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Table 4 Transfer function models from the second period 1983 to 2008

From: Physician and nurse supply in Serbia using time-series data

Dependent variable (labels and name)

Potential predictors in start model (name only)

Significant predictors in final model (name only)

Model type

Stationary R2

Number of outliers

Q-stat ( P-value)

Z-stat ( P-value)

Physicians (y1)

x1, x2, x3, x4, x5, x6

x1, x2

TF (0,1,0)

0.71

0

5.35 (0.50)

0.63 (0.82)

Nurses (y2)

y1, x1, x2, x3, x4, x5, x6

y1

TF (0,1,0)

0.92

2

7.34 (0.29)

0.53 (0.94)

Inpatient care discharges (x3)

y1, y2, x1, x2, x4, x5, x6

x2

TF (0,1,0)

0.78

1

7.34 (0.29)

0.51 (0.96)

Outpatient care visits (x4)

y1, y2, x1, x2, x3, x5, x6

y1

TF (0,1,0)

0.44

0

6.31 (0.39)

0.59 (0.88)

Students enrolled in the first year of studies (x5)

y1, y2, x1, x2, x3, x4, x5, x6

none

ARIMA (0,1,0)

0.73

1

4.97 (0.55)

0.67 (0.77)

Graduated medical doctors (x6)

y1, y2, x1, x2, x3, x4, x5, x6

none

ARIMA (0,1,0)

0.23

1

4.73 (0.58)

0.68 (0.74)

  1. Legend: stationary R2 - measure of goodness of fit of model. Range is from negative infinity to 1; Q-stat - is Ljung-Box Q(6) statistics that test the null hypotheses of no autocorrelation in residual series; Z-stat - is Kolmogorov-Smirnov statistics that test the null hypotheses of normal distribution of residual series.