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This study investigates the disaggregated behavioral responses of mobile money users' willingness to pay for electronic levy payments in Ghana. We use cross‐sectional survey primary data and a probit regression estimation technique with its associated average marginal effects and check robustness with a linear probability model. The evidence from the study indicates that the disaggregated behavioral factors that drive willingness to pay for the e‐levy include individuals maintaining their current levels of electronic fund transfers, the intention to increase their electronic fund transactions, and intention to stop using electronic fund transfers that attract the e‐levy. Beyond the disaggregated behavioral responses, psychological (e.g., trust in government) and socioeconomic factors (individual income and gender) are identified as important drivers of willingness to pay for the e‐levy. We suggest that policies around e‐levies must not only focus on individual behavioral responses alone, as the drivers include behavioral, psychological, and socioeconomic factors. Related Articles: Adegboye, Alex, Kofo Adegboye, Uwalomwa Uwuigbe, Stephen Ojeka, and Eyitemi Fasanu. 2023. "Taxation, Democracy, and Inequality in Sub‐Saharan Africa: Relevant Linkages for Sustainable Development Goals." Politics & Policy 51(4): 696–722. https://doi.org/10.1111/polp.12547. Lachapelle, Erick, Thomas Bergeron, Richard Nadeau, Jean‐François Daoust, Ruth Dassonneville, and Éric Bélanger. 2021. "Citizens' Willingness to Support New Taxes for COVID‐19 Measures and the Role of Trust." Politics & Policy 49(3): 534–65. https://doi.org/10.1111/polp.12404. Shock, David R. 2013. "The Significance of Opposition Entrepreneurs on Local Sales Tax Referendum Outcomes." Politics & Policy 41(4): 588–614. https://doi.org/10.1111/polp.12028. [ABSTRACT FROM AUTHOR]

Information-Centric Networking (ICN) is promising system architecture for distributing popular information across the network. Its important feature is the node cache. ICN with caching is a very promising featured network structural design. There are numerous cache nodes distributed in the ICN. Excessive consumption of cache information on a tremendous number of nodes dissipates a large storage space and causes data redundancy, which reduces the cache hit rate. Therefore, an efficient caching deployment approach is required to improve the cache hit rate. A novel RAndom probit regressive Bucklin DEcision Forest classifier (RADEF) technique is introduced in Information-Centric Networking (ICN) for minimal network latency and higher cache hit rate. In RADEF Technique, probit regression and random forest classification processes are carried out for ICN with healthcare patient data. First, the patient information is collected from different IoT devices and registered. Every request to the router node is analyzed in the content storage (CS) by using a random probit regressive Bucklin decision forest classifier. The Bucklin decision forest classifier is an ensemble technique that includes a set of weak learners as decision trees (i.e., probit regression tree) and IoHT data are selected randomly for each decision tree. The Probit regression tree is constructed to analyze the patient healthcare data request search in the content storage (CS) of the router node in the ICN network by using a simple matching coefficient. If the copy is present in the content storage, the particular router nodes are chosen and deliver the content. If the copy is absent, the patient information is stored in the cache. Then, the weak learner's results are combined to make a strong output. Then the votes are generated for each decision tree. The votes of all decision trees are combined to identify the majority votes of data for classification by minimizing the error using the Bucklin voting method. In this way, content catching is effectively performed in ICN with minimum latency and a higher cache hit ratio. Experimental evaluation is carried out on factors such as cache hit rate, network latency, average request length, average response time, server traffic ratio, and hop reduction ratio regarding respect to the number of patient healthcare data. The analyzed results demonstrate the superior performance of our proposed RADEF technique when compared with existing methods. [ABSTRACT FROM AUTHOR]

The telecommunications industry is highly competitive, as operators engage in fierce attacks, especially in bundled services, to acquire new customers originating high churn rate. The objective of this paper is to gain a comprehensive understanding of the factors influencing the switching of operators for bundled services among telecom operators. The paper includes a quantitative study with 3,004 customers utilizing bundled services from a Portuguese telecom operator. Employing covariance-based structural equation modeling and logit regression, the research shows that internet service, television service, and the service provided by the contact center exert the greatest impact on loyalty to the operator. In contrast, landline service has an insignificant effect, while loyalty has a negative influence on customer churn. This study offers telecommunications managers insights for identifying the main factors to retain customers and curbing customer defection. Additionally, it provides a framework for assessing customer experience within bundled telecom services, which is useful for researchers, managers and marketing practitioners alike. [ABSTRACT FROM AUTHOR]

Under the background of general financial knowledge confidence and insufficient retirement planning, this study investigates the relationship between overconfident financial knowledge and consumer retirement planning. Using data from the National Financial Capability Study, this study employs probit regressions and finds that consumers with overconfident financial knowledge are less likely to have retirement planning, that is, contribute to retirement accounts regularly. This study further explores the mediators in this relationship and concludes that consumers who are overconfident in their financial knowledge tend to be more preference to risk, fail to make ends meet, and do not care about their financial situation, therefore are less likely to plan for retirement. Furthermore, compared to retirement accounts such as 401(k) that are through an employer, consumers with overconfident financial knowledge are more willing to engage in those such as IRA that are not through an employer. This study also finds that underconfident financial knowledge, another type of incorrect subjective evaluation of financial knowledge, is positively associated with retirement planning. Based on these findings, this study recommends policymakers reduce financial knowledge overconfidence, guide individuals to regularly pay attention to their financial situation, and encourage employers to actively participate in retirement plans. [ABSTRACT FROM AUTHOR]

