The Risk of Agricultural Land Abandonment as a Socioeconomic Challenge for the Development of Agriculture in the European Union
Abstract
:1. Introduction
2. Literature Review
- poor environmental/biophysical suitability for agricultural activity;
- low farm stability and viability;
- negative drivers in the regional context.
- migration caused by military conflict, political instability, or large-scale natural disasters such as hurricanes [30];
- new production technologies, rapid industrialization, monopoly on land ownership, safety, availability of infrastructure, distance from potential markets [5];
- decrease in the biodiversity of agricultural landscapes and crop homogeneity associated with, for example, a higher risk of agricultural fires [3];
- depletion of water resources, loss of biodiversity, decrease in the population of species adapted to the local environmental conditions, loss of cultural and aesthetic values [3];
- historical events, such as the transition from a centrally planned to a market economy and the collapse of agriculture in Eastern European countries between 1990 and 2004; national and EU policies; problems with renewing agri-environmental contracts after five years; new sanitary requirements imposed on agricultural producers in Eastern Europe in 2004; decoupled payments that are not linked with production [8,24,31];
Agriculture Land Changes
3. Materials and Methods
Data Collection
- Choosing a set of variables
- 2.
- Construction of the taxonomic measure of risk using the Hellwig measurement method
- 3.
- Building a ranking of countries and their division into classes
- class I (low risk of farmland abandoning) ,
- class II (average risk of farmland abandoning) ,
- class III (high risk of farmland abandoning) ,
- 4.
- Regression
4. Results
5. Discussion and Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Region | Regression Equation | p | r2 |
---|---|---|---|
Africa | y = −3,478,144 + 2284x | 0.0000 | 0.9097 |
Northern America | y = 1,989,462 − 756x | 0.0000 | 0.9583 |
Central America | y = −217,966 + 169x | 0.0000 | 0.3215 |
South America | y = −2,080,185 + 1307x | 0.0000 | 0.5928 |
Asia | y = −25,400,495 + 13,466x | 0.0000 | 0.8568 |
Oceania | y = 5,701,947 − 2630x | 0.0000 | 0.7947 |
Europe | y = 16,128,571 − 7785x | 0.0000 | 0.7812 |
European Union (27) | y = 986,616 − 406x | 0.0000 | 0.7344 |
Country | Regression Equation | p | r2 | Change ** |
---|---|---|---|---|
Austria | y = 30,785.6714 − 13.9407x | 0.0000 | 0.9702 | −25.56 |
Belgium * | y = 19,679.1905 − 9.116x | 0.0000 | 0.8600 | −24.65 |
Bulgaria | y = 89,659.8084 − 42.0122x | 0.0000 | 0.8765 | −18.36 |
Croatia | y = 54,865.3825 − 26.5677x | 0.0015 | 0.3167 | −37.40 |
Cyprus | y = 10,280.0523 − 5.0613x | 0.0000 | 0.6895 | −66.80 |
Czechia | y = 77,247.8091 − 36.6115x | 0.0000 | 0.7438 | −17.71 |
Denmark | y = 20,045.4118 − 8.6618x | 0.0000 | 0.9289 | −17.09 |
Estonia | y = 11,475.1336 − 5.2341x | 0.0703 | 0.1163 | −28.31 |
Finland | y = 24,068.9314 − 10.8637x | 0.0000 | 0.8060 | −17.92 |
France | y = 2.3002 × 105 − 100.0331x | 0.0000 | 0.9685 | −17.33 |
Germany | y = 1.2933 × 105 − 55.9978x | 0.0000 | 0.9474 | −14.35 |
Greece | y = 1.0456 × 105 − 48.2826x | 0.0000 | 0.6363 | −34.15 |
Hungary | y = 72,743.1583 − 33.4103x | 0.0000 | 0.9499 | −30.78 |
Ireland | y = 64,141.9966 − 29.6907x | 0.0000 | 0.7123 | −20.13 |
Italy | y = 2.7813 × 105 − 131.4762x | 0.0000 | 0.9468 | −37.15 |
Latvia | y = 13,756.7232 − 5.9239x | 0.3041 | 0.0391 | −22.17 |
Lithuania | y = 41,019.231 − 18.9517x | 0.0014 | 0.3184 | −13.17 |
Luxembourg | y = −288.8289 + 0.2085x | 0.0000 | 0.7815 | 3.23 |
Malta | y = 227.9085 − 0.1084x | 0.0000 | 0.7866 | −42.33 |
Netherlands | y = 16,774.532 − 7.4168x | 0.0000 | 0.9168 | −21.59 |
Poland | y = 2.2811 × 105 − 105.6308x | 0.0000 | 0.8591 | −28.84 |
Portugal | y = 13,105.724 − 4.6431x | 0.0000 | 0.4343 | −0.06 |
Romania | y = 60,078.3191 − 22.8643x | 0.0000 | 0.5923 | −6.92 |
Slovakia | y = 55,807.7381 − 26.7671x | 0.0000 | 0.8086 | −23.02 |
