Econometric Methods Research Articles

Measuring Efficiency Performance in Economic Productivity Function: Parametric and Non-Parametric Frontier Approach

The parametric and non-parametric frontier approach is the famous frontier measurement efficiency in economic productivity. Many researches on economics-based has focused on efficiency. Basically, efficiency comprises two important components. First is technical efficiency and second is allocative efficiency. Combination of technical and allocative efficiency called as economic efficiency. In order to measure both components of efficiency, parametric and non-parametric approaches have been utilized to either estimate or calculate the efficiency frontier. Many studies have adopted non-parametric, deterministic approach such as Data Envelopment Analysis (DEA) that impose no functional form on the cost or production function, but parametric estimation of cost, production, or profit functions are more relevant approach in the economics-based literature. Stochastic Frontier Approach (SFA) is the most popular among parametric model approach. Deterministic frontier functions can be solved using either mathematical programming or econometric techniques, while stochastic specifications are estimated solely through econometric methods. This study’s main contribution is a review of efficiency concepts, measurement methods, and the strengths, limitations, and data requirements of parametric and non-parametric models.

Risk Of Eviction And Women’s Technology Adoption: Some Evidence From Southwestern Nigeria

ABSTRACT: In the presence of tenure insecurity that many women face in developing societies because of patriarchal norms, farmers may not adopt farm technologies because there is no assurance of reaping the benefits. This article examines how the risk of eviction affects women’s fertilizer use and adoption of early maturing seed varieties. For the empirical analysis, I employ individual-level data that was collected from 180 women rice farmers in southwestern Nigeria with a multistage sampling technique and analyse the data with both econometric methods that address possible endogeneity issues and those that do not. I analyse the relationship between the risk of eviction and fertilizer use with the Two Stage Least Squares (2SLS) and Ordinary Least Squares (OLS) methods and analyse the relationship between the risk of eviction and the adoption of early-maturing seed varieties with the Two Stage Conditional Maximum Likelihood (2SCML) and probit methods. I find women who are cultivating family-allocated, husband-allocated and purchased plots to be significantly less likely to have fears of eviction than those who are cultivating fixed-rent plots, even as the risk of eviction have different effects on fertilizer use and on the adoption of early-maturing rice varieties respectively. While it makes the women spend less on fertilizer, it makes them more likely to adopt early maturing seed varieties. These would suggest that the women are responding to the unfavourable production environment from tenure insecurity with lower investments in soil fertility and shortened time horizons towards minimizing their losses in the event of eviction. The results also suggest that the women may invest in soil fertility if the operating environment becomes more favourable with better tenure. The policy implications of the findings are thus evident. Women are evidently not averse to adopting farm technologies by default; to thus improve adoption rates of farm technologies, policymakers should adapt technologies to local socioeconomic conditions, while exploring how to make tenancy contracts and the social norms that underpin customary tenure systems more amenable to granting women tenure security. These would help protect land resources from degradation, make agricultural incomes sustainable, and facilitate socio-economic development.

Межрегиональные эффекты инноваций в России: анализ с позиций байесовского подхода

This study analyzes the interregional effects of innovation in Russia. The hypothesis of the presence of interregional effects is tested by combining the methods of spatial econometrics and Bayesian approach. Using panel data on Russian regions for the period from 2000 to 2021, the author calculates posterior probabilities for a set of spatial regression models that model interregional effects of innovation in different ways. Within the framework of Bayesian approach 6 models were selected for comparison: model without spatial effects (OLS), model with spatial lag of the dependent variable (SAR), model with spatial lag of the error (SEM), model with spatial lags of the explanatory variables (SLX), spatial Durbin model with lags of dependent and explanatory variables (SDM), as well as spatial Durbin model with lags of the explanatory variables and error (SDEM). Based on our calculations, we can conclude that the spatial correlation of innovation in Russian regions is not as strong as it has been assumed in previous studies. This can be considered as evidence in favor of the fact that the concept of interregional spillovers of innovations is poorly consistent with the historical, institutional and territorial peculiarities of Russia, and the methods generally accepted in other countries for such analysis are unsuitable in the Russian context. The results obtained can be taken into account in further research involving spatial modeling of regional innovations. More attention should be paid to the spatial effects of explanatory variables, in particular, interregional spillovers of R&D expenditures, as well as dynamics in the innovation process

