Tuesday, August 30, 2011
Economic Model Summary
What was learned from the economic models posted over the past several months?
• If the federal government raises taxes and receives more tax revenue it spends more money because the debt, budget and government spending continue to increase.
• Maximizing consumer spending does just as much to reduce the poverty level as increased government spending and debt.
• Government Social Benefits needs to be minimized. This economic parameter had the most significant negative impact on other economic parameters.
• Government budget deficits and debt need to be minimized. This economic parameter had the second most significant negative impact on other economic parameters.
• Population increases had little impact on economic parameters.
• State budget deficits and state social benefit payments had little overall impact on national economic parameters.
• Consumer spending needs to be maximized. This parameter had the most significant positive impact on other economic parameters.
• Personal income needs to be maximized. This parameter has the second most significant positive impact on other economic parameters.
• The trade deficit has a big impact on many economic indicators (some good and some bad).
• Economic parameters such as GDP, tax receipts, unemployment, inflation, and government spending had less of an impact on other economic parameters than one may suspect.
• Government spending is a leading cause for inflation and driving energy prices and healthcare costs higher.
These are just a few of the obvious observations. I will also post models in the future on other complex issues / problems including healthcare and climate change.
My Book: Is America Dying? (Amazon.com, Barnes and Noble)
Monday, August 29, 2011
Summary: The Relationship Between Taxes, Income, Debt, Spending, Social Benefits, and the Trade Deficit
This is summary of linear regression model results (posted over the past several weeks) on the relationship between taxes, income, debt, spending, social benefits, and the trade deficit. The following results are dependent on changing the fifth quintile’s effective tax rate from 13 to 17.5%, its income from 46,800 to 50,800 dollars, and its consumer spending rate from 36 to 40%. This models the result if the highest income bracket tax rate is increased from 35% to 39.5%.
• Federal government Tax Revenue will vary from 1.09 trillion to 1.26 trillion dollars. The model accuracy is perfect (R² = 1).
• Consumer Spending will vary from 12.2 trillion to 12.9 trillion dollars. The model accuracy is perfect (R² = 1).
• The federal government Effective Tax Rate will vary from 8.3% to 11.2%. The model accuracy is perfect (R² = 1).
• Federal government expenditures on Social Benefit spending will vary from 1.74 trillion to 2.13 trillion dollars. The model accuracy is near perfect (R² = 0.97).
• The national Debt will vary from 9.6 trillion to 11.5 trillion dollars. The model accuracy is perfect (R² = 1).
• The national Trade Deficit will vary from a loss of 441 billion to 813 billion dollars annually. The model accuracy is perfect (R² = 1). The trend results are similar if the trade deficit is adjusted for oil imports.
Similar results are achieved from another model that varies the effective tax rate from 8% to 11%, the first quintiles adjusted social benefits income from 17,800 dollars to 21,800 dollars, and the fifth quintiles adjusted social benefits income from 46,800 dollars to 50,800 dollars.
• Federal government expenditures on Social Benefit spending will vary from 1.8 trillion to 2.03 trillion dollars. The model accuracy is near perfect (R² = .97).
• The national Debt will vary from 9.15 trillion to 10.95 trillion dollars. The model accuracy is near perfect (R² = .99).
• The national Trade Deficit will vary from a loss of 725 billion to 881 billion dollars. The model accuracy is near perfect (R² = .98). The trend results are similar if the trade deficit is adjusted for oil imports.
Since consumer spending, income, and the tax rate are directly related – it makes sense to use all three when computing the tax rate. An example of a fair tax rate formula is: Tax Rate (TR) = Income (I) / (1 / (1 – Consumer Spending (CS))). After all, if the tax rate goes up and consumer spending goes down, it will adversely affect the economy.
Summary: If the federal government raises the income tax on the highest earners (fifth quintile) from 35% to 39.6%: tax revenues will go up nearly 170 billion dollars annually; consumer spending will go down 700 billion dollars; the effective federal income tax rate will go up from 8.3 to 11.2%; the federal government spending on social benefits will increase by 300 billion dollars; and the national debt will sore 1.9 trillion dollars. These results track if a separate model is created taking into account adjusted national incomes due to social benefits (entitlement spending). The bottom line – increasing taxes on the highest earners will only create higher social benefit spending, a much greater national debt, and much lower consumer spending that could cost the economy up to 2 million jobs. In other words, raising taxes is the main ingredient in a formula to create a recession. On the hand, there is an argument that increased taxes could both increase or decrease the trade deficit.
My Book: Is America Dying? (Amazon.com, Barnes and Noble)
• Federal government Tax Revenue will vary from 1.09 trillion to 1.26 trillion dollars. The model accuracy is perfect (R² = 1).
• Consumer Spending will vary from 12.2 trillion to 12.9 trillion dollars. The model accuracy is perfect (R² = 1).
• The federal government Effective Tax Rate will vary from 8.3% to 11.2%. The model accuracy is perfect (R² = 1).
• Federal government expenditures on Social Benefit spending will vary from 1.74 trillion to 2.13 trillion dollars. The model accuracy is near perfect (R² = 0.97).
• The national Debt will vary from 9.6 trillion to 11.5 trillion dollars. The model accuracy is perfect (R² = 1).
• The national Trade Deficit will vary from a loss of 441 billion to 813 billion dollars annually. The model accuracy is perfect (R² = 1). The trend results are similar if the trade deficit is adjusted for oil imports.
Similar results are achieved from another model that varies the effective tax rate from 8% to 11%, the first quintiles adjusted social benefits income from 17,800 dollars to 21,800 dollars, and the fifth quintiles adjusted social benefits income from 46,800 dollars to 50,800 dollars.
• Federal government expenditures on Social Benefit spending will vary from 1.8 trillion to 2.03 trillion dollars. The model accuracy is near perfect (R² = .97).
• The national Debt will vary from 9.15 trillion to 10.95 trillion dollars. The model accuracy is near perfect (R² = .99).
• The national Trade Deficit will vary from a loss of 725 billion to 881 billion dollars. The model accuracy is near perfect (R² = .98). The trend results are similar if the trade deficit is adjusted for oil imports.
Since consumer spending, income, and the tax rate are directly related – it makes sense to use all three when computing the tax rate. An example of a fair tax rate formula is: Tax Rate (TR) = Income (I) / (1 / (1 – Consumer Spending (CS))). After all, if the tax rate goes up and consumer spending goes down, it will adversely affect the economy.
