Consumer Demographics - Essay Example

Consumer Demographics Table of Contents Introduction 3 Analysis of Household Mortgage Expenditure Distributions in Fairfield and Leichhardt 4 Gini Coefficient 4 Chart Description 4 Conclusion 6 References 8 Appendix 9 Introduction The term, ‘demography’ is associated with the study of human population on the basis of diverse factors that differentiate one individual from other. For instance, the factors considered for demographic study include average earning as well as expenditure of a family that signifies their status in the society. It is in this context that demographic changes impose major influences on consumers. Consumers are changing their perspectives from the role of passive buyers. The phase of globalization herein signifies an active consumer participation in the emerging markets, where demographic change affects the population structure that is likely to influence consumer behaviour in turn (Martins & et. al., 2011). Based on the demographic perception, certain age groups decipher different choices than others. In addition to this, their choices of product are also influenced by cultural diversity. The buying behaviour of consumers is also mostly influenced by the income factor. Illustratively, luxurious products are preferred by people who have higher income than those who have lower income levels (Afzal & Pakistan, 2013). In order to justify the stated notions or speculations, the paper analyses the changes in household mortgage expenditure distributions and inequalities in Leichhardt and Fairfield from 2006 to 2011. The paper also aims to elaborate the distribution of household mortgage repayment differences in between the mentioned years. The Gini coefficients of the two cities, Leichhardt and Fairfield, have thus been analysed to measure inequality in the distribution of household mortgage expenditure. Analysis of Household Mortgage Expenditure Distributions in Fairfield and Leichhardt Gini Coefficient The Gini coefficient is used as a statistical measure associated with the income of a family that covers wages, salaries, income from properties, dividends, royalties and other sources of household incomes. The income earned by individuals is arranged according to certain ranking patterns and cumulative percentages of household are derived from it. Income and wealth are different from each perspective where income is defined as the total availability of monetary funds in the present situation whereas wealth refers to savings or other capital assets collected with the aim of future expenditure. Therefore, in a particular time period, the inequality in income would not affect the wealth distribution spontaneously within a demographic area. On the other hand, it is likely that a country with equal allocation of income has immeasurable inequality of wealth distribution. Contextually, Gini coefficient is important for the country, as it helps to determine the impact of welfare as well as expenditure distribution on consumers (Bosch & et. al., 2010). Chart Description The above chart indicates that income per head of Fairfield and Leichhardt increased in 2006 and growth was observed in the economic development of the concerned place. From the chart it can be analyzed that in 2006, Fairfield had a Gini coefficient of 31.87 but in 2011 it decreased to 28.48 (Chart 1 & 3 Appendix). This signifies the fact that in 2011, inequality in the distribution of household mortgage expenditure was more as compared to 2006 in Fairfield. On the other hand, in can be observed from the above data that Gini coefficient was 29.66 in Leichhardt in the same year. However, Gini coefficient has reduced to 27.54 in 2011that in turn affects income distribution of Leichhardt (Chart 2 & 4 Appendix). The Gini coefficient data of the two cities thus indicates existence of inequality in income distribution therein. Moreover, it can also be examined for the chart that the inequality with respect to income distribution is likely to increase the chances of economic gap in Fairfield as well as in Leichhardt. The Gini coefficient chart of 2011 indicates that though individual income was high with respect to the two places, inequality in income distribution is also high, which is likely to affect economic growth. The ownership of unequal income distribution was high that resulted in economic gap within the cities. The income and expenditure distribution are the two essential factors those affect the growth of the economy substantially. Additionally, income distribution defines the purchasing power of an individual that in turn is likely to influence their purchase behavior. The higher rate of income inequality and distribution thus results in inequality in labor market that in turn is likely to affect the condition of household and socio economic growth of the cities. The inequality of income affects status of an individual that makes rich richer and the condition of poor gets worsen. In case of Fairfield and Leichhardt, inequality of income signifies reduced expenditure. Therefore, developmental activities are affected in Fairfield and Leichhardt that in turn impose negative impacts on the growth of the concerned economy. The reduced household mortgage expenditure also prevents the government to collect taxes effectively that impedes the growth of country’s development (Chotikapanich, 2008). The job opportunity also decreases because the employers emphasize cost-cutting measures to keep their expenditure minimum. Thus, the overall growth of the cities decreased. The inequality in income distribution has the potential to increase mortality rate and mental illness within the country. Inequality of income hence reduces the overall investment in country that in turn signifies reduced household mortgage expenditure. As a result of which, people would avoid taking loan by mortgaging their household property. Therefore, Fairfield and Leichhardt household mortgage repayments were also decreased. The inequality of income has the potential to increase the rate of poverty that in turn has negative impacts on the growth of the economy. Additionally, national income and GDP of the cities is also affected by the changes in its demographic factors. Inequality in income thus results in under developed markets as well as it inhibits growth of economy. Furthermore, it can discourage and impede the growth of economic evolution as well as dampen the political growth, which in turn affects the accountability of the government. The increase in income inequality undermines the social and civic life as the rate of poor increases rapidly and reduced contribution to GDP affects growth of the respective country. Therefore, it can be analyzed that decrease in income of individuals is likely to affect the expenditure that in turn influences the growth of the economy (Haughton & Khandker, 2009). Conclusion From the above discussion it can be analyzed that lower percentage of Gini Coefficient signifies the economy to have a high percentage of inequality in income distribution. The lower range of Gini Coefficient thus imposes an impact on the resources of the city and is likely to develop certain problems, which might range from natural resources deprivation to health problems as well as increasing the rate of crime in the cities. Inequality in distribution of income restricts the citizens to acquire available goods and services. Additionally, the youth of the city fails to pursue their education that leads them to an uncertain future and results in family breakdown, poor parenting and other uncertainties. The in-depth analysis of chart hence indicates that increased income inequality is likely to affect the growth and development of the entire economy. Therefore, it is essential that the Fairfield and Leichhardt implement an effective strategy with respect to distribution system of income as well as wealth for protecting the country’s developmental activities and growth of the economy. Additionally, the strategies should focus on the social safety, coordination of the union to reduce the destructive nature of ecosystem and managing the tax wealth of these two cities so as to reduce the effects of low Gini Coefficient. References Afzal, N. & Pakistan, S., 2013. Impact of Customer Satisfaction and Demographic Factors on Customer’s Loyalty in Banking Sector of Pakistan. Middle-East Journal of Scientific Research, Vol. 18, No. 5, pp. 721-727. Bosch, A. & et. al., 2010. A Second Look at Measuring Inequality In South Africa: A Modified Gini Coefficient. School of Development Studies [Online] Available at: http://www.sds.ukzn.ac.za/files/WP%2058%20web.pdf [Accessed May 16, 2015]. Chotikapanich, D., 2008. Modeling Income Distributions and Lorenz Curves. Springer Science & Business Media. Haughton, J. H. & Khandker, S. R., 2009. Handbook on Poverty and Inequality. World Bank Publications. Martins, J. M. & et. al., 2011. Consumer Demographics and Behaviour. Springer Science & Business Media. Appendix Chart 1 Gini coefficient of Fairfield (2011) Chart 2 Gini Coefficient of Leichhardt (2011) Chart 3 Gini coefficient of Fairfield (2006) Chart 4 Gini coefficient of Leichhardt (2006) Read More