Estimating SUR system with random coefficients: the unbalanced panel data case

Biørn, Erik

doi:10.1007/s00181-013-0753-y

Cited by 3 publications

(4 citation statements)

References 14 publications

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“…To avoid survivor bias [33], we use a static three-equation seemingly unrelated regression (SUR) model framework for unbalanced panel data with latent individual heterogeneity [34,35]. The SUR model explains the variation of not just one dependent variable, as in the univariate multiple regression model, but the variation of a set of m dependent variables [36], estimating consistently better than the Ordinary Least Squares (OLS) does [37].…”

Section: Methodsmentioning

confidence: 99%

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China’s New Cooperative Medical Scheme’s Impact on the Medical Expenses of Elderly Rural Migrants

Huang

Nicholas

et al. 2019

IJERPH

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Background: With rapid urbanization in China, the scale of elderly migrants from rural areas to urban cities has increased rapidly from 5.03 million in 2000 to 13.4 million people in 2015. Methods: Based on the unbalanced panel data obtained from the Chinese Longitudinal Healthy Longevity Survey, this study investigates the impact of changes to the New Cooperative Medical Scheme (NCMS) on the medical expenditure of Chinese elderly rural migrants by using seemingly unrelated regression models. Results: NCMS coverage for elderly rural migrants rose from 11.83% in 2005 to 87.33% in 2014. The effective reimbursement rate increased significantly from 4.53% in 2005 to 36.44% in 2014, and out-of-pocket/income fell by 50% between 2005 and 2014. The NCMS significantly increased the effective reimbursement rate by 12.4% and out-of-pocket medical expenditure/income by 7.5% during this decade but played an insignificant role in reducing out-of-pocket payments. Conclusions: Policy makers need to promote a two-pronged strategy, which involves controlling the excessive growth of urban medical expenses and continuing to reform NCMS reimbursements for medical treatment, so non-urban resident elderly rural migrants can fully enjoy the welfare benefits of migration and urbanization.

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Section: Methodsmentioning

confidence: 99%

“…shows that the medical expenses and the effective reimbursement rate for elderly rural migrants rose over the decade. The per capita income of rural migrant elders increased sharply from US$817 34. in 2005 to US$2118.77 in 2014 and medical expenses also more than doubled from an average of US$197.8 in 2005 to US$456.92 in 2014.…”

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confidence: 99%

China’s New Cooperative Medical Scheme’s Impact on the Medical Expenses of Elderly Rural Migrants

Huang

Nicholas

et al. 2019

IJERPH

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“…In the case of this study, 15% of the sample trees produced sawlogs only, leaving 36 trees without the pulpwood subcomponent for product biomass. In such cases, it is presently problematic or impossible to estimate both major and sub-components in one system of additive biomass equations with cross-equational parameter constraints through seemingly unrelated regression without any loss of information, although some progress in this regard has been made in econometrics [87,88]. This problem was avoided by developing additive equations for the major components first and then breaking each major component into subcomponents through allocative biomass equations.…”

Section: Discussionmentioning

confidence: 99%

Product and Residue Biomass Equations for Individual Trees in Rotation Age Pinus radiata Stands under Three Thinning Regimes in New South Wales, Australia

Wang

Ximenes

et al. 2017

Forests

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Using data from 239 trees that were destructively sampled and completely weighed in the field, four systems of nonlinear additive equations were developed for the estimation of product and residue fresh and dry weight of individual trees in rotation age (28 to 42 years) Pinus radiata stands under three thinning regimes: unthinned (T0), one thinning (T1) and two thinnings (T2). To cater for all practical applications, the four systems of equations included diameter at breast height overbark (DBHOB) as the only independent variable or both DBHOB and total tree height as predictors either with or without the incorporation of dummy variables for stand types. For all systems, the property of additivity was guaranteed by placing constraints on the structural parameters of the system equations. The parameter estimates were obtained by the generalized methods of moments (GMM) following a comparison with weighted nonlinear seemingly unrelated regression (WNSUR). Based on the predicted values from the system that had DBHOB as the predictor and dummy variables for stand types, the percentage of total tree fresh weight accounted for by residues increased from 14.8% to 20.5%, from 15.6% to 22.2% and from 13.9% to 18.7% for trees in the T0, T1 and T2 stands, respectively, as DBHOB increased from 15 to 70 cm. The corresponding changes in the percentage of residue dry weight were from 15.1% to 16.1%, from 15.7% to 17.1% and from 14.9% to 15.8% for the three stand types. In addition, two systems of allocative equations were developed to allocate the predicted product and residue biomass to their respective subcomponents. The system of allocative equations for product biomass predicted that sawlogs with bark accounted for 83% to 85% of product fresh weight and 82% to 87% of product dry weight over the same range of DBHOB. The predicted allocation of total residue dry weight to stump changed little, between 12% and 13%, over the same diameter range, but it was slightly higher for trees with DBHOB between 30 and 45 cm. The predicted allocation of total residue biomass to branches increased from 18% to 65% in fresh weight and from 18% to 57% in dry weight and that to waste decreased from 71% to 27% in fresh weight and from 70% to 32% in dry weight as DBHOB increased from 15 to 70 cm. Among the five biomass components, prediction accuracy was the lowest for pulpwood and waste. The systems of additive and allocative biomass equations developed in this study provided the first example of how the two approaches could be used together for the estimation of total tree, major and sub-component biomass. They will provide forest management with an enhanced capacity to more accurately estimate product and residue biomass of rotation age trees and thus to include the production of biomass for renewable energy generation in their management systems for P. radiata plantations.

