Regional Patterns of Pesticide Consumption Determinants in the European Union
Abstract
:1. Introduction
2. Review of the Scientific Literature
2.1. Determinants of the Use of Pesticides in Agriculture
2.2. Cluster Analysis of Pesticide Consumption in Agriculture
3. Data and Methodology
3.1. Methods
3.2. Cluster Analysis
4. Results and Discussion
4.1. Regression Analysis
4.2. Cluster Analysis
5. Conclusions and Recommendations
- -
- Research and development and sharing expertise with other market participants might improve the experience of having a large organic agricultural area for the nations with the biggest population and GDP per capita (Italy, Spain, France, Germany). This cluster’s subsidies are higher than others, but better targeting, complementary regulatory circumstances, market access, etc. can increase their efficiency.
- -
- The second cluster (Poland, Lithuania, Greece, Portugal, Slovenia, Estonia, Romania, Croatia, Latvia, Czech Republic, Hungary, Slovakia, Bulgaria) has average pesticide use determinants. Competitive prices and large agricultural surfaces could benefit these countries. Subsidies can be increased while imposing their use in sustainable farming procedures, and there is a great deal of work to be completed in terms of regulations, market access for organic products not only on their own markets, but also on other European markets where consumers have higher incomes to spare on healthy food.
- -
- Ireland, Luxembourg, Finland, Denmark, Netherlands, Belgium, Sweden, Austria, and Luxembourg had the lowest agricultural production and subsidies in the third cluster. More in-depth studies are needed to see for which type of crop, subsidies would not represent a waste of resources given the more difficult environmental conditions.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Determinants | Implications | Correlation with Pesticide Use | |
---|---|---|---|
Population increase (c) | Food demand growth (a) [69] | Positive | |
Economic development (a) | low | Prohibitive pesticides costs (a) [40,41] | Positive |
high | Food demand growth = heavy users (a) [40,41] | Positive | |
very high | Focus on efficiency and growing demand for healthy food (a) [40,41] | Negative | |
Scarce or expensive workforce (c) [46] | Need to increase productivity (a) | Positive | |
Expensive land and growing competition (a) [47,48,49] | |||
Organic agricultural area | Specific certifications for organic products (a) [53] | Negative | |
Sales prices of crop products increase (a) [56] | Market for inorganic products becomes more profitable (a) | Positive | |
Real income increase (a) [57,58,59] | Pressure to improve input efficiency decreases (a) | Positive | |
Subsidies increase (a) [60,64] | Buy chemicals to improve agriculture productivity or Possibilities to invest in sustainable farming methods (a) | Ambiguous | |
Farmer age and education increase (b) [68] | Implementation of traditional farming methods (a) | Negative | |
Consumers’ education increase (b) [66] | Demand for healthy food (a) | Negative |
Variable | Definition | Source |
---|---|---|
Pesticides | Pesticide use per area of cropland (kilograms per hectare) | Our World in Data |
GDP per capita | Real GDP per capita (chain-linked volumes 2010, euro per capita) | Eurostat |
Selling prices | Sales prices of crop products (absolute prices, euro per 100 kg) | Eurostat |
Subsidies | Subsidies on agricultural products (million euro) | Eurostat |
Population | Population (total number) | Eurostat |
Organic agricultural area | Hectares of organic crop area fully converted and under conversion to organic farming) | Eurostat |
Real income | Index of the real income of factors in agriculture per annual work unit (2010 = 100) | Eurostat |
Panel Unit Root Test-Levin, Lin & Chu [76] | |||||
---|---|---|---|---|---|
Variable | Type of Test | t-Statistic | Prob. | Cross-Sections | Obs. |
Pesticides’ use | level, individual intercept and trend | −5.24169 | 0.0000 | 26 | 494 |
GDP per capita | level, individual intercept and trend | −1.75557 | 0.0396 | 27 | 484 |
Selling prices | level, individual intercept and trend | −10.3856 | 0.0000 | 25 | 426 |
Subsidies | level, individual intercept and trend | −3.34717 | 0.0004 | 26 | 378 |
Population | level, individual intercept and trend | −5.43467 | 0.0000 | 27 | 486 |
