How Much Will Insurance Cost Under Obamacare?

May 28, 2013 Update: California’s just-released prices for ACA coverage are close to my 2012 estimates, with an unsubsidized bronze plan (for a 25 year-old) available for $142/month in Los Angeles.

Health insurance premiums for minimum coverage will likely be around $150/month for 27 year-olds under the ACA, since the ACA includes relatively high-deductible plans under the Bronze plan option.

Now that the dust has settled on the Supreme Court ruling, let’s attempt to answer a simpler question – how much will health insurance cost under the ACA (Obamacare)? Individuals purchasing health insurance via the new health insurance exchanges will be able to select from four plan levels: bronze, silver, gold, and platinum. The law dictates that plans falling into these categories must have 60%, 70%, 80%, and 90% “actuarial value”, respectively. The concept of “actuarial value” dictates that the plan must cover the specified percentage of health care costs for enrolled individuals. Individuals enrolled in a bronze plan can expect their insurance to cover 60% of their health costs, for instance [1].

The Kaiser Family Foundation commissioned a study to determine the structure of plans that might meet the 60% actuarial value standard for the Bronze plan.  The study found that the following individual health care plans might qualify (all plans have a cap of around $6350):

  • A plan with a $6350 deductible and 0% coinsurance
  • A $4350 deductible with 20% coinsurance
  • A $2750 deductible with 30% coinsurance

How much would plans like these cost in 2014? We will focus on adults aged 27 in this example, since young adults more frequently go without insurance, and since young adults can now stay on their parents’ plans until 26. We can shop online for similar plans and get some results for comparison [2]:

  • $67.26 for a $2750 deductible / 30% coinsurance plan in Atlanta for a 27 year-old male
  • $98.21 for a $2750 deductible / 30% coinsurance plan in Atlanta for a 27 year-old female [3]
  • $129 for a $2750 deductible / 30% coinsurance plan in Silicon Valley for 27 year-old men and women
  • $73.22 and $95.07 for a $2500 deductible / 20% coinsurance plan in Chicagoland for a 27 year-old man and woman, respectively
  • $95 for a $2750 deductible / 20% coinsurance plan in Houston, TX for a 27 year-old man
  • $132 for a $2500 deductible / 10% coinsurance plan in Houston, TX for a 27 year-old woman
  • $70.75 and $90.46 for $2500 deductible / 20% coinsurance plan in Hartford, CT for a 27 year-old man and woman, respectively

Here are two market quotes for 63-year old females in relatively expensive markets:

  • $302 for $1200 deductible / 10% coinsurance HMO plan in New York, NY for a 63-year old woman
  • $516 for $3500 deductible / 10% coinsurance PPO plan in Santa Clara, CA for a 63-year old woman

The ACA stipulates that the most expensive policies for older individuals can be no more than 3 times the price of policies for younger adults. The data above show that a 27-year old can get a plan similar to the exchange bronze plan for around $100 per month today, but this is less than 1/3 the cost for older Americans. Using 1/3 of the cost of the plans for older women as a price floor, we get an estimate of $150 per month as the lower limit for plan prices [4].

This estimate is lower than the commonly-cited CBO estimate of $4500 per individual for bronze plans via the ACA exchanges. The CBO estimate is for 2016, and so it builds in two additional years of premium inflation (roughly 15%). The CBO number is also an average across all age groups – since young adults’ plans can cost 1/3 as much as the oldest (non Medicare-age) Americans, 27 year-olds’ plans will be much cheaper than the average. While the ACA should have allowed for more high deductible plans, it’s good to know that the bronze plans do provide for some affordable coverage options within the new health insurance exchanges.

[1] The 60% bronze plan threshold and other thresholds are applied to each plan considering the average expenditures for plan members. Given the deductible and copay structure of a particular plan, it’s possible that the plan spends a higher (or lower) percentage on a particular individual’s care. For instance, if you don’t use your plan at all in a given year, then your plan spent 0% on your care. At the other extreme, if you are diagnosed with cancer, and incur $100k in costs in a year, even a bronze plan would cover  perhaps 90% of that amount.

