• Title/Summary/Keyword: OLS(Ordinary Least Squares)

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Housing Transaction Prices and Depression Experience Rates According to Housing Types Before and After the COVID-19 Pandemic (코로나19 유행 시기 전후 주택유형에 따른 주택실거래가와 우울감 경험률)

  • Kangjae Lee;Yunyoung Kim;Keonyeop Kim
    • Journal of agricultural medicine and community health
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    • v.49 no.1
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    • pp.59-70
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    • 2024
  • Objectives: This research analyzed and compared housing transaction prices and depression rates according to housing types before and after the COVID-19 pandemic. Methods: Data on housing transaction prices and depression rates from 2018 to 2022 in 25 districts of Seoul, South Korea, were utilized. Dummy variables were employed to account for potential confounders influencing the relationship between the variables. Statistical analysis was conducted using R, and the relationship between depression rates and housing transaction prices was examined through Ordinary Least Squares (OLS) and panel data regression analysis. Results: The results of OLS and one-way random effects models indicated a significant relationship between apartment (p<.05) and officetel (p<.001) transaction prices and depression. However, detached/semi-detached and row/townhouse transaction prices did not exhibit a significant relationship with depression. Conclusion: It was observed that as apartment and officetel transaction prices increased in Seoul before and after the COVID-19 pandemic, depression rates also increased. Considering that changes in housing prices by housing type in South Korea may impact the mental health of local residents, it is deemed necessary to consider healthy housing and housing prices as comprehensive determinants of mental health.

Unbiasedness or Statistical Efficiency: Comparison between One-stage Tobit of MLE and Two-step Tobit of OLS

  • Park, Sun-Young
    • International Journal of Human Ecology
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    • v.4 no.2
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    • pp.77-87
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    • 2003
  • This paper tried to construct statistical and econometric models on the basis of economic theory in order to discuss the issue of statistical efficiency and unbiasedness including the sample selection bias correcting problem. Comparative analytical tool were one stage Tobit of Maximum Likelihood estimation and Heckman's two-step Tobit of Ordinary Least Squares. The results showed that the adequacy of model for the analysis on demand and choice, we believe that there is no big difference in explanatory variables between the first selection model and the second linear probability model. Since the Lambda, the self- selectivity correction factor, in the Type II Tobit is not statistically significant, there is no self-selectivity in the Type II Tobit model, indicating that Type I Tobit model would give us better explanation in the demand for and choice which is less complicated statistical method rather than type II model.

A comparison of neural networks to ols regression in process/quality control applications

  • Nam, Kyungdoo;Sanford, Clive C.;Jayakumar, Maliyakal D.
    • Korean Management Science Review
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    • v.11 no.2
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    • pp.133-146
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    • 1994
  • This study compares the performance of neural networks and ordinary least squares regression with quality-control processes. We examine the applicability of neural networks because they do not require any assumptions regarding either the functional from of the underlying process or the distribution of errors. The coefficient of determination($R^2$), mean absolute deviation(MAD), and the mean squared error(MSE) metrics indicate that neural networks are a viable and can be a superior technique. We also demonstrate that an assessment of the magnitude of the neural notwork input layer cumulative weights can be used to determine the relative importance of predictor variables.

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The Effect of the Minimum Wage on Employment Using Instrumental Variable (도구변수를 이용한 최저임금의 고용효과)

  • Kang, Seungbok
    • Journal of Labour Economics
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    • v.40 no.3
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    • pp.105-131
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    • 2017
  • This study analyses the effect of a minimum wage on employment by using the government's progressiveness as an instrumental variable. The Ordinary Least Squares regression (OLS) can result in upward biased employment effect due to the endogeneity among variables. Therefore, it is necessary to analyse the casuality that removed endogeneity between variables by using proper instrumental variables. The analysis using instrumental variable shows that the growth of the increasing rate of the minimum wage reduces employment. The negative effect of employment depending on the increase of minimum wage corresponds with the predictions of Neoclassical Economics.

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The existence of and deviations from housing consumption norms in the United States (미국의 주거소비규범에 관한 연구)

  • 김경자
    • Journal of the Korean Home Economics Association
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    • v.33 no.3
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    • pp.291-298
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    • 1995
  • 본 연구는 주거소비규범에서의 이탈과 관계된 변수들을 조사하고자 시도되었으며, 이러한 목적을 달성하기 위한 구체적인 연구과제는 다음과 같다. 1. 미국의 각기 다른 가구유형별(가족생활주기 측면에서 구성된) 주거소비규범이 존재하는가\ulcorner 2. 규범보다 높은수준의 주거소비와 관계된 변수는 무엇인가\ulcorner 규범보다 낮은 수준의 주거소비와 관계된 변수는 무엇인가\ulcorner 자료는 미국엣 실시된 1990년도 소비자지출 조사의 인터뷰대상에서 추출된 4,923개의 소비자단위로 연구과제를 해결하기 위해 ordinary least squares(OLS) 중회귀분석방법이 사용되었으며, 본 연구에서 주거소비규범은 다음과 같은 4가지 주거특성, 즉 방수, 주거유형, 침실당 사람수 및 주거소유유형으로 확인되었다. 분석결과, 가구유형 및 크기가 규범이 존재한다고 믿어지는 4가지 주거특성과 유의하게 관련되어 있었으며, 이는 이러한 특성에 대해 규범이 존재한다는 결론을 지지했다. 한편, 다른 많은 가구들이 그들의 가구유형규범과 크기규범에 일치하지 않는 주거에서 살고 있는 것으로 나타났는데, 이러한 이탈은 소득, 가장의 연령 및 성별과 같이 자원제약을 나타내는 변수와 관계되어 있었다. 본 연구의 결과는 왜 인구통계적 변수가 주거 및 다른 소비와 관계 되는지에 대한 이유를 설명할 수 있도록 하는 근거를 제시하고 있으며, 주거소비만족과 주거조정행동의 근거를 이해하는데 적용될 수 있을 것이다.

