An Econometric Analysis of Hospital Length of Stay for Cataract Operations in Japan by the Box-Cox Transformation Model and Hausman Tests: Evaluation of the 2010 Revision of the Medical Payment System

The Japanese medical costs for cataract treatments reached 270 billion yen in fiscal year 2012. Since the length of stay (LOS) in hospital is much longer than other major countries, controlling the medical costs by reducing LOS becomes an important issue in Japan. In this paper, we evaluated the effects of the 2010 revision of the Japanese medical payment system (DPC/PDPS) on LOS for cataract operations. The Box-Cox transformation model, Nawata’s estimators and Hausman tests were used in the analysis. To evaluate the effects, we analyzed a dataset obtained from 34 DPC hospitals (Hp1-34) where one-eye cataract operations were performed both before (April 2008-March 2010) and after (April 2010-March 2012) the 2010 revision and there were more than 500 patients. The dataset contained information from 32,593 patients. We did not admit the effect of the 2010 revision in this study, and there were large differences LOS among hospitals, even after removing the influences of factors such as patient characteristics and types of principal diseases.

Asymptotic Efficiency of the Maximum Likelihood Estimator for the Box-Cox Transformation Model with Heteroscedastic Disturbances

This paper considers the asymptotic efficiency of the maximum likelihood estimator (MLE) for the Box-Cox transformation model with heteroscedastic disturbances. The MLE under the normality assumption (BC MLE) is a consistent and asymptotically efficient estimator if the “small ” condition is satisfied and the number of parameters is finite. However, the BC MLE cannot be asymptotically efficient and its rate of convergence is slower than ordinal order when the number of parameters goes to infinity. Anew consistent estimator of order is proposed. One important implication of this study is that estimation methods should be carefully chosen when the model contains many parameters in actual empirical studies.

Investigating seasonality,policy intervention and forecasting in the Indian gold futures market:a comparison based on modeling non‑constant variance using two different methods

This study focuses on the Indian gold futures market where primary participants hold sentimental value for the underlying asset and are globally ranked number two in terms of the largest private holdings in the physical form.The trade of gold futures relates to seasons,festivity,and government policy.So,the paper will discuss seasonality and intervention in the analysis.Due to non-constant variance,we will also use the standard variance stabilization transformation method and the ARIMA/GARCH modelling method to compare the forecast performance on the gold futures prices.The results from the analysis show that while the standard variance transformation method may provide better point forecast values,the ARIMA/GARCH modelling method provides much shorter forecast intervals.The empirical results of this study which rationalise the effect of seasonality in the Indian bullion derivative market have not been reported in literature.

Growth Curves for Diameter and Height Using Mixed Models: An Application in Eucalyptus Seedling

The growth of a tree or a forest settlement is of great value to a forest enterprise, because many decisions are directly dependent of this information, for instance, determining the optimal cutting age. This study aims to apply a new class of models to fit growth curves for diameter and height of Eucalyptus grandis X Eucalyptus urophylla seedling data. Data were collected from a trial conducted in a green house at the Natural Resources Department at School of Agriculture, Botucatu, S?o Paulo, Brazil. The experiment’s design was completely randomized with eight treatments and four replications. In this trial, the growth variables referring to the height and the diameter were evaluated, being measured five and four times, respectively. The methodology was carried in a mixed longitudinal model using a new approach based on Box-Cox Normal (BCN) distribution, and comparisons with this model were made assuming normality of the data. The results revealed that the BCN mixed model provided similar results to the standard model in order to estimate growth curves;however, the BCN model was the best result according to Akaike criterion, considering the slight asymmetry in the data set. This approach is of great interest in case of outliers and robust procedures for parameter estimation.

