Introduction to the City

If you would be known, and not know, vegetate in a village; if you would know, and not be known, live in a city. Charles Caleb Colton

What is a city? Why do cities exist? Why do urban economists call them (with some exaggeration!) our greatest invention?  Those are some basic questions we will tackle from time to time in this blog.

The simplest definition of a city: a place with above average density. Think of a world without cities as a world in which our population (and other things, like capital goods) are randomly scattered across the land. That would be a very strange world, indeed. Much better is the world we live in, where most people cluster together in some form of urban settlement; and where most of those who remain in areas we call "rural" actually live in smaller clusters (think villages) that are actually functionally urban, albeit at a small scale.

There are many other definitions of "city" out there.  My venerable second edition Merriam Webster's says a city is "from the Latin, civitas, citizenship.  Vaguely, any large, important or noted town or unlabeld place, so called by way of distinction.  The collective body of citizens, or inhabitants of a city."

More colorfully, Robert Bevan, writing in The Guardian, libels the U.S. Midwest, where he claims "... the word ‘city’ has been appended with abandon to any one-brothel main street that once offered relief to travelers across the prairies.”  Waxing a little more poetic, polite, and concise, Richard Sennett offers "a place where strangers meet."  Gideon Sjoberg defines a city as “a community of substantial size and population density that shelters a variety of non-agricultural specialists, including a literate elite.”

Getting back to a more analytical focus, in a classic 1938 paper Louis Wirth defines a city as a place with: (1) a ‘large’ population; (2) in a ‘dense’ settlement; (3) more or less permanent; (4) with some social heterogeneity.  Of course this brings up a set of hard to answer questions, namely what’s "large?"  What’s "dense?"  What do we mean by "social heterogeneity?"

In my urban economics class, I suggest a quadrapite model of a city: (1) a city is a land and real estate market; (2) a city is a labor market and a collection of people; (3) a city is a collection of capital, both tangible and financial; and finally, (4) a city is also comprised of a selection of governments and institutions. 

"Above average density" and "where strangers meet" and the like get us started, but for some purposes are a little vague and abstract. For many purposes – data collection, legal matters, governance – we need very specific, to some extent arbitrary, definitions of the city.

When we speak of cities, then, we have to be clear whether we are discussing "the" city in a functional sense -- the way an urban economist things of "the city" -- or "a" city in a legal/political sense -- the way governments define cities with specific boundaries and governance structures.  Let us now focus on the latter.

Cities in the United States

In the U.S., cities are legally “creatures of states.”  The U.S. Constitution discusses the national government, and the states, extensively; cities and other local jurisdictions are never mentioned!
So each state defines its cities, towns, villages, etc.; and every state is different.

In some of its data collection, the Census Bureau works with these definitions;  among many other units of observation, Census tracks data on “places,” which can be incorporated, usually cities and villages.  Practices vary by state, but incorporated places can also be labeled boroughs or towns or municipalities; these can vary by size, and by the specific kinds of functions states delegate to them.  Places can also be unincorporated places; the Census refers to these as Census Designated Places, or CDPs.

A U.S. city or other incorporated place has received a charter from the state government, and will have elected officials.  Unincorporated places exist by tradition.  Nationally, there are about 19,000 incorporated places, and about 4,000 CDPs.

To recap, different states have different rules for designating cities.  These rules often include, but are not limited to, minimum population sizes in most states.  In the event, U.S. cities (as defined by the political-legal Census "place") range in size greatly from 8 million (New York) down to as few as single digit population in a few odd cases.

For more details, see Census web sites here and here.

Urban Areas

Closely related to the idea of a city is the idea of an urban area, of urbanization.  Merriam Webster, 2nd ed., defines urban as "of, or pertaining to cities."

Census defines "urban" a little differently than a "city;" urban areas are densely settled areas that are more fine grained, built up of densely settled census tracts and census blocks.  In a city like Madison, where some areas are still rural in character even though they are contained within the incorporated boundary, we can have a Census tract that is within the city but not counted as urban by Census.

Thus, in many respects, Census' definition of "urban areas" comes closer to a functional definition than does the legal definition of many U.S. cities.

I don't have a chart handy for Madison, but a demographic services firm called ProximityOne has posted a map for Lawrence, Kansas, using 2000 Census data and definitions:

The Lawrence city boundary in green; the urban urban area in yellow.  Obviously there is a lot of overlap, but clearly some parts of the incorporated city are outside the urban area; and some of the urban area is outside the city.

To sum up, and extend a bit, here is a summary of how Census defines "urban."   An urban area comprises (1) a densely settled core of census tracts and/or census blocks that meet minimum population density requirements (at least 500 people per square mile), along with:
(2) adjacent territory containing non-residential urban land uses, and (3) territory with low population density that links outlying densely settled territory with the densely settled core.

Furthermore, an urban area must encompass at least 2,500 people, at least 1,500 of which reside outside institutional group quarters.

Just to keep us on our toes, the Census Bureau identifies two types of urban areas: (1) Urbanized Areas (UAs) of 50,000 or more people; and (2) Urban Clusters (UCs) of at least 2,500 and less than 50,000 people.

“Rural” encompasses all population, housing, and territory not included within an urban area.

The figure shows the evolution of U.S. urban and rural population over time, since the first Census in 1790.  Two caveats attach to the figure.  First, the definition of "urban" and "rural" have changed over time, but the data are not revised to fit a single definition.  That accounts for some of the apparent blips in the data.

Second, the stacked area chart above gives us a look at the evolution of the levels of urban and rural population over time, but is very misleading with regard to growth rates.  To the untutored eye, it looks like U.S. population growth (especially urban growth) is accelerating, because the line is moving up at an increasing rate.  But growth rates are changes over levels, and as we move forward in time, both the change and the level are going up.  Eyeball the chart.  If you think it's showing faster growth in recent years, then you are a prime candidate for a future post on data transformations that will convince you that U.S. population growth is slowing down, in both the city and the countryside.

