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Posts by Max Gulker

Best of 2016: Why We Live Beyond Our Means

This week we are revisiting some of the best Daily Economy blogs of 2016. This piece first ran in April. Our January research brief, also by Max, will deal with the same topic.

Americans are living beyond their means more than ever before. In a recent series of articles, The Atlantic Monthly documents “the secret shame of middle class Americans”: spending more, saving less and often unable to come up with even a few hundred extra dollars in the face of a financial emergency.

Experts often chalk this trend up to government policy or culture, but ignore a very basic explanation: We simply have more opportunities to make bad financial decisions than in the past. While this explanation sounds simplistic, it actually places financial health in the context of many other problems we humans create for ourselves.

Take, for example, the fact that people in the developed world are increasingly overweight. One commonly accepted explanation is that fatty and high-carb foods were scarce when humans evolved, so we developed cravings to help get what we needed. But in an age of microwaves and convenience stores, such instant gratification is at our fingertips, and we end up consuming too much.

From food to electronics, cars to homes, we’ve witnessed an explosion in the amount and variety of consumer products available. At the same time, shopping is faster and easier than ever before due to the Internet and ease of transportation.

Finally, our financial system has made borrowing and credit easier for consumers across the socioeconomic spectrum. Buying the next new toy used to require planning, saving and perhaps most importantly, waiting. Now, we can get the rewards of a new purchase almost instantly while pushing the cost and financial risk to the future. In effect, we can run a Ponzi scheme on our future selves, seeking short-term benefit for future costs that, though less tangible, can pile up to the point of disaster.

So should the government step in and restrict our opportunities to make bad choices? Not so fast. It’s instructive to look at our efforts to fight the ultimate source of short-term pleasure in exchange for future disaster, illegal drugs. The consensus view is that prohibition, aggressive policing and prosecution have done little to solve the problem.

The best solution available may be a combination of education and steps to make it easier to make the right financial decisions. Here at AIER, we hope to contribute to the solution with our upcoming economic wellness initiative.

From consumer goods to junk food to narcotics, we have trouble making decisions when instant gratification is available for costs that only come down the road. These problems increase when society and technology make the quick payoff more available. There may be no easy fix to people living beyond their means, but understanding the problem in the broader context of how we make decisions is the first step down the road to better solutions.

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The Struggle to Save Money

In previous blog posts, I’ve discussed some reasons Americans spend more and save less than they should or even plan to. The implicit assumption in these discussions was that they had the option — in other words, that they had the resources to achieve some level of financial wellness.

But as my upcoming brief in January shows, that only includes about half the population. The other half of Americans cannot afford to set aside the money needed to be resilient to financial shocks and prepared for the future.

For the purposes of the work, I look at three major components of what are termed financial wellness: short-term liquid savings, longer-term savings and investment, and not having or paying off debt. I look at this question of who can “afford” financial wellness by simulating the budgets of young, single Americans. I estimate how much so-called discretionary income they have by subtracting out taxes and the cost of living for basic necessities (not including things like meals out, vacations, or home appliances). We’re then left with so-called discretionary income. That money can be saved or invested, or it can be spent on the type of lifestyle goods mentioned above.

I go over multiple plans in the brief, but here I’ll focus on putting 10 percent of one’s income toward the financial goals listed above. For instance, under this plan an individual could build an emergency savings fund equal to three months’ salary (a level recommended by some experts) in two-and-a-half years, before turning to longer-term investing goals such as retirement. Many experts recommend putting away more than 10 percent, but it’s a modest start.

I estimate that the median 30-year-old with annual income of $35,600 would likely do fine with this rule; put away 10 percent and he or she would still have $250 per month for meals out, vacations, or saving for a down payment on a home. However, moving not that far down the income distribution, those below the 43rd (about $32,000) percentile of income could not afford this plan while living even a modest lifestyle. And we haven’t even considered debt: Give that median earner the average American’s credit card debt, and he or she would no longer be able to afford the 10 percent rule.

