Percent Level Of Significance Research Articles

Water stress affect water relations, photosynthesis and oxidative defense mechanism in wheat (Triticum aestivum L.)

Water stress is a major obstacle to agricultural production, significantly impacting both yield and quality. During the 2017–18 crop year in Shahriar region near Tehran, Iran, known for its dry and cold climate, a study was conducted to examine the influence of different irrigation levels on the quantitative and qualitative characteristics of various wheat cultivars. The experiment involved three irrigation levels: normal irrigation (control), withholding irrigation at the flowering stage, and withholding irrigation at the seed-filling stage as primary factors, with 21 different cultivars as secondary factors. The analysis showed that irrigation, cultivar type, and their interactions had a significant effect on grain yield, proline, total chlorophyll, carbohydrate content in the first and second internodes during flowering and ripening, as well as on SOD, CAT, GPX, MDA, DT, and D-OH-dG levels at a one percent significance level. Withholding irrigation at the flowering stage had a more severe impact compared to the seed-filling stage. The Rakhshan and Sivand cultivars yielded the highest and lowest grain yields under normal irrigation conditions, while the drought-tolerant Ofogh cultivar showed lower yields when irrigation was withheld at the flowering stage. Water stress led to increased proline levels and higher levels of SOD, CAT, MDA, DT, and D-OH-dG in wheat cultivars. The Rakhshan and Sivand cultivars were identified as drought-tolerant in this region.

Rapid assessment of public interest in drought and its likely drivers in South Africa.

The monthly search volumes for drought were extracted from Google® for South Africa using the Keywordsevery-where.com plugin from January 2004 until June 2022. To identify the potential qualitative drivers for such public interest the following data extracted by the plugin were investigated and analysed: the drought-related keywords, the long-tail keywords similar to drought, and the "people also searched for category" from the South African users. The Google Trends monthly score was extracted for South Africa and the Eastern Cape Province, and specific local municipalities/towns/cities in the province. The aim was to assess the relative significance of the drought interest in comparison to public interest in other search terms. The results of the Kruskal-Wallis analyses of variance by ranks showed that there was a statistically significant difference between individual values of the monthly search volumes for drought in South Africa, as a function of time of data extraction (5 percent level of significance; p-value ≤ 4.7 × 10-14). The monthly search volumes increased with time, which is based on the results of the Mann-Kendall test at a 5 percent level of significance (p-value ≤ 0.0092). Analyses of the Google Trends scores indicate that the relative interest in drought in South Africa and the Eastern Cape Province increased with time between January 2004 and June 2022 (the Mann-Kendall test at a 5 percent level of significance; p-value = 0.0011). The population's searches for drought were relatively low when compared to other search terms on Google. Drought adaptation of the South African community could be considered a driver of the Google searches for drought, but it is a marginal topic compared to other topics in Google searches. It might be necessary to increase this significance by investigating the "Google-search patterns for droughts" in the areas of Tshikaro, Mafusini, Cofimvaba, and Nxotsheni in the Eastern Cape Province of South Africa.

INFLUENCE OF SCHOOL ENVIRONMENT ON INCLUSION OF LEARNERS WITH VISUAL IMPAIRMENT IN REGULAR PUBLIC PRIMARY SCHOOLS IN NYATIKE SUB-COUNTY, MIGORI COUNTY, KENYA

Inclusion of learners with disability is necessary for improving their enrolment and ensuring that their academic goals and objectives are met. Consequently, teachers and stakeholders have to identify any barriers that can deter the learners from achieving these goals. Interestingly, in Nyatike Sub-County, enrolment of learners with visual impairment in regular public primary schools has remained low at 10.1 percent compared to 33.6 percent in Suna East Sub-County, 24.8 percent in Suna West Sub-County and 31.5 percent in Uriri Sub-County for the years 2019 to 2023. Besides, the literacy level of learners with visual impairment is lower than the levels of learners with hearing and intellectual impairment in Nyatike Sub-County. Therefore, the study sought to find out the influence of the school environment on the inclusion of visually impaired learners in regular public primary schools in Nyatike Sub-County. Maslow’s hierarchy of needs theory was used to explain the roots of inclusion. A sample size of 98 (ninety-eight) respondents comprising 46 head teachers and 52 classroom teachers was selected using saturated and purposive sampling techniques. Pearson’s correlation, regression analysis,and ANOVA were used to analyse infferential data while qualitative data was transcribed and analyzed based on emerging themes and used for triangulation. The study established that at a 5 percent level of significance; the school environment significantly influenced the inclusion of learners with visual impairment, and accounted for 18.4% of the variation in inclusion of learners with visual impairment in regular primary schools. From the findings, it was concluded that the school environment (r= .433, p< .05) has a significant positive and moderate influence on the inclusion of visually impaired learners in regular public primary schools in Nyatike Sub-County, Migori County, Kenya. The study recommends that school administration mobilize more teaching and learning resources for learners with visual impairment. The study is significant to policymakers in the educational sector to develop a framework that links the inclusion of learners with visual impairment and their success in educational achievement.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/lit/0758/a.php" alt="Hit counter" /></p>

