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Table 4 Correlations with others methods

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

  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
  1. Rodríguez (2010c) use a multivariate Kalman filter
  2. t, lineal trend; t2, quadratic trend; t q 1, lineal trend with break in level (1990q3); t q 2, linear trend with break in level (1990q3) and slope (2002q1)