This study examines the influence of board characteristics on company’s sustainability reporting in the GCC region. In contrast to prior research, we investigate the relationship between variables across a span of eleven years, encompassing all nonfinancial firms listed on the GCC stock exchanges. Our study addresses the scarcity of research undertaken in the GCC region on this particular topic. This study empirically investigates the relationship between board characteristics (specifically, board size, board gender diversity, board meetings, and board independence) on the adoption of sustainable reporting while taking into account firm characteristics (including leverage, profitability, liquidity, and firm size) and controlling for macroeconomic variables (such as GDP and inflation). This research utilized Probit regression to examine the influence of the likelihood of various variables on the adoption of sustainable reporting. The findings indicated that larger board sizes, a higher proportion of female board members, the inclusion of more independent directors, and more frequent board meetings all contribute to the improvement of sustainable reporting. Furthermore, the greater the size, the greater is the impact of profitability and liquidity on the sustainability of reporting. The current research offers some insights into the connection between board characteristics and corporate sustainability reporting for corporate boards, regulators, and practitioners who are interested in promoting sustainable reporting. Further investigation should examine the comparison of sustainability reporting methodologies across different regions, as well as between privately held and publicly listed corporations. Finally, as evident by the results reported in the Maximum Likelihood Estimator our results are robust.

Over the past few years, there has been a significant focus on air pollution due to its various detrimental effects on human health. However, its influence on people's tendency to have children remains uncertain, as only a few studies have examined the correlation between public perception of air pollution and the desire to start a family. This article introduces a theoretical framework utilizing a two-stage interval iteration model to explore the connection between children's relative utility and the perception of air pollution. Data for this study were gathered from the "Chinese General Social Survey" (CGSS 2013). The CGSS 2013 project employed a four-stage stratified random sampling technique and conducted household interviews using questionnaires. The sample covered 28 provincial-level cities across China. The hypothesis was tested using a Probit regression model. The findings indicate that individuals considering air pollution a significant issue are 8.62% less likely to have more than one child. The variation in fertility desire sensitivity to air pollution points to heterogeneity among residents, such as registered residents and those living in various residential areas, as well as individuals with different characteristics like education levels. The study concludes that air quality significantly influences human fertility desire, highlighting the urgent necessity to raise awareness of environmental protection issues among both the public and authorities. In particular, there are two key steps to address this issue. Firstly, the government should establish clear air pollution control objectives and refine policies to enhance governance efficiency. Secondly, there is a need to encourage environmentally friendly behaviours among the public, promote more significant involvement in public environmental matters, and ensure effective oversight of the government's responsibilities in managing air pollution. [ABSTRACT FROM AUTHOR]

While most performance metrics of high‐explosive (HE) based devices like detonation velocity, detonation pressure, and energy output are expected to degrade over time, the evolution of initiation threshold appears less clear, with claims of both increasing and decreasing trends in threshold having been made in the literature. This work analyzes D‐optimally designed sequential binary test data for a few thermally conditioned porous‐powder and polymer‐bonded HE initiator systems using a Bayesian likelihood method employing the probit regression model. We find that in most cases the initiation threshold decreases (i. e., sensitivity increases) upon accelerated thermal conditioning. However, such results are nuanced and influenced by factors like the contact area of initiating stimulus, HE characteristics like density and specific surface area, as well as possible thermally induced changes to other materials and interfaces involved. [ABSTRACT FROM AUTHOR]

Athelia rolfsii, causal agent of "southern blight" disease, is a soilbome fungal pathogen with a wide host range of more than 500 species. This study's objectives were to (i) quantify the effects of two environmental factors, temperature and soil moisture, on germination of A. rolfsii inoculum (sclerotia), which is a critical event for the onset of disease epidemics and (ii) predict the timing of sclerotial germination by applying populationbased threshold-type hydrothermal time (HTT) models. We conducted in vitro germination experiments with three isolates of A. rolfsii isolated from peanuts, which were tested at five temperatures (7), ranging from 17 to 40°C, four matric potentials (W) between -0.12 and -1.57 MPa, and two soil types (fine sand and loamy fine sand), using a factorial design. When Mm was maintained between -0.12 and -0.53 MPa, T from 22 to 34°C was found to be conducive to sclerotial germination (>50%). The HTT models were fitted for a range of T (22 to 34°C) and Mm (-0.12 to -1.57 MPa) that accounted for 84% or more of variation in the timing of sclerotial germination. The estimated base T ranged between 0 and 4.5°C and the estimated base Mm between -2.96 and -1.52 MPa. The results suggest that the HTT modeling approach is a suitable means of predicting the timing of A. rolfsii sclerotial germination. This HTT methodology can potentially be tested to fine-tune fungicide application timing and in-season A. rolfsii management strategies. [ABSTRACT FROM AUTHOR]

Poverty continues to be one of the biggest challenges facing many economies worldwide, and its incidences and intensities are very high in developing economies. This paper utilized the Alkire-Foster (AF) method to compute the multidimensional poverty index (MPI) and analyze the incidence and intensity of multidimensional poverty among urban households in Kenya. The findings indicated that 8.7 % of urban households are multidimensionally deprived in 33.3 % of the selected dimensional indicators. Also, the results showed that over 50 % of urban households are deprived of drinking water and sanitation services. In addition, the findings revealed that higher poverty incidence, intensity, and urban multidimensional poverty exist among female-headed households, old household headships, and households residing in peri-urban regions. The Probit regression analysis indicated that large household size, number of children under five years, household head age, gender, marital status, urban food insecurity, health status, and residing in Malaria endemic zone are significant positive predictors of urban multidimensional poverty. On the other hand, an increase in the number of educated women, owners of insurance coverage, agricultural land, and wealthy and home-owning households is linked to a decline in urban multidimensional poverty. The paper professes that policymakers should cautiously consider household socioeconomic differences while designing poverty alleviation policies.