In the 2010 Census, about 250 million, or 81 percent, of the U.S. population resided in urban areas. About 60 million, or 19 percent, of the U.S. population resided in rural areas.

Because urban areas are denser, the fraction of U.S. land that's urbanized will be less than the fraction of population.  But it surprises many how little U.S. land is urbanized.  Separately, the U.S. Department of Agriculture estimates how much land area is urbanized.  In 2007, the last detailed accounting, about 25 million hectares (61 million acres), or about 3 percent of our 0.9 billion hectares (2.3 billion acres), was urbanized.  About another 2 percent comprised rural built up areas (e.g. farm buildings, rural housing and other real estate, and highways).

World Urbanization: A First Look

The figure above shows the urban population of the world, by decade.  Data come from the United Nations World Urbanization Prospects.

Today there are roughly 7.5 billion people spread over about 13 billion hectares (32 billion acres) of land. Of course much of this land is arid or otherwise inhospitable to settlement, but more on that another day.  Of those 7.5 billion people, about 4 billion live in cities/urban settlements, and 3.5 billion live in urban areas.

In 1950, just before I was added to the red bars, the world's urban population was only about 3/4 billion; that was only 30 percent of our total 2.5 billion population.

It's an auspicious time to study urbanization! Human history, at least that of homo sapiens, is currently thought to extend about 150,000 years, and some of us have lived in urban settlements for about ten millennia.  According to the best estimates – and these are rough numbers – in 2007 the red bar became bigger than the blue bar, and we very recently crossed over, for the first time, to a world where the majority of human population lives in cities.

Obviously we are unable to actually date the transition to majority urban as precisely as a given year, much less the date “May 23, 2007” announced, I presume tongue-in-cheek, by several U.S. sociologists a few years back.

Obviously the bar charts for 2020 through 2050 above are forecasts, subject to error. If these forecasts are correct -- and the one thing we know for sure about every numerical forecast is: it's wrong! -- by the time today's students are nearing career maturity, around 2050, about 2/3 of our 9 to 10 billion global population will live in cities.

The actual data up through 2010 are themselves subject to error, as they are built up from country estimates.  In addition to sampling errors, the UN's demographers use each country's own definition of "urban." Roughly, for the U.S, as noted above, our threshold for urban is a place of 2,500 or more.  As it happens, 2500 happens to be a common but not ubiquitous threshold for urban place in other countries. Country thresholds range from 1,000 to 10,000 and higher, although 2500 is the most common.   See the "Data Sources" page of World Urbanization Prospects for list of definitions by country as well as additional detail.

So far our brief discussion has focused on the levels of global urban and rural population.  The chart also shows annual growth rates for each decade.  In the 1950s, urban population was growing a bit over 3 percent per year, while urban population was growing about 1 percent; overall population growth was a little under 2 percent.  Today, urban population is growing about 2 percent, while rural population is flat, for a total global growth rate of about 1 percent. In several decades, the UN's forecast is that urban population growth will slow down to about 1 percent while rural population will start to decline.

Until recently, the UN and a number of other global projections suggested that population growth would level off and begin to decline sometime during this century.  More recent projections (see chart above, from Kunzig) suggest that population growth may continue, albeit at a declining rate, through the rest of this century.  

The forecast growth is concentrated in a relatively small group of the world's 200+ countries, mainly those that are large, with especially high fertility rates.  The UN World Population Prospects projects that half the world’s population growth will come from just nine countries; in order: India, Nigeria,Pakistan, Democratic Republic of the Congo, Ethiopia, United Republic of Tanzania, the U.S., Indonesia and Uganda.  

Note that the U.S. is the only "developed" country in the list; the U.S. has a much higher growth rate than most other developed countries, partly because of immigration, and partly because of higher fertility rates. (Interestingly, the higher U.S. fertility rate is in turn due in large part to immigration, since it's recent immigrants and their children who have the highest fertility rates within our borders).  U.S. population grows about 1 percent per year, close to the current global average; many other rich countries like France, Germany or Japan, are flat or declining.  Note also the absence of China in the short list; China is large, but has a modest rate of population growth, around 0.5 percent.

More to Come: Metropolitan Definitions

Another basic set of city-related definitions revolve around metropolitan areas.  These are collections of counties, that are economically connected to cities.  Metropolitan areas -- and related concepts, like micropolitan areas, "combined statistical areas," and the like -- are a big topic, so we will undertake a separate post to examine them.

If you can't wait -- and there's no reason why you should wait! -- see Frey et al. (2004) for a detailed discussion.

Reading for Life

Bevan, Robert. "What Makes a City a City - and Does It Really Matter Anyway?" The Guardian, May 8, 2014 2014.

Colton, Charles Caleb. Lacon: Or, Many Things in Few Words: Addressed to Those Who Think: Longman, Orme, Brown, Green, & Longmans, 1837.

Frey, William H, Jill H Wilson, Alan Berube, and Audrey Singer. "Tracking Metropolitan America into the 21st Century: A Field Guide to the New Metropolitan and Micropolitan Definitions." The Brookings Institution, 2004.

Frug, Gerald E. "The City as a Legal Concept." Harvard Law Review 93,  (1980): 1057-1154.

Glaeser, Edward L. Triumph of the City: How Our Greatest Invention Makes Us Richer, Smarter, Greener, Healthier, and Happier: Penguin, 2011.

Kunzig, Robert. "A World with 11 Billion People?  New Population Projections Shatter Earlier Estimates." National Geographic,  (2014).

