Event Information

A decade into the 21st century, the role of manufacturing in global and metropolitan economies continues to evolve. After 20 years of rapid globalization in which manufacturing production shifted to emerging markets, demand for consumption is growing there, too. Emerging market demand, in fact, has unprecedented momentum as 1.8 billion people enter the global consuming class. At the same time, a robust pipeline of product innovation and manufacturing processes has opened new ways for U.S. manufacturing companies to compete.

On November 19, the Metropolitan Policy Program at Brookings hosted a forum to release a report from the McKinsey Global Institute that examines the role of manufacturing in advanced and developing economies and the choices that manufacturers grapple with in this new era of global competition. Following presentations by the authors, an expert panel discussed the key trends shaping manufacturing competitiveness, global strategies, the next era of manufacturing innovation, and what these changes imply for growth and employment in manufacturing across the globe.

Video

• Bruce Katz: A Region Has to Know What It Can Do Well
• Martin Baily: Manufacturing Creates Jobs
• Katy George: Manufacturing Is an Entity That Is Constantly Shifting
• James Manyika: Manufacturing Matters a Great Deal
• Gardner Carrick: Education Is Key
• James W. Griffith: Closing Remarks

Audio

• Global Manufacturing: Entering a New Era

Transcript

• Uncorrected Transcript (.pdf)

Event Materials

• 20121119_global_manufacturing

       

Nearly 30 years ago, the economists Robert Solow and Stephen Roach caused a stir when they pointed out that, for all the billions of dollars being invested in information technology, there was no evidence of a payoff in productivity. Businesses were buying tens of millions of computers every year, and Microsoft had just gone public, netting Bill Gates his first billion. And yet, in what came to be known as the productivity paradox, national statistics showed that not only was productivity growth not accelerating; it was actually slowing down. “You can see the computer age everywhere,” quipped Solow, “but in the productivity statistics.”

Today, we seem to be at a similar historical moment with a new innovation: the much-hyped Internet of Things – the linking of machines and objects to digital networks. Sensors, tags, and other connected gadgets mean that the physical world can now be digitized, monitored, measured, and optimized. As with computers before, the possibilities seem endless, the predictions have been extravagant – and the data have yet to show a surge in productivity.

A year ago, research firm Gartner put the Internet of Things at the peak of its Hype Cycle of emerging technologies.

As more doubts about the Internet of Things productivity revolution are voiced, it is useful to recall what happened when Solow and Roach identified the original computer productivity paradox. For starters, it is important to note that business leaders largely ignored the productivity paradox, insisting that they were seeing improvements in the quality and speed of operations and decision-making. Investment in information and communications technology continued to grow, even in the absence of macroeconomic proof of its returns.

That turned out to be the right response. By the late 1990s, the economists Erik Brynjolfsson and Lorin Hitt had disproved the productivity paradox, uncovering problems in the way service-sector productivity was measured and, more important, noting that there was generally a long lag between technology investments and productivity gains.

Our own research at the time found a large jump in productivity in the late 1990s, driven largely by efficiencies made possible by earlier investments in information technology. These gains were visible in several sectors, including retail, wholesale trade, financial services, and the computer industry itself. The greatest productivity improvements were not the result of information technology on its own, but by its combination with process changes and organizational and managerial innovations.

Our latest research, The Internet of Things: Mapping the Value Beyond the Hype, indicates that a similar cycle could repeat itself. We predict that as the Internet of Things transforms factories, homes, and cities, it will yield greater economic value than even the hype suggests. By 2025, according to our estimates, the economic impact will reach $3.9-$11.1 trillion per year, equivalent to roughly 11% of world GDP. In the meantime, however, we are likely to see another productivity paradox; the gains from changes in the way businesses operate will take time to be detected at the macroeconomic level.

One major factor likely to delay the productivity payoff will be the need to achieve interoperability. Sensors on cars can deliver immediate gains by monitoring the engine, cutting maintenance costs, and extending the life of the vehicle. But even greater gains can be made by connecting the sensors to traffic monitoring systems, thereby cutting travel time for thousands of motorists, saving energy, and reducing pollution. However, this will first require auto manufacturers, transit operators, and engineers to collaborate on traffic-management technologies and protocols.

Indeed, we estimate that 40% of the potential economic value of the Internet of Things will depend on interoperability. Yet some of the basic building blocks for interoperability are still missing. Two-thirds of the things that could be connected do not use standard Internet Protocol networks.

Other barriers standing in the way of capturing the full potential of the Internet of Things include the need for privacy and security protections and long investment cycles in areas such as infrastructure, where it could take many years to retrofit legacy assets. The cybersecurity challenges are particularly vexing, as the Internet of Things increases the opportunities for attack and amplifies the consequences of any breach.

But, as in the 1980s, the biggest hurdles for achieving the full potential of the new technology will be organizational. Some of the productivity gains from the Internet of Things will result from the use of data to guide changes in processes and develop new business models. Today, little of the data being collected by the Internet of Things is being used, and it is being applied only in basic ways – detecting anomalies in the performance of machines, for example.

It could be a while before such data are routinely used to optimize processes, make predictions, or inform decision-making – the uses that lead to efficiencies and innovations. But it will happen. And, just as with the adoption of information technology, the first companies to master the Internet of Things are likely to lock in significant advantages, putting them far ahead of competitors by the time the significance of the change is obvious to everyone.

Editor's Note: This opinion originally appeared on Project Syndicate August 6, 2015.

       

Employers continued to boost payrolls in 2015, capping six straight years of job gains. It was the third year in a row in which employment gains topped 210,000 a month. In the 12 months ending in November, public and private payrolls increased 220,000 a month, or about 1.9 percent over the year. Virtually all the growth in payrolls was in the private sector, which added 212,000 jobs a month. The public sector added modestly to its payrolls last year, but the number of government employees remains more than one million (4.4 percent) below the peak level attained in 2010. 

Nearly all major industries except mining contributed to job gains in the past 12 months, though gains in manufacturing were weaker than in any year since the expansion began in 2010.  Payrolls in the mining industry tumbled more than 10 percent, hurt by a steep fall in oil and gas prices and the decline in exploration for new energy reserves. The construction industry continued to add to payrolls last year at about the same pace as in the previous two years, although the level of employment is still about 1.2 million (15 percent) below the peak level achieved in 2006.

Based on the age composition of the U.S. population, between 65,000-80,000 new jobs are needed every month to keep the unemployment rate from rising. Since late 2010, monthly payroll gains have comfortably exceeded this threshold. As a result, the jobless rate has declined steadily. In the 12 months through November 2015, the unemployment rate dropped another 0.8 percentage point, falling to 5.0 percent. The jobless rate is now within a half percentage point of its level immediately before the Great Recession. Since reaching a peak in the autumn of 2009, the unemployment rate has been cut in half.