Econometric Modeling of Environmental Pollution Factors and Their Impact on Life Expectancy in Uzbekistan

The article examines the impact of environmental pollution factors on life expectancy in Uzbekistan. The study is based on econometric modeling methods, including panel data on the country’s regions for the period of 2010-2023. The area of protected natural areas, the volume of pollutant emissions into the atmosphere, the provision of doctors and hospital beds, and access to drinking water were utilized as factors influencing life expectancy. Despite the identification of some relationships, the modeling results showed limited explanatory power of the selected models, which is associated with the low quality and incompleteness of statistical data. The study revealed significant regional differentiation and polarization in environmental indicators, which requires measures to improve the quality of data and take into account additional factors.

MNEs Entry Mode Choices: The Impact of Past on Current. Evidence from an Emerging Economy

The paper examines the effect past entry strategies have on current ones on a country level, Turkey. It illustrates how international experience and institutional distance affect the way an entry-strategy is formed, and the procedure followed -mode learning, mode inertia, mode dynamics. To do so, it synthesizes the literature review within the framework of Benito et al. (2009). This paper’s modifications are empirically tested through a sample of 408 foreign equity investments. The econometric testing method implemented is that of Binary Logistic Regression. The period of investigation extends between 2011 and 2017. Results indicate that MNEs entering the Turkish secondary and tertiary Turkish sectors tend to utilize past entry mode strategies. Furthermore, the higher the past mode strategy is for an MNE, then it is 4.4 more possible for them to choose a wholly owned subsidiary.

Macroprudential Policies in the Light of the Development of Information Technologies: A Synthesis on the Effective Early Warning Signals

In response to recent recurrent crises, innovative macroprudential policies (MaPs) have been framed and implemented to address the weaknesses of market-led microprudential mechanisms and enhance the stabili­ty of financial systems. However, the effectiveness of the tools used to implement MaPs remains a critical research question. Early warning signals (EWS) serve as indicators of potential future crises. This paper explores approaches for identifying EWS to optimize the impact of MaPs, particularly in light of advances in information technology. It provides a comprehensive review of academic studies that identify effective EWS by analyzing numerical data through econometric and machine learning (ML) methods or by extracting economic insights from text using deep learning (DL) techniques — innovative methods for financial supervision and regu­lation. The findings, considering current regulatory practices, highlight the benefits of ML-based approaches for processing large sets of numerical data and the growing potential of text-based methods for assessing economic expectations.

Удаленная занятость в больших городах: выгода для работников в терминах заработной платы

Introduction. The transition to telecommuting in response to restrictive measures implemented in the context of the COVID-19 pandemic raises the question of its long-term effects in defining a new post-covid labor market. Purpose. The article aims at establishing spatial aspects in the analysis of the profession-defined differences found among remote workers’ wages. Materials and Methods. The data base of the research includes HeadHunter job vacancies with a remote work schedule posted in the period from December 12, 2022, to January 12, 2023. Econometric analysis methods help estimate the return of job vacancies in large cities in terms of population on the remote workers’ proposed wages. Results. Unlike in small cities, remote employment in large cities has a negative influence on the proposed wages, except for IT and sale areas. It is worth highlighting an IT area with the highest increase in the offered wages taking into consideration the size of the post vacancy city: employment in Moscow, St Petersburg, and other million-plus cities are “rewarded” by 45.5, 20.8, and 8.4 %, respectively. At the same time, Moscow employers in science and education, marketing, advertisement, PR, and administration offer the lowest wages among both large and small cities’ employers. Conclusions. The transition to remote employment in the post-COVID labor market has led to refocusing on secondary forms of employment, as well as spatial heterogeneity in the remote workers’ wages. Further research may be devoted to the research of differences in the office and remote IT workers’ wages in terms of compensatory differences.