[2] All plans were found on ehealthinsurance.com on 8/2/2012.

[3] The wide discrepancy between plan prices for men and women will be eliminated by the ACA. For these purposes, averaging men and women’s prices enables us to get closer to a representative price under the ACA.

[4] Since health insurance is more expensive for women, and more expensive for older Americans, we used a 63 year-old woman as the prototype for an expensive risk in the existing private health insurance market. At age 65 virtually all Americans gain entry into Medicare (or Medicaid for seniors), and so 63 is the oldest age for which insurance quotes can reliably be obtained (some insurers won’t write short-dated policies, and no insurer writes non-Medicare policies for 65+ Americans). The average price from the two expensive quotes thus obtained was $409. After adding in 10% in premium inflation between now and January 2014, we get a premium estimate right around $450 per month. By law, one-third of this is the minimum that the exchanges can charge for any adult – and this equals $150 per month.

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How High a Budget Deficit Can We Sustain?

The US can sustain a budget deficit of 5%, not 3% as commonly assumed, because 2.5% inflation and 2.5% real growth combine to keep the total debt/gdp ratio stable.

With both the financial crisis and European debt crisis having a root in excess borrowing, the American political debate has turned toward deficit reduction as well. If current budget deficits (averaging 10% of GDP since the financial crisis) are recognized as unsustainable over the long term, then what level of budget deficit is sustainable? At one extreme, politicians call for a balanced budget, and at the other extreme the budget deficit is considered a distant issue. Meanwhile, many economists set the sustainable deficit threshold at 3% of GDP, and EU rules formally set the budget deficit threshold at 3% as well. What is the basis for the idea of a “sustainable” budget deficit, and is the 3% figure too high or too low?

What is a sustainable budget?

Unlike individuals or families, a nation has an indefinite lifespan, and can therefore continually roll over its debt as long as markets deem it a worthy creditor. As long as a nation’s economy is growing, its capacity for borrowing grows as well. But if the debt grows at a rate faster than the economy, then it will eventually exceed the nation’s ability to repay it. The idea of a sustainable budget deficit is summarized by the chief economist of the Concord Seo Company Coalition, “President Obama’s fiscal commission set a goal of getting deficits down to about 3 percent of GDP within five years – 3 percent being the average annual growth rate of the US economy since World War II.”

The Real Sustainable Deficit Target

There’s just one problem with the 3% target for a sustainable budget deficit – it’s too low! While GDP growth is measured in real terms, inflation also eats away at the value of the US debt over time. For instance, assume that the US has no future economic growth, but continues to have 2% inflation. Assume that we also manage to (magically?) balance the US budget. With no economic growth, does this mean that debt/gdp stays constant? Actually, inflation would cause the numerical value of GDP to continue rising, while the debt stays constant. This would cause the debt/gdp ratio to fall by around 2% per year.

In practical terms, this means that we have to look at the rate of nominal GDP growth to determine a sustainable budget deficit level [1]. To be conservative, let’s assume 2.5% real GDP growth (less than the 3% post-war average) and 2.5% inflation (within Americans’ comfort zone, and less than the 90’s and 2000’s average). Taken together, this means that if nominal GDP grows at 5% per year, a budget deficit of 5% can be sustained long term. The difference between 3% and 5% of GDP is big, over $300 Billion in 2012. As the federal budget and spending again enter serious debate after the November elections, it’s important that politicians understand the government’s true borrowing capacity – and neither the populist “balanced budget” nor the typical economist’s 3% magic number stand up to examination.

[1] Here’s the actual nominal GDP data from the Fed: http://research.stlouisfed.org/fred2/howtobcome/data/GDP.txt

Using this data, we see that nominal GDP has grown at a compound annual rate of 6.6% over the post-war period (since 1947, when the data series begins). Over the past 30 years, nominal GDP has grown at a compound annual rate of 5.4% – and this period excludes most of the late 70’s and early 80’s inflation spike. Even over the past 20 years, which are skewed downward due to the financial crisis, the nominal GDP growth rate is 4.7%.