Malpezzi, Stephen. "Urban Growth and Development at Six Scales: An Economist's View." In Global Urbanization, edited by Eugenie L. Birch and Susan M. Wachter. Philadelphia: University of Pennsylvania Press, 2011.

________. "Population Density: Some Facts and Some Predictions." Cityscape 15, no. 3 (2013): 183-201.

Nickerson, Cynthia, Robert Ebel, Allison Borchers, and Fernando Carriazo. Major Uses of Land in the United States, 2007: United States Department of Agriculture, Economic Research Service, 2011.

Sjoberg, Gideon. "The Origin and Evolution of Cities." Scientific American 213, no. 3 (1965): 55-63.

United Nations. World Urbanization Prospects: The 2014 Revision: UN Department of Economic Social Affairs. Population Division, 2014.

________. World Population Prospects: The 2015 Revision: UN Department of Economic Social Affairs. Population Division, 2015.

Wirth, Louis. "Urbanism as a Way of Life." American Journal of Sociology,  (1938): 1-24.

A Digression on (Brutalist) Architecture

I haven't ever had the opportunity to study architecture in a serious way.  But given my interests in housing, real estate, and urban development, it's not surprising I like to pick up a little knowledge about architecture here and there.

My interest is also derived partly from my family's business in tile, terrazzo and marble.  I was once, for brief periods, a productive member of society.  Though my father might have told you, not too terribly productive.

From time to time, in my urban economics and other courses, I like to take short digressions into architecture.  Real estate students sometimes come to the field with pre-existing interest in the design of the built environment; but undergrads in particular often find themselves choosing the major after taking a good intro class or hanging out with the Real Estate Club, and architecture is completely new to them. At the other extreme, some of our MBA students are practicing architects, some of whom have helped me learn a bit about the subject.  (Those former students are not responsible for my opinions or errors!)  Over time, everyone who works in real estate develops some kind of interest in architecture.  As an aside, UW-Madison has no architecture school or department; we sometimes collaborate with friends at UW-Milwaukee architecture.

My interest was piqued today by an article in the New York Times, a little puff piece on the architect Dominque Perrault.  The article itself wasn't terribly interesting, except this quote caught my eye:  "I follow socialistmodernism.com, which is a website that focuses on the preservation of 20th-century brutalism architecture."   Well!

The website Perrault referred to, as you'll see if you follow the link, is devoted to the preservation of architecture in Eastern and Central Europe dating from the communist era.  My interest -- a negative interest, I admit up front -- comes from a little work I've done, and a lot more done by colleagues, that makes me suspicious of the idea that a lot of communist era Brutalist architecture needs to be preserved.  If some of it is to be preserved, the twin challenges are to choose buildings judiciously, and to preserve them in a way that doesn't impose large costs on those who depend on a well-functioning stock of real estate.

Along these lines, shame on me for visiting Budapest and not taking the time to check out Memento Park, where socialist-realist statuary and other reminders of the communist era are there for perusal, and our edification.  (Thanks to my friend Alain Bertaud for the head's up about this park!)  Of course, it's easier to collect a bunch of statues and other art in a park than to round up a bunch of buildings.  Nevertheless, it's an idea...

But the real reason I react so strongly to socialist modernism/brutalism in architecture is that I spent 26 years next door to the most ironically named building of all time, UW-Madison's Humanities Building.  Designed by Chicago architect Harry Weese and completed in 1969, a decade ago it was renamed the George L. Mosse Humanities building in honor of a long-time UW history professor.

 Not only did I have to look at it, from time to time I've had to teach in it.  To paraphrase Dr Who, it's worse on the inside.

Interestingly, student lore from at least the 90s on has it that the built in in-accessibility was because the university wanted a "riot-proof" building.

So I have had to explain to generations of students how to riot.  (We have to teach so much stuff outside the syllabus these days!)

Specifically, students don't mass outside the building and charge it.  Such a charge is what Weese's design brilliantly impedes, as this slide shows:

You are students.  You are allowed inside.  The way to organize a building takeover is to enter in small groups. Then meet at the preordained spot at the agreed upon time.  Announce that you have taken over the building in the name of ______, and present your list of non-negotiable demands.

Which today would probably revolve around forcing professors to allow smartphone and laptop use in class. (If you don't know why many of us wrestle with banning them, you haven't taught much lately.)

Brutalism is an offshoot of modernist architecture.  Early modernists like Ludwig Mies van der Rohe eschewed adornment but used a lot of glass curtain walls, giving some of their work a lightness that the brutalists reacted against, preferring a heavy, monumental look.  The term is usually traced to Le Corbusier's use of raw concrete (béton brut, en français).

Wither Humanities?   (I'm talking about the building, not the field of study!) As UW re-develops the campus, several 60s era buildings, including Humanities, are slated to come down.  Not because of aesthetics, or even because they are functional failures -- Humanities has insufficient HVAC, classrooms where students can't all see the blackboard, and don't even ask about the inability to bring IT into a class.  Rather, the 60s era buildings were built on the cheap.  Their foundations are crumbling, the HVAC can't be maintained, and roofs are collapsing.  Given budget issues faced at UW, I'm not sure of the timetable, but Humanities is slated to come down; so here's a hot debate about this, with a number of preservationists arguing that UW students and faculty should just suck it up.  Of course as an economist, with limited aesthetic sense, my opinions should be appropriately discounted.  But my dim opinion of Humanities is shared by at least a few more knowledgeable colleagues, including architectural writer Brent Brolin.  Brent suggests that buildings worthy of preservation would be either the best of what was built in the past; or in some cases, examples of historic and significant townscapes.  Humanities fits neither criterion.