The weather index crop insurance (WICI) scheme was introduced under a pilot project for rice in Cambodia in 2021. The adoption rate was low and the loss ratio was higher than 200%. The increase in farmers' participation would help reduce the loss ratio, which can sustain the WICI scheme. This study, therefore, examines Cambodian rice farmers' willingness to purchase WICI in Cambodia. The hypothesis is that the low adoption rate is due to a lack of awareness, lack of understanding of WICI, lack of trust in weather stations, and the problem of basis risk. This study would like to test the influence of those factors on the willingness to purchase in Cambodia. Battambang Province was chosen as the study area as it is the largest area for rice production and has the largest take-up rate of farmers buying WICI. Detailed interviews of 232 farmers were conducted in the districts of Bavel and Moung Ruessei. The probit regression model was used to identify factors that significantly impact farmers' willingness to purchase WICI. The results indicate that land size, level of trust in weather stations, level of farmers' understanding of WICI, and joining the WICI awareness program have positive effects on the probability of farmers' willingness to buy WICI, whereas the number of household laborers and expectation of floods have negative influences. The probability of willingness to purchase by farmers who attended the awareness program on WICI was 38% higher than those who did not. The size of farmland, level of trust in weather stations, and level of understanding of WICI increase in one unit affecting the probability of willingness to purchase WICI by 4%, 16%, and 25%, respectively. On the other hand, the increase in the number of household laborers in the rice field by one person and the increase in the probability of expected flood increase by 0.1 drag back the probability of farmers' willingness to purchase by 16% and 5%, respectively. The results suggest the government to raise the insurance awareness and understanding of WICI. Development of weather station infrastructure, as well as maintenance of weather stations, is needed to guarantee the accuracy of data generated from the weather station. [ABSTRACT FROM AUTHOR]

Genomic selection (GS) is a disruptive methodology that is revolutionizing animal and plant breeding. However, its practical implementation is challenging since many times there is a mismatch in the distribution of the training and testing sets. Adversarial validation is an approach popular in machine learning to detect and address the difference between the training and testing distributions. For this reason, the adversarial validation method in this research was implemented using probit regression to detect the mismatch in distributions and also to select an optimal training set. We evaluated the proposed method with 14 datasets, and the results were benchmarked regarding of using the whole reference population and simple random samples. We found that the proposed method is effective for detecting the mismatch in distributions and outperformed in prediction accuracy by 11.67% (in terms of mean square error) and by 5.35% (in terms of normalized mean square error) when the whole reference population was used as training sets. Also, in general, this outperformed some existing methods for optimal training designs in the context of GS. [ABSTRACT FROM AUTHOR]

The study identifies determinants of vegetable farmers' market participation and evaluates their impact on households' welfare. In this study, we collected 175 cross‐sectional household data and employed a probit regression model to identify the determinants of vegetable farmers' market participation. The study estimates the impact of market participation on households' income and per capita consumption using the propensity score matching approach (PSM). Subsequently, the study used the endogenous switch regression (ESR) model to control sample selection bias and unobserved heterogeneity. ESR also evaluates the robustness of PSM outcomes. Results from PSM and ESR approaches suggest that vegetable market participation positively and significantly impacts smallholders' income and consumption expenditure. The study rejects the null hypothesis that vegetable market participation does not significantly impact farmers' welfare. Results show that vegetable market participation increases the farmers' monthly income and annual per capita consumption expenditure on average by Indian rupee (INR) 8360 and INR 26,410, respectively. Findings also indicate that household size, distance to market, off‐farm income, access to training, price information, vehicle ownership, and storage systems are critical determinants of vegetable farmers' market participation. Identified determinants may support policymakers in designing suitable agricultural marketing policies to reduce market entry barriers and motivate farmers for market participation. [EconLit Citations: Q13, D60]. [ABSTRACT FROM AUTHOR]

This study provides new evidence on factors driving firms´ eco innovation in the European Union, based on the data of the Community Innovation Survey for the years 2008 and 2014 for eleven European countries. First, our findings reveal that the propensity to eco-innovate changes over time. Second, the propensity to eco-innovate is unequally distributed across sectors, given that it is concentrated in a few sectors. Third, we find that sectoral behavior is strongly influenced by the taxonomy of green sectors introduced by the European Union, since the propensity to innovate is higher in the carbon leakage taxonomy than in the mitigation and adaptation taxonomy. These results provide further insights into the sectoral factors driving eco-innovation diffusion. Moreover, these findings are relevant to increase environmental stringency, as they contribute to the diffusion of eco-innovation across sectors, especially in those that do not innovate.

The article presents methodological tools for assessing the value of the company, taking into account the fact of distortion of the accounting (financial) statements of the company. The reliability of the reporting of companies of the type of economic activity “Construction” is determined - one of the most important industries for the development of the Siberian Federal District (SFD) in the post-pandemic reality. The cost of construction companies of the SFD is estimated, the existence of a relationship between the manipulation of reporting and the value of the company is revealed. The authors propose an algorithm for assessing the value of the company, taking into account the fact of manipulation of reporting data. The steps of the algorithm of actions involve building a probit regression on an array of reporting data of companies with an interesting type of economic activity, determining the probability of manipulating reporting data based on the regression obtained, assessing the real value of the company taking into account the facts of manipulation. The proposed methodology for assessing the value of a company, taking into account manipulation, can be used to make management and investment decisions by external and internal stakeholders, including banks, credit organizations, suppliers, owners of construction companies, and other interested parties.