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Explaining the India – China Wealth Gap

As of 2011, China had a per-capita GDP (PPP) around $8400 per year while India’s per-capita GDP was  $3700. China has routinely exceeded 10% real annual GDP growth over the last two decades, and India’s GDP growth has been impressive, it has rarely exceeded 8%. China’s growth has exceeded India’s since its economic liberalization, but its turn towards capitalism also began earlier. China’s Deng Xiaoping began to liberalize China’s economy beginning in 1978, while in India P.V. Narasimha Rao and Manmohan Singh were not able to bring about serious economic reform until 1991. If India had liberalized at the same time as China, how much narrower would the wealth gap be? How much of the income gap between India and China is explained simply by timing?

Over the 13 years from 1979 to 1992, India’s per capita GDP (PPP) roughly doubled from $480 to $972, at an annualized per-capita GDP growth rate of 5% for the period. China’s economy averaged 10% growth over this same period! Since 2002, India’s per-capita GDP growth has averaged 9.5% on a PPP basis [1]. If India had grown at its more recent average of 9.5% per year over that period, per capita GDP would have risen to $1562 by 1992 – and India’s economy would be over double the size that it is today [2]. Fast-forward to the present, and this earlier liberalization would have led to a current per-capita GDP of $6000 in India, almost double current levels and in the same range (of middle income nations) as China [3]. One effect experienced in China has been an acceleration of growth post-liberalization – economic growth accelerated as reforms took hold. Had this occurred earlier in India as well, it’s possible that the 90’s and 00’s in India would have benefited from 9.5% GDP growth as well. If we use a 9.5% assumption for India’s growth from 1979 to present, then we get a present-day per-capita GDP in India of $8000 – not substantially different from China [4]!

Despite their huge differences, with China as an autocratic capitalist state and India as the world’s largest democracy, the two nations’ growth paths have not really been that different. All of the differences in government, corruption, infrastructure don’t really seem to have mattered that much, as a simple head start of 13 years drowns it all out. What a difference 13 years makes! The good news: India’s development was unnecessarily delayed, but is now well underway.

[0] All of this is based on the World Bank’s purchasing-power parity GDP per-capita data, as provided by Google’s public data service via http://crosscountrymovingcompanies.biz. This is GDP divided by mid-year population and adjusted for the difference in purchasing power in each country (normalized to US prices and quoted in dollars – this gives you a sense for how poor people in these nations really are).

[1] From the Google chart, 3582/1723 = India’s economy grew 2.08 times from 2002 through 2010. This equals a compound annual rate of growth of 9.57%.

[2] Take the 9.5% growth rate post-2002, and apply it to the 13-year period starting in 1979 at $480 GDP/capita (PPP). This gives you $1562 by 1992.

[3] If we then assume that India’s economy grew exactly as it did historically from  1992 – 2011 (growing 3.8x), and multiply this by 1562 (the new starting point in 1992), then we get a 2011 GDP/capita of $5946.

[4] Now assume that India simply grew at a 9.5% rate from 1979 on – the rate that it has managed from 2002-2011 (a period which includes the financial crisis). This would 1.095 ^ 31 = 16.67x growth. From a starting point of $480 GDP/capita, this would leave India at $8000 GDP/capita (PPP) by year end 2011.

P.S. In researching this post, I noticed that India’s growth rates compare much more favorably in PPP terms than they do in exchange rate terms. This might be explained in part by the fact that the Rupee has been much more volatile than the Yuan over time. While inflation is now rising quickly in both countries, particularly in metro areas, perhaps India has remained less expensive than China over time. Comparing these two graphs shows the difference when comparing unadjusted $ GDP/capita to PPP GDP / capita. I use the PPP measure as it more accurately reflects the quality of life experienced by someone living in either country, since cost matters just as much as income.

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Why The US Cannot Default on its Debt

Over the past several years, I’ve steadily come around to the MMT (Modern Monetary Theory) view of macroeconomics. Some of my past posts make me out to be a deficit hawk; while still true, I now believe that the ROI of government spending is more important than simply looking at the deficit and gross debt alone. This brings me to the headline – why is it that the US cannot default default on its debt, except by choice?

