FORECASTING OF AGRICULTURAL PRODUCTION INDICATORS IN SURKHANDARYA REGION USING THE ARIMA MODEL

Abdurayimov Kamoliddin Khurram Oglu

GREEN ECONOMY AND DEVELOPMENT, 2026, vol. 4, issue 7, 369-376

Abstract: This article applies the ARIMA (1,2,0) model to forecast agricultural production in theSurkhandarya region. The stationarity of the time series was examined using the Augmented Dickey–Fullertest, while the model parameters were identified based on the ACF and PACF correlograms. Model reliabilitywas evaluated using the coefficient of determination, information criteria, and the Mean Absolute PercentageError (MAPE). The absence of autocorrelation was confirmed by the Ljung–Box test, whereas the absence ofheteroscedasticity was verified using the ARCH–LM test. Forecast values for 2026–2030 were estimated witha 95% confidence interval

Keywords: ARIMA model; forecasting; agricultural production; time series; stationarity; Augmented Dickey–Fuller test; autocorrelation; Surkhandarya region (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:teu:ged000:v:4:y:2026:i:7:id:11610

DOI: 10.5281/zenodo.21324207

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