Abstract
Household expenditures are important indicators in many aspects, especially in the economic growth of a country. One of the most important determinants of expenditures is the head of the household working within the framework of the household's income. From this point of view, the aim of the study is to determine the factors affecting the household expenditures of the heads of the household who are 60 years of age and older living in Turkey. In this framework, the data set of the Household Budget Survey of the Turkish Statistical Institute was used for the years 2015-2019. The least absolute deviation regression was used for the data set analysis. As a result of the study, it was determined that the gender of the head of the household, educational status, economic indicators, especially income, and social indicators were effective on the expenditures of the households. The results of the study provide valuable information to researchers, decision-makers, and policymakers who want to study this issue to understand the household spending patterns of working elderly household heads.
TopLiterature Review
There are many studies on household expenditure items from past to present (Bellante and Foster, 1984; Bryant, 1988; Cook et al, 1995; Jacobs et al, 1989; Koelln et al, 1995; Paulin, 2000; Rubin and Koelln, 1996; Strober and Weinberg, 1977; Yen, 1993; Weinberg and Winer, 1983). In this section, summaries of some of these studies will be presented.
Expenditure patterns of elderly individuals were examined by Chung and Magrabi (1990). The data set of the study was obtained through the 1986 Consumer Expenditure Survey. Multiple regression analysis was applied in the study. As a result of the study, it was determined that age is an important factor in expenditures, compared to younger households, older households spend more on public services, care, and domestic services, and less on clothing, housing, and entertainment. In addition, it has been identified that there is no statistically significant difference between old and young individuals in terms of eating at home and making food expenditures outside.
Key Terms in this Chapter
Least Absolute Deviation Regression: It is an estimation method that aims to obtain estimators that minimize the sum of the absolute values of the errors.
Heteroscedasticity: It means that error terms do not have constant variance. Thus, the variance of the error terms will change with the independent variable.
Cross-Sectional Data: Data collected from different units at a certain time is called cross-sectional data.
Ordinary Least Squares Method: It is an estimation method that aims to obtain estimators that minimize the sum of squares of error.
Normal Distribution Assumption: It is an assumption that the error terms are normally distributed.