Sunday, September 29, 2013

Should Hamburgers and French Fries be heavily taxed?

Fighting youth body fatness: The role of food prices 


Michael Grossman, Erdal Tekin, Roy Wada, 28 September 2013
According to the World Health Organization, childhood obesity is one of the most serious public-health problems of the 21st century. The prevalence of obesity among children has been on the rise globally over the last several decades and is now an epidemic in the US.
  • Since the mid-1970s, the proportion of children aged 12 to 19 who are obese has more than tripled from 5.0% to 18.1% in the US (Ogden et al. 2010).
These trends are extremely alarming.
  • Childhood obesity has been associated with a host of chronic health problems, such as high blood pressure, hypertension, gallbladder disease, and Type 2 diabetes as early as adolescence (Serdula et al. 1993; Freedman et al. 1999; 2007; Hill, Catenacci, and Wyatt 2006).
Children who are obese during early childhood are likely to be obese during adulthood. This not only exacerbates the aforementioned health problems, but also leads to negative long-term psychological and labour market outcomes ranging from poor self-esteem and depression to discrimination and lower wages (Daniels 2006; Mocan and Tekin 2011; Dietz 1998; Strauss 2000).

Why the extra weight?

There is a long list of explanations offered for the rapid rise in childhood obesity and overweightness. These include:
  • Falling food prices.
  • Increased demand for sugary drinks.
  • Advertising of unhealthy foods targeted at children.
  • Increased time spent in sedentary activities, such as watching TV or videos, using a computer, or playing computer games.
  • Lack of vigorous physical activity.
  • Increased food-portion sizes.
Just as there is no single explanation for the obesity epidemic, there is no single or simple solution. Most public interventions aimed at improving child and adolescent health generally take the form of policies that limit access and provide price incentives or disincentives.
The latest policy proposals for reducing childhood obesity rates involve raising the prices of unhealthy, nutrient-dense food items such as sugar-sweetened beverages and fast-foods through taxations. Such policy proposals are based on findings that selective applications of taxation and subsidies are effective in shifting food consumption away from unhealthy food towards healthier alternatives (Cawley 2010; Powell and Chaloupka 2009).
  • In general, empirical studies that examined the effects of prices on obesity found stronger effects than studies that examined the effects of food taxes (Powell, Chriqui, and Chaloupka 2009; Fletcher, Frisvold, and Tefft 2010).1
  • There is also reasonably consistent evidence demonstrating that fruit and vegetable prices, particularly of the non-starch variety, are associated with lower weight outcomes while fast-food prices are associated with higher weight outcomes for the adolescent population (Powell et al. 2013).
Moreover, these effects tend to be larger for minorities, children in lower-income families, and children whose mothers have less than a high school education.

Problems with the BMI as an indicator of obesity

The existing evidence almost exclusively comes from studies that rely solely on body mass index (BMI) as the measure of obesity. This is not surprising since BMI is easy to calculate and readily available from many social science datasets, but its reliability for use in epidemiological studies has come into question recently.
  • It is argued that some of the weak or mixed results documented by studies using BMI may be due to its limited ability to correctly distinguish body fat from lean body mass (e.g., Yusuf et al. 2004, 2005; Romero-Corral et al. 2006, 2007).
Since it is body fat (and not fat-free mass) that is responsible for the detrimental health effects of obesity, several studies caution against a sole reliance on BMI and point to a need for using direct measures of body composition in obesity studies (e.g. Smalley et al. 1990; Romero-Corral et al. 2006).

Our contribution

In a recent paper, we use clinically obtained body composition measures to conduct a comprehensive and comparative analysis of the effects of various food prices on body fatness among youths ages 12 through 18 and compare the sensitivity of our findings to results using BMI (Grossman, Tekin, and Wada 2013). Ours is the first study to consider clinically measured levels of body composition to examine the effects of food prices on body fatness among youths. It is important to assess the extent to which alternative body fat measurements are reliable and precise in the identification of the degree of obesity among youths in order to better understand the risk factors associated with obesity and develop policies to counter these risk factors.
The body composition measure that we employ is percentage body fat (PBF). We derive our PBF measure from three separate sources, two of which rely upon bioelectrical impedance analysis (BIA) and one of which relies upon dual energy x-ray absorptiometry (DXA). We also employ clinically measured height and weight to estimate the effects of prices on BMI. We draw on data from the restricted-use versions of National Health and Nutrition Examination Survey (NHANES) to merge various county-level time-varying price variables.