Пространственный анализ инфраструктурных эффектов экономической динамики регионов России

Sustainable development of the transport system ensures the economic space unity, integrity and national security. The study hypothesises that infrastructure as an essential factor of well-being brings economic benefits to a region and determines its socio-economic growth, with effects extending beyond the region itself. Econometric and geoinformation methods were combined to conduct a spatial analysis of the impact of the capital-labour ratio, transport and telecommunication infrastructure on gross regional product per capita and labour productivity in industry, as well as to assess direct and spillover effects. The estimates revealed a statistically significant positive spillover effect of the capital-labour ratio, railway and telecommunication development indices on economic development. At the same time, negative direct effects of railway infrastructure indices on industry indicate that, in conditions of concentration of economic activity, the increasing transport system load does not correspond to its physical growth rates under heavy wear. This conclusion is confirmed by a negative spillover effect of the capital-labour ratio on labour productivity in industry in two model specifications with a direct positive effect. Providing access to networks and information resources for enterprises and population, as well as increasing technological capabilities and the speed of interaction between economic entities cause positive externalities of telecommunications for economy. Telecommunication infrastructure is a factor of industrial production growth, however, its negative spillover effects show that regions surrounded by regions with high mobile penetration rate are experiencing a slowdown in labour productivity in industry. The obtained estimates and the spatial correlation between gross regional product per capita and labour productivity in industry should be considered in programmes for financing infrastructure projects.

Assessment of the impact of socio-economic indicators of the Volga Federal District of the Russian Federation on the number of payers of the Professional income tax

This article examines the impact of socio-economic indicators of the Volga Federal District (hereinafter – VFD) on the number of payers of the special tax - «Professional income tax (hereinafter – PIT)». The relevance of the article is due to the need to assess various socio-economic effects that cause an increase in the number of PIT payers in the regions of the Russian Federation. The purpose of this article is to identify these socio-economic indicators and then assess their impact on increasing the number of PIT payers in the region, which allows us to develop measures aimed at tax management in a particular region. Using econometric modeling methods, the authors assessed the impact on the number of PIT payers of such socio-economic indicators of the regions of the Volga Federal District as the number of individual entrepreneurs (hereinafter referred to as sole proprietors), GRP, the execution of regional budgets on PIT revenues, unemployment and nominal accrued wages. The materials used in the research process were obtained from open sources of official state statistics, consolidated tax and budget reports. The main results of this study are: - the indicator of the number of sole proprietors has a positive relationship with the number of PIT payers, which allows us to conclude that in regions with a larger number of individual entrepreneurs, the number of NPD payers is also growing; - the indicator of the number of unemployed has an inverse relationship with the number of PIT payers in the regions of the Russian Federation; Based on the results of an econometric study, the author concludes that a number of socio-economic indicators of the regions of the Volga Federal District have a significant impact on the number of PIT payers.