Impacts of household income on beef at-home consumption:Evidence from urban China

Beef consumption in China has increased substantially from 5.0 million tons in 2000 to 7.7 million tons in 2019 thanks to rapid income growth,but still remains low compared to pork and poultry consumption.Improving the understanding about the impacts of household income on beef consumption in China is necessary to forecast future beef demand and inform the domestic beef industry,especially in the context of unprecedented expansion of middle income class in China.Based on survey data of 32878 urban households collected by the National Bureau of Statistics of China,we employed the inverse hyperbolic sine(IHS)double-hurdle model to estimate income elasticities of beef demand across different income groups and simulated possible trends of future beef consumption of Chinese urban residents.The empirical results showed that the unconditional income elasticities of beef consumption at home vary between 0.169 for the lowincome group and 0.671 for the high-income group.The simulated results indicated that beef consumption is expected to increase by 12.0 to 38.8%in 10 years and by 18.6 to 70.5%in 15 years under distinct income growth scenarios.Our findings provide practical insights for policy makers and other stakeholders about future beef demand,such as potential opportunities embedded in rising beef demand for domestic producers and world beef exporters as well as the urgency of improving the supply chain resilience of beef in China.

Semiparametric estimation of a Box-Cox transformation model with varying coefficients model

This paper considers the estimation of a Box-Cox transformation model with varying coefficient. A two-step approach is proposed in which the first step estimates the varying coefficients nonparametrically for any given parameter a in the transformation function. Then a one-dimensional search of a has been employed based on some least absolute deviation criterion function. The validity of our estimator does not require independence assumption thus is robust to the conditional heteroscedasticity. A simulation study shows a reasonably well finite sample performance. Additionally, a comprehensive empirical study has been carefully examined.

A Class of Box-Cox Transformation Models for Recurrent Event Data with a Terminal Event

In this article, we study a class of Box-Cox transformation models for recurrent event data in the presence of terminal event, which includes the proportional means models as special cases. Estimating equation approaches and the inverse probability weighting technique are used for estimation of the regression parameters. The asymptotic properties of the resulting estimators are established. The finite sample behavior of the proposed methods is examined through simulation studies, and an application to a heart failure study is presented to illustrate the proposed method.

Evaluation of Length of Hospital Stay Joining Educational Programs for Type 2 Diabetes Mellitus Patients: Can We Control Medical Costs in Japan?

Diabetes has become a growing concern in Japan, both medically and financially. The medical cost of diabetes was estimated at 1215 billion yen for fiscal year 2011. We analyzed the length of stay (LOS) in a hospital for type 2 diabetes mellitus patients who participated in educational programs to determine factors affecting LOS. Data on 991 patients obtained from 28 Red Cross hospitals in 2008 were used. For the analysis, we used the Box-Cox transformation model and Hausman test. The results revealed that patients aged 75 years and above and those with comorbidities and complications were prone to longer LOS. The analysis also revealed significant differences in LOS across the hospitals, even after controlling for patient characteristics. Finally, we applied the least squares method to determine the effects of hospital and regional factors and revealed that patients’ LOS was affected by the region’s average LOS. Regional corporations and networks appeared to be important in improving educational programs.

Financial Sustainability of the Japanese Medical Payment System: Analysis of the Japanese Medical Expenditure for Educational Hospitalization of Patients with Type 2 Diabetes

Japanese medical expenditures have increased rapidly in recent years and are predicted to continue rising. Indeed, it remains uncertain whether the current Japanese medical system can be sustained. In this paper, we analyzed the medical expenditures for educational hospitalization of patients with type 2 diabetes. A dataset of 6173 patients from 36 hospitals was used in the analysis. The sample period was from July 2008 to March 2012. We analyzed the medical expenditures in two ways. First, we analyzed the length of hospital stay (LOS). Next, we analyzed the daily expenditure per patient. The Box-Cox transformation model was used in the first analysis and the ordinary least squares method in the second. Comorbidities and complications prolonged LOS and increased daily expenditures. The LOS was significantly different among hospitals. On the other hand, the differences in daily expenditures among hospitals were relatively small, such that LOS was the main determinant of medical expenditures. Previous studies suggested that LOS could be shortened without degradation of medical quality. Moreover, LOS could be controlled by introducing proper critical paths and improving and standardizing educational programs. Hence, it would be possible to control the medical expenditures for this disease.

