Interesting Discussions on U.S. Health Care

Earlier this year I read Overtreated by Shannon Brownlee and Healthy Competition by Michael Tanner and Michael Cannon. I was therefore, pleasantly surprised to come across and listen to two online discussions on U.S. health care that touched on some of same issues. First, Inside-Out Documentaries did an interesting piece on the shortage of primary care physicians called "The Doctor Can't See You Now." Second, Arnold Kling discusses his book, The Crisis of Abundance, in this podcast and includes interesting responses from Jason Furman and Sebastian Mallaby. Both are well worth your time.

Update: Here is Arnold Kling discussing his health care research with Russ Roberts on EconTalk. Also on EconTalk discussing health care policy is Henry Aaron of the Brookings Institution.

Nominal Income Targeting or (More Economic) Bust!

Awhile back I made the case that the Fed could improve macroeconomic stability by adopting a nominal income targeting rule. Such a rule would (1) force the Fed to be more vigilant in stabilizing nominal spending while (2) allowing it to avoid the distraction of rigidly following inflation. Nominal spending shocks, after all, are the real source of macroeconomic volatility while inflation is merely a symptom of these shocks. Moreover, inflation can sometimes can be hard to interpret--Is the high(low) inflation due to positive(negative) aggregate demand shocks or negative(positive) aggregate supply shocks?--and as a result monetary policy that targets inflation may make the wrong call. For example, I noted the following scenario earlier:

Imagine the U.S. economy is buffeted with a series of positive productivity shocks that increases aggregate supply. This development would put downward pressure on the price level and set off the deflation red alert sign at the Federal Reserve. Now, in order to keep the price level from falling, the Federal Reserve must act to increase nominal spending. If this change in monetary policy were unexpected, or if there were significant nominal rigidities (i.e upward sloping Short-run aggregate supply curve), the nominal spending increase that stabilizes the price level would also push actual output beyond its natural rate level. Hence, there would be both a sustainable component—the productivity gains—and a non-sustainable component—the monetary stimulus—to the subsequent increase in real output. Moreover, the unsustainable pickup in actual output would occur without any alarming increases in the price level ... The increase in nominal spending could thus create a boom-bust cycle in real economic activity without any of the standard inflationary signs of overheating.

As I have argued elsewhere, I believe the above scenario is a good description of what happened in the U.S. from 2003-2005. But I digress; the key point is that monetary policy should aim to stabilize the cause of macroeconomic instability rather than a symptom of it.

Now some observers will reply that the Fed is not just focused on an inflation target, but also looks at the the output gap as is mandated by law. So in some sense, it may already be close to following a nominal income targeting rule. While there is some truth to this claim, there still appears to be an implicit inflation target for the Fed that implies when push comes to shove inflation worries will trump any concerns over full employment. The recent inflation hawk talk by Fed Chairman Ben Bernanke is a case in point; other examples include the deflation scares of 1998 and 2003.

Other observers will argue that even if one concedes the advantages of nominal income targeting there still is the difficulty of implementing it: how does one measure nominal income in real time? My answer is that there are monthly measures of real economic activity--coincident index or industrial production--that can be used in conjunction with a monthly price level measure to estimate current nominal income. At a minimum, there is no reason to believe that nominal income targeting would be any harder to implement than a monetary policy following a Taylor rule, which requires ones knows the hard-to-measure in real time output gap.

The importance of stabilizing nominal spending can be seen in the graph below that plots the relationship between the output gap and nominal spending shocks. The output gap is calculated as the percent difference between actual real GDP and the U.S. Congressional Budget Office’s potential real GDP. The nominal spending shocks series is calculated as the deviation of the year-on-year growth rate of quarterly final sales to domestic purchasers from its preceding 10-year moving average. The data cover the period 1953:Q1 - 2008:Q1.

The scatterplot makes it clear there is a strong, positive relationship between nominal spending shocks and the output gap. As a comparison, I have constructed in the same way an inflation shock series from the PCE price index and plotted it below against the output gap.

