Econometric Research Articles

Determinants of Formal Agricultural Credit Flow to Districts in India: An Econometric Analysis

Aims: This study investigates the determinants of formal agricultural credit flow at the district level in India, using region-wise fixed effects models. Study Design: Panel data regression technique. Place and Duration of Study: Data from districts across Indian states from 2000 to 2021 were analyzed. Methodology: Districts categorized into high, medium, and low credit exposure groups based on average outstanding agricultural credit by Scheduled Commercial Banks (SCBs) through a clustering technique. One district from each category in each state was selected for analysis. The study examined outstanding agricultural advances by SCBs, the number of SCB branches, gross sown area, gross irrigated area, area under commercial crops, and annual rainfall using an unbalanced panel model. Results: The findings reveal that an increased number of SCB branches in a district significantly enhances agricultural credit availability. The share of gross irrigated area positively impacts credit flow, especially in the southern, western, and central regions, highlighting the importance of irrigation in accessing credit for high-value crops. In contrast, a higher share of area under commercial crops negatively affects credit flow in the southern and western regions, possibly due to limited financing for rainfed commercial crops. Rainfall was found to have no significant impact on agricultural credit at the district level. Additionally, there is a noticeable trend of increasing urban branches, particularly in the southern, northern, and northeastern regions, alongside a decline in rural branches in most regions except the eastern region. Conclusion: The study emphasizes the need for targeted policy measures to improve agricultural credit distribution. Policymakers should focus on the number of SCB branches, the share of irrigated area in total sown area, and address the rural-urban branch shift while considering region-specific agricultural requirements to ensure equitable and efficient credit allocation.

Effect of small-scale irrigation on rural household agricultural income in Demba-Gofa District, Southern Ethiopia

Even though small-scale irrigation (SSI) is a practical solution to address issues like poverty, food insecurity, and low farm production, its promise is often overlooked in Ethiopia. In the Demba Gofa District of southern Ethiopia, many rural households continued to rely primarily on rain-fed agriculture despite the possibility of irrigation. Therefore, the purpose of this study was to determine the factors that influence the adoption of SSI in Demba Gofa and its effect on farm income. A cross-sectional explanatory research design with a mixed-methods approach was employed on a total of 369 households selected through a multistage sampling procedure. An econometric data analysis using the propensity score matching model was employed to evaluate the effect of small-scale participation on households' farm income. The analysis revealed that the gender of the household head, cultivated land area, market accessibility, livestock ownership, and credit service accessibility positively affect irrigation adoption. Households' irrigation adoption was negatively and significantly associated with the age of the household head and the distance of the farm from the irrigation site. Furthermore, households that did not adopt small-scale irrigation schemes lost 4831.77 ETB in farm revenue compared to those that did. Thus, the study advises the government to support the establishment of adequate, long canals and government-guaranteed credit services for smallholder farmers in order to boost household income and, consequently, food security. Agricultural agents ought to conduct routine evaluations of the canals' operation and offer farmers training to enhance their skills in the sustainable use of irrigation systems.

Impact of solar geoengineering on temperature-attributable mortality

Decisions about solar geoengineering (SG) entail risk-risk tradeoffs between the direct risks of SG and SG's ability to reduce climate risks. Quantitative comparisons between these risks are needed to inform public policy. We evaluate idealized SG's effectiveness in reducing deaths from warming using two climate models and an econometric analysis of temperature-attributable mortality. We find SG's impact on temperature-attributable mortality is uneven with decreases for hotter, poorer regions and increases in cooler, richer regions. Relative to no SG, global mortality is reduced by over 400,000 deaths annually [90% CI: (-1.2 million,2.7 million)] for cooling of 1 °C from 2.5 °C above preindustrial in 2080. We find no evidence that mortality reduction achieved by SG is smaller than the reduction from equivalent cooling by emissions reductions. Combining our estimates with existing estimates of sulphate aerosol injection direct mortality risk from air quality and UV-attributable cancer enables the first quantitative risk-risk comparison of SG. We estimate with 61% probability that the mortality benefits of cooling outweigh these direct SG risks. We find the benefits outweigh these risks by 13 times for our central estimates, or 4 deaths per 100,000 per 1 °C per year [90% CI: (-11,23)]. This is not a comprehensive evaluation of the risk-risk tradeoffs around SG, yet by comparing some of the most consequential impacts on human welfare it is a useful first step. While these findings are robust to a variety of alternative assumptions, considerable uncertainties remain and require further investigation.

