Here is another set of models I ran on economic indicators which support my earlier claims from previous posts.
Below are the results of running a linear regression model on various economic data (obtained from the Bureau of Economic Analysis [BEA] government site) from 1947 to the present solving for the Gross Domestic Product (GDP) variable:
Adjusted R2 1.00
Term Coefficient 95% CI SE t statistic DF p
Intercept 27.19 -205.03 to 259.42 115.619 0.24 50 0.8150
Population 0.3053 -0.9047 to 1.5152 0.60240 0.51 50 0.6146
Unemployment -9.103 -25.583 to 7.377 8.2047 -1.11 50 0.2725
Inflation -0.04267 -5.29017 to 5.20484 2.612572 -0.02 50 0.9870
Debt -0.1244 -0.2315 to -0.0173 0.05331 -2.33 50 0.0237
Tax Receipts -0.1041 -0.6123 to 0.4041 0.25301 -0.41 50 0.6825
Gov Spending 0.7386 0.2151 to 1.2620 0.26060 2.83 50 0.0066
Budget -0.1211 -0.7680 to 0.5258 0.32208 -0.38 50 0.7085
Trade Deficit 0.3913 0.0034 to 0.7793 0.19314 2.03 50 0.0481
Consumer Spending 0.9912 0.4034 to 1.5790 0.29265 3.39 50 0.0014
State Deficit 1.486 -0.019 to 2.990 0.7491 1.98 50 0.0528
State Social Payment 0.9698 -2.5630 to 4.5025 1.75886 0.55 50 0.5838
Gov Social Benefits -0.897 -2.120 to 0.326 0.6088 -1.47 50 0.1469
Personal Income 0.3691 -0.0767 to 0.8150 0.22198 1.66 50 0.1026
The economic parameters used to model GDP over the past 64 (n) years are: the U.S. population, the unemployment rate, the inflation rate, the federal government debt, federal government tax receipts, federal government spending, the federal government budget size, the trade deficit, consumer spending, state government deficits, state government spending on social benefits, federal government spending on social benefits, and personal income. The intercept value in the above table is not a parameter – it is the value of GDP (in billions of dollars) if all other parameters equal zero. These economic parameters are denoted in the above table.
The R² statistic illustrates how closely the linear regression model resembles a straight line (the ideal condition). If R² equals one then the model is 100% linear and the parameters correlate 100%. On the other hand, if R² is equal to zero then there is no correlation and the data in the linear regression model is completely random. T statistics reveal which of the economic parameters has the best correlation to the parameter being tested (GDP in this case). The higher the absolute value of the t statistic, the better the correlation the corresponding economic parameter has to the tested variable (GDP in this case). If a coefficient value of an economic parameter is positive then it trends in the same direction of the tested variable (GDP in this case). If a coefficient value is negative then the corresponding variable trends in the opposite direction of the tested variable (GDP in this case). It is time to do some math to prove higher taxes and government spending cripple economies. What economic parameters have the biggest effect on GDP?
Consumer spending has the biggest positive impact on GDP and economic growth. Government spending can increase GDP as well, but increased tax receipts have a negative effect. Unemployment, deficit spending (Debt), government expenditures for social benefits, and increased federal budgets all have a negative effect on GDP. An increased trade deficit also increases GDP – it means consumers and both the federal and state governments are spending more money to import products including oil (our biggest import). These results are not surprising and support conservative fiscal claims for decades.
My Book: Is America Dying? (Amazon.com, Barnes and Noble)