These figures indicate nominal spending shocks are more closely related to the output gap than inflation shocks. Given these results, I went ahead and plugged the nominal spending shock and output gap series into a vector autoregression (VAR) to get a sense of their dynamic relationship. Five lags were used in the VAR, which is enough to remove serial correlation from the quarterly data (data already in growth rates so no unit roots). After estimating the model and imposing recursive ordering to identify the structural shocks, I got the following impulse response function (IRF) for the output gap given a 1 standard deviation shock to nominal spending:

In plain English, the above figure shows that the typical shock to nominal spending leads to about a 0.5% increase in the output gap--a positive output gap--that persist for about a year and then begins unwinding. Another interesting exercise is to look at the decomposition of the forecast error from the VAR. This exercise explains how much of the forecast error can be attributed to a certain shock. (It tells us whether the interesting results from the IRF really matter)

Here we see that nominal spending shocks account for about 50% of output gap forecast error, a significant amount. By comparison, if the VAR is reestimated with the above inflation shock series instead of the nominal spending shock series, only about 8% of the forecast error can be explained by the inflation shock. Nominal spending shocks matter greatly!

Now I do want to oversell the findings presented here since they are based on a two variable VAR, but they are highly suggestive that nominal spending shocks are more important to macroeconomic stability than inflation shocks. Hence, monetary authorities should pay more attention to nominal spending. Moreover, stabilizing nominal spending should do better than inflation targeting at preventing the buildup of financial imbalances and asset bubbles for reasons explained here. In short, I am big believer that there would be meaningful gains in macroeconomic stability should the Fed should adopt a nominal income targeting rule.

Add This Book to Your Summer Reading List

This is a book that has policy implications for central banks today. From the publisher:

In Good Money, George Selgin tells the story of a fascinating and important yet almost unknown episode in the history of money—British manufacturers’ challenge to the Crown’s monopoly on coinage.

In the 1780s, when the Industrial Revolution was gathering momentum, the Royal Mint failed to produce enough small-denomination coinage for factory owners to pay their workers. As the currency shortage threatened to derail industrial progress, manufacturers began to mint custom-made coins, called “tradesman’s tokens.” Rapidly gaining wide acceptance, these tokens served as the nation’s most popular currency for wages and retail sales until 1821, when the Crown outlawed all moneys except its own.

Good Money not only examines the crucial role of private coinage in fueling Great Britain’s Industrial Revolution, but it also challenges beliefs upon which all modern government-currency monopolies rest. It thereby sheds light on contemporary private-sector alternatives to government-issued money, such as digital monies, cash cards, electronic funds transfer, and (outside of the United States) spontaneous “dollarization.”

Read more about the book here.

Where People Are Moving

I came across this interesting report by Mark J. Perry of the U.S. Census Bureau on domestic net migration in the United States for the years 2000-2004. There were no surprises in the report, but rather a continuation of migration patterns from earlier years. From the summary:

Domestic migration continues to redistribute the country’s population. The longstanding pattern of net outmigration from the Northeast and the Midwest and net inmigrationto the South and the West continued between 2000 and 2004 with modest change from the regional patterns in the 1990s.

So my move from Michigan to Texas last summer was not exceptional, just part of a long-term trend. Still, it interesting to put my personal experience into the context of larger migration patterns in the United States.

Below are some of the interesting images from the report (click on images to enlarge):

Net Domestic Migration for 1990-2000 & 2000-2004

The Great Moderation vs. Rising Household Income Volatility

Just last week I revisited the question of how to reconcile the findings from the "Great Moderation" literature that shows a significant decline in aggregate economic volatility since the early-to-mid 1980s with the findings of Jacob Hacker and others that show there has been a marked increase in household income volatility over this same period. One would think some of the decreased macroeconomic volatility would be experienced and observed at the household level. The data, however, says otherwise. How is this possible? A new paper on the "Great Moderation" by Steven Davis and James Kahn attempts, among other things, to answer this question.

