Macroeconomic forecasting in Poland: The role of forecasting competitions

Jakub Rybacki

doi:10.2478/ceej-2020-0001

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Macroeconomic forecasting in Poland: The role of forecasting competitions

Central European Economic Journal

Volume 7 (2020): Issue 54 (January 2020)

By: Jakub Rybacki

Open Access

|Sep 2020

Figures & Tables

Final score in Parkiet's competition depending on a standard deviation of forecast's disagreement (σ) and absolute forecast's error. *Source*: The author.

Final score depending on standardised error. *Source*: The author.

Table 1

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

[i] Source: The author. Full table is presented in Appendix.

Table 2

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

[i] Source: The author. Full table is presented in Appendix.

Table 3

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

[i] Source: The author. Model diagnostics are presented in the Section A2 in Appendix.

Table 4

Are some analysts persistently better than others in forecasting? Models’ estimations output of Eq. (6)

Variable	β₁	β₀	Prob (x1 = 0)	Prob (x1 = 1)
CPI	0.70	−1.02	15%	38%
	0.37 (0.06)	0.18 (0.00)

Core inflation	0.83	−1.09	17%	38%
	0.38 (0.03)	0.18 (0.00)

CA	0.66	−0.94	17%	39%
	0.35 (0.06)	0.18 (0.00)

Export	0.23	−1.00
	0.38 (0.54)	0.18 (0.00)

Import	0.64	−0.96
	0.36 (0.08)	0.18 (0.00)

Construction output	0.19	−0.78
	0.36 (0.59)	0.17 (0.00)

Production	0.07	−0.91
	0.41 (0.86)	0.17 (0.00)

Retail sales	0.07	−0.83
	0.37 (0.86)	0.17 (0.00)

Employment	−0.74	−0.59
	0.41 (0.07)	0.17 (0.00)

Unemployment rate	0.02	−0.78
	0.37 (0.96)	0.17 (0.00)

M3	0.65	−0.99	16%	37%
	0.35 (0.06)	0.18 (0.00)

PMI	0.35	−0.89
	0.36 (0.33)	0.17 (0.00)

EUR/PLN	−0.44	−0.74
	0.43 (0.3)	0.17 (0.00)

USD/PLN	0.02	−0.74
	0.37 (0.95)	0.17 (0.00)
POLGBs 10Y	−0.13	−0.71
	0.36 (0.72)	0.17 (0.00)

[i] Source: The author.

Standard deviations of final scores in competition categories						Median scores in the competition categories

Year	2019	2018	2017	2016	2015	Year	2019	2018	2017	2016	2015
PMI	1.44	0.73	0.80	0.89	0.80	PMI	3.65	3.13	3.79	2.90	3.10

CPI	1.70	1.40	1.19	1.18	1.11	CPI	4.82	4.95	4.45	3.79	3.16

CA balance	1.60	0.85	1.23	1.42	0.95	CA balance	3.66	4.91	4.74	5.28	4.49

Export	2.18	1.55	0.97	0.85	0.84	Export	5.08	5.78	4.59	4.35	3.18

Import	1.76	1.35	1.50	1.55	1.57	Import	4.50	5.24	6.34	5.35	5.74

Core inflation	1.52	1.39	0.91	1.40	1.13	Core inflation	3.50	4.91	5.18	5.37	4.33

Employment	1.55	1.68	1.26	1.36	1.11	Employment	4.89	6.56	5.19	5.02	4.38

Wage growth	1.28	1.04	0.97	0.94	1.35	Wage growth	4.05	4.73	5.01	4.03	5.16

PPI	1.89	1.36	1.07	1.18	1.33	PPI	4.63	5.61	3.90	4.94	4.40

Industrial Output	1.68	1.18	1.19	1.22	1.68	Industrial Output	4.71	5.65	5.54	4.72	4.91

Construction Output	1.39	1.13	0.84	1.43	1.38	Construction Output	4.21	5.25	4.19	3.94	4.79

Retail Sales	1.60	0.91	0.54	0.95	0.97	Retail Sales	4.58	4.58	3.63	3.01	4.14

M3	1.49	1.40	0.91	1.01	0.98	M3	4.50	5.65	5.26	4.16	4.42
Unemployment rate	3.02	1.52	1.14	1.99	1.79	Unemployment rate	7.76	7.15	5.85	7.34	6.28

Variable's value	Count	Percent
success_i,t = 0	96	79.34%
success_i,t = 1	25	20.66%

Expectation-Prediction Evaluation – Model response vs. observed variables

	Estimated equation			Constant probability model

	success_i,t = 0	success_i,t = 1	Total	success_i,t = 0	success_i,t = 1	Total
Correct	95	12	107	96	0	96
%	99	48	88	100	0	79

Expected number of observations in the sample based on the model specification

	Estimated equation			Constant probability model

	success_i,t = 0	success_i,t = 1	Total	success_i,t = 0	success_i,t= 1	Total
Total	96	25	121	96	25	121

Correct	87	16	102	76	5	81
%	90	62	84	79	21	67

Goodness-of-Fit test statistics

	success_i,t = 0		success_i,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

References

Authors

Metrics

Articles in this issue

DOI: https://doi.org/10.2478/ceej-2020-0001 | Journal eISSN: 2543-6821 | Journal ISSN: 2544-9001

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Language: English

Page range: 1 - 11

Published on: Sep 10, 2020

Published by: Faculty of Economic Sciences, University of Warsaw

In partnership with: Paradigm Publishing Services

Keywords:

JEL:

E17,

E37

Related subjects:

Business and economics,

Political economics,

Economic theory, systems and structures,

Microeconomics,

Macroeconomics,

Economic policy

© 2020 Jakub Rybacki, published by Faculty of Economic Sciences, University of Warsaw
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 7 (2020): Issue 54 (January 2020)

Macroeconomic forecasting in Poland: The role of forecasting competitions

Figures & Tables

Fig. 1

Fig. 2

Table 1

Table 2

Table 3

Table 4

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