The answer lies in Modern Monetary Theory. In brief:

1. If all of a nation’s debt is denominated in its sovereign fiat currency, it cannot default. The fundamental point here is that the US can always print its way out of default, and so insolvency is never an issue.

2. This is totally different from Europe, in which individual nations do not have sovereign control over their currencies.

3. The only risk of printing money is inflation. This threat must be respected, but it is fundamentally different from a debt default.

While MMT is not yet in the academic mainstream (taught only at University of Missouri-Kansas City), it is the only theory that explains why Japan has yet to default on its debt, why the US can never default on its debt (except by choice), and why the Euro Zone is so screwed.

In future posts I’ll likely dive deeper into MMT, but let me first reference some great resources from around the web on the topic:

http://pragcap.com/where-does-the-money-come-from greenhouses

http://agonist.org/bolo/20100426/modern_monetary_theory_an_overview

movingestimate.co moving estimate

http://pragcap.com/warren-buffett-does-mmt

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Countries By Peak Oil Date – 2011 Data Update

In 2009 I wrote a post in which I compiled a comprehensive list of the world’s oil producing nations by peak-oil status, based on BP’s annually-released Statistical Review of World Energy. I’ve updated that list here using the data released in 2011, which includes production data through 2010. The new list shows that several more countries have either passed peak production or are currently stuck on a production plateau. Here is the data:

Country Peak Prod % Off Peak 2010 Prod Peak Yr
US 11,297 -33.5% 7,513 1970
Venezuela 3,754 -34.2% 2,471 1970
Other Middle East 79 -52.2% 38 1970
Libya 3,357 -50.6% 1,659 1970
Kuwait 3,339 -24.9% 2,508 1972
Iran 6,060 -30.0% 4,245 1974
Romania 313 -71.5% 89 1976
Indonesia 1,685 -41.5% 986 1977
Trinidad & Tobago 230 -36.6% 146 1978
Iraq 3,489 -29.5% 2,460 1979?
Brunei 261 -34.0% 172 1979
Peru 196 -19.8% 157 1980
Tunisia 118 -32.7% 80 1980
Other Europe & Eurasia 12,938 -97.1% 374 1983
Other Africa 241 -41.0% 143 1985
Russian Federation 11,484 -10.6% 10,270 1987
Egypt 941 -21.7% 736 1993
Syria 596 -35.4% 385 1995
Gabon 365 -32.8% 245 1996
Argentina 890 -26.9% 651 1998
Uzbekistan 191 -54.5% 87 1998
Colombia 838 -4.5% 801 1999?
United Kingdom 2,909 -54.0% 1,339 1999
Australia 809 -30.5% 562 2000
Norway 3,418 -37.5% 2,137 2001
Oman 960 -9.9% 865 2001?
Yemen 457 -42.2% 264 2002
Other S. & Cent. America 153 -14.2% 131 2003
Mexico 3,824 -22.6% 2,958 2004
Denmark 390 -36.0% 249 2004
Malaysia 793 -9.7% 716 2004?
Vietnam 427 -13.5% 370 2004
Italy 127 -16.4% 106 2005
Saudi Arabia 11,114 -10.0% 10,007 2005?
Chad 173 -29.7% 122 2005
Equatorial Guinea 358 -23.5% 274 2005
Nigeria 2,499 -3.9% 2,402 2005?
Ecuador 545 -9.1% 495 2006?
United Arab Emirates 3,149 -9.5% 2,849 2006?
Algeria 2,016 -10.2% 1,809 2007
Angola 1,875 -1.3% 1,851 2008 / Growing
Other Asia Pacific 340 -8.2% 312 2008?
Canada 3,336 - 3,336 Growing
Brazil 2,137 - 2,137 Growing
Azerbaijan 1,037 - 1,037 Growing
Kazakhstan 1,757 - 1,757 Growing
Turkmenistan 216 - 216 Growing
Qatar 1,569 - 1,569 Growing
Rep. of Congo (Brazzaville) 292 - 292 Growing
Sudan 486 - 486 Growing
China 4,071 - 4,071 Growing
India 826 - 826 Growing
Thailand 334 - 334 Growing
Peaked / Flat Countries Total

