Trend-cycle decomposition for Peruvian GDP: application of an alternative method

Latin American Economic Review

Table 4 Correlations with others methods

	UC-C	UC-N	UC-P	UC-CN	UC-CP	UC-NP	UC-CNP
t	0.81	0.28	0.29	0.54	0.81	0.06	0.51
t ²	0.88	0.42	0.37	0.66	0.87	0.15	0.60
\(t_{q_{1}}\)	0.65	0.41	0.51	0.80	0.65	0.05	0.67
\(t_{q_{2}}\)	0.84	0.50	0.62	0.94	0.84	0.17	0.83
HP 1600	0.71	0.69	0.50	0.76	0.71	0.39	0.72
BK	0.74	0.68	0.46	0.77	0.74	0.36	0.73
CF	0.68	0.75	0.52	0.75	0.68	0.46	0.75
BW	0.65	0.75	0.54	0.72	0.65	0.49	0.74
Clark	0.71	0.34	0.26	0.83	0.71	0.10	0.77
Rodríguez	0.87	0.36	0.40	0.68	0.87	0.09	0.67
Hamilton	0.33	0.45	0.45	0.68	0.34	0.12	0.47
Plucking	0.88	0.31	0.33	0.81	0.88	0.12	0.81
Promedio	0.73	0.50	0.44	0.74	0.73	0.21	0.69

Rodríguez (2010c) use a multivariate Kalman filter
t, lineal trend; t², quadratic trend; t_q₁, lineal trend with break in level (1990q3); t_q₂, linear trend with break in level (1990q3) and slope (2002q1)