Submitted:
30 June 2023
Posted:
04 July 2023
You are already at the latest version
Abstract
Keywords:
1. Introduction
2. Survey of Relevant Literature
2.1. Preponderant Factors in Agricultural Fields Appraisal
2.2. The Positive Amenities
2.3. The Negative Externalities
2.4. Public Policies
2.5. The Proximity to the Urban Centres
3. Methodology
4. Empirical Study
4.1. Descriptive Analysis of the Results of the Agricultural Land Survey
4.2. Exploratory Factor Analysis
4.3. Mean Differences
4.3.1. The Difference in Means in the Variables Encountered when Purchasing Agricultural Land between Males and Females
4.3.2. Difference between People who Only Work in Agriculture and those who have another Job in Addition to Agriculture
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- Ardakani, Z.; Bartolini, F.; Brunori, G. New Evaluation of Small Farms: Implication for an Analysis of Food Security. Agriculture 2020, 10(3), 74. [Google Scholar] [CrossRef]
- Buday, Š.; Roháčiková, O.; Rumanovská, Ľ. Analysis of the agricultural land market transactions in selected regions of Slovakia in the years 2007–2016. Acta Regionalia et Environmentalica 2018, 15(2), 28–37. [Google Scholar] [CrossRef]
- Caballer, V. Nuevas endências en la valoración territorial. CT/Catastro 2002, 45(11).
- Del Río, B. S. G.; Marqués-Pérez, I. Spatial analysis of agricultural land prices. Economía Agraria y Recursos Naturales-Agricultural and Resource Economics. [CrossRef]
- Gracia, A.; Pérez Y Pérez, L.; San Juan, A., Barreiro, J. Análisis hedónico de los precios del suelo rústico. VI Encuentro de economı́a aplicada 2003, Granada.
- Gripp JR, J.; Marques, M. É. T.; Gonçalves, R. P.; Andrade, R. J. Avaliação de imóveis rurais. In Congresso Brasileiro de Cadastro Técnico Multifinalitário-UFSC 2006, Florianópolis-SC (Vol. 15).
- Herzberg, R.; Pham, T. G.; Kappas, M.; Wyss, D.; Tran, C. T. M. Multi-criteria decision analysis for the land evaluation of potential agricultural land use types in a hilly area of Central Vietnam. Land 2019, 90, 1–25. [Google Scholar] [CrossRef]
- Khương, N. I. Factors Affecting Land Prices In The Urban Fringe Of The Mekong Delta. Journal of Economic Development 2019, 02–08. [Google Scholar] [CrossRef]
- Kilić, J.; Rogulj, K.; Jajac, N. Fuzzy expert system for land valuation in land consolidation processes. Croatian Operational Research Review 2019, 10(1), 89–103. [Google Scholar] [CrossRef]
- Kocur-Bera, K. Determinants of agricultural land price in Poland–a case study covering a part of the Euroregion Baltic. Cahiers Agricultures 2016, 25(2), 25004. [Google Scholar] [CrossRef]
- Li, M.; Wang, J.; Chen, Y. Evaluation and influencing factors of sustainable development capability of agriculture in countries along the Belt and Road Route. Sustainability 2019, 11(7), 2004. [Google Scholar] [CrossRef]
- Lima, A.; Soares, V. S. Modelo de avaliação hedónico de terrenos rústicos e seus desafios: o estudo de caso da realidade da Região do Porto, Norte de Portugal. População e Sociedade 2015, 23, 145-159.
- Lima, D. A.; Nóbrega, M. L. Análise do preço de terras agrícolas no tocantins: decifrando os caminhos do agronegócio. Raega-O Espaço Geográfico em Análise. [CrossRef]
- Livanis, G.; Moss, C. B.; Breneman, V. E.; Nehring, R. F. Urban sprawl and farmland prices. American Journal of Agricultural Economics 2006, 88(4), 915–929. [Google Scholar] [CrossRef]
- Luo, D.; Ye, L.; Sun, D. Risk evaluation of agricultural drought disaster using a grey cloud clustering model in Henan province, China. International Journal of Disaster Risk Reduction 2020, 49, 101759. [Google Scholar] [CrossRef]
- Marôco J. Análise Estatística com o SPSS Statistics. 7. Ed 2018. ReportNumber, Lisboa.
- Meneses, T. G. Desarrollo de la valoración catastral de fincas rústicas. Aplicación a la Comunidad Foral de Navarra. CT: Catastro 2003, 63–74.
