Forecasting and managing the development of regional manufacturing based on econometric modeling and digital interface

The article focuses on modeling, forecasting, and scenario-based management of manufacturing output, using the Nizhny Novgorod Region as a case study. The relevance of the work stems from the need of government authorities and businesses for a reliable tool when making strategic decisions under conditions of economic uncertainty. The main objective is to construct econometric models that provide medium-term forecasts of industrial output shipments and to develop a digital calculator with a web interface for analyzing various scenarios of industrial sector development. The scientific novelty of the study is fourfold: (1) an extended Cobb – Douglas production function incorporating macro-level conditions is refined; (2) an approach to separately modeling the real and inflationary components of industrial output shipments is proposed and implemented; (3) a novel methodological technique for forecasting one price index (the producer price index, PPI) based on another (the consumer price index, CPI) is proposed and implemented; and (4) new approaches to scenario modeling of the regional economy that incorporate macro-forecasts are proposed and implemented. The study employs a wide range of time-series econometric methods, including ARIMAX and ARDL models, stationarity tests, residual diagnostics, and automated specification selection. The principal findings consist of two predictive ARDL models, which were integrated into the newly developed digital calculator with a user-friendly web interface. It is shown that real manufacturing output in the Nizhny Novgorod Region is influenced by the value of fixed assets in the “Manufacturing” type of economic activity, the permanent resident population, retail trade turnover, the monthly average consumer price index, and the price of Urals crude oil. Based on the constructed models, a digital calculator was developed – a flexible tool that enables users to promptly assess the consequences of changes in key macroeconomic parameters, compare alternative development scenarios, and produce analytically grounded forecasts of the region's manufacturing development. This tool appears highly useful for government authorities and other users in planning and optimizing production processes.