Asymmetric effect of environment tax and spending on CO2 emissions of European Union.

This study investigates the effects of environmental tax and environmental spending on CO2 emissions of 27 countries of the European Union EU27 countries using annual time series data from 1995 to 2022. The study used linear and non-linear autoregressive distributive lag (ARDL and NARDL) to examine the relationship. Estimates claim that the variables have a symmetric and asymmetric long-term and short-term relationship. The negative impacts of environmental taxes on CO2 emissions prove that emissions are reduced when polluting activities are taxed. Fiscal policy instrument such as taxation changes the behaviour of the private sector in the EU27 nations by disincentivizing polluting activities. On the other hand, government investment in environmental protection has encouraged the private sector in the EU27 nations to embrace and invest in green technologies, decreasing CO2 emissions. The ECM term is negative and statistically significant at a 1 percent significance level for ARDL and NARDL models, implying a stable long-run relationship between variables. It demonstrates that short-run disequilibrium converges to long-run equilibrium at a speed of 9.2% (in the ARDL model) and 22.7% (in the NARDL model). The study also sheds fresh light on the effectiveness of environmental taxes vs. expenditure, where taxes serve as a counter-incentive policy for CO2 emissions, and spending is a positive policy intervention.

Impact of Domestic Investment on Economic Growth in Nigeria

This study investigated the impact of domestic investment on economic growth in Nigeria from the period 1990 to 2022. The dimensions that were used to proxy the independent variable are domestic investment, total exports, interest rate and inflation while real gross domestic product was used to proxy economic growth which is the dependent variable. Data used were sourced from secondary sources which includes; World Bank development indicators for various years and the Central Bank of Nigeria annual statistical bulletin. The Statistical Software employed to analyse the data was the eviews9. The results of the Unit root test show that domestic investment, total exports, interest rate and real gross domestic variables evaluated are all stationary after first difference- I(1)- while inflation rate was stationary at level- I(0)-. The Autoregressive distributed lag was used to analyze data. The results of the Autoregressive distributed lag estimates reveal that in both the long run and short run, domestic investment, total exports, coefficients have positive impact on real gross domestic product in Nigeria and both are also statistically significant at five percent level of significance in the long-run in Nigeria. Since it was found that increase domestic investment and total exports bring about economic growth, the study therefore, recommends amongst others that appropriate trade policies in favour of export expansion should be encouraged. The federal government of Nigeria should make concerted effort towards export promotion policy by encouraging domestic investors to go into more production. In order to achieve this, there is need for the government to reduce interest rate and tax rate.

Police Organisational Behaviour and the Trend of Criminal Activities in Rivers State Nigeria

