Food Security Indices In Ukraine: Forecast Methods And Trends

Abstract

The paper offers the calculation procedure of the integrated Food Security Index (FSI) based on the three-component analysis: economic accessibility, physical security, the sufficiency of consumption. It offers the methodology for forecasting under the conditions of macroeconomic instability based on the Food Security Indices. It shows that the standard forecasting methodology based on the separation of trend (deterministic) and random components cannot be applied in conditions of alternating intervals of economic growth and crises. In particular emphasis is placed on Jackson-Watson's methodology, which is based on the analysis of the internal structure of the process. The three-parameter ARIMA model was used in the forecast estimates of the Food Security Indices. The applied methods are complemented by exponential smoothing, damped trend model, linear and exponential smoothing, namely, Brown method, and two-parameter smoothing method (Holt's method), Pearl-Reed curve model. The research offers a food security risk assessment procedure in virtue of the econometric forecast error properties. Based on data mining, the results of forecasting the individual indices and the integrated Food Security Index make it possible to state a satisfactory condition that is unlikely to change shortly.

Minimizing the Error Gap in Smart Framing by Forecasting Production and Demand Using ARIMA Model

“…Analysts have been centered on straight models for the beyond a couple of many years since they have demonstrated to be easy to comprehend and apply. Whenever the occasional change request is enormous or the diagnostics neglect to demonstrate that the time series is fixed after the occasional change, the conventional ARIMA approach turns out to be expensive, and as a rule, it is challenging to lay out a model [38,39]. e static boundaries of the old-style ARIMA model are viewed as the essential requirement in extending high factor occasional interest in such examples.…”

“…e cumulative influence of specific cycles may have an impact on the behavior of the time series. For example, utilization and supply are constantly altering stock status, but the usual level of stocks is not totally fixed in stone by the cumulative influence of the rapid changes throughout the inventory interval [39,40]. Albeit momentary stock qualities might change with significant factors concerning this normal worth, the series' drawn out level will stay consistent.…”

Management and Production Engineering Review

“…The innovation can address the challenges that these economies face, such as cleaner production (Kadiyevskyy and Klymenko, 2014;, overcoming poverty and social insecurity (Starychenko et al, 2021), importing technology and adapting to modernize production, particularly agriculture (Hyk, 2021;Kaminskyi et al, 2021).…”

Formation of a System of Indicators of Assessment of Economic Security of Regions

“…Representative indicators of economic security make it possible to assess the protection against threats to the economy of the region, to timely assess the state of the economy of the region and to apply appropriate mechanisms (Iarmosh & Khomiakova, 2020). The quality and reliability of the preparatory phase depend not only on the results of the research and analysis, but also on the correctness of the conclusions that form the basis of management decisions and the foundation of practical measures programs to ensure a sufficient level of economic security of the region (Starychenko, et al, 2021). The indicators do not reveal the reasons for the region's non-compliance with the parameters of sufficient socio-economic development, but the economic security indicators can be used to judge the effectiveness of socioeconomic activities in the region (Podgorna, et al, 2020).…”