Determinants of Household Expenditure on Computer Hardware and Software

This study investigated households' expenditure on computer hardware and software using the 2000 Consumer Expenditure Survey. Based on neoclassical consumer theory, a conceptual model of computer expenditure was developed that included economic resources and consumer tastes and preferences. A double-hurdle model was conducted to estimate whether or not households spent on computer hardware and software and the amount spent on computer hardware and software. Implications are offered for consumers and policy makers. ********** In the last half of the twentieth century and beginning of the twenty-first, there is no doubt that the personal computer has touched more lives more quickly than any other technological item. Large-scale computers, costing millions of dollars, filled entire buildings in the 1950s. By the late 1980s, that computing capability was reduced to the size of a single computer chip that could be manufactured for a few dollars (Kominski and Newburger 1999). Twenty years after the advent of the personal computer, computers have diffused rapidly into homes, but they may still he a resource that is acquired more readily by affluent and well-educated Americans (Papadakis 2001). Although socioeconomic and demographic variables have been shown to predict use of the home computer, research is needed to better understand consumer expenditure on computers. Data from the Current Population Survey and the Census Bureau portray the dramatic growth of computer ownership. In 1984, when data on home computers were first collected by the Current Population Survey, only 7.9% of U.S. households owned a home computer (Kominski and Newburger 1999). In 2000, the Census Bureau reported that 51% of U.S. households owned one or more computers (U.S. Department of Commerce, Bureau of the Census 2001). Although descriptive studies show that computer ownership varies by age, gender, marital status, race, education, and income (Papadakis 2001), current research on computers has mostly focused on the diffusion of technology and on computer adoption (Agarwal and Prasad 1999; Caselli and Coleman 2001; Davis 1986). There is a lack of research on computer expenditure from a consumer economics perspective. The lack of information on home computers and the factors related to their purchase have played a role in the relatively limited amount of research on computer ownership (Papadakis 2001). However, the Consumer Expenditure Survey (CES) collected by the Bureau of Labor Statistics includes information on computer expenditure. Although the CES has included the purchase of computers since 1982 (Gray 1992), expenditure on computers has not been examined. Because the CES contains both detailed socioeconomic information on U.S. households and spending on computers by households, it is an appropriate data set for this study. In many previous studies on expenditures, the expenditure of goods has been examined as if the decision had only one dimension. Instead, the study of expenditure should be examined as if it consisted of two decisions: whether to purchase a good or service and the amount spent on the good or service (Liu and Putler 2001). To analyze this two-part decision, the double-hurdle model proposed by Cragg (1971) is an appropriate technique. This study proposes to examine consumer spending on computers to fill gaps in the literature on computers. First, the study will develop a conceptual model for computer expenditure. Then, the study will examine the factors that are expected to influence consumers' expenditure on computers using a double-hurdle model. REVIEW OF LITERATURE Because there is a lack of information on expenditure for computers, the research on expenditure on other goods will be examined. A conceptual model of computer expenditure should include age because age has an important influence on the pattern of household expenditures. However, the relationship of age and the pattern of expenditures varies for different types of goods and services (Paulin 1995). …