ПРОГНОЗ ФАКТОРОВ, ОКАЗЫВАЮЩИХ ВЛИЯНИЕ НА ПОКАЗАТЕЛИ ИННОВАЦИОННОЙ АКТИВНОСТИ РЕГИОНОВ РОССИИ

the article examines the problem of limitations of existing rating models in forecasting and analyzing the development of innovation processes in a regional context due to limited possibilities for integrating various factors, such as educational systems and financial instruments. The need to develop and implement new forecast models that take into account multiple aspects related to education and the financial component of regional development is emphasized. The study also addresses the importance of socio-economic development in determining the readiness of regions to introduce innovations and create an innovative economic environment. The article presents an analysis of the factors influencing the innovative development of regions, with an emphasis on the level of monopolization of the market environment as an important factor affecting the dynamics of innovation, and also puts forward proposals for stimulating technological innovation and ensuring their financial support to improve financial stability at the state and regional levels. Using econometric modeling methods, the authors assess the impact of various variables. Studying the impact of these factors on the dependent variable allows us to determine their significance for the economic process and the development of resource management strategies. It is shown that investments in innovative research, human resources, educational structure and technological parameters of production have a significant impact on innovative activity. The study is conducted using econometric modeling techniques, including multiple linear regression and short regression models to identify significant factors. Models are checked for compliance with the conditions of the Gauss-Markov theorem, heteroscedasticity and autocorrelation of residuals using appropriate statistical tests. The results of the analysis confirm the statistical significance and adequacy of the models, and also allow us to identify key factors. At the same time, opportunities for improving the coordination of actions to develop the innovative potential of regions are identified based on the results of econometric modeling.

КРИВАЯ БЕВЕРИДЖА О РЫНКЕ ТРУДА В РОССИИ

The purpose of this research is to analyze the labor market employing the Beveridge curve. The following tasks were set: 1) to describe conceptually the properties of the curve, 2) to build the curve using real data, 3) to apply the curve to the analysis of the labor market, 4) to decompose vacancy and unemployment levels into groups of changes driven by different factors, 5) to test econometrically the hypothesis that there is no long-term relation between the two levels. Certain methods of econometrics of time series were applied. The results are as follows: using data for 2000-2023 we 1) visualized the Beveridge curve, 2) applied it to the analysis of the labor market, 3) decomposed vacancy and unemployment levels into three groups of changes, 4) found empirical evidence of long-term relationship between these levels. To conclude, the Beveridge curve is a useful and reliable instrument of labor market diagnostics.

THE RESPONSE OF BRICS TRADE INTEGRATION TO GEOPOLITICAL RISKS

Mounting geopolitical risks have led over time to a reorientation of trade integrations across different economic blocs. As one of the increasingly dominant global blocks, the organisation comprised of Brazil, Russia, India, China, and South Africa (BRICS) has intensified their trade integration. Therefore, we conducted a thorough analysis of how BRICS countries’ multilateral trade integration responded to geopolitical risk events from January 1996 to December 2021. To achieve this, we utilized a sophisticated econometric method, specifically the cross-quantilogram approach, to analyse high frequency data due to their non-normal and fat-tailed features. Our study confirms the proposition that geopolitical risks strengthened trade integration within the BRICS bloc. Specifically, our findings show that the volume of exports from one economy to another responded positively at lower to medium quantiles of exports and lower geopolitical risks, considering a 12–36-month horizon. Moreover, we found that the quantity of exports from Russia to China was higher in the presence of higher geopolitical risks. Our study demonstrates that geopolitical risks can create a sense of shared identity and mutual interest among the BRICS countries, fostering greater cooperation and trade integration.

Влияние профсоюзного членства на трудовую жизнь наемных работников (на материалах по Вологодской области)

Despite the rich history and authority, the trade union movement is gradually losing its influence in the modern world. This is most evident in the decline in unionization rates among workers, driven by a variety of socio-economic and political factors (deindustrialization, scientific and technological progress, the spread of non-standard forms of employment, the reduction of the public sector, etc.). As a result, many experts express an opinion about a crisis in trade unions, whose future is difficult to predict. Under such conditions, issues of employment and decent working conditions acquire special significance. The aim of the article is to analyze the differences in the status of workers who are and are not members of a trade union. This will become the basis for a subsequent study of the effects of its activities using the example of a particular business entity. To reach this aim, I turned to data from a monitoring study in Vologda Oblast, selected a sample of employees, and divided them into those who are and are not union members. A comparative analysis of the resulting groups showed that trade unions have a multifaceted positive impact on the working life. This is reflected in the prevalence of permanent employment contracts, increased access to social guarantees, and opportunities to claim labor rights without the threat of punishment. Union members have higher wages and are more likely to participate in professional development. It is no coincidence that they are distinguished by great optimism regarding professional prospects, including demand and self-realization in a profession with decent wages and career growth. Moreover, employment in such conditions is relatively stable. Despite the widespread dominance of material needs, the work motivation of unionized employees is more strongly associated with an internal interest in work, which involves a desire to acquire new knowledge, achieve success, and gain recognition. Hence the best self-assessments of labor activity indicators: output, quality of work performed, and discipline. In conclusion, the potential of trade unions as a source of labor productivity growth is highlighted, which could be highly relevant for small and medium-sized businesses, whose representatives do not have much interest in this kind of associations. The main limitation of the study is the small sample of respondents who are trade union members, which complicates not only the application of econometric methods of analysis, but also a deep immersion into the specifics of ongoing processes, including in a territorial context.

