What is the most important determinant of consumer spending

18.10.2020 By Fenrizuru

what is the most important determinant of consumer spending

What are the determinants of consumer spending?

The five main determinants of consumption spending are current disposable income, household wealth, expected future income, the price level and the interest rate. The most important determinant is current disposable income. Also, how do you calculate consumer spending? Sep 27,  · Changes in any of these components will affect consumer spending. The most important determinant is disposable income. 5 ? That's the average income minus taxes. 6 ? Without it, no one would have the funds to buy the things they need. That makes disposable income one of the most important determinants of vitoriayvitorianos.comted Reading Time: 6 mins.

The following article what does a ladybug bite look like guide you about the top nine factors determining consumption spending. The factors are: 1. Income distribution 2. The rate of interest 3.

Liquid assets and wealth 4. Expected future income 5. Sales effort 6. Capital gains 7. Consumer credit 8. Fiscal policy 9.

Other factors. Keynes believed that the MPC of low income groups would be higher than that of high income groups. So, aggregate demand could be stepped up by a policy of income redistribution — i. Changes in the distribution of income may alter consumption demand if high-income households consume a smaller proportion of disposable income than do low-income households.

It has long been supposed that an increase in the rate what is the most important determinant of consumer spending interest would lead to an increase in savings and, therefore, a reduction in consumption. Other things remaining the same, the lower the real interest rate, the greater is the amount of consumption expenditure and the smaller is the amount of saving. This opportunity cost arises regardless of whether a person is a borrower or a lender.

For a borrower, increasing consumption this year means paying more interest next year. For a lender, increasing consumption this year means receiving less interest next year. The effect of the real interest rate on consumption expenditure is an example of the principle of substitution. If the opportunity cost of an action increases, people substitute other actions in its place. Both the supply of liquid assets money, securities, or bonds and the wealth represented by existing quantities of durable goods may influence consumer expenditures.

Consider liquid assets first. Many observers contend that a greater stock of liquid assets enhances feelings of economic security and may thereby prompt greater consumption expenditures. That is, if two households have the same disposable income on consumption goods and services. An increase or decrease in the amount of sales effort may affect the total volume of consumer expenditures, given the level of income.

Advertising has the effect of shifting demand from one product to another. But, as Ackley has put it, whether as a result of advertising, aggregate consumption, expenditure will fall or not is debatable. It is the matter of empirical statistical test and verification. Keynes also recognised that consumption spending might be influenced not only how to make a body wash income but by capital gains.

The terms of consumer credit have often been important in influencing consumption behaviour in respect of durable goods like automobiles, TV sets, radios, etc. The extent to which consumers can borrow to finance purchases may affect their levels of consumption.

The demand for durable goods like appliances and automobiles is particularly sensitive to the availability of credit, because such goods involve sizable expenditures. A high level of debt may dampen consumer demand, because repayment in the future will be necessary, making less funds available for current consumption.

Tax and transfer payments also affect consumption. An increase in indirect taxes raise commodity prices what is mr clean magic eraser may lead to a fall in the demand for the taxed commodity. Likewise an increase in income tax may reduce the disposable income of individuals and may lower total consumption expenditure.

These include certain motives to consumption such as enjoyment, short-sightedness, generosity, miscalculation, ostentation and extravagance. Keynes calls these subjective factors. The real interest rate, which is the opportunity cost of consumption cost of consumption, determines the long-run allocation of disposable income between consumption and how to watch abc family. Disposable income is the key short run influence on consumption and saving.

It may also be noted that since consumption and saving are two mirror image concepts, all the factors which determine consumption spending are also the determinants of saving behaviour.

If and when there is a change in income there is movement along the consumption line. But if there is a change in any other variable the whole consumption line will shift to a new position. Article Shared by Nipun S. Related Articles.

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Consumer Spending is a derivative of the disposable income that the household is left with once the taxes are paid. Hence, the most important determinant of the Consumer spending would be level of disposable income. According to Keynes, the most important determinant of (or influence on) the level of Consumer Spending households undertake in a time period is disposable income. Disposable income is view the full answer Previous question Next question. The most important determinant of consumer spending is the level of income.