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“…We use a static two-equation seemingly unrelated regression (SUR) model framework for unbalanced panel data with latent individual heterogeneity and the reimbursement ratio and OOP% as endogenous variables [22–24]. The seemingly unrelated regressions (SUR) model explains the variation of not just one dependent variable, as in the univariate multiple regression model, but the variation of a set of many dependent variables [25].…”

Section: Methodsmentioning

confidence: 99%

The effect of China’s new cooperative medical scheme on health expenditures among the rural elderly

Zeng

Yuan

et al. 2019

Int J Equity Health

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BackgroundThe alarming progression of an increasingly aging population in China has attracted much attention within the country and abroad. In 2003, the Chinese central government launched the New Cooperative Medical Scheme (NCMS) to resolve problems of healthcare inequity in regions with inadequate infrastructure and relative poverty. The purpose of this study was to investigate the effect of NCMS on health expenditures by the Chinese rural elderly population.MethodsThe data were obtained from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), which was conducted in 2005, 2008, 2011 and 2014. Elderly people living in rural areas and 60 years old or above were screened for the investigation. The sample size was 7472 in 2005, 11,705 in 2008, 9239 in 2011, and 6059 in 2014. The OOP% and reimbursement ratio were the medical expenses paid by individuals accounting for their per capita annual income and the medical expenses paid by medical insurance accounting for their total medical expenses, respectively. By controlling for individuals’ sociodemographic characteristics, pensions, demands and utilization of health services, we estimated the effect of the NCMS on the OOP% and reimbursement ratio for the rural elderly using seemingly unrelated regression (SUR).ResultsThe NCMS coverage ranged from 11.63% in 2005 to 80.34% in 2014. The medical expenses of the elderly also increased from an average of $204.77 in 2005 to $696.23 in 2014, which was more than three times as much as in 2005. From 2005 to 2014, the reimbursement ratio for medical expenses of rural elderly people with NCMS increased significantly from 30.6% in 2005 to 56.1% in 2014. The proportion of reimbursement ratio for rural seniors with NCMS increased by 6.4% across each survey cycle (every 3 years). However, the NCMS resulted in an insignificant decrease in OOP% by 1.4% across each survey cycle (every 3 years). Among other medical insurances, public insurance and private elder insurance had significant positive impacts on reimbursement ratio but did not influence OOP%.ConclusionsNCMS remarkably increased the rural elderly’s reimbursement ratio but insignificantly decreased the rural elderly’s OOP%. In addition, the proportion of reimbursement ratio for NCMS participants increased by 6.4% every 3 years. Lower outpatient reimbursement, migration, limited reimbursement scope, an increasing demand for medical services and the rapid growth of medical expenses may be reasons for the gaps between the nominal reimbursement ratio and the actual reimbursement ratio and OOP%. Policymakers should further modify NCMS policies in rural China.

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Estimating SUR system with random coefficients: the unbalanced panel data case

Cited by 3 publications

References 14 publications

China’s New Cooperative Medical Scheme’s Impact on the Medical Expenses of Elderly Rural Migrants

China’s New Cooperative Medical Scheme’s Impact on the Medical Expenses of Elderly Rural Migrants

Product and Residue Biomass Equations for Individual Trees in Rotation Age Pinus radiata Stands under Three Thinning Regimes in New South Wales, Australia

The effect of China’s new cooperative medical scheme on health expenditures among the rural elderly

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