Forecasting of Bull Carcasses Prices for the Future with Box-Jenkins Models: The Case of Tokat Province

Aim to study: The purpose of this study is to make future forecast of bull carcass meat prices in Tokat province using econometric methods. It is aimed to analyze bull carcass prices in Tokat province with time series analysis and estimate these prices for 2025. Material and methods: The data set of the study consists of monthly bull carcass prices slaughtered between June 2018 and May 2024. The estimates were made with the Box-Jenkins method, one of the econometric analysis methods. Results: As a result of the time series analysis, the most suitable model for bull carcass prices was determined as ARIMA (0,1,0) (1,1,0). According to the estimation results of bull carcass prices in line with the determined ARIMA models, it was estimated that the bull carcass price in Turkey would reach an average of 550.37 TL/kg in the May 2025 period. Conclusion: In conclusion, time series analysis can be utilized to forecast future bull carcass prices, though these estimates should be regularly updated. This approach can support the future planning efforts of both producers and consumers.

The impact of Gender Diversity on Innovative Performance: Empirical Analysis in the Caribbean Region

This paper investigates the impact of gender diversity on the innovative performance of Caribbean firms, specifically analyzing women’s representation across three organizational areas: the overall workforce, management, and skilled production and non-production roles. The study used data from the Innovation, Firm Productivity, and Gender (IFPG) database, encompassing 1,979 firms across 13 Caribbean countries from 2017 to 2020. Probit models were employed for econometric analysis. The results confirm that diversity significantly enhances the likelihood of innovation, though the magnitude of its impact varies depending on women’s roles within firms. Gender diversity has stronger effects within the overall workforce and skilled production and non-production roles than within management teams. These findings suggest important managerial and policy implications for developing measures to reduce gender disparities in innovation.

Do geopolitical uncertainty and inflation transmit opportunities or threats to green energy consumption?

Purpose This study aims to examine the impact of geopolitical uncertainty and inflation on green energy consumption. In addition, it aims to reveal the cause-and-effect relationship among these variables. Design/methodology/approach The authors exert the panel dynamic ordinary least squares (OLS) approach of Kao and Chiang (2000) and the Granger non-causality method of Dumitrescu and Hurlin (2011). On the other hand, current study relies on the annual time series data of 29 countries from 1985 to 2022. Findings The panel dynamic OLS results confirm a long-run relationship between geopolitical uncertainty, inflation and green energy consumption. On the other hand, inflation negatively impacts green energy consumption, with high inflation levels potentially halting the transition. Conversely, geopolitical uncertainty shows no significant effect on green energy use, indicating a reliance on traditional energy sources. Moreover, the current investigation reveals the unidirectional causality from green energy consumption to inflation, while no short-run causality exists from inflation as well as geopolitical uncertainty to green energy consumption in the selected countries. Research limitations/implications The authors drew conclusions about the potential impact of geopolitical uncertainty and inflation on green energy uses by considering the macro-level data. However, this investigation further be enhanced by looking at such issues through the micro perspective by understating the thought and perspective of public on the implication of geopolitical uncertainty and inflation on green energy uses. Such micro-level, country-specific study would definitely help us to generate more concrete ideas about such themes. Practical implications The empirical findings have important implications for policymakers. Results suggest that high inflation negatively impacts green energy use, so policymakers must consider implementing measures to control the inflation while promoting green energy uses for economic prosperity and environmental sustainability. In the short run, green energy use leads to inflation. Therefore, macroeconomic policymakers can implement various subsidy policies for the general public to mitigate the short-term inflationary impact of green energy use. Originality/value This investigation is novel in three ways. First, it explores the impact of geopolitical uncertainty and inflation on green energy use, using Caldara and Iacoviello’s (2022) geopolitical risk index as a proxy of geopolitical uncertainty. Second, it uses panel data econometric analysis, a method that most previous studies have not contemplated for this type of investigation. Finally, by including both advanced and emerging economies, it provides valuable insights for policymakers to develop effective strategies related to green energy consumption for achieving sustainable economic development.

