I predict future happiness for Americans if they can prevent the government from wasting the labors of the people under the pretense of taking care of them.- Thomas Jefferson.

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Tuesday, July 31, 2012

Auditing Shooting Rampage Statistics

July 31st, 2012   Submitted by Davi Barker

Firearm prohibitionists love to use tragedy to leverage their agenda. So, it’s important for gun rights advocates to stand their ground and fire back (proverbially) whenever this happens.
Last week I posted a graphic on Facebook claiming the average number of people killed in mass shootings when stopped by police is 18.25, and the average number of people killed in a mass shooting when stopped by civilians is 2.2. I based it on 10 shootings I found listed on some timeline somewhere. I honestly don’t even remember where. I presented the case studies in a blog post on the Silver Circle blog and I did the math myself.
The graphic was met with great enthusiasm and much skepticism. Leave it to Facebook users to demand an audit on a meme. So, I started over, only much more meticulous this time. I compiled and analyzed 93 shootings, noting my methodology, and I am now prepared to present my findings, complete with links to the data. But here’s a spoiler… It’s not that different.
The average number of people killed in mass shootings when stopped by police is 14.3
The average number of people killed in a mass shooting when stopped by a civilian is 2.3.
I was so close! Here’s what I think accounts for the difference. In the first sample there was likely a selection error based on what grabs headlines. Larger shootings get more press, so if you take a small sampling you’re going to be working with a data set of the worst shootings. As for the consistency of the civilian statistic, it makes perfect sense if you think about from inside the mind of a heroic civilian with a concealed carry permit. It goes something like this:
“Holy crap! that guy shot that other guy.”
“He’s just going to keep shooting people.”
And the shooter goes down.
Quite a few cases went something like that. In fact, I found only one example of a shooter stopped by civilians who killed more than 3 people. Jared Loughner killed 6 people in Tucson, Arizona before he was tackled by two civilians. Maybe it’d have been less if one of those two men were armed.
I want to be perfectly clear. I am not much of a firearms enthusiast. I don’t own a firearm. I’ve only ever been shooting twice. For me it’s not an issue of gun rights. It’s about property rights. A person has a natural right to own a hunk of iron in any damn shape they want, and they shouldn’t be criminalized until they use that hunk of iron to harm someone. People can argue crime statistics ’till they’re blue in face. I frankly don’t care about people’s ideas for managing society.
What I am is a math enthusiast, so without further delay, here’s how I arrived at these numbers.
Step One: Amassing a data set
I searched for timelines of shootings and selected 5 that appeared the most comprehensive.
  1. Info Please
  2. CNN
  3. Denver Post
  4. News Max
  5. TruTV
While doing this I learned some important vocabulary. A “spree shooting” is when a killer murders in multiple locations with no break between murders. As in the Virginia Tech killer who began shooting in one hall, and then walked across campus and continued shooting in another hall. A “mass shooting” is when a killer murders multiple people, usually in a single location. As in the Fort Hood shooter who killed 13 people at one military base. A “school shooting” can be either of these as long as one or more locations is a school. As in the Columbine shooting, which is also classified as a spree shooting because they went from room to room. The term “rampage shooting” is used to describe all of these, and does not differentiate between them. So that is the term I’ll be using from here on out.
I selected these lists because they were the most comprehensive of those that I found, and I was seeking as large a data set as possible. I combined them all, including the first 10 from my previous post, and removed all redundant data for a total list of 93 shootings.
Step Two: Trimming irrelevant data.
While the list was comprehensive, the details about each shooting were not. In each shooting I had a date and a location, but often important details, like the number of people killed, or how the shooter was apprehended were missing. So, I set to the long task researching each incident to fill in the missing data. I didn’t incorporate the number of wounded people because so many were not reported. But the reason they call a single death a shooting rampage is because there were many injuries. All relevant data is contained in the links in the finished list below or in the timelines linked above. Most of the data came from either Wikipedia, a mainstream news article about the incident, or a handy resource I discovered called Murderpedia.
Next I removed incidents that did not fit within the scope of this analysis. Even though every incident on the list was a shooting, not every incident was a rampage shooting. So, I selected for incidents that included at least some indiscriminate targeting of bystanders. I removed incidents like Dedric Darnell Owens who shot and killed his classmate Kayla Rolland and then threw his handgun in a wastebasket. And I removed incidents like Michele Kristen Anderson who killed her entire family at a Christmas Party. So what remained were specifically rampage shootings in which a killer went someplace public and began firing at random people.
