Volume 4 Number 2 February 2018

Differences Between Prices of Goods and Services in China

Authors: Gaolu Zou
Pages: 24-27
Given a budget constraint, a family allocates its expenditures among food, clothing, and housing and transportation services based on their respective prices. This study tested for differences between these price components. Data were monthly changes for 1999-2017. Prices contained four components of CPI: Price indices of clothing, food, housing and transportation. Unit root tests include ADF, PP and DF-GLS. Cointegration tests include the Engle-Granger and Johansen tests. Four series variables contained a unit root but not cointegrated. A first-differenced VAR(k=3) was estimated. Major findings are that while housing prices grew by 1%, food prices reduced by -0.47% in two months. While clothing prices grew by 1%, food prices reduced by -0.77% in one month. While transportation prices grew by 1%, food prices reduced by -0.53% in one month. Hence, this paper suggests that an increase in expenditures on clothing, housing and transportation may be made at the cost of food consumption. However, an inconsistency of changes across various prices does not necessarily mean causal links between variables or exogeneity of a given variable.

Socio-Demographic Factors That Determine the Usage of Mobile Phones in Rural Communities

Authors: Akinleke W. Olaitan
Pages: 16-23
The aim of this study was to examine the perception and attitude of Nigerian rural dwellers as a gauge for determining whether there is (or not) perceived beneficial use of mobile technologies among rural inhabitants. It also tries to find out the factors that determine mobile phone usage in rural areas. Two factors that determine technology acceptance and use were identified: Perceived Usefulness (PU) and Perceived Ease of Use (PEU). A cross sectional research design was employed for this study using questionnaire as a data collection technique. Using the Statistical Package for the Social Science (SPSS) V15, the findings showed that socio-demographic factors such as age, gender, status, level of education, occupation, income, and social influence are the major determinants of mobile phone ownership and usage in rural areas. It also showed that age and gender affect the perceived benefit and satisfaction of mobile phone in rural communities. It is believed that policy makers will find it helpful if they understood rural inhabitants’ perception and attitude toward mobile phone.