It’s staggering to think that almost half of Americans (many defined as middle class) cannot afford to set aside the money required to achieve what’s being called financial wellness. But there’s a second group deemed financially well, who could afford to put the money away but do not. For instance, well over half of earners in the top quartile do not have the recommended amounts of money in short-term savings. It’s important to estimate the relative size of these two groups because they need different assistance in addressing the problem. Those who can afford financial wellness may benefit from “nudge” type rules like making investing in a 401(k) the default option. But the group that cannot afford to set the money aside likely needs investment in human capital, as well as real discussion from experts that provide help about more modest  goals that would help more people set at least some money aside.

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How Will Small Business Fare Under Trump?

President-Elect Donald Trump rarely made specific mention of small businesses during the campaign. But many of the policies he promised to enact have the potential to effect small business, for better or for worse. Presidents are notorious for breaking campaign promises, but especially in the case of a winner with no track record in government, promises are  all we have to go on. So let’s look at some of Trump’s promises as they relate to America’s small businesses.

Trump’s promises to ease the federal regulatory burden may help small businesses who are often disproportionately affected by such rules. When I spoke to small businesses owners for a previous study, many noted regulations related to the minimum wage and health care as top concerns. Trump is far less likely to advocate for a drastically higher federal minimum wage, but he has shown openness to a minimum wage as high as $10/hour. He has also promised to repeal Obamacare, though business owners will have to wait and see what changes he actually makes to the Affordable Care Act and other legislation.

Another area of potential promise to small business owners under Trump is tax reform. In addition to lower corporate taxes, he has at least at times discussed reforming and simplifying the overall tax code. One area where small businesses have struggled is keeping up with the highly complex federal tax code, as they lack the departments of accounting and legal experts employed by their larger competitors. However, this all may be wishful thinking, as simplifying the tax code in a meaningful way would involve breaking the powerful nexus of big business, lobbying and campaign contributions underlying the current system.

On the other hand, small business may take a hit from Trump’s approaches to trade and immigration. Advocacy groups generally consider freer trade as good for small business, due to reduced expenses and access to markets. And more aggressive immigration policies could create new regulations just as the president eliminates others.

Finally, Trump’s stated priorities do not address many of our economy’s fundamental problems: His proposed tax cuts are likely to increase the budget deficit, and none of his plans address the future of government entitlements like Social Security and Medicare.

One last concern with the next president’s policies takes us back to his lack of specific attention to small businesses during the campaign. President-Elect Trump is often seen as being pro-big business. Without attention to how the playing field may be tilted from government policies, small businesses stand a chance of facing new competitive threats from larger firms. The president-elect’s promises of radical change, combined with a lack of specifics, have small business owners attempting to read the tea leaves along with everyone else.

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Did Polling Really Fail to Spot Trump’s Rise?

Many Americans did a double take Tuesday night as the election results began to come in. In state after state, Donald Trump was consistently outperforming even the most recent polls on his way to what many considered a shocking victory. So why did the actual results of the 2016 presidential election look so different than the picture painted by pre-election polls?

First, let’s look at how far off the polls actually were. An average of nine major polls taken in the week or so before the election, as reported by fivethirtyeight.com, gave Clinton about a 3 point lead in the national popular vote. While it looks like Clinton may finish slightly ahead when the votes are counted, the actual popular vote cast Tuesday was essentially a tie. In some swing states, polling error was slightly larger, while in others it was slightly smaller. A similar average of polls had Clinton up 3.5 points in Pennsylvania, while Trump won the state by 1 point. In Michigan, the average actually showed the two candidates in a dead heat, and Trump again won by 1 point.