Summary: If the federal government raises the income tax on the highest earners (fifth quintile) from 35% to 39.6%: tax revenues will go up nearly 170 billion dollars annually; consumer spending will go down 700 billion dollars; the effective federal income tax rate will go up from 8.3 to 11.2%; the federal government spending on social benefits will increase by 300 billion dollars; and the national debt will sore 1.9 trillion dollars. These results track if a separate model is created taking into account adjusted national incomes due to social benefits (entitlement spending). The bottom line – increasing taxes on the highest earners will only create higher social benefit spending, a much greater national debt, and much lower consumer spending that could cost the economy up to 2 million jobs. In other words, raising taxes is the main ingredient in a formula to create a recession. On the hand, there is an argument that increased taxes could both increase or decrease the trade deficit.
My Book: Is America Dying? (Amazon.com, Barnes and Noble)
Friday, August 26, 2011
Advanced Economic Data
The economic data in my last post included the effects of inflation, unemployment, the budget, debt, and the gross domestic product on our economy. The below data adds the effects of consumer spending on the results from 1930 to 2010 from yesterday’s data. The last two columns add the effects of housing and auto sales as well as the trade surplus/deficit numbers on the economy from 1960 to 2010. Each of the annual results is ranked in order from best to worst.
Year Administration Administration Rank Year Rank Year Result Year Result Year Rank
Lower is Better Higher is Better Higher is Better
Included Trade Deficit/Housing/Auto
1930 Hoover 67.5 71 0.139345797
1931 64 0.210419081
1932 FDR 62.53846154 74 0.105261784
1933 77 0.065927047
1934 78 0.055874251
1935 75 0.089663178
1936 72 0.12937271
1937 73 0.112178013
1938 60 0.284495172
1939 59 0.292502039
1940 53 0.338303809
1941 61 0.243776477
1942 69 0.173640032
1943 47 0.404796287
1944 15 0.838565937
1945 Truman 72.57142857 65 0.201738546
1946 81 0.013678973
1947 80 0.01763889
1948 79 0.039130755
1949 67 0.190822755
1950 66 0.197421359
1951 70 0.153934325
1952 12 0.877539585
1953 Eisenhower 16.125 1 0.995273461
1954 25 0.682557344
1955 2 0.987840742
1956 11 0.886158024
1957 24 0.68423737
1958 40 0.454862223
1959 10 0.904730878
1960 16 0.806800956 0.7849878 10
1961 JFK 11 17 0.779490145 0.743358727 13
1962 7 0.92143518 0.932567101 6
1963 9 0.905784462 0.922851096 7
1964 LBJ 5.2 4 0.970212036 0.984982067 2
1965 3 0.978814616 0.990796696 1
1966 6 0.966284763 0.977612794 4
1967 5 0.967106177 0.977930996 3
1968 8 0.920402421 0.933475042 5
1969 Nixon 17.25 14 0.845067242 0.835257479 9
1970 22 0.704881829 0.650154781 16
1971 20 0.732382156 0.689598547 14
1972 13 0.857633796 0.863472246 8
1973 Ford 42.25 23 0.686493028 0.62434431 19
1974 55 0.33211444 0.179404386 44
1975 57 0.321579972 0.173544939 45
1976 34 0.509598854 0.36580158 28
1977 Carter 47.75 38 0.48539981 0.35316351 30
1978 36 0.490971433 0.348099757 32
1979 54 0.332565903 0.180633892 43
1980 63 0.233279209 0.097806068 49
1981 Regan 35.25 56 0.321743838 0.153677774 47
1982 49 0.381772329 0.208356036 41
1983 35 0.503995857 0.348178555 31
1984 32 0.54773218 0.406056681 24
1985 28 0.597794466 0.492928298 20
1986 21 0.710379159 0.639846296 17
1987 31 0.566435225 0.44269449 23
1988 30 0.580800208 0.462933805 22
1989 Bush 45.25 33 0.521165415 0.383677149 25
1990 46 0.412307398 0.270617242 38
1991 50 0.355030984 0.156074549 46
1992 52 0.345444204 0.182286727 42
1993 Clinton 34.125 51 0.347354183 0.211766125 40
1994 45 0.427773702 0.305690265 35
1995 43 0.437206907 0.304397475 36
1996 42 0.441622034 0.347118254 33
1997 29 0.590670423 0.475517612 21
1998 18 0.779123193 0.7652657 11
1999 19 0.739476814 0.756822966 12
2000 26 0.633036039 0.626496742 18
2001 Bush 44.5 27 0.623196359 0.679603264 15
2002 58 0.309619948 0.219628872 39
2003 39 0.461385592 0.317257402 34
2004 44 0.436895133 0.372577876 26
2005 48 0.392233115 0.279763426 37
2006 41 0.448807255 0.354638429 29
2007 37 0.485572252 0.370304654 27
2008 62 0.243657754 0.101303216 48
2009 Obama 72 68 0.185875697 0.04675897 50
2010 76 0.085299188 0.017963418 51
My Book: Is America Dying? (Amazon.com, Barnes and Noble)
Year Administration Administration Rank Year Rank Year Result Year Result Year Rank
Lower is Better Higher is Better Higher is Better
Included Trade Deficit/Housing/Auto
1930 Hoover 67.5 71 0.139345797
1931 64 0.210419081
1932 FDR 62.53846154 74 0.105261784
1933 77 0.065927047
1934 78 0.055874251
1935 75 0.089663178
1936 72 0.12937271
1937 73 0.112178013
1938 60 0.284495172
1939 59 0.292502039
1940 53 0.338303809
1941 61 0.243776477
1942 69 0.173640032
1943 47 0.404796287
1944 15 0.838565937
1945 Truman 72.57142857 65 0.201738546
1946 81 0.013678973
1947 80 0.01763889
1948 79 0.039130755
1949 67 0.190822755
1950 66 0.197421359
1951 70 0.153934325
1952 12 0.877539585
1953 Eisenhower 16.125 1 0.995273461
1954 25 0.682557344
1955 2 0.987840742
1956 11 0.886158024
1957 24 0.68423737
1958 40 0.454862223
1959 10 0.904730878
1960 16 0.806800956 0.7849878 10
1961 JFK 11 17 0.779490145 0.743358727 13
1962 7 0.92143518 0.932567101 6
1963 9 0.905784462 0.922851096 7
1964 LBJ 5.2 4 0.970212036 0.984982067 2
1965 3 0.978814616 0.990796696 1
1966 6 0.966284763 0.977612794 4
1967 5 0.967106177 0.977930996 3
1968 8 0.920402421 0.933475042 5
1969 Nixon 17.25 14 0.845067242 0.835257479 9
1970 22 0.704881829 0.650154781 16
1971 20 0.732382156 0.689598547 14
1972 13 0.857633796 0.863472246 8
1973 Ford 42.25 23 0.686493028 0.62434431 19
1974 55 0.33211444 0.179404386 44