Slovenia | y = −8235.0307 + 4.3848x | 0.00003 | 0.4800 | 8.24 |
Spain | y = 2.6407 × 105 − 117.557x | 0.0000 | 0.9516 | −21.33 |
Sweden | y = 40,440.7114 − 18.5956x | 0.0000 | 0.9387 | −29.06 |
Variable Code | Name | Data Source | Unit | Description | Role |
---|---|---|---|---|---|
D1 | Weak land market | [72] SE375/SE030 | €/ha | SE375. Rent paid for farm land and buildings and rental charges SE030. Utilized agricultural areas rented by the holder under a tenancy agreement for a period of at least one year (remuneration in cash or in kind); in hectares. High land sale and lease prices are generally associated with high demand for agricultural land, and thus with a lower risk of abandonment (the higher, the lower the risk of abandonment). | stimulant |
D2 | Low farm income | [72,73] SE415/DGP per capita | € | SE451. Farm Net Value Added; Remuneration to the fixed factors of production (work, land and capital), whether they be external or family factors. As a result, holdings can be compared irrespective of their family/non-family nature of the factors of production employed. This indicator is sensitive, however, to the production methods employed: the ratio (intermediate consumption + depreciation)/fixed factors may vary and therefore influence the FNVA level. For example, in the livestock sector, if production is mostly without the use of land (purchased feed) or extensive (purchase and renting of forage land). SE415 is a weighted mean (average) calculated as a [sum of sample farm incomes x sample farm weights]/[sum of sample farm weights]. DGP per capita—Gross domestic product at market prices, Current prices, euro per capita. Agricultural land is at greater risk of abandonment when it ceases to generate sufficient income (the higher, the lower the risk of abandonment). | stimulant |
D3 | Low investment in the farm | [72] SE521/SE025 | €/ha | SE521. Net Investment on fixed assets. Gross Investment on fixed assets—Depreciation. SE025. Total Utilized Agricultural Area. Total utilized agricultural area of holding. Does not include areas used for mushrooms, land rented for less than one year on an occasional basis, woodland and other farm areas (roads, ponds, non-farmed areas, etc.). It consists of land in owner occupation, rented land, land in share-cropping (remuneration linked to output from land made available). It includes agricultural land temporarily not under cultivation for agricultural reasons or being withdrawn from production as part of agricultural policy measures. It is expressed in hectares (10,000 m2). As from 2014, it includes kitchen gardens. Investment behavior reflects the dynamics of the farm, its adaptability and expectations for the future. New investments signal a medium/long-term strategy and can be an indicator of the desire to continue farming (the higher, the lower the risk of abandonment). | stimulant |
D4 | Age of farm holder | [74] Age 65 and more/Total age | % | The ratio between farm holders above 65 years and the total number of farm holders has been calculated. Abandonment of farmland is more likely when the farmer population is older, close to retirement (the higher, the greater the risk of abandonment). | destimulant |
D7a | Low population density | [75] Population density | person/km2 | Scarcely populated areas are identified from population statistics and were defined as areas with a population density below 50 inhabitants/km2. The higher the population density, the less likely agricultural land is to be abandoned | stimulant |
D7b | Remoteness | [76] Road networks | km/km2 | Motorways and other roads per thousand square kilometers. Abandonment of agricultural land is likely to occur in remote areas with inadequate access to basic services (health care, school and other services) and fewer marketing opportunities (the higher up, the lower the risk of abandonment). | stimulant |
N = 25 | b * | Std. Error with b * | b | Std. Error with b | t(23) | p |
---|---|---|---|---|---|---|
