Output Uji Unit Root
Lampiran 2: Output Uji Unit Root
---------------------------------------------- EasyReg International [September 20, 2012] Session date: Wednesday January 29, 2014 Session time: 22:41:12 ----------------------------------------------
KPSS trend stationarity test Reference: Kwiatkowski, D., P. Phillips, P. Schmidt, and Y. Shin (1992) Testing the Null of Stationarity Against the Alternative of a Unit Root Journal of Econometrics 54, 159-178. Null hypothesis H0: z(t) = c + d.t + u(t), where u(t) is a zero-mean stationary process and c and d are constants. Alternative hypothesis H1: z(t) is a unit root process with drift: z(t) = z(t-1) + c + u(t) The KPSS test employs a Newey-West type variance estimator of the long-run variance of u(t), with truncation lag m = [c.n^s], where c > 0 and 0< s <1/2. The default values of c and s are c = 5, s = .25
PPOP
m = 12 = [c.n^s], where c=5, s=.25, n=41 5% critical region 10% critical region > 0.146 > 0.119
Test results: Test statistic Conclusion (5%) Conclusion (10%) 0.1204 (accept H0) (reject H0)
----------------------------------------------
KPSS trend stationarity test Reference: Kwiatkowski, D., P. Phillips, P. Schmidt, and Y. Shin (1992) Testing the Null of Stationarity Against the Alternative of a Unit Root Journal of Econometrics 54, 159-178. Null hypothesis H0: z(t) = c + d.t + u(t), where u(t) is a zero-mean stationary process and c and d are constants. Alternative hypothesis H1: z(t) is a unit root process with drift: z(t) = z(t-1) + c + u(t) The KPSS test employs a Newey-West type variance estimator of the long-run variance of u(t), with truncation lag m = [c.n^s], where c > 0 and 0< s <1/2. The default values of c and s are c = 5, s = .25
GDP
m = 12 = [c.n^s], where c=5, s=.25, n=41 5% critical region 10% critical region > 0.146 > 0.119
Test results: Test statistic Conclusion (5%) Conclusion (10%) 0.1406 (accept H0) (reject H0)
----------------------------------------------
KPSS trend stationarity test Reference: Kwiatkowski, D., P. Phillips, P. Schmidt, and Y. Shin (1992) Testing the Null of Stationarity Against the Alternative of a Unit Root Journal of Econometrics 54, 159-178. Null hypothesis H0: z(t) = c + d.t + u(t), where u(t) is a zero-mean stationary process and c and d are constants. Alternative hypothesis H1: z(t) is a unit root process with drift: z(t) = z(t-1) + c + u(t) The KPSS test employs a Newey-West type variance estimator of the long-run variance of u(t), with truncation lag m = [c.n^s], where c > 0 and 0< s <1/2. The default values of c and s are c = 5, s = .25
LnEC
m = 12 = [c.n^s], where c=5, s=.25, n=41 5% critical region 10% critical region > 0.146 > 0.119
Test results: Test statistic Conclusion (5%) Conclusion (10%) 0.1421 (accept H0) (reject H0)
----------------------------------------------
KPSS trend stationarity test Reference: Kwiatkowski, D., P. Phillips, P. Schmidt, and Y. Shin (1992) Testing the Null of Stationarity Against the Alternative of a Unit Root Journal of Econometrics 54, 159-178.
Null hypothesis H0: z(t) = c + d.t + u(t), where u(t) is a zero-mean stationary process and c and d are constants. Alternative hypothesis H1: z(t) is a unit root process with drift: z(t) = z(t-1) + c + u(t) The KPSS test employs a Newey-West type variance estimator of the long-run variance of u(t), with truncation lag m = [c.n^s], where c > 0 and 0< s <1/2. The default values of c and s are c = 5, s = .25
LnCO
m = 12 = [c.n^s], where c=5, s=.25, n=41 5% critical region 10% critical region > 0.146 > 0.119
Test results: Test statistic Conclusion (5%) Conclusion (10%) 0.1132 (accept H0) (accept H0)