Macro Debt Burden and Consumption Expansion:An Analysis Based on Panel Model and Panel Quantile Regression Model

As the level of social credit burden rises,to ease the liquidity constraint for residents is currently an important way to boost the domestic demand in China.This paper uses the panel data of Chinese provincial-level administrative units in 2007−2017 and adopts the panel regression model and panel quantile regression model to empirically analyze the relationship between debt burden level and average propensity to consume(APC).The result shows that increase in the level of macro debt burden can significantly improve the APC of residents;the marginal promoting effect of macro debt burden for the APC is in a V-shaped structure;such marginal influence differs evidently in different areas,with the marginal promoting effect turning out most prominent in the northeast of China.Accordingly,it’s suggested for government to keep refining the credit market,increase residents’income in multiple means,guide supply of liquidity towards the real economy and promote equalization of basic public services,so as to realize the expansion and upgrade of consumption.

Using Quantile Regression Approach to Analyze Price Movements of Agricultural Products in China

This paper studies how the price movements of pork,chicken and egg respond to those of related cost factors in short terms in Chinese market.We employ a linear quantile approach not only to explore potential data heteroscedasticity but also to generate confidence bands for the purpose of price stability study.We then evaluate our models by comparing the prediction intervals generated from the quantile regression models with in-sample and out-of-sample forecasts.Using monthly data from January 2000 to October 2010,we observed these findings：（i） the price changes of cost factors asymmetrically and unequally influence those of the livestock across different quantiles;（ii） the performance of our models is robust and consistent for both in-sample and out-of-sample forecasts;（iii） the confidence intervals generated from 0.05th and 0.95th quantile regression models are good methods to forecast livestock price fluctuation.

L1/2 -Regularized Quantile Method for Sparse Phase Retrieval

The sparse phase retrieval aims to recover the sparse signal from quadratic measurements. However, the measurements are often affected by outliers and asymmetric distribution noise. This paper introduces a novel method that combines the quantile regression and the L1/2-regularizer. It is a non-convex, non-smooth, non-Lipschitz optimization problem. We propose an efficient algorithm based on the Alternating Direction Methods of Multiplier (ADMM) to solve the corresponding optimization problem. Numerous numerical experiments show that this method can recover sparse signals with fewer measurements and is robust to dense bounded noise and Laplace noise.

Analysis of hospitalization costs related to fall injuries in elderly patients

BACKGROUND With the aging world population,the incidence of falls has intensified and fallrelated hospitalization costs are increasing.Falls are one type of event studied in the health economics of patient safety,and many developed countries have conducted such research on fall-related hospitalization costs.However,China,a developing country,still lacks large-scale studies in this area.AIM To investigate the factors related to the hospitalization costs of fall-related injuries in elderly inpatients and establish factor-based,cost-related groupings.METHODS A retrospective study was conducted.Patient information and cost data for elderly inpatients(age≥60 years,n=3362)who were hospitalized between 2016 and 2019 due to falls was collected from the medical record systems of two grade-A tertiary hospitals in China.Quantile regression(QR)analysis was used to identify the factors related to fall-related hospitalization costs.A decision tree model based on the chi-squared automatic interaction detector algorithm for hospitalization cost grouping was built by setting the factors in the regression results as separation nodes.RESULTS The total hospitalization cost of fall-related injuries in the included elderly patients was 180479203.03 RMB,and the reimbursement rate of medical benefit funds was 51.0%(92039709.52 RMB/180479203.03 RMB).The medical material costs were the highest component of the total hospitalization cost,followed(in order)by drug costs,test costs,treatment costs,integrated medical service costs and blood transfusion costs The QR results showed that patient age,gender,length of hospital stay,payment method,wound position,wound type,operation times and operation type significantly influenced the inpatient cost(P<0.05).The cost grouping model was established based on the QR results,and age,length of stay,operation type,wound position and wound type were the most important influencing factors in the model.Furthermore,the cost of each combination varied significantly.CONCLUSION Our grouping model of hospitalization costs clearly reflected the key factors affecting hospitalization costs and can be used to strengthen the reasonable control of these costs.

The Non-Linear Effect of China’s Energy Consumption on Eco-Environment Pollution

With the increase of total energy consumption,eco-environmental quality drops sharply,which has attracted concerns from all circles.It has become the top priority of construction of socialist ecological civilization to clarify the influences of energy consumption on the level of eco-environmental pollution.Ecological environmental pollution control cannot be one size fits all.It can avoid resource depletion and environmental deterioration via adjusting measures to local conditions to coordinate ecological environmental pollution and energy consumption problems.In this essay,entropy method is adopted to measure the composite indexes of eco-environmental pollution of 30 provinces and cities in China,based on which kernel density function is used to analyze the dynamic law of eco-environmental pollution.And then,traditional fixed effect model and panel quantile regression model are adopted respectively to analyze the influences of energy consumption on eco-environmental pollution.The research finds that composite index of eco-environmental pollution shows N-shaped curve of“rising-dropping-rising”during the sample period,with the overall difference decreasing gradually and the polarization disappearing gradually;in areas with higher eco-environmental pollution,energy consumption has aggravated ecoenvironmental pollution,while in areas with lower eco-environmental pollution,energy consumption could alleviate eco-environmental pollution to some degree;foreign direct investment could relieve eco-environmental pollution.Therefore,corresponding measures should be taken to improve the quality of eco-environment based on the changes of energy consumption in areas with different levels of eco-environmental pollution.

Heterogeneity analysis of the role of film box office revenue factors:Based on quantile regression analysis

In this paper I apply the Quantile Regression model that suits for the different contribution of the attributes surrounding different levels of film revenues.The regression coefficients from this model reflects the correlation between the film revenue and the various attributes(production budget,popularity,runtime,vote average and vote count).The empirical analysis result shows that QR coefficients vary across different intervals of film revenue.This implies that the size of the effect for the influencing factors differ between profitability quantiles of films.

Estimating the effect of minimum wage on firm profitability in China

Using the firm-level panel datasets and hand-collected data on county level minimum wage,this paper estimates the effect of minimum wage on firm profitability.As firms may take time to adjust in response to changes in minimum wage,this paper estimates a dynamic panel model with lagged minimum wage.To capture the heterogeneous effect of minimum wage on profitability,this paper further estimates quantile regression dynamic panel model.The estimation results suggest that the effect on firm profitability of minimum wage in the current year is negative across the whole conditional distribution of profitability and it exhibits an inverted-U shape across conditional quantiles.The effect on profitability of lagged minimum wage is positive at the 5th,10th,15th quantiles,negative at the 90th and 95th quantiles,and not significant at other quantiles.Turning to the overall effect on profitability of minimum wage,we find that minimum wage exerts significantly negative effect on profitability at the 5th quantile and quantiles higher than 40th and the absolute value of the effect of minimum wage increases with these quantiles.For other quantiles,the overall effect of minimum wage on profitability is negligible.