Application of a Nonparametric Method for Assessing the Cointegration of the Indices of Change in Capital Rate, Return on Assets and Labor Productivity
- Authors: Portnov A.V.1
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Affiliations:
- Saint Petersburg State University of Economics
- Issue: Vol 19, No 2 (2023)
- Pages: 260-265
- Section: Regional and Sectoral Economics
- URL: https://journals.eco-vector.com/2541-8025/article/view/568559
- ID: 568559
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Abstract
The article presents an assessment of the cointegration of the indices of capital productivity, stock-labor ratio, and labor productivity index. The purpose of the research. Evaluation of the existence of long-term relationships between the indices of capital productivity, stock-labor ratio, and labor productivity index. As part of the study, an attempt was made to assess the presence of a long-term equilibrium between the studied indicators using a non-parametric method for a more detailed understanding of the economic nature of labor productivity. A non-parametric method for assessing the probability of cointegration was used for the first time in the focus of indicators of capital productivity, capital-labor ratio, and productivity. Results. As a result of the study, we can conclude that with an extremely low probability, changes in fixed assets and indicators including them (capital-labor ratio, capital productivity) in the long run have a unidirectional development with the labor productivity index. In this regard, the prospect of searching for performance properties and relationships with fixed assets opens to determine the optimal ratio of production resources, monitoring and management at the enterprise level. Approbation of the non-parametric method has confirmed its applicability to time series with a small number of observations, which makes it possible to use this method for conducting economic research in conditions of limited (short) data.
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About the authors
Aleksandr V. Portnov
Saint Petersburg State University of Economics
Author for correspondence.
Email: portnov-14@mail.ru
SPIN-code: 2111-8676
postgraduate student of the Department of Statistics and Econometrics
Russian Federation, St. PetersburgReferences
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