Econometric Model Research Articles

Analysis of Factors Affecting Participation of Smallholder Farmers in Wheat Cluster Farming: The Case of Gasera District, Bale Zone, Oromia Region, Ethiopia

Agriculture is the main means of livelihood in Africa. Wheat is one of the globally produced and marketed cereal crops which cover 15% of the total sowing areas of cereal crops in the world. This study focused on the analysis of factors affecting smallholder farmer’s participation in wheat cluster farming in Gasera District of Bale zone. A multi-stage sampling method was employed for this study. Simple random sampling technique was used to select 259 sample respondents in three selected Kebeles out of 24 total kebeles in the woreda. Primary data sources were generated using an interview schedule, five Focus Group Discussions, and eight key informant interviews. Besides, secondary data were obtained from literature and the Woreda Agricultural Office. Both descriptive statistics and econometric models were employed to analyze the collected data. The descriptive statistics results showed that from the total sampled households, 169 (65.3%) were participant and, 90 (34.7%) were non-participant smallholder farmers of wheat cluster farming technology. According to the probit regression model, education status, wheat land, livestock size, frequency of extension contact, credit access, availability of fair price, market information, agricultural input access, training access and membership in a cooperative had a positive influence on farmers’ decisions to participate in wheat cluster farming. Therefore, the local community, Woreda Agriculture Office and research institutes need to expand cluster farming technology to increase wheat production and policies aiming at increasing farmers’ awareness of producing wheat in cluster to increase yield of farmers.

Evaluating the influence of environmental regulations on green economic growth in China: A focus on renewable energy and energy efficiency guidelines

China's status as the world's largest energy consumer highlights its pivotal role in global energy consumption and the urgency of enhancing its energy efficiency and renewable energy development. This study evaluates the influence of environmental regulations on green economic growth in China, with a focus on renewable energy and energy efficiency, from 2000 to 2023 across 30 provinces. Using the Metafrontier-Global-SBM super-efficient DEA model, the research measures green economic development through the lens of energy efficiency. An enhanced fuzzy comprehensive assessment gauges the stringency of environmental regulations. To explore non-linear impacts, regional spillover, and feedback effects, a spatial econometric model was applied. The results reveal a U-shaped non-linear relationship between environmental regulations and green economic growth, with significant spatial feedback and regional spillover effects. Environmental regulations are also shown to have a substantial positive influence on the development of renewable energy, a critical driver of green economic growth. Policy implications suggest that strengthening environmental regulations could accelerate renewable energy adoption and foster sustainable economic growth across regions in China.

Analysis of Determinants of Envitonmrntal Awareness Among Beef Consumers

Objective: The objective of this study is to analyze the determinants of environmental awareness among beef consumers in Brazil, focusing on the acceptance of the Carbon Neutral Beef label. Theoretical Framework: The literature review covers the growing consumer concern for sustainability and animal welfare. The concept of Carbon Neutral Beef, developed by EMBRAPA, is discussed as a strategy to mitigate methane emissions in livestock production. Previous studies indicate that factors such as education, income, and environmental awareness influence consumers' willingness to pay more for sustainable beef. Method: The research employed a quantitative approach, applying a survey to beef consumers in Brazil. A total of 256 completed questionnaires were analyzed, and the data were processed using Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM). The Tobit econometric model was employed to identify the determinants of consumers' environmental awareness. Results and Discussion: The results show that most consumers prefer beef with sustainability attributes, influenced by income, education, and concern for the environment. The Tobit model indicated that variables such as educational level and household income are significant determinants of environmental awareness. These consumers are willing to pay more for beef that respects the environment and animal welfare. Research Implications: The study provides insights for the beef industry on the importance of adopting sustainable production practices. Originality/Value: The study provides insights for the beef industry on the importance of adopting sustainable production practices.

How to enhance the resilience of domestic tourism?

Enhancing domestic tourism resilience (DTR) is crucial to achieving high-quality development of the tourism industry. However, owing to the vulnerability of the tourism industry during the COVID-19 pandemic, the enhancement pathways and associated mechanisms of DTR need to be further investigated. Therefore, this study measures the DTR of China's 31 provinces by creatively combining the simple harmonic motion and regime-switching vector autoregressive models and explores its characteristics to lay the foundation for an empirical analysis. Furthermore, the study empirically analyzes the enhancement pathways and associated mechanisms of DTR using a spatial econometric model. First, this study found that tourism agglomeration, specialization, and diversification determine the characteristics of dynamic response and spatial distributions of DTR. Second, from the perspective of spatial effects, DTR in one region positively impacts that in adjacent regions, and tourism agglomeration in a specific region positively impacts DTR in adjacent regions. Third, in terms of mechanisms, tourism agglomeration enhances DTR by optimizing industrial structure and improving production efficiency, whereas tourism specialization and diversification enhance DTR by improving production efficiency and optimizing industrial structure, respectively. These findings provide information for the enhancement of DTR and achievement of high-quality development of the tourism industry.

