Ordinary Least Squares Results Research Articles

Geographically specific associations between county-level socioeconomic and household distress and mortality from drug poisoning, suicide, alcohol, and homicide among working-age adults in the United States

BackgroundMortality rates from drug poisoning, suicide, alcohol, and homicide vary significantly across the United States. This study explores localized relationships (i.e., geographically specific associations) between county-level economic and household distress and mortality rates from these causes among working-age adults (25–64). MethodsMortality data were from the National Vital Statistics System for 2014–2019. County-level socioeconomic distress (poverty, employment, income, education, disability, insurance) and household distress (single-parent, no vehicle, crowded housing, renter occupied) were from the 2009–2013 American Community Survey. We conducted Ordinary Least Squares (OLS) regression to estimate average associations and Geographically Weighted Regression (GWR) to estimate localized spatial associations between county-level distress and working-age mortality. ResultsIn terms of national average associations, OLS results indicate that a one standard deviation increase in socioeconomic distress was associated with an average of 6.1 additional drug poisoning deaths, 3.0 suicides, 2.1 alcohol-induced deaths, and 2.0 homicides per 100,000 population. A one standard deviation increase in household distress was associated with an average of 1.4 additional drug poisonings, 4.7 alcohol-induced deaths, and 1.1 homicides per 100,000 population. However, the GWR results showed that these associations vary substantially across the U.S., with socioeconomic and household distress associated with significantly higher mortality rates in some parts of the U.S than others, significantly lower rates in other parts of the U.S., and no significant associations in others. There were also some areas where distress overlapped to influence multiple causes of death, in a type of compounded disadvantage. ConclusionsSocioeconomic and household distress are significant and substantial predictors of higher rates of drug poisoning mortality, suicide, alcohol-induced deaths, and homicide in specific regions of the U.S. However, these associations are not universal. Understanding the place-level factors that contribute to them can inform geographically tailored strategies to reduce rates from these preventable causes of death in different places.

Strategic Management Accounting on Competitive Advantage

This study investigates the effect of business strategy on strategic management accounting (SMA) and its indirect effect on the competitive advantage of the rice export business in Thailand. A total of 215 major rice export businesses in Thailand in 2022 are chosen as the sample population, and data are collected. The results of the structural equation model (SEM) of the analysis model are found using an index that examines the absolute quality-of-fit measure. Additionally, the results of ordinary least squares (OLS) regression analysis, path coefficients, and hypothesis testing show that business strategy positively affects SMA. In addition, SMA plays a positive and significant role in competitive advantage. As for the theoretical contribution, conceptual SMA is explained by a resource-based view that focuses on resources influence on sustainable performance through competitive advantage. It is hoped that the present study will contribute significantly to the managerial contribution of rice export businesses, as SMA could support organizations in creating a competitive advantage.

The effect among innovative accountant competency, business management efficiency, financial reporting quality, and firm growth

This study aims to examine the effect of innovative accountants' competency on firm growth through the mediating effect of business management efficiency and financial reporting quality, and to examine the effect of innovative accountants' competency on the firm image through the mediating effect of financial reporting quality. A total of 441 accounting directors were chosen as the sample, and the data were collected. The results of the structural equation model (SEM) of the analysis model's fit index of innovative accountant competency are indicated by the index examining the absolute quality of fit measure. Additionally, the results of ordinary least squares (OLS) regression analysis show that innovative accountant competency indirectly impacts firm growth. Business management efficiency and financial reporting quality are mediators of innovative accountant competency-firm growth. Additionally, innovative accountant competency indirectly impacts the firm image. Financial reporting quality is also the mediator of innovative accountant competency-firm image relationships in this study.