Navigating the Green Frontier: The Impact of Digitalization on Environmental Pollution in Selected South East Asian Economies

The objective of this paper is to re-examine the impact of digitalization on environmental pollution. Past studies use CO2 as a representation of potential environmental harm. In this paper, environmental pollution is extended to cover other sources of pollution such as methane and nitrous oxide. Prior to the analysis, the cross-dependency and panel unit root tests were conducted to understand the underlying structure of the data and to examine the suitability of the econometrics method used. Given the absence of cross-dependency and the presence of unit roots, the panel ARDL estimation method is used to examine the interplay between digitalization and environmental pollution. In addition, CO2 is segregated into different categories of emission such as CO2 resulting from the production of electricity and heat, manufacturing, and emissions from transportation. The sample consists of ten Southeast Asian countries spanning from 2003 to 2022. Results indicate that digitalization amplifies environmental pollution irrespective of the proxy used. The surge in the number of internet users induces higher emissions due to increased production of electricity and heat, emissions from solid and liquid fuel usage, and transport. Similarly, an increase in mobile users increases CO2 emissions from fuel and liquid consumption, manufacturing, construction, and transportation. Moving forward, it is crucial to consider the adoption of green technology in production and explore alternative energy sources to curtail environmental pollution.

Transformation of customer experience management in the restaurant business in the context of digitalization

The catering sector in Russia today is being significantly transformed under the influence of two modern factors: the transition to a digital model of orders and a decrease in the purchasing power of the population in general. In the context of digitalization and increased competition, restaurant business enterprises are faced with the need to improve the efficiency of customer experience management. Customer experience is a set of impressions, emotions, knowledge that the customer receives at all stages of interaction with the PSR. The purpose of the study is to determine the direction of transformation of customer experience management in the restaurant business in the context of digitalization. Methodology and organization of the study. In this work, a complex was used, consisting of econometric methods, methods of comparative and system analysis, and generalization. Special literature on the chosen research topic was also analyzed. In particular, sources on the problem of customer experience management, digitalization of structures included in the public catering system became the basis for the literature review. Some of the materials were taken from the RSCI and Scopus websites. business.

The Role of Carbon Taxing and Green Innovation in Achieving Decarbonization Goals in Global South

