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Posts Tagged ‘Freedom in the 50 States’

Are you an economics graduate student casting about for dissertation topics? I have a few ideas for you. As part of the rewriting of Freedom in the 50 States, I’ve been reviewing the economic literature on how various public policies affect consumer and producer surplus, deadweight loss, and so on. We use an estimate of “victim cost” for each policy to weight the policy. The weighted sum of policies comprises the freedom index. Interestingly, the literature on some public policy issues is quite thin. That makes it difficult for us to come up with weights, and sometimes we have to do no more than guess.

Without further ado, here is a list of research questions to which I for one would like to see credible answers:

  1. How productive are publicly owned hospitals relative to for-profit and charitable ones?
  2. How accurate are people in estimating how much of their state’s residents’ income is taken in state and local taxes?
  3. How do state-level regulatory takings compensation requirements affect local land-use regulation and economic outcomes such as housing prices and population growth?
  4. How does state-level eminent domain reform affect actual local eminent domain takings?
  5. How do laws forbidding employers from forbidding guns on their property affect employers’ liability insurance rates?
  6. What are the effects of state workers’ compensation laws on workers’ comp costs? What is the effect of employers’ WC coverage costs on employment and wages? How efficient are state funds relative to private insurers?
  7. What is the incidence of state short-term disability insurance coverage mandates? In other words, which workers lose, which ones win, and by how much? What is the effect on labor supply?
  8. How does mandatory paid family leave affect labor supply and wages?
  9. How do state mandatory E-Verify programs affect employment rates of natives and immigrants and aggregate economic growth? What are their administrative costs?
  10. How do state anti-discrimination laws in employment (above the federal minimum) affect lawsuits, liability insurance rates, and tort judgments against companies? How effective are they at reducing employment and wage differentials?
  11. How do state-mandated health insurance benefits affect premiums after the PPACA? How do direct access to provider mandates affect premiums and health care spending? What about standing referral mandates?
  12. How do video franchising reform and general telecom deregulation (along different dimensions) affect broadband rollout, competition, and prices?
  13. How does severity of occupational licensing (education and examination requirements especially), not just prevalence or existence of licensing, affect prices, wages, and deadweight loss?
  14. Here’s one for the political scientists: do state sunrise and sunset provisions affect occupational licensing burdens?
  15. What are the economic impacts of being inside versus outside the Nurse Licensure Compact? What are the effects of having a “nursing consultation exception” that permits some interstate practice?
  16. How does membership in the Interstate Insurance Product Regulation Compact affect the number of life insurance and annuity offerings in a state and their premiums? How does it affect wages of life insurance agents, independent versus employed? How do state form filing requirements affect these outcomes?
  17. How do certificate of need laws affect density of ambulatory surgery centers?
  18. What is the effect of state rate filing requirements for personal auto insurance and homeowners’ insurance on premiums and coverage rates (residual markets)? What about bans on certain kinds of rating, e.g., territorial?
  19. What is the effect of California’s Proposition 65 on prices of consumer products, manufacturing production, and manufacturing employment? How many products are not sold at all in California as a result of the law, and what are the economic losses?
  20. What is the effect of allowing direct-to-consumer Tesla sales on consumer surplus?
  21. What is the effect of requiring certificates of public convenience and necessity for household goods moving companies on prices, moving company profits, consumer surplus, and deadweight loss?
  22. What is the effect of general retail sales-below-cost laws on retailer margins, prices, and productivity?
  23. How effective are certain tort reforms, such as joint and several liability reform/abolition and punitive damages caps/abolition, on liability insurance costs?
  24. How does concealed carry license cost, including mandatory training, affect the number of license holders? How do various state gun regulations, such as assault weapons bans, high-capacity magazine bans, “Saturday night special” bans, licensing of gun buyers/owners, mandatory sale of locking devices, and state licensing of dealers, affect gun prices, sales, and ownership rates?
  25. How do happy hour bans affect alcohol sales and restaurant and bar profitability?
  26. How do direct-to-consumer wine shipping bans affect wine prices and sales?
  27. How does permitting wine and spirits sales in grocery stores affect sales?
  28. How does marijuana decriminalization affect consumption and producer and consumer surplus? What is the price elasticity of demand for marijuana?
  29. How do penalties for marijuana cultivation and distribution affect quantity supplied?
  30. How do Salvia divinorum bans affect consumption and producer and consumer surplus?
  31. What would Americans be willing to pay for greater privacy? E.g., not having fingerprints on driver’s licenses, not having SSN’s stored in government databases, not having to go through sobriety checkpoints, not being tracked by automated license plate readers, etc.?
  32. Do bans on home poker games affect the prevalence of such games? Do gambling penalties (felony vs. misdemeanor) affect the prevalence of illegal gambling?
  33. What is the price elasticity of demand for casino gambling? How do casino regulations/legalization affect consumer surplus?
  34. What is the size of the U.S. raw milk industry? What is the consumer and producer surplus? How would banning raw milk affect welfare?
  35. How have restaurant trans fat bans affected sales, prices, and consumer welfare?
  36. What is the consumer surplus from mixed martial arts? What are the economic effects of state legalization?
  37. How do mandatory state approval/accreditation and registration of private schools affect private school enrollment and competition? What about mandatory licensure of private school teachers?
  38. How do home school regulations affect the number of home schoolers by state?
  39. How do smoking bans in bars affect bar turnover, profitability, and competition? Believe it or not, no one has analyzed bars separately from restaurants, even though the effects on bars are hypothesized to be much larger.
  40. Do regulations on cigarette vending machines and Internet sales affect consumption?
  41. How did sodomy laws, gay marriage bans, and “super-DOMAs” affect the migration of gay couples? What can we infer about their effect on gay Americans’ well-being?
  42. How do campaign contribution limits affect would-be contributors’ welfare?