PSY 검정을 활용한 지역별 아파트가격 거품과 원인에 대한 분석

This study examines the timing of the boom and bust of bubbles in South Korea’s apartment market by region using the test developed by Phillips et al. (2015a, 2015b). The study also identifies the factors causing housing bubbles using ordinary least squares (OLS) and probit models. The sample covers the period from January 2000 to June 2022, comprising 270 monthly observations. The main results of this study are as follows. First, the generalized sup Augmented Dickey–Fuller test results indicate that housing bubbles partially existed in all five regions. Second, the bubble date stamping shows some differences across regions. Third, OLS results indicate that although housing bubbles are inversely related to the loan-to-deposit ratio (LDR), interest rate (IR), and stock index (SI), they are positively associated with the producer price index (PPI), the exchange rate of US dollar to Korean won (ER), and the total amount of interim payment in the construction sector (TIP). Fourth, probit results suggest that the probability of housing bubbles is influenced by PPI, LDR, IR, SI, ER, and TIP in order of magnitude.

Impact of Demographic Vulnerabilities and Socio-Economic Resilience on Food Insecurity in Pakistan

Despite being an agrarian economy, food insecurity is pervasive in Pakistan. This study examines the impact of multiple dimensions of household vulnerability and socio-economic resilience on food insecurity. The results of ordinary least squares and Logistic regression based on data from Pakistan Standard and Living Measurement Survey (2018–2019) and Food Insecurity Experience Scale showed that vulnerabilities like age and employment dependency, household size, and gender composition play a significant role in food insecurity. The key policy interventions that can prevent households from experiencing food insecurity would be investments in human capital, empowering women, and reduction in rural–urban disparity.

The effects of the limited exhaustibility of knowledge on firm size and the direction of technological change

The new knowledge intensive direction of technological change is magnified at the firm level by the limited exhaustibility of knowledge. This limited exhaustibility triggers cumulability and extensibility for which the larger the firm, the lower the knowledge generation costs from using a larger stock of existing knowledge, and the lower the knowledge exploitation costs related to a larger output based on use of the same piece of knowledge. The consequences for the direction of technological change are twofold. First, the larger the firm size, the larger the share of intangible capital in total capital. Second, the output elasticity of intangible capital increases with the size of the firm. We test our hypotheses on data on US listed companies over the period 1977–2016. The results of ordinary least squares, two-stage least squares and production function estimations confirm our theoretical expectations.

The Effect of Lean Accounting Implementation on Organizational Performance

This study aims to examine the effect of lean accounting implementation on organizational performance through the mediating effect of strategic decision-making and continuous improvement. Five hundred and five executives in the medical device manufacturing industry's organization were chosen as the sample, and the data were collected. The results of the structural equation model (SEM) of the analysis model's fit index of conceptual model are indicated by the index examining the absolute quality of fit measure. Additionally, the results of ordinary least squares (OLS) regression analysis and path coefficients and hypothesis testing show that lean accounting implementation plays a positive, significant role in determining and driving strategic decision-making and continuous improvement. Strategic decision-making and continuous improvement positively affect organizational performance. Therefore, firms with lean manufacturing must focus lean accounting to lead to information for decision making and revenue improvement and to increase the profit for firms.

The effects of drought on stock prices: An industry-specific perspective

In this study, we examine the effect of drought on industry stock prices using a balanced panel of monthly data for 15 industries classified by China Securities Regulatory Commission in 2012. By combining the results of ordinary least squares (OLS) estimation and quantile regression models, we present a comprehensive evaluation of the relationship between drought and industry stock prices. The OLS regression results generally show that drought is negatively correlated with industry stock prices. However, quantile regression reveals that the effect of drought changes from positive to negative from the lowest to the highest stock price quantile. In addition, drought resistance capacity varies by industry. We further use threshold regression to determine the effects of investor sentiment on the relationship between drought and stock prices and identify two different regimes: low sentiment and high sentiment. In the low sentiment regime, drought has a significant negative effect on industry stock prices, while in the high sentiment regime, drought has a significant positive impact on industry stock prices.

