Economic trend
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Introduction
This report will include the study of economic activities in the United States of America. The study of the economy in the United States of America will be in the form of a trend, gross domestic product together with its components and the calculation of the cyclic comments of the economy. Pattern refers to the change or variations of the elements of the time series over a short time. The trend consists of variations and fluctuation of phenomena at low, medium and high-frequency jitter. The cyclic variation refers to the changes that occur on the economy that are naturally seasonal that corresponds to the business cycle.
Data analysis
The analysis of the data is going to be done by the use of the Hodrick Prescott filter. The Hodrich Prescott is a technique that is used to smoothen data, especially in the field of economy. This technique is essential as it is necessary to remove fluctuations of the short term variations. These type of changes occur in association with the data of the business cycle. When the short term variation is removed, one can obtain the trends of the long term period. This process is useful in carrying out some forecasting or prediction in relation to the business cycle (Hudson, 2007). Data smoothing is the procedure involves the use of the algorithm individual traces from the data like the noise to allow specific patterns of the data to appear clearly. Data smoothing can be done using the simple exponential, seasonal exponential, linear exponential and the random walk smoothing method.
The use of the excel will analyze the data in this particular research of the study of the economic activities in the United States of America. The excel of the data on the excel will enable us to get all the components of the Gross domestic product (GDP), investment and consumption over time. There are four main components in the study of the gross domestic product. The four parts include the net exports, business spending, government spending and personal consumption. Private or personal expenditure is usually denoted by C, which involves goods and services that are under use in a given country without any profit. The expense of investment is another component that is meant by ‘I’ which consists of the construction of offices and factories, the purchase of machines and other inventory of tangible goods (Hudson, 2007). The Component of government spending includes the salaries, salaries and wages that are paid to public servants, construction of infrastructure and another formal spending. Therefore the formula of getting g the GDP is given by:
GDP = C + I + G + (X-M)
Where C represents the rate of consumption, “I” the investment component, (X-M) represents the net export and “I” represents the expenditure of investment.
The focus will be on the GDP of the United States in the given number of years while analyzing its variations or fluctuations in terms of trends and cycles.
Figure 1.1: The GDP components of the year 2018
Figure 1.1 shows the components of the Gross domestic product in the year 2018. The trend the fluctuations are visualized in percentage measures of change with time over the given the year of 2018.
Figure 1.2 GDP components of the year 2019
Figure 1.2 shows the fluctuation rate of the Gross domestic product in the year 2019.
Figure 1.3: The relation between the GDP component of the year 2018 and the year 2019.
Figure 1.3 above shows the relationship between the Gross domestic product of the year 2019 and 2018.
Summary and conclusion
All the calculations about the components of the Gross domestic product have dined on the excel. Some of the parts under the gross domestic product that was being been being calculated include; the private consumption, total investments, government investments and the net export. The highest peak of the trend on the data fluctuation of the gross domestic product can be begotten using the visual impression from the three graphs above.
The correlation of the data between the two variables that is the Gross domestic product in the year 2018 and the year 2019 was also done using the excel. The correlation between the Gross domestic product of the year 2018 and the year 2019 is 0.99. The relationship of the value 0.99 is a clear illustration that the two variables under study have got healthy and positive correlation.
As per the graph of fig 1.3 that shows the relationship between the gross domestic product of the year 2018 and the year 2019, the rate of fluctuation of the year 2019 is higher than that of the year 2018 about the gross domestic product (Hudson, 2007), the fluctuations of the local variables ( gross domestic product of the year 2018 and 2019) are incredibly high at the first, second quartile and the third quartile of the year. The trend of the gross domestic product is also relatively constant in the middle parts of the year.
In accordance with the distribution of the data from the graphs, there is a persistent deviation of the gross domestic products from the GDP. In the year 2019 is when the united state of America experienced break-in volatility on the microeconomics, especially at the middle point of the year. The net export has got lesser volatility as compared to the general gross domestic product. The moderation of the violated in the united states of America a persistent as per the analysis of the data (Hudson, 2007). Therefore, as per the study and analysis of the distribution of the Gross domestic product in the united states of America, the cost or expenditure of personal spending is very high. The government should come up with the appropriate measures to ensure that the gross domestic product of the united states of America is very stable to avoid some economic crisis. The government should also reduce its spending within the nation. Appropriate measures should also be put in place to increase the rate of productivity in the united states of America. More industries should be established and allow the citizens to venture into various types of economical occupations.
Reference
Hoag, H. (2007). Thomas Hudson, president and scientific director, Ontario Institute for Cancer Research, Toronto, Canada. Nature, 446(7138), 946-946.