1975 57 0.321579972 0.173544939 45
1976 34 0.509598854 0.36580158 28
1977 Carter 47.75 38 0.48539981 0.35316351 30
1978 36 0.490971433 0.348099757 32
1979 54 0.332565903 0.180633892 43
1980 63 0.233279209 0.097806068 49
1981 Regan 35.25 56 0.321743838 0.153677774 47
1982 49 0.381772329 0.208356036 41
1983 35 0.503995857 0.348178555 31
1984 32 0.54773218 0.406056681 24
1985 28 0.597794466 0.492928298 20
1986 21 0.710379159 0.639846296 17
1987 31 0.566435225 0.44269449 23
1988 30 0.580800208 0.462933805 22
1989 Bush 45.25 33 0.521165415 0.383677149 25
1990 46 0.412307398 0.270617242 38
1991 50 0.355030984 0.156074549 46
1992 52 0.345444204 0.182286727 42
1993 Clinton 34.125 51 0.347354183 0.211766125 40
1994 45 0.427773702 0.305690265 35
1995 43 0.437206907 0.304397475 36
1996 42 0.441622034 0.347118254 33
1997 29 0.590670423 0.475517612 21
1998 18 0.779123193 0.7652657 11
1999 19 0.739476814 0.756822966 12
2000 26 0.633036039 0.626496742 18
2001 Bush 44.5 27 0.623196359 0.679603264 15
2002 58 0.309619948 0.219628872 39
2003 39 0.461385592 0.317257402 34
2004 44 0.436895133 0.372577876 26
2005 48 0.392233115 0.279763426 37
2006 41 0.448807255 0.354638429 29
2007 37 0.485572252 0.370304654 27
2008 62 0.243657754 0.101303216 48
2009 Obama 72 68 0.185875697 0.04675897 50
2010 76 0.085299188 0.017963418 51
My Book: Is America Dying? (Amazon.com, Barnes and Noble)
Monday, August 22, 2011
Economic Data Results
Below is the data that described and summarized in the last post.
Year Administration Administration Rank Year Rank Year Result
Lower is Better Higher is Better
1930 Hoover 67 70 0.130831887
1931 64 0.221734166
1932 FDR 61.84615385 71 0.122935228
1933 77 0.076671222
1934 78 0.049809404
1935 76 0.087318947
1936 72 0.121703976
1937 75 0.10023436
1938 56 0.311094304
1939 57 0.303852641
1940 54 0.334176301
1941 65 0.201564244
1942 69 0.150541944
1943 47 0.425730648
1944 7 0.916082866
1945 Truman 72.85714286 62 0.243494218
1946 81 0.009172218
1947 80 0.0120532
1948 79 0.028445666
1949 67 0.194375385
1950 68 0.178107058
1951 73 0.118795401
1952 13 0.858361589
1953 Eisenhower 17.75 1 0.994400033
1954 25 0.647240426
1955 2 0.98599563
1956 12 0.865117379
1957 26 0.640643105
1958 48 0.409641689
1959 10 0.889323577
1960 18 0.772019672
1961 JFK 13.33333333 20 0.73786751
1962 9 0.899980138
1963 11 0.880492743
1964 LBJ 5.2 4 0.959708924
1965 3 0.971483705
1966 6 0.957280896
1967 5 0.958452384
1968 8 0.902734896
1969 Nixon 19.25 16 0.815206674
1970 24 0.662566989
1971 23 0.695704785
1972 14 0.838745449
1973 Ford 47 27 0.638245657
1974 58 0.291196251
1975 61 0.269105837
1976 42 0.462022164
1977 Carter 53.5 45 0.450375938
1978 44 0.451813686
1979 59 0.288065432
1980 66 0.194419637
1981 Regan 37.25 60 0.274939679
1982 51 0.344763124
1983 39 0.489134255
1984 36 0.544792581
1985 30 0.609247419
1986 19 0.741096527
1987 32 0.593746561
1988 31 0.598178077
1989 Bush 47.75 37 0.524901208
1990 49 0.408674223
1991 52 0.341571053
1992 53 0.336825808
1993 Clinton 32.625 50 0.349906492
1994 46 0.445423691
1995 43 0.459736113
1996 41 0.466937537
1997 28 0.626830293
1998 15 0.83470193
1999 17 0.814179757
2000 21 0.728106057
2001 Bush 35.75 22 0.719220129
2002 40 0.474852286
2003 34 0.567047555
2004 35 0.554101245
2005 38 0.510451053
2006 33 0.582860235
2007 29 0.6187823
2008 55 0.314333976
2009 Obama 68.5 63 0.226752781
2010 74 0.103257823
My Book: Is America Dying? (Amazon.com, Barnes and Noble)
Year Administration Administration Rank Year Rank Year Result
Lower is Better Higher is Better
1930 Hoover 67 70 0.130831887
1931 64 0.221734166
1932 FDR 61.84615385 71 0.122935228
1933 77 0.076671222
1934 78 0.049809404
1935 76 0.087318947
1936 72 0.121703976
1937 75 0.10023436
1938 56 0.311094304
1939 57 0.303852641
1940 54 0.334176301
1941 65 0.201564244
1942 69 0.150541944
1943 47 0.425730648
1944 7 0.916082866
1945 Truman 72.85714286 62 0.243494218
1946 81 0.009172218
1947 80 0.0120532
1948 79 0.028445666
1949 67 0.194375385
1950 68 0.178107058
1951 73 0.118795401
1952 13 0.858361589
1953 Eisenhower 17.75 1 0.994400033
1954 25 0.647240426
1955 2 0.98599563
1956 12 0.865117379
1957 26 0.640643105
1958 48 0.409641689
1959 10 0.889323577
1960 18 0.772019672
1961 JFK 13.33333333 20 0.73786751
1962 9 0.899980138
1963 11 0.880492743
1964 LBJ 5.2 4 0.959708924
1965 3 0.971483705
1966 6 0.957280896
1967 5 0.958452384
1968 8 0.902734896
1969 Nixon 19.25 16 0.815206674
1970 24 0.662566989
1971 23 0.695704785
1972 14 0.838745449
1973 Ford 47 27 0.638245657
1974 58 0.291196251
1975 61 0.269105837
1976 42 0.462022164
1977 Carter 53.5 45 0.450375938
1978 44 0.451813686
1979 59 0.288065432
1980 66 0.194419637
1981 Regan 37.25 60 0.274939679
1982 51 0.344763124
1983 39 0.489134255
1984 36 0.544792581
1985 30 0.609247419
1986 19 0.741096527
1987 32 0.593746561
1988 31 0.598178077
1989 Bush 47.75 37 0.524901208
1990 49 0.408674223
1991 52 0.341571053
1992 53 0.336825808
1993 Clinton 32.625 50 0.349906492
1994 46 0.445423691
1995 43 0.459736113
1996 41 0.466937537
1997 28 0.626830293
1998 15 0.83470193
1999 17 0.814179757
2000 21 0.728106057
2001 Bush 35.75 22 0.719220129
2002 40 0.474852286
2003 34 0.567047555
2004 35 0.554101245
2005 38 0.510451053
2006 33 0.582860235
2007 29 0.6187823
2008 55 0.314333976
2009 Obama 68.5 63 0.226752781
2010 74 0.103257823
My Book: Is America Dying? (Amazon.com, Barnes and Noble)
Making Sense of Economic Data
For years pundits have argued which years have been the best or worst in our nation’s economic history. Pundits have argued which president led our economy through the best or worst times. Today, we continually hear the Obama administration claim we are going through the worst recession since the Great Depression. Is this true?