Spatial non-stationary characteristics between grass yield and its influencing factors in the Ningxia temperate grasslands based on a mixed geographically weighted regression model

Spatial models are effective in obtaining local details on grassland biomass, and their accuracy has important practical significance for the stable management of grasses and livestock. To this end, the present study utilized measured quadrat data of grass yield across different regions in the main growing season of temperate grasslands in Ningxia of China (August 2020), combined with hydrometeorology, elevation, net primary productivity (NPP), and other auxiliary data over the same period. Accordingly, non-stationary characteristics of the spatial scale, and the effects of influencing factors on grass yield were analyzed using a mixed geographically weighted regression (MGWR) model. The results showed that the model was suitable for correlation analysis. The spatial scale of ratio resident-area index (PRI) was the largest, followed by the digital elevation model, NPP, distance from gully, distance from river, average July rainfall, and daily temperature range; whereas the spatial scales of night light, distance from roads, and relative humidity (RH) were the most limited. All influencing factors maintained positive and negative effects on grass yield, save for the strictly negative effect of RH. The regression results revealed a multiscale differential spatial response regularity of different influencing factors on grass yield. Regression parameters revealed that the results of Ordinary least squares (OLS) (Adjusted R2 = 0.642) and geographically weighted regression (GWR) (Adjusted R2 = 0.797) models were worse than those of MGWR (Adjusted R2 = 0.889) models. Based on the results of the RMSE and radius index, the simulation effect also was MGWR > GWR > OLS models. Ultimately, the MGWR model held the strongest prediction performance (R2 = 0.8306). Spatially, the grass yield was high in the south and west, and low in the north and east of the study area. The results of this study provide a new technical support for rapid and accurate estimation of grassland yield to dynamically adjust grazing decision in the semi-arid loess hilly region.

Appeal to the head and heart: The persuasive effects of medical crowdfunding charitable appeals on willingness to donate

Medical crowdfunding helps low-income patients raise money for medical treatment and has grown tremendously in recent years. The most appropriate messaging strategy for writing charitable appeals to attract donations remains unclear. This study fills this gap by drawing on Aristotle's three modes of persuasion to explore factors affecting willingness to donate to medical crowdfunding projects from three aspects: logos, pathos, and ethos. This study adopted a multi-method approach by conducting two laboratory experiments (N = 125 and N = 123) and a field study (N = 1645). Analysis of variance (ANOVA) in Study 1 showed that high information quality (F = 9.774, p = 0.002) and gain frame (F = 8.620, p = 0.004) have positive effects on the trustworthiness of the project initiator (ethos), which in turn promoting potential donors’ willingness to donate (β = 0.339, p = 0.001). Study 2 confirmed the findings about information quality in Study 1, and further show that there was no significant difference between gain-first and gain-last frame on trustworthiness and willingness to donate (p > 0.05). Then, information quality is further detailed into three sub-dimensions in Study 3: text length, number of images, and number of health-related words. The results of ordinary least squares (OLS) regression with robust standard error indicate that the text length (β = 0.350, p < 0.001) and number of images (β = 0.048, p < 0.001) positively influence donation behavior, but the opposite conclusion yields health-related words (β = -0.027, p < 0.01). This study provides theoretical insights into the role of medical crowdfunding charitable appeals by verifying the persuasion effects of rational, emotional, and credibility appeals. This study also contributes to persuasion theory by highlighting the role of emotional appeals and identifying the mediating impact of credibility appeals in the context of medical crowdfunding. This study also has important practical implications by guiding funders to write persuasive charity appeals that will attract the attention of potential donors.

Prior information in econometric real estate appraisal: a mixed estimation procedure