- Middelberg, S. L. Agricultural land valuation methods used by financiers: The case of South Africa. Agrekon 2014, 53(3), 101–115. [Google Scholar] [CrossRef]
- Pacheco, L.; Lote, E.; Tavares, F. Empresas Agrícolas e Desenvolvimento Económico: Potencialidades da Província do Huambo, em Angola. Revista em Agronegócio e Meio Ambiente, Maringá (PR), 1051. [Google Scholar] [CrossRef]
- Pestana, M.; Gageiro, J. Análise de Dados para Ciências Sociais: A Complementaridade do SPSS. 6ª Edição 2014. Lisboa. Edições Sílabo.
- Plantinga, A. J.; Miller, D. J. Agricultural land values and the value of rights to future land development. Land economics 2001, 77(1), 56–67. [Google Scholar] [CrossRef]
- Rondhi, M.; Pratiwi, P. A.; Handini, V. T.; Sunartomo, A. F.; Budiman, S. A. Agricultural land conversion, land economic value, and sustainable agriculture: A case study in East Java, Indonesia. Land 2018, 7(4), 148. [Google Scholar] [CrossRef]
- Ruivo, P. Amenidades rurais-que contributo? Estu do de caso em territórios rurais. III Congresso de Estudos Rurais 2008, Faro, Universidade do Algarve.
- Sal, A. G.; García, A. G. A comprehensive assessment of multifunctional agricultural land-use systems in Spain using a multi-dimensional evaluative model. Agriculture, Ecosystems e Environment 2007, 120(1), 82-91. [CrossRef]
- Santos, E.; Tavares, F.; Tavares, V.; Ratten V. Comparative Analysis of the Importance of Determining Factors in the Choice and Sale of Apartments. Sustainability 2021; 13(16):8731. [CrossRef]
- Sardaro, R.; La Sala, P.; Roselli, L. How does the land market capitalize environmental, historical and cultural components in rural areas? Evidences from Italy. Journal of Environmental Management 2020, 269, 110776. [Google Scholar] [CrossRef] [PubMed]
- Schwarcz, P.; Bandlerová, A.; Schwarczová, L. Selected issues of the agricultural land market in Slovak Republic. Journal of Central European Agriculture 2013, 14(3), 0–0. [Google Scholar] [CrossRef]
- Silva, M. L.; Rocha, R. R.; Cordeiro, S. A.; Silva, M. L.; Bezerra, A. F. Estudo comparativo de três métodos de avaliação de terras florestais. Cerne 2011, 17, 209–213. [Google Scholar] [CrossRef]
- Somantri, L.; Ridwana, R.; Himayah, S. Land value analysis in the suburban of Bandung and agricultural land availability impact. In IOP Conference Series: Earth and Environmental Science 2021, 683(1), 012088. [CrossRef]
- Szturc, J.; Karásek, P.; Podhrázská, J. (2017). Historical Changes in the Land Use Connected with Appropriation of Agricultural Land-Case Study of Cadastral Areas Dolní Věstonice and Modřice (Czech Republic). European Countryside 2017, 9(4), 658-678. [CrossRef]
- Tavares, F.O.; Almeida L.; Pinto A.; Tavares V.C. The Role of Stakeholders in Thermal Tourism: A Bibliography Review. In: Ratten V., Braga V. (eds) Stakeholder Entrepreneurship 2021. Springer, Singapore. [CrossRef]
- Tavares, F.; Santos, E. M. Validation of an Information Asymmetry Scale in the Portuguese Real Estate Market. Review of Business Management 2021, 23(4), p. 586-599. [CrossRef]
- Tavares, V. C.; Tavares, F.; Santos, E. The Value of Farmland and Its Determinants - The Current State of the Art. Land 2022, 11(11), 1908. [Google Scholar] [CrossRef]
- Tezcan, A.; Büyüktaş, K.; Aslan, Ş. A multi-criteria model for land valuation in the land consolidation. Land Use Policy 2020, 95, 104572. [Google Scholar] [CrossRef]
- Tione, S. E.; Holden, S. T. Urban proximity, demand for land and land shadow prices in Malawi. Land Use Policy 2020, 94, 104509. [Google Scholar] [CrossRef]