All of these policies show some variation across states, making it possible to do some research on their effects across states. Not all of them are hugely economically significant, but they are all at least somewhat controversial politically. How can legislators make informed decisions about these policies without at least rough estimates of their consequences for citizens?

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This post will illustrate how users can customize the freedom index according to their own judgments about how various policies affect freedom. In particular, it will show how the weighting for tax burden can be significantly reduced and explores the consequences of this choice. It will also discuss briefly how abortion policies might be included in a customized index. Readers interested in customizing the freedom index should download the weighting spreadsheet at freedominthe50states.org.

Weighting Taxation

The freedom index “weights” each policy variable by the dollar-terms amount of benefit received by victims of government intervention from a one-standard-deviation, nationwide shift in the variable in a freer direction. So the weight for taxation is simply the number of dollars represented by a one-standard-deviation shift in state and local tax burden as a percentage of personal income. The mean of tax burden is 0.095 (9.5% of personal income). The standard deviation is 0.0124. Therefore, the weight of the variable in the index is 0.0124 times national personal income, which was $12.357 trillion in 2010: $153.1 billion. That ends up being worth 28.6% of the total weights for all variables in the index.

That’s a lot. The numbers don’t lie, but we do note in the text one reason why this number may actually overestimate the true “loss of freedom” caused by taxation:

This index’s weight for tax burden assumes that all taxes take away freedom. But in fact some taxpayers consent to at least some of the taxes that they pay, as long as the taxes are legal and generally paid by others. Therefore, taxation is not wholly a violation of their freedom, as “freedom” is defined above. However, most criminal justice policies do not operate along these lines. For instance, an imprisoned drug possessor is no more likely to consent to being confined if others are as well, and a driver fined for not wearing a seat belt does not usually consent to being fined if others are, and so on.

Rather than trying to figure out how much of the observed taxation truly represents a diminution of freedom, this study uses aggressive estimates of the value of freedom from taxation and other fiscal policy measures, and then boosts the weighting of certain personal freedoms and economic regulations, as explained in the relevant sections below. The point is to make sure that the index is using an equally aggressive method for estimating the values of all the different freedoms it covers.