Semi-parametric estimation for the Box-Cox transformation model with partially linear structure

The Box-Cox transformation model has been widely used in applied econometrics, positive accounting, positive finance and statistics. There is a large literature on Box-Cox transformation model with linear structure. However, there is seldom seen on the discussion for such a model with partially linear structure. Considering the importance of the partially linear model, in this paper, a relatively simple semi-parametric estimation procedure is proposed for the Box-Cox transformation model without presuming the linear functional form and without specifying any parametric form of the disturbance, which largely reduces the risk of model misspecification. We show that the proposed estimator is consistent and asymptotically normally distributed. Its covariance matrix is also in a closed form, which can be easily estimated. Finally, a simulation study is conducted to see the finite sample performance of our estimator.

The Analysis of Spring Precipitation in Semi-Arid Regions: Case Study in Iran

In this study, Zanjan from Iran has been chosen from among all the semi-arid regions of world, which has Synoptic station and statistical data since 1955. Spring and monthly precipitations are also provided in the period of 1956-2005. First, all data has been controlled by double mass method with the help of adjacent stations, and then it was normalized by the box-cox transformations method. The global SPI index was calculated for all months and spring, also drought and wet periods were determined and finally compared. In the drought category view, spring months have represented the great similarities. The moving averages are represented all months and spring’s precipitations such as three years, five years, seven years and nine years are shown. Statistical period was observed and analyzed based on five periods of ten years, and results precipitation with more than 5mm and 10mm has gradually decreased on April. However the number of days with precipitation has increased. The calculated spring precipitations and all of the atmospheric factors represented the dependence of this model to maximum average of spring temperature and relative humidity of spring and winter by the use of multi variable regression method. The predicted precipitation of spring also showed the gradual decline of precipitation in the next 30 years by the arima model.

A Long Term Evaluation of the Japanese Medical Payment System for Cataract Surgeries: Did the Medical Policy Reduce the Long Hospital Stay in Japan?

In this paper, we conducted a long term survey of the cataract surgeries. The sample period was about 7 years, from July 2005 to March 2012. We evaluated the effects of three revisions of the medical payment system that were done in 2006, 2008 and 2010. For the analysis, the Box-Cox transformation model and Hausman test using Nawata’s estimator were used for the length of stay (LOS) in hospitals, and the ordinary least squares method was used for the non-inclusive (mainly payments for surgeries) payments. We analyzed a dataset of 51,054 patients obtained from 60 hospitals (Hp1-60) where more than 300 one-eye cataract surgeries were performed during the period. For the LOS, we found that only the 2008 revision had significant impact on shortening the LOS but the other two did not. We also found very large differences among hospitals even after eliminating effects of patients’ characteristics and type of principle diseases as previous studies. For non-inclusive payments 2006 and 2008 revisions had significant impacts and the differences among hospitals were much smaller than those of the LOS.

DIAGNOSTICS FOR NONLINEAR REGRESSION MODEL WITH WEIGHTING OR TRANSFORMATION

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Optimization of friction and wear characteristics of varied cryogenically treated hot die steel grade AISI-H13 under dry condition

Cryogenic treatment (CT) is a relatively new field,which has emerged during the last three decades of the twentieth century.However,its impact on material shaping and making tool life,and enhancement of their mechanical properties are quite remarkable.The selection of appropriate process parameters for CT is essential for cost reduction and optimum productivity.This study focuses on the influence of key parameters of CT cycles (i.e.,soaking temperature and duration) on the friction and wear behavior of AISI H13 hot die steel under dry sliding conditions against hardened and tempered AISI D3 cold work tool steel (counter face) at varying sliding speeds and loads.Mathematical models have been developed for wear rate,the average coefficient of friction,and maximum contact temperature using the Box-Cox methodology.The developed mathematical models have been validated by comparing with the experimental results.Moreover,the optimum values of the process parameter have been employed to maximize the output and validate the same by confirmation of the experiments.To the best of our knowledge,this is the first study that demonstrates the modeling and optimization of sliding friction and wear characteristics of AISI H13 under varied CT cycles.