To answer these questions I have tried to compare our economic strengths and weaknesses annually from 1930 to the present. I have combined yearly unemployment, inflation, federal budget levels, federal debt levels, and our gross domestic product (GDP) into one metric or figure of merit. These are arguably the most critical yearly statistics to measure an economies wellness or sickness. The data is fitted into a normal distribution curve and ranked in order from best to worst economic years.
The presidential administrations from 1930 to the present ranked as follows (ratings are in brackets []. Each of 81 years is ranked 1 through 81. The ranking indicates the average yearly ranking for each administration.): first, Lyndon Johnson (LBJ) [5]; second, John Kennedy (JFK) [13]; third, Dwight Eisenhower [17]; fourth, Richard Nixon [19]; fifth, Bill Clinton [33]; sixth, George W. Bush [37]; seventh, Ronald Reagan [38]; eighth, Gerald Ford [47]; ninth, George H.W. Bush [48]; tenth, Jimmy Carter [54]; eleventh, Franklin Roosevelt (FDR) [62]; twelfth, Herbert Hoover [67]; thirteenth, Barack Obama [68]; fourteenth, Harry Truman [72]. This data can be misleading because it does not account for trends. For instance, Eisenhower could be credited with stabilizing the economy that benefited JFK and LBJ. Reagan was responsible for getting the Carter mess under control. And yes, although George W. Bush is ranked 6th, the economic status under his guidance got worse each year. Thus, he could have benefited from Clinton’s leadership and could be responsible for hurting Obama’s numbers.
The top 10 years according to this statistical average are as follows: 1. 1953 (.994); 2. 1955 (.986); 3. 1965 (.971); 4. 1964 (.960); 5. 1967 (.958); 6. 1966 (.957); 7. 1944 (.916); 8. 1968 (.903); 9. 1962 (.900); and 10. 1959 (.889). The ratings in parenthesis are a percentage as to where each year lies in the normal distribution curve. A rating of 0.50 is average, and any number higher than that is above average and any number lower than that is below average. The 10 worst years are as follows: 1. 1946 (.010); 2. 1945 (0.12); 3. 1948 (.028); 1934 (.050); 5. 1933 (.077); 6. 1935 (.087); 7. 1937 (.100); 8. 2010 (.103); 9. 1951 (.119); 10. 1936 (.122). In essence, the figure of merit for 1953 is at the 99.4 percentile while 1946 is at the 1 percentile in terms of economic stability.
Here is a list of each administrations best and worst years. Barack Obama: 2009 (.227), 2010 (.103); George W. Bush: 2001 (.719), 2008 (.314); Bill Clinton: 1998 (.837), 1993 (.350); George H.W. Bush: 1989 (.525), 1992 (.334); Ronald Reagan: 1986 (.741), 1981 (.274); Jimmy Carter: 1978 (.452), 1980 (.194); Gerald Ford: 1973 (.638), 1975 (.269); Richard Nixon: 1972 (.839), 1970 (.663); LBJ: 1965 (.971), 1968 (.903); JFK: 1962 (.900), 1961 (.738); Dwight Eisenhower: 1953 (.994), 1958 (.410); Harry Truman: 1952 (.858); 1946 (.010); FDR: 1944 (.916), 1934 (.050); Herbert Hoover: 1931 (.222), 1930 (.130).
I will post the entire results of this analysis in my next blog post.
My Book: Is America Dying? (Amazon.com, Barnes and Noble)
To answer these questions I have tried to compare our economic strengths and weaknesses annually from 1930 to the present. I have combined yearly unemployment, inflation, federal budget levels, federal debt levels, and our gross domestic product (GDP) into one metric or figure of merit. These are arguably the most critical yearly statistics to measure an economies wellness or sickness. The data is fitted into a normal distribution curve and ranked in order from best to worst economic years.
The presidential administrations from 1930 to the present ranked as follows (ratings are in brackets []. Each of 81 years is ranked 1 through 81. The ranking indicates the average yearly ranking for each administration.): first, Lyndon Johnson (LBJ) [5]; second, John Kennedy (JFK) [13]; third, Dwight Eisenhower [17]; fourth, Richard Nixon [19]; fifth, Bill Clinton [33]; sixth, George W. Bush [37]; seventh, Ronald Reagan [38]; eighth, Gerald Ford [47]; ninth, George H.W. Bush [48]; tenth, Jimmy Carter [54]; eleventh, Franklin Roosevelt (FDR) [62]; twelfth, Herbert Hoover [67]; thirteenth, Barack Obama [68]; fourteenth, Harry Truman [72]. This data can be misleading because it does not account for trends. For instance, Eisenhower could be credited with stabilizing the economy that benefited JFK and LBJ. Reagan was responsible for getting the Carter mess under control. And yes, although George W. Bush is ranked 6th, the economic status under his guidance got worse each year. Thus, he could have benefited from Clinton’s leadership and could be responsible for hurting Obama’s numbers.
The top 10 years according to this statistical average are as follows: 1. 1953 (.994); 2. 1955 (.986); 3. 1965 (.971); 4. 1964 (.960); 5. 1967 (.958); 6. 1966 (.957); 7. 1944 (.916); 8. 1968 (.903); 9. 1962 (.900); and 10. 1959 (.889). The ratings in parenthesis are a percentage as to where each year lies in the normal distribution curve. A rating of 0.50 is average, and any number higher than that is above average and any number lower than that is below average. The 10 worst years are as follows: 1. 1946 (.010); 2. 1945 (0.12); 3. 1948 (.028); 1934 (.050); 5. 1933 (.077); 6. 1935 (.087); 7. 1937 (.100); 8. 2010 (.103); 9. 1951 (.119); 10. 1936 (.122). In essence, the figure of merit for 1953 is at the 99.4 percentile while 1946 is at the 1 percentile in terms of economic stability.