The Impact of Monetary Policy on Healthcare Affordability: A Case Study of China's Urban and Rural Basic Medical Insurance

Longer life expectancy and improved health are key indicators of economic growth. As such, strategies to bolster the medical security system are priorities in government budgeting. The government is dedicating all available resources to better healthcare in rural and underdeveloped areas, narrowing the urban-rural healthcare gap, and achieving equitable healthcare resource distribution. This study examines the effect of monetary policy on healthcare affordability, focusing on China's Urban and Rural Basic Medical Insurance (URRBMI). It investigates how macroeconomic policies, such as interest rates and inflation control, affect healthcare costs and shape URRBMI's financial protection. Using an integrated methodology, including a literature review, theoretical framework, and econometric analysis, the research uncovers how monetary policy impacts healthcare costs and URRBMI's effectiveness. The findings highlight the importance of monetary policy in healthcare affordability. The study recommends collaboration between monetary authorities and healthcare policymakers to improve China's healthcare system's sustainability and effectiveness. Furthermore, these insights are crucial for refining URRBMI and provide new understandings of optimizing macroeconomic policy interactions with social welfare programs.

The Correlation of China's Social Fixed Asset Investment with GDP, Fiscal Expenditure and Total Retail Consumer Goods

Since the reform and opening up, China's economy has experienced unprecedented rapid growth, in which social fixed asset investment, as a key driver, has contributed to economic development that cannot be ignored. This study focuses on the period from 2003 to 2022 and employs key economic indicators, including gross domestic product (GDP), fiscal expenditure, and total retail sales of consumer goods, to investigate the correlation between these variables and their impact on fixed asset investment. To this end, econometric analysis is utilized to elucidate the underlying mechanisms through which these variables influence fixed asset investment. The results indicate a positive correlation between fiscal expenditure, retail sales of social consumer goods and overall fixed asset investment. Furthermore, a negative correlation exists between GDP and fixed investment. This is due to the fact that an increase in GDP leads to an increase in total social consumer goods, which in turn reduces the funds available for investment. Consequently, a negative correlation emerges between total social consumer goods and fixed asset investment. This illustrates that fiscal expenditure exerts the greatest influence on social fixed asset investment, followed by GDP and total social consumer goods. The objective of this empirical analysis is to identify the key factors influencing China's fixed asset investment. The findings are intended to inform the formulation of more precise and effective economic policies by the government, facilitate the optimization of the investment structure, and support the advancement of high-quality economic development.

Impact of Earnings Management on Market Value in Light of Dividend Policy: an Econometric Study of a Sample of Saudi Stock Exchange-Listed Companies During the Period 2010–2021

This study aimed at examining the impact of earnings management on market value under a dividend policy for a sample of institutions listed on the Saudi Stock Exchange and registered in TASI during the period (2010–2021). A descriptive analytical approach and a quantitative econometric analysis using One-Step System GMM Dynamic Panel Data Model were employed. The study reported that all the institutions performed a short-term earnings management oscillating up and down by different proportions during the study period, and that there is an impact of earnings management on value market in both the absence and presence of the dividend policy. The study therefore points to the need for investors education about accounting manipulation in general and earnings management in particular as the latter has an impact on the market value of institutional shares and accordingly on their investment decisions.