PurposeThe purpose of this paper is to present how prior knowledge about the impact of real estate features on value might be utilised in the econometric models of real estate appraisal. In these models, price is a dependent variable and real estate features are explanatory variables. Moreover, these kinds of models might support individual and mass appraisals.Design/methodology/approachA mixed estimation procedure was discussed in the research. It enables using sample and prior information in an estimation process. Prior information was provided by real estate experts in the form of parameter intervals. Also, sample information about the prices and features of undeveloped land for low-residential purposes was used. Then, mixed estimation results were compared with ordinary least squares (OLS) outcomes. Finally, the estimated econometric models were assessed with regard to both formal criteria and valuation accuracy.FindingsThe OLS results were unacceptable, mostly because of the low quality of the database, which is often the case on local, undeveloped real estate markets. The mixed results are much more consistent with formal expectations and the real estate valuations are also better for a mixed model. In a mixed model, the impact of each real estate feature could be estimated, even if there is no variability in the sample information. Valuations are also more precise in terms of their consistency with market prices. The mean error (ME) and mean absolute percentage error (MAPE) are lower for a mixed model.Originality/valueThe crucial problem in econometric property valuation is that it involves the unreliability of databases, especially on undeveloped, local markets. The applied mixed estimation procedure might support sample information with prior knowledge, in the form of stochastic restrictions imposed on parameters. Thus, that kind of knowledge might be obtained from real estate experts, practitioners, etc.

Factors affecting the volume of Indonesian CPO exports in international trade

Palm oil is one of the commodities of plantation products that has an important economic role in Indonesia and is also an export commodity as foreign exchange earner for oil and gas. Palm oil produces the main product Crude Palm Oil (CPO). As main product, CPO continues to experience an increase in export volumes in line with the growing need for CPO in export destination countries, both as food raw material and biodiesel. However, when the implementation of the customs policy was issued in 2009, there was a change in the composition of exports from CPO to palm-derived products, namely RBD palm olein and PFAD. The main markets for Indonesian palm oil products are in Asia and Europe, the four largest countries, including India, Malaysia, the Netherlands, and Italy. This research aims to analyze the factors that influence the volume of Indonesian CPO exports in export destination countries. Based on the results of Ordinary Least Square (OLS), the variables that significantly affect Indonesia’s CPO exports in export destination countries are (1) India: export volume lag, (2) Malaysia: soybean oil prices, (3) Netherlands: RCA, and (4) Italy: estimates of sunflower oil, RCA, exchange rates and dummy exit fees.

Variation Comparison of OLS and GLS Estimators using Monte Carlo Simulation of Linear Regression Model with Autoregressive Scheme

In this research we discusses to Ordinary Least Squares and Generalized Least Squares techniques and estimate with First Order Autoregressive scheme from different correlation levels by using simple linear regression model. A comparison has been made between these two methods on the basis of variances results. For the purpose of comparison, we use simulation of Monte Carlo study and the experiment is repeated 5000 times. We use sample sizes 50, 100, 200, 300 and 500, and observe the influence of different sample sizes on the estimators.&#x0D; By comparing variances of OLS and GLS at different values of sample sizes and correlation levels with , we found that variance of ( ) at sample size 500, OLS and GLS gives similar results but at sample size 50 variance of GLS ( ) has minimum values as compared to OLS. So it is clear that variance of GLS ( ) is best. Similarly variance of ( ) from OLS and GLS at sample size 500 and correlation -0.05 with , GLS give minimum value as compared to all other sample sizes and correlations.&#x0D; By comparing overall results of Ordinary Least Squares (OLS) and Generalized Least Squares (GLS), we conclude that in large samples both are gives similar results but small samples GLS is best fitted as compared to OLS.

Annual report readability, agency costs, firm performance: an investigation of Oman's financial sector