Here is a list of each administrations best and worst years. Barack Obama: 2009 (.227), 2010 (.103); George W. Bush: 2001 (.719), 2008 (.314); Bill Clinton: 1998 (.837), 1993 (.350); George H.W. Bush: 1989 (.525), 1992 (.334); Ronald Reagan: 1986 (.741), 1981 (.274); Jimmy Carter: 1978 (.452), 1980 (.194); Gerald Ford: 1973 (.638), 1975 (.269); Richard Nixon: 1972 (.839), 1970 (.663); LBJ: 1965 (.971), 1968 (.903); JFK: 1962 (.900), 1961 (.738); Dwight Eisenhower: 1953 (.994), 1958 (.410); Harry Truman: 1952 (.858); 1946 (.010); FDR: 1944 (.916), 1934 (.050); Herbert Hoover: 1931 (.222), 1930 (.130).
I will post the entire results of this analysis in my next blog post.
My Book: Is America Dying? (Amazon.com, Barnes and Noble)
Thursday, August 18, 2011
What Economic Indicators Have the Biggest Effect on the Economy? (Part II)
When performing a linear regression model and solving for Debt, Trade Deficit, GDP, Inflation, Tax Revenue, Unemployment, Budget, and Consumer Spending we get the following equations:
Parameter Intercept Unemployment Inflation GDP Debt Budget Home Price Housing CPI Trade Deficit Tax Revenue Consumer Spending Auto Sales
Debt = -2376 -145.5 32.43 -1.792 0 3.052 -0.00231 0.9519 26.18 -0.004196 0.0003138 0.003041 -6.192
Trade Deficit = -1998 -32294 3619 -487 -114 1894 0.8807 254.1 -3220 0 0.04326 0.8848 -2816
GDP = 938.6 -66.82 -28.08 0 -0.1021 -0.1053 0.002069 0.2452 -7.214 -0.001058 4.89E-05 0.00169 -4.819
Inflation = 22.29 -0.5324 0 -0.00574 0.000391 -0.00753 3.15E-05 -0.01656 -0.1417 1.61E-06 -1.33E-06 1.02E-05 -0.03918
Tax Revenue = 1657362 -70587 -14010 105.7 40.01 -818.6 -3.349 -92.53 -9519 0.203 0 0.4324 -2671
Unemployment = 15.83 0 0.2722 -0.00693 -0.0009 -0.00198 -6.25E-06 0.001771 -0.1215 -7.34E-06 -3.42E-06 1.42E-05 -5.22E-02
Budget = 1382 -15.92 -31.05 -0.08868 0.1518 0 0.0007186 -0.1167 -11 0.0003468 0.0003193 0.000348 -2.086
Consumer Spending = -691475 44461 16049 544.7 57.85 133.1 -0.7387 -143.9 5940 0.6197 0.06453 0 3156
For example, for the national Debt the equation is equal to -2376 – 145.5 x Unemployment + 32.43 x Inflation – 1.792 x GDP + 3.052 x Budget – 0.00231 x Home Price + .9519 x Housing Startups + 26.18 x CPI – 0.004196 x Trade Deficit + 0.0003138 x Tax Revenue + 0.003041 x Consumer Spending – 6.192 x Auto Sales.
We can learn a lot about our economy by evaluating each equation. For instance, the debt equation shows that the debt will decrease as unemployment increases; the debt will go up as inflation increases; the debt will decrease as GDP goes up; the debt will increase as the national budget increases; the debt will go down as home prices increase; the debt will go up as housing starts increase; the debt will go up as Consumer Price Index (CPI) goes up; the debt will go down as the trade deficit increases, the debt will go up with tax revenue increases; the debt will go up with consumer spending; and the debt will go down as auto sales increase.
It certainly is not surprising that our national debt is lowered if GDP or other economic indicators such as auto sales or home prices go up. And it is certainly not surprising that our national debt goes up if the federal budget increases, or if there is higher inflation, or if CPI prices increase. There are however, some surprising results – in particular, even as tax revenues and consumer spending increase the debt continues to go up – that is because as the government receives more in tax revenues, they spend more money. This result is apparent by reviewing the results of the other 7 equations. But there are some mind boggling results. For instance, if unemployment and our trade deficit increase it would yield a lower national debt. This actually states that the federal government tends to be more frugal during recessions – this is certainly not the case with our current president.
But there are some other more logical explanations for the strange results in the national debt formula. First, the intercept value starts negative (so there has already been a negative compensation in the formula), so there has to be more upward movement in the formula. Secondly, unemployment and the trade deficit are in the bottom five parameters that affect our economy. The impact of each economic indicator can be weighted in each of the above 8 equations. The 4 most significant parameters that affect the economy are GDP, Consumer Spending, Debt, and the national Budget. The parameters that have the smallest impact on the economy are inflation, tax revenues, and the trade deficit.
Thus, a thriving economy is one where GDP and consumer spending are maximized whereas tax revenues are minimized while at the same time balancing the budget. In other words, we need a society that emphasizes capitalism over government interference. The bottom line is that higher tax revenues do little to fix the budget deficit because the federal government irresponsibly spends any additional revenues it receives.
My Book: Is America Dying? (Amazon.com, Barnes and Noble)
Parameter Intercept Unemployment Inflation GDP Debt Budget Home Price Housing CPI Trade Deficit Tax Revenue Consumer Spending Auto Sales
Debt = -2376 -145.5 32.43 -1.792 0 3.052 -0.00231 0.9519 26.18 -0.004196 0.0003138 0.003041 -6.192
Trade Deficit = -1998 -32294 3619 -487 -114 1894 0.8807 254.1 -3220 0 0.04326 0.8848 -2816
GDP = 938.6 -66.82 -28.08 0 -0.1021 -0.1053 0.002069 0.2452 -7.214 -0.001058 4.89E-05 0.00169 -4.819
Inflation = 22.29 -0.5324 0 -0.00574 0.000391 -0.00753 3.15E-05 -0.01656 -0.1417 1.61E-06 -1.33E-06 1.02E-05 -0.03918
Tax Revenue = 1657362 -70587 -14010 105.7 40.01 -818.6 -3.349 -92.53 -9519 0.203 0 0.4324 -2671
Unemployment = 15.83 0 0.2722 -0.00693 -0.0009 -0.00198 -6.25E-06 0.001771 -0.1215 -7.34E-06 -3.42E-06 1.42E-05 -5.22E-02
Budget = 1382 -15.92 -31.05 -0.08868 0.1518 0 0.0007186 -0.1167 -11 0.0003468 0.0003193 0.000348 -2.086
Consumer Spending = -691475 44461 16049 544.7 57.85 133.1 -0.7387 -143.9 5940 0.6197 0.06453 0 3156
For example, for the national Debt the equation is equal to -2376 – 145.5 x Unemployment + 32.43 x Inflation – 1.792 x GDP + 3.052 x Budget – 0.00231 x Home Price + .9519 x Housing Startups + 26.18 x CPI – 0.004196 x Trade Deficit + 0.0003138 x Tax Revenue + 0.003041 x Consumer Spending – 6.192 x Auto Sales.