Environmental degradation, pollution, and rising temperatures pose a hazard to the world. A carbon-free economy requires policies to preserve sustainability, development, and the environment. Carbon taxing has emerged as a new hope for low-carbon sustainable economic growth after its successful trial in the developed and developing world. Implementing carbon taxation, energy transition, and green innovation can provide effective answers for defending the globe from environmental challenges. Therefore, both developed and developing economies focus on carbon taxing and green innovation to cope with carbon neutrality targets. The objectives of this study were to examine carbon taxing, green innovation, energy transition, digital infrastructure, sustainable mineral extraction and gross domestic product in acquiring carbon neutrality in Global South (China, India and Pakistan). For this purpose, the global south dataset from 1990–2022 was analyzed. Novel econometric methods Cross-sectional augmented autoregressive distributed lag (CS-ARDL) were used for estimations. The results reveal that carbon taxing, green innovation (GI), energy transition (EN), digital infrastructure (DI), sustainable mineral extraction (MN) and gross domestic product (GDP) significantly affects carbon neutrality. Furthermore, carbon taxing, energy transition, and green innovation significantly assist in attaining carbon neutrality in the long run. Green innovation has a coefficient of 4.3156 with a p-value of 0.000, indicating a highly significant impact on decarbonization. Energy transition, digital Infrastructure, mineral extraction, and GDP also show statistically significant effects with p-values all below 0.01. Policy measures are required in carbon taxation, energy transition, green innovation, and digital infrastructure usage in achieving carbon neutrality. The governments should encourage the use of green energy solutions through subsidies and support technology that reduces carbon emissions. This study contributes a novel framework of carbon taxing and green innovation policies for carbon neutralization in the global south.

Econometric studies in forecasting increased yield productivity of agricultural crops

The article, based on econometric research, examines the relevance of econometric methods of planning and forecasting, as well as methods for compiling econometric models for quantitative analysis and forecasting of agricultural crop yields. In addition, using methods of analysis and forecasting of econometric modeling based on experimental data, the work examined the trend in the dynamics of agricultural crop yields and made a forecast for the future using compiled linear trend equations, as well as provided feedback and suggestions on the results of the study.

Construction Strategy of Regional Investment and Financial Management System under Spatial Effect Modeling

Abstract In recent years, China’s regional economic differences have become more and more apparent, and the problem of unbalanced allocation of financial resources has become more and more prominent. In this context, it is of great practical significance to study the construction strategy of regional investment and financial management systems using the spatial effect model. This study adopts the spatial econometric method to establish the spatial effect model. Considering the limitations of the spatial panel data model, this paper also uses the general dynamic spatial panel model with fixed effects to analyze the relationship between regional investment and the financial management system. Finally, through the Granger causality test on the spatial effect analysis of regional investment and financial management, this paper verifies the study of the interaction between the financial management system and regional investment. The research data show that in the spatial panel model, the regression coefficient of the explanatory variable F financial management system is 0.2431, which is significant at the 1% level, indicating that with a little increase in the degree of financial management system, the regional economy grows by 0.2431. The fixed effect general dynamic spatial panel model’s superiority is confirmed by the higher goodness of fit of the general dynamic spatial panel model compared to the spatial panel model.

Empirical Analysis of the Effectiveness of Fiscal Agricultural Support Policies Based on Spatial Econometric Methods

Empirical Analysis of the Effectiveness of Fiscal Agricultural Support Policies Based on Spatial Econometric Methods

ЛОГИТ-МОДЕЛИ В АНАЛИЗЕ ВЛИЯНИЯ СОЦИАЛЬНЫХ ФАКТОРОВ НА МЕЖРЕГИОНАЛЬНЫЕ МИГРАЦИОННЫЕ ПРОЦЕССЫ

One of the manifestations of the uneven socioeconomic development of the constituent entities of the Russian Federation is interregional population movements. These processes in some regions may be persistently negative and hinder economic development. Therefore, the task of managing migration processes becomes urgent. Different approaches are used to model and predict migration. Traditional is the use of econometric methods, within which, based on statistical data, quantitative characteristics of the influence of factors on migration processes are established. But in conditions of significant external shocks, the impact of factors can change significantly, which makes it difficult to obtain statistically significant model parameters. The paper presents logistic models for predicting not the quantitative characteristics of population movement in the region, but the fact of migration growth or outflow. Data on migration in 82 regions of the Russian Federation for 2015–2022 are used as initial data. The study identified social factors that significantly influence the migration influx of people into the region. It has been established that the growth of these factors increases the likelihood of a migration influx of population into the region. The impact may be felt this year and next. The resulting models have good predictive properties and can be used to solve the problem of reducing the migration outflow of the population in the regions.