Below are the results of a running 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 consumer spending economic variable:
Adjusted R2 1.00
Term Coefficient 95% CI SE t statistic DF p
Intercept -39.02 -139.68 to 61.64 50.115 -0.78 50 0.4398
Population 0.2086 -0.3167 to 0.7340 0.26156 0.80 50 0.4288
Unemployment 2.502 -4.734 to 9.737 3.6022 0.69 50 0.4906
Inflation 0.4412 -1.8424 to 2.7248 1.13692 0.39 50 0.6996
GDP 0.1883 0.0766 to 0.2999 0.05559 3.39 50 0.0014
Debt 0.05213 0.00527 to 0.09899 0.023331 2.23 50 0.0300
Tax Receipts 0.005178 -0.216671 to 0.227026 0.1104516 0.05 50 0.9628
Gov Spending -0.08237 -0.32702 to 0.16228 0.121803 -0.68 50 0.5020
Budget 0.2829 0.0122 to 0.5536 0.13476 2.10 50 0.0408
Trade Deficit -0.5131 -0.6115 to -0.4147 0.04901 -10.47 50 <0.0001
State Deficit -0.1945 -0.8733 to 0.4843 0.33794 -0.58 50 0.5675
State Social Payment 3.814 2.714 to 4.915 0.5479 6.96 50 <0.0001
Gov Social Benefits -0.7581 -1.2581 to -0.2582 0.24890 -3.05 50 0.0037
Personal Income 0.4576 0.3061 to 0.6091 0.07543 6.07 50 <0.0001
The economic parameters used to model consumer spending 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, 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 consumer spending (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 (Consumer Spending 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 (Consumer Spending in this case). If a coefficient value of an economic parameter is positive then it trends in the same direction of the tested variable (Consumer Spending in this case). If a coefficient value is negative then the corresponding variable trends in the opposite direction of the tested variable (Consumer Spending 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 consumer spending?
Increased personal income, GDP, the federal deficit, and federal budget levels lead to more consumer spending. When times are good not only do individuals spend more money the federal government also spends more. Increased federal government payments in social benefits and increased trade deficit levels lead to lower consumer spending (in other words bad economic times).
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