• Title/Summary/Keyword: Seemingly unrelated regression models

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Application of covariance adjustment to seemingly unrelated multivariate regressions

  • Wang, Lichun;Pettit, Lawrence
    • Communications for Statistical Applications and Methods
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    • v.25 no.6
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    • pp.577-590
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    • 2018
  • Employing the covariance adjustment technique, we show that in the system of two seemingly unrelated multivariate regressions the estimator of regression coefficients can be expressed as a matrix power series, and conclude that the matrix series only has a unique simpler form. In the case that the covariance matrix of the system is unknown, we define a two-stage estimator for the regression coefficients which is shown to be unique and unbiased. Numerical simulations are also presented to illustrate its superiority over the ordinary least square estimator. Also, as an example we apply our results to the seemingly unrelated growth curve models.

Tree Size Distribution Modelling: Moving from Complexity to Finite Mixture

  • Ogana, Friday Nwabueze;Chukwu, Onyekachi;Ajayi, Samuel
    • Journal of Forest and Environmental Science
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    • v.36 no.1
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    • pp.7-16
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    • 2020
  • Tree size distribution modelling is an integral part of forest management. Most distribution yield systems rely on some flexible probability models. In this study, a simple finite mixture of two components two-parameter Weibull distribution was compared with complex four-parameter distributions in terms of their fitness to predict tree size distribution of teak (Tectona grandis Linn f) plantations. Also, a system of equation was developed using Seemingly Unrelated Regression wherein the size distributions of the stand were predicted. Generalized beta, Johnson's SB, Logit-Logistic and generalized Weibull distributions were the four-parameter distributions considered. The Kolmogorov-Smirnov test and negative log-likelihood value were used to assess the distributions. The results show that the simple finite mixture outperformed the four-parameter distributions especially in stands that are bimodal and heavily skewed. Twelve models were developed in the system of equation-one for predicting mean diameter, seven for predicting percentiles and four for predicting the parameters of the finite mixture distribution. Predictions from the system of equation are reasonable and compare well with observed distributions of the stand. This simplified mixture would allow for wider application in distribution modelling and can also be integrated as component model in stand density management diagram.

An Analysis of the Impact of National Fishing Port Investment on Fisheries Disaster Damage by Typhoons (국가어항 투자가 태풍으로 인한 수산재해피해에 미치는 영향 분석)

  • Kim, Eun-Ji;Bae, Hyeon-Jeong
    • The Journal of Fisheries Business Administration
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    • v.53 no.1
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    • pp.73-84
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    • 2022
  • The purpose of this study is the impact of national fishing port investment and typhoons on fisheries disaster damage. The dependent variables were the amount of damage to fishing ports, fishing boats, fisheries enhancement, external facilities, mooring facilities, functional facilities, fishing port and typhoons. The analysis period is from 2002 to 2018. Since the error term is in a simultaneous correlation, it was efficiently estimated by analyzing it with a seemingly unrelated regression (SUR) method. As a result of the analysis, external facilities have not significance to all models. Investing in mooring facilities increased the amount of damage to fishing ports for five years. Investing in functional facilities reduced the amount of damage to fishing ports and aquaculture over five years. Typhoons have significance to all models, and the amount of damage increased every time a typhoon occurred. Based on these results, as the influence of typhoons increases, it seems necessary to establish preventive measures. Timely investment and maintenance to enable the role and function of national fishing ports are considered important.

An Econometric Analysis of Imported Softwood Log Markets in South Korea - on the Basis of the Lagged Dependent Variable -

  • Park, Yong Bae;Youn, Yeo-Chang
    • Journal of Korean Society of Forest Science
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    • v.98 no.2
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    • pp.148-155
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    • 2009
  • The objective of this study is to know market structures of softwood logs being imported to South Korea from log producing countries. Import demand of softwood logs imported to South Korea from America, New Zealand and Chile is fixed as a function of log prices, the lagged dependent variable and output. On the basis of the adaptive expectations model, linear regression models that the explanatory variables included and the lagged dependent variable were estimated by Seemingly Unrelated Regression Equations (SURE). The short-run and long-run own price elasticity of America's softwood log import demand is -1.738 and -4.250 respectively. Then long-run elasticity is much higher than short-run elasticity. Short-run and long-run crosselasticity of New Zealand's softwood log import demand with respect to American's softwood log import price are inelastic at 0.505 and 0.883 respectively. Short-run and long-run cross-elasticity of Chile's softwood log import demands with respect to American's softwood log import prices were highly elastic at 2.442 and 4.462 respectively. Long-run elasticity was almost twice as high as short-run elasticity.