Suicide presented a tricky variable in the analysis. Roughly half of the remaining rampage shooters ended their own lives. So, I removed all incidents where the shooter killed themselves before police arrived reasoning that they had killed all they were going to kill and police had no impact in stopping them. Theoretically these incidents could have been stopped sooner by a civilian, but let’s not speculate. What I left in were incidents where shooters commit suicide after engaging the police, either during a shootout with police, or after a chase. I included, for example, Jiverly Wong, who witnesses say stopped shooting and killed himself as soon as he heard sirens but before police arrived, crediting the police’s response time with stopping the murders. But I did not include the shooters themselves in the total number of people killed.
I also removed cases like Edward Charles Allaway who shot up a library, then fled to a nearby hotel and called police to turn himself in, and cases like Darrell Ingram who shot up a high school dance and fled the scene only to be apprehended later after a long investigation. I was only looking for incidents when intervention from police or civilian saved lives.
What remained was 30 cases of gunmen firing indiscriminately whose rampage was cut short through the intervention of either a civilian or a police officer.
Step Three: The List
I divided the remaining cases into two categories, those stopped by police and those stopped by civilians. I included both armed and unarmed civilians for reasons that will become clear in the final analysis. I also removed one final case from the list. Dominick Maldonado went on a shooting rampage in a shopping mall in Tacoma, Washington, and although he ultimately surrendered to police he was confronted by two legally armed civilians who interrupted his shooting, but did not fire for fear of hitting innocent bystanders. So, I’m calling this one an assist from the civilians and taking it out of the analysis as an anomaly.
  • 9/6/1949 - Howard Barton Unruh went on a shooting rampage in Camden, New Jersey with a German Luger. He shot up a barber shop, a pharmacy and a tailor’s shop killing 13 people. He finally surrendered after a shoot-out with police.
  • 8/1/1966 - Charles Joseph Whitman climbed a tower at the University of Texas in Austin, Texas and began shooting at other students and faculty with a sniper rifle. He killed 16 people before being shot and killed by police.
  • 7/18/1984 – James Oliver Huberty shot up a McDonalds in San Ysidro, California killing 21 people before police shoot and killed him.
  • 10/16/1991 - George Hennard entered Luby’s Cafeteria in Killeen, Texas and began indiscriminately shooting the patrons. He killed 23 people in all. He commit suicide after being cornered and wounded in a shootout with police.
  • 11/15/1995 – Jamie Rouse used a .22-caliber semi-automatic rifle to fire indiscriminately inside Richland High School in Lynnville, Tennessee. He killed 2 people before being tackled by a football player and a coach.
  • 2/2/1996 - Barry Loukaitis entered Frontier Middle School in Moses Lake, Washington with a rifle and two handguns. He killed 3 people before the Gym teacher, Jon Lane grabbed the rifle and wrestled the gunman to the ground.
  • 10/1/1997 - Luke Woodham put on a trench coat to conceal a hunting rifle and entered Pearl High School in Pearl, Mississippi. He killed 3 students before vice principal Joel Myrick apprehended him with a Colt .45 without firing.
  • 12/1/1997 - Michael Carneal brought a pistol, two rifles and two shotguns to his high school in Paducah, Kentucky and opened fire on a small prayer group killing 3 girls. His rampage was halted when he was tackled by another student.
  • 4/24/1998 - Andrew Wurst attended a middle school dance in Edinboro, Pennsylvania intent on killing a bully but shot wildly into the crowd. He killed 1 student. James Strand lived next door. When he heard the shots he ran over with his 12 gauge shotgun and apprehended the gunman without firing.
  • 5/21/1998 - Kipland Kinkel entered Thurston High School in Springfield, Oregon with two pistols and a semi-automatic rifle hidden under a trench coat. He opened fire killing 2 students, but while reloading a wounded student named Jacob Ryker tackled him.
  • 4/20/1999 - Dylan Klebold and Eric Harris were the killers behind the Columbine shooting in Littleton, Colorado. The two both commit suicide after police arrived, but what many people do not know is that the school’s armed security guard and the police all stood and waited outside the library while executions happed right inside. 15 people died, not including the shooters.
  • 7/31/1999 - Mark Barton was a daytrader who went on a shooting rampage through two day trading firms in Atlanta, Georgia. He killed 12 people in all and after a police chase he was surrounded by police at a gas station where he commit suicide.
  • 1/16/2002 – Peter Odighizuwa opened fire with a handgun at The Appalachian School in Grundy, Virginia. 3 people were killed before the shooter was apprehended by 3 students, Mikael Gross, Ted Besen, and Tracy Bridges with handguns without firing.
  • 8/27/2003 – Salvador Tapia entered an auto parts store in Chicago, Illinois and shot and killed 6 people with a handgun. He then waged a gunbattle with police before a SWAT team fatally wounded him.