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Short-Term Load Forecasting Using Multiple Time-Series Model Including Dummy Variables (더미변수(Dummy Variable)를 포함하는 다변수 시계열 모델을 이용한 단기부하예측)

  • 이경훈;김진오
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.52 no.8
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    • pp.450-456
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    • 2003
  • This paper proposes a multiple time-series model with dummy variables for one-hour ahead load forecasting. We used 11 dummy variables that were classified by day characteristics such as day of the week, holiday, and special holiday. Also, model specification and selection of input variables including dummy variables were made by test statistics such as AIC(Akaike Information Criterion) and t-test statistics of each coefficient. OLS (Ordinary Least Squares) method was used for estimation and forecasting. We found out that model specifications for each hour are not identical usually at 30% of optimal significance level, and dummy variables reduce the forecasting error if they are classified properly. The proposed model has much more accurate estimates in forecasting with less MAPE (Mean Absolute Percentage Error).

R&D Intensity and Market Structure (R&D집약도와 시장구조)

  • Kim, Byung-Woo
    • Journal of Technology Innovation
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    • v.12 no.3
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    • pp.97-109
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    • 2004
  • According to "structure-conduct-performance" paradigm in IO, market structure (concentration) determines conduct (R&D investments), and conduct yields market performance (ratio of price to marginal cost). Previous empirical studies on Schumpeter Mark I, II assumed that the explanatory variable (market structure) and the disturbance are uncorrelated in the R&D equation. In this situation, Ordinary Least Squares (OLS) estimates of the structural parameters are inconsistent, because the endogeneous variables (R&D and market structure) can be determined simultaneously. So, in this study, full information (or system methods) estimation is used to test Schumpeter hypothesis since joint estimation can as well bring efficiency gains in the seemingly uncorrelated regressions (SUR) setting.

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Exploring the Spatial Relationships between Environmental Equity and Urban Quality of Life (환경적 형평성과 도시 삶의 질의 공간적 관계에 대한 탐색)

  • Jun, Byong-Woon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.14 no.3
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    • pp.223-235
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    • 2011
  • Although ordinary least squares (OLS) regression analysis can be used to examine the spatial relationships between environmental equity and urban quality of life, this global method may mask the local variations in the relationships between them. These geographical variations can not be captured without using local methods. In this context, this paper explores the spatially varying relationships between environmental equity and urban quality of life across the Atlanta metropolitan area by geographically weighted regression (GWR), a local method. Environmental equity and urban quality of life were quantified with an integrated approach of GIS and remote sensing. Results show that generally, there is a negatively significant relationship between them over the Atlanta metropolitan area. The results also suggest that the relationships between environmental equity and urban quality of life vary significantly over space and the GWR (local) model is a significant improvement on the OLS (global) model for the Atlanta metropolitan area.

Peer Firm Effect on Cooperate Investment Decisions (경쟁 기업이 기업의 투자결정에 미치는 영향 연구)

  • Yang, Insun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.12
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    • pp.611-620
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    • 2016
  • Firms grow in a competitive environment and competition can be a source of corporate growth. In an increasingly global market, companies face increased competition. As such, it is natural that all firms face some degree of risk due to competition. While firms compete for market share, they also imitate competitors in order to minimize risk that accompanies competition. This research attempts to demonstrate the effects of inter-firm competition on investment decisions. Using idiosyncratic equity returns as the instrument variable, this paper uses a two-stage least squares regression, as well as an ordinary least squares (OLS), to identify the influence of peer firms' investment decisions on a firm's own investment strategy. The results confirm that firms show stronger imitative behavior with more intense competition. Also, firms with higher debt ratios show higher peer group influence. This imitative factor provides clues to measure the risk-averseness in investment decisions.

Factors Affecting Job Motivation among Faculty Members: Evidence from Vietnamese Public Universities

  • TRAN, The Tuan;DO, Quang Hung
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.9
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    • pp.603-611
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    • 2020
  • Higher education has long been considered as a means of human resource development in a nation. The faculty member plays a significant role in improving the quality of higher education. It is clear that job satisfaction and motivation have effect on the faculty member's performance. The objective of this study is to investigate the levels and factors affecting lecturers' motivation in Vietnamese public universities. In this study, ordinary least squares (OLS) and exploratory factor analysis (EFA) have been utilized to identify the factors affecting work motivation of lecturers at Vietnamese universities. A questionnaire was administered to a sample of 189 lecturers at different public universities in Vietnam. The finding indicates that seven factors including Work characteristics (WC), Wage and welfare (WW), Social recognition (SR), Peer relationships (PR), Training and promotion opportunities (PO), Leader caring (LC) and Teacher-student interaction and student's attitude (IA) have positive effect on lecturers' work motivation. Among these factors, Teacher-student interaction and student's attitude (IA) has the strongest impact with the coefficient of 0.631 and Peer relationships (PR) has the least impact on work motivation with the coefficient of 0.020. The study findings can facilitate the understanding of how to increase work satisfaction at the universities in Vietnam.