Asymmetric impact of the COVID-19 on the Moroccan stock exchange

PurposeThis study aims to investigate the asymmetric impact of the COVID-19 pandemic on the stock market returns of companies listed on the Casablanca Stock Exchange.Design/methodology/approachTo achieve this objective, we utilized the SymCovid series, which comprises two sub-series: one representing the deterioration of the pandemic situation (NEG) and the other representing the improvement of the pandemic situation (POS). We employed the Nonlinear Autoregressive Distributed Lag model, incorporating Bounds Testing as proposed by Pesaran and Shin (1999) and Pesaran et al. (2001), to explore the asymmetry of the pandemic’s impact on stock prices listed on the Casablanca stock exchange.FindingsOur analysis using the NARDL econometric model reveals an asymmetric effect of COVID-19 on stock prices. Notably, we observe that stock prices react more strongly to a worsening pandemic situation than to an improvement, on average. Furthermore, our main findings indicate that while the improvement in the pandemic situation has no significant long-term impact on stock prices, it does exhibit a significant positive effect in the short term. Conversely, the deterioration in the pandemic situation has a more pronounced negative effect on stock prices in the long term than the short term.Originality/valueOur study fills a gap in the existing literature by focusing on the impact of the COVID-19 pandemic on stock returns in the context of the Casablanca Stock Exchange, which has been relatively understudied compared to other regions such as Asia, Europe and the Americas. We go beyond previous research by examining whether stock returns exhibit asymmetric responses to changes in the pandemic situation, highlighting potentially unique dynamics in emerging market economies during crises and providing valuable information for investors, policymakers and researchers.

Time-frequency comovements between news sentiments, Non-fungible tokens, and DeFi assets: evidence from the wavelet analysis

ABSTRACT Growth in digitalization has created a potential boost for Non-fungible tokens (NFTs) and decentralized finance (DeFis) assets in the modern world. Therefore, this study aims to examine the comovement between the recently developed comprehensive measure of news sentiment index (NSI) and selected digital assets. For this purpose, we have utilized the wavelet transform, wavelet correlation, and wavelet coherence econometric model to assess interdependency in both time and frequency between news sentiments and digital assets. Our wavelet correlation and covariance results suggest that almost all the digital assets exhibit a negative relationship with NSI. Moreover, the wavelet coherence results confirm that there is no significant comovement in the short to medium-term horizon, suggesting that both NFTs and DeFi can be used as hedges against the NSI. Furthermore, we observe small patches of significant negative comovement between NSI and digital assets in the long term, which correspond to the initial days of COVID-19. Our results confirm selected digital assets’ hedging role against news-driven uncertainty. This study finding provides essential information to policymakers, international investors, and investment managers to make effective decisions.

Profitability of Energy Sector Companies in Poland: Do Internal Factors Matter?

The aim of this article is to examine which selected internal factors influence the profitability (ROA) of companies in the energy sector in Poland and how they do so, over the period 2018–2021, taking into account two groups: all types of activities (984 companies) and electricity production (508 companies). This study uses Pearson correlation analysis, Wilcoxon pairwise rank test, descriptive statistics and multiple linear regression to build eight ROA econometric models, four for each group. The research shows that in the energy sector, in particular, variables relating to the capital structure (total equity/total assets, long-term liabilities/total assets, short-term liabilities/total assets and long-term liabilities/short-term liabilities ratios) have a statistically significant impact (positive or negative) on the profitability (ROA). The aforementioned ratios appear in various combinations in all eight ROA models. The use of equity to finance the activities of companies in this sector seems to be particularly beneficial, as the total equity/total assets ratio occurs in as many as seven out of eight models and, moreover, it always has a positive impact on the ROA. The remaining analyzed variables relating to the structure of assets (fixed assets/total assets ratio), financial liquidity (current ratio) and the age of the company appear in the models as statistically significant quite rarely, having a different impact on the ROA (positively or negatively). However, variables such as the fixed assets/current assets and total liabilities/total equity ratios do not have a statistically significant impact on the ROA at all in any of the studied groups of enterprises. The research results suggest that managers, in order to shape profitability (measured by ROA), should pay special attention to the capital structure, i.e., the proportions of the use of equity, long-term liabilities and short-term liabilities to finance the operations of energy companies as these independent variables appear most often in ROA models. Other analyzed factors, such as the assets structure (the share of fixed assets in total assets) or financial liquidity, also have an impact on the return on assets; therefore, their use in energy companies should also be considered. Moreover, the research shows a large diversity of factors shaping ROA in econometric models, the way they affect the dependent variable (positive or negative) and the degree of model fit (R2), both in individual years and in the two groups of companies studied. This proves that it is not possible to clearly and finally determine which factors and how (positive or negative) they affect the profitability. This influence can change over time depending on the circumstances, which indicates the need for the continuous involvement of decision makers in the management process and making decisions based on reliable and appropriate-to-the-situation analyses.

