tfp.md
In RGAP: Production Function Output Gap Estimation

TFP model

Call:
TFPmodel(tsl = tsList, cycle = "RAR2")

    State space model object of class TFPmodel

cycle               RAR2
trend               DT
cubs
  cycle lags            0
  error term            iid normal
  exogenous variables       -
anchor
  value             -
  horizon           -
dimensions
  number of observations    36
  period            1985 - 2020
  frequency             annual

Object is a valid object of class TFPmodel.

TFP MLE fit

Call:
fit.TFPmodel(model = model)

    State space model object of class TFPmodel

cycle               RAR2
trend               DT
cubs
  cycle lags            0
  error term            iid normal
  exogenous variables       -
anchor
  value             -
  horizon           -
dimensions
  number of observations    36
  period            1985 - 2020
  frequency             annual


    Maximum likelihood estimation results

cycle
         Coefficient Standard Error t-statistic  p-value
  cA           0.533          0.153        3.49 0.000485
  cSigma       0.862          0.226        3.82 0.000133
  cTau         8.709          3.270        2.66 0.007746

trend
          Coefficient Standard Error t-statistic p-value
  tdOmega      0.5016         0.3853        1.30   0.193
  tdPhi        0.8944         0.1019        8.77   0.000
  tdSigma      0.0777         0.0668        1.16   0.245

cubs
          Coefficient Standard Error t-statistic p-value
  cuC0           2.72          0.296        9.17 0.00000
  cuConst        0.21          0.915        0.23 0.81825
  cuSigma        1.53          0.561        2.73 0.00631
  RMSE: 2.89
  R2: 0.367
  Box-Ljung test: X-squared = 2.17, df = 7.2, p-value = 0.956

         loglik             AIC             BIC             HQC signal-to-noise 
     -120.28316       258.56631       272.81799       263.54053         0.09013

TFP bayesian fit

Call:
fit.TFPmodel(model = model, method = "bayesian", R = 1000, thin = 2, 
    MLEfit = f)

    State space model object of class TFPmodel

cycle               RAR2
trend               DT
cubs
  cycle lags            0
  error term            iid normal
  exogenous variables       -
anchor
  value             -
  horizon           -
dimensions
  number of observations    36
  period            1985 - 2020
  frequency             annual


    MCMC estimation results

cycle
          Mean Median 85% HPDI-LB 85% HPDI-UB
  cA     0.417  0.410       0.164       0.656
  cSigma 1.077  0.915       0.521       1.462
  cTau   8.079  7.589       3.086      12.394

trend
            Mean Median 85% HPDI-LB 85% HPDI-UB
  tdOmega 0.0145 0.0143   -0.000777      0.0258
  tdPhi   0.9447 0.9628    0.900142      0.9898
  tdSigma 0.0519 0.0424    0.015013      0.0832

cubs
              Mean   Median 85% HPDI-LB 85% HPDI-UB
  cuC0     2.74864 2.712603      2.2410      3.1618
  cuConst -0.00115 0.000207     -0.0722      0.0693
  cuSigma  2.78277 2.611966      1.6156      3.7409
          MRMSE signal-to-noise 
        1.48578         0.04823