The actual error when comparing an average of polls to the results was somewhat small: typically just a few percentage points. But the error was systematic. Trump outperformed his projections virtually everywhere. It’s likely that a number of factors led to this error, potentially including:

  • Underperformance of third-party candidates – While Gary Johnson, the Libertarian candidate, performed just about on par with his polls nationally, he often underperformed his polling numbers in swing states. He received almost 2 percent less of the vote than the polling average in Pennsylvania, and 1 percent in Michigan. It’s possible that some voters who identified as Johnson supporters in the polls either changed their mind before Election Day and cast their votes for Trump, or simply felt more comfortable telling pollsters they were voting for Johnson.
  • Undecided voters — Virtually all polls before Election Day had at least a few percent of responders saying they were unsure for whom they would vote. Since “none of the above” is not an option on the ballot, these voters might have largely broken for Trump before Election Day.
  • Systematic sampling error – Donald Trump was a unique candidate in recent history, and it’s very possible that typically used sampling techniques missed a small portion of his electorate. Coming on the heels of polls also underestimating Brexit, the British vote to leave the European Union, observers have speculated that polls tend to miss some populist support.

In addition to these polling issues, some of the perceived error may be due to our own perceptions when forecasting uncertain events. Every reputable poll reports sampling error along with their numbers, and many of today’s projections are made in terms of probability rather than certain outcomes. For instance, fivethirtyeight.com put Clinton’s win probability between 65 and 75 percent in the couple of weeks prior to the election. That translates to a 1-in-3 or -4 chance of a Trump victory. We perceive Trump’s victory as a shock, but with odds like that, it shouldn’t be. A 1-in-3 or -4 event isn’t all that unlikely.

Forecasting outcomes in complex systems, such as the sum total of the decisions of millions of human beings, is fraught with opportunities for error. Four years from now, we’ll still be watching the polls, but perhaps we’ll interpret the results with a bit more nuance and humility.

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Why One Vote Matters

Do people vote their pocketbook? We often express confusion when Americans in one demographic group or another tend to vote for a particular party when they would likely be financially better off under the policies of the other party. It’s easy to think of examples on both sides (though I’ll avoid turning this post into such a list). But if personal finances are the only driving force behind your decision, why vote at all? Unless the election is decided by one vote, you’ll live under the same outcome either way, and won’t have to sacrifice your time lining up at a polling place. Looking at this question of why people vote at all can help inform why they vote for whom they do.

Let’s step back and look at a classic example of a public good. Suppose you’re in a public park and see a piece of litter on the ground. Picking it up would involve effort and perhaps handling something unsavory, and besides, someone else will come along and do it. That’s the so-called free-rider problem at work. So why might you pick up the piece of litter? It could be pure altruism, if you feel duty-bound to contribute to the cleanliness of the park for all to enjoy. But it also might give you a sense of identity and belonging: You care about the community and the planet, and fit in with others who feel the same way.

While unique in some ways, the issue of voting largely mirrors the public good problem above. Many people choose not to vote, just like many people don’t pick up the litter. Altruism comes into play as a motivation to vote when people aren’t passionate about any candidate but feel they are doing their “civic duty” (though doing one’s duty can certainly enhance someone’s positive identity). But often, a candidate’s core supporters are those to whom he or she truly speaks: Those who feel better about their own identity or sense of belonging by supporting the candidate. For these people, standing in line is a small price to pay.

When you’re confused as to why a candidate has the support they do, it’s often informative to look beyond their policy proposals and whether you perceive them as fit for the job. Take a look at what the candidate is telling supporters about themselves. And think about what your own candidates or party of choice tell you about your own identity and where you fit in. For many people, the decision to take time out of their day to cast a ballot isn’t about tangible personal benefit, nor is it about pure sense of duty. Instead, it’s about who they are and aspire to be.

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Student Entrepreneurs Show the Power of Ideas

From left: NAACE President and CEO Dr. Rebecca Corbin, Max Gulker, and Amanda Gordon, award recipient.

One advantage for our economy of small businesses is that they form their own ecosystem where the best ideas can evolve and rise to the top. When allowed to robustly compete for investors and customers, many small entrepreneurs will fail. But those few that truly succeed will have products and services that meet consumer needs, often in ways that a single large business could not have planned in advance.

