test, based on a variance-difference, is that, instead of having to deal with non-standard distributions, it takes the testing back to the normal distribution and offers a way to increase power without having to increase the sample size substantially. Monte Carlo simulations show minimal size distortions even when the AR root is close to unity and that the test offers substantial gains in power against near-null alternatives in moderate size samples. An empirical exercise illustrates the relative usefulness of the test further. |
| Keywords: | Null of stationarity, MA unit root, mixed-frequency regression, variance difference, normal distribution, power. |
| JEL: | C12 C22 |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:eab:macroe:2383&r=ets |
| By: | Rao, B. Bhaskara; Kumar, Saten |
| Abstract: | This paper uses the extreme bounds analysis (EBA) of Leamer (1983 &1985) to analyze the robust determinants of the demand for money in a panel of 17 Asian countries for the period 1970 to 2009. These robust determinants are found to be unit root variables. Therefore, cointegration between these variables is tested with a recent time series panel method developed by Westerlund (2007). This method uses the error-correction formulation and has more power against the null of no cointegration. The results show that there is a well-defined long-run demand for money. Using the lagged error correction term from the estimated cointegrating equation, the short-run dynamic relationships are estimated. This paper, thus, suggests some useful guidelines to estimate other relationships with panel data. |
| Keywords: | Demand for money; Extreme bounds analysis; Panel ECM; Structural breaks |
| JEL: | C33 E41 |
| Date: | 2010–12–06 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:27263&r=ets |