Of course I've had other run-ins with dysfunctional modernist buildings nominally temples to "functionalism."  I spent many years in Washington, and my fellow urban economist Tony Yezer (long ago, my PhD advisor at GWU), reminds me not to forget HUD's headquarters building, where I've spent some hours in interesting meetings; and other hours lost, trying to find the interesting meetings:

Here's the Robert C. Weaver building, above.  Designed by Marcel Breuer, it was completed in 1968.  It's part of the L'Enfant Plaza complex, itself worth a blog entry someday.


No need to fly back to Madison or take a train to DC to get my Brutalist fix.  Now that I live in the Boston area, I just hop on the D train to go straight to Boston's City Hall.  Gerhardt Kallman and Michael McKinnell have a lot to answer for:

Obviously I don't warm up easily to most Brutalist architecture, or some other Modernist buildings.  But the best Modernist architecure can be positively inspiring.  Edward Durrell Stone's Aon Building (Chicago), for example, or I.M. Pei's Hancock Tower (Boston), to give just two examples.  I can even name one Brutalist example by Weese that works well, in my opinion: the DC metro stations.    Weese designed the honeycombed vaults using "raw" concrete, and to my eye the results are functional, appropriate to the environment, and even beautiful.

There's much we could learn about the economics of architectural design.  One model for studies of the value of good design is a classic paper by Kerry Vandell and Jonathan Lane, "The Economics of Architecture and Urban Design," published in Real Estate Economics in 1989 (vol. 17, no. 2, pp. 235-60.)  A good addition to your "Reading for Life" list.

Housing in the Great Financial Crisis, the Great Recession, and their Aftermath

In case you just woke up from a long nap in the Kaatskills, circa 2007-9 the U.S. (and much of the rest of the world) experienced a severe financial crisis, and the worst recession since the 1930s.

Since those events, the U.S. has been in a long, but by all accounts, disappointingly slow economic expansion:

The Great Financial Crisis and the Great Recession are events economists and others will study and argue about for decades.  There is already a huge literature on these events, some of which I'll explore in a future "Reading for Life" post.  Recently, I abandoned prudence to add my own current thoughts regarding these events.

I wrote the paper Residential Real Estate In the U.S. Financial Crisis, the Great Recession, and their Aftermath, at the invitation of Charles Leung and Nan-Kuang Chen for a special issue of Taiwan Economic Review

What caused the crisis?  Like the Great Depression and other such watershed events, it is unlikely that there will ever by a simple, tidy set of agreed-upon explanations.  In my own class notes on the crisis, I present four slides listing 91 potential “causes,” some proximate and some deeper; some economic, some financial, some political, some sociological, some psychological.  Examples, in no particular order, and without endorsing or ranking any particular “cause” here: the rise of subprime lending, “too-big-to-fail” financial institutions, financial deregulation, poor underwriting practices, risky mortgage designs (e.g. option ARMs), the Community Reinvestment Act, perverse incentives in Fannie Mae and Freddie Mac (“Government Sponsored Enterprises”), perverse incentives among private investors, myopic expectations, adaptive expectations, a global savings glut, political resistance to appropriate financial policies, non-recourse mortgages, a widening distribution of income, financial economists who failed to understand the operation of housing markets, housing economists who failed to understand the risks building up among counterparties in ever-more complex housing based derivatives, fraud by lenders, fraud by borrowers… and so on.

Jazz master Miles Davis famously said “It’s not the note you play, it’s the notes you don’t play.” In this paper I focus on two causes:  increased leverage, and a boom and bust (some dare call it a bubble) in house prices.

The figure above shows one of many charts we could present demonstrating that individual borrowers increased leverage substantially in the run-up to the crisis.  Other data and research are presented that examine at the level of individual institutions (e.g. the investment banks that levered up 30 to 1 and even higher, meaning that even a 3 or 4 percent decline in their assets could drive them into insolvency; and the increases in systemic risk associated with ever more counter-party risk, and less transparency.

Asthe figure above shows, from 1975 to 1995, average U.S. prices grew at about 0.4 percent per annum (inflation adjusted). During the boom, 1996 through 2006, real prices grew by about 7 percent per annum.  But “every housing boom is followed by something else that starts with the letter ‘B,’” as long run analyses have repeatedly demonstrated.  The second recurring theme of the paper is the role played by housing prices in the crisis; and the reasons we saw such an unusual and unsustainable boom in the early 2000s.

Why focus on those two, house prices and leverage?  Whatever your current beliefs about many potential causes of the U.S. crisis – subprime, mistakes in securitization, Wall Street, the GSEs, fraud, macro policy mistakes, and on and on… suppose that as in a classical Greek play, some deus ex machina had imposed the following conditions: (a) all mortgagors were required to retain significant equity in their houses, while all mortgagees were required to limit their own institutional leverage; and (b) that house prices followed time paths qualitatively similar to the 1970s, 80s and early 90s, i.e. with moderate growth and volatility.  On the face of it, how could we have generated the 2007-9 crisis without high leverage and volatile housing prices?  Moderate leverage and stable underlying asset markets can help protect the financial system and the aggregate economy, even when we make mistakes in other government and private actions and policies.

What Are Those Millennials Up To?

I'm not trying to cause a big s-s-sensation
I'm just talkin' 'bout my g-g-g-generation
Pete Townshend

Everybody's talking about Millennials, Millennials, Millennials...  including me.

From time to time I write some short pieces for the Wisconsin Realtors Association.

For example, for several years I've been writing a short outlook piece for the January issues of the Wisconsin Real Estate Magazine.

Want to see my sage thoughts -- and at least a few howlers?  ("It's tough to make predictions, especially about the future," said noted econometrician and philosopher Lawrence Peter Berra.)

