A modelling of the number of almazaras by municipality in Andalusia
- Cueva López, Valentina
- Rodriguez Avi, José 1
- Olmo Jiménez, María José 1
- Rodríguez Reinoso, Julia 1
- 1 Departamento de Estadística e I. O., UNIVERSITY OF JAÉN. SPAIN
ISSN: 1133-3197, 1697-5731
Año de publicación: 2022
Título del ejemplar: The Economic Problems between Economic Globalization and Crisis Management II
Volumen: 40
Número: 3
Tipo: Artículo
Otras publicaciones en: Estudios de economía aplicada
Resumen
An almazara (oil mill) is an essential piece in the production of olive oil since it is the place where the olive is milled and the olive oil is obtained. They are usually linked to producer cooperatives. They are structures that require specialized machinery and that on multiple occasions are underutilised, given the presence of several of them at very close distances. In addition, they characterise the mainly olive grove municipalities and their study provides a valuable information of economic interest. From a statistical point of view, the “number of oil mills per municipality” is a count data variable that exhibits overdispersion. In this study, we focus on the oil mills found in municipalities of Andalusia. First, we make a descriptive study of the variable. Second, we model this data according to the most suitable probabilistic model. Finally, several generalized linear regression models based on different geographic and socioeconomic variables are proposed and the best one (using the Akaike information criterion) is selected.
Referencias bibliográficas
- AICA3 (2020). Agencia de Información y Control Alimentarios. Información del sector
- Akaike, H. (1974), A new look at the statistical model identification, IEEE Transactions on Automatic Control 19 (6): 716-723.
- Cameron A. C, Trivedi P. K. (2013). Regression analysis of count data, 2nd ed. Cambridge University Press, Cambridge
- Consul, P. C.; Famoye, F. (1988): Maximum likelihood estimation for the generalized Poisson distribution when sample is larger than variance. Communications in Statistics: Theory and Methods, 17, 299-309.
- Consul, P.C.; Famoye, F. (1992): Generalized Poisson Regression Model. Communications in Statistics: Theory and Methods, 21(1), 89-109.
- Cueva-López, V.; Olmo-Jiménez, M.J.; Rodríguez-Avi, J. (2021). An over and underdispersed Biparametric extension of the Waring Distribution. Mathematics 9, 170.
- Damas Rico, E. (1997). Análisis no paramétrico de la eficiencia relativa de las almazaras cooperativas en la provincia de Jaén durante el período 1975-1993. In Revista española de economía agraria (Issue 180, pp. 279–303). Ministerio de Agricultura, Pesca y Alimentación,
- Famoye F, Wulu J. T., Singh K. P. (2004) On the generalized Poisson regression model with an application to accident data. J Sci 2:287–295
- Hilbe J. M. (2011). Negative binomial regression, 2nd ed. Cambridge University Press, Cambridge
- Irwing, J.O. (1968): The generalized Waring distribution applied to accident theory. Journal of the Royal Statistical Society. Series A, 131, 205-225.
- Johnson, N. L.; Kemp, A. W.; Kotz, S. (2005): Univariate discrete distributions. Wiley, New York.
- Ministerio de Agricultura, Pesca y Alimentación de España (2019): Encuesta sobre superficies y rendimientos de cultivo.
- Olmo-Jiménez, M.J.; Rodríguez-Avi, J.; Cueva-López, V. (2019): A review of the CTP distribution: a comparison with other over- and underdispersed count data models. Journal of Statistical Computation and Simulation, 88(14), 2684-2706.
- Parras Rosa, M and Mozas Moral, A. (2021). La Cadena de Valor de los Aceites de Oliva. In Informe anual de coyuntura del sector oleícola, pp 11-26. University of Jaén.
- R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
- Rapoport, H.F. (2008): Botánica y morfología. En: Barranco, D., Fernández Escobar, R., Rallo, L., (Eds.). El cultivo del Olivo. 6ª Edición. Madrid. Junta de Andalucía y Ediciones Mundi-Prensa, 37-62.
- Rodríguez-Avi, J.; Conde-Sánchez, A.; Sáez-Castillo, A. (2003): A new class of discrete distributions with complex parameters. Statistical Papers, 44, 67-88.
- Rodríguez-Avi, J.; Conde-Sánchez, A.; Sáez-Castillo, A.; Olmo-Jiménez, M.J. (2007) A new generalization of the Waring distribution. Computational Statistics and Data Analysis, 51; 6138 – 6150
- Rodríguez-Avi, J.; Conde-Sánchez, A.; Sáez-Castillo, A.; Olmo-Jiménez, M.J. Martínez-Rodríguez, A.M. (2009): A generalized waring regression model for count data. Comput Stat Data Anal, 53, 3717–3725.
- Rodríguez-Avi, J.; Olmo-Jiménez, M.J. (2017): A regression model for overdispersed data without too many zeros. Statistical Papers, 58, 749-773.
- Ruiz, C. (2006): Disfunciones en el gobierno de las sociedades cooperativas agrarias: el caso de las almazaras cooperativas. GEZKI, 2, 73-103.
- Ruiz Jiménez, C.; García Martí, E.; Hernández Ortiz, M.J. (2013): Cómo responden a la crisis económica actual las Sociedades cooperativas agrarias. El caso de las Almazaras cooperativas andaluzas. REVESCO. Revista de Estudios Cooperativos, 113, 120-149.
- Sellers, K.F.; Borle, S.; Shmueli, G. (2012). The COM-Poisson model for count data: a survey of methods and applications. Appl Stoch Models Bus Ind., 28, 104–116.
- SIMA (2021). Sistema de Información Multiterritorial de Andalucía. IECA. Dirección web: https://www.juntadeandalucia.es/institutodeestadisticaycartografia/sima/index2.htm
- Xelakaki, E. (1983): The univariate generalized Waring distribution in relation to accident theory: proneness, spells or contagion? Biometrics, 39, 887-895.