Empirical Econometrics Project Using E views
The methods of econometric are used in the attaining the parameters of the initial mathematical coefficient form of the relationships of economic. The adoption of the statistical methods such as regression analysis, linearity, autocorrelation etc. are used to explain the phenomenon of the economic and used as methods of econometrics. The behavior of the relationships of economic are basically depicted by econometrics as opposed to the mathematical formulations which do not Econometric model used to simplify the representation of the views. The representation contains the parts which are variables, independent and dependent under the study phenomena. The theory reveals the rise in the housing demand is associated with the inflation that leads the prices of the house hence the need for building the new housing, the mortgages are not index linked.
However, with the absence of the land prices data, the use of the lagged stock of housing that specifying in the housing starts equation. The theory also added that there is side input for the housing prices potential in-line with the needs rather than what the US housing market expects. The application of this theory to the econometric and economic analysis in the forecasting` and evaluation of economic phenomenon and behavior. The problem to be evaluated involves; supply, demand, investment, consumption, and production. The activity of the housing has a direct effect on the rates of the mortgage. Housing costs increase when the interest rates increases which in turn leads to a reduction in the qualified number of borrower person. Hence, there is a decrease in the sales of home and housing starts.
In another hand, the interest rates when is low leads to the affordability of the housing and leading to sales of the home and housing starts to increase. The data for housing is very vital in the bonding market effects. The adjustment is mainly used to make sure the element of stochastic in the real data which leads to the data observed determination. The data from this model is basically a random sample that tools from statistical are needed to analyze. The econometric model application is to the particular parts of the econometric theory and challenges such as production, demand consumption, and supply. It basically applies the econometric theory tools for the evaluation of the forecasting the behavior and phenomenon of economic.
Data collection. The phenomenon is depicted as a whole: the happening of the phenomenon cannot be put in terms of data. Therefore, it is expressed as the conclusions as for the correct or appropriateness. The true results are based on average: the data collected in the analysis most of the time are interpolated or averaged in terms of time series, probability or regression. The results that are obtained from the analysis of the interpolated data only true on average but in a real sense, there are data that are more than the average value and other lower. Therefore, average only shows the trend but not the true picture of each item. In this indications, the observed error of uncertainty is identical to all.
The distribution of the error term is independently and there is no correlation in the dependent variables observation. • Limitation; autocorrelation or serial correlation, and spatial correlation. Analysis of E-View The accepted measure of the economic output is a real gross domestic product (GDP). According to the real GDP, the largest expenditure is consumption, the spending of the government, relative gross investment and the exports net. D. dependent var 2,585. 986 Log likelihood 1,556. 687 F-statistic 83,196. 72 Durbin–Watson stat 0. C 22. 0000 D(RPDI) 0. 0000 R2 0. 182581 Mean dependent var 32. 18062 Adjusted R2 0. The F-statistic obtained after autocorrelation was 57. 18 and the t-starts were 9. 83 and 7. 56 for C and RPDI respectively. Limitations The test of Durbin Watson possesses a challenge in serially correlated in only first-order autocorrelation is possible. Civilian unemployment rate, 1972–2015 [Percent 1; monthly data seasonally adjusted, except as noted] Year or month All civilian workers Males Females Both sexes 16–19 years By race Hispanic or Latino ethnicity 3 Women who maintain families 4 Total 16–19 years 20 years and over Total 16–19 years 20 years and over White 2 Black or African Ameri-can 2 Asian 2 1972.
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