Now, one might believe that we have not gone far enough to adjust for this problem, and indeed that is the whole point of putting the spreadsheet online and encouraging reader customization. The freedom index as it currently stands is in some ways a libertarian’s index. If you think that all taxation diminishes freedom, you will like the weight it enjoys in the published study.

But what if you are a philosophically sophisticated progressive or “liberaltarian,” who does not have any personal issue with taxation, but who nevertheless thinks that negative liberty is part of justice, and that the costs that others associate with taxation are worth taking into account. What weight should you put on tax burden?

Let’s assume that the current tax burden in each state represents the ideal point of the median voter. Positive theories of democracy would suggest that this is as good a guess about where public opinion lies as any. Then 50% of voters would prefer a higher tax burden (and the services it would finance), and 50% would prefer a lower tax burden. Right away, we can slash the tax burden weight in half, because 50% of voters nationally would not see the taxes they currently pay as any diminution of their freedom at all. Now, this move assumes that the median-dollar taxpayer is the same as the median voter. That is unlikely to be the case. In fact, the median-dollar taxpayer is likely to be somewhat wealthier than the median voter and thus more ideologically conservative and more hostile to taxation. Thus, if anything, slashing tax burden in half on these grounds is somewhat too aggressive.

But we’re not done yet. Of the 50% of voters/taxpayers who would prefer a lower tax burden, most of them would not see all of the taxes they pay as a diminution of their freedom. That is, they would be fully willing to pay a lower tax burden that is greater than zero. To illustrate the logic, assume a normal probability density function over possible tax burdens, as follows:
normal
On the X axis is tax burden, and on the Y axis is the proportion of the population corresponding to a particular view on tax burden. Fifty percent of the curve lies to the left or right of the mean of the tax burden distribution, which is 9.5, the actual national mean of state and local tax burden. (I have drawn the curve under the assumption of a standard deviation of 2.375, a fourth of the mean, but nothing that follows hinges on this assumption. Note that the standard deviation of voters’ views on taxation should be significantly greater than the standard deviation of actual state tax burdens, because each state tax burden roughly represents a median of a distribution.)

Now, what are the losses experienced by those who prefer a lower tax burden than what currently exists in their state? The loss curve will look like a mirror image of the left side of the normal density function. Those who want zero taxation will see all 9.5% of income taxed away as a loss of freedom. Those who want taxation of 2.5% of income will see 7% of income taxed away as a loss of freedom. And so on. Because the loss function is a mirror image of the probability density function, the area under the loss curve is also 0.5. So only 4.75% of personal income, in total, is a loss to those who prefer lower taxation. We can divide tax burden’s weight by two again, or by four in total.

The way to do this in the weighting spreadsheet is as follows. On the 2001-2011 worksheet, you can find all the standard deviations and weights of the variables in column GW. The weight for tax burden (“ainctot3”) is in cell GW10. You can divide the value there by four to create a new weight. All the other weighting cells automatically recalculate, and you now see in cell GV10 that tax burden is now worth just 9.19% of the index. (Why not one-fourth of 28%? Because reducing taxation’s weight also reduces the sum of all weights.) Fiscal policy as a whole is now worth just 17% of overall freedom, while personal freedom is 42%, and regulatory policy is 41%.

Note that all of the measures we took to boost personal freedom in the study remain in place, so this approach really does aggressively reduce the importance of taxation. I’ll call this new, nerfed-taxation index “Sandals,” as contrasted with the published index, which I’ll call “Suits.” How do the rankings of states differ between “Suits” and “Sandals”? See the table below.