The financial literacy level determines the economic condition of every social stratum. In other words, when farmers experience failure in regulating their economic activities, it is most likely due to their low financial literacy level. The study aims to identify the financial literacy level of chilli farmers in Rural Areas, analyze the factors that influence the financial literacy level, and analyze the impact of financial literacy on increasing the income of chilli farmers in Rural Areas. This study uses Propensity Score Matching (PSM) method to analyze the impact of financial literacy. The results of the study provide information that (1) The majority of chilli farmers' financial literacy in Rural Areas is at a high level with 65% of the total respondent, (2) The existence of financial literacy in Rural Areas has a positive impact on increasing the income of chilli farmers with a comparison that farmers at high literacy levels have higher incomes of Rp. 65,384,503 compared to farmers who have low literacy levels, and (3) The results of the analysis of factors that influence financial literacy state that the factors of age, education level, land area, land status, farming experience, and family responsibilities have a relationship with financial literacy, but the gender factor cannot be identified statistically.

IntroductionAn intense debate has been on-going about how artificial intelligence (AI) technology investments have an impact on employment. The debate has often focused on the potential of AI for human task automation, omitting the strategic incentive for firms to cooperate with their workers as to exploit AI technologies for the most relevant benefit of new product and service innovation.MethodWe calibrate an empirical probit regression model of how changes in employment relate to AI diffusion, based on formalizing a game-theoretical model of a firm exploiting the twin role of AI innovation and AI automation for both absolute and competitive advantage.ResultsThe theoretical game-theory prediction is that employment following AI technology adoption is not negative, and ultimately depends on how AI leads to new success in innovation, competition which defines the competitive reward of innovation and profit sharing between workers and firms. Our estimation, is based on a global survey of 3,000 large companies across 10 countries, demonstrates that a firm employment growth depends on two strategic postures, that is, the firm relative maturity of AI adoption as well as its relative bias toward AI-based product innovation.DiscussionThe contribution of this research is to highlight the twin role of firm and workers in shaping how technology will affect employment. AI in particular marries the potential of task automation with even more potential for expansion.

The covid-19 pandemic has had a devastating impact on the operations of all enterprises but particularly on Small and Medium Enterprises (SMEs). In the case of Zambia, SMEs experienced a significant decrease in revenue, while confronting a dramatic increase in the costs of inputs. Furthermore, few SMEs had access to financial support from the government. This paper implements a binary Probit regression model to analyse the impact of the level of fulltime female workers, the business environment, and adaptations on innovation among SMEs in Zambia. Our results show that those SMEs that are willing to adapt are also more likely to innovate. Our results also show that an increasing presence of women as full-time workers is a conduit for innovation. Among other things, we conclude that Zambia must focus on the development and promotion of domestic markets and SMEs resilience, as well as strategies that support female labour participation, female entrepreneurs, and job creation. [ABSTRACT FROM AUTHOR]

AbstractGlobally Financial inclusion provides an opportunity to promote equal access to resources for all. One of the crucial catalysts for microenterprises development is access to the financial market. However, the growth of many microenterprises has been truncated in Ghana due to limited access to financial opportunities. Despite this challenge, little is known about the drivers of financial inclusion in Wa Municipality of the Upper West Region of Ghana. This paper examines the drivers of financial inclusion of microentrepreneurs in the Wa Municipality of the Upper West Region of Ghana. Using a close ended questionnaire, this study employed an exploratory survey design to collect data from 200 engaged in trading, manufacturing, and services. The respondents were sampled using a simple random sampling technique. Given that the outcome variable is binary, the study used a binary probit regression model for the data analysis. The results predicted that religion, awareness of loan services, business registration, and preparation of financial statements drive financial inclusion in Wa Municipality. From the results, the study recommends that financial service providers should consider social networks, entrepreneurial practice, gender and religion as sensitive drivers of financial inclusion. In addition, financial education should be intensified as knowledge of the available financial products is a key driver of financial inclusion in the Municipality. While this study has contributed to the body of literature on financial inclusion in Ghana, further research is necessary to identify consumer financial needs to meet clients’ expectations.

Globally Financial inclusion provides an opportunity to promote equal access to resources for all. One of the crucial catalysts for microenterprises development is access to the financial market. However, the growth of many microenterprises has been truncated in Ghana due to limited access to financial opportunities. Despite this challenge, little is known about the drivers of financial inclusion in Wa Municipality of the Upper West Region of Ghana. This paper examines the drivers of financial inclusion of microentrepreneurs in the Wa Municipality of the Upper West Region of Ghana. Using a close ended questionnaire, this study employed an exploratory survey design to collect data from 200 engaged in trading, manufacturing, and services. The respondents were sampled using a simple random sampling technique. Given that the outcome variable is binary, the study used a binary probit regression model for the data analysis. The results predicted that religion, awareness of loan services, business registration, and preparation of financial statements drive financial inclusion in Wa Municipality. From the results, the study recommends that financial service providers should consider social networks, entrepreneurial practice, gender and religion as sensitive drivers of financial inclusion. In addition, financial education should be intensified as knowledge of the available financial products is a key driver of financial inclusion in the Municipality. While this study has contributed to the body of literature on financial inclusion in Ghana, further research is necessary to identify consumer financial needs to meet clients' expectations. [ABSTRACT FROM AUTHOR]