This study was carried out to investigate the extent to which the Nigeria Police Force (NPF) organizational behavior has reduced the trend of criminal activities in Rivers State. A descriptive survey research method of correlational research design was employed in this study to provide detailed investigation of the procedure used to establish the relationship between the Nigeria police force organizational behavior and the trend of criminal activities in Rivers State. The population of the study was 193,392,500 persons consisting of residents drawn from the cities and rural communities in Rivers State. A sample size of 400 respondents was determined, using Taro Yamene’s sample size techniques at 0.5 percent level of significance. A purposive sampling technique was adopted using a considerable percentage representation approach to ensure effective selection of the representative sample elements of the population from respondents who have adequate knowledge of the study under investigation. A structured instrument for data collection containing twenty (20) item questions was used for the study. The face and content validation of the instrument was obtained through the judgment of experts. A test-retest method was used to determine the reliability of the instrument and a reliability index of .83 was obtained. The data collected were analyzed using the descriptive statistics involving the mean score test and the percentage test method to answer the research questions, while the Z-score test of the inferential statistics method was used to test the hypothesized variables at .05 level of significance. The results obtained revealed that “Nigeria Police Force organizational behavior does not significantly reduce the trend of criminal activities in Rivers State.” The implication of the finding is that the discovered weakness of the Nigeria police force organizational behavior is that it lacks the needed proactive ethical improvement value to carry out its responsible assignments as an organization. Consequently, increasing the level of police compromise with many related criminal activities is considered mephitic enough to uplift or expand the trend of criminal activities in the state if more punitive measures are not employed by the government. It was therefore advisable that the federal government should employ legal assessor that will be used to form “Police Behavioral Monitoring Task Force (PBMT)” in every local government areas to oversee or monitor unethical and irresponsible behaviors of the Nigeria police officers in each state to curtail or curb police dysfunctional involvement in criminal related practices.

Assessing risk factors for malnutrition among women in Bangladesh and forecasting malnutrition using machine learning approaches

BackgroundThis paper presents an in-depth examination of malnutrition in women in Bangladesh. Malnutrition in women is a major public health issue related to different diseases and has negative repercussions for children, such as premature birth, decreased infection resistance, and an increased risk of death. Moreover, malnutrition is a severe problem in Bangladesh. Data from the Bangladesh Demographic Health Survey (BDHS) conducted in 2017-18 was used to identify risk factors for malnourished women and to create a machine learning-based strategy to detect their nutritional status.MethodsA total of 17022 women participants are taken to conduct the research. All the participants are from different regions and different ages. A chi-square test with a five percent significance level is used to identify possible risk variables for malnutrition in women and six machine learning-based classifiers (Naïve Bayes, two types of Decision Tree, Logistic Regression, Random Forest, and Gradient Boosting Machine) were used to predict the malnutrition of women. The models are being evaluated using different parameters like accuracy, sensitivity, specificity, positive predictive value, negative predictive value, F1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$F_1$$\\end{document} score, and area under the curve (AUC).ResultsDescriptive data showed that 45% of the population studied were malnourished women, and the chi-square test illustrated that all fourteen variables are significantly associated with malnutrition in women and among them, age and wealth index had the most influence on their nutritional status, while water source had the least impact. Random Forest had an accuracy of 60% and 60.2% for training and test data sets, respectively. CART and Gradient Boosting Machine also had close accuracy like Random Forest but based on other performance metrics such as kappa and F1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$F_1$$\\end{document} scores Random Forest got the highest rank among others. Also, it had the highest accuracy and F1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$F_1$$\\end{document} scores in k-fold validation along with the highest AUC (0.604).ConclusionThe Random Forest (RF) approach is a reasonably superior machine learning-based algorithm for forecasting women’s nutritional status in Bangladesh in comparison to other ML algorithms investigated in this work. The suggested approach will aid in forecasting which women are at high susceptibility to malnutrition, hence decreasing the strain on the healthcare system.

Health and Infrastructural Security of Rural Households for Sustainable Livelihood: A Study in Bundelkhand Region of India

Poor health tends to be critical for marginal and small farmers who work in their own field and cannot afford to hire an alternative farmer during the time of illness. The research was conducted to assess the health and infrastructural status of farm households. The present study purposefully conducted in Bundelkhand.From each selected village a list of dairy farmers based on land holding was prepared and respondents were selected based on proportionate stratified random sampling method. Data were gathered through personal interview method with the help of the structured interview schedule. The collected data were quantified and analyzed. After data collection, the results were analyzed by using some statistical tools like percentage analysis, correlation and regression. Results revealed that among the marginal farmers the majority (59.26%) of the respondents had low health security, followed by medium and high health security i.e. 32.10 and 8.64 percent respectively. The variables such as annual income and milk production had positive and highly significant relationship with health security at the 1 percent level of significance. This shows that as the value of the annual income and milk production increases the health security of the respondents also increases. The results showed that 58.20 percent variability towards infrastructural security was due to explained or undertaken variables included in the study and the remaining was due to some other factors. The fitted regression model was observed to be significant at the 1 percent level of significance. It can be concluded that there is a need to stress upon improving their overall health and infrastructural security.