To browse Academia. Skip to main content. By using our site, you agree to our collection of information through the use of cookies. To learn more, view our Privacy Policy. Log In Sign Up. Download Free PDF. Yibeltal Meslie. Digvijay Pandey. Download PDF. A short summary of this paper.

Determinants of Household Consumption Expenditure. The right to food is fundamental and without it many other human rights cannot be enjoyed. Consumption is spending carried out by households and services in order to meet the needs of those who make these purchases. The proportion of household food consumption expenditure is often used as a benchmark determinant of the welfare level.

The main core objective for this study was to determine the factors those affect household food expenditure in case of Tepi Town. A total of households were included in the present study using simple random sampling technique from the Andenet kebele.

Cross- sectional design was appropriate for this study. Primary source of data was employed collected from households. Descriptive and inferential statistics were applied. The descriptive statistics revealed that the households spend on food per monthly with minimum of and maximum of birr while, the mean of household for food expenditure was However, age, occupation, religion, mother education level, father education level, is there high price of food, reason for high price change and decision making were not found to be significant effect to household food expenditure per monthly at study area.

All the assumption of regression analysis was satisfied. Normality, Constant variance, absence of Multicolinearity, linearity and absence of autocorrelation were satisfied due to formal tests and diagnostic plots. Finally, study recommended that advisable for being educator and also households to improve their income level per month by involving in various different activities that help them generate additional income.

However, the accessibility and availability of food in the desired quantity and quality throughout a given year remains a dream for many people around the world [1]. Food is important of human need and consumed in large number in developing and developed country.

The proportion of household food consumption expenditure is often used as a benchmark determinant of the welfare level [2]. Consumption is the most important component of national income accounting and the aggregate demand. It is the ultimate economic activity on which the welfare of the economy depends and constitutes a major portion of disposable income of the households on micro economic level [3].

Consumption is spending carried out by households and services in order to meet the needs of those who make these purchases [4]. Food security is a broad concept, encompassing issues related to the nature, quality, and security of the food supply as well as issues of food access. The world has been facing a paradox of widespread food insecurity and malnutrition amid net food surpluses.

Increased food supplies do not automatically enhance access to food by the poorer groups of society [5]. At food expenditure levels reported in the IES, one in five households meets their average dietary energy cost.

Effect of the number of family dependents on the expenditure of poor households. The variable number of family dependents shows that the value of Probability less than 0. Demographic factors such as low family planning and low land holding size compared to family size, due to weakness of rural administration, low rural infrastructure [5]. These findings have policy implications for livelihoods, household welfare and overall development.

For livelihoods, there is the need for economic empowerment of poor rural farming households to enable them caters for their food needs [8]. Therefore, an increase in cost of production may lead to less farm income and may indirectly affect farm household food security status. The third indicator, the transportation cost is also negatively associated with food security status [9]. According to economic theory and observed behavior age has negative effect on consumption.

The study also demonstrates that as the age increases consumption decrease. According to Life cycle hypothesis, when age increase saving of individual increases more rapidly this will leads to reduction in consumption.

There is also positive relationship exists between gender, education and family structure with household consumption. The study found that education has positive effect on consumption. Socio-economic factors such as low level of income income constraint , low level of education, low level of access to new technology such as improved seeds, chemical fertilizer, herbicide, pesticide, high expenditure for social ceremonies and celebrations.

Demographic factors such as low family planning and low land holding size compared to family size, due to weakness of rural administration, low rural infrastructure [11]. Similarly, the households with bigger size of land holding, nearness to road heads and markets, and the members having off-farm and non- farm occupation contributed positively to food security whereas bigger household size contributed negatively to the food security [12].

Using a national household survey and a newly established food security scale, socio- demographic factors affecting the level of household food insecurity in Mexico were identified. Households more likely to be food in secure include those with younger, less-educated household heads, headed by single, widowed or divorced women, with disabled household members, with native language speakers, with children, as well as rural and lower-income households. The number of family has a positive and very significant effect on the household expenditure with the estimator parameter value of 4.