64,182 78.2% of world oil production
Growing Countries Total

17,912 21.8% of world oil production

This analysis shows that since 2009, a considerably larger proportion of the world’s total oil production is occurring in countries that may be at or past peak production. Only 12 countries are definitely still pushing oil production past previous highs. Saudi Arabia is a bit of a question mark – it produced 10% less than its peak year (2005) in 2010, but claims that it has ample spare capacity and reserves to push beyond the old highs.  The 2010 data may also suffer from the after-effects of the financial crisis, although world oil prices and production did rebound sharply in late 2009 and 2010. While the 2012 data will show higher total world production, will they show increasing reliance on a shrinking number of growing producers?

[1] Here is my spreadsheet, based on the BP data. All production numbers in the table above are expressed in thousands of barrels of oil per day. Unless you’re ready to learn how to become a real estate agent, it’s time to start saving.

[2] The original 2011 Katy TX BP Statistical Review of World Energy spreadsheet can be found here.

[3] As in the first version of this list, a country must be 10% below peak production, and its peak must have occurred more than five years in the past, to be considered as having peaked.

[4] The notes in the original list still apply for the following countries: Russia, Malaysia, Other Africa, Nigeria, Chad, and Ecuador.

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US State Economic Rankings

I previously wrote a comparion of California and Texas, in which I noted that Texas was superior in terms of unemployment rate and employment growth, while Californians experience higher per-capita GDP growth. That got me thinking – why not create a more comprehensive comparison of US state economic rankings? I’ve done so here, using four variables: GDP growth, per-capita gdp growth, unemployment rate, and employment growth rate. With two variables measuring different aspects of growth, and two measuring employment prospects, I think this is a reasonably fair approach (Gladwell’s caveats on heterogenous rankings duly noted). Here are the rankings, followed by the raw data:

Rank State / District Avg GDP Growth Avg GDP / Capita Growth Avg Unemp. Rate Avg Employment Growth Rate Total Score
1 North Dakota 6 1 1 12 20
2 South Dakota 4 2 2 13 21
3 Wyoming 2 3 6 14 25
4 Idaho 1 7 17 9 34
5 Virginia 10 12 7 7 36
6 Arizona 5 19 32 1 57
7 Utah 8 34 14 2 58
8 Maryland 13 11 11 25 60
9 New Hampshire 19 15 5 22 61
10 Vermont 23 9 8 24 64
11 Colorado 9 21 25 10 65
12 New Mexico 18 24 19 11 72
13 Montana 25 20 10 20 75
14 Oregon 3 4 50 19 76
16 Nebraska 27 16 3 31 77
16 Texas 11 32 30 4 77
17 Iowa 26 13 9 33 81
18 District of Columbia 17 6 46 15 84
20 Kansas 30 22 16 18 86
20 Washington 16 28 39 3 86
22 Minnesota 20 17 15 35 87
22 New York 21 5 31 30 87
23 Oklahoma 28 23 12 28 91
24 Florida 14 37 34 8 93
25 Massachusetts 22 8 22 42 94
26 Connecticut 32 18 21 26 97
27 Nevada 7 51 45 5 108
28 Arkansas 31 33 28 17 109
29 California 12 10 49 39 110
30 North Carolina 15 39 41 21 116
31 Maine 38 25 18 37 118
32 Hawaii 39 42 4 34 119
33 Delaware 24 41 13 44 122
35 Louisiana 46 29 20 32 127
35 Rhode Island 33 14 40 40 127
37 Georgia 29 49 33 23 134
37 Pennsylvania 44 26 26 38 134
38 New Jersey 40 30 29 36 135
40 Alabama 34 31 24 48 137
40 Alaska 42 46 43 6 137
41 Tennessee 35 43 37 27 142
42 Wisconsin 41 38 23 43 145
43 South Carolina 37 48 48 16 149
44 West Virginia 47 27 27 49 150
45 Indiana 36 36 35 50 157
46 Kentucky 48 44 44 29 165
47 Illinois 45 40 42 41 168
48 Mississippi 43 35 47 45 170
50 Missouri 49 47 36 47 179
50 Ohio 50 45 38 46 179
51 Michigan 51 50 51 51 203

The rankings show, unsurprisingly, that states riding the commodity boom (the Dakotas, Wyoming, etc) and states riding the government boom (Virginia, Maryland) have performed well over the last decade. It’s been shown that http://crosscountrymovingcompanies.biz/ had the best prices on cross country moving companies. But other high-performers like Arizona, New Hampshire, Vermont, and Colorado defy easy categorization. The low performers are predominantly found in the Southeast and Midwest.