We can learn a lot about our economy by evaluating each equation. For instance, the debt equation shows that the debt will decrease as unemployment increases; the debt will go up as inflation increases; the debt will decrease as GDP goes up; the debt will increase as the national budget increases; the debt will go down as home prices increase; the debt will go up as housing starts increase; the debt will go up as Consumer Price Index (CPI) goes up; the debt will go down as the trade deficit increases, the debt will go up with tax revenue increases; the debt will go up with consumer spending; and the debt will go down as auto sales increase.
It certainly is not surprising that our national debt is lowered if GDP or other economic indicators such as auto sales or home prices go up. And it is certainly not surprising that our national debt goes up if the federal budget increases, or if there is higher inflation, or if CPI prices increase. There are however, some surprising results – in particular, even as tax revenues and consumer spending increase the debt continues to go up – that is because as the government receives more in tax revenues, they spend more money. This result is apparent by reviewing the results of the other 7 equations. But there are some mind boggling results. For instance, if unemployment and our trade deficit increase it would yield a lower national debt. This actually states that the federal government tends to be more frugal during recessions – this is certainly not the case with our current president.
But there are some other more logical explanations for the strange results in the national debt formula. First, the intercept value starts negative (so there has already been a negative compensation in the formula), so there has to be more upward movement in the formula. Secondly, unemployment and the trade deficit are in the bottom five parameters that affect our economy. The impact of each economic indicator can be weighted in each of the above 8 equations. The 4 most significant parameters that affect the economy are GDP, Consumer Spending, Debt, and the national Budget. The parameters that have the smallest impact on the economy are inflation, tax revenues, and the trade deficit.
Thus, a thriving economy is one where GDP and consumer spending are maximized whereas tax revenues are minimized while at the same time balancing the budget. In other words, we need a society that emphasizes capitalism over government interference. The bottom line is that higher tax revenues do little to fix the budget deficit because the federal government irresponsibly spends any additional revenues it receives.
My Book: Is America Dying? (Amazon.com, Barnes and Noble)
Monday, August 15, 2011
What Economic Indicators Have the Biggest Impact on the Economy (Part I)?
I built an economic model using the following leading indicators from 1982 to 2010 (some parameters data only goes back to 1982): Unemployment, Inflation, Debt, Trade Deficit, Consumer Price Index, the Gross Domestic Product (GDP), Consumer Spending, Auto Sales, Tax Revenue, Housing Prices, and Housing Start Ups. The data is readily available from the Bureau of Economic Analysis (BEA). The model is below (the parameters are in percent or thousands or millions of dollars).
Year Unemployment Inflation GDP Debt Budget Home Price Housing Starts CPI Trade Deficit Tax Revenue Consumer Spending Auto Sales
1982 9.7 6.16 3253 1142 746 83900 1,062.2 42.29 24156 617766 2075500 79.6
1983 9.6 3.22 3534 1377 808 89800 1,703.0 43.29 57767 600562 2288600 100.8
1984 7.5 4.3 3931 1572 852 97600 1,749.5 45.25 109072 666438 2501100 124.4
1985 7.2 3.55 4218 1823 946 100800 1,741.8 41.45 121880 734037 2717600 146.6
1986 7 1.91 4460 2125 990 111900 1,805.4 45.62 138563 769155 2896700 164
1987 6.2 3.66 4736 2350 1004 127200 1,620.5 45.61 151684 854288 3097000 164.2
1988 5.5 4.08 5100 2602 1064 138300 1,488.1 45.52 114566 909238 3350100 175.9
1989 5.3 4.83 5482 2857 1144 148800 1,376.1 46.93 93141 991105 3594500 180.8
1990 5.6 5.39 5801 3233 1253 149800 1,192.7 48.21 80864 1031922 3835500 176.9
1991 6.8 4.25 5992 3665 1324 147200 1,013.9 49.6 31135 1054996 3980100 157.9
1992 7.5 3.03 6342 4064 1381 144100 1,199.7 51.17 39212 1091223 4236900 176.1
1993 6.9 2.96 6667 4411 1409 147700 1,287.6 53.46 70311 1154341 4483600 193.9
1994 6.1 2.61 7085 4692 1462 154500 1,457.0 53.99 98493 1258579 4750800 216.1
1995 5.6 2.81 7414 4974 1516 158700 1,354.1 54.66 96384 1351801 4987300 220.3
1996 5.4 2.93 7839 5225 1561 166400 1,476.8 55.29 104065 1453055 5273600 235.8
1997 4.9 2.34 8332 5413 1601 176200 1,474.0 55.45 108273 1579240 5570600 254
1998 4.5 1.55 8794 5526 1653 181900 1,616.9 51.56 166140 1721733 5918500 280.7
1999 4.2 2.19 9354 5656 1702 195600 1,640.9 51.23 264239 1822459 6342800 309.7
2000 4 3.38 9951 5674 1789 207000 1,568.7 52.47 378780 2025198 6830400 321.4
2001 4.7 2.83 10286 5807 1863 213200 1,602.7 55 364393 1991142 7148800 342
2002 5.8 1.59 10642 6228 2011 228700 1,704.9 54.45 420524 1853149 7439200 359.7
2003 6 2.27 11142 6783 2160 246300 1,847.7 56.18 494183 1782321 7804000 358.2
2004 5.5 2.68 11868 7379 2293 274500 1,955.8 57.71 609345 1880126 8285100 359.5
2005 5.1 3.39 12638 7933 2472 297000 2,068.3 61.05 714176 2153625 8819000 361.6
2006 4.6 3.24 13398 8507 2655 305900 1,800.9 66.63 759240 2406876 9322700 346.6
2007 4.6 2.85 14077 9008 2729 313600 1,355.0 69.72 702099 2568001 9806300 349.9
2008 5.8 3.85 14441 10023 2982 292600 905.5 75.36 698802 2523991 10104500 291
2009 9.3 -0.34 14256 11910 3518 270900 554.0 75.41 374908 2104989 10001300 269.4
2010 9.6 1 14500 13300 3721 272400 586.9 75.89 497824 2162724 10500000 303
In part 2 of this blog I will evaluate the impact of the parameters in the above model by finding a linear regression solution.
