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Vol. 5 No. 3 (2026)
"Labor Economics and Human Capital" scientific electronic journal

Entrepreneurship Development

ECONOMETRIC MODELING AND EVALUATION OF DEVELOPMENT INDICATORS OF COTTON – TEXTILE CLUSTERS

DOI 10.67668/LEHC/vol5iss3/338 Google Scholar Google Scholar Pages 133-141

Published 2026-09-30

Authors
Djuraev Turabay
Affiliation
Tashkent State University of Economics image/svg+xml
PDF (Russian)

Abstract

The article is devoted to the development and application of an econometric model in the form of a system of simultaneous equations for forecasting the development indicators of a cotton-textile cluster (CTC). Particular attention is paid to testing the identifiability of the system. Due to the presence of endogenous variables, the two-stage least squares method (2SLS) is applied to estimate the model parameters. The authors propose an over identified system consisting of six linear equations with four variables. Based on this model, a six-step algorithm for evaluating CTC development indicators has been developed in specialized econometric software. At the first step, the volume of raw cotton (seed cotton) production on a farm is determined using either a classical linear equation or the Cobb-Douglas production function in logarithmic form. The result of this step is the pure theoretical forecast values of the volume of raw material produced, excluding the influence of random factors. At the second step, the volume of cotton fiber production is calculated: for this purpose, the previously obtained value of the raw cotton volume is multiplied by the technological fiber yield coefficient. From the third to the fifth step, the indicators of the vertically integrated technological chain are calculated, covering enterprises of the oil and fat sector, as well as spinning, weaving, finishing, and garment production. At the sixth step, an algorithm for calculating financial indicators is applied, which makes it possible to assess the overall economic efficiency of the CTC.

Keywords

Cotton-textile cluster, econometric modeling, integration, time series, econometric analysis, efficiency evaluation, value-added chain

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