Univariate analysis to describe and forecast banana production in the piura region

Abstract

Agricultural activity in the Piura region is a fundamental activity for its development, the implementation of forecasts is a useful tool for economic agents to plan and make correct decisions. Two results are of interest in the study, the first to identify, estimate and validate an adjusted model to forecast banana production and the second to make the forecast of banana production for the period from October 2020 to October 2022. To specify the objectives, the univariate analysis was carried out with the Box and Jenkins methodology. The data comes from the Central Reserve Bank of Peru, monthly data from July 2000 to September 2020 were considered. Once the assumptions have been met, the best fit model to represent banana production and make forecasts is an Autoregressive Integrated Moving Average or ARIMA model. The forecast for banana production has a downward trend for the next few years.

Keywords: Forecast, Time series, ARIMA models, Agricultural production.

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