- Wentland, S. A.; Ancona, Z. H.; Bagstad, K. J.; Boyd, J.; Hass, J. L.; Gindelsky, M.; Moulton, J. G. Accounting for land in the United States: Integrating physical land cover, land use, and monetary valuation. Ecosystem Services 2020, 46, 101178. [Google Scholar] [CrossRef]
- Xu, F.; Ho, H. C.; Chi, G.; Wang, Z. Abandoned rural residential land: Using machine learning techniques to identify rural residential land vulnerable to be abandoned in mountainous areas. Habitat International 2019, 84, 43–56. [Google Scholar]
- Zhao, F.; Hitzhusen, F.; Chern, W. S. Impact and implications of price policy and land degradation on agricultural growth in developing countries. Agricultural economics 1991, 5(4), 311–324. [Google Scholar] [CrossRef]
- Zhao, Q.; Bao, H. X.; Zhang, Z. Off-farm employment and agricultural land use efficiency in China. Land Use Policy 2021, 101, 105097. [Google Scholar] [CrossRef]
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| The fields’ rent near urban areas have higher values. | 3.94 | 4 | 4 | 1.027 | 4.3 | 5.4 | 13.7 | 45.3 | 31.2 |
| In zones where more people live, land value is higher. | 3.92 | 4 | 4 | 1.107 | 6.1 | 4.8 | 14.4 | 40.1 | 34.6 |
| Fields which have national streets and other infrastructures nearby have more value. | 3.89 | 4 | 4 | 1.142 | 6.2 | 6.5 | 14.1 | 37.9 | 35.2 |
| If the fields are dry and lack water they have less value. | 3.88 | 4 | 4 | 1.047 | 4.7 | 5.6 | 16.6 | 43.2 | 30.0 |
| Fields with electricity have more value. | 3.87 | 4 | 4 | 1.134 | 6.1 | 6.5 | 15.5 | 38.0 | 33.9 |
| The kind of soil has an importance in the land’s value. | 3.87 | 4 | 4 | 1.098 | 5.3 | 7.9 | 12.3 | 43.9 | 30.6 |
| Fields which are next to urban zones have more value. | 3.86 | 4 | 4 | 1.07 | 5.1 | 7.0 | 13.2 | 45.8 | 28.9 |
| Flat fields are worth more than declivous ones | 3.86 | 4 | 4 | 1.053 | 4.2 | 7.1 | 16.8 | 42.2 | 29.7 |
| The soil quality and the cultivation made there affect the field’s value. | 3.85 | 4 | 4 | 1.024 | 4.7 | 5.9 | 15.2 | 48.1 | 26.1 |
| Fields next to the agricultural products selling markets have more value. | 3.85 | 4 | 4 | 1.098 | 5.4 | 7.9 | 12.7 | 44.4 | 29.5 |
| Climate changes have impact in property value. | 3.84 | 4 | 4 | 1.073 | 5 | 7.8 | 14.0 | 45.3 | 28.0 |
| The lower the drainage of the land, the lower its value. | 3.80 | 4 | 4 | 1.061 | 5 | 7.0 | 17.2 | 44.4 | 26.4 |
| A field that permits the use of agricultural equipment (tractors) has more value. | 3.80 | 4 | 4 | 1.112 | 5.4 | 8.2 | 16.6 | 40.5 | 29.2 |
| The more the declivous, the minor its value. | 3.78 | 4 | 4 | 1.053 | 5 | 7.6 | 15.8 | 47.2 | 24.4 |
| The smaller agricultural fields produce less. | 3.78 | 4 | 4 | 1.16 | 7.8 | 7 | 13 | 43.9 | 28.3 |
| The fields’ value is determined by the rent they offer. | 3.75 | 4 | 4 | 1.142 | 7.8 | 6.2 | 15.4 | 44.4 | 26.2 |
| Land value is the reflex of agricultural and forest cultures that it offers. | 3.74 | 4 | 4 | 1.019 | 5.1 | 7.0 | 16.3 | 51.7 | 19.9 |
| The land in less windy areas has higher value. | 3.73 | 4 | 4 | 1.115 | 6.1 | 8.1 | 18.6 | 41.3 | 25.9 |
| The bigger the property, the less its value per square meter is. | 3.63 | 4 | 4 | 1.172 | 7.3 | 10.4 | 18.8 | 38.8 | 24.7 |
| The land next to one that is already owned should be purchased, even if the value is high. | 3.09 | 3 | 4 | 1.391 | 20 | 16.3 | 15.1 | 32.3 | 16.3 |