2010 Economic Outlook

2011 Economic Outlook

2012 Deja Vu All Over Again

2013 A Healing Market, Some Risks Remain

2014 Moving from "Meh" to "Wha?"

2015 Searching for Warren G. Harding

2016 In Fed Do We Trust?


Now WRA is starting a new feature, to appear several times per year, called "Insights."  Mike Theo of the WRA, Jim Wood of Wood Communications Group, and I recently prepared the first Insight feature, What REALTORS® Should Know About Millennials.

The largest population cohort ever is hitting the housing market – by the Census Bureau’s count, 83 million Millennials.  How will this play out? Millennials have or are about to reach prime first time homebuyer age.  So far this cohort’s home-buying, and other housing market activity, has been below par, by several past norms.  But there’s some evidence it may be catch-up time, as we explore in this Insight feature.

Chart(s) of the week: Crime -- Just How Bad Is It?

I’m still reeling from Donald Trump’s dystopian vision of America and the world we live in, as laid out in his GOP convention acceptance speech.  The theme of that speech, in a nutshell: America is going to hell, and only Donald Trump can save us.

Now, in case you think I'm concerned about the bleak nature of the speech because I'm a leftie: not so.  For the moment please provisionally entertain my assertion; I'll leave discussion of my own political leanings to another post, where you can learn more about my biases.

One theme of this post is cribbed from Daniel Patrick Moynihan:  "Everybody is entitled to his own opinion, but not his own facts."  In this post, I am inspired partly by The Donald's own call to "present the facts plainly and honestly."  We will see that, in fact, some of Trump's facts are correct, and some of his concerns have some foundation.  We will also see that even when he cites some correct statistics, his discussion is seriously incomplete, and often misleading.

I'm an Economist, not a Political Pundit; so Why This Post?

Why would an economist comment on politics?  I’ve long been interested in politics, including but not limited to their interaction with economics.  My first degree was in Political Science from La Salle University, where I studied U.S. government, foreign policy, international politics and history with Bob Courtney, Fred Foley, Michael Dillon, Ken Hill, Minna Weinstein, and my senior thesis advisor and mentor C. Richard Cleary, among others.  Graduate study in international affairs at GWU followed, with political scientists Burt Sapin and Stephen Shaffer among my teachers.  At Wisconsin I had too many outstanding friends and colleagues in political science and related areas to list here, though I’d be remiss if I didn’t mention Karen Bogenschneder, who involved me in her Family Impact Seminars for the Wisconsin State Legislator; Don Kettl, who recruited me for Governor Tommy Thompson's Blue Ribbon Commission on State and Local Partnerships.

In this post I just want to lay out a few charts that have a bearing on some of the assertions in Trump’s speech.  Specifically, how bad are things?  In future posts we’ll look briefly at incomes, poverty, the state of U.S. manufacturing, trade, and other kinds of violence, including terrorism; all things Trump brought into his speech; these are things that I’ve been concerned about, too.  In those future posts, I’ll also add a few items that Trump did not mention, e.g. life expectancy.

Each chart we present is one simple look at an important and complex topic, certainly worthy of a separate, more detailed blog post in the future.  But for now, let’s just get a few facts about crime, specifically homicides, on the table.

(As discussed briefly at the end of this post, we're going to follow common usage and use "homicide" and "murder" as synonyms, although the homicide data we use includes non-negligent manslaughter, which is technically not a murder.)

Why focus on homicides?  One reason is that depriving someone of their life is such a heinous crime. Another is that they have such large externalities, especially some kinds of murders, like those of children and of police officers.  "Externality" is economist-speak for spillovers, good or bad.  That is, externalities are things that affect not only those directly involved, but also families and friends, neighbors, and even society at large.  Any significant crime is likely to have spillover costs, but murders surely have especially larger spillovers.

Another aspect of homicides is that they are, and have been throughout our history, tied up in our discussion of many other social issues, including those of race and poverty.  Some unlawful deaths are classified as "terrorism," and these have special and very large negative externalities.

Examining statistics on homicide or any other serious crime can seem bloodless and unfeeling.  Reducing the murder rate is a good thing, for sure, but a low murder rate may be cold comfort to remaining individual victims and their families in a "low rate" environment.

One reason to study homicides is that, because they are so heinous, they are measured better, and more consistently over time and across jurisdictions, than other kinds of crimes.  Of course, "measured better and more consistently" doesn't mean measured perfectly.  Murders are also usually found to be correlated with other kinds of violent crime, including those that are less well measured.  So murders are of interest for their own sake, but also give us a start at thinking about other kinds of crimes.

In this post, having noted these shortcomings, we'll focus mostly on the numbers.  Discussion of externalities, of terrorism, of other kinds of crime will wait for another day.

I’m motivated by Donald Trump's comments in this post, but these are important issues whatever your political leanings, in an election year, or not.  In future posts, I certainly won’t let his opponent Hillary Clinton off the hook.  And I’m sure to throw in some charts relevant to pronouncements by Bernie Sanders, Paul Ryan, and others on the way.

Let’s get started!

Early in Trump's speech, he stated:

"Homicides last year increased by 17 percent in America's fifty largest cities. That's the largest increase in 25 years.In our nation's capital, killings have risen by 50 percent. They are up nearly 60% in nearby Baltimore.In the President's hometown of Chicago, more than 2,000 people have been the victims of shootings this year alone.And more than 4,000 have been killed in the Chicago area since he took office."

His grade, if Trump had turned in such a report in my urban economics course?  Incomplete, and misleadingly so.  Revise and resubmit, so I can grade a proper answer.

Recent Trends in Homicides

I'm giving Trump a big fat "I" even though the data Trump cites are consistent with preliminary FBI crime reports for 2014 and 2015.  As has been widely reported, Trump's speech appears to draw on a Washington Post Wonkblog story by Max Ehrenfreund and Denise Lu that reports preliminary homicide data for 2015 for 50 large cities. The data do, indeed show a disturbingly large increase in murders across these cities.

