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Fig. 1
Final score in Parkiet's competition depending on a standard deviation of forecast's disagreement (σ) and absolute forecast's error. Source: The author.
Fig. 2
Final score depending on standardised error. Source: The author.
Goodness-of-Fit test statistics
successi,t = 0
successi,t = 1
Percentile
Actual
Expected
Actual
Expected
H-L Value
1
12
11.99
0
0.01
0.01
2
12
11.99
0
0.01
0.01
3
12
11.90
0
0.10
0.10
4
12
11.80
0
0.20
0.20
5
11
11.49
1
0.51
0.50
6
11
11.29
1
0.71
0.12
8
8
8.24
4
3.76
0.02
9
6
6.05
6
5.95
0.00
10
1
1.27
12
11.73
0.06
Total
96
96.18
25
24.82
1.47
H-L Statistic
1.47
Prob. Chi-Sq (8)
0.99
Andrews Statistic
55.82
Prob. Chi-Sq (10)
0.00
Median score in selected categories of Parkiet's competition
Year
PMI index
Industrial production
CPI
Unemployment rate
2019
3.65
4.71
4.82
7.76
2018
3.13
5.65
4.95
7.15
2017
3.79
5.54
4.45
5.85
2016
2.90
4.72
3.79
7.34
2015
3.10
4.91
3.16
6.28
Standard deviation of scores in selected categories of Parkiet's competition
Year
PMI index
Industrial production
CPI
Unemployment rate
2019
1.44
1.68
1.70
3.02
2018
0.73
1.18
1.40
1.52
2017
0.80
1.19
1.19
1.14
2016
0.89
1.22
1.18
1.99
Which variables increase the odds of scoring top five in Parkiet's competition
Model parameters – Eq. (5)
Variable
Coefficient
Std. Error
z-Statistic
Prob.
CPI
0.94
0.44
2.15
0.03
Core inflation
1.25
0.45
2.75
0.01
Unemployment rate
1.18
0.45
2.63
0.01
Employment
1.53
0.48
3.21
0.00
CA
1.67
0.47
3.58
0.00
EUR/PLN
0.91
0.53
1.71
0.09
POLGB10
1.46
0.41
3.58
0.00
Constant
−3.18
0.54
−5.87
0.00
Model diagnostics
McFadden R-squared
0.51
Obs with Dep = 0
96
LR statistic
62.57
Obs with Dep = 1
25
Prob (LR statistic)
0.00
Total obs
121
Are some analysts persistently better than others in forecasting? Models’ estimations output of Eq. (6)