We’ve also seen improvement in other indicators of job market distress in the past year. The number of Americans who want full-time jobs but have been forced to take part-time positions fell more than 11 percent in the 12 months through November 2015. About 9 million workers who wanted a full-time job were employed part-time in the middle of 2010. That number has fallen to about 6 million in recent months.  Similarly, the number of Americans in long spells of unemployment continues to shrink. Workers reporting they were unemployed 6 months or longer fell to 2.05 million in November, representing a considerable improvement since 2010. In that year, more than 6 million jobless workers reported they had been looking for work for at least a half a year.

The most welcome news for Americans who hold jobs is that inflation-adjusted wage levels improved last year.  Real average hourly earnings increased 1.8 percent between November 2014 and November 2015, and real weekly earnings climbed 1.6 percent.  These gains represent a considerable improvement compared with earlier years in the recovery, when real wage gains were negligible.  Nonetheless, nominal wage gains in 2015 were only slightly faster than they were in earlier years of the recovery. The reason for the startling turnaround in real wage growth is that consumer prices increased very little over the past year.  In the 12 months ending in November, the CPI edged up just 0.5 percent, almost a full percentage point more slowly than the average rate of consumer inflation in the previous three years.  The slowdown was driven by lower prices for energy and other key commodities.  (The “core” consumer inflation rate, which strips out the effects of price changes in energy and food, was 2.0 percent last year, a bit higher than the rate in the previous year.) 

Back when politicians and voters cared more about inflation than they currently do, Brookings economist Arthur Okun proposed an economic indicator called the “misery index” to summarize the dual hardships of inflation and unemployment. To measure economic misery Okun suggested adding the current unemployment rate and a measure of consumer price inflation.  In Chart 1 below I have added the civilian unemployment rate and the trailing 12-month percentage change in the CPI.  In the 11 months of 2012 through November, the misery index averaged just 5.4, its lowest level since the 1950s and well below its average levels in the 1990s (8.8) and in the period from 2000 to 2007 (7.8). When inflation is benign and has remained subdued for a long time, Americans may forget the pain they feel when price increases are frequent and large. Okun’s misery index fell to an exceptionally low level in 2015, even if a small majority of Americans continues to believe the economy is getting worse.

The good news in 2015 is that unemployment continued to fall and real wages began to rise.  The less welcome news is that key measures of labor force participation failed to improve.  For example, the labor force participation rate of Americans between 25 and 54 was the same in November 2015 as it was in November 2014. More worryingly, it was 2.1 percentage points below its level in November 2007, just before the Great Recession.  So far we have seen no rebound in participation among people in prime working ages, despite abundant signs that it’s easier to land a job. 

Low participation is the main explanation for depressed employment rates among prime-age Americans.  Participation rates are not only low in comparison to levels seen before the Great Recession, they are also now below those in other rich countries.  Charts 2 and 3 compare employment-to-population rates among 25-54 year-olds in seven OECD member countries (Canada, France, Germany, Japan, Sweden, the United Kingdom, and the United States).  The charts show employment rates separately for men and women in two different years, 2000 and 2014.  The countries are ranked, from left to right, by their employment rates in 2014. In 2000 the U.S. had the second highest male employment rate (Chart 2) and the second highest female employment rate (Chart 3) of the seven countries listed.  By 2014, the U.S. had the lowest male and female employment rates among the countries compared.  Although several nations saw declines in their prime-age male employment rate, only the U.S. also experienced a decline in its prime-age female employment rate.  The other six countries all saw increases in female employment.

The main reason for the drop in prime-age U.S. employment was the decline in prime-age participation. An enduring puzzle of the current recovery is the failure of participation rates to rebound, even in the face of steady improvement in the job market.

      

Editor’s note: The following remarks were prepared and delivered by Gary Burtless at a roundtable sponsored by the American Tax Policy Institute on January 7, 2016. Video of Burtless’ remarks are also available on the Institute’s website. Download the related slides at the right. 

We are here to discuss income inequality, alternative ways to evaluate its size and trend over time, and how it might be affected by tax policy.  My job is to introduce you to the problem of defining income and to show how the definition affects our understanding of inequality.

To eliminate suspense from the start: Nothing I am about to say undermines the popular narrative about recent inequality trends.  For the past 35 years, U.S. inequality has increased.  Inequality has increased noticeably, no matter what income definition you care to use.  A couple of things you read in the newspaper are untrue under some income definitions. For example, under a comprehensive income definition it is false to claim that all the income gains of the past 2 or 3 decades have gone to the top 1 percent, or the top 5 percent, or the top 10 percent of income recipients.  Middle- and low-income Americans have managed to achieve income gains, too, as we shall see.

Tax policy certainly affects overall inequality, but I shall leave it for Scott, David, and Tracy to take that up. Let me turn to my main job, which is to distinguish between different reasonable income measures.

The crucial thing to know is that contradictory statements can be made about some income trends because of differences in the definition of income.  In general, the most pessimistic statements about trends rely on an income definition that is restrictive in some way.  The definition may exclude important income items, items, for example, that tend to equalize or boost family incomes.  The definition may leave out adjustments to income … adjustments that tend to boost the rate of income gain for low- or middle-income recipients, but not for top-income recipients.

The narrowest income definition commonly used to evaluate income trends is Definition #1 in my slide, “pretax private, cash income.”  Columnists and news reporters are unknowingly using this income definition when they make pronouncements about the income share of the “top 1 percent.”  The data about income under this definition are almost always based on IRS income tax returns, supplemented with a bit of information from the Commerce Department’s National Income and Product Account (NIPA) data file.

The single most common income definition used to assess income trends and inequality is the Census Bureau’s “money income” definition, Definition #2 on the slide.  It is just the same as the first definition I mentioned, except this income concept also includes government cash transfer payments – Social Security, unemployment insurance, cash public assistance, Veterans’ benefits, etc.

A slightly more expansive definition (#3) also adds food stamp (or SNAP) benefits plus other government benefits that are straightforward to evaluate. Items of this kind include the implicit rent subsidy low-income families receive in publicly-subsidized housing, school lunch subsides, and means-tested home heating subsidies.

Now we come to subtractions from income. These typically reflect families’ tax obligations.  The Census Bureau makes estimates of state and federal income tax liabilities as well as payroll taxes owed by workers (though not by their employers).  Since income and payroll taxes subtract from the income available to pay for other stuff families want to buy, it seems logical to also subtract them from countable income. This is done under income Definition #4.  Some tax obligations – notably the Earned Income Credit (EIC) – are in fact subtractions from taxes owed, which would not be a problem in the case of families that still owe positive taxes to the government.  However, the EIC is refundable to taxpayers, meaning that some families have negative tax liabilities:  The government owes them money.  In this case, if you do not take taxes into account you understate low-income families’ incomes, even as you’re overstating the net incomes available to middle- and high-income families.