The basic data we use to analyze murder rates comes from the FBI's Uniform Crime Reporting data. The majority of homicides are reported to state and local law enforcement, not to federal authorities directly, so the more complete data come out with a lag.  As of this writing, 2014 data are the most recent complete data, which is why the preliminary 50 cities data for 2015 have been widely reported.  All in, these 50 cities (n.b. cities, not metropolitan areas!) contain about 50 million people, or about 15 percent of the U.S. population.  The data are not nationally representative; among other issues, murder rates tend to be higher in cities than in suburbs; rural murder rates are usually somewhere in between.  Nevertheless, it's reasonable to start with this preliminary data; certainly they are of intense interest to the people that live there, and they may presage qualitative results that we'll see in the later, more complete data.

In the event, Ehrenfreund and Lu's report is well worth careful reading, including their interactive graphics.  Pull up their article here, in a separate browser window, and look again at their charts along with this commentary.  I'll insert some screenshots of the charts here, but be sure to go to their site; you lose the interactive feature with these screenshots!

Their first chart (screenshot above) is a simple bar chart of changes in homicide rates.  Of their 50 cities, 36 show an increase in homicides between 2014 and 2015; and 13 have increases over 40 percent.  The top five percentage increases were in Cleveland, Nashville, Milwaukee, Denver, and Oklahoma City. Thirteen cities had fewer homicides in 2015 than in 2014; the largest declines were in Boston, Austin, El Paso, Fresno, and Tucson. One city, Mesa, Arizona, had roughly no change.

Rates of change are important, but they only tell part of the story.  Ehrenfreund and Lu's second chart is complex but extremely informative and interesting one.  That chart, screenshot with link above, plots the murder rate (murders per 100,000 people) annually for each of the 50 cities, from 1985 to 2015.  Thus, while Cleveland has the increase in murders from 2014 to 2015 (90%!), and Baltimore ranks "only" seventh, albeit with a still distressing increase of 59%.  Both cities have above average murder rates as well; but here the relative ranking is reversed.  Cleveland's average murder rate came in at 16 per 100,000 in 2014, and 31 per 100,000 in 2015.  That's bad, but Baltimore is even worse; Charm City's murder rate rose from 35 per 100,000 to 53.  For comparison, Ehrenfreund and Lu calculate the average murder rate over the 50 cities 9.3 to 10.8; an increase of about 16 percent.

Their third chart, above, looks at the average yearly percentage change in the murder rate in the 50 large cities.  It puts the large 9.3% increase from 2014 to 2015 in perspective, i.e. it comes after years of mainly declines; and those declines, in turn, came after some large increases in the late 1980s.  We'll have more to say about these trends, too, below.

Ehrenfreund and Lu's UCR Data Transformed

A recurring theme in my teaching is that, when looking at consequential data, it's important to chart it and otherwise analyze it correctly; and in particular to remember that there are almost always several alternative ways to present even basic charts.  Ehrenfreund and Lu present three different looks at the data, and I congratulate them for their data work.  I'm particularly impressed at their second chart, which you should examine carefully, in its full interactive form at their site.

After you examine their charts, come back to this blog and we'll extend their work a little further, starting here.

Our first chart is a simple one, that plots the 2015 homicide rates for the 50 cities against the 2014 rates.  The area of each circle is proportional to each city's population; the circles, and the (admittedly hard to read in some cases) city names are centered on the data points.  The diagonal line shows where 2015 rates equal 2014 rates, so crime rates are getting worse in cities that lie above the line.

Here again Cleveland and Baltimore stand out.  But we also note that the two deadliest cities, New Orleans and Detroit, haven't changed much, in percentage terms. (Not that zero change is good -- we want to see some declines!)

Taken as a whole, this chart shows that there were big changes in a few deadly cities (cities with murder rates over 10 per 100,000), especially Baltimore and Cleveland, but also Milwaukee and Washington DC and Kansas City.  Among the safer cities, Minneapolis, Nashville, Oklahoma City, Omaha saw significant increases.  Boston stands out among the safer cities that became safer still.

Let's look at New Orleans again.  It's growth in murder rates is about 9.3 percent, which means it's average for the 50 cities.  But that growth rate, applied to a higher level of murders, means its murder rate went up by about 3.7 per 100,000.  A similar increase in murder rates in safer cities like Austin or Raleigh would have meant the murder rate roughly doubled!  Put another way, a modest (though still undesirable) increase in murders in safer cities translates into a larger percentage increase than we'd calculate for a more deadly city.  The point is not that growth rates are irrelevant; rather, it's that we should carefully examine both levels and rates of change.  Let's do that next!

Our second chart uses the same basic data, but another transformation.  This time, we plot the 2014-2015 percentage change against the starting point.  Here we get a clearer look at the crime growth rates of the safer cities; Austin and El Paso and Fresno have noticeable percentage declines as well as the aforementioned Boston.  Some of the safer cities, Nashville, Denver, Oklahoma City, Minneapolis and Long Beach, have some large percentage increases, albeit over a small base.  Again, multiple looks at the data with well-chosen transformations tells us more about what's going on.

Decades of Data Tells a Different Story than Two Years of Data

Preliminary data for 50 cities may be warning us of crime increases in other places, and in future years; or it may not.  Let's look at longer patterns, including but not limited to the 29 years of data presented in Ehrenfreund and Lu that Trump did NOT mention in his address, that we can glean from their second and third figures.  Their second figure, in particular, shows that the recent 50 city increase in murder rates, from a 2014 average of 9.3, to a 2015 average of 10.8, comes after a peak of 27 in 1991; in 1985, their starting point, the 50 city average murder rate was 19.4 per 100,000.  I'm concerned about the recent increase in preliminary data, but we're not back to the high crime 1980s and 90s, at least not yet!