From their paper, Interpreting the Great Moderation: Changes in the Volatility of Economic Activity at the Macro and Micro Levels, we get the following discussion of this issue:

[A] puzzle that research on the Great Moderation has yet to confront: Why has the dramatic decline in the volatility of aggregate real activity, and the roughly coincident decline in firm-level volatility and job-loss rates, not translated into sizable reductions in earnings uncertainty and consumption volatility facing individuals and households?

We do not know the answer to this question, but we conjecture that greater flexibility in pay setting for workers played a role, possibly a major one. Greater pay flexibility is consistent with the rise in wage and earnings inequality in U.S. labor markets since 1980 and with increases in individual income volatility and earnings uncertainty. If these developments involve a rise in the variance of idiosyncratic permanent income shocks to households, then household consumption volatility also rises according to permanent income theory. Greater wage (and hours) flexibility also leads to smaller firm-level employment responses to idiosyncratic shocks and smaller aggregate responses to common shocks, because firms can respond by adjusting compensation rather than relying entirely on layoffs and hires. By the same logic, wage adjustments can substitute for unwanted job loss. So, at least in principle, greater wage flexibility offers a unified explanation for the rise in wage and earnings inequality, flat or rising volatility in household consumption, a decline in job-loss rates, and declines in firm-level and aggregate volatility measures.

In short, their argument is that greater wage volatility has been traded for reduced output and employment volatility. If true, this interpretation has two implications: (1) labor markets are working better since the price of labor is now more flexible; (2) more economic risk has been shifted to labor.

Read the rest of the article.

Update I: See further discussion of this posting here.

More on the Health Benefits of Recessions

I previously posted on Christopher Ruhm's research that shows recessions can improve one's health. Ruhm recently did an interview with the Richmond Federal Reserve Bank where he discussed his work in this area. Below are some excerpts:

RF: One of your articles is provocatively titled, "Are Recessions Good for Your Health?" Discuss the relationships you've discovered between economic growth and health.

Ruhm: Many years ago I did quite a lot of work examining the consequences of job turnover and labor displacement. One of the things you would read a lot about at the time was that when the economy stagnates, lots of bad things would happen. Wages don't go up and housing values fall. Then you'd also see other things reported such as how more marriages break up, crime increases, and health deteriorates. That seemed plausible, so I read a bunch of studies that had been done and realized they weren't using state-of-the-art methods. They were written by epidemiologists and social psychologists but did seem to include plausible mechanisms: When the economy goes bad, for instance, people get stressed out and stress is bad for your health. In addition, stress leads to people drinking more and smoking more and they engage in all this risky behavior as a consequence. I doubted the specific estimates, but not the overall direction of the effect. I wanted to come up with a better way to confirm the results and ended up finding something different.

In these early studies by others, there was a tendency to look at long time-series of aggregate data. They'd look at the United States or Britain from the 1930s to the 1970s and look to see, when the economy gets better, whether the health measures — hospital admissions or mortality rates — were improving or deteriorating. The studies tended to find that when the economy improved, health seemed to get better. But lots of things were going on at once during that period. For example, at roughly the same time the Great Depression ended, there were improvements in nutrition and in the availability of antibiotics.

So I looked at each state in the United States as a laboratory. I studied changes within states relative to what was going on in other states. The advantage to this method is that if there was a change in, say, medical technology, it is likely to affect workers in all states. But the Virginia economy might be improving at the same time the Texas economy is worsening. You can use the fact that there was independent variation in macroeconomic conditions across states to estimate the effects on health.

My first analysis of mortality rates was not at all what I expected. When times were good, mortality rates were increasing and when times were bad they were decreasing. When I first got the results, I didn't particularly believe them. I expanded the analysis in a variety of ways to see if the results would change, but they didn't.