The influence of renewable energy and financial development on testing the environmental Kuznets curve in Lebanon: ARDL approach

This study considers the impacts of financial development and the consumption of renewable energy in Lebanon for the period 1990–2021, employing the Environmental Kuznets Curve. The financial sector in Lebanon is considered a major engine in the economic development. Green energy sources and environmental protection are taking higher importance nowadays with the increase of implications for climate change and global warming worldwide. This paper examines the Environmental Kuznets Curve’s presence and implications for Lebanon’s financial development and renewable energy consumption. The econometric model used annual data from the World Development Indicators. Utilizing the autoregressive distributed lag (ARDL) technique, both near- and long-term relationships were estimated. The findings support the Environmental Kuznets Curve hypothesis and show that energy consumption and real income have a statistically significant beneficial effect on carbon emissions and that their square has a statistically significant negative impact on carbon emissions over the long and short term. The results show variations in signs for financial development between the short and long term and stable results for renewable energy with negative signs in both terms. These results show the importance of further research on the influence of financial development and green energy consumption on EKC. Therefore, policymakers need to pay more attention to these variables for a sustainable economy that is facing the effects of climate change.

SUSTAINABLE GROWTH THROUGH GREEN ECONOMY: AN ECONOMETRIC ANALYSIS

Objective: In recent years, the growing interest and awareness of environmental issues have once again brought the issue of population growth to the forefront, exerting significant pressure on production. The increased pressure on production and the resultant rise in production have led to a faster trend in consumption. As a natural consequence of both trends, detrimental effects on ecological balance and the environment have begun to emerge. The concept of "green economy" has emerged as an approach to restore the disrupted ecological balance and operationalize this order. This widely spreading concept has begun to generate significant policies at both national and international levels. Method: This study aims to examine the relationship between renewable energy production, consumption, wastewater, and solid waste data, covering the years 1980-2022, using econometric methods to explore the relationship between green economy and economic growth in the context of Turkey. The objective is to analyze the impact of the recent and rapidly increasing transformation towards "green economy" on the long-term trajectory of economic growth in Turkey. Result and Discussion: Based on the findings of the study, it has been determined that, at the 0.05 level of statistical significance, there is no long-term relationship between the variables and economic growth, as well as no long-term significant relationship between any of the variables. When the statistical significance is accepted at the 0.10 level, a significant long-term relationship is identified between the amount of wastewater and renewable energy, with a 1% increase in wastewater leading to a 0.82% increase in renewable energy. Implications: The findings of this study and the transformation towards a green economy, widely covered in the literature, have been recognized in Turkey and an unnamed green transformation movement has begun. As the results of the analysis of the study indicate, the policies introduced for the transition to a green economy and transformation efforts have a positive and significant impact on economic growth in the long term, but the same cannot be claimed for the short term, but in the future, advances in scientific and technological progress and over-specialization will inevitably have positive consequences on global and domestic sustainable development in the short term. Originality/Value: The distinctive feature of this study from similar studies in the literature is that the relationship between the green economy and sustainable growth was analyzed empirically and with five separate econometric models. Recommendations: Turkey needs serious reforms in education in its transition to a green economy. In addition, there is a need for political determination to use environmentally friendly sectors that are more open to innovation and competition, such as renewable energy and green building sectors.