  • 9/24/2003 – John Jason McLaughlin brought a .22-caliber pistol to Rocori High School in Cold Spring, Minnesota. He killed 2 people before PE teacher, Mark Johnson confronted him, disarmed him, and held him in the school office for police to arrive.
  • 2/25/2005 – David Hernandez Arroyo Sr. opened fire on a public square from the steps of a courthouse in Tyler, Texas. The shooter was armed with an assault rifle and wearing body armor. Mark Wilson fired back with a handgun, hitting the shooter but not penetrating the armor. Mark drew the shooter’s fire, and ultimately drove him off, but was fatally wounded. Mark was the only death in this incident.
  • 3/21/2005 – Jeff Weise was a student at Red Lake High School in Red Lake, Minnesota. He killed 7 people including a teacher and a security guard. When police cornered him inside the school, he shot and killed himself.
  • 11/8/2005 – Kenneth Bartley, Jr. brought a .22 caliber pistol to Campbell County Comprehensive High School in Jacksboro, Tennessee and killed 1 person before being disarmed by a teacher.
  • 9/29/2006 – Eric Hainstock brought a .22 caliber revolver and a 20-gauge shotgun into Weston High School in Cazenovia, Wisconson. He killed 1 person before staff and students apprehended him and held him until the police arrived.
  • 4/16/2007 – Seung-Hui Cho was the shooter behind the Virgina Tech shooting in Blacksburg, Virginia. Police apprehend the wrong suspect allowing the shooter to walk across campus and open fire again in a second location. He eventually commit suicide after murdering 32 people.
  • 9/3/2008 – Isaac Zamora went on a shooting rampage in Alger, Washington that killed 6 people, including a motorist shot during a high speed chase with police. He eventually surrendered to police.
  • 3/29/2009 – Robert Stewart went on a killing rampage armed with a rifle, and a shotgun in a nursing home in Carthage, North Carolina. He killed 8 people and was apprehended after a shootout with police.
  • 4/3/2009 – Jiverly Wong went on a shooting rampage at a American Civic Association immigration center in Binghamton, New York where he was enrolled in a citizenship class. 13 people were killed before the shooter killed himself. Witnesses say he turned the gun on himself as soon as he heard police sirens approaching.
  • 11/5/2009 – Nidal Malik Hasan was the shooter behind the Fort Hood shooting at a military base just outside Killeen, Texas. The shooter entered the Soldier Readiness Processing Center, where personnel are disarmed, armed with a laser sighted pistol and a Smith & Wesson revolver. He killed 13 people before he was shot by a Civilian Police officer.
  • 2/12/2010 – Amy Bishop went on a shooting rampage in classroom at the University of Alabama in Huntsville, Alabama. She killed 3 people before the Dean of the University, Debra Moriarity pushed the her out of the room and blockaded the door. She was arrested later.
  • 1/8/2011 – Jared Lee Loughner is charged with the shooting in Tucson, Arizona that killed 6 people, including Chief U.S. District Court Judge John Roll. He was stopped when he was tackled by two civilians.
  • 2/27/2012 – T.J. Lane entered Chardon High School in Chardon, Ohio with a handgun and started shooting. 3 students died. The shooter was chased out of the building by a teacher and apprehended by police later.
  • 4/22/2012 – Kiarron Parker opened fire in a church parking lot in Aurora, Colorado. The shooter killed 1 person before being shot and killed by a member of the congregation who was carrying concealed.
  • 7/20/2012 – James Holmes went into a crowded movie theater in Aurora, Colorado and opens fire with an AR-15 semi-automatic assault rifle. 12 people were killed, before the shooter surrendered to police.
Step Four: Final analysis
With 14 incidents stopped by police with a total of 200 dead that’s an average of about 14.3. With 15 incidents stopped by civilians and 35 dead that’s an average of 2.3.
The first point I want to draw your attention to is that roughly half of shooting rampages end in suicide anyway. What that means is that police are not even in a position to stop most of them. Only the civilians present at the time of the shooting have any opportunity to stop those shooters. That’s probably more important than the statistic itself. In a shooting rampage, counting on the police to intervene at all is a coin flip at best.
Second, within the civilian category 10 of the 15 shootings were stopped by unarmed civilians. What’s amazing about that is that whether armed or not, when a civilian plays hero it seems to save a lot of lives. The courthouse shooting in Tyler, Texas was the only incident where the heroic civilian was killed. In that incident the hero was armed with a handgun and the villain was armed with an assault rifle and body armor. If you compare the average of people killed in shootings stopped by armed civilians and unarmed civilians you get 1.8 and 2.6, but that’s not nearly as significant as the difference between a proactive civilian, and a cowering civilian who waits for police.