Now let’s get a bit more complicated.  Forget what I said about taxes, because our next income definition (#5) also ignores them.  It is an even-more-comprehensive definition of gross or pretax income.  In addition to all those cash and near-cash items I mentioned in Definition #3, Definition #5 includes imputed income items, such as: 

• The value of your employer’s premium contribution to your employee health plan;
• The value of the government’s subsidy to your public health plan – Medicare, Medicaid, state CHIP plans, etc.
• Realized taxable gains from the sale of assets; and
• Corporate income that is earned by companies in which you own a share even though it is not income that is paid directly to you.

This is the most comprehensive income definition of which I am aware that refers to gross or pre-tax income.

Finally we have Definition #6, which subtracts your direct and indirect tax payments.  The only agency that uses this income definition is principally interested in the Federal budget, so the subtractions are limited to Federal income and payroll taxes, Federal corporate income taxes, and excise taxes.

Before we go into why you should care about any of these definitions, let me mention a somewhat less important issue, namely, how we define the income-sharing group over which we estimate inequality.  The most common assessment unit for income included under Definition #1 (“Pre-tax private cash income”) is the Federal income tax filing unit.  Sometimes this unit has one person; sometimes 2 (a married couple); and sometimes more than 2, including dependents.

The Census Bureau (and, consequently, most users of Census-published statistics) mainly uses “households” as reference units, without any adjustment for variations in the size of different households.  The Bureau’s median income estimate, for example, is estimated using the annual “money income” of households, some of which contain 1 person, some contain 2, some contain 3, and so on.

Many economists and sociologists find this unsatisfactory because they think a $20,000 annual income goes a lot farther if it is supporting just one person rather than 12.  Therefore, a number of organizations—notably, the Luxembourg Income Study (LIS), the Organisation of Economic Cooperation and Development (OECD), and the Congressional Budget Office (CBO)—assume household income is equally shared within each household, but that household “needs” increase with the square root of the number of people in the household.  That is, a household containing 9 members is assumed to require 1½ times as much income to enjoy the same standard of living as a family containing 4 members.  After an adjustment is made to account for the impact of household size, these organizations then calculate inequality among persons rather than among households.

How are these alternative income definitions estimated?  Who uses them?  What do the estimates show?  I’ll only consider a two or three basic cases.

First, pretax, private, cash income. By far the most famous users of this definition are Professors Thomas Piketty and Emmanuel Saez.  Their most celebrated product is an annual estimate of the share of total U.S. income (under this restricted definition) that is received by the top 1 percent of tax filing units.

Here is their most famous chart, showing the income share of the top 1 percent going back to 1913. (I use the Piketty-Saez estimates that exclude realized capital gains in the calculation of taxpayers’ incomes.) The notable feature of the chart is the huge rise in the top income share between 1970—when it was 8 percent of all pretax private cash income—and last year—when the comparable share was 18 percent.  

I have circled one part of the line—between 1986 and 1988—to show you how sensitive their income definition is to changes in the income tax code.  In 1986 Congress passed the Tax Reform Act of 1986 (TRA86). By 1988 the reform was fully implemented.  Wealthy taxpayers noticed that TRA86 sharply reduced the payoff to holding corporate earnings inside a separately taxed corporate entity. Rich business owners or shareholders could increase their after-tax income by arranging things so their business income was taxed only once, at the individual level.  The result was that a lot of income, once earned by and held within corporations, was now passed through to the tax returns of rich individual taxpayers. These taxpayers appeared to enjoy a sudden surge in their taxable incomes between 1986 and 1988.  No one seriously believes rich people failed to get the benefits of this income before 1987.  Before 1987 the same income simply showed up on corporate rather than on individual income tax returns.

A final point:  The chart displayed in SLIDE #6 is the source of the widely believed claim that U.S. inequality is nowadays about the same as it was at the end of the Roaring 1920s, before the Great Depression.  That is close to being true – under this income definition.

Census “money income”: This income definition is very similar to the one just discussed, except that it includes cash government transfer payments.  The producer of the series is the Census Bureau, and its most famous uses are to measure trends in real median household income and the official U.S. poverty rate. Furthermore, the Census Bureau uses the income definition to compile estimates of the Gini coefficient of household income inequality and the income shares received by each one-fifth of households, ranked from lowest to highest income, and received by the top 5 percent of households.

Here is a famous graph based on the Bureau’s “median household income” series.  I have normalized the historical series using the 1999 real median income level (1999 and 2000 were the peak income years according to Census data).  Since 1999 and 2000, median income has fallen about 10 percent.  If we accept this estimate without qualification, it certainly represents bad news for living standards of the nation’s middle class. The conclusion is contradicted by other government income statistics that use a broader, more inclusive income definition, however.

And here is the Bureau’s most widely cited distributional statistic (after its “official poverty rate” estimate).  Since 1979, the Gini coefficient has increased 17 percent under this income definition. (It is worth noting, however, that the portion of the increase that occurred between 1992 and 1993 is mainly the result of methodological changes in the way the Census Bureau ascertained incomes in its 1994 income survey.)

When you hear U.S. inequality compared with that in other rich countries, the numbers are most likely based on calculations of the LIS or OECD.  Their income definition is basically “Cash and Near-cash Public and Private income minus Income and Payroll taxes owed by households.”  Under this income definition, the U.S. looks relatively very unequal and America appears to have an exceptionally high poverty rate.  U.S. inequality has been rising under this income definition, as indeed has also been the case in most other rich countries. The increase in the United States has been above average, however, helping us to retain our leadership position, both in income inequality and in relative poverty.

We turn last to the most expansive income definition:  CBO’s measure of net after-tax income.  I will use CBO’s tabulations using this income definition to shed light on some of the inequality and living standard trends implied by the narrower income definitions discussed above.

Let’s consider some potential limitations of a couple of those definitions.  The limitations do not necessarily make them flawed or uninteresting.  They do mean the narrower income measures cannot tell us some of the things that users claim they tell us.

An obvious shortcoming of the “cash pretax private income” definition is that it excludes virtually everything the government does to equalize Americans’ incomes.  Believe it or not, the Federal tax system is mildly progressive.  It claims a bigger percentage of the (declared) incomes of the rich than it does of middle-income families’ and especially the poor.  Any pretax income measure will miss that redistribution.

More seriously, it excludes all government transfer payments.  You may think the rich get a bigger percentage of their income from government handouts compared with middle class and poorer households.  That is simply wrong.  The rich get a lot less.  And the percentage of total personal income that Americans derive from government transfer payments has gone way up over the years.  In the Roaring 1920s, Americans received almost nothing in the form of government transfers. Less than 1 percent of Americans’ incomes were received as transfer payments.  By 1970—near the low point of inequality according to the Piketty-Saez measure—8.3 percent of Americans’ personal income was derived from government transfers.  Last year, the share was 17 percent. None of the increase in government transfers is reflected in Piketty and Saez’s estimates of the trend in inequality.  Inequality is nowadays lower than it was in the late 1920s, mainly because the government does more redistribution through taxes and transfers.