“Suits” “Sandals”
1. North Dakota 1. North Dakota
2. South Dakota 2. Indiana
3. Tennessee 3. New Hampshire
4. New Hampshire 4. Tennessee
5. Oklahoma 5. Nevada
6. Idaho 6. South Dakota
7. Missouri 7. Utah
8. Virginia 8. Iowa
9. Georgia 9. Delaware
10. Utah 10. Georgia
11. Arizona 11. Idaho
12. Montana 12. Nebraska
13. Alaska 13. Virginia
14. Texas 14. Missouri
15. South Carolina 15. Kansas
16. Indiana 16. Arizona
17. Delaware 17. Colorado
18. Alabama 18. Oklahoma
19. Colorado 19. North Carolina
20. Nevada 20. Alaska
21. New Mexico 21. Maine
22. Nebraska 22. Texas
23. Florida 23. South Carolina
24. North Carolina 24. Minnesota
25. Iowa 25. Wyoming
26. Kansas 26. Massachusetts
27. Kentucky 27. Oregon
28. Oregon 28. Montana
29. Washington 29. Florida
30. Massachusetts 30. Ohio
31. Pennsylvania 31. Pennsylvania
32. Arkansas 32. Wisconsin
33. Ohio 33. New Mexico
34. Minnesota 34. Kentucky
35. Michigan 35. Vermont
36. Wyoming 36. Washington
37. Louisiana 37. Michigan
38. Wisconsin 38. Connecticut
39. Maine 39. Arkansas
40. Connecticut 40. Alabama
41. Mississippi 41. Rhode Island
42. West Virginia 42. Louisiana
43. Vermont 43. Maryland
44. Maryland 44. West Virginia
45. Illinois 45. Hawaii
46. Rhode Island 46. Illinois
47. Hawaii 47. Mississippi
48. New Jersey 48. New Jersey
49. California 49. California
50. New York 50. New York

The two rankings still look pretty similar! Three of the same states are in the top five in both indices, and the bottom three are identical as well. Indiana moves up from #16 to #2 between “Suits” and “Sandals,” and Nevada moves up from #20 to #5. Meanwhile, Oklahoma falls from #5 to #18, and Alabama falls from #18 to #40. But those are some of the biggest changes in rank; most states stay in a pretty similar location. It turns out that even a left-leaning index of negative liberty puts red and purple states at the top and deep blue states at the bottom.

Including Abortion

Abortion policies have to be imported from another spreadsheet in order to be included in the freedom index. A little more Excel mastery is helpful here. The abortion policy spreadsheet is available at statepolicyindex.com (p_abor_11.xls).

Now, there are a few things to note about state abortion laws. Most state abortion laws that are actually enforced do not do much to limit first- and second-trimester abortions. Because of Roe v. Wade, states do not have the right to prohibit abortions before fetal viability. However, some abortion policies we code, like requiring that only licensed physicians perform abortions, requiring that abortions be performed in a hospital, restricting private insurance coverage of abortions, and imposing waiting periods for abortions, can raise the effective cost of getting even an early abortion. Some pro-choicers, particularly libertarians, might well see certain state restrictions, such as prohibiting Medicaid funding for abortions, restricting partial-birth and late-term abortions, and requiring parental notification for minors’ abortions, as justifiable.

The variable “pabor” gives a summary indicator of state abortion laws based on principal component analysis. It is available only for 2006-2010 because one of the constituent variables is unavailable for 2000. States scoring higher on “pabor” have more abortion restrictions, including limits on public funding. To insert the variable into the freedom index, simply create two new rows in the freedom index spreadsheet and paste the “pabor” values into the first row (values/transpose). Since abortion laws affect personal freedoms on any interpretation, you may wish to include abortion policies with the personal freedoms, for instance on rows 139 and 140. You may wish to carry 2006/7 values back to 2001.

Next, you need to adjust the raw values of “pabor” to put them on a standardized scale with other variables. Every other row of the spreadsheet consists of these adjusted values. The adjusted values lie right below the raw values of each policy variable. If you think fewer abortion restrictions enhance freedom, then you think that higher values on “pabor” are worse. Find another variable like that — “tpubfin” is an example on rows 125-126. You can copy and paste the formula for adjusted “tpubfin” values to adjust the “pabor” values. If you think fewer abortion restrictions threaten freedom, then you think that higher values on “pabor” are better. Find another variable like that — “tgprp” on rows 133-134 is an example. Copy and paste the “adjusted” row.