Our findings suggest that:
  • Increases in the real price of one calorie of food for home consumption and the real price of fast-food restaurant food result in significant reductions in the in PBF among youths.
  • An increase in the real price of fruits and vegetables has negative consequences for these outcomes.
  • Measures of PBF derived from BIA and DXA are no less sensitive and in some cases more sensitive to the food prices just mentioned than BMI, and serve an important role in demonstrating that rising food prices (except for those of fruits and vegetables) are associated with reductions in obesity rather than in body-size proportions alone.

Policy implications

These findings have important implications for the optimal targeting of public policies designed to reverse the epidemic of childhood obesity. In particular, they have implications for how changes in agricultural, tax, and subsidy policies might affect food and beverage consumption patterns. 
  • We show that selective taxes or subsidies may be able to accomplish part of this goal through changes in food prices.
We also document that uniform increases or decreases in the price of food have the expected impacts on body fatness.
  • It should be kept in mind that taxes are blunt instruments that impose significant welfare costs on individuals who consume food in moderation.
There is also the question as to whether parents may more easily and immediately affect the choices made by their children than the government policies.
Some of our results point to higher rates of time preference and lower expected future wage rates among non-white parents and youths as explanations of why minorities are more sensitive to fast-food prices and less sensitive to fruits and vegetables prices than whites. These interpretations add to the existing evidence on the wide range of benefits to early childhood intervention programs emphasised by Heckman and colleagues (e.g., Conti and Heckman 2012). We view our contribution as an important input into the policy debate concerning the most effective ways to reverse the upward trend in obesity.

Sunday, September 22, 2013

Interest Rates and Home Sales


 (The following article is an interesting read since it demonstrates the fact that two opposite conclusions are arrived at from looking at the same data)

Are Higher Mortgage Rates Boosting Home Sales? Nobody Knows.

John Maxfield
September 22, 2013

Are higher mortgage rates helping or hurting home sales? That's been one of the biggest unexpected conundrums that economists have run into of late, as there's data to support both conclusions.
Just so we're all on the same page, let's review what's happened to mortgage rates over the past few months.
We started the year out at historically low levels. Weekly data collected by Freddie Mac shows that the average rate on a 30-year fixed rate mortgage oscillated around 3.5% for much of the first half of the year, even dipping below 3.4% on two occasions.
All this changed, however, in May, as investors convinced themselves that the Federal Reserve would reduce its support for the economy and thereby drive long-term borrowing costs higher. Needless to say, it was a self-fulfilling prophecy.
In the months that followed, the cost of a home loan shot up by more than 100 basis points, ultimately settling in around 4.5%.
Looking at that chart, one would be excused for thinking that the housing market must be suffering. Like anything else, mortgage volumes are a function of supply and demand. And demand is a function of price -- that is, the interest rate. As the price goes up, demand goes down.
This is exactly what we've seen.
Since the beginning of May, purchase-money mortgage applications are down by 16%, says the Mortgage Bankers Association. And many of the nation's largest mortgage lenders are forecasting even sharper declines for overall mortgage activity.
At a recent industry conference, Timothy Sloan, the chief financial officer of Wells Fargo (NYSE: WFC), predicted that the bank's home loan volumes would drop to $80 billion in the third quarter. That's off the more than $100 billion that it's originated for each of the past seven quarters.
Sloan's counterpart at JPMorgan Chase (NYSE: JPM) made things sound even worse. "In the second quarter, we told you that if rates remained at these levels, we would expect volumes to be reduced by 30% to 40% in the second half of this year versus the first half on the back of a dramatic reduction in refinance volume," CFO Marianne Lake said.
"This is indeed ... what we're experiencing, and all of Fannie, Freddie, and the [Mortgage Bankers Association] agree that the volume reduction will be 35% flat."
But here's where it gets interesting.
The underlying data from the housing market itself appears to be accelerating in the face of these headwinds. Just last week, the National Association of Realtors released its estimate of existing-home sales for the month of August.
How do you think they fared?
Even though July witnessed a 6.5% sequential surge in sales of previously owned homes, they continued to climb in August. On a year-over-year basis, they were up by more than 13%, coming in at the highest level in six and a half years.
The reason? According to the trade group's chief economist, Lawrence Yun, "Rising mortgage interest rates pushed more buyers to close deals."
On top of this, data on the homebuilding front is, for the most part, similarly upbeat.
Earlier this year, the CEO of PulteGroup (NYSE: PHM), the nation's second largest homebuilder by volume (click here to see a graphic of the top five), noted that "[i]n a number of communities across the country, demand has been so strong that we have taken action to slow the overall pace of sales."
Addressing interest rates specifically, he said in the second-quarter earnings release that "[e]ven the recent rise in interest rates has had little effect on overall activity, as consumers continue to perceive good values, amid limited supply and generally rising sales prices, combined with the reality of high lease rates in the rental market."
The head of Lennar (NYSE: LEN), the third largest builder, chimed in as well, noting that "there are too few dwellings for a growing population and for normalized household formation." Not coincidentally, Lennar's second-quarter home deliveries jumped by 39% over to the same period last year.
Whether higher mortgage rates are going to help or hurt home sales simply isn't answerable right now. Despite the evidence that they're doing the former, I can't help believing that this relationship will reverse in the not-too-distant future.