PurposeThe readability of annual reports is an important feature that determines the quality of communication between a firm and its stakeholders. Extant literature has demonstrated that readability characteristics of annual reports are crucial in facilitating the investor's ability to process and analyze information, resulting in higher firm performance and lower agency costs. This study examines the relationship between annual report readability, agency costs and the firm performance of listed financial sector companies in Oman.Design/methodology/approachUsing a sample of 150 firm-year observations of listed financial sector companies on the Muscat Securities Market (MSM) over the period 2014 to 2018, a panel regression analysis is used, along with the system generalized method of moments (GMM) estimation to address endogeneity concerns. The readability of annual reports is proxied by the length of the annual report, the Flesch reading ease and the Flesch–Kincaid index.FindingsThe ordinary least squares (OLS) results suggest that readability proxied by the length of the annual report has no significant relationship with agency cost, return on assets (ROA) or stock returns. The OLS results are confirmed through the system GMM estimation model for agency costs, Tobin's Q and stock returns. Easier-to-read annual reports measured by the Flesch reading ease demonstrate high asset utilization ratio and Tobin's Q. These results emphasize Flesch reading ease measure in explaining the economic significance of agency cost and Tobin's Q. In contrast, difficult-to-read annual reports are observed for firms with high ROA.Research limitations/implicationsThe study is limited to the financial sector. Its generalizability could be extended to a similar sector or countries with features similar to Oman. Future studies on readability could be extended to other sectors of Oman, and financial firms with easier-to-read annual reports show a high Tobin's Q, which reflects the confidence of investors in the stock market. These findings may encourage policymakers to regulate the readability features of annual reports and influence the reporting quality of financials and disclosures also including cross-country comparisons.Practical implicationsFinancial firms with easier-to-read annual reports show a high Tobin's Q, which reflects the confidence of investors in the stock market. These findings may encourage policymakers to regulate the readability features of annual reports and influence the reporting quality of financials and disclosures.Originality/valueWhile the study extends prior literature on readability, agency costs and firm performance, it is also one of the first to examine the financial sector of an emerging country, namely, Oman. The study supports the obfuscation hypothesis through the association of readability measure with agency cost. Unlike prior research that has focused on common computational linguistic literature, this study uses three proxies for readability to assess information quality.

Migration drivers, income inequality and rural attachment in deprived remote areas prone to cattle rustling in Nigeria

ABSTRACT While the broader concept of human security emphasizes the need for safety from livelihood security threats, the roles of attachment and violent conflicts on rural migration remain a subject of considerable debate. This study examines the drivers of rural migration within the context of potential relative deprivation. Using data from 1,750 households residing in rural areas of Nigeria, the study reports two key findings. First, the results show that migration is structured by the socio-economic stratification of rural households. Secondly, the results of ordinary least squares reveal that rural attachments, deprivation, cattle rustling and human capital are salient factors determining the patterns of rural migration. It can be argued that cattle rustling, as one of the major security threats affecting pastoral communities, is constraining pastoral households from pursuing their normal livelihoods and thus reducing the raiding of pastoral livelihood assets may help in reducing rural-urban migration in Nigeria.

Lean manufacturing implementation and performance: the role of economic volatility in an emerging economy

PurposeThe purpose of this study is to explore the mediation effect of volatile economic conditions on performance benefits of successful kean manufacturing implementation (LMI). The mediating factor of economic volatility (EV) is constructed based on four macroeconomic dimensions – supplier uncertainty, market demand fluctuations, governmental policy changes and peer competition.Design/methodology/approachAn attempt is made to build an exhaustive list of the internal operational manifests grouped into one human and three technical input factors. Similarly the benefits accrued are collated under two performance measures – customer satisfaction (CS) and organizational goal satisfaction (OGS). Based on data from the Indian manufacturing sector, structural equation modelling (SEM) and ordinary least square (OLS) analyses are carried out to validate the proposed model.FindingsResults of the structural model validate the first six hypotheses posited in the model. Results of OLS further reveal the mediation effect of EV having negative impact on LMI–CS and LMI–OGS nexus.Practical implicationsThis research offers a fair understanding of the internal operational lean factors and the effect of volatile macroeconomic conditions on lean benefits. The structural model will aid the academicians and lean implementers comprehend the dimensional structure underlying the lean practices and beliefs. This work further helps to understand the moderation effect of environmental complexity on the output measures of LMI in the Indian manufacturing sector.Originality/valueThis work is one of the very first empirical analyses of lean performance under contingent economic conditions. The paper presents a valuable recommendation to practitioners for considering the dynamism of external economic environment instead of simply adopting standalone internal lean parameters, if satisfactory levels of performance in terms of CS and OGS are to be achieved.

Who bypasses the Great Firewall in China?