Study on Temporal Comparison Analysis of Factors to Affect Travel Time Budget: A Case for Seoul (통행시간예산에 미치는 요인의 시계열적 비교·분석 연구: 서울시를 사례로)

  • Lee, Hyangsook;Choo, Sangho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.6
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    • pp.180-191
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    • 2020
  • This study analyzes factors that affect average daily travel time budgets, using the Time Use Survey data from 1999 to 2014 in Seoul. We first developed multivariate regression models for travel time from each year, considering demographic and socio-economic variables as well as non-home activity time. The model results showed that household and personal characteristics and non-home activities significantly affect travel time, and their effects are different over time. In addition, we developed seemingly unrelated regression (SUR) models for time allocation for non-home activity and travel, considering their correlations, and explanatory variables were compared over time. Overall, demographic and socio-economic variables significantly affect travel time as well as non-home activity time.

A Comparison of Bayesian and Maximum Likelihood Estimations in a SUR Tobit Regression Model (SUR 토빗회귀모형에서 베이지안 추정과 최대가능도 추정의 비교)

  • Lee, Seung-Chun;Choi, Byongsu
    • The Korean Journal of Applied Statistics
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    • v.27 no.6
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    • pp.991-1002
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    • 2014
  • Both Bayesian and maximum likelihood methods are efficient for the estimation of regression coefficients of various Tobit regression models (see. e.g. Chib, 1992; Greene, 1990; Lee and Choi, 2013); however, some researchers recognized that the maximum likelihood method tends to underestimate the disturbance variance, which has implications for the estimation of marginal effects and the asymptotic standard error of estimates. The underestimation of the maximum likelihood estimate in a seemingly unrelated Tobit regression model is examined. A Bayesian method based on an objective noninformative prior is shown to provide proper estimates of the disturbance variance as well as other regression parameters

Sentiment Shock and Housing Prices: Evidence from Korea

  • DONG-JIN, PYO
    • KDI Journal of Economic Policy
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    • v.44 no.4
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    • pp.79-108
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    • 2022
  • This study examines the impact of sentiment shock, which is defined as a stochastic innovation to the Housing Market Confidence Index (HMCI) that is orthogonal to past housing price changes, on aggregate housing price changes and housing price volatility. This paper documents empirical evidence that sentiment shock has a statistically significant relationship with Korea's aggregate housing price changes. Specifically, the key findings show that an increase in sentiment shock predicts a rise in the aggregate housing price and a drop in its volatility at the national level. For the Seoul Metropolitan Region (SMR), this study also suggests that sentiment shock is positively associated with one-month-ahead aggregate housing price changes, whereas an increase in sentiment volatility tends to increase housing price volatility as well. In addition, the out-of-sample forecasting exercises conducted here reveal that the prediction model endowed with sentiment shock and sentiment volatility outperforms other competing prediction models.

Monthly Hanwoo supply and forecasting models

  • Hyungwoo, Lee;Seonu, Ji;Tongjoo, Suh
    • Korean Journal of Agricultural Science
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    • v.48 no.4
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    • pp.797-806
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    • 2021
  • As the number of scaled-up ranches increased and agile responses to market changes became possible, decision-making by Hanwoo cattle farms also began to affect short-term shipments. Considering the changing environment of the Hanwoo supply market and the response speed of producers, it is necessary quickly to grasp the forecast ahead of time and to respond accordingly in an effort to stabilize supply and demand in the Hanwoo market. In this study, short-term forecasting model centered on the supply of Hanwoo was established. The analysis conducted here indicates that the slaughter of Hanwoo males increases by 0.248 as the number of beef cattle raised over 29 months of age in the previous month increases by one, and 0.764 Hanwoo females were slaughtered under average conditions for every Hanwoo male slaughtered. With regard to time, the slaughtering of Hanwoo was higher in January and August, which are months known for holiday food preparation activities for the New Year and Chuseok in Korea, respectively. Simulations indicated that errors were within 10% in all simulations performed through the Hanwoo supply model. Accordingly, it is considered that the estimation results from the supply model devised in this study are reliable and that the model has good structural stability.