Early warning models credit risk play a crucial role in helping the financial institutions to reasonably predict the credit status of family farms and ranches. An attempt is made in this paper to construct a new credit risk early warning model based on Probit regression and Kmeans clustering algorithm, and testing the model by using data from 246 family farms in 12 leagues and cities in Inner Mongolia. First, the credit risk evaluation indicators of family farms and ranches were screened out through a three-combination model with partial correlation analysis, tolerance analysis and Probit regression. Second, the ratios of the Z-squared statistic of a single indicator to the sum of the Z-squared statistics of all the selected indicators were used to measure the weights of the credit evaluation indicators. Finally, four warning levels containing heavy alert level Ⅰ, medium alert level Ⅱ, light alert level Ⅲ and no alert level Ⅳ were classified by Kmeans clustering with large intra-cluster similarity and small inter-cluster similarity. The empirical evidence shows that the early warning model of credit risk for family farms and ranches is effective.

IntroductionThe food justice movement focuses on resolving food system inequalities, including, but not limited to, income, ethnicity, and race differences related to household access to food, farmer access to markets, and the fair treatment of farmworkers. Previous studies have focused on food system inequalities from the consumer demand side, but only a few studies have focused on the role farmers play in creating more equitable food systems. An example of a market model aiming to fulfill various missions of the food justice movement is Fresh Stop Markets (FSMs). FSMs aggregate food from local farmers and sell shares on a sliding scale based on consumers’ income. Lower income households pay less than higher-income households for the same food. A vital component of this market concept is farmers’ willingness to sell produce through FSMs.MethodsWe used data from a 2020 survey of Tennessee and Kentucky fruit and vegetable farmers and the double-bounded dichotomous choice contingent valuation approach to assess farmers’ willingness to sell produce through FSMs when faced with a price discount scenario. A probit regression was used to investigate the factors correlated with farmers’ willingness to sell produce through FSMs.Results and discussionResults suggest gross farm revenue, farmer age, education, experience selling produce through farmers markets, and running programs on the farm to educate communities about sustainable agriculture and food systems are associated with farmers’ willingness to sell produce through FSMs.ConclusionFarmer and farm business characteristics, as well as prior experience running education programs on the farm related to sustainable agriculture and food systems are important factors to consider when trying to engage farmers willing to sell produce through FSMs.

Mobile Ad hoc Networks (MANET) are structure less, autonomous wireless networks with mobile nodes that dynamically establish data transmission connections. Due to dynamic topological change, MANET routes are unbalanced and break repeatedly. Hence, providing efficient and reliable data delivery with effective utilization of network resources is a challenging issue to be considered in MANET. This paper proposes an instant-runoff Ranked Decision Forests Probit Regression-based Connectionist Multilayer Deep Neural Network (IRDFPR-CMDNN) for efficient data transmission and higher data delivery with a minimum end-to-end delay. This IRDFPR-CMDNN method performs route identification, data delivery, and route maintenance with more than three layers. Then the mobile nodes are sent to the input layer of the Connectionist Multilayer Deep Neural Network. In hidden layer 1, the Instant-runoff Ranked Decision Forests algorithm is applied for classifying the mobile nodes depending on the residual energy and load capacity. With selected mobile nodes, the Probit Regression is applied for finding the nearest neighboring nodes in the second hidden layer based on the link quality and received signal strength for route path establishment. Then multiple paths for routing are established from source to destination node and start to perform the data transmission. If link failure occurs during the data transmission, another alternative route with better link quality is selected for routing. In this way, energy-efficient data transmission is performed from source to destination with a higher data delivery rate and minimal time consumption. Experimental evaluation is carried out on energy consumption, packet delivery ratio, packet drop rate, throughput, and end-to-end delay with varying numbers of mobile nodes and data packets. Simulation results show that the IRDFPRCMDNN technique effectively enhances data delivery, throughput and minimizes energy consumption, packet loss rate, delay with respect to conventional methods.

This work seeks to statistically verify the hypothesis that there is a link between violations of environmental legislation and distortions in the financial reporting of economic entities. For this purpose, the authors studied the reporting documents of companies that are operating in Russia and have violated environmental legislation. The financial reporting of the latter was analyzed based on the authors' methodology. In order to determine the probability of distortion, companies were typologized and a probit model was constructed. The results confirmed the working hypothesis that economic entities' opportunistic behavior in the area of environmental protection is, as a rule, accompanied by distortions of financial information about their activities. [ABSTRACT FROM AUTHOR]

Aim/purpose – External aid allocation by the donors in recent years has been fraught with instability and volatility. This has a negative consequence on the recipient economies particularly those that are highly aid-dependent. A good solution to the problem requires much understanding of factors influencing the behavior of external aid in the respective recipient economy. In this study, the focus was on analyzing two economic factors uncommonly discussed in the empirical literature – the influence of the degree of economic freedom and external debt burden on aid allocation, with emphasis on African economy.