Sunday, September 15, 2013

National Debt: Why Is It $16 Trillion ?

The National Debt Clock in New York on Dec. 31, 2012. (JUSTIN LANE/EPA - EPA)

“Our government has built up too much debt. …At $16 trillion and rising, our national debt is draining free enterprise and weakening the ship of state.”
— House Speaker John A. Boehner, Jan. 3, 2013
With a debt ceiling limit looming in the next two months, Congress and the Obama administration appear set to have another bruising battle over spending priorities.
 Before embarking on that course, lawmakers might want to re-read the Standard & Poor’s report on why it reduced the nation’s debt rating after the 2011 deal that ended the last conflict over the debt ceiling. The report offered two key reasons:
1) “The downgrade reflects our opinion that the fiscal consolidation plan  that Congress and the Administration recently agreed to falls short of  what, in our view, would be necessary to stabilize the government's medium-term debt dynamics.”
 2) “More broadly, the downgrade reflects our view that the effectiveness, stability, and predictability of American policymaking and political institutions have weakened at a time of ongoing fiscal and economic challenges to a degree more than we envisioned when we assigned a negative outlook to the rating on April 18, 2011.”
As part of its analysis, S&P assumed Republicans in Congress would never agree to raise taxes, but that actually happened as part of the “fiscal cliff’ negotiations. But S&P was also worried Congress would not fulfill the second half of promised spending cuts — and those have now been deferred for two months.
In any case, S&P was clearly looking for more signs of cooperation on restraining the debt — not confrontation.
As a refresher course, let’s look anew at the sources of this $16 trillion in debt.
The Facts
 While polls indicate that many Americans continue to believe that foreign aid is a large part of government spending, it actually constitutes less than 1 percent of the budget. And, no, the deficit can’t be eliminated by just cracking down on “waste, fraud and abuse.” We once awarded the American public Four Pinocchios for ignorance about the federal budget.
So where does the debt come from? This clever Washington Post interactive feature provides some clues — much of it comes from promises made to keep paying Social Security and Medicare. The programs annually funded by Congress generally have become a smaller share of the U.S. economy, even with funding two wars.
 (An aside: the national debt is made up of publicly held debt and money that the government owes to itself. Boehner’s $16 trillion number is this “gross debt” figure. About $11.5 trillion is public debt and the rest comes from bonds held by Social Security, Medicare and other trust funds. You can have an endless debate about whether these bonds are real or not — read our Social Security primer — but ultimately these are obligations that must be paid with either new debt or general government funds, thus taking away from other programs. There is also dispute over whether gross debt is really the best picture of the U.S. debt load, as economists often focus mostly on publicly traded debt.)
Using the White House’s historical budget tables, let’s look at what has happened to the growth of the debt under various presidents — both the overall debt and the debt that government owes to itself. The figures are for the end of each presidential term, except for Obama. The figure for Obama is as of Jan. 2, based on the Treasury’s debt-to-the-penny Web site.
                                           Size of gross debt           Federal account debt
Before Reagan                           $1 trillion                            $250 billion
Ronald Reagan                          $2.9 trillion                         $677 billion
George H.W. Bush                    $4 trillion                             $1 trillion
Bill Clinton                                 $5.6 trillion                          $2.2 trillion
George W. Bush                         $10.6 trillion                       $4.3 trillion
Barack Obama                          $16.4 trillion                       $4.9 trillion
 While raw numbers are interesting, the more telling statistic is when debt is expressed as a percentage of the overall economy (gross domestic product). We’ve rounded the numbers to keep it simple.
                                             Size of gross debt           Federal account debt
Before Reagan                           33 percent                          7 percent
Ronald Reagan                          53 percent                         12.5 percent
George H.W. Bush                    64 percent                          16 percent
Bill Clinton                                 56.5 percent                        24 percent
George W. Bush                        77 percent                          30 percent
Barack Obama                          105 percent                         31 percent
The Bottom Line
The data show that the growth of the debt in the last three decades certainly has been a bipartisan enterprise, with only Clinton reducing debt as a percentage of the U.S. economy. But even then, debt owed to Social Security, Medicare and the like kept climbing as a share of the U.S. economy.
Moreover, an increasingly large portion of the debt is money that the government owes to itself because of borrowing from large entitlement programs such as Social Security and the Medicare. That’s because the money spent on discretionary programs has generally declined, as a share of the economy, while spending on mandatory programs has soared — and will only consume a larger share of the economy as the Baby Boom generation heads into retirement.
In fact, the debt owed to entitlement programs is now almost as large a share of the economy as all U.S. government debt before Ronald Reagan became president.
Willie Sutton once supposedly said he robbed banks because “that’s where the money is.” By the numbers, some restraint on the growth of entitlements will be needed in order to control the growth of the national debt.

Saturday, September 07, 2013


What Is Economics Good For?