Next, make sure that the mean and standard deviation of the variable are calculated in columns GV and GW. Below the mean and standard deviation are the weights. For the purposes of this exercise, I’ll give abortion a weight equal to same-sex partnerships, about $10.4 billion. Make sure that the percentage weight is calculated in column GV by copying and pasting one of the bolded percentage weights from another variable (it doesn’t matter which). Also make sure that the summed weights is updated by changing the formula at the bottom of column GW (row 243 after inserting two rows for abortion). Make sure that the dollar weight for abortion laws is included.

Finally, update the personal freedom scores. For instance, go into GU143 and type at the end of the parenthetical expression: “+GU140*$GV140” (without quotes). That updates Wyoming’s score. Then just drag the formula all the way to the left. Personal freedom scores are all updated, and overall freedom updates automatically.

Now what does the freedom ranking look like? I’ve taken the steps to create a pro-choice ranking that also nerfs taxation. Here it is:

Pro-Choice Sandals
1. New Hampshire
2. North Dakota
3. Indiana
4. Tennessee
5. Nevada
6. Delaware
7. South Dakota
8. Iowa
9. Utah
10. Nebraska
11. Georgia
12. Idaho
13. Virginia
14. Colorado
15. Kansas
16. Arizona
17. Alaska
18. Missouri
19. North Carolina
20. Oklahoma
21. Maine
22. Texas
23. Oregon
24. South Carolina
25. Wyoming
26. Minnesota
27. Montana
28. Massachusetts
29. New Mexico
30. Florida
31. Vermont
32. Ohio
33. Pennsylvania
34. Wisconsin
35. Washington
36. Kentucky
37. Michigan
38. Connecticut
39. Arkansas
40. Alabama
41. Rhode Island
42. West Virginia
43. Maryland
44. Hawaii
45. Louisiana
46. Illinois
47. Mississippi
48. New Jersey
49. California
50. New York

Not all that different. I’ve taken all the assumptions most favorable to a “liberaltarian” conception of negative liberty, and most states do not jump or fall very many places in the ranking. I don’t say this to tweak liberaltarians, but to point out how robust the freedom ranking is to even drastic changes of assumptions. It’s such a big dataset that seemingly big changes have small effects on the end result. New York, California, and New Jersey really are the most regulated states, no matter how you slice it. The Dakotas, Tennessee, and New Hampshire really are among the least regulated states. “Conservatarians” may be distressed by the low placement of states like Mississippi, West Virginia, and Louisiana in the published index. My guess is that the freedom ranking will be equally robust to changes in more right-wing direction, such as by nerfing many of the bonuses we gave to personal freedom variables, including abortion restrictions as a plus for freedom, and so on.

Although the freedom index is reasonably robust to changing assumptions about which freedoms matter how much, we still encourage readers to tinker with customizing the index. For one thing, very radical changes may well have radical effects. If you are interested in marijuana laws and business regulations but not at all in taxation, gun laws, or tobacco laws, your freedom index might look quite different after all. Our freedom index is tailored to the “average American” adversely affected by government intervention, but the “average American” is a statistical construct that probably corresponds to no actual person.

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In Freedom in the 50 States, we present some statistical results on the association between the three dimensions of freedom — fiscal, regulatory, and personal — and “net interstate migration,” that is, the number of movers into a state from other states minus the number of movers from a state to other states, divided by initial population. We found that all three dimensions are positively associated with net in-migration, usually statistically significantly so. Moreover, the substantive importance of the associations is large. A half-point increase in each of the three dimensions, measured in 2001, is associated with between two and five percentage points more in-migration from 2000 to 2011, as a percentage of 2000 population.

The results seem to imply that Americans value freedom and are willing to vote with their feet for it. Of course, some freedoms are not very plausibly related to migration. Tobacco, alcohol, and gambling laws can be evaded through travel or the black market. It seems unlikely that very many people at all will move from New York simply because of the high cigarette taxes. There are cheaper alternatives. And some freedoms with high symbolic importance, like eminent domain reform or legalization of sodomy (prior to 2003), are unlikely to drive anyone to move, simply because so few people are likely to suffer from their denial. Sodomy laws were almost never enforced, and eminent domain for private gain is rather rare even where totally unregulated.