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| Lands with good water drainage are more valued. | 4.15 | 4 | 4 | 0.923 | 3.3 | 2.5 | 9.3 | 46.3 | 38.7 |
| The better the quality of the soil, the higher its value. | 4.13 | 4 | 4 | 0.97 | 3.4 | 4.2 | 8.2 | 44.3 | 39.9 |
| Agricultural lands in safer areas (with fewer thefts and disturbances) have a higher value. | 4.07 | 4 | 4 | 0.981 | 3.4 | 4.2 | 12.0 | 43.3 | 37.1 |
| Lands with year-round water springs have a higher value. | 4.06 | 4 | 4 | 1.013 | 3.3 | 5.7 | 11.8 | 40.5 | 38.7 |
| Lands located on riverbanks where water flows all year round have a higher value. | 4.04 | 4 | 4 | 1.019 | 3.9 | 4.5 | 13.4 | 40.7 | 37.6 |
| Lands near tourist attractions are more sought after and have a higher value. | 3.99 | 4 | 4 | 0.99 | 3.6 | 4.2 | 15.4 | 43.3 | 33.5 |
| Lands with easy access for machinery have a higher value. | 3.98 | 4 | 4 | 1.004 | 3.4 | 5.7 | 13.8 | 43.8 | 33.2 |
| Flat or gently sloping lands have a higher value. | 3.95 | 4 | 4 | 0.979 | 3.0 | 5.4 | 16.1 | 44.1 | 31.4 |
| Lands with ponds or water reservoirs have a higher value. | 3.95 | 4 | 4 | 1.004 | 2.8 | 7.1 | 14.4 | 43 | 32.6 |
| Lands closer to transportation networks have a higher value. | 3.95 | 4 | 4 | 1.003 | 3.1 | 6.5 | 14.9 | 43.6 | 31.8 |
| Farmers, in general, face financial difficulties in acquiring large plots of land. | 3.94 | 4 | 4 | 1.037 | 3.9 | 6.4 | 14.3 | 42.5 | 32.9 |
| Lands near natural beauty spots have a higher value. | 3.94 | 4 | 4 | 1.022 | 3.6 | 5.6 | 17.2 | 40.7 | 32.9 |
| Lands near recreational areas are more attractive and have a higher value. | 3.94 | 4 | 4 | 1.048 | 4.8 | 5.3 | 13 | 44.4 | 32.5 |
| In areas with a higher population growth, lands have a higher value. | 3.94 | 4 | 4 | 1.022 | 3.6 | 6.7 | 13.8 | 44.4 | 31.5 |
| Areas with greater rural development have higher land values per square meter. | 3.93 | 4 | 4 | 1.104 | 7 | 3.0 | 13.7 | 42.7 | 33.7 |
| Lands with fruit tree plantations have a higher value. | 3.92 | 4 | 4 | 1.003 | 3.9 | 5.1 | 15.7 | 45.3 | 30 |
| Lands where irrigation systems can be used have a higher value. | 3.91 | 4 | 4 | 1.014 | 3.7 | 6.1 | 16 | 44.4 | 29.8 |
| Lands with higher population density have a higher value. | 3.90 | 4 | 4 | 0.963 | 3.1 | 5.3 | 17.2 | 47.0 | 27.3 |
| Lands near locations with historical heritage have a higher value. | 3.89 | 4 | 4 | 1.026 | 3.7 | 5.6 | 19.3 | 40.4 | 31.1 |
| Lands with artificial water resources (artesian wells, ponds, dams, watering holes, water tanks) have a higher value. | 3.86 | 4 | 4 | 1.063 | 4.3 | 7.1 | 16.6 | 41.6 | 30.3 |
| Lands with difficult access for machinery have a lower value. | 3.83 | 4 | 4 | 1075 | 4.3 | 8.9 | 15.1 | 43 | 28.7 |
| Lands in pollution-free environments have a higher value. | 3.83 | 4 | 4 | 1.061 | 5.4 | 5.6 | 16..6 | 45 | 27.3 |
| Lands at risk of waterlogging have a lower value. | 3.83 | 4 | 4 | 1.075 | 5.7 | 5.6 | 16.5 | 44.4 | 27.8 |
| Lands with a larger labor force available have a higher value. | 3.83 | 4 | 4 | 1.04 | 4.2 | 6.5 | 19.1 | 42.2 | 28 |
| Lands with higher rainfall have a higher value. | 3.82 | 4 | 4 | 1.077 | 5.3 | 6.5 | 17.4 | 42.7 | 28.1 |
| Older farmers possess more land than younger farmers. | 3.81 | 4 | 4 | 1.15 | 5.9 | 8.5 | 16.3 | 37.1 | 32.1 |
| Lands in animal hunting areas have a higher value. | 3.81 | 4 | 4 | 1.067 | 4.3 | 8.4 | 16.6 | 42.9 | 27.8 |
| Lands with rainfed crops have a lower value. | 3.80 | 4 | 4 | 1.015 | 3.7 | 7.5 | 19.1 | 45 | 24.7 |