We introduce a method of Robust Learning (' robl ') for binary data, and propose its use in situations where Active Learning is appropriate, and where sampling the predictors is easy and cheap, but learning the responses is hard and expensive. We seek robustness against both modelling errors and the mislabelling of the binary responses. Thus we aim to sample effectively from the population of predictors, and learn the responses only for an 'influential' sub-population. This is carried out by probability weighted sampling, for which we derive optimal 'unbiased' sampling weights, and weighted likelihood estimation, for which we also derive optimal estimation weights. The robustness issues can lead to biased estimates and classifiers; it is somewhat remarkable that our weights eliminate the mean of the bias – which is a random variable as a result of the sampling – due to both types of errors mentioned above. These weights are then tailored to minimize the mean squared error of the predicted values. Simulation studies indicate that when bias is of significant concern, robl allows for substantial reductions, relative to Passive Learning, in the prediction errors. The methods are then illustrated in real-data analyses. • Robustness is considered simultaneously for misspecification and misclassification. • Asymptotic properties are provided. • Simulated and real examples show the performance of this approach. [ABSTRACT FROM AUTHOR]

The regulations of fruit trade for safe consumption are taken seriously in the EU and US markets to protect the health of the consumers, animals, plants and environmental safety, and thereby reduce health expenditures. The fruit safety regulations as trade policy measures could be either trade-promoting or -impeding. The extensiveness and intensiveness of fruit safety regulations in these markets often have consequences for exporters from Africa and their desire to attain sustainable economic development. The effects of fruit safety regulations are heterogeneous across economic agents. To this end, many stakeholders in Africa's food system have perceived compliance with these food regulatory measures as necessary conditions to access the developed countries' markets, particularly in the EU and US. Besides, the competitiveness of Africa's fruit exports has been impacted by the preponderance of the measures despite its comparative advantages in the fruits sub-sector. Therefore, this study aims to investigate the impact of the EU and US sanitary and phytosanitary measures on Africa's fruit exports. The empirical strategy involves the use of an augmented gravity model which explore the disentangling of these impact at the extensive and intensive margins of exports. Given the nature of trade data and specifically for this study, the zero trade flows are considered at both margins of exports for 45 African countries from 1995 to 2017. This study finds that the US market is more trade-impeding to Africa's fruit exports than the EU market. Thus, Africa needs policies tweaking in the fruit value chain quality infrastructure, fruits' quality and standards enforcement, capacity development, continuous update and modernisation of the fruits' safety laws, directives and/or regulations. This will enhance the fruits' quality to propel their access to the transatlantic markets. [ABSTRACT FROM AUTHOR]

SMEs in the Arab region are widely viewed as important for their multiple roles, notably in employment creation. Yet, they consistently encounter several constraints such as financing, which impede innovation, growth and internationalisation. This paper examines the external finance-innovation nexus for SMEs operating in five non-oil Arab countries—Egypt, Jordan, Lebanon, Morocco and Tunisia. To achieve this, a probit regression with instrumental variables is applied to firm-level data from the World Bank Enterprise Surveys. The primary findings reveal that the external finance providers are more likely to be reluctant to fund SMEs' innovation; yet, it thrives with finance. The findings accord with the hypothesis that the accessibility to external funds is a mainstay of SMEs' innovation. There is a need to develop policies that support equity and debt capitals for innovative SMEs. [ABSTRACT FROM AUTHOR]

Estimates of treatment effects in non-experimental studies are subject to bias owing to unobserved confounding. It is desirable to assess the sensitivity of an estimated treatment effect to a hypothetical unmeasured confounder, U. A commonly used approach to sensitivity analysis requires two parameters: one parameter relates U to the treatment and the other relates it to the outcome. The method uses a simple algebraic formula with these two parameters to relate the true treatment effect to the apparent treatment effect, obtained from a reduced model without U. This formula approximately holds for logistic and proportional hazards models, which are frequently used to model binary and survival outcomes. This approximation works with an assumption that the absolute regression coefficient for the unmeasured confounder is small. Therefore, when the unmeasured confounding is relatively large, the formula will not perform well. In this article, we propose alternative sensitivity analysis methods for binary and survival outcomes. We develop sensitivity analysis formulas for treatment effect estimates under probit and additive hazard models, which are alternatives to the logistic and proportional hazards models, respectively. The proposed formulae hold without any approximations. We also discuss a method to postulate reasonable values of the sensitivity parameters using the observed covariates. Simulation studies demonstrate that the proposed formulae perform well for moderate and severe unmeasured confounding even when the model used for the sensitivity analysis is moderately mis-specified. The practical utility of the approach is illustrated in two example studies. [ABSTRACT FROM AUTHOR]

We apply a semiparametric approach to 19 metropolitan areas in the US to relate normalized house prices to the age distribution within each area. We find that, although the elderly population has a negative impact on house prices in most areas, the shape of the estimated age response function differs between areas. We further find via probit and logit regressions that the age-response function is more likely to become inverted U-shaped as the population of an area becomes more aged, which is also suggestive of the negative impact of aging. These results indicate that the impact of the elderly population becomes more negative as the population ages. [ABSTRACT FROM AUTHOR]

Better working conditions promote employee creativity and loyalty. Meanwhile, a stable and skilled workforce contributes to a firm's sustainable growth. Therefore, providing favorable working conditions is one of the critical sustainable goals of many countries worldwide. However, some critics are concerned participating in international trade causes worsening employment conditions in developing countries. Driven by these concerns, the relationship between exports and labor conditions is worth illuminating. This study adopts the data from Vietnam's small and medium-sized manufacturing enterprises (SMEs). The dataset was collected by the Ministry of Labour, Invalids and Social Affairs (MOLISA) and the University of Copenhagen, UNU-WIDER from 2011 to 2015. Unlike previous studies, this study clusters firms by export status, including four groups: non-exporting, consecutive exporting, start-exporting, and exit-exporting. Observing dynamic exports sheds light on the effects of export decisions more thoroughly than the static export. Another contribution, this study focuses on an essential aspect of working conditions: providing fringe benefits. Subsequently, the analysis is upgraded by controlling for firm constraints as interaction variables. A major constraint and financial constraint are adopted to proxy for a firm's constraints. This work promotes assessments to be more accurate, thereby providing more valuable information to policymakers. Finally, a robustness test is applied to each type of fringe benefit. Instrumental variables are used to solve the problem of endogeneity. The results found that exporting firms provide better working conditions. Additionally, constrained firms have worse working conditions. [ABSTRACT FROM AUTHOR]

