Results Of Ordinary Least Squares Regression Research Articles

FACTORS AFFECTING LIVESTOCK HERD SIZE IN THE LEPELLE-NKUMPI MUNICIPALITY OF LIMPOPO PROVINCE, SOUTH AFRICA: A CASE OF SMALLHOLDER CATTLE FARMERS

Purpose: This study aimed to investigate factors affecting cattle herd size in the Lepelle-Nkumpi Municipality, Limpopo Province. Method: A proportionate random sampling technique was used and a total of 261 smallholder cattle farmers were selected as participants in this study. Primary data were obtained using a well-structured questionnaire, where the participants were interviewed face to face. The data obtained were captured and analysed using Statistical Package for Social Sciences (SPSS) version 28.0. Descriptive statistics and ordinary least squares (OLS), using a multiple linear regression model, were employed to analyse factors affecting cattle herd size in the study area. Results and conclusion: Descriptive statistics results revealed that the prevailing factors that affect cattle herd size in the study area included the following: draught; practical knowledge; no/lack of; maintenance; water circulation; access to good breeding stock; poor market prices; grazing land; stock theft; insufficient or no breeding stock and pests/parasites. The OLS regression results, derived from a multiple linear regression model, revealed the variables that significantly affected cattle herd size, and this included age, household size, sales per year, livestock keeping, and planted pasture. Most farmers (91.4%) would like to increase their livestock numbers. It was recommended that extension services should be encouraged, training should be provided, and stakeholders should be engaged to help cattle farmers in the study area. Policies aimed at improving livestock production among smallholder farmers should be informed by the factors and determinates found in this study. Value: This study contributes useful information for potential livestock farmers. In addition, the outcome of this study could be used as the basis for informed policy formulation to improve livestock production which will ultimately improve food security status of farmers.

THE IMPACT OF DIGITAL TRANSFORMATION ON ENTREPRENEURIAL ACTIVITY. EMPIRICAL EVIDENCE FROM THE EUROPEAN UNION

The paper explores the impact of digital transformation (DT) on new business creation in the case of European Union member states over the period 2015–2020 by employing several econometric techniques such as Ordinary Least Squares (OLS) and quantile regression (QR). The results of OLS regression indicate a positive and significant link between DT and entrepreneurial activity. However, the quantile regression results highlight a parameter heterogeneity in the effect of DT on entrepreneurial activity. Furthermore, the magnitude of the impact is greater at the higher size quantiles of the new business density distribution. Overall, the empirical findings highlight the key role of DT in developing public policies aimed to spur entrepreneurial activity. Thus, this paper brings significant contributions to the extant literature on the macro determinants of firm creation.

Biomass or LPG? A case study for unraveling cooking fuel choices and motivations of rural users in Maheshkhali Island, Bangladesh

Biomass fuel could effectively address the existing energy crisis in developing countries, including Bangladesh, yet its potential remains largely overlooked in scholarly and policy discussions. The objective of this study was to understand the people's perception of fuelwood, LPG, and cow dung as well as to identify factors influencing the choices of solid cooking fuels and the extent of daily fuelwood consumption in Maheshkhali, a secluded island off the coast of the Bay of Bengal in Bangladesh, characterized by its diverse landscapes. Primary data was collected through a questionnaire survey and focus group discussions and were analyzed using descriptive statistics, binomial logistic regression, and ordinary least squares regression (OLSR) to identify key determinants. Our findings suggest a pronounced preference for biomass fuel, as indicated by the odds ratio and user perceptions grounded in the central capability approach. The OLSR results indicate that cooking time, quantity collection, the number of school-going children, and educational score explain 82.5% of the total variance in fuelwood consumption, making them major driving factors. The household survey revealed a stark reliance on biomass fuel, with 87% of families using it exclusively, while only 4% rely solely on LPG. Fuelwood collection, primarily a task for women and children, also involved men who spent approximately five hours to traverse 1.5 km to collect 23 kg of biomass per trip. The strong biomass preference for fuel, in terms of central capability, underscores the challenges in motivating users to cleaner alternatives like LPG.

