THE USE OF GENERATIVE ARTIFICIAL INTELLIGENCE IN THE MODELING AND ECONOMIC ANALYSIS OF ECONOMETRIC MODELS
Abstract
The article is devoted to the study of the use of free functions of generative artificial intelligence (AI) system in econometric modeling of nonlinear multifactor economic processes, using the Cobb–Douglas production function as an example. The relevance of such research at the present stage of development and integration of artificial intelligence elements into all areas of economic activity is beyond doubt. The paper emphasizes the necessity of studying production functions that make it possible to account for the asymmetric laws of social production, the uneven distribution of economic resources among the structural components of the national economy, and to provide the most accurate macroeconomic forecasts. The article presents the results of a comparative analysis of estimated model parameters based on the provided data using the MS Excel application and queries to the generative AI ChatGPT. The paper examines the problem of discrepancies that arose between the calculations in MS Excel spreadsheets and the values of the production function and economic indicators generated by generative AI ChatGPT, based on the specified form of the Cobb–Douglas function and observational data describing enterprise performance over several periods, including the value of output, the value of fixed production assets, and labor costs. Through experimental investigation, the source of inaccuracies in the calculations compared to the results obtained in MS Excel spreadsheets was identified by analyzing the algorithm applied by generative AI ChatGPT in computing exponential functions. The results of constructing isoquants for the specified form of the production function using generative AI ChatGPT are analyzed, which may not fully correspond to the needs of a practicing economist. Finally, the advantages and disadvantages of employing free functions of generative artificial intelligence ChatGPT in econometric modeling of nonlinear multifactor economic processes are assessed, illustrated through the case of a comprehensive economic analysis of the Cobb–Douglas production function indicators.
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