Semiparametric Time-Series Model Using Local Polynomial: An Application on the Effects of Financial Risk Factors on Crop Yield

Syed Ejaz Ahmed, Dursun Aydin and Ersin Yilmaz
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Syed Ejaz Ahmed: Department of Statistics, Faculty of Mathematics and Science, Brock University, St. Catharines, ON L2S 3A1, Canada
Dursun Aydin: Department of Statistics, Faculty of Science, Mugla Sitki Kocman University, Muğla 48000, Turkey
Ersin Yilmaz: Department of Statistics, Faculty of Science, Mugla Sitki Kocman University, Muğla 48000, Turkey

JRFM, 2022, vol. 15, issue 3, 1-12

Abstract: This paper proposes a semiparametric local polynomial estimator for modelling agricultural time-series. We consider the modelling of the crop yield variable according to determined financial risk factors in Turkey. The derivation of a semiparametric local polynomial estimator is provided with its fundamental statistical properties to estimate the semiparametric time-series model. This paper attaches importance to precision agriculture (PA) and therefore a local polynomial technique is considered due to some advantages it has over alternative methods. The introduced estimator provides less estimation risk, involving both parametric and nonparametric components that allow the estimator to represent the data structure better. From that, it can be said that the proposed estimator and model is beneficial to agricultural researchers for financial decision-making processes.

Keywords: local polynomial regression; crop yield; financial risk; semiparametric time series (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2022
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