Spatial Distribution and Predictors of Vitamin A Deficiency among Infants 6-23 Months in Bungoma and Busia Counties, Kenya

The study determined the prevalence and geospatial distribution of vitamin A deficiency among children aged 6-23 months in Busia and Bungoma counties. Analysis of spatial patterns using spatial indices and geographical visualizations of the presence and absence of significant high and low values of VAD was done. ArcGIS and GeoDa 1.6 were used for spatial analysis. A null hypothesis of spatial randomness was tested at a level of significance α=0.005 against the thought of Spatial Autocorrelation (SA). It was rejected giving a strong evidence of significant spatial patterns of VAD distribution in Bungoma and Busia. Local Indicators of Spatial Association were used to assess levels of local clustering. Regression analysis was conducted to model the most significant prediction equation for a set of 12 covariates. Exploratory Spatial Data Analysis was conducted followed by Ordinary Least Squares Regression (OLSR) on the predictor variables. Dependent variable was VAD while spatial and demographic variables were the independent variables. The results of OLSR were scrutinized by a set test diagnostic for the existence of spatial dependence (Lagrange Multiplier diagnostics). Analysis of Moran’s Index in Bungoma and Busia revealed heavy clustering of High-High (MI≥0.9). Lower parts of Bungoma and Busia showed heavy clustering of Low-Low values of VAD (MI≥0.9). Spatial error model yielded varying levels of coefficients with diverse spatial and non-spatial independent variables at α≤0.005 with a sensitivity of 999 permutations and λ=0.381. OLSR identified length of crop growing period, distance to health facilities and towns as the most significant spatial predictors of VAD.

Determinants of Academic Performance of Accounting Students in Ghana

Purpose: The purpose of this paper is to investigate the determinants of academic performance of accounting students in Ghanaian secondary and tertiary education institutions. Specifically, the study examines whether motivational (expectation and volition) and engagement and commitment (academic interest and learning attitude) factors are related to academic performance. Design/methodology/approach: Data analysis is based on a sample of 500 accounting students enrolled at secondary and tertiary education institutions in Ghana who responded to a 21-item questionnaire. Ordinary Least Squares (OLS) regression analysis was used to determine the relationships between motivational, engagement and commitment factors and academic performance. Findings: The OLS regression results indicate that both secondary and tertiary education institutions accounting students’ academic performances are affected by motivational (expectation and volition) and engagement and commitment (academic interest and learning attitude) factors. However, when the data is analysed separately by level of study, the results indicate that expectation only affects the academic performance of secondary school students while volition only affects the academic performance of tertiary institutions students. The results in respect of engagement and commitment remain the same. Research limitation/implication: The results relate to a particular region of Ghana so cannot be generalised to the rest of the country. The implication of the differences in the effect of expectation and volition on academic performance at secondary and tertiary level suggest that accounting educational stakeholders should institute separate measures at each level relating to these factors to strengthen their effect on academic performance. Originality/value: This study contributes by providing empirical evidence that the influence of motivational factors on academic performance differs by level of study in the context of Ghana and to the best of knowledge no such evidence exists.

Access to Saloons, Wet Voter Turnout, and Statewide Prohibition Referenda, 1907–1919

When explaining the success of the Prohibition movement in the United States between 1900 and 1920, scholars argue that prohibitionists were able both to tap into the distrust of many rural, native-born, evangelical Protestants toward modern urban life and to bring together disparate groups of reformers around one goal: the elimination of the saloon. Furthermore, localized campaigns resulting in the elimination of saloons from many rural areas kept this base of voters energized, ultimately leading to impressive dry turnouts in statewide Prohibition referenda. This study extends and amplifies these findings through an analysis of three sets of factors on voting outcomes: the percentage of various demographic groups (urban, immigrant, and ritualistic religious populations) residing in a county; the distance of each county to saloons; the presence or absence of producers of alcohol in a county. Results of ordinary least-squares regression demonstrate that access to saloons and the percentage of immigrant and ritualistic church members in a county are the variables that most influence the results of Prohibition referenda. Furthermore, unlike what previous research has demonstrated, these variables have their greatest influence by affecting wet turnout rates.

Racial, Ethnic, and Sociodemographic Differences in the Level of Psychosocial Distress among Older Americans

More than 2 million older Americans suffer from some form of depression. Yet late-life depression is often undiagnosed or underdiagnosed. The aim of this study was to explore the reasons for the observed differences in the level of depressive symptoms between older African Americans, Hispanics, and Whites. The data are from Wave 1 of the Asset and Health Dynamics Among the Oldest Old survey administered during 1993-1994. Ordinary least-squares regression results indicate that language acculturation, the number of years of education, and the number of years of U.S. residency are significant factors that help to explain differences in self-reported levels of depressive symptoms among this older population. In general, those who are men, are married, have more education, and are in better health have lower levels of depressive symptoms.