Modeling the Ukrainian consumption


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Consumption is a fundamental determinant of the economic success. Consumer spending is approximately 70 percent of the Gross domestic product (GDP). It is common to divide consumer spending into nondurables (clothing and food), durables (“large” goods, which are not purchased very often), and of course services (day care, banking, medical). The way to identify how the economy influences consumption is to look at specific economic cycles. At the top of the economy (when the economy is strong), people reaction is physically powerful, and consumers spend money freely. When the economy falters, confidence falls; consumers cut back on the spending and conserve their money. They stop buying, getting out of debt and focus on saving money. Understanding consumption is vital to the implementation and development of marketing strategies. The purpose for this empirical research is to review main indicators, which influence on consumption and identify methodological issues in need of resolution, and present possible approaches that may prove helpful in resolving those issues. The growth of interest in modeling consumption has led to behaviorally conceptual models in which selection dynamics play a vital role. The authors introduce two empirical models, which demonstrate correlation between macroeconomic indicators, social factors and Consumer price index (CPI). The first conceptual model shows that the CPI is a straighter measure than per capita Gross domestic product of the standard of living in Ukraine. By including a wide range of thousands of services and goods with the basket (fixed), the CPI can obtain a precise estimate of the cost of living. The second empirical model shows the interdependence of economic indicators (CPI, GDP, and Average wage index (AWI)) and social factors (gender, age, location).

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    • Figure 1. The impact of 14 components on CPI
    • Figure 2. The impact of 14 components
    • Figure 3. The impact of 14 components
    • Figure 4. The impact of 14 components
    • Table 1. Data variables (economic and social indicators)
    • Table 2. Calculations of the result
    • Table 3. Principal components analysis
    • Table 4. Component weights
    • Table 5. Principal Components
    • Table A1. Input data (Economic and Social Indicators)