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008			240327b |||||||| |||| 00| 0 eng d
040			_aMSU _bEnglish _cMSU _erda
050	0	0	_aHB139.T52 ECO
100	1		_aHarvey,David I. _eauthor
245	1	0	_aSimple, robust, and powerful tests of the breaking trend hypothesis _cby David I. Harvey, Stephen J. Leybourne and A. M. Robert Taylor
264	1		_aCambridge : _bCambridge University Press, _c2009
336			_2rdacontent _atext _btxt
337			_2rdamedia _aunmediated _bn
338			_2rdacarrier _avolume _bnc
440			_aEconometric Theory _vVolume 25, number 4
520			_aIn this paper we develop a simple procedure which delivers tests for the presence of a broken trend in a univariate time series which do not require knowledge of the form of serial correlation in the data and are robust as to whether the shocks are generated by an I(0) or an I(1) process. Two trend break models are considered: the first holds the level fixed while allowing the trend to break, while the latter allows for a simultaneous break in level and trend. For the known break date case our proposed tests are formed as a weighted average of the optimal tests appropriate for I(0) and I(1) shocks. The weighted statistics are shown to have standard normal limiting null distributions and to attain the Gaussian asymptotic local power envelope, in each case regardless of whether the shocks are I(0) or I(1). In the unknown break date case we adopt the method of Andrews (1993) and take a weighted average of the statistics formed as the supremum over all possible break dates, subject to a trimming parameter, in both the I(0) and I(1) environments. Monte Carlo evidence suggests that our tests are in most cases more powerful, often substantially so, than the robust broken trend tests of Sayginsoy and Vogelsang (2004). An empirical application highlights the practical usefulness of our proposed tests.
650			_aTime series analysis
700			_aLeybourne, Stephen J.
700			_aTaylor, A. M. Robert
856			_u10.1017/S0266466608090373
942			_2lcc _cJA
999			_c164580 _d164580