Resources Allocation as an Institutional Determinant of Strategic Plan Implementation in Public Secondary Schools in Kenya.

The study sought to examine the influence of school resource allocation on Strategic plan implementation. The study used a descriptive survey research design. The study targeted 351 public secondary schools, 351 public school principals, 1,404 class teachers and 1,755 academic Heads of Departments from which the sample of 105 principals, 176 academic Heads of Departments and 140 class teachers were derived. The respondents were sampled using stratified sampling technique. A questionnaire and an interview guide were the data collection instruments. Descriptive and inferential statistics were used to analyze data. Data was presented by used of frequency distribution tables and pie charts. Pearson’s product moment correlation coefficient and multiple linear regression was used to analyze the inferential data. The set level of hypothesis testing was at 0.05 level of significance. This may be significant to the school Board of Management policy makers in terms of know-how skills formulation, implementation and evaluation of strategic plan. This study found that resource allocation does not influence strategic plan implementation. Based on these findings, the study recommends that; the Government need to provide enough funds at the right time to finance the implementation of the schools’ strategic plan and to ensure schools have enough physical resources, enough human resources, and adequate learning resources. The researcher conducted Hypothesis testing using a multiple regression model at the 5 percent level of significance. The results of hypothesis testing gave a negative coefficient of -0.0168 on resource allocation was realized with a p-value of 0.714 which was not statistically significant at the 0.05 level. . Hence we fail to reject the hypothesis that, resource allocation has no effect on strategic plan implementation. This indicates that, resource allocation does not have a statistically significant effect on strategic plan implementation in public secondary schools in Machakos County.

Exploring Antenatal Health Care Service Utilization in Nepal: A Comprehensive Analysis

The utilization of maternal health care is one of the important factors in reducing the incidence of maternal mortality. Studies in Nepal and in developing countries shows that various demographic, socio-economic and economic factors are associated with ANC service utilization. The main objective of this study is to identify and examine socio-demographic and economic factors affecting antenatal healthcare service utilization in Nepal. This study used data from the Nepal Demographic and Health Survey 2016 and analyzed the data using logistic regression analysis. This research analyzes ANC (antenatal care) concerning dependent variables: age, birth order, religion, ethnicity, educational attainment, province, residence, and wealth indices. Maternal health has been receiving increased attention in the global health, development, and human rights agenda, representing a priority area for accelerating progress on the SDGs and sustaining the gains of the MDGs. Bivariate analysis was conducted for all variables, and some of them were statistically significant at the 5 percent significance level (since p < 0.05). The dichotomous use of modern maternal healthcare utilization, namely whether a woman utilized maternal health care or not, employed dichotomous logistic regression to determine which factors best explain and predict the outcome of maternal health care utilization during pregnancy. A positive estimated value indicates that the odds favor the event and the event is likely to occur, while a negative value indicates that the event is not likely to occur. ANC visits of women decrease with birth order. Based on empirical results, the major factors for ANC services were income, awareness, access to health care services, and birth order attended. The level of awareness among women about the utilization of maternal healthcare in the study area was low. Maternal healthcare service utilization differed across various components of maternity. It would be better to increase awareness about the utilization of modern maternal healthcare for mothers and improve access to healthcare services in their villages to minimize transportation costs and waiting times from the government's side, thus increasing the utilization of maternal health care services in Nepal.

Trade Openness and Economic Growth of Nepal: An Econometric Analysis

Background: The relationship between trade openness and economic growth has been a subject of empirical investigation- a multifaceted and evolving issue in the context of Nepal which is a highly import-based economy. In this background, the results of the exploration of the relationship between trade openness and economic growth would be relevant to suggest that policymakers in adopting the policies and boosting the available capital and labour to attain the benefits of trade openness. Objectives: This study examines the impact of trade openness on the economic growth of Nepal considering GDP, human capital, real gross capital formation, and trade openness employing both descriptive and econometric methods. Methods: This study incorporated the annual time series data published by the government of Nepal from the year 1990 to 2021 and analyzed employing the vector error correction model (VECM) along with the descriptive analysis. Results: Descriptive statistics reveal that the model follows a normal distribution, as indicated by the results of JarqueBera, where the p-values of the variables exceed 0.05. The variables demonstrate stationary at the first order and are cointegrated as such vector error correction model (VECM) is employed. The presence of a negative and significant error correction term (ECT) indicates that the variables are adjusting towards long run equilibrium. Furthermore, the stability of the model is confirmed by the cumulative sum (CUSUM) test as the residual plots remain within acceptable boundaries of a 5 percent significance level. Finally, the results indicate that trade openness does not have a significant and pivotal influence on economic growth. Conclusion: Trade openness does not have a significant influence on economic growth. Capital has a significant and positive relationship with stimulating economic growth, however, human capital has a significant but negative relationship with economic growth in the long run in Nepal.