My Book: Is America Dying? (Amazon.com, Barnes and Noble)
Year Unemployment Inflation GDP Debt Budget Home Price Housing Starts CPI Trade Deficit Tax Revenue Consumer Spending Auto Sales
1982 9.7 6.16 3253 1142 746 83900 1,062.2 42.29 24156 617766 2075500 79.6
1983 9.6 3.22 3534 1377 808 89800 1,703.0 43.29 57767 600562 2288600 100.8
1984 7.5 4.3 3931 1572 852 97600 1,749.5 45.25 109072 666438 2501100 124.4
1985 7.2 3.55 4218 1823 946 100800 1,741.8 41.45 121880 734037 2717600 146.6
1986 7 1.91 4460 2125 990 111900 1,805.4 45.62 138563 769155 2896700 164
1987 6.2 3.66 4736 2350 1004 127200 1,620.5 45.61 151684 854288 3097000 164.2
1988 5.5 4.08 5100 2602 1064 138300 1,488.1 45.52 114566 909238 3350100 175.9
1989 5.3 4.83 5482 2857 1144 148800 1,376.1 46.93 93141 991105 3594500 180.8
1990 5.6 5.39 5801 3233 1253 149800 1,192.7 48.21 80864 1031922 3835500 176.9
1991 6.8 4.25 5992 3665 1324 147200 1,013.9 49.6 31135 1054996 3980100 157.9
1992 7.5 3.03 6342 4064 1381 144100 1,199.7 51.17 39212 1091223 4236900 176.1
1993 6.9 2.96 6667 4411 1409 147700 1,287.6 53.46 70311 1154341 4483600 193.9
1994 6.1 2.61 7085 4692 1462 154500 1,457.0 53.99 98493 1258579 4750800 216.1
1995 5.6 2.81 7414 4974 1516 158700 1,354.1 54.66 96384 1351801 4987300 220.3
1996 5.4 2.93 7839 5225 1561 166400 1,476.8 55.29 104065 1453055 5273600 235.8
1997 4.9 2.34 8332 5413 1601 176200 1,474.0 55.45 108273 1579240 5570600 254
1998 4.5 1.55 8794 5526 1653 181900 1,616.9 51.56 166140 1721733 5918500 280.7
1999 4.2 2.19 9354 5656 1702 195600 1,640.9 51.23 264239 1822459 6342800 309.7
2000 4 3.38 9951 5674 1789 207000 1,568.7 52.47 378780 2025198 6830400 321.4
2001 4.7 2.83 10286 5807 1863 213200 1,602.7 55 364393 1991142 7148800 342
2002 5.8 1.59 10642 6228 2011 228700 1,704.9 54.45 420524 1853149 7439200 359.7
2003 6 2.27 11142 6783 2160 246300 1,847.7 56.18 494183 1782321 7804000 358.2
2004 5.5 2.68 11868 7379 2293 274500 1,955.8 57.71 609345 1880126 8285100 359.5
2005 5.1 3.39 12638 7933 2472 297000 2,068.3 61.05 714176 2153625 8819000 361.6
2006 4.6 3.24 13398 8507 2655 305900 1,800.9 66.63 759240 2406876 9322700 346.6
2007 4.6 2.85 14077 9008 2729 313600 1,355.0 69.72 702099 2568001 9806300 349.9
2008 5.8 3.85 14441 10023 2982 292600 905.5 75.36 698802 2523991 10104500 291
2009 9.3 -0.34 14256 11910 3518 270900 554.0 75.41 374908 2104989 10001300 269.4
2010 9.6 1 14500 13300 3721 272400 586.9 75.89 497824 2162724 10500000 303
In part 2 of this blog I will evaluate the impact of the parameters in the above model by finding a linear regression solution.
My Book: Is America Dying? (Amazon.com, Barnes and Noble)
Saturday, August 13, 2011
Unemployment Model
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 unemployment economic parameter:
n 64
R2 0.79
Adjusted R2 0.74
SE 0.82
Term Coefficient 95% CI SE t statistic DF p
Intercept 5.545 1.916 to 9.175 1.8070 3.07 50 0.0035
Population 0.002931 -0.017709 to 0.023570 0.0102759 0.29 50 0.7767
Inflation -0.1406 -0.2205 to -0.0606 0.03980 -3.53 50 0.0009
GDP -0.00264 -0.00742 to 0.00214 0.002379 -1.11 50 0.2725
Debt -0.004598 -0.006006 to -0.003191 0.0007007 -6.56 50 <0.0001
Tax Receipts -0.001045 -0.009708 to 0.007618 0.0043131 -0.24 50 0.8095
Gov Spending 0.00789 -0.00145 to 0.01723 0.004649 1.70 50 0.0959
Budget -0.002198 -0.013211 to 0.008816 0.0054834 -0.40 50 0.6903
Trade Deficit 0.007352 0.000805 to 0.013899 0.0032594 2.26 50 0.0285
Consumer Spending 0.003819 -0.007226 to 0.014864 0.0054991 0.69 50 0.4906
State Deficit 0.01752 -0.00862 to 0.04366 0.013014 1.35 50 0.1843
State Social Payment -0.01106 -0.07132 to 0.04920 0.030001 -0.37 50 0.7139
Gov Social Benefits 0.03103 0.01167 to 0.05038 0.009637 3.22 50 0.0023
Personal Income -0.002082 -0.009859 to 0.005695 0.0038719 -0.54 50 0.5932
The economic parameters used to model unemployment over the past 64 (n) years are: the U.S. population, the inflation rate, personal income, 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, state government spending on social benefits, and federal government social benefit payments. The intercept value in the above table is not a parameter – it is the value of unemployment (in percent) 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 (Unemployment 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 (Unemployment in this case). If a coefficient value of an economic parameter is positive then it trends in the same direction of the tested variable (Unemployment in this case). If a coefficient value is negative then the corresponding variable trends in the opposite direction of the tested variable (Unemployment 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 unemployment?
In times of high unemployment the federal government debt is increased as it tries to spend its way out of a recession. Once inflation and GDP increase then unemployment levels decrease. But it is important to note that increased federal social benefit payments does not lead to lower unemployment.