Recent debates over who is most qualified to serve as the next chairman of the Federal Reserve have focused on more than just the candidates’ theory-driven economic expertise. They have touched on matters of personality and character as well. This is as it should be. Given the nature of economies, and our ability to understand them, the task of the Fed’s next leader will be more a matter of craft and wisdom than of science.
When we put a satellite in orbit around Mars, we have the scientific knowledge that guarantees accuracy and precision in the prediction of its orbit. Achieving a comparable level of certainty about the outcomes of an economy is far dicier.
The fact that the discipline of economics hasn’t helped us improve our predictive abilities suggests it is still far from being a science, and may never be. Still, the misperceptions persist. A student who graduates with a degree in economics leaves college with a bachelor of science, but possesses nothing so firm as the student of the real world processes of chemistry or even agriculture.
Before the 1970s, the discussion of how to make economics a science was left mostly to economists. But like war, which is too important to be left to the generals, economics was too important to be left to the Nobel-winning members of the University of Chicago faculty. Over time, the question of why economics has not (yet) qualified as a science has become an obsession among theorists, including philosophers of science like us.
It’s easy to understand why economics might be mistaken for science. It uses quantitative expression in mathematics and the succinct statement of its theories in axioms and derived “theorems,” so economics looks a lot like the models of science we are familiar with from physics. Its approach to economic outcomes — determined from the choices of a large number of “atomic” individuals — recalls the way atomic theory explains chemical reactions. Economics employs partial differential equations like those in a Black-Scholes account of derivatives markets, equations that look remarkably like ones familiar from physics. The trouble with economics is that it lacks the most important of science’s characteristics — a record of improvement in predictive range and accuracy.
This is what makes economics a subject of special interest among philosophers of science. None of our models of science really fit economics at all.
The irony is that for a long time economists announced a semiofficial allegiance to Karl Popper’s demand for falsifiability as the litmus test for science, and adopted Milton Friedman’s thesis that the only thing that mattered in science was predictive power. Mr. Friedman was reacting to a criticism made by Marxist economists and historical economists that mathematical economics was useless because it made so many idealized assumptions about economic processes: perfect rationality, infinite divisibility of commodities, constant returns to scale, complete information, no price setting.
Mr. Friedman argued that false assumptions didn’t matter any more in economics than they did in physics. Like the “ideal gas,” “frictionless plane” and “center of gravity” in physics, idealizations in economics are both harmless and necessary. They are indispensable calculating devices and approximations that enable the economist to make predictions about markets, industries and economies the way they enable physicists to predict eclipses and tides, or prevent bridge collapses and power failures.
But economics has never been able to show the record of improvement in predictive successes that physical science has shown through its use of harmless idealizations. In fact, when it comes to economic theory’s track record, there isn’t much predictive success to speak of at all.