I got to see this small business ecosystem in action on October 10, when I had the privilege of presenting the 2016 Student Entrepreneur Awards (made possible by the C. Lowell Harriss Scholarship Fund established at AIER) at the annual conference of the National Association for Community College Entrepreneurship (NACCE).

The three award recipients all embody the power of motivated young people who are mentored by the right programs. But in listening to their stories, what really struck me is that all three young entrepreneurs found the basis of their ideas from personal life experience, demonstrating their understanding of niche markets where small businesses often excel.

Third place winner Ezekiel “Zeke” MacMillan loved visiting local clothing shops, but always seemed to walk away empty handed. As told on his website, his reaction to the high-end clothing on display was “I can do that, but cooler and cheaper.” Zeke, a student at Haywood Community College in North Carolina, started Don Raven, specializing in T-shirts and sweatshirts. Born and raised in the Carolinas, Zeke’s shirts are inspired by Southern style, but are versatile enough to be worn for different uses and by people with all sorts of different taste in clothing. When I asked Zeke what sets him apart from the competition, he focused on the quality of material he uses, to which I can personally attest, after having bought a shirt myself!

Second-place winner Amanda Gordon is a creative and highly motivated student at Sir Francis Drake High School, who is also enrolled in business classes at the College of Marin in California. Amanda had a talent and interest in making jewelry, and like Zeke, saw that she could make a product better and cheaper than what was out there. The result was California Gem, offering hand and body chain jewelry personally made by Amanda. She runs a successful online business, and has also leveraged her own network and relationships by displaying a collection at Embellish Marin, a local brick-and-mortar store. Amanda is also using her business as a catalyst for social change, educating consumers on problems with child labor and exploitation in the supply chain of too much of the jewelry sold in the U.S.

First-place winner Tac Mohammed started Toppy Toddler USA, manufacturing, wholesaling and retailing waterproof baby bibs. Tac, who recently graduated from Miami-Dade College in Florida, was inspired by a need he saw all too clearly in his own life as parent of a toddler.

“I sat in awe, watching a hailstorm of rice and beans plummeting to the ground, as my 18-month-old son sat joyfully eating his dinner. Half of what was in his bowl was now resting on the table, his clothing, and the floor.” Tac turned his son’s mess into a growing company that already has $9,000 per month in revenue. Like virtually all successful entrepreneurs, Tac knows the importance of the pivot, refining not only his product along the way, but also his means of distribution. He has found a successful niche selling bulk orders to day-care centers.

It was informative to see this entrepreneurial ecosystem in action. By giving lots of small but motivated entrepreneurs help with starting a businesses, but then subjecting them to the competition of the market, ideas naturally rise to the top that a centralized planner at a large business could never have had in advance.

I’m proud that AIER, through the Harriss Scholarship Fund, is making a significant contribution to this process.

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Can Body Language Help Get a Small Business Loan?

One finding of my research on small businesses earlier this year is that they are better than their larger competitors at responding to so-called “soft” information. In larger firms, information often must be communicated through several hierarchical layers to a centralized decision maker; in small businesses, the decision maker is typically more closely linked to the direct gathering of this information.

One obvious place to test this hypothesis is the banking industry. When determining whether to make a commercial loan (as well as the interest rate to charge), a bank looks at hard data on a business’s finances and credit history. But a loan officer at a bank branch also takes in information more difficult to quantify.

The loan officer might know people around town who have dealt with the business, or even observe the body language of the business owner when discussing the loan. This is precisely the information that is difficult to pass up a chain of management. If such information is important, we might expect to see differing behavior and outcomes in commercial lending for small versus large banks.