Impact of Debt on the Economic Growth of Nepal

Public debt and Economic growth have always been the major topic of discussion in the Nepalese economy. Nepal, an underdeveloped country, is always trying to take a leap towards development but both external debt and domestic debt have been the major challenging tasks to perform in the economy. This study has empirically explored the relationship between foreign debt, internal debt and economic growth in Nepal. The time series data for the period of 1975-2021 AD has been applied. Unit root test with Augmented Dickey Fuller (ADF) model has been used to test data stationarity. The result of Autoregressive Distributed Lag (ARDL) model shows that internal debt has positive relationship with GDP whereas foreign debt has negative relationship with GDP. Toda-Yamamoto causality test method has been applied because of the non -stationarity of the data at level. The stationarity of data was seen only at first difference and second difference. Toda-Yamamoto Causality Test found the casual relationship between foreign debt, internal debt and economic growth in Nepal. The test is set at 5 percent level of significance. According to the results of the study, foreign debt and internal debt have unilateral relationship with GDP i.e. economic growth. This study shows there is long-run unidirectional causal relationship between foreign debt to GDP and also between internal debt to GDP in Nepal.

Impact of environmental fiscal reforms on carbon emissions of EURO-4 countries: CS-NARDL approach

This study investigates the effects of the Environmental Fiscal Reforms (EFR) policy on carbon emissions of the top 4 economies of Europe, using annual time series data from 1995 to 2022. The study used a cross-sectional nonlinear autoregressive distributed lag (CS-NARDL) model to examine the relationship. Estimates claim that the variables have an asymmetric long-term and short-term relationship. The negative impacts of carbon taxes on carbon emissions prove that emissions are reduced when polluting activities are taxed. Fiscal policy instrument such as taxation changes the behaviour of the private sector by disincentivizing polluting activities. On the other hand, government expenditure on environmental protection encourages the private sector to embrace and invest in green technologies, decreasing carbon emissions. The ECM term is negative and statistically significant at a 1 percent significance level for CS-NARDL model, implying a stable long-run relationship between variables. It demonstrates that short-run disequilibrium converges to long-run equilibrium at a speed of 47.2 percent. The study also propels new insight into the effectiveness of EFR policy, showing that taxes act as a counter-incentive and expenditure as a positive policy intervention for reducing carbon emissions. EURO-4 countries set an example for policymakers worldwide by rebalancing their energy mix and expanding the use of cleaner alternative energy sources.

The Effect of Environmental and Ergonomic Stimuli of the Work Environment on Employees’ Behavior by the Mediating Role of General Health

Objectives: Considering the importance of employees' behavior in service organizations and its significant impact on their success and failure, the present study investigates the environmental and ergonomic factors affecting the mental health and behavior of employees in one of the branches of Islamic Azad University.
 Methods: The present study is applied in terms of purpose and descriptive-correlational in terms of data gathering and analysis. The statistical population of the study includes: 315 employees of Rasht Branch of Azad University, out of them 196 people were selected by random sampling method and the necessary data were collected using a questionnaire. Structural equation modeling and SMART PLS3 software were used to test the hypotheses.
 Results: According to the findings, workplace layout affects on use of work equipment (0.389), use of office chair (0.252) and environmental conditions (0.538), but the effect of workplace layout on the posture of employees was not confirmed in 5 percent significance level. Also, the effect of posture (0.586), layout (0.440), work equipment (0.458), office chair (0.345) and environmental conditions (0.550) on public health and also the effect of general health (0.690) and environmental conditions (0.158) on employees’ behavior is significant. Examining the indirect relationships of the research model also shows that workplace layout affects employee behavior through the general health and environmental conditions. Workplace layout influences employees’ behavior through work equipment, office chair, environment conditions and general health.
 Conclusion: The indirect effect of workplace layout on employees’ behavior through public health has the highest impact (0.304), therefore, making policies for the general health, can improve employees’ behavior.

