Econometric modeling of Lamuyo and Blocky sweet pepper seed demand in Costa Rica using univariate time series

Main Article Content

Javier Paniagua Molina, M.Sc.
https://orcid.org/0000-0003-4987-1651

Abstract

A research was carried out to estimate the demand for commercial vegetable hybrid seed, in this case, the hybrid seed of Lamuyo and Blocky type sweet pepper. The interest is to contribute to the reduction of uncertainty in the strategic planning of companies interested in venturing this seed production of hybrids as a result of genetic improvement achieved by local initiatives. 


The annual time series of the harvested area of sweet pepper was used as a basis to create a forecast model and from the analysis of the import statistics, it was estimated the probability that found a sweet pepper and the probability of being lamuyo or blocky type. 


The model generated good forecasts for several years in the future, with stable confidence intervals, however, it is advisable to incorporate the new data presented each year and re-run the model to rectify the projections, since these models were created to be applied to short-term forecasts. 

Article Details

How to Cite
Paniagua Molina, J. (2017). Econometric modeling of Lamuyo and Blocky sweet pepper seed demand in Costa Rica using univariate time series. E-Agronegocios, 3(2). https://doi.org/10.18845/rea.v3i2.3687
Section
Artículos
Author Biography

Javier Paniagua Molina, M.Sc. , University of Costa Rica, Costa Rica.

Economista Agrícola, Master en Administración y Dirección de Empresas con Énfasis en Finanzas, docente Escuela de Economía Agrícola y Agronegocios, investigador en el Centro de Investigación en Economía Agrícola y Desarrollo Agroempresarial (CIEDA), Universidad de Costa Rica.

References

Gujarati, G.; Porter. D. (2010). Econometría. (5 ed). McGraw-Hill: México

Gutiérrez, M. (2015). “Dulcitico” el chile dulce tico. CRHoy.com. Disponible en:

http://www.crhoy.com/archivo/dulcitico-el-chile-dulce-tico/nacionales/

Hamilton, J. (1994). Time Series Analysis. Princenton University Press: West Sussex.

Kumar, V., Raut, S. (2012). Demand Forecasting for Fertilizers: A Tactical Planning Framework for Industrial Use. Proceedings of AIPA 2012, India.

Parkin, M., Loría, E. (2010). Microeconomía. Versión para Latinoamérica. (9 ed). Pearson Educación: México.

Sankaran, S. (2014) Demand forecasting of fresh vegetable product by seasonal ARIMA model. International Journal of Operational Research, 20 (3): 315-330

Stock, J.; Watson, M. (2012). Introducción a la Econometría. (3 ed). Pearson Educación:

Madrid.

Yang, H., Hu, J. (2013). Forecasting of Fresh Agricultural Products Demand Based on the ARIMA Model. Advance Journal of Food Science and Technology, 5(7): 855-858

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