This means that the number of households determines more on the rise or fall in line with the household expenditure amounted to 4. This can be understood because more family members are increasing the household expenditure, especially for the daily needs of each individual in the family [14]. Education significantly affected access to enough food positively.

The more the head of household is educated the more the household is likely to access enough food. Educated household heads were more likely to be absorbed in the labor market and would get remunerations that would improve their access to enough food [15]. According to the results of this study, we can expect that livestock development programs such as training of farmers in animal husbandry would improve livestock productivity and, thus, increase food security [16].

Marital status had a mean 0. With a calculated mean of 0. The findings clearly suggest that education, gender, age of household head and household size affect both mild-to-moderate food insecurity as well as the experience of severe household food insecurity in the study area. Additionally, household production of vegetables, low dependency ratio, steady income source such as those from formal employment as well as household receipts of social grants and remittances were associated with lower levels of mild- to-moderate food insecurity [19].

A multiple regression model was used to explain responses in monthly expenditures to socio-economic factors. Household income, household size, the number of people who are employed, employment status, and the educational attainment of the household head were found to exert a strong positive impact on household expenditure.

The marital status of the household head was associated with a negative impact on household expenditure. The gender and age of the household head had no impact on the variations in household expenditure. The results of this study contribute to the understanding of township residents by analyzing the socio-economic factors associated with household expenditure [20].

However, household income has a relatively smaller effect in magnitude as compared to the rest of these factors. Furthermore, the results show that the relationships differ along the quintiles. In other words, some factors had a significant and higher effect in the lower quintile compared to the higher quintile [21]. This study attempt to explore the factors those affect food expenditure in case of Tepi town. The main objective of this study is to determine the factors those affect household food expenditure.

DATA AND METHODS This deals with detailed description about study area, source of data, study population, sampling technique, study variables, sample size determination and study design explanation about the theory behind the methods of and models for the analysis. Sheka is bordered on the south by Bench-Maji, on the west by the Gambela Region, on the north by the Oromiya Region, and on the east by Kaffa.

Our target population for this study is households who live in Tepi Town in Andenet Kebele. For this study, we use simple random sampling techniques by selecting appropriate sampling size from the population in Tepi town in case of Andenet Kebele.

The goal is to include sufficient numbers of subjects so that statistically significant results can be detected. In this study, researcher collected the data from the households directly in a particular time primary data. Here are some explanatory variables with their categories that affect household average monthly food expenditure. Therefore, the independent variables included in this study were list out below Table 1. In descriptive statistics the statistician tries to describe a situation.

Once data is collected, the researcher must organize and summarize them. Finally, the researcher needs presenting the data in some meaningful form, such as charts, graphs, or tables.

Multiple Linear Regression Model Multiple linear regression models are used to model the relationship between a single dependent variable response variable and more than one independent variable. Multiple linear regression is required so that the dependent variable to be continuous and the independent variable to be discrete, continuous and categorical. In the model of multiple linear regressions, response variable is a linear function of the k explanatory variables and of a statistical error term.

The model also has an intercept. The ordinary least square estimation can be work as after a certain procedures. Autocorrelation occurs when the residuals are not independent from each other. It occurs when several independent variables correlate at high levels with one another. Hypothesis Testing for ANOVA Adequacy of the model in multiple linear regressions can be checked by testing the regression coefficient associated with the independent variable.

The explanatory variables corresponding to such regression coefficients are important for the model. Rejecting the null hypothesis implies that ith independent variable has statistically significant contribution to the model. Step 5: Make conclusion 2. In this study, descriptive analysis and multiple regression analysis were employed to identify the risk factors. Data analysis was presented in this study based on a total of households. The descriptive statistics revealed that the households spend on food with minimum of and maximum of birr while, the mean of household for food expenditure was Table 2.

The present or absent of auto correlation checked by Durbin Watson test DW.