Does the integration of digital and real economies promote urban green total factor productivity? Evidence from China

Enhancing urban green total factor productivity (UGTFP) is of great significance in driving the green transformation of cities. The integration of the digital economy and real economy (IDR) offers a novel approach to improving UGTFP. This paper constructs a theoretical analytical framework to examine the impact of IDR on UGTFP. Utilizing a range of econometric models and Chinese urban data, this paper empirically analyzes the influence, mechanism, and spatial spillover effect of IDR on UGTFP. The findings reveal that China's IDR is currently at a stage of low integration, exhibiting significant regional disparities, with a spatial distribution pattern declining from east to west. IDR can significantly enhance UGTFP, and the conclusion is supported by robustness tests. Heterogeneity analysis indicates that the positive effect of IDR on UGTFP is more pronounced in the eastern and western regions, as well as in areas with a large Internet scale. The mechanism test suggests that economic agglomeration can significantly amplify the promotional effect of IDR on UGTFP. IDR can boost UGTFP by elevating innovation levels and optimizing labor resource allocation. Further exploration reveals a significant positive spatial spillover effect of IDR on UGTFP. These insights not only offer a practical pathway for green transformation but also provide empirical evidence for policymakers to formulate scientific policies, enhance coordination, and improve data governance, thereby facilitating high-quality and green economic development.

Multivariate Analysis of the Determinants of Total Mortality in the European Union with Focus on Fat Intake, Diabetes, Myocardial Infarction, Life Expectancy, and Preventable Mortality: A Panel Data Fixed-Effects Panel Data Model Approach.

Cardiovascular disease is the leading cause of death in the European Union (EU), and while the mortality rates of diabetes, myocardial infarction, and the total fat intake have been extensively studied, we believe that understanding the interaction between such closely correlated determinants is crucial to the development of effective health policies in the EU. Our paper's novelty is represented by the econometric modelling, and its ability to capture both temporal and unit variations. The research methodology consists of using a panel data model with fixed effects for the 27 EU member states over the period 2010-2021. The results of the study show that the standardized mortality rate for deaths preventable by prevention and treatment and diabetes-related mortality are significant predictors of total mortality in the EU. The standardized mortality rate for deaths preventable by prevention and treatment had a significant positive impact, suggesting that improved preventive and therapeutic interventions can significantly reduce total mortality. Diabetes-associated mortality also showed a strong positive correlation with total mortality, emphasizing the need for effective diabetes management and prevention strategies. These results are useful for the formulation of public health strategies aimed at improving life expectancy and reducing the burden of chronic diseases.

The resilience and determinants of global mineral resource supply chains: a network percolation perspective

Mineral resources are the basic materials for global economic development. Assessing mineral resource supply chain resilience is an important pillar of mineral resource supply chain stability management. The globality, heterogeneity and complexity of supply chain bring challenges to the resilience assessment of global mineral resource supply chain. To solve this problem, a method based on multi-region input-output model, network percolation model and econometric model is proposed, which is able to measure the resilience of global mineral resource supply chain and its influencing factors from the perspective of the whole system. The percolation phase transition is introduced to measure the critical state of global mineral resource supply chain system collapse facing external disruption. Using the proposed method, this paper conducts an empirical study on the evolution of global mineral resource supply chain resilience from 2005 to 2014. The results show that the resilience of global mineral resource supply chain declined by 39.6% in 2005–2014. Most of the critical links that caused the collapse of the global mineral resource supply chain network are the manufacturing sector and its upstream and downstream sectors. The structure of supply chain network plays a key role in network resilience. Increasing the number of linkages in upstream and downstream could improve network resilience, but the increase of linkage strength would deteriorate network resilience.

Poverty Inflation, FDI Consumption, and Economic Growth in Indonesia in the Vector Autoregressive Model Analysis

The difference in the results from previous studies on the impact of inflation on poverty, coupled with an increase in the money supply from direct investment, inspired this research. This study aimed to ascertain how poverty, inflation, and foreign investment affect consumption spending in Indonesia based on 1997-2021 time series data. This study used Vector Autoregression estimation, utilizing data sources from the World Bank. The data will be processed with econometric models. From the study’s findings, it may be inferred that overall consumption affects inflation, which can be seen from the Granger causality test that shows that this variable has a one-way causal relationship. The results of the same test also show that FDI has an effect on total consumption and conversely consumption has an effect on FDI. However, the poverty variable does not affect total consumption and vice versa, because according to the causality test, the variable obtains an insignificant probability value. However, the VECM results explain that poverty has an effect on total consumption, and that the effect of consumption on inflation is due to the larger t-statistic value and has a positive relationship. This implies that the rate of inflation will increase the lower the level of consumption. However, the Impulse Reason test shows that poverty has a negative trend, as does the FDI variable. Keywords: poverty, inflation, FDI, consumption, economic growth, Indonesia