In a 2002 paper, a group of authors looked at lending decisions by small and large banks to businesses with varying degrees of financial documentation. They found that large banks were significantly less likely to lend to businesses without formal financial records than small banks. This result is consistent with the idea of soft information discussed above. If small businesses can take in and respond to soft information more efficiently than large ones, their need for hard data may be less. These findings are echoed in a 2004 paper that finds small banks utilize more information on a potential borrower’s “character” than larger banks.

While the evidence that soft information is a greater influence on small banks’ lending decisions is compelling, the ultimate test would compare commercial lending outcomes for small and large banks. Consider a business that wants a loan and, in terms of hard financial data, is right on the threshold of what banks consider credit worthy. If small banks respond to soft information more efficiently, we would expect to see a lower default rate than for large banks among these threshold cases. I’m currently in the preliminary stages of research on just this question, and I am looking for the best data sources to shed light on lending outcomes.

In addition to testing theories on the lending side for small and large banks, the results above might be important for small businesses doing the borrowing. Numerous sources say that lending to small business has not kept pace with the overall recovery since the Great Recession. To the extent that credit-worthy small business owners can better understand the right banks with which to do business, their odds of getting much-needed loans may increase. Look in this space in the coming months for more updates on this research.

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Hillary Clinton and Donald Trump on Small Business

Politicians love to talk about small business, but often use the topic for a quick photo op and feel-good story about the economy. However, both major presidential candidates are proposing policies that are highly relevant to small business owners.

Hillary Clinton focuses on “leveling the playing field” between small and large businesses, while Donald Trump advocates policies intended to help businesses regardless of size. A comparison of these proposals highlights an interesting question: How differently should the government treat small and large businesses?

Clinton’s website has a page dedicated to small business, including those photo ops, but also a sizable list of policy proposals. Virtually all of the proposals focus on the premise that small businesses face greater or different challenges related to taxation, financing and regulation than their large counterparts. Perhaps the proposal of Clinton’s that could have the most impact is a new standard tax deduction for small businesses. In addition, she proposes “easing the burdens” on local banks to lend to small businesses, and simplifying the licensing and regulation of small businesses at all levels of government. While the site offers many specific ideas, it is largely devoid of numbers: We aren’t told how large Clinton’s tax deduction will be, or the size of any potential bank subsidy for small business lending.

Donald Trump’s website makes no specific mention of small business, but puts forward some policies aimed at business in general. Trump proposes limiting taxes to 15 percent for all businesses, lower than the current average rate of 19.8 percent paid by small business, according to the Small Business Administration. He proposes a review and prioritization of regulations by every federal agency, as well as trade reform. While his tax plan offers a more specific number than Clinton’s, it is harder to predict how the end results of regulatory review and trade reform would help small businesses.

So is it more effective to have policies specifically targeted to small businesses, or to simply target business in general? There are clear differences in the structures of small and large firms that put small firms at a disadvantage when dealing with complex tax or regulatory rules, or the search for financing. Large businesses are typically big organizations with many specialized employees, often including lawyers and accountants who can negotiate the processes discussed above. Therefore, the marginal cost of one more regulation or change to the tax code is likely lower for large firms. They can also obtain financing from equity and debt markets usually out of reach to small businesses. Helping small businesses clear these hurdles may make them more competitive.

At the same time, one might argue that more differences in regulatory treatment of small and large businesses inevitably leads to more red tape, and simple policies aimed at all businesses are ultimately more efficient.

Both candidates’ proposals also carry risks for small businesses. Clinton’s proposals will require a good deal more specificity and negotiation, carrying the risk that they could get lost in the sea of photo ops and feel-good talk about Main Street. Under Trump, small businesses risk getting lost in the shuffle entirely, carrying the possibility that the playing field may tip even further toward large firms. Despite these unanswered questions, the clear differences in approach between the candidates will give small business owners plenty of food for thought on Election Day.

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The Resilient, Adaptable Travel Agent

Travel icons 500 pix

When large businesses expand or enter a new market, we can expect some degree of change, and often, some smaller businesses will go out of business. But observers often overestimate such trends, predicting that small businesses will become obsolete. As I discussed in my recent research brief, there are areas in which small businesses are likely to outperform their competitors, potentially leaving room in the market even as larger businesses grow. The travel agency industry over the past two decades is a prime example.