So, given that far less people die in rampage shootings stopped by a proactive civilian, only civilians have any opportunity to stop rampage shootings in roughly half of incidents, and armed civilians do better on average than unarmed civilians, wouldn’t you want those heroic individuals who risk their lives to save others to have every tool available at their disposal?
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Monday, July 16, 2012

From Jason Hommel

At Freedom Fest this weekend in Las Vegas, Libertarian Carla Howell made the point that Romney would be far worse than Obama.  This surprised me, but it took me only moments of listening to realize it is true. 
Carla Howell's reason is that Romney is a big government politician.  Obamacare was based on Romneycare.  If the nation elects Romney, national health care, at least a replaced Romneycare, will be a reality for 50 years, and debate will be OVER, because it will be continually pointed out by the liberal media and controlled press that "both parties" and "everyone" wants it, even though that will not be true. 
I hope and pray that delegates will vote Ron Paul and nominate him as the Republican's choice for president.  But that might not happen.
The only other choice, the ONLY CHOICE, if Ron Paul does not become the Republican nominee, is Libertarian candidate, Gary Johnson, who was the former governor of New Mexico, who vetoed over 700 bills while in office, more than all the rest of the nation's governors combined.  When he ran for office, governor, for the first time, he spent $510,000 of his own money on his campaign, and received only $30,000 in donations at the last moment when it appeared as if he might win!  Amazing! 
The man is unbribable.  He's like an angel, but maybe better.  Bible says that a third of the angels fell.
I asked him if it was difficult to raise money, since nobody can bribe him with donations, since his principles are to libertarian truths, and not for sale.  Not even Libertarians can "get something" from a man who would have the government spend nothing!
He admitted it was difficult to raise money, and related the story above of spending his own money to gain office, with a mere $30,000 in donations!
How fortunate for the nation at this time that we have TWO excellent Libertarians entering the national debate and race for the office of the presidency!
How much more successful will Gary Johnson be with actual campaign contributions, this time around!  So, I'm proud to say that I just donated the maximum to his campaign, $2500.  Consider.  Ponder this next point:
Even if Gary Johnson does not win, he deserves your support, if you value freedom, if you value the future of your lives and children.
Even if Gary Johnson does not win, you have a chance to let your fellow Americans know that you refuse to vote for the lessor of two evils, and that you can support and encourage real freedom, and encourage other people to study and think about real libertarian ideals.
Voting is not a popularity contest.  It is not a chance for you to "show off" and to try to pick who other people think might be the winner. 
Voting is a chance for your own self-expression.  Trying to vote for who you think the winner might be is beyond foolishness.
Voting is your chance to raise your voice for real meaningful change.  The only way you can vote for real change is to vote for a man who will actually bring honest changes!
Even if "the libertarian" does not win, other politicians at all levels will take notice of how many people voted libertarian, and will be more likely to move their own views towards libertarian ideals of freedom.  But only to the extent that people vote libertarian!
And as it stands, Romney is likely the worse of two evils, since it appears he is willing to not only embrace every single big government idea, but even worse, propose his own!
The way I look at it, I can only hope that the nation is not headed into violent chaos of hyperinflation and big government oppression and violent revolution if the nation votes for Romney.  Or Obama.
As I see it, it's far more likely that the nation will discover a peaceful way towards freedom by supporting and voting for Gary Johnson.  As I see it, lives depend on this.  It is all the more important to vote for Gary Johnson if you live in a "blue" state like California who will likely vote for Obama anyway, because a vote for Romney would not only be harmful for the nation as described above, but a lost vote, as it would mean that you support the "status quo" of big government spending and continued erosion and oppression of our rights. 
Only a vote for Gary Johnson can register your peaceful discontent with the state and direction of our nation.  And if a vote counts, your early and immediate financial support means so much more.
But more important than political involvement, as a way to increase freedom in the US, is to buy silver!  Buying silver is an act of voting "no confidence" in the current government.  Buying silver reduces the oppressive power of the printing press of the Federal Reserve, which they use to bribe politicians, buy the media, bail out the banks, and buy votes. 
I spoke with Gary Johnson's running mate, Judge Jim Gray, a bit about a certain difficulty I have in understanding the consequences of electing freedom minded politicians.  I said, "Look at Ronald Reagan.  He was a gold advocate, and advocate for liberty, and he did good things for increasing freedom by reducing tax rates from 76% down to 33%.  Suppose that Gary Johnson manages to balance the budget and reduce government spending by 40%.  I asked, "Wouldn't this save the dollar, and preserve big government's control over us all the more?"  Yes, it might, but it's better than the alternative; potentially violent revolution through hyperinflation and big government crackdowns on freedom.  I agree.