Both the Piketty-Saez and the Census “money income” statistics are affected by the exclusion of government- and employer-provided health benefits from the income definition. This slide contains numbers, starting in 1960, that show the share of total U.S. personal consumption consisting of personal health care consumption.  I have divided the total into two parts. The first is the share that is paid for out of our own cash incomes (the blue part at the bottom).  This includes our out-of-pocket spending for doctors’ charges, hospital fees, pharmaceutical purchases, and other provider charges as well as our out-of-pocket spending on health insurance premiums. The second is the share of our personal health consumption that is paid out of government subsidies to Medicare, Medicaid, CHIP, etc., or out of employer subsidies to employee health plans (the red part). 

As everyone knows, the share of total consumption that consists of health consumption has gone way up.  What few people recognize is that the share that is directly paid by consumers—through payments to doctors, hospitals, and household health insurance premium payments—has remained unchanged.  All of the increase in the health consumption share since 1960 has been financed through government and employer subsidies to health insurance plans. None of those government or employer contributions is counted as “income” under the Piketty-Saez and Census “money income” definitions.  You would have to be quite a cynic to claim the subsidies have brought households no living standard improvements since 1960, yet that is how they are counted under the Piketty-Saez and Census “money income” definitions.

Final slide: How much has inequality gone up under income definitions that count all income sources and subtract the Federal income, payroll, corporation, and excise taxes we pay?  CBO gives us the numbers, though unfortunately its numbers end in 2011.

Here are CBO’s estimates of real income gains between 1979 and 2011.  These numbers show that real net incomes increased in every income category, from the very bottom to the very top.  They also show that real incomes per person have increased much faster at the top—over on the right—than in the middle or at the bottom—over on the left.  Still, contrary to a common complaint that all the income gains in recent years have been received by folks at the top, the CBO numbers suggest net income gains have been nontrivial among the poor and middle class as well as among top income recipients.

Suppose we look at trends in the more recent past, say, between 2000 and 2011.  That lower panel in this slide presents a very different picture from the one implied by the Census Bureau’s “money income” statistics.  Unlike the “money income numbers” [SLIDE #9], these show that inequality has declined since 2000.  Unlike the “money income numbers” [SLIDE #8], these show that incomes of middle-income families have improved since 2000.  There are a variety of explanations for the marked contrast between the Census Bureau and CBO numbers.  But a big one is the differing income definitions the two conclusions are based on.  The more inclusive measure of income shows faster real income gains among middle-income and poorer households, and it suggests a somewhat different trend in inequality.

      

Unlike prime-age Americans, who have experienced declines in employment and labor force participation since the onset of the Great Recession, Americans past 60 have seen their employment and labor force participation rates increase.

In order to understand the contrasting labor force developments among the old, on the one hand, and the prime-aged, on the other, this paper develops and analyzes a new data file containing information on monthly labor force changes of adults interviewed in the Current Population Survey (CPS).

The paper documents notable differences among age groups with respect to the changes in labor force transition rates that have occurred over the past two decades. What is crucial for understanding the surprising strength of old-age labor force participation and employment are changes in labor force transition probabilities within and across age groups. The paper identifies several shifts that help account for the increase in old-age employment and labor force participation:

• Like workers in all age groups, workers in older groups saw a surge in monthly transitions from employment to unemployment in the Great Recession.
• Unlike workers in prime-age and younger groups, however, older workers also saw a sizeable decline in exits to nonparticipation during and after the recession. While the surge in exits from employment to unemployment tended to reduce the employment rates of all age groups, the drop in employment exits to nonparticipation among the aged tended to hold up labor force participation rates and employment rates among the elderly compared with the nonelderly. Among the elderly, but not the nonelderly, the exit rate from employment into nonparticipation fell more than the exit rate from employment into unemployment increased.
• The Great Recession and slow recovery from that recession made it harder for the unemployed to transition into employment. Exit rates from unemployment into employment fell sharply in all age groups, old and young.
• In contrast to unemployed workers in younger age groups, the unemployed in the oldest age groups also saw a drop in their exits to nonparticipation. Compared with the nonaged, this tended to help maintain the labor force participation rates of the old.
• Flows from out-of-the-labor-force status into employment have declined for most age groups, but they have declined the least or have actually increased modestly among older nonparticipants.

Some of the favorable trends seen in older age groups are likely to be explained, in part, by the substantial improvement in older Americans’ educational attainment. Better educated older people tend to have lower monthly flows from employment into unemployment and nonparticipation, and they have higher monthly flows from nonparticipant status into employment compared with less educated workers.

The policy implications of the paper are:

• A serious recession inflicts severe and immediate harm on workers and potential workers in all age groups, in the form of layoffs and depressed prospects for finding work.
• Unlike younger age groups, however, workers in older groups have high rates of voluntary exit from employment and the workforce, even when labor markets are strong. Consequently, reduced rates of voluntary exit from employment and the labor force can have an outsize impact on their employment and participation rates.
• The aged, as a whole, can therefore experience rising employment and participation rates even as a minority of aged workers suffer severe harm as a result of permanent job loss at an unexpectedly early age and exceptional difficulty finding a new job.
• Between 2001 and 2015, the old-age employment and participation rates rose, apparently signaling that older workers did not suffer severe harm in the Great Recession.
• Analysis of the gross flow data suggests, however, that the apparent improvements were the combined result of continued declines in age-specific voluntary exit rates, mostly from the ranks of the employed, and worsening reemployment rates among the unemployed. The older workers who suffered involuntary layoffs were more numerous than before the Great Recession, and they found it much harder to get reemployed than laid off workers in years before 2008. The turnover data show that it has proved much harder for these workers to recover from the loss of their late-career job loss.

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Financial advisors offer their clients many advantages, such as setting reasonable savings goals, avoiding fraudulent investments and mistakes like buying high and selling low, and determining the right level of risk for a particular household. However, these same advisors are often incentivized to choose funds that increase their own financial rewards, and the nature and amount of the fees received by advisors may not be transparent to their clients, and small-scale savers may not be able to access affordable advice at all.  What is in the best interest of an individual may not be in the best interest of his or her financial advisor.

To combat this problem, the Department of Labor (DoL) recently proposed a regulation designed to increase consumer protection by treating some investment advisors as fiduciaries under ERISA and the 1986 Internal Revenue Code.  The proposed conflict of interest rule is an important step in the right direction to increasing consumer protections.  It addresses evidence from a February 2015 report by the Council of Economic Advisers suggesting that consumers often receive poor recommendations from their financial advisors and that as a result their investment returns on IRAs are about 1 percentage point lower each year.   Naturally, the proposal is not without its controversies and it has already attracted at least 775 public comments, including one from us .