The Impact of Voluntary Environmental Standards on Domestic and Foreign Sales Growth: Evidence From Pakistan

ABSTRACTIn the current business environment, voluntary environmental standards (VES), including environmental management standards (EMS) and eco‐labeling schemes, have become important organizational tools to increase firms' market competitiveness and sustainability. This study provides novel insights by empirically examining the effects of EMS (ISO 14001) and eco‐label certifications on domestic and foreign sales growth, specifically in the context of Pakistani firms. The study utilized data from 245 listed firms from 2009 to 2023 to accomplish this objective. The study applied panel econometric regression analysis to estimate the results empirically. The results showed a positive impact of VES on firms' domestic and foreign sales growth. In particular, manufacturing firms that comply with ISO 14001 standards and textile firms with eco‐label certification have exceptionally high domestic and foreign sales growth. The study's outcomes indicate that adopting VES can serve as a valuable strategy for enhancing firms' market competitiveness and expanding their sales in both domestic and international markets. The result suggests that VES enhances market competitiveness and offers a pathway for sustainable growth strategies, specifically in developing economies like Pakistan. Notably, by promoting VES, policymakers can support firms in improving their international market presence and contributing to broader sustainable development goals.

Elementary econometric and strategic analysis of curling matches

PurposeWe develop a Markov model of curling matches. This enables strategic and econometric analyses to be performed alongside computer simulation work.Design/methodology/approachWe develop a Markov model of curling matches, parametrised by the probability of winning an end and the probability distribution of scoring ends. In practical applications, these end-winning probabilities can be estimated econometrically and are shown to depend on which team holds the hammer as well as the offensive and defensive strengths of the respective teams. Using a maximum entropy argument, based on the idea of characteristic scoring patterns in curling, we predict that the points distribution of scoring ends should follow a constrained geometric distribution.FindingsWe provide analytical results detailing when it is optimal to blank the end in preference to scoring one point and losing possession of the hammer. Statistical and simulation analysis of international curling matches is also performed.Originality/valueOur work adds to the theory and application of sports analytics, especially Markov models, and to the econometric and strategic analysis of curling matches.

The Impact of the Pacific Alliance on Trade Creation and Trade Diversion in the COVID-19 Period: A Robust Econometric Analysis

(1) Background: The COVID-19 pandemic severely disrupted global trade, posing challenges for regional trade agreements such as the Pacific Alliance, comprising Chile, Colombia, Mexico, and Peru. This study investigates the Pacific Alliance’s impact on trade creation and diversion during the pandemic, exploring how regional cooperation mitigated trade disruptions. (2) Methods: A quantitative approach utilizing econometric models, including ordinary least squares, Poisson pseudo-maximum likelihood, and the Heckman selection model, was employed. The gravity model of trade was applied to bilateral trade data from 1948 to 2021, incorporating COVID-19-specific variables to assess trade dynamics. (3) Results: The analysis revealed significant trade creation within the Pacific Alliance during the pandemic, with intra-bloc trade strengthening despite global disruptions. However, evidence of trade diversion from non-member countries was mixed and inconclusive. (4) Conclusions: The Pacific Alliance demonstrated resilience during the COVID-19 period, fostering regional trade creation and cushioning the impact of global trade shocks. While trade diversion remains uncertain, the study highlights the critical role of regional trade agreements in stabilizing trade flows during global crises, offering valuable insights for future policy and regional cooperation strategies.

