Figure 1.
Basic efficiency characteristics aggregated for all countries_
| Characteristic | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 |
|---|---|---|---|---|---|---|
| Minimum | 0.4101 | 0.3891 | 0.3552 | 0.2795 | 0.2200 | 0.3207 |
| Lower quartile | 0.6797 | 0.5959 | 0.6141 | 0.5612 | 0.5517 | 0.6225 |
| Median | 0.8467 | 0.8966 | 0.7821 | 0.7751 | 0.7981 | 0.9770 |
| Average | 0.8119 | 0.7967 | 0.7574 | 0.7404 | 0.7428 | 0.8359 |
| Upper quartile | 1 | 1 | 0.9684 | 0.9396 | 0.9913 | 1 |
| Maximum | 1 | 1 | 1 | 1 | 1 | 1 |
Basic characteristics of the input and output variables used_
| Variable | Char. | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 |
|---|---|---|---|---|---|---|---|
| Employees (thousand) | Min | 4 | 3 | 4 | 3 | 3 | 2 |
| Average | 26 | 26 | 26 | 25 | 25 | 24 | |
| Median | 22 | 233 | 23 | 24 | 21 | 19 | |
| Max | 73 | 77 | 86 | 73 | 63 | 72 | |
| Area of wooded land (thousand hectares) | Min | 1,248 | 1,246 | 1,244 | 1,242 | 1,240 | 1,238 |
| Average | 7,874 | 7,885 | 7,896 | 7,905 | 7,915 | 8,215 | |
| Median | 3,833 | 3,841 | 3,854 | 3,867 | 3,880 | 3,896 | |
| Max | 27,980 | 27,980 | 27,980 | 27,980 | 27,980 | 27,980 | |
| Volume of timber (thousand cubic metres) | Min | 378,530 | 381,900 | 386,000 | 389,300 | 393,100 | 397,030 |
| Average | 1,374,903 | 1,392,871 | 1,401,526 | 1,409,962 | 1,418,532 | 1,462,409 | |
| Median | 768,150 | 771,780 | 775,370 | 782,250 | 786,470 | 937,885 | |
| Max | 3,663,000 | 3,663,000 | 3,663,000 | 3,663,000 | 3,663,000 | 3,663,000 | |
| Roundwood production (thousand cubic metres) | Min | 4,357 | 4,263 | 4,484 | 4,975 | 4,397 | 3,891 |
| Average | 21,955 | 22,091 | 23,083 | 24,746 | 24,855 | 23,613 | |
| Median | 12,294 | 12,794 | 12,896 | 14,392 | 14,822 | 13,318 | |
| Max | 74,300 | 74,800 | 74,300 | 75,233 | 77,821 | 78,673 | |
| Value added (millions of EUR) | Min | 150 | 182 | 196 | 216 | 198 | 198 |
| Average | 1,255 | 1,266 | 1,277 | 1,336 | 1,262 | 1,180 | |
| Median | 876 | 860 | 833 | 919 | 870 | 665 | |
| Max | 3,446 | 3,511 | 3,784 | 4,111 | 4,187 | 4,046 |
Derived ranking of countries by calculated efficiency rate for the period between 2015 and 2020_
| Country | Efficiency in | Average | Rank | |||||
|---|---|---|---|---|---|---|---|---|
| 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | |||
| Finland | 1 | 1 | 1 | 1 | 1 | 1 | 1.0000 | 1–3 |
| Germany | 1 | 1 | 1 | 1 | 1 | 1 | 1.0000 | 1–3 |
| Czech Rep. | 1 | 1 | 1 | 1 | 1 | X | 1.0000 | 1–3 |
| Austria | 1 | 1 | 1 | 0.9520 | 0.9610 | 0.9770 | 0.9820 | 4 |
| Estonia | 1 | 1 | 1 | 1 | 0.8060 | 1 | 0.9680 | 5 |
| Sweden | 1 | 1 | 0.9130 | 0.8060 | 1 | 1 | 0.9530 | 6 |
| France | 1 | 0.9450 | 0.9480 | 0.8900 | 0.9140 | 0.8790 | 0.9290 | 7 |
| Italy | 0.8930 | 0.9360 | 0.8730 | 0.9020 | 0.9650 | 1 | 0.9280 | 8 |
| Slovenia | 0.8310 | 0.9910 | 0.8040 | 0.8680 | 1 | 1 | 0.9160 | 9 |
| Latvia | 0.8620 | 0.8570 | 0.8010 | 0.7320 | 0.6310 | 1 | 0.8140 | 10 |
| Slovakia | 0.8240 | 0.7530 | 0.7010 | 0.7440 | 0.7900 | 1 | 0.8020 | 11 |
| Poland | 0.8300 | 0.7540 | 0.7160 | 0.6340 | 0.6200 | 0.8460 | 0.7330 | 12 |