The blockage of foreign Web sites, which is often called the “Great Firewall (GFW)”, serves an important part of the Internet censorship in mainland China. This study investigated the inequality of bypassing the GFW in mainland China, and the possible difference in some “capital-enhancing” uses of the Internet (using the Internet for work, learning and political expression) between GFW-bypassing netizens and those still suffer from strict Internet censorship. This study used data from the China Family Panel Studies (CFPS). Although there is no direct measurement of netizens’ GFW bypassing, a variable measuring the ownership of Facebook accounts was used as a proxy of the status of GFW bypassing. Firstly, the results of bivariate analyses and multiple correspondence analysis (MCA) suggest that mainland Chinese netizens who can bypass Internet censorship and access blocked foreign Web sites are more socio-economically better off (higher social class, well-educated and urban residing) and younger. Moreover, the results of ordinary least squares (OLS) regression and logistic regression models tell that in general bypassing the GFW is related to more activeness in using the Internet for learning and political expression. After controlling socio-economic and demographic characteristics, GFW bypassing is no longer found to be related to online learning, but is still related to an expression of political views online.

Understanding public support for carbon capture and storage policy: The roles of social capital, stakeholder perceptions, and perceived risk/benefit of technology

As climate change mitigation technologies emerge, there is an increased need to understand public support for the technology and the policies that will shape or thwart its evolution. Of particular importance are the communities most directly impacted. The current study focuses on a random sample of 970 adults in eight counties within the oil and gas industry-reliant region of southeast Texas in order to explore support for carbon capture and storage (CCS), which is a climate change mitigation technology that has seen a great deal of investment in that area. Results of ordinary least squares (OLS) regression analysis and general linear modeling (GLM) suggest that policy support –individual support and perceived community support – is dependent on perceived risks and benefits of CCS, community-focused perceptions (including Bourdieu's social capital), and perceptions about stakeholders (trustworthiness and expected role in CCS policy making). One key takeaway is that social capital was both a predictor and moderator in community-level CCS support and helped explain the hidden effects of risk perception of CCS and CCS knowledge on community-level CCS support. Implications for public policy and stakeholder relations are discussed.

AN OWNERSHIP STRUCTURES AND DIVIDEND POLICY: EVIDENCE FROM LISTED PLANTATION COMPANIES IN MALAYSIA

This research analyzes the relationship of ownership structures with dividend policy using a sample of 43 plantation companies listed on Bursa Malaysia from 2013 to 2015. The results of Ordinary Least Square (OLS) find that foreign ownership has a positive and significant influence on dividend policy while state ownership has a negative and significant influence on dividend policy. Furthermore, it also finds that Government Linked Investment Companies (GLICs) ownership has insignificant influence on dividend policy. This study provides evidence to policymakers of government through their GLICs and state in selecting and deciding their dividend policies. Furthermore, it also provides evidence to shareholders and managers that companies with foreign ownership pay higher dividends while companies with state ownership pay lower dividends. This study is the first study that contributes to the finance and corporate governance literature at examining the relationship between GLICs as whole and foreign ownerships with dividend policy in Malaysia.

At home, in public, and in between: gender differences in public, private and transportation pro-environmental behaviors in the US Intermountain West

ABSTRACTResearch in environmental sociology finds differences between men and women in the performance of pro-environmental behaviors, but gender effects change over time, and vary by location and type of pro-environmental behavior. Thus, research needs to explore gender differences in various pro-environmental behaviors across different contexts, in order to contribute to better understanding of the connections between sustainability and gender equity. This paper analyzes the gendered differences in pro-environmental behaviors in the Intermountain West region of the United States using survey data collected in 2016 from five states: Colorado, Idaho, Montana, Utah, and Wyoming. Results of ordinary least squares and ordered logistic regression analyses indicate women are more likely than men to engage in pro-environmental behaviors in the private sphere. Gendered differences are also evident in public pro-environmental behaviors, though results suggest those may be a consequence of higher levels of environmental concern among women. An analysis of transportation behaviors yields mixed results. All three types of behaviors have implications for gender equity.