For us, the DoL’s proposed rule is a significant step in the right direction towards increased consumer protection and retirement security.  It is important to make sure that retirement advisors face the right incentives and place customer interests first.  It is also important make sure savers can access good advice so they can make sound decisions and avoid costly mistakes.  However, some thoughtful revisions are needed to ensure the rule offers a net benefit. 

If the rule causes advisors’ compliance costs to rise, they may abandon clients with small-scale savings, since these clients will no longer be profitable for them.  If these small-scale savers are crowded out of the financial advice market, we might see the retirement savings gap widen.  Therefore we encourage the DoL to consider ways to minimize or manage these costs, perhaps by incentivizing advisors to continue guiding these types of clients.  We also worry that the proposed rule does not adequately clarify the difference between education and advice, and encourage the DoL to close any potential loopholes by standardizing the general educational information that advisors can share without triggering fiduciary responsibility (which DoL is trying to do).  Finally, the proposed rule could encourage some advisors to become excessively risk averse in an overzealous attempt to avoid litigation or other negative consequences.  Extreme risk aversion could decrease market returns for investors and the ‘value-add’ of professional advisors, so we suggest the DoL think carefully about discouraging conflicted advice without also discouraging healthy risk.

The proposed rule addresses an important problem, but in its current form it may open the door to some undesirable or problematic outcomes.  We explore these issues in further detail in our recent paper.

      

Americans are enjoying longer lifespans than ever before. Living longer affords individuals the opportunity to make more contributions to the world, to spend more time with their loved ones, and to devote more years to their favorite activities – but a longer life, and particularly a longer retirement, is also expensive. The retirement security landscape is evolving as workers, employers, retirees, and financial services companies find their needs shifting. Once, many workers planned to stay with a single employer for most or all of their careers, building up a sizeable pension and looking forward to a comfortable retirement. Today, workers more and more workers will be employed by many different employers.  Additionally, generous defined benefit (DB) retirement plans are less popular than they once were – though they were never truly commonplace – and defined contribution (DC) plans are becoming ever more prevalent.  

Figure 1, below, shows the change from DB to DC that has occurred over the past three decades.

In the past many retirees struggled financially towards the end of their lives, just as they do now, but even so, the changes to the retirement security landscape have been real and marked, and have had a serious impact on workers and retirees alike. DB plans are dwindling, DC plans are on the rise, and as a result individuals must now take a more active role in managing their retirement savings. DC plans incorporate contributions from employees and employers alike, and workers much choose how to invest their nest egg.  When a worker leaves a job for retirement or for a different job he or she will often roll over the money from a 401(k) plan into an Individual Retirement Account (IRA). While having more control over one’s retirement funds might seem on its face to be a net improvement, the reality is that the average American lacks the financial literacy to make sound decisions (SEC 2012).

The Council of Economic Advisers (CEA) expressed concern earlier this year that savers with IRA accounts may receive poor investment advice, particularly in cases where their financial advisors are compensated through fees and commissions. “[The] best recommendation for the saver may not be the best recommendation for the adviser’s bottom line” (CEA 2015). President Obama echoed these concerns in a speech at AARP in February, asking the Department of Labor (DoL) to update its rules for financial advisors to follow when handling IRA accounts (White House 2015). The DoL receives its authority to craft such rules and requirements from the 1974 Employee Retirement Income Security Act (ERISA) (DoL 2015a).

The DoL recently proposed a regulation designed to increase consumer protection by treating some investment advisors as fiduciaries under ERISA and the 1986 Internal Revenue Code (DoL 2015b). The proposed rule has generated heated debate, and some financial advisors have responded with great concern, arguing that it will be difficult or impossible to comply with the rule without raising costs to consumers and/or abandoning smaller accounts that generate little or no profit. Advisors who have traditionally offered only the proprietary products of a single company worry that the business model they have used for many years will no longer be considered to be serving the best interests of clients.

Rather than offering detailed comments on the DoL proposals, this paper will look more broadly at the problem of saving for retirement and the role for professional advice. This is, of course, a well-travelled road with a large literature by academics, institutions and policy-makers, however, it is worthwhile to think about market failures, lack of information and individual incentives and what they imply for the investment advice market.

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Nearly 30 years ago, the economists Robert Solow and Stephen Roach caused a stir when they pointed out that, for all the billions of dollars being invested in information technology, there was no evidence of a payoff in productivity. Businesses were buying tens of millions of computers every year, and Microsoft had just gone public, netting Bill Gates his first billion. And yet, in what came to be known as the productivity paradox, national statistics showed that not only was productivity growth not accelerating; it was actually slowing down. “You can see the computer age everywhere,” quipped Solow, “but in the productivity statistics.”

Today, we seem to be at a similar historical moment with a new innovation: the much-hyped Internet of Things – the linking of machines and objects to digital networks. Sensors, tags, and other connected gadgets mean that the physical world can now be digitized, monitored, measured, and optimized. As with computers before, the possibilities seem endless, the predictions have been extravagant – and the data have yet to show a surge in productivity.

A year ago, research firm Gartner put the Internet of Things at the peak of its Hype Cycle of emerging technologies.

As more doubts about the Internet of Things productivity revolution are voiced, it is useful to recall what happened when Solow and Roach identified the original computer productivity paradox. For starters, it is important to note that business leaders largely ignored the productivity paradox, insisting that they were seeing improvements in the quality and speed of operations and decision-making. Investment in information and communications technology continued to grow, even in the absence of macroeconomic proof of its returns.

That turned out to be the right response. By the late 1990s, the economists Erik Brynjolfsson and Lorin Hitt had disproved the productivity paradox, uncovering problems in the way service-sector productivity was measured and, more important, noting that there was generally a long lag between technology investments and productivity gains.

Our own research at the time found a large jump in productivity in the late 1990s, driven largely by efficiencies made possible by earlier investments in information technology. These gains were visible in several sectors, including retail, wholesale trade, financial services, and the computer industry itself. The greatest productivity improvements were not the result of information technology on its own, but by its combination with process changes and organizational and managerial innovations.

Our latest research, The Internet of Things: Mapping the Value Beyond the Hype, indicates that a similar cycle could repeat itself. We predict that as the Internet of Things transforms factories, homes, and cities, it will yield greater economic value than even the hype suggests. By 2025, according to our estimates, the economic impact will reach $3.9-$11.1 trillion per year, equivalent to roughly 11% of world GDP. In the meantime, however, we are likely to see another productivity paradox; the gains from changes in the way businesses operate will take time to be detected at the macroeconomic level.

One major factor likely to delay the productivity payoff will be the need to achieve interoperability. Sensors on cars can deliver immediate gains by monitoring the engine, cutting maintenance costs, and extending the life of the vehicle. But even greater gains can be made by connecting the sensors to traffic monitoring systems, thereby cutting travel time for thousands of motorists, saving energy, and reducing pollution. However, this will first require auto manufacturers, transit operators, and engineers to collaborate on traffic-management technologies and protocols.

