Modeling the household milk consumption data by endogenous Bayesian Tobit Quantile (BTQ) regression in sidoarjo

Sartika Wulandari, I. Zain, S. Rahayu
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Abstract

In surveys conducted by Badan Pusat Statistik (BPS), such as SUSENAS, many households do not allocate expenditures for certain types of consumer goods. This causes a lot of censored data. An example of such expenditure is spending on milk consumption. Previous studies that analyzed household expenditure for milk consumption were conducted using the Bayesian Tobit Quantile (BTQ) model. However, the research has not been able to include household income variable that is not linear. This raises the assumption that the variable is endogenous. If the endogenous variable is used in BTQ model, the result of parameter estimation will be biased. Thus, an alternative model that can accommodate the endogenous variables is required. Based on the descriptions, this research used Endogenous Bayesian Tobit Quantile (BTQ) model. The variables used are household expenditures for milk consumption as the censored response variable, household income as the endogenous variable, household head education, percentage of household expenditure for food, numbers of household member, percentage of household member aged < 12 years, average of per capita expenditure, and percentage of working household member as the exogenous variables, and working hours of household head as the instrumantal variable. Furthermore, Endogenous BTQ models for household expenditure data for milk consumption are compared with both Tobit Quantile (TQ) and BTQ models using RMSE and the result is Endogenous BTQ models perform better when endogenous problems arise. In addition, it was found that from the data, significant endogeneity was found on the left side of 0.55-th quantile and on the right side of 0.80-th quantile. It's also found that in the lower quantiles, the percentage of household expenditure on food does not significantly affect household expenditure for milk consumption. Besides, in the upper quantile the percentage of household member aged < 12 years have no significant effect.
基于内源性贝叶斯Tobit分位数(BTQ)回归的家庭牛奶消费数据建模
在巴丹市统计局(BPS)进行的调查中,如SUSENAS,许多家庭没有为某些类型的消费品分配支出。这导致了大量经过审查的数据。此类支出的一个例子是牛奶消费支出。以前分析家庭牛奶消费支出的研究是使用贝叶斯托比分位数(BTQ)模型进行的。然而,该研究未能纳入非线性的家庭收入变量。这就提出了一个假设,即变量是内生的。如果在BTQ模型中使用内生变量,参数估计的结果会有偏倚。因此,需要一种能够容纳内生变量的替代模型。在此基础上,本研究采用内源性贝叶斯Tobit分位数(Endogenous Bayesian Tobit Quantile, BTQ)模型。变量以家庭牛奶消费支出为审查响应变量,家庭收入为内生变量,户主教育程度、家庭食品支出百分比、家庭成员人数、家庭成员年龄< 12岁的百分比、人均支出平均值、家庭工作成员百分比为外生变量,户主工作时间为工具变量。此外,使用RMSE将家庭牛奶消费支出数据的内源性BTQ模型与Tobit分位数(TQ)和BTQ模型进行了比较,结果表明,当出现内源性问题时,内源性BTQ模型表现更好。此外,从数据中发现,在0.55分位数的左侧和0.80分位数的右侧存在显著的内生性。研究还发现,在较低的分位数中,家庭食品支出的百分比对家庭牛奶消费支出的影响并不显著。此外,在上分位数中,家庭成员年龄< 12岁的百分比没有显著影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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