When agricultural policymakers promote the accumulation of idle farmland to leading farmers, it is more important to predict the intentions of landowners (i.e., intentions to sell, rent, or cultivate) with high accuracy than to elucidate structural factors. In this study, we attempted to solve this problem by specifying a support vector machine (SVM) based on agricultural land information systems in two regions of the Tokyo metropolitan area. As a result, the SVM showed high prediction accuracy on the training data set and the test data set. [ABSTRACT FROM AUTHOR]

This study examined farmers’ willingness to pay for participatory poultry research in Kwara State, Nigeria using ex-ante approach. The study utilized primary data collected with the aid of structured questionnaire. A random sampling technique was utilized to select a total number of 102 poultry farmers from Poultry Association of Nigeria (PAN) Kwara State Chapter. Descriptive statistics, Contingent Valuation (CV) techniques and probit regression model were used to achieve the research objectives. The CV results showed that 64.7% of the households were willing to pay. The monthly individual aggregate WTP amount ranged from N2,000 to N6,000, and on average N 2,576 per month, generating aggregate annual values ranging from N12,000.00 to N72,000.00 and on average N30,912.00 (ceteris paribus). Probit regression model demonstrated a significant (p

Understanding household disaster risk perception is crucial to formulate and apply disaster risk reduction strategies. Using survey data from 300 households from three highly disaster-prone areas of the lower Teesta River basin in Bangladesh, this study explores households' risk perception of drought, earthquake, and flood at the local level. The ordered probit regression model was applied to identify the factors influencing household disaster risk perception. Most of the respondents perceived the likelihood of occurring drought, earthquake, and flood hazards on a large scale in the selected areas which cause negative impacts on their quality of life and financial losses. They have lack knowledge on mitigation actions which makes them unable to control the devastating impacts of disasters. Econometric results show that households' age, gender, education, and income-generating sources had significantly influenced the respondent's drought, earthquake, and flood risk perception. Female participants have less knowledge on mitigations actions and are less capable of controlling the hazards than their counterparts making them more vulnerable to the impacts of hazards. Urgent action is required to improve their socio-economic conditions, and to reduce the knowledge gap between males and females as well as to improve the household's understanding of mitigation and preparedness for disaster risk. [ABSTRACT FROM AUTHOR]

The modernised consumption of canned sweet corn is being discouraged health wise. Raw sweet corn is grown as substitute to canned ones to curtail its negative impact on the health. However, the extent of acceptability and willingness to pay for raw corn is not fully documented. The University of Ibadan community was stratified into four major groups which were academic staff members (5,759), the non-academic members (4,210), the undergraduate students (16,248), and the postgraduate students (13,056). Data on socio-economic characteristics, monthly food and non-food expenditure, monthly expenditure on corn, level of awareness and perception of raw sweet corn, factors determining the point of purchase and willingness to pay for raw sweet corn were collected randomly from a sample of 120 respondents from halls of residence, boy’s quarters, chalets, flats and block-of-flats, respectively. The data were then subjected to descriptive statistics, probit regression and contingent valuation technique. The contingent valuation method revealed that household size, average monthly income and frequency of corn consumption were the determinants of WTP for raw sweet corn. The mean WTP was ₦ 505 as premium for 10 cobs of raw sweet corn. Following the results obtained, it was concluded that not all the socio-economic characteristics affected WTP for raw sweet corn significantly. Also, average monthly income of respondents in the study was observed to affect willingness to pay positively can be adjusted to enhance the probability of willingness to pay for raw sweet corn. [ABSTRACT FROM AUTHOR]

Despite the major structural changes in the Indian credit system, landless and near landless agricultural labour households are still facing difficulties while accessing formal credit services. The paper tries to examine the possible factors influencing the accessibility of institutional credit by agricultural labour households and its role in their livelihood. Based on a village-level field investigation in the district of East Medinipur, West Bengal, the study shows that the possession of operational land, membership of SHG, diversified farm and non-farm income, and higher financial literacy index are the significant determinants to increase the possibility of receiving institutional credit for these households. Using the two-stage least square method, the paper further reveals that the monthly per capita income of the agricultural labour households can increase if they use institutional and non-institutional sources of loans in income-generating activities. The study also suggests that the lower is the age of the household head and the less dependency on the informal credits for consumption purposes of the households, the higher is the possibility of improving the livelihood of the agricultural labour households. [ABSTRACT FROM AUTHOR]

Despite the conceptual promise and attractiveness of Climate Smart Agriculture (CSA) in ensuring farmers’ resilience and food security, empirical evidence of its success are observed to be scanty and mixed in terms of results, thus prompting further research. In this article, we analyzed the effect of adopting six Agricultural Practices with CSA Potentials (AP-CSAPs) on food security status using recent cross-sectional data on 238 maize farmers from Northern Nigeria. Data were analyzed using descriptive statistics and Probit regression. The results showed that 92.4% of the maize farmers were male, with a mean age and household size of 44 years and nine persons, respectively. We find that 37.0% of the farm households were food insecure, and adoption of the AP-CSAPs was generally low. However, while refuse retention and agroforestry influenced food security, the remaining four practices considered did not. In addition, we find that land fragmentation, off-farm income and age influence the likelihood of being food secure. We recommend further research on the medium- to long-term effects of AP-CSAPs and suggest that policies aimed at consolidating landholdings to promote monocropping among rural farmers be discouraged.