Indeed, we estimate that 40% of the potential economic value of the Internet of Things will depend on interoperability. Yet some of the basic building blocks for interoperability are still missing. Two-thirds of the things that could be connected do not use standard Internet Protocol networks.

Other barriers standing in the way of capturing the full potential of the Internet of Things include the need for privacy and security protections and long investment cycles in areas such as infrastructure, where it could take many years to retrofit legacy assets. The cybersecurity challenges are particularly vexing, as the Internet of Things increases the opportunities for attack and amplifies the consequences of any breach.

But, as in the 1980s, the biggest hurdles for achieving the full potential of the new technology will be organizational. Some of the productivity gains from the Internet of Things will result from the use of data to guide changes in processes and develop new business models. Today, little of the data being collected by the Internet of Things is being used, and it is being applied only in basic ways – detecting anomalies in the performance of machines, for example.

It could be a while before such data are routinely used to optimize processes, make predictions, or inform decision-making – the uses that lead to efficiencies and innovations. But it will happen. And, just as with the adoption of information technology, the first companies to master the Internet of Things are likely to lock in significant advantages, putting them far ahead of competitors by the time the significance of the change is obvious to everyone.

Editor's Note: This opinion originally appeared on Project Syndicate August 6, 2015.

      

Introduction

I would like to thank the Department for giving me the opportunity to testify on this important issue. The document I submitted to you is more general than most of the comments you have received, talking about the issues facing retirement savers and policymakers, rather than engaging in a point-by-point discussion of the detailed DOL proposal¹.

Issues around Retirement Saving

1. Most workers in the bottom third of the income distribution will rely on Social Security to support them in retirement and will save little. Hence it is vital that we support Social Security in roughly its present form and make sure it remains funded, either by raising revenues or by scaling back benefits for higher income retirees, or both.

2. Those in the middle and upper middle income levels must now rely on 401k and IRA funds to provide income support in retirement. Many and perhaps most households lack a good understanding of the amount they need to save and how to allocate their savings. This is true even of many savers with high levels of education and capabilities.

3. The most important mistakes made are: not saving enough; withdrawing savings prior to retirement; taking Social Security benefits too early² ; not managing tax liabilities effectively; and failing to adequately manage risk in investment choices. This last category includes those who are too risk averse and choose low-return investments as well as those that overestimate their own ability to pick stocks and time market movements. These points are discussed in the paper I submitted to DoL in July. They indicate that retirement savers can benefit substantially from good advice.

4. The market for investment advice is one where there is asymmetric information and such markets are prone to inefficiency. It is very hard to get incentives correctly aligned. Professional standards are often used as a way of dealing with such markets but these are only partially successful. Advisers may be compensated through fees paid by the investment funds they recommend, either a load fee or a wrap fee. This arrangement can create an incentive for advisers to recommend high fee plans.

5. At the same time, advisers who encourage increased saving, help savers select products with good returns and adequate diversification, and follow a strategy of holding assets until retirement provide benefits to their clients.

Implications for the DoL’s proposed conflicted interest rule

1. Disclosure. There should be a standardized and simple disclosure form provided to all households receiving investment advice, detailing the fees they will be paying based on the choices they make. Different investment choices offered to clients should be accompanied by a statement describing how the fees received by the adviser would be impacted by the alternative recommendations made to the client.

2. Implications for small-scale savers. The proposed rule will bring with it increased compliance costs. These costs, combined with a reluctance to assume more risk and a fear of litigation, may make some advisers less likely to offer retirement advice to households with modest savings. These households are the ones most in need of direction and education, but because their accounts will not turn profits for advisors, they may be abandoned. According to the Employee Benefits Security Administration (EBSA), the proposed rule will save families with IRAs more than $40 billion over the next decade. However, this benefit must be weighed against the attendant costs of implementing the rule. It is possible that the rule will leave low- and medium-income households without professional guidance, further widening the retirement savings gap. The DoL should consider ways to minimize or manage these costs. Options include incentivizing advisors to continue guiding small-scale savers, perhaps through the tax code, and promoting increased financial literacy training for households with modest savings. Streamlining and simplifying the rules would also help.

3. Need for Research on Online Solutions. The Administration has argued that online advice may be the solution for these savers, and for some fraction of this group that may be a good alternative. Relying on online sites to solve the problem seems a stretch, however. Maybe at some time in the future that will be a viable option but at present there are many people, especially in the older generation, who lack sufficient knowledge and experience to rely on web solutions. The web offers dangers as well as solutions, with the potential for sub-optimal or fraudulent advice. I urge the DoL to commission independent research to determine how well a typical saver does when looking for investment advice online. Do they receive good advice? Do they act on that advice? What classes of savers do well or badly with online advice? Can web advice be made safer? To what extent do persons receiving online advice avoid the mistakes described earlier?

4. Pitfalls of MyRA. Another suggestion by the Administration is that small savers use MyRA as a guide to their decisions and this option is low cost and safe, but the returns are very low and will not provide much of a cushion in retirement unless households set aside a much larger share of their income than has been the case historically.

5. Clarifications about education versus advice. The proposed rule distinguished education from advisement. An advisor can share general information on best practices in retirement planning, including making age-appropriate asset allocations and determining the ideal age at which to retire, without triggering fiduciary responsibility. This is certainly a useful distinction. However, some advisors could frame this general information in a way that encourages clients to make decisions that are not in their own best interest. The DoL ought to think carefully about the line between education and advice, and how to discourage advisors from sharing information in a way that leads to future conflicts of interest. One option may be standardizing the general information that may be provided without triggering fiduciary responsibility.

6. Implications for risk management. Under the proposed rule advisors may be reluctant to assume additional risk and worry about litigation. In addition to pushing small-scale savers out of the market, the rule may encourage excessive risk aversion in some advisors. General wisdom suggests that young savers should have relatively high-risk portfolios, de-risking as they age, and ending with a relatively low-risk portfolio at the end of the accumulation period. The proposed rule could cause advisors to discourage clients from taking on risk, even when the risk is generally appropriate and the investor has healthy expectations. Extreme risk aversion could decrease both market returns for investors and the “value-add” of professional advisors. The DoL should think carefully about how it can discourage conflicted advice without encouraging overzealous risk reductions.

The proposed rule is an important effort to increase consumer protection and retirement security. However, in its current form, it may open the door to some undesirable or problematic outcomes. With some thoughtful revisions, I believe the rule can provide a net benefit to the country.