2010 | R = 0.99629431 R2 = 0.99260235 Corrected. R2 = 0.99013646 F(6,18) = 402.53 p < 0.00000 std. error: 0.01503 | |||||
Intersept | 0.139 | 0.008 | 16.887 | 0.0000 | ||
D1 | 0.289 | 0.034 | 0.0004 | 0.00005 | 8.373 | 0.0000 |
D2 | 0.245 | 0.026 | 0.0003 | 0.00003 | 9.589 | 0.0000 |
D3 | −0.176 | 0.022 | −0.0017 | 0.0002 | −8.128 | 0.0000 |
D4 | 0.298 | 0.027 | 0.0003 | 0.00002 | 10.866 | 0.0000 |
D7a | 0.265 | 0.032 | 0.00004 | 0.000005 | 8.217 | 0.0000 |
D7b | 0.168 | 0.024 | 0.0161 | 0.0023 | 7.124 | 0.0000 |
2013 | R = 0.99288540 R2 = 0.98582142 Corrected. R2 = 0.98109523 F(6,18) = 208.59 p < 0.00000 std. error: 0.01811 | |||||
Intersept | 0.126425 | 0.00896 | 14.11051 | 0.000000 | ||
D1 | 0.2561 | 0.049056 | 0.000305 | 0.000059 | 5.22055 | 0.000058 |
D2 | 0.28482 | 0.039563 | 0.00022 | 0.000031 | 7.1992 | 0.000001 |
D3 | −0.184943 | 0.028719 | −0.001711 | 0.000266 | −6.43984 | 0.000005 |
D4 | 0.292759 | 0.041806 | 0.000184 | 0.000026 | 7.00279 | 0.000002 |
D7a | 0.227376 | 0.030905 | 0.011945 | 0.001624 | 7.35716 | 0.000001 |
D7b | 0.224572 | 0.046893 | 0.000029 | 0.000006 | 4.789 | 0.000147 |
2016 | R = 0.98691592 R2 = 0.97400304 Corrected. R2 = 0.96533739 F(6,18) = 112.40 p < 0.00000 std. error: 0.02043 | |||||
Intersept | 0.108666 | 0.009221 | 11.78459 | 0.000000 | ||
D1 | 0.281342 | 0.066686 | 0.000276 | 0.000065 | 4.21893 | 0.000516 |
D2 | 0.319762 | 0.042822 | 0.000282 | 0.000038 | 7.46728 | 0.000001 |
D3 | 0.288382 | 0.039478 | 0.009957 | 0.001363 | 7.30489 | 0.000001 |
D4 | 0.349819 | 0.05475 | 0.000176 | 0.000027 | 6.38936 | 0.000005 |
D7a | −0.214998 | 0.038488 | −0.001699 | 0.000304 | −5.58606 | 0.000027 |
D7b | 0.208994 | 0.062852 | 0.000023 | 0.000007 | 3.32519 | 0.003766 |
2019 | R = 0.99398472 R2 = 0.98800563 Corrected. R2 = 0.98400751 F(6,18) = 247.12 p < 0.00000 std. error: 0.01613 | |||||
Intersept | 0.119548 | 0.009112 | 13.12017 | 0.000000 | ||
D1 | 0.240778 | 0.045427 | 0.000271 | 0.000051 | 5.30037 | 0.000049 |
D2 | 0.279099 | 0.04781 | 0.000197 | 0.000034 | 5.83769 | 0.000016 |
D3 | −0.176622 | 0.026478 | −0.001409 | 0.000211 | −6.6704 | 0.000003 |
D4 | 0.218311 | 0.027317 | 0.011527 | 0.001442 | 7.99184 | 0.000000 |
D7a | 0.292289 | 0.039854 | 0.000173 | 0.000024 | 7.33394 | 0.000001 |
D7b | 0.222805 | 0.047874 | 0.000028 | 0.000006 | 4.65399 | 0.000197 |
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2010 | 2013 | 2016 | 2019 | |
---|---|---|---|---|
Belgium | I | I | I | I |
Bulgaria | II | II | II | II |
Czechia | II | II | II | II |
Denmark | I | I | I | I |
Germany | I | I | I | I |
Estonia | II | II | III | II |
Ireland | II | II | II | II |
Greece | III | III | III | III |
Spain | III | III | III | III |
France | II | II | II | II |
Italy | III | III | II | III |
Cyprus | III | III | III | II |
Latvia | III | III | II | III |
Lithuania | II | II | II | III |
Hungary | II | II | II | II |
Netherlands | I | I | I | I |
Austria | II | II | II | II |
Poland | II | II | III | II |
Portugal | III | III | III | III |
Romania | III | III | III | III |
Slovenia | II | II | III | II |
Slovakia | II | II | I | II |
Finland | III | III | III | III |
Sweden | II | III | II | III |
United Kingdom | I | II | I | II |
Legend | ||||
Class I (low risk) | Class II (average risk) | Class III (high risk) |
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Pawlewicz, A.; Pawlewicz, K. The Risk of Agricultural Land Abandonment as a Socioeconomic Challenge for the Development of Agriculture in the European Union. Sustainability 2023, 15, 3233. https://doi.org/10.3390/su15043233
Pawlewicz A, Pawlewicz K. The Risk of Agricultural Land Abandonment as a Socioeconomic Challenge for the Development of Agriculture in the European Union. Sustainability. 2023; 15(4):3233. https://doi.org/10.3390/su15043233
Chicago/Turabian StylePawlewicz, Adam, and Katarzyna Pawlewicz. 2023. "The Risk of Agricultural Land Abandonment as a Socioeconomic Challenge for the Development of Agriculture in the European Union" Sustainability 15, no. 4: 3233. https://doi.org/10.3390/su15043233