What ultimately convinced me of the result is [that] I made a picture that overlaid the national mortality rates and unemployment rates — after de-trending them and normalizing them so the scales matched — and when I did all that, I found they were almost a mirror image. It was at that point I really believed my results.

[...]

The reasons for mortality increasing when the economy strengthens vary by cause of death. If you look at motor vehicle fatalities, they go up pretty dramatically when the economy improves. That's not so surprising. People drive more when times are good. But it's also true that deaths from heart disease or flu and pneumonia go up when the economy improves and down when the economy deteriorates. Across a wide variety of health measures I was finding the same result.

There were a couple of exceptions. Cancer was unrelated to economic trends. Since we were looking at relatively short-term changes, it's no surprise that we would see this result. Whereas, for something like heart attacks, we do notice that short-term macroeconomic changes can have a big effect.

Another exception was suicides. They went down when the economy improved, and up when it deteriorated. That's consistent with a long line of work on suicides. That also suggests to me, since suicide has a mental health component, it might be the case that economic patterns I had identified mainly refer to physical health measures. That led me to conclude that when the economy tanks, people are healthier but they may not necessarily be happier.

RF: What sorts of mechanisms do you think drive the health trends you studied?

Ruhm: In my research, I also look at behaviors, like drinking, smoking, and exercise. All of these trends exhibit a consistent pattern. When the economy weakens, people smoke less, they are less likely to drink heavily, and they tend to exercise more.

If you look at drinking, you notice that heavy drinkers become light drinkers when the economy deteriorates. Yet light drinkers don't abstain from drinking. For smoking, you see the same result. People also shift from being sedentary to being somewhat active, but not very active. We also don't see a big change in the number of people who are overweight, but we do see a reduction in severe obesity.

Monetary Policy and Asset Bubbles

Gerald P. O'Driscoll Jr. has a new paper titled Asset Bubbles and Their Consequences. The paper discusses how many of the recent asset boom-bust cycles had their origins in an overly accommodative monetary policy. From the summary:

[M]onetary policy has become a source of moral hazard. In acting to counter the economic effects of declining asset prices, the Federal Reserve has come to be viewed as underwriting risky investments. Policy pronouncements by senior Fed officials have reinforced that perception. These actions and pronouncements are mutually reinforcing and destructive to the operation of financial markets. The current financial crisis began in the subprime housing market and then spread throughout credit markets. The new Fed policy fueled the housing boom. Refusing to accept responsibility for the housing bubble, the Fed’s recent actions will likely fuel a new asset bubble.

O'Driscoll makes a point in the paper to which I am partial:

In a vibrant market economy with technological innovation and ever new profit opportunities, the monetary policy that maintains price stability in consumer goods (or zero price inflation) requires substantial monetary stimulus. That stimulus will have a number of real consequences, including asset bubbles. These asset bubbles have real costs and involve misallocations of capital. For example, by the peak of the tech and telecom boom in March 2000, too much capital had been invested in high-tech companies and too little in “old economy firms.” Too much fiber optic cable and too few miles of railroad track were laid.

By 2002, the Fed was worried about the possibility of price deflation. The experiences of Japan in the 1990s and the Great Depression were clearly weighing on the minds of policymakers. A tilt to stimulus was understandable at the time. A continued bias against deflation will, however, produce a continued bias upward in price inflation. With the bursting of each asset bubble and the fear of deflationary pressure, Fed policy must ease. The inflation rate begins at the positive number. The Greenspan doctrine prescribes a simulative overkill that begins the cycle anew.

This story makes sense to me. As I have argued elsewhere, the Fed's deflation concerns were off the mark by 2003. Deflationary pressures by that time were the result of rapid productivity growth, not weak aggregate demand. The Fed's easing then, pushed the real interest rate below the natural interest rate and set off a Wicksellian disequilibrium. The housing boom was one manifestation of this development.

Read the rest of the O'Driscoll paper.