My Book: Is America Dying? (Amazon.com, Barnes and Noble)
n 64
R2 0.79
Adjusted R2 0.74
SE 0.82
Term Coefficient 95% CI SE t statistic DF p
Intercept 5.545 1.916 to 9.175 1.8070 3.07 50 0.0035
Population 0.002931 -0.017709 to 0.023570 0.0102759 0.29 50 0.7767
Inflation -0.1406 -0.2205 to -0.0606 0.03980 -3.53 50 0.0009
GDP -0.00264 -0.00742 to 0.00214 0.002379 -1.11 50 0.2725
Debt -0.004598 -0.006006 to -0.003191 0.0007007 -6.56 50 <0.0001
Tax Receipts -0.001045 -0.009708 to 0.007618 0.0043131 -0.24 50 0.8095
Gov Spending 0.00789 -0.00145 to 0.01723 0.004649 1.70 50 0.0959
Budget -0.002198 -0.013211 to 0.008816 0.0054834 -0.40 50 0.6903
Trade Deficit 0.007352 0.000805 to 0.013899 0.0032594 2.26 50 0.0285
Consumer Spending 0.003819 -0.007226 to 0.014864 0.0054991 0.69 50 0.4906
State Deficit 0.01752 -0.00862 to 0.04366 0.013014 1.35 50 0.1843
State Social Payment -0.01106 -0.07132 to 0.04920 0.030001 -0.37 50 0.7139
Gov Social Benefits 0.03103 0.01167 to 0.05038 0.009637 3.22 50 0.0023
Personal Income -0.002082 -0.009859 to 0.005695 0.0038719 -0.54 50 0.5932
The economic parameters used to model unemployment over the past 64 (n) years are: the U.S. population, the inflation rate, personal income, 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, state government spending on social benefits, and federal government social benefit payments. The intercept value in the above table is not a parameter – it is the value of unemployment (in percent) 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 (Unemployment 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 (Unemployment in this case). If a coefficient value of an economic parameter is positive then it trends in the same direction of the tested variable (Unemployment in this case). If a coefficient value is negative then the corresponding variable trends in the opposite direction of the tested variable (Unemployment 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 unemployment?
In times of high unemployment the federal government debt is increased as it tries to spend its way out of a recession. Once inflation and GDP increase then unemployment levels decrease. But it is important to note that increased federal social benefit payments does not lead to lower unemployment.
My Book: Is America Dying? (Amazon.com, Barnes and Noble)
Monday, August 8, 2011
Personal Income Model
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 personal income economic parameter:
n 64
R2 1.00
Adjusted R2 1.00
SE 29.91
Term Coefficient 95% CI SE t statistic DF p
Intercept 65.45 -77.45 to 208.35 71.144 0.92 50 0.3620
Population -0.3092 -1.0563 to 0.4380 0.37199 -0.83 50 0.4098
Unemployment -2.761 -13.077 to 7.554 5.1358 -0.54 50 0.5932
Inflation -1.952 -5.159 to 1.255 1.5966 -1.22 50 0.2272
GDP 0.142 -0.030 to 0.313 0.0854 1.66 50 0.1026
Debt -0.05684 -0.12488 to 0.01121 0.033877 -1.68 50 0.0996
Tax Receipts 0.5459 0.2709 to 0.8209 0.13691 3.99 50 0.0002
Gov Spending -0.2901 -0.6300 to 0.0498 0.16921 -1.71 50 0.0927
Budget -0.04835 -0.44988 to 0.35318 0.199910 -0.24 50 0.8099
Trade Deficit 0.4869 0.2783 to 0.6955 0.10385 4.69 50 <0.0001
Consumer Spending 0.9265 0.6197 to 1.2333 0.15274 6.07 50 <0.0001
State Social Payment -5.385 -6.963 to -3.807 0.7856 -6.85 50 <0.0001
Gov Social Benefits 1.845 1.274 to 2.415 0.2840 6.49 50 <0.0001
State Deficit -1.496 -2.367 to -0.625 0.4336 -3.45 50 0.0011
The economic parameters used to model personal income 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, state government spending on social benefits, and federal government social benefit payments. The intercept value in the above table is not a parameter – it is the value of personal income (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 (Personal Income 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 (Personal Income in this case). If a coefficient value of an economic parameter is positive then it trends in the same direction of the tested variable (Personal Income in this case). If a coefficient value is negative then the corresponding variable trends in the opposite direction of the tested variable (Personal Income 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 personal income?
It should come as no surprise when economic times are good and GDP, federal tax receipts, the trade deficit, and consumer spending are all increasing then so is personal income. Generally, when state and federal government spending and debt levels increase then personal income is declining. It is interesting to note that personal income levels have been decreasing with population increases.
My Book: Is America Dying? (Amazon.com, Barnes and Noble)
n 64
R2 1.00
Adjusted R2 1.00
SE 29.91
Term Coefficient 95% CI SE t statistic DF p
Intercept 65.45 -77.45 to 208.35 71.144 0.92 50 0.3620
Population -0.3092 -1.0563 to 0.4380 0.37199 -0.83 50 0.4098
Unemployment -2.761 -13.077 to 7.554 5.1358 -0.54 50 0.5932
Inflation -1.952 -5.159 to 1.255 1.5966 -1.22 50 0.2272
GDP 0.142 -0.030 to 0.313 0.0854 1.66 50 0.1026
Debt -0.05684 -0.12488 to 0.01121 0.033877 -1.68 50 0.0996
Tax Receipts 0.5459 0.2709 to 0.8209 0.13691 3.99 50 0.0002
Gov Spending -0.2901 -0.6300 to 0.0498 0.16921 -1.71 50 0.0927
Budget -0.04835 -0.44988 to 0.35318 0.199910 -0.24 50 0.8099
Trade Deficit 0.4869 0.2783 to 0.6955 0.10385 4.69 50 <0.0001
Consumer Spending 0.9265 0.6197 to 1.2333 0.15274 6.07 50 <0.0001
State Social Payment -5.385 -6.963 to -3.807 0.7856 -6.85 50 <0.0001
Gov Social Benefits 1.845 1.274 to 2.415 0.2840 6.49 50 <0.0001
State Deficit -1.496 -2.367 to -0.625 0.4336 -3.45 50 0.0011
The economic parameters used to model personal income 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, state government spending on social benefits, and federal government social benefit payments. The intercept value in the above table is not a parameter – it is the value of personal income (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 (Personal Income 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 (Personal Income in this case). If a coefficient value of an economic parameter is positive then it trends in the same direction of the tested variable (Personal Income in this case). If a coefficient value is negative then the corresponding variable trends in the opposite direction of the tested variable (Personal Income 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 personal income?
It should come as no surprise when economic times are good and GDP, federal tax receipts, the trade deficit, and consumer spending are all increasing then so is personal income. Generally, when state and federal government spending and debt levels increase then personal income is declining. It is interesting to note that personal income levels have been decreasing with population increases.
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