Rural and small holder famers in Nigeria and other developing countries have low capital base and poor access to finance. The inability of these farmers’ access to adequate credit has increased the problem of low efficiency in production. Inadequate credit supply is a major problem with which other production factors may exert negative influence on farmers’ output and efficiency. In ascertaining the sources and accessibility of credit by crop farmers in Enugu-Ezike in Enugu State, Nigeria, the sources of credit to farmers, the socio-economic characteristics of crop farmers’ that have access to credit, access to credit constraints and possible ways of improving farmers’ access to credit were investigated. Primary data collected through the administration of questionnaire were analysed using descriptive statistics and probit regression. Results showed that most crop farmers obtained credit mainly for farming and have accessed credit through informal sources, with friends and relatives being the most popular source. Majority of the farmers, who obtained information about credit through phone calls agreed that there were no delays in loan approval. Although, probit regression revealed that the independent variables (gender, age, marital status, education, household size, farm size, membership of cooperatives and farming experience) were not significant in jointly affecting access to credit at all probability levels, however, membership of cooperatives had an individually negative significant relationship with access to credit at the 10% (p

The study aimed to determine the level of adoption of organic fertilizers on vegetable farms in central Jordan. By conducting a statistical analysis of the data collected from the questionnaires collected from a sample of farmers in 2021 distributed to a sample of 368. Data was Analyses using Descriptive Statistics and Regression Analysis. The results showed that the average age of farmers was 46.91 years, their average experience got to 19.58 years, the size of the farm was 16.68 dunms (1000 Sq. m), and the number of family members working on the farm reached 3.5 members, and the average number of years of study was 12.64 years, with an average annual income of 9750 Jordanian dinars.. The results showed that the farmers' adoption rate of using organic fertilizers was within the average level. The probability regression analysis that indicated age and farm size reduced farmers' adoption of organic fertilizers while agricultural education, experience and annual income increased the use of organic fertilizers in the study area. The study recommended the need to conduct awareness training courses for them on organic farming. Extension agents should encourage farmers to participate in adult education and training activities that would improve their skills in using organic fertilizers, in order to increase productivity of vegetable production. [ABSTRACT FROM AUTHOR]

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Bu çalışmada, TÜİK hane halkı bütçe anketlerinden yararlanılarak kadınların işgücüne katılımını belirleyen faktörler araştırılmaktadır. Bebek sahipliği, eğitim durumu, yaş ve hane geliri değişkenleri kullanılarak probit model tahmincileri elde edilmektedir. İktisat teorisinden bilindiği gibi, işgücüne katılım-boş zaman arasındaki bireysel tercihler gelir ve ikame etkisi üzerinden belirlenmektedir. Gelir etkisini tahmininde, “toplam hanenin geliri” değişkeninin kullanılması, ekonometrik açıdan içsellik problemine yol açmaktadır. Bu çerçevede çalışmada geleneksel probit modellerine ek olarak, araç değişken tekniği üzerinden kurulan probit modeli tahmincileri elde edilmektedir. Kadınların işgücüne katılımı üzerinde; bebek sahipliği, yaş ve hane gelirin etkisi negatif iken üniversite mezuniyetinin etkisi pozitiftir.

The article discusses the federal tools to expand the relative (to the regional level) financial capacity of local budgets in Russia’s budgetary system. Local fiscal decentralization is generally viewed as favorable to local and regional economic development. Reversing the trend of diminishing local powers at the regional level enables unique growth-friendly actions inside broader fiscal policy measures. It has been established that the Ministry of Finance has the ability to shape the fiscal incentives of regional peers toward increasing local decentralization The likelihood of regional authorities taking appropriate actions can be increased if the federal intergovernmental policy measures already planned are implemented, specifically, equalization transfers, balancing grants and earmarked transfers (“subsidies”) are expanded, and the mechanisms of their allocation are upgraded. From the methodological perspective, the “share of local budgets in region-wide total collected tax revenues” has been found to be an unreliable indicator of local fiscal decentralization.

Poverty continues to be one of the biggest challenges facing many economies worldwide, and its incidences and intensities are very high in developing economies. This paper utilized the Alkire-Foster (AF) method to compute the multidimensional poverty index (MPI) and analyze the incidence and intensity of multidimensional poverty among urban households in Kenya. The findings indicated that 8.7 % of urban households are multidimensionally deprived in 33.3 % of the selected dimensional indicators. Also, the results showed that over 50 % of urban households are deprived of drinking water and sanitation services. In addition, the findings revealed that higher poverty incidence, intensity, and urban multidimensional poverty exist among female-headed households, old household headships, and households residing in peri-urban regions. The Probit regression analysis indicated that large household size, number of children under five years, household head age, gender, marital status, urban food insecurity, health status, and residing in Malaria endemic zone are significant positive predictors of urban multidimensional poverty. On the other hand, an increase in the number of educated women, owners of insurance coverage, agricultural land, and wealthy and home-owning households is linked to a decline in urban multidimensional poverty. The paper professes that policymakers should cautiously consider household socioeconomic differences while designing poverty alleviation policies., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: No additional relationships. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author.)