^{1. Baily’s work has been assisted by Sarah E. Holmes. He is a Senior Fellow at the Brookings Institution and a Director of The Phoenix Companies, but the views expressed are his alone.}

^{2. As you know, postponing Social Security benefits yields an 8 percent real rate of return, far higher than most people earn on their investments. For most of those that can manage to do so, postponing the receipt of benefits is the best decision.}

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Community banks play a key role in their local communities by offering traditional banking services to households and lending to nearby small businesses in the commercial, agriculture, and real estate sectors. Because of their close relationship with small businesses, they drive an important segment of economic growth. In fact, compared to all other banks (and to credit unions), small banks devote the greatest share of their assets to small business loans.

In this paper, titled "The community banks: The evolution of the financial sector, Part III," (PDF) Baily and Montalbano examine the evolution of community banks before, through, and after the financial crisis to assess their recovery.

The authors find that despite concerns about the long-term survival of community banks due a decline in the number of banks and increased Dodd-Frank regulations, they continue to recover from the financial crisis and are in fact out-performing the Big Four banks in several key measures.

Although the number of community banks has been steadily declining since before 2003, most of the decline has come from the steep drop in the smallest banking organizations—those with total consolidated assets of less than $100 million. Community banks with total consolidated assets that exceed $300 million have in fact increased in number. Most of the decline in community banks can be attributed to the lack of entry into commercial banking.

In a previous paper, Baily and Montalbano showed that the gap in loans and leases among the Big Four has widened since the financial crisis, but the new research finds that community banks seem to be returning to their pre-crisis pattern, although slowly, with the gap between deposits and loans shrinking since 2011. While total deposits grew gradually after 2011, though at a pace slower than their pre-crisis rate, loans and leases bottomed out in 2011 at $1.219 trillion.

The authors also examine community banks' return on assets (ROA), finding it was lower overall than for the Big Four or for the regionals, and has come back to a level closer to the pre-crisis level than was the case for the larger banks. The level of profitability was slightly lower for community banks in 2003 than it was for the larger banks—about 1.1 percent compared to 1.7 percent for the regional banks—but it did not dip as low, reaching a bottom of about -0.1 percent compared to -0.8 percent for the regional banks.

Baily and Montalbano also find that total assets of the community banks increased 22.5 percent (adjusted for inflation, the increase was 7 percent); the average size of community banks has increased substantially; total bank liabilities grew steadily from 2003-2014; the composition of liabilities in post-crisis years looked largely similar to the composition in the pre-crisis years; and securitization—which plays a relatively small role in the community banking model—has been steadily increasing in the time period both before and after the crisis. 

To read more, download the full paper here.

The paper is the third in a series that examines how the financial sector has evolved over the periods both before and after the financial crisis of 2007-2008. The first paper examines the Big Four banks, and the second takes a closer look at regional banks.

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Neel Kashkari, the newly appointed President of the Federal Reserve Bank of Minneapolis, is super-smart with extensive experience in the financial industry at Goldman Sachs and then running the government’s TARP program, but his call to break up the big banks misses the mark.

Sure, big banks, medium-sized banks and small banks all contributed to the devastating financial crisis, but so did the rating agencies and the state-regulated institutions (mostly small) that originated many of the bad mortgages.  It was vital that regulation be strengthened to avoid a repetition of what happened – and it has been.  There should never again be a situation where policymakers are faced with either bailing out failing institutions or letting them fail and seeing financial panic spread.

That’s why the Dodd-Frank Act gave the authorities a new tool to avoid that dilemma titled “Orderly Liquidation Authority,” which gives them the ability to fail a firm but sustain the key parts whose failure might cause financial instability.  Kashkari thinks that the authorities will not want to exercise this option in a crisis because they will be fearful of the consequences of imposing heavy losses on the original owners of the largest banks.  It’s a legitimate concern, but he underestimates the progress that has been made in making the orderly liquidation authority workable in practice.  He also underestimates the determination of regulators not to bail out financial institutions from now on.

To make orderly liquidation operational, the Federal Deposit Insurance Corporation (FDIC) devised something called the “single point of entry” approach, or SPOE, which provides a way of dealing with large failing banks.  The bank holding company is separated from the operating subsidiaries and takes with it all of the losses, which are then imposed on the shareholders and unsecured bond holders of the original holding company, and not on the creditors of the critical operating subs and not on  taxpayers.  The operating subsidiaries of the failing institution are placed into a new bank entity, and they are kept open and operating so that customers can still go into their bank branch or ATM and get their money, and the bank can still make loans to support household and business spending or the investment bank can continue to help businesses and households raise funds in securities markets.  The largest banks also have foreign subsidiaries and these too would stay open to serve customers in Brazil or Mexico.

This innovative approach to failing banks is not magic, although it is hard for most people to understand.  However, the reason that Kashkari and other knowledgeable officials have not embraced SPOE is that they believe the authorities will be hesitant to use it and will try to find ways around it.  When a new crisis hits, the argument goes, government regulators will always bail out the big banks.

First, let’s get the facts straight about the recent crisis.  The government did step in to protect the customers of banks of all sizes as well as money market funds.  In the process, they also protected most bondholders, and people who had lent money to the troubled institutions, including the creditors of Bear Stearns, a broker dealer, and AIG, an insurance company.  This was done for a good reason because a collapse in the banking and financial system more broadly would have been even worse if markets stopped lending to them.  Shareholders of banks and other systemically important institutions lost a lot of money in the crisis, as they should have.  The CEOs lost their jobs, as they should have (although not their bonuses).  Most bondholders were protected because it was an unfortunate necessity.

As a result of Dodd-Frank rules the situation is different now from what it was in 2007.  Banks are required to hold much more capital, meaning that there is more shareholder equity in the banks.  In addition, banks must hold long-term unsecured debt, bonds that essentially become a form of equity in the event of a bank failure.  It is being made clear to markets that this form of lending to banks will be subject to losses in the event the bank fails—unlike in 2008.  Under the new rules, both the owners of the shares of big banks and the holders of their unsecured bonds have a lot to lose if the bank fails, providing market discipline and a buffer that makes it very unlikely indeed that taxpayers would be on the hook for losses.

The tricky part is to understand the situation facing the operating subsidiaries of the bank holding company — the parts that are placed into a new bank entity and remain open for business.  The subsidiaries may in fact be the part of the bank that caused it to fail in the first place, perhaps by making bad loans or speculating on bad risks.  Some of these subsidiaries may need to be broken off and allowed to fail along with the holding company—provided that can be done without risking spillover to the economy.  Other parts may be sold separately or wound down in an orderly way.  In fact the systemically important banks are required to submit “living wills” to the FDIC and the Federal Reserve that will enable the critical pieces of a failing bank to be separated from the rest.

It is possible that markets will be reluctant to lend money to the new entity but the key point is that this new entity will be solvent because the losses, wherever they originated, have been taken away and the new entities recapitalized by the creditors of the holding company that have been “bailed in.”   Even if it proves necessary for the government to lend money to the newly formed bank entity, this can be done with reasonable assurance that the loans will be repaid with interest.  Importantly, it can be done through the orderly liquidation authority and would not require Congress to pass another TARP, the very unpopular fund that was used to inject capital into failing institutions.