But some other freedoms are plausibly related to migration. People definitely consider tax burden in their choice of a new home. Business regulation can dampen job opportunities, and people tend to move where the jobs are. Medical cannabis users move where their medicine is legal; gun enthusiasts move where their lifestyle is respected; same-sex couples move where they have legal rights; home-schooling parents move where they can educate with less state control.

In this blog post, I explore some other ways of testing whether the relationship between freedom and migration is causal. The first technique is something I call “matched-neighbors analysis.” The independent variables here, including freedom, represent the value of the variable for the given state minus the average value for its neighbors (technically, the weighted-average value, where the weights are the neighboring states’ populations — I’ve also tried using a pure average, with nearly identical results). This procedure is called “spatial differencing.” So the notion here is that states that are freer than their neighbors will be more likely to see net in-migration. Let’s see if that’s true.

First, some specs: regressions include all 50 states (unlike the results with just the Lower 48 included in the F50S study), all independent variables are standardized to mean zero and standard deviation one (so that the coefficient estimates represent the effect of a standard-deviation change in each variable), and the dependent variable, net migration, is measured over 2000-2012 instead of just 2000-2011 as in the original study. Here are the results: (more…)

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Cross-posted to freedominthe50states.org

The recent release of the 2013 edition of Freedom in the 50 States has sparked a great deal of interest and comment among academics, students, the media, and the general public. Since the goal of our study is really to spark a conversation about freedom and state policies, William and I have been happy to see all the feedback. From the hundreds of positive comments we’ve received over the past week, it’s clear the study sparked a conversation in which many are eager to participate. In this blog post I will address some of the feedback and questions about the study we’ve received.

First, it’s important to understand how our study conceptualizes freedom. We ground our conception of freedom on an individual rights framework. In our view, individuals should be allowed to dispose of their lives, liberties, and property as they see fit, so long as they do not infringe on the rights of others. The study is an index of how state and local public policies conform to this framework.

As is the case with any index, the “freedom index” has some limitations—-it cannot capture all aspects of freedom, such as freedom from depredations originating outside government. Nor is freedom all there is to quality of life. We thus encourage readers to use our scores in conjunction with other indicators when assessing government effectiveness, “quality of life,” or other, similar concepts. Visitors to our Web site can also personalize the rankings by choosing which aspects of freedom they value and see how the states compare against one another.

To ensure the transparency of the freedom index, which has been a critical goal for us from the start of this project, we try to answer as many readers’ questions as possible on our website. The most common questions that we have received have centered on why certain policies were included or not included in the index. Here, we address the policies readers have asked about the most. (more…)

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Pileus blogger Jason Sorens recently released his co-authored study “Freedom in the 50 States.” This is now the second edition of the report, and it has deservedly generated a lot of attention. Even Paul Krugman has added his two cents.

At Salon.com, Andrew Leonard criticizes the report under the sarcastic headline, “Why do liberals hate freedom so much?” Because the Mercatus Center, which sponsored the research that led to the report, has received funding from the Koch Foundation, by a long chain of guilt-by-association reasoning, Leonard implies that the intent of the report is not really to gather and present data that provide an objective, quantifiable measure of both economic and personal freedom in each state, but is rather simply to bash liberals. A rather egocentric view of the world, that.

Of course, even if Leonard’s insinuations were true, that the study were part of Charles and David Koch’s nefarious plot to, well, extend economic and personal freedom, that fact would have no bearing on whether its findings were true. Attacking an author, or an author’s (alleged) motives, does not defeat the author’s argument. Philosophy 101: the ad hominem fallacy is . . . a fallacy.

But Leonard raises two other objections. The first:

[According to the report,] Most Americans are not free. A telling example: In the Mercatus rankings the two states blessed by the highest freedom quotient boast a combined population of a little over 2 million—South Dakota and New Hampshire (the latter of which, admittedly, went for Obama in 2008). The bottom three states were New York, New Jersey and California, which have a combined population of over 65 million.