Let's look at this city by city.  I pulled the city murder rates for a few years later, 1993 (average of 25.6), and repeated my first plot from above, but this time used the 1993 homicide rates.  A few cities -- Las Vegas, Milwaukee, Baltimore -- have current murder rates a bit above their 1993 rates; most have fallen, even after the last year's increase. As bad as New Orleans' current murder rate is, it's half the rate they experienced in 1993; DC's improvement is even more striking, though much remains to be done.  Moving away from the extremes of the data, cities including New York, Los Angeles, in fact the great majority of cities are far safer now than they were two decades or so ago.

A Century of Homicide Data -- and Some Related Policy Debates

As noted above, the latest comprehensive murder data we have as of this writing (and the conventions) stops at 2014.  Statistics on murders in the United States are available back to 1900.  Of course, older data, before the modern UCR system was put in place in the 1930s, should be treated with some caution.

Our chart shows some fascinating patterns. I'm not sure what to make of the low murder rates circa 1900; but there is a lot of anecdotal evidence as well as scholarship that suggests murders (and other crimes) increased substantially during Prohibition.  Was the end of Prohibition the sole reason for the post 1933 decline?  Hmmm.

Maybe the end of Prohibition had a lot to do with the 1933 to circa 1960 decline.  But what caused the run back up in the 1960s to a new peak in 1974?  What caused the volatility from that era until the early 1990s?  And, if we can unpack those changes, what might we expect for the future?

Geek Alert: Two Paragraphs on Properties of Time Series!

First, let me state the obvious.  No simple "trend forecasting" is going to tell us much about murder rates.  A time series of data that has a constant mean and variance (among a few other properties) is called a "stationary" series. A stationary series that's "mean reverting" can be forecast by studying how fast we get back to that constant mean if something pushes us away temporarily.  Recognizing that a "trend" is just a mean that is shifting in a very predictable manner, we can also forecast a series that's "trend stationary."

I haven't run any formal tests, but my eyeballs tell me that murder rates are not likely mean reverting, or trend reverting; that the variances aren't constant over time; and that it's not going to be easy to foreast murder rates with some simple trend analysis.  If I had to bet, I'd bet murder rates turn out to be a "random walk," a series with no memory.  Like a drunkard's walk, it's going to be hard to forecast.

End of Geek Alert; Now a Wonk Alert!

How can we explain the variation in murder rates (which, by the way, are correlated with other violent crime rates)?  In particular, why have homicides fallen substantially over the past two decades?  If we can understand these patterns better, can we gain some insight into whether the apparent increase in crime in a number of large cities over the past year is a blip in the data, or a harbinger of other increases?  Even better, can understanding determinants of homicide rates help us reduce it?

The short answer is, much rigorous research on homicide rates, and other crime, remains to be done. My reading of the literature, still in process as of this writing, can be briefly summarized as follows.  Overall, there are no obvious silver bullets.  And a number of contentious points are hotly debated.  Candidate explanations for the post-1993 decline include, but are not limited to:

• Demographic shifts;
• Changes in economic opportunity, unemployment rates;
• Higher rates of incarceration;
• Improved policing;
• Changes in the size and organization of drug markets;
• The availability of firearms;
• Increased immigration;
• Declining rates of births of unwanted children;
• Reduction in childhood exposure to lead;
• Cultural and institutional changes;
• Housing conditions and affordability.

Selected surveys of the relevant literature can be found below.  A future post will discuss some of the details of research on these issues.

So: How Bad Is Crime? And What Can We Do About It?

Back to the question we started with.  While there is some data behind Trump's assertion of rising crime rates, the data are highly selective and preliminary.  The recent increase in murder rates for a single year in a number of large cities is troubling.  But our look at a fuller dataset, including more places and longer time periods, tells us the increase comes in the context of twenty five years of surprisingly steady declines in murder and other crime rates.  Overall, based on these data, we're a lot safer than we've been for much of my lifetime.

My students are familiar with "Occam's Razor," the principle by which a simple theory that fits the facts is usually preferred to a complicated theory that also fits.  But what about the facts themselves?  Nobel-prize winning biologist Sydney Brenner is credited with coining the phrase "Occam's Broom," a process by which inconvenient facts are swept under the carpet.  Another term in common usage is "cherry picking the data."  We'll run into this practice a lot, often among pundits and politicians, and (sadly) sometimes among shoddy academics who don't uphold normal research standards.

Whether or not the preliminary 2015 data are one-off, or harbinger of some change in trend, nobody is, or should be, satisfied with a national murder rate of 4 or 5 per 100,000, just because it used to be 10.  Nobody in Detroit or Baltimore or New Orleans or Cleveland or DC should be satisfied with murder rates of 30 to 50 per 100,000 just because we've had some cities hit 80 murders per 100,000 in the past.

So what do we do about it?  As conservative columnist Charlie Sykes ruminated after Trump's acceptance speech, "on day one, he ends crime and violence; you sort of wonder how you accomplish some of it."  That's not much of a plan.

There are ways forward.  For example, a number of serious policy proposals regarding improved policing and criminal justice reform are under discussion (although political progress will likely now be stalled until after the election).  But it's hard to find any mention of these, or other specific proposals that empirical evidence suggests would reduce crime, in Trump's vague pronouncements on the subject..

So, what should we do?  Despite the length of this post, there's a lot more to be said in future posts about what research by economists, criminologists and others have taught us about crime; and about other aspects of safety and security, including terrorism, and natural disasters.  More to come!

A Few Notes on Data and Definitions

In this blog I follow common practice and use "homicide" and "murder" as synonyms.  In fact, the FBI Uniform Crime Report homicide data includes both murders, and non-negligent manslaughter.

