STATISTICAL FORECASTING OF DEMOGRAPHIC PROCESSES AND LABOUR MARKET BALANCE: AN INTEGRATION OF HOLT EXPONENTIAL SMOOTHING AND CANONICAL CORRELATION ANALYSIS (CCA) METHODS

Abstract

The article presents a medium-term scenario forecast of labour market and demographic indicators of the Republic of Karakalpakstan for 2026–2030. The study is based on a two-stage approach that integrates C.C.Holt’s two-parameter exponential smoothing method with Canonical Correlation Analysis (CCA). At the first stage, a baseline forecast is constructed using the Holt method; at the second stage, it is adjusted on the basis of multivariate canonical relationships between demographic-digital factors and labour market indicators. The forecasting accuracy of the model corresponds to international standards and has been empirically validated through backtesting and leave-one-out cross-validation procedures. Three scenarios — pessimistic, baseline, and optimistic — have been developed, with the differences between them decomposed into contributing factors using the Laspeyres-Paasche-Fisher index decomposition. The findings empirically substantiate the priority role of digital skills development and labour migration management policies for the region.