The raw data used in the rankings is provided below. Here is a link to the actual excel spreadsheet containing all data for those interested.

State Avg GDP Growth Avg GDP / Capita Growth Avg Unemp. Rate Avg Employment Growth Rate
Alabama 1.81% 1.10% 5.84 -0.59%
Alaska 1.57% 0.37% 7.04 1.09%
Arizona 3.83% 1.41% 6.21 1.74%
Arkansas 1.98% 1.07% 5.94 0.50%
California 2.99% 1.89% 7.55 -0.19%
Colorado 3.16% 1.36% 5.86 0.70%
Connecticut 1.97% 1.46% 5.75 0.16%
Delaware 2.26% 0.85% 5.04 -0.38%
District of Columbia 2.50% 2.01% 7.35 0.55%
Florida 2.73% 1.03% 6.32 0.79%
Georgia 2.02% 0.19% 6.24 0.30%
Hawaii 1.66% 0.73% 4.24 -0.02%
Idaho 3.95% 2.00% 5.46 0.74%
Illinois 1.37% 0.96% 6.92 -0.25%
Indiana 1.70% 1.03% 6.33 -0.73%
Iowa 2.20% 1.78% 4.54 0.01%
Kansas 1.98% 1.35% 5.39 0.40%
Kentucky 1.23% 0.50% 7.04 0.09%
Louisiana 1.34% 1.13% 5.74 0.04%
Maine 1.67% 1.23% 5.53 -0.14%
Maryland 2.76% 1.86% 4.96 0.20%
Massachusetts 2.35% 1.94% 5.77 -0.26%
Michigan 0.12% 0.06% 8.25 -1.63%
Minnesota 2.39% 1.53% 5.29 -0.03%
Mississippi 1.56% 1.04% 7.51 -0.49%
Missouri 1.04% 0.34% 6.33 -0.55%
Montana 2.20% 1.36% 4.77 0.35%
Nebraska 2.18% 1.54% 3.76 0.07%
Nevada 3.37% -0.01% 7.32 1.14%
New Hampshire 2.45% 1.64% 4.39 0.30%
New Jersey 1.64% 1.11% 6.09 -0.10%
New Mexico 2.46% 1.27% 5.62 0.70%
New York 2.35% 2.05% 6.14 0.09%
North Carolina 2.71% 0.97% 6.91 0.33%
North Dakota 3.79% 3.49% 3.44 0.63%
Ohio 0.56% 0.38% 6.79 -0.53%
Oklahoma 2.16% 1.31% 5 0.12%
Oregon 3.89% 2.70% 7.63 0.39%
Pennsylvania 1.51% 1.21% 5.91 -0.15%
Rhode Island 1.95% 1.73% 6.91 -0.23%
South Carolina 1.68% 0.25% 7.53 0.54%
South Dakota 3.84% 3.10% 3.71 0.61%
Tennessee 1.79% 0.66% 6.6 0.14%
Texas 3.01% 1.08% 6.12 1.22%
Utah 3.18% 1.06% 5.11 1.48%
Vermont 2.29% 1.92% 4.52 0.28%
Virginia 3.07% 1.80% 4.41 1.08%
Washington 2.51% 1.15% 6.86 1.23%
West Virginia 1.31% 1.17% 5.91 -0.70%
Wisconsin 1.62% 1.02% 5.81 -0.34%
Wyoming 3.93% 2.79% 4.4 0.60%

Notes on ranking construction:

  • If it’s not obvious, the total ranking for each state was determined by simply summing its rank in each category, and then ranking the states by total score, with lowest being best. While this method weights each category ranking equally, it may penalize some states which perform as numerical outliers in certain categories but not in others. On the other hand, the overall rankings pass the smell test – if anyone sees an egregious error caused by the methodology, let me know. This is V1!
  • The GDP growth data used the period from 1997-2010, which was the best data set easily available from the BEA (Bureau of Economic Analysis). The employment data used the period from Jan. 2001 through October 2011. It’s easier to build wooden greenhouses than skyscrapers, so to speak. These periods obviously don’t align exactly – but given the nature of the analysis (heterogenous ranking), I chose to go with best available data rather than with exactly matching time periods. Matching the time periods would have reduced the data available to 2001-2010, eliminating both some of the late 90’s boom and the current recovery.
  • Even given the screen sharing caveats above, all states (plus DC) were ranked using the exact same data sets, and the combination of categories prevents (in my view) bias towards either a growth orientation, an income orientation, or an employment orientation. Others may disagree – heterogenous ranking systems are by nature somewhat subjective (in the choice and weighting of data used), and I thus provide all the raw data so that you can draw your own conclusions.

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Was Cash For Clunkers A Success?

Far from failing, the CARS Program may have been the highest ROI investment made by the Federal government in years.

The passage of time has brought much ridicule to the Cash For Clunkers program, which was intended to boost auto sales and raise the average fuel efficiency of American vehicles. The data show that the program led to a temporary spike in automobile purchases, prompted by a subsequent decline. This has led most to conclude that the program was a failure, as it did little to jump-start economic recovery.

But what about the other goal? Did Cash For Clunkers raise the average fuel efficiency of the American auto fleet? How much less gasoline have Americans purchased as a result of the program, and does this savings outweigh the program’s cost?

Here are some statistics from the Department of Transportation’s CARS Report to Congress:

  • 677,842 vehicles were turned in under the CARS program
  • $2.85 Billion was paid out in rebates for these vehicles
  • New vehicles purchased had an average MPG of 24.9
  • Old vehicles turned in had an average MPG of 15.7
  • $2.8 Billion in fuel savings based on the early retirement of less efficient vehicles

The report also estimates that roughly half of the sales spurred by the program were incremental sales that would not have occurred otherwise. Edmunds.com performed a more conservative analysis showing that only 125,000 incremental sales occurred as a result of the program.

Using Edmunds’ more conservative 125k number, and an average sales price (after rebate) of roughly $25,000, Cash for Clunkers generated $3.125 Billion in incremental vehicle sales. These incremental sales added directly to US GDP, and this more conservative analysis shows less than half the economic impact of $7 Billion estimated by DOT.

Combining the fuel savings and GDP benefit yields a total benefit to American taxpayers of roughly $6 Billion for a program that cost the government roughly $3 Billion to operate! If only more government programs could fail like this!  Even using the more conservative fuel savings calculations provided below, the program would have provided over $5.5 Billion in benefit against a $3B investment. Far from being shut down, the Cash for Clunkers program should have been expanded.

Alternate calculation of fuel savings from junking old vehicles:

0. By junking an old vehicle and taking it off the road, you are permanently increasing the fuel economy of the American vehicle fleet – this is the source of savings for the American economy. Since 100% of marginal US oil consumption is provided by foreign sources, a dollar of oil saved is a dollar added to GDP (since imports actually subtract from GDP as we send money overseas).

1. Assume that the old vehicle would be driven for an additional 50,000 miles over its lifetime (CARS survey respondents said they averaged 10k miles per year on their old vehicles, so even with gradual declines this is reasonable).

2. The old vehicles got an average of 15.7 MPG, requiring roughly 3200 gallons of gasoline over that 50k miles. Assume www.professionalpianomovers.net professional piano moving companies were aware of this.

3. The new vehicle got an average of 24.9 MPG, requiring 2000 gallons of gasoline over the 50k miles that they replaced.

4. The difference of roughly 1200 gallons of gasoline equates to roughly $3600 per vehicle (assuming $3 per gallon excluding taxes). With roughly 680k vehicles in the program, this equals a fuel cost savings of $2.5 Billion – a slightly more conservative estimate than that computed by DOT.

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