We silver and gold bugs are a curious lot.  We are among the only ones who will actively work against the best interests of our own investments, for the good of the nation.  We buy gold and silver, but generally support politicians that might make our purchases of gold and silver unnecessary!
So, ironically, more important than voting, there is another non-political alternative, and something else you can do, in addition to donating and voting.  BUY SILVER!  Buying silver exponentially reduces the power of government's printing press, which they use to steal the productive capacity of the nation, and use to pay the manpower for their oppressive government programs.
If Libertarians Johnson/Gray advocate buying silver on the campaign trail, they have the potential to reach so many more people.  As it stands, the world wide physical silver investment market is only about $3 billion.  The Libertarians usually garner 1% of the vote.  But if they get 1% of the people to buy silver, well, 1% of money in the banks would be $180 billion.  Imagine what that would do to the silver market!  
Jim Gray got it.  He understood.  He wants to learn more.
People need to understand that it's not the government that needs to return to silver; the people must do it first.  Government will never lead, it will only follow.  It's up to the people to lead.
People get the government they deserve. 
Expect big things for silver and the Gary Johnson campaign in the coming months.  Donate early.  Help out early.  Volunteer.  Blog.  Facebook.  The more you do, the sooner, the better.
Gary Johnson has not paid for this endorsement, it was the other way around.
God bless.

Thursday, July 12, 2012

Gun Control Restricts Those Least Likely to Commit Violent Crimes: Newsroom: The Independent Institute

Gun Control Restricts Those Least Likely to Commit Violent Crimes: Newsroom: The Independent Institute

US health care: A reality check on cross-country comparisons

US health care: A reality check on cross-country comparisons
The United States spends substantially more on health care per capita than other developed countries. Based on comparison data of health status, the Organisation for Economic Co-operation and Development (OECD) published a report on health system performance, finding that the US system does not perform better than systems in countries that spend less. On many measures, US health status is inferior to those of other countries. We find these cross-country comparisons unable to adequately differentiate between health system performance and other confounding factors that determine health. In this Outlook, we provide a comprehensive critique of the OECD report and suggest several ways in which to strengthen the analysis. This includes improving the accuracy of infant mortality rates, employing life expectancy and premature mortality measures that are less sensitive to external factors, improving controls for external elements, and distinguishing between country-specific differences in health status and countries’ health care system efficiency.
Key points in this Outlook:
  • The United States spends substantially more per capita on health care than other developed countries, yet commonly cited reports indicate that the United States does not have superior health system performance.
  • The Organisation for Economic Co-operation and Development (OECD) uses mortality metrics to measure health care system performance, but these data do not adequately indicate health status differences and do not accurately judge health care system efficiency.
  • The OECD and other researchers must adjust their methods for measuring infant mortality, life expectancy, and premature mortality and control for confounding factors such as lifestyle to give a more accurate picture of health system performance.

The United States spends substantially more on health care as a percentage of gross domestic product (GDP) than other developed countries. In 2010, US health care spending amounted to 17.9 percent of GDP, which worked out to $8402 per person.[1] On the unadjusted measures customarily used to assess population health, US results are not better than those of countries that spend less, and on many of these measures, US outcomes are inferior.
This raises the question of whether the US health care system is inefficient. The primary source of comparison data on health outcomes is the Organisation for Economic Co-operation and Development’s (OECD) health system performance data and reports. This information is used to support broad criticisms of the US health care system and to compare it unfavorably with others, particularly the state-operated or state-controlled systems of Europe. Illustrations of such critiques include assessments by Washington Post columnist Richard Cohen and the Commonwealth Fund.[2]
Using these health comparison data, the OECD Economics Department issued a major report in 2008, henceforth referred to as “the OECD report.”[3] More recently, the OECD issued an expansion of the report, which is primarily based on the same underlying empirical analysis and was written by some of the same authors as the earlier report.[4]
"The combination of higher delivery costs because of greater NICU use and the unique way the United States counts live briths could lead one to erroneously conclude that the United States is highly inefficient compared to other industrialized nations."
This Outlook offers a brief critical assessment of international health system performance metrics. We will focus on three statistics that the OECD delves into in its report: infant mortality, life expectancy, and premature death. The strengths and weaknesses of these measures are illuminated through brief examples that ultimately demonstrate that the measures do not reflect the efficiency of any country’s health system. Given that organizations such as the OECD continually try to evaluate countries’ health systems, US policymakers and analysts must understand the limitations of such exercises. We conclude with suggested changes in approach and a road map for improved research.