Moreover, many economists don’t seem troubled when they make predictions that go wrong. Readers of Paul Krugman and other like-minded commentators are familiar with their repeated complaints about the refusal of economists to revise their theories in the face of recalcitrant facts. Philosophers of science are puzzled by the same question. What is economics up to if it isn’t interested enough in predictive success to adjust its theories the way a science does when its predictions go wrong?
Unlike the physical world, the domain of economics includes a wide range of social “constructions” — institutions like markets and objects like currency and stock shares — that even when idealized don’t behave uniformly. They are made up of unrecognized but artificial conventions that people persistently change and even destroy in ways that no social scientist can really anticipate. We can exploit gravity, but we can’t change it or destroy it. No one can say the same for the socially constructed causes and effects of our choices that economics deals with.
Another factor economics has never been able to tame is science itself. These are the drivers of economic growth, the “creative destruction” of capitalism. But no one can predict the direction of scientific discovery and its technological application. That was Popper’s key insight. Philosophers and historians of science like Thomas S. Kuhn have helped us see why scientific paradigm shifts seem to come almost out of nowhere. As the rate of acceleration of innovation increases, the prospects of an economic theory that tames the economy’s most powerful forces must diminish — and with it, any hope of improvements in prediction declines as well.
SO if predictive power is not in the cards for economics, what is it good for?
Social and political philosophers have helped us answer this question, and so understand what economics is really all about. Since Hobbes, philosophers have been concerned about the design and management of institutions that will protect us from “the knave” within us all, those parts of our selves tempted to opportunism, free riding and generally avoiding the costs of civil life while securing its benefits. Hobbes and, later, Hume — along with modern philosophers like John Rawls and Robert Nozick — recognized that an economic approach had much to contribute to the design and creative management of such institutions. Fixing bad economic and political institutions (concentrations of power, collusions and monopolies), improving good ones (like the Fed’s open-market operations), designing new ones (like electromagnetic bandwidth auctions), in the private and public sectors, are all attainable tasks of economic theory.
Which brings us back to the Fed. An effective chair of the central bank will be one who understands that economics is not yet a science and may never be. At this point it is a craft, to be executed with wisdom, not algorithms, in the design and management of institutions. What made Ben S. Bernanke, the current chairman, successful was his willingness to use methods — like “quantitative easing,” buying bonds to lower long-term interest rates — that demanded a feeling for the economy, one that mere rational-expectations macroeconomics would have denied him.
For the foreseeable future economic theory should be understood more on the model of music theory than Newtonian theory. The Fed chairman must, like a first violinist tuning the orchestra, have the rare ear to fine-tune complexity (probably a Keynesian ability to fine-tune at that). Like musicians’, economists’ expertise is still a matter of craft. They must avoid the hubris of thinking their theory is perfectly suited to the task, while employing it wisely enough to produce some harmony amid the cacophony.