A Review of Studies on the Effects of Anthropogenic Disturbances on Plant–Soil–Microorganism Interactions in Grassland Ecosystems: Based on Grazing and Tourism Perspectives

As the most widely distributed and largest terrestrial ecosystem in the world, grasslands play an important role in supporting global livestock production and maintaining ecosystem services. In light of the accelerated global socio-economic development and sustained population growth, grassland ecosystems are increasingly subjected to anthropogenic disturbances. However, there is a paucity of research examining the impact of such disturbances on plant–soil–microorganism interactions in grassland systems, particularly from the perspectives of grazing and tourism. Accordingly, this study presents a comprehensive analysis of the impacts of anthropogenic disturbance on grassland ecosystems over the past two decades, employing a dual perspective of grazing and tourism and utilizing econometric analysis of the existing literature through software such as CiteSpace. The results of this study demonstrate the following: (1) The current research focus is primarily concentrated in the fields of ecology and environmental sciences, particularly on the topics of plant diversity, abundance, and diversity, as well as the intensity of grazing. These areas may represent key development direction of future research. (2) The impact of anthropogenic disturbances on grassland ecosystems is primarily associated with grazing activities. Moderate grazing disturbances can facilitate the healthy development of grassland ecosystems. However, the intermediate disturbance hypothesis (IDH) may not fully account for the effects of grazing intensity on grassland ecology. At present, there is still a paucity of systematic research to determine the ecological indicators of grassland under a dual-disturbance scenario. It is recommended that future research be carried out to investigate the compound effects of trampling by tourism activities on plant–soil–microorganism interactions in grassland ecosystems. (3) The mutual feedback mechanism may represent a potential mechanism by which anthropogenic disturbances affect the coupled relationship between the plant, soil, and microbial systems in grassland ecosystems. Furthermore, the interaction among these three systems has the potential to exert direct or indirect impacts on the structure and function of grassland ecosystems in the context of disturbances. The present study aims to provide an overview of the structure and function of grassland ecosystems under anthropogenic disturbances. The objective is to identify a balance between the rational use of grassland and ecological protection under anthropogenic disturbance and to provide scientific reference for the sustainable use of grassland worldwide.

What drives urban redevelopment activity? Evidence from machine learning and econometric analysis in three American cities

What drives urban redevelopment activity? Evidence from machine learning and econometric analysis in three American cities

An Econometric and Time Series Analysis of the USTC Depeg’s Impact on the LUNA Classic Price Crash During Spring 2022’s Crypto Market Turmoil

The cryptocurrency market is characterized by extreme volatility, with events such as the Terra-LUNA crash of 2022 raising significant questions about the resilience of algorithmic stablecoins. This paper investigates the collapse of LUNA Classic during the USTC depeg, focusing on the role of trading volumes and collateral assets like Bitcoin in amplifying the price crash. Using a Vector Logistic Smooth Transition AutoRegressive (VLSTAR) model, we analyze daily data from October 2020 to November 2022 to uncover how exogenous volumes influenced LUNA’s price trajectory during the crisis. Our findings reveal that high trading volumes, particularly during regime two (the post-depeg period), significantly exacerbated the price decline, validating the impact of large-scale liquidations on LUNA’s price path. Additionally, Bitcoin volumes played a critical role in destabilizing the system, confirming that the liquidity of underlying collateral assets is pivotal in maintaining price stability. These insights contribute to understanding the systemic vulnerabilities in algorithmic stablecoins and offer implications for future stablecoin design and risk management strategies. They are relevant for investors, policymakers, and researchers seeking to be aware of market volatility and prevent future crises in stablecoin ecosystems.

Can green trade development promote energy security in China? The role of financial development

Energy security is an essential component of overall national security. This paper investigates the impact of green trade (GRTR) on China's energy security and financial development's role in this nexus. The energy security evaluation index in this study is constructed from availability, applicability, acceptability, and affordability (the 4-As) and calculated by employing the Improved Entropy Method (IEM). Based on the two-step robust system-generalized method of moments (SYS-GMM) and data from China's 30 provinces between 2004-2020, this article investigates the impact of GRTR on energy security, the moderating effect of financial development and the impact mechanism of renewable energy development on the GRTR-energy security nexus. Our econometric analysis results indicate that increased GRTR can notably enhance energy security, and financial development can strengthen the positive impact of GRTR on energy security. The advancement of GRTR contributes positively to enhanced energy availability, acceptability, and affordability, but it could potentially decrease progress in the applicability of energy security; the promoting effect of GRTR on energy security in low-GRTR areas will be limited. The results of the mediating mechanism indicate that GRTR can accelerate energy security growth through renewable energy development. These insights provide policy implications for combining GRTR incentives to promote energy security.