Before describing the key metrics for international comparison, it is useful to recall the relatively recent origin of international health statistics. The OECD was created in 1948 as the Organisation for European Economic Co-operation (OEEC) to administer funds made available by the US Marshall Plan for the reconstruction of Europe after World War II. Later, the OEEC’s membership was extended beyond Europe. In 1961, it was reformed into the OECD. Today, its members are thirty-four developed countries.[5]
Over the last three decades, OECD has published a set of international health statistics based on data supplied by member countries. The data are collected and collated by the Health Division within the Directorate for Employment, Labor, and Social Affairs.
Health Status Metrics
A common misconception is that people value health care in and of itself. In reality, people value the improved health status that they hope to gain from receiving health care. Indeed, using most health care is unpleasant. Health status is not directly measurable; it can only be approximated through related factors that can be measured.
The OECD report focused on observable measures as proxies of health status to provide comparative statistics. A depressing reality is that these observable measures are all some derivative of mortality. The OECD expects all its member states to provide death registers as part of a planned, one-hundred-year public health mission to identify sources of death and time of death to track epidemiological emergencies such as those resulting from infectious diseases. In the service of OECD, mortality metrics are outcome measures that are meant to proxy health status and the output of health care systems, rather than the consumption of health services.
The OECD uses infant mortality, life expectancy, and premature death as measures of mortality in their report.[6] The validity of each one of these measures as proxies for health system performance is examined below.
Infant Mortality. There are three overlapping OECD infant mortality measures: infant, neonatal, and perinatal mortality.[7] Infant mortality is the number of deaths in the first year per one thousand live births. Neonatal mortality is the number of deaths in the first twenty-eight days per one thousand live births. Perinatal mortality is the number of deaths in the first week after birth, plus fetal deaths after twenty-eight weeks of gestation or fetuses that exceed a weight of one thousand grams.
Partly based on an argument by Nixon and Ullmann, the OECD report states that these infant mortality measures are less influenced by factors unrelated to the health care system than are other possible measures.[8] However, we believe that the opposite is true. One major concern is that the basic definitions of infant mortality are not consistent across countries.
For example, babies who are not viable and who die quickly after birth are more likely to be classified as stillbirths in countries outside the United States, especially in Japan, Sweden, Norway, Ireland, the Netherlands, and France. This is especially likely for babies who die before their birth is legally registered.[9] In the United States, however, nonviable births are often recorded as live births, making the US infant mortality rate appear misleadingly high. In a detailed study of medical records and birth and death certificates in Philadelphia, Gibson and colleagues found that infant mortality had been overstated by 40 percent, merely as a result of these nonviable births that were recorded as live births.[10]
There is another problem with using infant mortality to represent health care efficacy. US physicians often go to great efforts—at the prenatal and postnatal stages—to save a baby with poor survival chances. The additional prenatal care an American doctor provides may improve the odds of the live birth of a baby with poor survival chances, who is then likely to require extensive neonatal care. Accordingly, the US uses substantially more neonatal intensive care units (NICU) than other industrialized countries. In this case, the additional health care may actually worsen reported infant mortality rates and misleadingly suggest poor care in the United States. Similarly, US physicians are more likely to resuscitate very small premature babies, many of whom nevertheless die and many others of whom live with serious and expensive medical problems. This practice also raises measured infant mortality rates for the United States.
The combination of higher delivery costs because of greater NICU use and the unique way the United States counts live births could lead one to erroneously conclude that the United States is highly inefficient compared to other industrialized nations. Furthermore, infant mortality is strongly and immediately affected by external influences such as the mother’s age, behavior, and lifestyle (meaning factors such as obesity and use of tobacco, alcohol, and illicit drugs).[11] Infant mortality is strongly linked to birth weight and gestational age, which are highly, but not perfectly, correlated. Indeed, the correlation is high enough that researchers will often use one or the other measure according to conveniences. In any case, both measures are largely a result of parental lifestyles.
Teenage mothers are more likely to have preterm, low-birth-weight babies. The mortality rate for infants born to US teenage mothers is 1.5 to 3.5 times as high as the rate for infants born to mothers ages twenty-five to twenty-nine.[12] The US rate of births for teenage mothers is very high—2.8 times that of Canada and 7.0 times that of Sweden and Japan. If the United States had the same birth weights as Canada, its infant mortality rate—adjusting for this variable alone—would be slightly lower than Canada’s (5.4 versus 5.5 per one thousand births).[13]
Turning to gestational age, MacDorman and  Mathews calculate that if the United States had the same distribution of gestational ages as Sweden, its recorded infant mortality rate would drop by 33 percent,  tying it with France as the fifth lowest rate out of twenty-one developed countries.[14] Moreover, in the United States, mortality rates for infants born to unwed mothers were about twice as high as for infants born to married women.[15]
Overall, these lifestyle and socioeconomic factors may reflect poorly on some aspects of society in the United States in comparison to other countries. It is inappropriate, however, to conclude that the root cause is the US health care system rather than societal factors in a dynamic heterogeneous society. Infant mortality is a particularly misleading metric by which to grade country-specific health system performance and to make international comparisons.