SUSTAINABLE DEVELOPMENT OF RURAL AREAS IN THE REPUBLIC OF MOLDOVA THROUGH INCREASING THE EFFICIENCY OF THE LAND RESOURCE USE IN THE AGRICULTURAL SECTOR

The evaluation of the agricultural land in the Republic of Moldova represents the main factor in the sustainable rural space development and it emphasizes economic criteria for the efficiency of land resources. The hedonic price in the sales-purchase transactions of parcels in agricultural land may be the scientific innovation and originality of the geographically weighted regression methodology with the spatial approach in the used econometric model. The price of agricultural land used parcels in Maiovca village, Ocnița district were evaluated by using the data from transactions registered in 2022 and the results of the geographically weighted regression stands up the suitable conclusions of the licensed assessors in the field. The autocorrelation coefficient value evaluated by SAR is ρ = 0.072 according to Cobb Douglas model confirms the high quality of the regression techniques carried out and the used spatial methodology can be implemented in cadastral practice for the taxation in the agrarian sector. The geographically weighted regression utility proposed in this methodology has advantage in research area because of the similar evaluation techniques carried out in the countries of the European Union that are adjacent to the Republic of Moldova.

Intensity of Adoption of Improved Malt Barley Production Technologies in Ethiopia: A Case Study in Oromia Region

Improved malt barley production technology packages are not yet widely adopted in Ethiopia. Stakeholders, including brewers, malt factories, research institutes, and farmer-based organizations, have been collaborating and promoting new malt barley production technologies in order to boost the intensity of acceptance. The aim of this study was to find out the intensity of improved malt barley production technologies adoption in Arsi zones, Oromia region, Ethiopia. A stratified random sampling approach with multiple stages was employed to collect primary data from 384 malt barley household heads. The data was analyzed using descriptive statistics, and the intensity of adoption of improved malt barley production technologies was determined using an econometric Tobit regression model. The findings specified that the most adopted improved malt barley variety was Traveler (47.92%), which was followed in descending order by Iboni (14.58%), Sabini (9.38%), Grace (5.47%), Holker (4.43%), and 18.23% unnamed varieties. The Tobit model result also depicted that the intensity to which improved malt barley varieties adopted were affected by, taking into account factors including contract farming involvement, cooperative membership, off-farm income, size of livestock holdings, access to training, and mobile ownership. Enhancing farmers’ knowledge of the advantages of contract farming, income diversification, and mobile phone-based information delivery are among the many ways to support access to and accelerate the adoption of improved malt barley technology in the research area and beyond.

Re-Visiting the Co-movement between FinTech, Economic Policy Uncertainty, Governance Quality and Bank Variability in Pakistan: A Wavelet Coherence Approach

The recent literature about FinTech services in Pakistani commercial banks has grabbed much attention as these services have increased rapidly in the last few decades. This paper examines the co-movement between FinTech, economic policy uncertainty, bank- variability, and governance quality. The data was obtained from 2014-2020 on a monthly frequency. To address the relationship and co-movement, we have applied more advanced and sophisticated econometric models, autoregressive distributed lag model (ARDL), and continuous wavelet (CTW) to investigate the relationship between the variables. These approaches provide flexibility of assumptions for time-series data and provide robust results. The results indicate a short and long-run symmetric relationship with a significant co-movement between the variables.

Influence mechanism of digital economy development on the supply efficiency of ecological products

Improving the supply efficiency of ecological products (EPSE) is of great significance to protect the ecological environment, promote the development of green industry and the sustainable growth of the economy. This paper focuses on constructing an evaluation index system for EPSE and exploring the relationship between the development level of the digital economy (DE) and EPSE in China. To measure the EPSE, the study employs the Undesirable Slacks-Based Measurement (SBM) Model across 30 provinces, cities and districts in China from 2011 to 2022. Furthermore, the research utilizes spatial econometric models, panel threshold effect models, and other methodologies to investigate the impact mechanism and non-linear relationship between DE and EPSE. The research shows that: (1) The overall level of EPSE in the study area is relatively low, with significant development differences observed; (2) The DE has a nota-ble spatial spillover effect on EPSE, with a significantly negative impact in neighboring areas; (3) The development of the DE promotes EPSE through the upgrading of human capital structure, industrial structure, and increases in local government fiscal revenue and corporate operating profits; (4) Heterogeneity analysis shows that the impact of DE on EPSE varies significantly across eastern, central, and western China, with positive effects pronounced in the eastern and western regions; (5) Regression results of the threshold effect indicate a significant single threshold effect on the impact of DE development level on EPSE. Specifically, when the threshold value is less than 0.1232, DE significantly contributes to the improvement of EPSE. This paper contributes new literature evidence and factual references to the understanding of the causal relationship between DE and EPSE. The findings highlight the importance of considering spatial spillover effects, impact mechanisms, and regional heterogeneity in analyzing the relationship between DE and EPSE. The research also suggests that promoting the development of the digital economy could be a viable strategy to enhance EPSE, especially in regions where the threshold value is below 0.1232