Attention to biodiversity and stock returns

Our study empirically explores how public interest in biodiversity influences the financial performance of novel investment solutions that specifically promote biodiversity. We consider three distinct metrics capturing public attention to biodiversity: the daily Google Search Volume index for “biodiversity”, the daily media coverage of biodiversity, and the daily visits to the “biodiversity” page on Wikipedia. We also use the UN Biodiversity Conference (COP 15) as quasi-natural experiment. Our econometric analyses reveal a positive association between attention to biodiversity and excess stock returns on biodiversity stock indices. This suggests a growing investor preference for companies with the lowest biodiversity footprints when attention to biodiversity is particularly intense. These fresh insights offer important financial and policy implications.

Stochastic behavior of green bond premiums

This paper aims to examine the stochastic behavior of green bond premiums that can characterize the benefits of green bonds. We propose a novel affine model of green bond pricing with mean-reverting interest rates and green bond premiums and a new model parameter estimation method using conventional and green bond prices to capture the stochastic behavior. Then, the model parameter estimation results demonstrate mean-reverting stochastic behavior for conventional bond yield and green bond premium using the US and EU green bond indexes for Corporate and three corporate bond indexes for intermediate, total, and long-term periods of the Bloomberg Fixed Income Indices from November 3, 2014 to December 11, 2020. Comparative statics using simulated green bond premiums show that green bond premiums orient toward negative values in nature. Moreover, the stochastic behavior of green bond premiums demonstrates that the greenness of green bonds has a downward effect on interest rates in COVID-19 and has a mitigating impact on liquidity risk in corporate bond markets. These results confirm the benefits of green bonds. Finally, the discussions secure the validity of the green bond pricing model by conducting econometric analyses of regime switching, principal component ones, and the GARCH (1,1) model.

Social norms and individual climate protection activities: A survey experiment for Germany

Based on the well-known observation that social norms can guide individual behavior, this paper empirically examines the causal effect of related information interventions on climate protection activities, measured through incentivized donations. In our experimental setting, we distinguish between descriptive social norms by providing information about individual climate protection activities in Germany, injunctive social norms by providing information about what people in Germany think about the need for climate protection activities, and a combination of both social norms. Based on representative survey data from more than 1600 individuals in Germany, our econometric analysis shows some weak evidence that information about both descriptive and injunctive social norms increases donations for climate protection. The decomposition of this estimated average treatment effect reveals that the corresponding treatment particularly has a significantly positive effect at the extensive margin, i.e. on the probability to donate for climate protection. These results suggest that a combined information intervention referring to both descriptive and injunctive social norms is at least able to stimulate the general willingness for climate protection.

DOES GENDER EQUALITY IMPACT REGIONAL ECONOMIC GROWTH?:

This research aims to examine the impact of gender equality on regional development, represented by regional economic growth. The analysis applies econometric methods to panel data from 27 districts/cities in West Java Province for the 2018–2022 period, with the Common Effect Model (CEM) selected as the optimal regression model for this study. Gender equality is represented by indicators such as the ratio of female to male in per capita expenditure, mean years of schooling, life expectancy, and labor force participation rate. The findings reveal heterogeneous effects: gender equality in per capita expenditure, education, and health positively influences economic growth, with health, as measured by life expectancy, being the most significant factor. Conversely, the labor force participation rate exhibits a negative effect, indicating challenges in optimizing female's roles in the labor market. Overall, the study finds that gender equality development contributes 12.34% to West Java's economic growth. These findings highlight the need to provide equal opportunities for female by enhancing access to education, healthcare, and economic resources while addressing barriers in labor force participation to achieve inclusive and sustainable development.Keywords: Econometrics Analysis, Economic Growth, Gender Equality, Regional Development.