| Lands closer to urban areas have a higher value. | 3.80 | 4 | 4 | 1.046 | 5.3 | 5.3 | 19.4 | 44.7 | 25.3 |
| Lands with surrounding walls or fences have a higher value. | 3.79 | 4 | 4 | 1.107 | 5.9 | 7.1 | 16.8 | 42.1 | 28.1 |
| Lands with forest plantations have higher market values. | 3.77 | 4 | 4 | 1.085 | 5.3 | 7.9 | 17.4 | 43.2 | 26.2 |
| Lands with regular shapes (square, rectangle) have a higher value. | 3.70 | 4 | 4 | 1.127 | 5.9 | 9.5 | 19.4 | 39.6 | 25.6 |
| Lands near churches, chapels, and other monuments have a higher value. | 3.70 | 4 | 4 | 1.147 | 5.7 | 10.1 | 20.7 | 35.7 | 27.8 |
| Smaller plots of land are more sought after than larger ones. | 3.40 | 4 | 4 | 1.268 | 9.6 | 17.7 | 17.9 | 33.1 | 21.7 |
| Initial eigenvalues | Extraction Sums of Squared Loadings | Rotation Sums of Squared Loadings | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Total | % of | % | Total | % of | % | Total | % of | % | |
| Variance | Accumulative | Variance | Accumulative | Variance | Accumulative | ||||
| 1 | 12.504 | 35.727 | 3.727 | 12.504 | 35.727 | 35.727 | 4.551 | 13.003 | 13.003 |
| 2 | 2.496 | 7.13 | 4.857 | 2.496 | 7.13 | 42.857 | 3.368 | 9.621 | 22.624 |
| 3 | 1.422 | 4.064 | 46.921 | 1.422 | 4.064 | 46.921 | 3.159 | 9.025 | 31.649 |
| 4 | 1.418 | 4.05 | 50.971 | 1.418 | 4.05 | 50.971 | 3.115 | 8.899 | 40.549 |
| 5 | 1.287 | 3.677 | 54.648 | 1.287 | 3.677 | 54648 | 2.916 | 8.331 | 48.879 |
| 6 | 1.235 | 3.529 | 58.177 | 1.235 | 3.529 | 58.177 | 2.18 | 6.228 | 55.108 |
| 7 | 1. 105 | 3.157 | 61.334 | 1.105 | 3.157 | 61.334 | 2.179 | 6.226 | 61.334 |
| Items | Component | Factors Interpretation | ||||||
|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | ||
| Wildlife hunting areas have higher value. | .693 | .146 | .008 | .274 | .122 | .057 | .101 | Characteristics intrinsic to the property's location |
| Land with more labor availability has higher value. | .664 | .129 | .329 | .001 | .084 | .120 | .213 | |
| Land closer to urban areas has higher value. | .650 | .257 | .125 | .238 | .074 | .080 | .248 | |
| Land closer to transportation networks has higher value. | .632 | .203 | .050 | .351 | -.011 | .227 | -.006 | |
| Land with a risk of waterlogging has lower value. | .620 | .061 | .287 | .170 | .289 | .011 | -.006 | |
| Land where irrigation systems can be used has higher value. | .606 | .132 | .427 | .111 | .163 | .091 | .107 | |
| Land with dryland crops has lower value. | .604 | .210 | .240 | .055 | .014 | .092 | .381 | |
| Land with fruit tree plantations has higher value. | .604 | .096 | .402 | .146 | .124 | .090 | .108 | |
| Land with higher rainfall has higher value. | .582 | .111 | .234 | .254 | .249 | .012 | .091 | |
| Smaller agricultural land has lower productivity. | .184 | .705 | .014 | .043 | .161 | .055 | .227 | Dynamic characteristics of the agricultural land market |
| Higher population areas have higher land value. | .087 | .699 | .255 | .169 | .156 | .180 | -.003 | |
| Less windy areas have higher land value. | .195 | .691 | .054 | .186 | .172 | .035 | -.089 | |
| Rents in land near urban areas are higher. | .080 | .688 | .236 | .173 | .106 | .259 | .122 | |
| Climate changes impact property value. | .155 | .548 | .139 | .127 | .268 | .206 | .135 | |
| Larger properties have lower value per square meter. | .215 | .547 | -.034 | .080 | .263 | .042 | .210 | |
| Land on riverbanks with year-round water flow has higher value. | .244 | .153 | .706 | .230 | .091 | .118 | .178 | Importance of water availability on agricultural land |