As more and more consumers booked travel online, many traditional “brick and mortar” agents were forced out of the market, but others found ways to play to their strengths and sustain their business.

I first thought about travel agents in graduate school, when I was interested in how the rise of e-commerce was affecting retail industries. Until the late 1990’s, booking air travel was agents’ bread and butter. But as consumers began to purchase tickets online, traditional agents, typically small and independently owned, had to adjust or leave the market. Many observers predicted the end of the traditional travel agency.

But the industry adapted. It touted its advantages over online platforms in booking packaged tours and other more complex travel. While I couldn’t directly observe brick and mortar agent profits over time from different types of travel, I was able to observe how many agents stayed in business in each local market, and used this along with data on demand for air and more complex travel services to estimate the composition of agents’ profits over time (this statistical technique was developed by economists Tim Bresnahan and Peter Reiss). While estimated profits related to air travel virtually vanished between 1998 and 2003, I found no significant decline in agent profits related to cruises and packaged tours.

A look at the number of travel agents in the U.S. over time helps confirm the idea that many agents were able to weather the storm. The number of agents fell by about 12,000 from 1998 to 2005, but the decline slowed to about 4,000 in the following seven years. While there has been an uptick since 2012, industry employment has remained flat, suggesting a rise in independent contractors related to the sharing economy.

max chart ps 650 pix

I’ve discussed how small businesses are often better positioned than their rivals to form relationships with customers and understand the specifics of demand in their local market. These are exactly the type of traits that help traditional travel agents book complex travel arrangements for their customers. Growth in large businesses, whether enabled by technology or simple expansion, will inevitably change markets and force some firms out of business. But many firms can and do survive by playing to their strengths.

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Big Data vs. Small Data

I received many interesting questions from the audience at my lecture last week, titled “Mom and Pop vs. Big Box – How Small Businesses Compete With Larger Rivals,” but one in particular stood out. One theme of my talk was that small businesses can gather and respond to richer and more detailed information about their local or niche markets and customers than can larger firms.

However, an audience member asked if this was changing because of Big Data. In retail, for example, large firms such as Walmart or Amazon can use data on the spending behavior of thousands or millions of customers to gather information at a level of detail previously unheard of. While I believe the answer to that question is no, it’s useful in highlighting the key differences in the advantages that businesses of different sizes have with respect to information.

Big Data is extremely useful in predicting the preferences, on average, of a consumer with a given set of characteristics. But for small local markets, for example, the sample size may not be large enough to meaningfully tease out idiosyncrasies in a community’s preferences that a small business on the ground might readily see. By talking to a few customers, a local grocer might easily notice what brands neighbors are recommending to each other, long before the resulting purchases would trigger anything in a Big Data algorithm. This is not to say the predictions yielded by Big Data aren’t useful—most small business owners would likely love to be privy to the information gathered by larger competitors—but such information is different in nature from that which smaller businesses are better positioned to gather and understand.

Another audience member brought up a key point in response to the discussion: Big Data will never directly capture the emotions behind consumers’ purchasing decisions or relationships to certain products and brands. As I discussed, many small businesses may be better positioned to forge deep relationships with customers, and therefore better understand this very human component of their decisions. The value of this type of information is underscored by the fact that many large companies hire ethnographic consultants to have personal conversations on the ground and find out what makes consumers tick.

Maybe it’s time to coin the term “small data” to reflect this type of understanding of one’s consumers and market. Such data can only be gathered through means such as direct conversations or roots in a local community. Small data can’t be gathered by a grocery store scanner, or aggregated across millions of observations. But it can greatly enhance the understanding of the environment in which a business operates. Both kinds of data certainly have their place, but much like we often forget the competitive strengths of small businesses, we tend to minimize the importance of small data.

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