David Maneiro Project 312/12/191)The three variables I I'm using for this project are General National Income, GDP, and Unemployment Rate. For this project I will be using GDP as the depend variable and General National Income, and Unemployment Rate as the independent variables. GDP is the dependent variable because both of the independent variables are part of what makes up GDP2)Looking at the Graph between GDP and Unemployment Rate we see that there is a negative relationship, as UER goes up GDP goes down. This is to be expected as if people are out of jobs companies are not making as much product leading to a drop in GDP, and if people are jobless there will be a drop in demand for goods and services.Looking at the Graph between GDP and General National Income we see that there is a Positive relationship, as GNI goes up GDP goes down. This is to be expected as if people are making more money the demand for goods and service will increasing leading to an increase in GDP.3)Looking at the regressions we confirm that UER has a negative relationship with GDP and GNI has a positive relationship with GDP however looking that the t-values we see that both of thesevariables are insignificant, possible do the omission bias, as GDP has many factors that go into it.4)Looking at the Holt’s methods I found the alpha of UER and GNI to be 0.89 and 0.99 respectivelyand an initial forecast of 5.74 and 12041.47 using this information I forecasted the UER and GNI for Q3 2019 to be 3.6 and 21,618.22 respectively.5)331,190.24=(6.741e-03)21,618.22+(-5.931e-02)3.6+-8.011e+01Using the forecasted data from part 4 we forecasted the GDP for Q3 2019 to be 331,190.24Coding library(ggplot2)library(forecast)library(tseries)library(TSA)data=read.csv(file.choose(), header=TRUE)GDP=ts(data$GDPC1, frequency=4, start = c(2004,04))UER=ts(data$UER, frequency=4, start = c(2004,04))GNI=ts(data$GNI, frequency=4, start = c(2004,04))autoplot(GDP)+xlab("Year") + ylab("GDP")plot(UER)plot(GNI)autoplot(diff(log(GDP))*100)dars=diff(log(GDP)*100)dri = diff(UER)dps=diff(GNI)autoplot(UER)autoplot(GNI)r1=tslm(GDP~UER)r2=tslm(GDP~GNI)summary(r1)ress=residuals(r1)plot(ress)summary(r2)ress=residuals(r2)plot(ress)fc1=holt(UER, h=1)plot(fc1)summary(fc1)fc2=holt(GNI,