PTSD Symptom Severity and Overall Quality of Life Pre-and During COVID-19 Among Adults Seeking Housing Support Services

COVID-19 stay-at-home orders have had far-reaching negative consequences on mental health and quality of life (QOL). This is especially true for vulnerable populations, such as those who are unhoused, as they are more likely than the general population to have been struggling with a mental illness and poor QOL well before the pandemic. This exploratory cross-sectional study explored differences in PTSD symptom severity and overall QOL among a cohort of adults who were seeking housing support services pre-COVID-19 (n = 226 compared to a cohort of adults who were seeking housing support services during COVID-19 (n =205). All data were collected upon enrollment into a permanent supportive housing program. Participants seeking housing support services during COVID-19 compared to pre-COVID-19 were significantly more likely to report higher PTSD symptoms (t=3.14, p=0.001) and poorer QOL (=9.81, p=0.001), however differences were no longer observed at the five percent significance level once several covariates were controlled for in the analysis. Despite the lack of statistical significance at the multivariate level (which is likely a result of challenges with the data and the level of statistical significance selected and not a reflection of true differences between the cohorts), the clinical significance of the findings has implications for planning behavioral health services for unhoused individuals seeking housing support services, especially as we exit the pandemic.

Analysis of Educational and Institutional Security among Dairy Farmers in Bundelkhand Region, India

Education plays an important role in the modernized farm environment rather than the traditional one. The ability of farmers to deal with disequilibrium produced by the use of modern technologies is primarily determined by their education. Based on a thorough examination of the literature and discussions with extension professionals, an index was developed to assess the educational and institutional security of dairy farmers. Data were gathered through personal interview method with the help of the structured interview schedule. After the collection of data, the results were analyzed by using some statistical tools like percentage analysis, correlation and regression. The majority (>75%) of the respondents among medium farmers had a low to medium level of institutional security, whereas among large farmers the majority (53.34%) of the respondents had a high level of institutional security. Education, land holding, annual income and mass media exposure had positive and highly significant relationship with educational security at the 1 percent level of significance. The beta coefficient and their corresponding value indicate varying level of contribution towards dependent variable under the study. When the data was put into a regression analysis for asserting the R2 value, then it was found that they were cumulatively responsible for accounting 53.90 percent variability towards dependent variable i.e. educational security. The fitted regression model was observed to be significant at 1 percent level of significance. The variables education, social participation and annual income were found to be highly significant (p<0.01) while, experience in dairying, land holding and extension contact was found to be significant (p<0.05).

SOCIAL MEDIA AND ENTREPRENEURSHIP DEVELOPMENT NEXUS IN BENUE STATE NIGERIA: EVIDENCE FROM A BINARY LOGISTIC REGRESSION MODEL

This study carried out an analysis of social media and entrepreneurship development nexus in Benue State. The researcher used mainly primary data from a sample of three hundred entrepreneurs in Zone A, B & C in Benue State Nigeria. The primary data was obtained using a structured questionnaire. The data collected were analyzed using logit regression to establish the relationship between social media and entrepreneurship development while principal component analysis was used to identify the most important factors that affects the use of social media in entrepreneurship development. The result of the binary logistic regression analysis indicates that Social Media added significantly to the model/prediction. This means that the logistic model was statistically significant at 5 percent level of significance. Increasing the use of social media was associated with an increased likelihood of entrepreneurship development in Benue State. The logistic regression model was statistically significant, using values from the Omnibus Test of Model Coefficient. The model explained of the variance in post harvest losses of orange in the studied areas and correctly classified of cases. Use of social media was 0.018 times more likely to bring about entrepreneurship development in the studied areas. It was concluded that social media have a positive and significant effect on entrepreneurship development in Benue State Nigeria. It was recommended among others that entrepreneurs in the study area should engage more qualified personnel who can create the right content needed to engage the diverse customers of the business. When this is done, the likelihood of the use of social media in bringing about entrepreneurship development in Benue State can be increased.

Determinants of the food insecurity at household level in Pakistan: A multilevel model approach.