| Land with ponds or pools has higher value. | .278 | .092 | .649 | .252 | .100 | .059 | .122 | |
| Land with year-round water springs has higher value. | .262 | .068 | .632 | .240 | .104 | .182 | .040 | |
| Land with artificial water resources has higher value. | .321 | .203 | .620 | .143 | .175 | .005 | .160 | |
| Land near recreational areas is more attractive and has higher value. | .230 | .140 | .095 | .710 | .108 | .084 | .258 | Proximity to tourist destinations |
| Land near historical heritage sites has higher value. | .251 | .179 | .161 | .707 | .191 | .091 | .103 | |
| Land near natural attractions has higher value. | .218 | .163 | .265 | .682 | .160 | .112 | .188 | |
| Land near tourist destinations is in higher demand and has higher value. | .243 | .128 | .325 | .603 | .121 | .056 | .144 | |
| Better soil quality correlates with higher land value. | .194 | .203 | .362 | .537 | .106 | .197 | .142 | |
| Land with steeper slopes has lower value. | .171 | .162 | .129 | .080 | .762 | .088 | .101 | Physical characteristics of the land |
| Soil quality and suitable crops affect land value. | .161 | .133 | .002 | .111 | .682 | .292 | .129 | |
| Flat land is more valuable than sloped land. | .087 | .246 | .121 | .238 | .665 | .075 | .039 | |
| Poor drainage reduces land value. | .057 | .327 | .257 | .032 | .585 | -.003 | .170 | |
| Land near urban areas has higher value. | .154 | .207 | .056 | .129 | .575 | .329 | .044 | |
| Land with national roads and other infrastructure has higher value. | .104 | .137 | .197 | .113 | .148 | .762 | .033 | Positive externalities created |
| Land with access to electricity has higher value. | .140 | .174 | .230 | .045 | .180 | .728 | .007 | |
| Land value is influenced by agricultural and forestry crops it can support. | .063 | .142 | -.110 | .136 | .158 | .675 | .202 | |
| Land surrounded by fences or walls has higher value. | .162 | .107 | .212 | .152 | .125 | .175 | .744 | Improvements made on the property |
| Land with forest plantations has higher market value. | .150 | .204 | .232 | .289 | .095 | .011 | .670 | |
| Land with regular shape has higher value. | .299 | .090 | .019 | .254 | .209 | .084 | .647 | |
| Cronbach's alpha | .897 | .828 | .821 | .856 | .807 | .721 | .865 | |
| Items | Levene test for variance equality (Do we accept HO?) | Test for means equality | ||
|---|---|---|---|---|
| t-test | Male | Female | t-test (p-value) |
|
| The land adjacent to one already owned should be purchased, even if the value is high. | -2.557 | 2.97 | 3.96 | 0.011 |
| Land where irrigation systems can be used has greater value. | 2.202 | 3.97 | 3.80 | 0.028 |
| Items | Levene test for variance equality (Do we accept HO?) | Test for means equality | ||
|---|---|---|---|---|
| t-test | Yes, has another job besides agriculture | Does not have another job besides agriculture | t-test (p-value) |
|
| The value of land reflects the agricultural and forestry crops it can offer. | 2.057 | 3.80 | 3.63 | 0.040 |
| Land close to urban areas has a higher value. | 2.294 | 3.93 | 3.73 | 0.022 |
| Land that allows the use of agricultural equipment (tractors) has a higher value. | 2.119 | 3.86 | 3.67 | 0.034 |
| In areas with higher population growth, land has a higher value. | 2.561 | 4.01 | 3.79 | 0.011 |
| Land with year-round water springs has a higher value. | 2.266 | 4.12 | 3.93 | 0.024 |
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