There are proposals to enhance the SPOE approach by creating a new chapter of the bankruptcy code, so that a judge would control the failure process for a big bank and this could ensure there is no government bailout.  I support these efforts to use bankruptcy proceedings where possible, although I am doubtful if the courts could handle a severe crisis with multiple failures of global financial institutions.  But regardless of whether failing financial institutions are resolved through judicial proceedings or through the intervention of the FDIC (as specified under Title II of Dodd-Frank) the new regulations guaranty that shareholders and unsecured bondholders bear the losses so that the parts of the firm that are essential for keeping financial services going in the economy are kept alive.  That should assure the authorities that bankruptcy or resolution can be undertaken while keeping the economy relatively safe.

The Federal Reserve regulates the largest banks and it is making sure that the bigger the bank, the greater is the loss-absorbing buffer it must hold—and it will be making sure that systemically important nonbanks also have extra capital and can be resolved in an orderly manner.  Once that process is complete, it can be left to the market to decide whether or not it pays to be a big bank.  Regulators do not have to break up the banks or figure out how that would be done without disrupting the financial system.

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Editor's note: This piece originally appeared in Bloomberg Government. 

       

       

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The failed coup in Turkey on July 15 to 16, organized by factions within the Turkish military in an attempt to overthrow the government of President Erdoğan, represents both a victory and a new trial for Turkish democracy. Although the Turkish citizenry brought the country back from the brink of anarchy and civil war, many analysts see last week’s events as a consequence of the political instability and discord that has been mounting for years as Erdoğan has consolidated powers, marginalized the opposition, and redefined Turkey’s democracy. How will the president react in the aftermath of the coup? Will the democratic backsliding intensify, or can the thwarted coup offer new opportunity for reconciling the deeply-polarized nation?

The upheaval and political instability in Turkey also holds significant implications for Turkey’s foreign policy and the fate of a neighboring region already in turmoil from the war in Syria and insecurity in Iraq. The West desperately needs a stable, democratic, and predictable partner in its NATO-ally Turkey to address the many challenges besetting the region and to fight the Islamic State (or ISIS). How will recent events affect regional stability and Turkey’s cooperation with the West on security issues, including the resettlement of Syrian refugees? What does the failed coup mean for the coalition against ISIS engagement in Syria?

On July 20, the Foreign Policy program (FP) at Brookings hosted a panel discussion to consider these questions and other domestic and international consequences of the coup attempt in Turkey. Brookings Senior Fellow and Director of the Center on the United States and Europe Fiona Hill introduced and moderated a wide-ranging conversation featuring FP Senior Fellows Shadi Hamid, Kemal Kirişci, Michael O'Hanlon, and Ömer Taşpınar.

After the discussion, the speakers took questions from the audience.

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The failed coup in Turkey on July 15 to 16, organized by factions within the Turkish military in an attempt to overthrow the government of President Erdoğan, represents both a victory and a new trial for Turkish democracy. Although the Turkish citizenry brought the country back from the brink of anarchy and civil war, many analysts see last week’s events as a consequence of the political instability and discord that has been mounting for years as Erdoğan has consolidated powers, marginalized the opposition, and redefined Turkey’s democracy. How will the president react in the aftermath of the coup? Will the democratic backsliding intensify, or can the thwarted coup offer new opportunity for reconciling the deeply-polarized nation?

The upheaval and political instability in Turkey also holds significant implications for Turkey’s foreign policy and the fate of a neighboring region already in turmoil from the war in Syria and insecurity in Iraq. The West desperately needs a stable, democratic, and predictable partner in its NATO-ally Turkey to address the many challenges besetting the region and to fight the Islamic State (or ISIS). How will recent events affect regional stability and Turkey’s cooperation with the West on security issues, including the resettlement of Syrian refugees? What does the failed coup mean for the coalition against ISIS engagement in Syria?

On July 20, the Foreign Policy program (FP) at Brookings hosted a panel discussion to consider these questions and other domestic and international consequences of the coup attempt in Turkey. Brookings Senior Fellow and Director of the Center on the United States and Europe Fiona Hill introduced and moderated a wide-ranging conversation featuring FP Senior Fellows Shadi Hamid, Kemal Kirişci, Michael O'Hanlon, and Ömer Taşpınar.

After the discussion, the speakers took questions from the audience.

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• Turkey coup attempt was a shock
• Institutional collapse of Turkey unprecedented
• Disaster averted in failed Turkey coup
• Incirlik Air Base not irreplaceable
• Turkey after the coup attempt: Implications for Turkish democracy, foreign policy, and the future of the Syrian War

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Abstract

An individual-based computational model of smallpox epidemics in a two-town county is presented and used to develop strategies for bioterror containment. A powerful and feasible combination of preemptive and reactive vaccination and isolation strategies is developed which achieves epidemic quenching while minimizing risks of adverse side effects. Calibration of the model to historical data is described. Various model extensions and applications to other public health problems are noted.

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Campaign finance remains one of the most important and controversial aspects of U.S. democracy, as shown by recent legislation, court challenges, and demands for reform. A new Brookings Institution Press book, Financing the 2004 Election, examines the implications that the costs and trends of 2004 have for the current elections.

On September 12, as the 2006 election cycle shifted into high gear, Brookings hosted a panel of experts on money and politics to examine how the year's campaign spending patterns compared to those in previous elections.

Brookings Senior Fellow Thomas Mann addressed these issues along with co-editors Anthony Corrado, Brookings nonresident senior fellow and professor of government at Colby College in Waterville, Maine; and David Magleby, Senior Research Fellow at the Center for the Study of Elections and Democracy and Dean of the School of Family, Home and Social Sciences at Brigham Young University in Utah.

The speakers compared candidate and party receipts of 2006 to date with those of 2002 and 2004, and examined the importance of the surge in individual donors and the role of 527 and 501(c) organizations. They also discussed how the Bipartisan Campaign Reform Act (BCRA) performed in 2004 and how the 2006 elections further test federal elections legislation. The briefing was co-sponsored by the Center for the Study of Elections and Democracy.

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The 2008 elections showcased the power of the Internet to generate voter enthusiasm, mobilize volunteers and increase small-donor contributions. After the political world has been arguing about campaign finance policy for decades, the digital revolution has altered the calculus of participation.

On January 14, a joint project of the Campaign Finance Institute, American Enterprise Institute and the Brookings Institution unveiled a new report that seeks to change the ongoing national dialogue about money in politics. At this event, the four authors of the report will detail their findings and recommendations. Relying on lessons from the record-shattering 2008 elections and the rise of Internet campaigning, experts will present a new vision of how campaign finance and communications policy can help further democracy through broader participation.

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