Food insecurity is a major concern for the developing world and around 37% of the population of Pakistan is food insecure. This paper utilizes the Food Insecurity Experience Scale (FIES) to assess the population prevalence of food insecurity and to identify their risk factors and determinants at the household level in Pakistan. This study employs a multi-level random coefficient model, using the Pakistan Panel Household Survey (PPHS-2010) dataset; representative data from 4,130 households. Factors like; income of the household, gender, education, household size, land ownership, and shocks of food insecurity allow the incidence of idiosyncratic shocks (injuries and/or casualties) at the community level, which affects the food insecurity situation of the community, rather differently were included. The study confirms a statistically significant inverse relationship between household income, household size, and household head education with food insecurity and a positive association of shocks and inflation with food insecurity at the household level. Specifically, with increasing per capita income of the household, food insecurity declines (coefficient: -0.083, statistically significant at 1%) and food insecurity increases with shocks (coefficient: 0.058, statistically significant at 1% significance level). The study also reveals a significant heterogeneity at a one percent significance level in the determinants of food insecurity at the district, community, and household levels. The income of the household, household head gender and education level, household size, household assets, shocks, injuries, and inflationary pressure are important determinants of food insecurity in Pakistan.

Government policy interventions during COVID-19 pandemic and economic performance

This paper examines the impacts of government policy interventions during COVID-19 pandemic on economic performance. The study pooled daily data from 108 countries across 5 regions based on World Bank classification from March 22, 2020 to July 31, 2020. These regions are East Asia and Pacific; Europe and Central Asia; Latin America and the Caribbean; Middle East and North Africa as well as sub-Saharan Africa. The study employs Autoregressive Distributed Lagged (ARDL) model. This study uses STATA 15.0 to estimate error correction-based Pooled Mean Group (PMG), Mean Group (MG) and Dynamic Fixed Effect (DFE) model for analyzing dynamic heterogeneous panel data. The empirical result from each region of the World is as follows: (1) Result from PMG on East Asia and Pacific region reveals that government policy of debt/contract relief towards cushioning the effects of COVID-19 pandemic has positive impact on economic performance in the short run while none of the government policy measure is statistically significant in the long run. (2) Result from MG on Europe and Central Asia shows that in both the long run and the short run, number of confirmed cases and school closure policy have negative impacts on economic performance and statistically significant at 1 percent level while in the long run, international travel control and public information campaign have negative and positive impacts on economic performance in the region respectively. Both International travel control and public information campaign are statistically significant at 1 percent and 10 percent levels respectively. (3) Result from PMG on Latin America and the Caribbean shows that the number of confirmed cases and debt/contract relief are statistically significant and have negative and positive impacts on economic performance respectively in the short run. The former is statistically significant at 5 percent level while the latter is statistically significant at 10 percent level. In the long run however, only international travel control imposed by government is significant at 5 percent level and has negative impact on economic performance in the region. (4) Result from PMG on Middle East and North Africa shows that only number of confirmed cases is significant and has positive impact on economic performance at 10 percent level in the short run. No robust impacts is found in the long run. (5) Result from PMG on sub-Saharan African region shows that number of confirmed cases has positive impact, which is statistically significant at 10 percent level on economic performance while in the long run, income support package has negative impact on economic performance at 5 percent level of significance. The study therefore, concludes that, the relative economic potency and effectiveness of government interventionist policy measures towards putting COVID-19 pandemic under control vary across regions of the world. Economically, Europe and Central Asia is the region that is worst hit by the pandemic when compared with other regions.

ANALISIS PENGARUH PROFITABILITAS, LIKUIDITAS, KEBIJAKAN DIVIDEN, DAN KEPUTUSAN INVESTASI TERHADAP NILAI PERUSAHAAN PADA PERUSAHAAN SEKTOR INDUSTRI FARMASI DI BURSA EFEK INDONESIA

Firm worth can be deciphered as market esteem or describes the condition and financial performance of a company, besides that company value is an indicator to be thought about by investors in making decisions. As a predictive model for company value, This research aims to ascertain how the pharmaceutical industry's IDX firm value (PBV) is affected by profitability (ROA), liquidity (CR), dividend policy (DPR), and investment decision (PER). The time period that was used for the research was five years 2017-2021. The method of research that will be Multiple Linear Regression Analysis is used in this study. with the SPSS 21 program with a 5 percent significance level. This study found that profitability has no significant impact on company value, that liquidity has no impact on company value, that dividend policy has no impact on company value, and that investment decisions have an impact on company value.