Sixty-five million Americans in just three states cower under a totalitarian shadow! That’s a little distressing!

(Why “admittedly”? Is Leonard aiming to provide analysis, or advocacy? But that is by the by.)

As analysis, this is quite weak. Sorens and his co-author William Ruger claim that there are real differences between the least “free” and most “free” states in their report, but they do not claim that even residents of the, by their measure, “least free” state, New York, face anything like what people in, say, North Korea face. Although there are real relative differences among the states, no place in America is under a “totalitarian shadow.” To say otherwise is just moral posturing.

More substantively, however, one need not believe that their conception of economic and personal “freedom” is the only or the best one. They provide an explicit definition of their terms; they provide explanations and justifications for the metrics they use; and their data are openly available. If they make an error in their math or their reasoning, that should be simple enough to discover and point out. Leonard does not do that.

Leonard apparently wants to define “freedom” differently. Fair enough. He unfortunately is not as explicit about his own preferred definition as Sorens and Ruger are. Yet Leonard does, perhaps inadvertantly, disclose a clue about what his definition of freedom would be. He writes:

But from my perspective, not having access to universal healthcare is an imposition on my freedom. The fact that for most Americans healthcare is tied to one’s employer is a dread shackle limiting the freedom of movement of every worker. How much more liberated would we all be if we could switch jobs or work for ourselves without the fear that at any moment we might be crippled by an exorbitantly expensive health emergency? Similarly, a state requirement that employers offer paid parental leave (another black mark against California) clearly frees me to be a better father to my newborn. I’d really love to see what would happen to internal migration patterns in the United States if all the big blue states had universal single-payer healthcare, while everyone else was left at the mercy of a completely unregulated private market. That civil war would end rather quickly, I suspect. [Leonard’s emphasis]

So his objection is that Sorens and Ruger do not consider the enjoyment of government-provided health care as an element of freedom, along with government-mandated (paid, presumably) parental leave from work. How much freer would Leonard be if he did not have to pay for his own health care? How much freer would he be if he did not have to work to support his family, but could instead simply spend time with his family?

How much freer indeed. The life Leonard wants for himself has its attractions. It is the life of an old-fashioned aristocrat, of a manorly lord. Leonard has the freedom of leisure to be a gentleman, pursuing properly gentlemanly ends—not the ignominious and base life of a man who has to actually work to support himself in the lifestyle he chooses. 

Now, Leonard has the feigned greatness of soul to allow that he would like this life of gentlemanly leisure for “all” of us. But that is dishonesty. He knows as well as anyone that we cannot all be leisured gentlemen. Someone will actually have to labor to provide the goods and services off which the gentlemen will live. Who are those people making his life free? Who are the people providing him his health care, paying his bills while he takes time off to romp with the kids, bearing the costs generated by his insousciant skipping from one activity to the next as he follows his bliss?

And now we see the real import of the “freedom” Leonard wants. It is the freedom of the pharaoh: the serfs, whom I never deign to see and whom I never condescend to consider, will labor to provide me the comforts and enjoyments and leisure I require. I am not held responsible for them—that would be beneath me.

I believe that is not only a loathsome attitude, but it is a morally reprehensible position. Mr. Leonard, you have no right to live off the fruits of others’ labor. Yes, it would increase your freedom if you could command others to work for you, but yours is a moral code that entitles one group of people to live at the expense of unwilling others, that requires one group of people to be held responsible for the leisurely lifestyle of another, that treats one group as superior to others and fails to respect the inherent dignity of the members of the other group as independent moral agents and indeed as fully human.

Realizing that we are not entitled to others’ labor, and that we are ourselves responsible for the choices—and the consequences of the choices—that we make is bracing and can be, depending on where our moral heads were to begin with, startling. But it is the only way to respect human dignity, both in ourselves and in others. And it implies the only freedom worth the name.

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