An Examination on the Structure and Behaviour of Global Agricultural Productivity: a Markov-Switching Regression

Yen Shen Huan, Chun Cheong Woon, Siok Kun Sek, Khang Yi Sim
Statistika, 105(3): 333–351
https://doi.org/10.54694/stat.2024.47

Abstract
This study investigates the behaviour of agricultural productivity and its determinants using nonlinear Markovswitching regression. The objective is to investigate how agricultural productivity reacts to global factors and if the regression function varies due to threshold breaks. The study focuses on three agricultural sectors (crop, food, and livestock) from 1961 to 2021. The results are compared. The results show that the world uncertainty index has negative effects on the production of crops and food, but not on livestock. Besides, other global factors, namely GDP, inflation, energy, and non-energy commodity prices, have limited or no direct impact on agricultural production growth, but these factors may affect agricultural production indirectly. Furthermore, all agricultural production categories tend to grow at a decreasing rate. Additionally, agricultural production growth for all categories is expected to remain in a high production state with a higher probability. The findings might provide useful information to policymakers to improve the production and development of agricultural sectors.

Keywords
Agriculture, commodity price, inflation, macroeconomic factors, nonlinear Markov-switching regression, uncertainty