"A further limitation of using potential years of life lost as a mortality measurement is that many deaths are caused by other external factors--such as obesity and pollution--which are disguised by the disease they cause."
Life Expectancy. In the abstract, life expectancy (LE) could be an effective metric for comparing international health systems. But there are problems with this measure. One important flaw is that it incorporates infant mortality, which, as discussed above, is confounded by external factors and is not identically measured across all countries covered in the OECD report.
Our main concern is the dependency of LE upon which benchmark age is used. For example, LE can be measured at birth or at older ages such as at the age of forty, sixty, or sixty-five. The OECD uses LE at birth. But LE at older ages is less affected by the measurement, lifestyle, and cultural problems inherent in infant mortality and in LE at birth. Measurement errors and definitional differences related to infant mortality do not directly affect LE at later ages.
Thus, the measurement errors and lifestyle and cultural influences that affect the infant mortality measure are directly imported into LE calculations. In a comparative study of the United States, the United Kingdom, and Germany, Martin Neil Baily and Alan Garber conclude:
Neonatal mortality is heavily influenced by social and economic factors, along with individual health behaviors, that are not strongly related to health care delivery. Overall life expectancy at birth, then, may be an unsuitable measure of health outcomes for the purpose of measuring productivity of health services.[16]
As a result of the problems with infant mortality (as well as mortality due to violence and accidents), the difference between US life expectancy and that of other countries is reduced at later ages. This is demonstrated in empirical studies of the production of health, including in the OECD report itself and also in the raw data. For example, in 2000, female life expectancy at birth was 79.3 years in the United States, 80.3 in the United Kingdom and 81.2 in Germany. Female life expectancy at sixty-five was 19.0 years in the United States, 19.0 years in the United Kingdom and 19.6 years in Germany.[17] The differences decline from 1.0 and 1.9 to 0.0 and 0.6.
Premature Mortality. Premature mortality, which is determined by potential years of life lost (PYLL), is a useful measure if appropriately calculated, though it is also strongly influenced by infant mortality. One advantage—stressed by the OECD—is that PYLL can be linked to cause of death.[18] Since PYLL is calculated from deaths that occur before the defined full life (seventy years in the OECD report), one can include or exclude deaths based on their specific causes. This allows the analyst to reduce, but not eliminate, the confounding of some external causes with health care inputs and with country-specific effects. Oddly, the OECD does not use PYLL measurements for cross-country comparisons.
One can calculate PYLL numbers for categories of diseases that are more related to health care and analyze the effect of the health care system and other variables on PYLL by those categories. Miller and Frech have done this for the respiratory, circulatory, and cancer categories and Or, Wang, and Jamison have done the same for heart disease.[19]
With this in mind, the OECD states that adjustments to PYLL numbers were made in one area, namely to exclude transport accidents, accidental falls, assaults, and suicides. However, while the OECD performs some analyses with these PYLL number adjustments, it does not do so for the country-specific analyses.
Though helpful, moreover, adjustments of PYLL numbers are not perfect. Accident and assault victims use health care resources, especially if they do not die quickly. But the costs associated with this care cannot be accounted for.
A further limitation of using  PYLL as a mortality measurement is that many deaths are caused by other external factors—such as obesity and pollution—which are disguised by the disease they cause (respectively, circulatory and respiratory disease). PYLL cannot be adjusted to reflect these factors; the mediating disease, not the underlying external cause, will be recorded as the cause of death.
In the OECD report, the maximum age at which to establish PYLL is seventy. Thus, the costs and success (or lack of success) of a health care system in extending life and the quality of life beyond age seventy are not reflected. The authors of the report recognize that this is a weakness of this measure.[20] The costs of this care for consumers ages seventy years or more are reflected in the OECD expenditure data, but the health outcomes are not reflected in the PYLL measure.
Accounting for Quality of Life
Mortality data are an inadequate proxy for health system performance for another reason: they measure years of life, but do not reflect the quality of that life. Mortality measures need to be adjusted to give a better picture of health status. The common terms for these adjusted measures are quality-adjusted LE (QALE), disability-adjusted LE (DALE), and health-adjusted LE (HALE).[21] These adjustments depend on the values of the individual consumers and thus differ person by person. In practice, surveys of consumers or experts (typically panels of physicians) are used to find average weights to be applied in research.[22] In some surveys, for instance, a year spent with a migraine headache is considered to be an indicator of very low quality of life and is counted as equivalent to only a month of healthy time; the year with the migraine would be weighted at one-twelfth, or 0.083 of a healthy year.