Can Social Technologies Drive Purchases in E-Commerce Live Streaming? An Empirical Study of Broadcasters’ Cognitive and Affective Social Call-to-Actions

As an emerging social technology, live streaming has facilitated a synchronous and interactive selling setting for e-commerce sellers and consumers. Despite growing operations management (OM) in e-commerce live streaming (ELS), the prior literature has largely neglected the directive social operations of ELS broadcasters, which are crucial to a company's business operations and marketing strategies. To mitigate this gap, we investigated the effects of social call-to-actions (SCTAs), an ELS-specific directive social operation, on consumer purchase outcomes in ELS. To explicate the mechanisms driving the purchase effect of SCTAs, we draw upon the notions of cognitive and affective marketing appeals to categorize SCTAs into two types: cognitive and affective SCTAs. We measure broadcasters’ SCTAs from ELS speech-to-text data using text-mining techniques and adopt econometric model estimations via an instrumental variables identification approach to quantify the relationships between ELS broadcasters’ SCTAs and consumer purchases. Our results uncover a significant positive purchase effect of affective SCTAs but an insignificant effect of cognitive SCTAs on product-level purchase orders in ELS. Specifically, a one-unit increase in affective SCTA-related words per minute is related to increased purchase orders of a product by 0.43%, i.e., averaging a 1.10% growth in demand per minute. Additionally, we find that the effects of cognitive and affective SCTAs are contingent on product and broadcaster types. Our session-level mediation effect analysis verifies the underlying mechanisms that drive the purchase effects of broadcasters’ SCTAs. Specifically, we find that cognitive SCTAs impede social engagements and thereby purchases, whereas affective SCTAs can boost social engagements, leading to increased session traffic and ultimately product sales in ELS. Our study provides novel empirical findings and important practical implications for ELS platforms and broadcasters.

EXCHANGE RATE DYNAMICS AND THEIR IMPLICATIONS

This research paper explores the dynamics of exchange rate fluctuations and their far-reaching implications for the global economy. Exchange rates are pivotal in shaping trade balances, inflation, and capital flows, making them a critical factor for policymakers, multinational corporations, and investors. By examining both theoretical frameworks and empirical evidence, this study analyzes the effects of exchange rate movements on key economic variables such as inflation rates, gross domestic product (GDP), foreign direct investment (FDI), and international trade balances. The paper employs a combination of econometric modeling and historical data analysis to evaluate how these fluctuations have influenced emerging and developed economies over the past two decades. Results indicate that exchange rate volatility can lead to inflationary pressures in import-dependent economies, disrupt trade balances, and influence FDI inflows. The findings also underscore the importance of stable exchange rate policies to mitigate economic uncertainty. This study concludes with recommendations for future research, particularly regarding the influence of digital currencies and geopolitical tensions on exchange rate stability.

The Impact of Key Performance Indicators on Faculty Research in Higher Education

This study investigates the effectiveness of key performance indicators (KPIs) in evaluating the research contributions of academic staff in Uzbekistan, aiming to provide a nuanced understanding of faculty performance assessment. Employing a mixed-methods approach, the research integrates quantitative bibliometric analysis of publication data from 500 faculty members with qualitative interviews from 30 academics. The quantitative analysis focuses on metrics such as total publications, citation counts, and h-index scores, while the qualitative component explores faculty perceptions regarding the influence of KPIs on their research activities and career development. The analysis reveals significant variability in research productivity, with faculty averaging 12.4 publications and 110.2 citations. Econometric modeling indicates a strong positive correlation between publication metrics and citation impact, suggesting that higher publication output enhances academic visibility. Qualitative insights highlight the pressures of a "publish-or-perish" culture, which adversely affects research quality and faculty morale, particularly in contexts with limited institutional support. This research contributes to the discourse on academic performance evaluation by emphasizing the limitations of traditional metrics and advocating for a more holistic assessment framework. It highlights the need for higher education institutions to consider both quantitative and qualitative measures to better reflect the complexities of academic contributions in Uzbekistan.