| Spain | 0.6780 | 0.5870 | 0.5910 | 0.5590 | 0.5290 | 0.5830 | 0.5880 | 13 |
| Hungary | 0.6850 | 0.6200 | 0.5830 | 0.4680 | 0.5200 | 0.6200 | 0.5820 | 14 |
| Lithuania | 0.6050 | 0.5880 | 0.5310 | 0.4830 | 0.4150 | 0.5790 | 0.5340 | 15 |
| Romania | 0.4100 | 0.3890 | 0.3960 | 0.5680 | 0.6370 | 0.7830 | 0.5310 | 16 |
| Croatia | 0.5750 | 0.5300 | 0.5070 | 0.4430 | 0.3630 | 0.6230 | 0.5070 | 17 |
| Bulgaria | 0.4210 | 0.3900 | 0.3550 | 0.2800 | 0.2200 | 0.3210 | 0.3310 | 18 |
Average values of variables for each cluster for 2015 and 2020_
| Cluster No. | Year | Employees | Area of wooded land | Volume of timber | Roundwood production | Value added |
|---|---|---|---|---|---|---|
| 1 | 2015 | 58.27 | 8,539.35 | 2,051,903.33 | 1,593.80 | 20,580.70 |
| 2020 | 57.60 | 8,659.39 | 2,169,730.00 | 1,795.50 | 22,514.91 | |
| 2 | 2015 | 27.78 | 19,661.00 | 3,111,322.50 | 3,375.43 | 60,083.94 |
| 2020 | 28.38 | 19,765.25 | 3,205,397.50 | 2,843.32 | 65,072.36 | |
| 3 | 2015 | 17.80 | 4,007.80 | 643,860.91 | 473.35 | 10,064.28 |
| 2020 | 14.74 | 4,157.04 | 654,347.00 | 414.84 | 9,262.07 |
Results of the overall and average Malmquist index, including decomposition into efficiency change (catch-up) and production possibilities change (frontier)_
| Cluster | Country | Catch-up | Frontier | Malmquist | |||
|---|---|---|---|---|---|---|---|
| Total | Average | Total | Average | Total | Average | ||
| 1 | Poland | 0.8814 | 0.9523 | 1.0495 | 1.0812 | 0.9250 | 1.0247 |
| Romania | 1.5298 | 1.1029 | 0.9719 | 0.9987 | 1.4869 | 1.0940 | |
| Italy | 1 | 1.0169 | 1.1369 | 1.0103 | 1.1369 | 1.0250 | |
| 2 | Sweden | 1 | 1.0073 | 1.0864 | 1.0183 | 1.0864 | 1.0173 |
| Finland | 1 | 1 | 1.1212 | 1.0313 | 1.1212 | 1.0313 | |
| France | 0.8790 | 0.9738 | 0.9705 | 0.9969 | 0.8530 | 0.9695 | |
| Germany | 1 | 1 | 1.0368 | 0.9940 | 1.0368 | 0.9940 | |
| 3 | Bulgaria | 0.6839 | 0.8606 | 1.1326 | 1.1115 | 0.7745 | 0.9514 |
| Estonia | 1 | 0.9653 | 1.2003 | 1.0687 | 1.2003 | 1.0326 | |
| Spain | 0.8603 | 0.9505 | 1.0167 | 1.0407 | 0.8746 | 0.9884 | |
| Croatia | 0.9325 | 0.9337 | 1.1024 | 1.0831 | 1.0280 | 1.0039 | |
| Latvia | 1.0460 | 0.9468 | 1.1705 | 1.0952 | 1.2244 | 1.0332 | |
| Lithuania | 0.8582 | 0.9357 | 1.1986 | 1.0689 | 1.0286 | 0.9963 | |
| Hungary | 0.8063 | 0.9405 | 1.0950 | 1.0529 | 0.8828 | 0.9790 | |
| Austria | 0.9782 | 0.9878 | 0.8438 | 0.9362 | 0.8254 | 0.9236 | |
| Slovenia | 1.2025 | 1.0471 | 0.9048 | 0.9807 | 1.0880 | 1.0183 | |
| Slovakia | 1 | 0.9936 | 1.0625 | 1.0536 | 1.0625 | 1.0444 | |
| Czech Rep. | 1 | 1 | 1.2934 | 1.0674 | 1.2934 | 1.0674 | |
Derived ranking of identified clusters by calculated average efficiency rate for the period between 2015 and 2020_
| Cluster | Efficiency in | |||||||
|---|---|---|---|---|---|---|---|---|
| 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | Average | Rank | |
| 1 | 0.7110 | 0.6930 | 0.6617 | 0.7013 | 0.7407 | 0.8763 | 0.7307 | 2 |
| 2 | 1 | 0.9863 | 0.9653 | 0.9240 | 0.9785 | 0.9698 | 0.9706 | 1 |
| 3 | 0.7710 | 0.7560 | 0.7157 | 0.6845 | 0.6577 | 0.7703 | 0.7259 | 3 |