The OECD report, however, treats all years of life as the same, regardless of health status. HALE is discussed, but not used. The OECD report sticks with raw LE—rather than using quality-adjusted versions—because of the wider availability of unadjusted LE data, but at the expense of conceptual accuracy. As a result, the OECD report attributes no value to expenditures that permit people to enjoy a better life by, for example, being able to work or to be functional longer; it correlates expenditures only with mortality. Thus, money spent on knee replacements, for instance, would appear to be inefficient in that it does not decrease mortality, despite the obvious advantages of improved mobility and prevention of falls. Therefore, it is difficult to see mortality alone as an accurate measure of health system efficiency.
A Road Map for Improvement
We propose some improvements for future research of this kind, beginning with infant mortality. Infant mortality seems to be the least accurate measure of health status because it is most heavily influenced by factors external to the health care system. However, many of those external factors could be addressed by controlling for birth weight and gestational age. Keeping birth weight and gestational age constant would eliminate some of the confounding effects of lifestyle and other influences. The result of doing so is dramatic, as we have seen. One could form an index by picking a distribution of weights to multiply by the birth-weight-specific infant mortality rates.
LE at birth and PYLL numbers are at risk of being seriously flawed because of infant mortality miscalculations. Considering a version of PYLL that excludes most of the causes of death that affect infants would decrease this risk.
One can somewhat reduce the problem of confounding variables by focusing on LE at later ages. As discussed (and contrary to the assertions of the OECD report), infant mortality is highly influenced by external factors and by definitional and measurement problems. LE at later ages—such as at forty, sixty, or sixty-five—eliminates the people who have died before the selected ages. Furthermore, many of the lifestyle choices that lead to bad health outcomes are more heavily concentrated among younger consumers and affect LE more at younger ages. For example, in 2003-2005, annual US motor vehicle deaths peaked at 33 per 100,000 people at age seventeen. This peak was a maximum statistic that was not reached at any subsequent age.
Similarly, the all-injury death rate has an early peak at age eighteen. After that, the all-injury death rate does not catch up to that level until age seventy-five.[23] Using LE at birth fails to adjust for these factors and incorrectly lowers the apparent efficiency of the US health care system.
Accidental and violent deaths need to be excluded from PYLL measurements in making country-level comparisons. The OECD pursues this to some extent by excluding certain accidental and violent deaths from their measurements. But since the PYLL results for country-level efficiency are not reported, the result of adjusting for these causes of death is not reflected. The country-level analysis is entirely in terms of LE and infant mortality, which have questionable validity.[24]
"It is overreaching to interpret country-specific variation in health outcomes as a measure of health care system productivity."
Finally, since morbidity is so important, it would also be relevant to use a measure of quality-adjusted or disability-adjusted LE. This change would be a major contribution to the cross-country health status comparisons.
The OECD report raises important questions on how to determine the efficiency of health care in producing positive health outcomes and how to compare and contrast efficiency of systems among different countries. The OECD staff concludes that health care is highly productive in improving health outcomes and that efficiency varies greatly across countries. It provides country-specific estimates of that efficiency.
Unfortunately, major problems in OECD’s analysis render their conclusions—especially the country-specific conclusions—unreliable. Many external factors that influence health outcomes are either omitted or poorly measured. The net effect is to underweight the role that non-health care factors play in determining health. And since the United States scores relatively poorly on most of these external measures, omitting them or not adequately controlling for them increases the apparent relative inefficiency of the US health care system and probably biases the estimated productivity of health care as well. The OECD report controls to a limited extent for some lifestyle differences by gross measures (for example, consumption of alcohol, tobacco, fruits, and vegetables). It adjusts one health measure—PYLL—for violence and accidents, but does not use that measure for country-specific efficiency numbers. As explained above, we believe that these controls and adjustments are inadequate.
It is overreaching to interpret country-specific variation in health outcomes as a measure of health care system productivity. In reality, the country-specific estimates reflect all differences in country-level influences, whatever their source and measurement issues. As econometrician William Greene stated in a similar context, there are considerable differences among countries that masquerade as inefficiency. More carefully calibrated research is necessary to identify these differences.[25]
H.E. Frech III (frech@econ.uscb.edu) is an adjunct scholar at AEI and a professor in the Department of Economics at the University of California, Santa Barbara; Stephen T. Parente (stephen.parente@gmail.com) is an adjunct scholar at AEI and a professor in the Department of Finance at the Carlson School of Management at the University of Minnesota; and John S. Hoff (johnseaburyhoff@yahoo.com) is a visiting scholar at AEI and was health attaché to the US mission to the Organisation for Economic Co-operation and Development, 2005-2009.