Organic agricultural area | level, individual intercept and trend | −0.00809 | 0.4968 | 27 | 427 |
level, individual intercept | 1.49809 | 0.9329 | 27 | 427 | |
level, none | 1.49809 | 0.9329 | 27 | 427 | |
1st difference, individual intercept and trend | −7.28873 | 0.0000 | 27 | 400 | |
Real income | level, individual intercept and trend | −4.1117 | 0.0000 | 27 | 455 |
Variable/ Indicator | Mean | Median | Max. | Min. | Std. Dev. | Obs. |
---|---|---|---|---|---|---|
Pesticides | 3.153327 | 2.260000 | 12.06000 | 0.240000 | 2.720559 | 520 |
GDP per capita | 24,279.59 | 20,245.00 | 88,120.00 | 2990.000 | 16,500.82 | 538 |
Selling prices | 15.05340 | 14.97000 | 33.07000 | 7.940000 | 3.881449 | 476 |
Subsidies | 331.1159 | 34.52000 | 5121.500 | 0.010000 | 816.3447 | 439 |
Population | 16,239,962 | 8,343,323 | 83,019,213 | 388,759.0 | 21,354,486 | 540 |
Organic agricultural area | 337,059.8 | 167,538.0 | 2,354,916 | 1.000000 | 440,774.1 | 482 |
Real income | 102.4768 | 100.0000 | 250.3800 | 33.60000 | 29.49577 | 509 |
Dependent Variable: Annual Pesticides’ Use (2001–2019) | ||||
---|---|---|---|---|
Method: Generalized Least Squares-Seemingly Unrelated Regression | ||||
Equation | 1 | 2 | 3 | 4 |
No. Obs./ Variable | 474 | 408 | 375 | 361 |
C | −5.6136 * (0.3812) (−14.7237) | −8.9782 * (0.5365) (−16.7321) | −9.4161 * (0.5459) (−17.248) | −10.8320 * (0.5862) (−18.477) |
GDP per capita | 0.2252 * (0.2148) (1.0485) | 0.5787 * (0.0409) (14.1375) | 0.5466 * (0.0495) (11.0409) | 0.5097 * (0.0463) (10.9983) |
Selling prices | 0.5727 * (0.0377) (15.1749) | 0.1098 * (0.0303) (3.6202) | 0.2299 * (0.0412) (5.5710) | 0.0829 *** (0.0441) (1.8799) |
Subsidies | −0.0024 (0.0049) (−0.4892) | −0.0122 ** (0.0054) (−2.2562) | −0.0067 (0.0055) (−1.2197) | |
Population | 0.2312 * (0.0227) (10.1592) | 0.4083 * (0.0306) (13.3363) | 0.4327 * (0.0306) (14.1349) | |
Organic agricultural area | −0.1948 * (0.0232) (−8.3907) | −0.1902 * (0.0242) (−7.8432) | ||
Real income | 0.3710 * (0.0507) (7.3132) | |||
Prob (F-statistic) | 0.0000 | 0.0000 | 0.0000 | 0.0000 |
R2 | 0.3441 | 0.3316 | 0.4005 | 0.4508 |
Adjusted R2 | 0.3413 | 0.3250 | 0.3924 | 0.4415 |
Durbin–Watson stat | 1.9784 | 1.9254 | 1.8424 | 1.7928 |
Variance Inflation Factors | |
---|---|
Variable | Centred VIF |
GDP per capita | 1.1476 |
Selling prices | 1.1878 |
Subsidies | 1.2151 |
Population | 1.9623 |
Organic agricultural area | 1.7374 |
Real income | 1.2083 |
Test | Null Hypothesis | Result | Decision | |||
---|---|---|---|---|---|---|
Redundant variable test | Population is not significant | Value | Df | Probability | Reject the null hypothesis | |
t-statistic | 11.3756 | 354 | 0.0000 | |||
F-statistic | 129.4044 | (1, 354) | 0.0000 | |||
Omitted variable test | Agriculture (% of GDP) is not significant | Value | Df | Probability | Accept the null hypothesis | |
t-statistic | 1.6448 | 353 | 0.1010 | |||
F-statistic | 2.7043 | (1, 353) | 0.1010 |
Cluster Number | Countries within Each Cluster |
---|---|
1 | Italy, Spain, France, Germany |
2 | Poland, Lithuania, Greece, Portugal, Slovenia, Estonia, Romania, Croatia, Latvia, Czech Republic, Hungary, Slovakia, Bulgaria |
3 | Ireland, Luxembourg, Finland, Denmark, Netherlands, Belgium, Sweden, Austria |
Cluster no. | GDP per Capita | Population | Selling Prices | Subsidies | Real Income | Organic Crop Area |
---|---|---|---|---|---|---|
1 | 30,427.50 | 64,237,645.50 | 18.85 | 253.20 | 125.62 | 1,969,944.25 |
2 | 14,486.92 | 9,496,740.62 | 16.58 | 94.26 | 151.16 | 291,458.85 |
3 | 48,998.75 | 8,083,597.00 | 15.38 | 3.79 | 104.87 | 265,543.88 |
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Robu, R.G.; Holobiuc, A.-M.; Alexoaei, A.P.; Cojanu, V.; Miron, D. Regional Patterns of Pesticide Consumption Determinants in the European Union. Sustainability 2023, 15, 2070. https://doi.org/10.3390/su15032070
Robu RG, Holobiuc A-M, Alexoaei AP, Cojanu V, Miron D. Regional Patterns of Pesticide Consumption Determinants in the European Union. Sustainability. 2023; 15(3):2070. https://doi.org/10.3390/su15032070
Chicago/Turabian StyleRobu, Raluca Georgiana, Ana-Maria Holobiuc, Alina Petronela Alexoaei, Valentin Cojanu, and Dumitru Miron. 2023. "Regional Patterns of Pesticide Consumption Determinants in the European Union" Sustainability 15, no. 3: 2070. https://doi.org/10.3390/su15032070