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 individual state social benefit economic parameter:
Adjusted R2 1.00
Term Coefficient 95% CI SE t statistic DF p
Intercept -0.05944 -18.68551 to 18.56664 9.273352 -0.01 50 0.9949
Population -0.006422 -0.103646 to 0.090803 0.0484051 -0.13 50 0.8950
Unemployment -0.2451 -1.5805 to 1.0903 0.66485 -0.37 50 0.7139
Inflation -0.1318 -0.5508 to 0.2872 0.20860 -0.63 50 0.5303
GDP 0.006232 -0.016470 to 0.028933 0.0113023 0.55 50 0.5838
Debt -0.0006797 -0.0097169 to 0.0083575 0.00449934 -0.15 50 0.8805
Tax Receipts 0.005785 -0.034988 to 0.046557 0.0202994 0.28 50 0.7768
Gov Spending -0.003856 -0.049047 to 0.041334 0.0224990 -0.17 50 0.8646
Budget -0.08189 -0.12832 to -0.03546 0.023116 -3.54 50 0.0009
Trade Deficit 0.05975 0.03221 to 0.08729 0.013711 4.36 50 <0.0001
Consumer Spending 0.129 0.092 to 0.166 0.0185 6.96 50 <0.0001
State Deficit -0.06561 -0.18947 to 0.05826 0.061669 -1.06 50 0.2925
Gov Social Benefits 0.2491 0.1782 to 0.3199 0.03527 7.06 50 <0.0001
Personal Income -0.08997 -0.11633 to -0.06360 0.013125 -6.85 50 <0.0001
The economic parameters used to model state government social benefit payments over the past 64 (n) years are: the U.S. population, the unemployment rate, the inflation rate, the U.S. Gross Domestic Product (GDP), federal government debt, federal government tax receipts, federal government spending, the federal government budget levels, the federal trade deficit, consumer spending, state government budget levels, 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 state government social benefit payments (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 (State Social Benefits 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 (State Social Benefits in this case). If a coefficient value of an economic parameter is positive then it trends in the same direction of the tested variable (State Social Benefits in this case). If a coefficient value is negative then the corresponding variable trends in the opposite direction of the tested variable (State Social Benefits 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 state government social benefit expenditures?
As the federal government increases social benefit payments so do the states. Also, as consumers increase spending and the trade deficit increases so do state social benefit payments. As personal incomes and state deficits increase then state social benefit payments decrease. It is strange how state government budget deficits and social benefit payments are inversely related in this model.
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