Report on the estimated model

Report on the estimated model

Introduction

Consumer spending can be defined as the everyday purchase done by the household to fulfil daily needs. In this case, it intensely relies upon both the good and the services which every person consume in each day. Through the definition, it is easy to assert that each person in the universe is a consumer and thus each of these goods and services which we purchase everyday creates the demand which makes and keep many companies earn profit and able to run each day operation a such as hiring new workers. The paper aims at forecasting and testing on the accuracy of univariate time-series model to analyze the Consumer expenditure consumption in the US through the use of forecast sample for the period between the year 2009M01 to the year 2011M05.

Discussion on the nature of data

From the data, it is clear the most used determinant data is the disposable income. In this case, it is the average of the whole population income minus the government taxes. Without the determinant data, it becomes more than hard to get the funds which the citizens needed to make their daily purchases. Through this, the country disposable income is one of the significant determinants of the country demand.  Notably, from the data, it is clear that as the country income increases, it triggers the increase in need too.  If the country manufacturer tends to ramp up and thus to meet the market, they then end up creating jobs which leads to the workers’ wages also rising and thus it leads to more spending.  Considerably, if the market tends to increase, and the manufacturers don’t increase the supply, it leads to a situation whereby the price of products raises and thus leading to inflation.

From the data, it is clear that the second determinate of the United State Consumer expenditure is the income per capita. In this case, it plays a significant role in telling on the amount which each person tend to spend.  However, the country income measurement may tend to rise due to the increase in the country population.  Through checking on the income per person in the country, it becomes easy to reveal and measure if each of the people in the country standard of living is too improving.

On the other hand, the nature of data also reveals that income inequality seems to affect and determine the country expenditure. However,    in some cases, some people income may tend to rise in fast pace when compared to other others.  As per this consideration, the country economy ends up benefiting when most of the citizen’s benefits and gain tend to be oriented towards the low income earning families. The USA seems to have, in a way spent more of the significant share and thus impacting on the necessities of each dollar to a situation whereby these families have reached a living wage. In cases whereby the country income-earning moves towards the high incomes earners, then the state doesn’t benefit much in terms of growth.   In most circumstance, the high-income earners end up saving the excess in banks instead of spending and releasing the money back to the economy.

The nature of the available data also shows that each of the country levels of household debts also plays a significant role in country expenditure. These include credit card debt, the school loans and auto loans. By checking on D consumption graph, it is easy to check on the country current consumer debts and statistics. In this case, the data shows that the household debts of the country seem to have reached new record levels. Notably, the high health care cost in the USA appears to be one of the major causes of the country overwhelming debts when compared to other obligations.

Through checking on coefficient and variance available on Dickey-Fuller text equation, consumer expectation could be another determinant of the consumer expenditure. In this case, the hope of a consumer to earn money frequent builds the confidence to spend more and even the ability to pay now and then. Notably, this also relies on the consumer confidence index, which mainly concentrates in measuring the confidence which people have and the expectation for them to spend in future. It primarily depends upon the hope of situations such as inflation,  if the country consumers expect inflation to rise they may participate in buying more products to help in avoiding the unnecessary spending due to the increase on the prices in the future.

Econometric methodology used

The use of data set econometric method is seen to be the one used on analyzing the data.  The presence of analysis which is applied to get the variance, hypothesis and the coefficient is one of the significant evidence. Notably, the presence of the cross-sectional data, the time series data, the panel data and even the multidimensional panel data is much evident on the whole analysis. Considerably, these data sets seem to contain a kind of observation which is done over a period of time, such as the inflation which is determined by analysis of a period of several years.  Conversely, the presence of cross-sectional data which in this case shows the observations which are made on a single point in a moment is much evident. For example, the individual country income which is then given with a period of one year. The panel data, in this case, relies on both the use of the time series and the cross-section type of observations which is still evident on the data.

   How you chose your final specifications

Through analyzing on the available data and also considering on the coefficient and the variance evident from the data set, it is more than easy to come up with final expectations and how the country consumer expenditure may end up to be in future. In this case, through the use of statistical tools such as getting the null hypothesis which makes it possible to come with a conclusion about the data also help much in developing the final specifications. On the other hand, considering on the current data trends and even in participating in activities such as analyzing the available data to a more virtual form through the use of the graphs, charts, diagram and other statistical tools it also makes it easy to come up with a final conclusion about the country consumers expenditure. Notably, the current information and the ready researches already conducted by other scholars can give one an idea about the last expectation on the country and even making it easy to analyze and predict the consumer expenditure power in the future.

Limitation and weakness

From the above methodology used, there are limitations which may arise; for example, the act of analyzing the country per capita income may be biased due to many activities. For example, the methodology only relied on data from reliable legal income sources. However, there are other significant portion of income earners in the USA who earn money through other illegal business which may be hard to track and thus hard to determine their accurately making.  Through this, they end up spending much than expected from the data provided. Notably, the data available may be biased in case one uses to predict the country future expenditure expectation. For example due to the presence of dangerous outbreak of diseases and other technology development which may affect the lives of human beings and thus may lead change the overall standard of living as the country spends much on the medical bills.

Conclusion

From the above information, it is clear that USA expenditure seems to increase each day positively.  Through checking on factors such the good wages, high level of employment, senior healthcare facilities and the high standard of living deeply trigger the country future expenditure to rise. Notably, the presence of good and well-paying jobs and the skilled labour forces in the country which triggers good pay is another factor which portrays on the future high expenditure in the country.  Conversely, the gap between the rich and the poor is in a way reducing each day and thus clear evidence of how the company standard of living is rising daily, and thus much consumers spending power is expected in the future.