The FBI does not classify some unlawful deaths as murders or homicides. Notably, the 2,996 deaths on September 11, 2001 (New York City; the Pentagon; Shanksville, Pa.) were classified as deaths from terrorism, and not included in murder statistics.

On the other hand, the 168 deaths on April 19, 1995, in Oklahoma City from the bombing of the Alfred P. Murrah Federal Building were included in homicide statistics.  See FBI Terrorism Reports; we'll discuss these in a future post.

My charts make use of the data from Max Ehrenfreund and Denise Lu's Wonkblog post.  They discuss the data in some detail at the end of their blog post, I recommend that you read that section carefully.  I didn't find a table or spreadsheet at the site, so I copied down the 1985, 1993, 2014 and 2015 homicide rates from their second chart.  (It's a nicely interactive chart, as you drag the cursor over the picture it pulls up the city, year and value of the variable).  I also copied down the percentage change in murder rates 2014 to 2015 from their first chart.  I obtained Census data for 2014 population as well.  My spreadsheet containing this data, and the three charts posted above can be downloaded here.

For Excel freaks:  I'm using Excel 2010, which does not do true data labels; so I have a VBA macro that labels the points with the city name.  If you are unfamiliar with VBA, see my teaching materials on Excel and VBA here. 

Reading for Life

Barker, Vanessa. "Explaining the Great American Crime Decline: A Review of Blumstein and Wallman, Goldberger and Rosenfeld, and Zimring." Law & Social Inquiry 35, no. 2 (2010): 489-516.

Blumstein, Alfred, Frederick P Rivara, and Richard Rosenfeld. "The Rise and Decline of Homicide-and Why." Annual review of public health 21, no. 1 (2000): 505-41.

Blumstein, Alfred, and Joel Wallman. The Crime Drop in America. Cambridge University Press, 2006.

Goldberger, Arthur S, and Richard Rosenfeld, eds. Understanding Crime Trends: Workshop Report, Washington, Dc: The National Academies Press, 2008.
Roeder, Oliver K, Lauren-Brooke Eisen, and Julia Bowling. "What Caused the Crime Decline?": New York University, Brennan Center for Justice, 2015.

Yezer, Anthony M. Economics of Crime and Enforcement. ME Sharpe, 2013.

Zimring, Franklin E. The Great American Crime Decline. Oxford University Press, USA, 2007.

A Little Graaskamp Center History

When I arrived at Wisconsin in 1990, two years after Jim Graaskamp's death, Wisconsin's Center for Urban Land Economics (CULER) lay fallow after the active years under Richard Ratcliff and Richard Andrews.  CULER, of course, later became the James A. Graaskamp Center for Real Estate.

As detailed in a previous post, Kerry Vandell arrived in 1989 to rebuild the program, followed in 1990 by myself, Jim Shilling and Richard Green.  Kerry decided to re-constitute the Center, with help from Richard Green and Rod Matthews.  Other supporters, including Bill Malkasian and Mike Theo and their Wisconsin Realtors Association, and state legislator David Clarenbach, stepped up.

In 1992, Governor Tommy Thompson cut a ceremonial ribbon to re-open the Center.  Pictured, left to right:  Jim Shilling, Governor Thompson, Jean Davis (Jim Graaskamp's life and professional partner), Marjorie Tiefenthaler (who donated a major chair in honor of her husband Lorin and herself), myself (pre-gray hair), Kerry Vandell, and Richard Green.


Here's a little tidbit.  Governor Thompson arrived early that day.  All by himself, no entourage whatsoever.

For whatever reason the only person around with an open door was me.

If I may channel what I'm sure he was thinking:  "I'm too early, how do I not waste this downtime?  Aha, a constituent!  A voter!"

So he popped in, put out his hand and said, "Hi, I'm Tommy Thompson."  We had the nicest chat for 10 minutes or so until other folks showed up.

Something that would never happen in 2016, I think.

Most Inspirational CEO: Mike Brennan, of Brennan Investment Group, and Graaskamp Center Executive Director

Real estate is well known as a "people business;" that's true for the business itself, as well as for real estate research and real estate education.

Over the past weekend I received some good news about friends in real estate, and some sad news.

First, the good news!

Real Estate Forum has just come out with a survey of the best CEOs in the real estate industry.  Based on their survey results, my friend and colleague Mike Brennan was named "Most Inspirational."

As Real Estate Forum notes,“true leaders are defined not only how they perform, but even more so by the way their people view them.”  In the survey, Brennan's employees used words like “caring,” “kind,” “committed,” “nurturing,” and above all “inspirational” to describe Mike.

Mike is co-founder, chairman, and managing principal of Brennan Investment Group, which focuses on industrial real estate.  I was happy to meet Mike through another one of his activities: in 2010, he joined us as Executive Director of the James A. Graaskamp Center for Real Estate, when I was Professor and Department Chair.  In our time together at Wisconsin, he has succeeded in moving our Center ahead, not just in the usual metrics -- Board Members recruited, funds raised, and so on -- but serves as a first class role model to our students, and with his deep and broad business experience, Mike provides a great complement to the classroom experience with academics like myself.  Among other specific undertakings, Mike has partnered with my friend Tim Riddiough to teach our acclaimed Applied Real Estate Investment Track (AREIT).  AREIT students actively manage a $1MM REIT portfolio.  I've noticed that real money concentrates the mind!

Another of Mike's many initiatives has been his championing of the Graaskamp Center Innovator Award.  As he points out at the website, "A rich history cannot be established without continuous improvement in ideas and in practice."

An academic's highest praise is this: "I learned a lot from that (paper, conference, person)."  For six years, I've learned a lot from Mike Brennan, both about real estate, and about even more important things.  I look forward to years more of the same.  Congratulations, Michael!

Credit

Photo by Steve Becker