Remembering Jim Curtis

James J. Curtis III passed away at the end of June 2019, after a full but all-to-short life.  When I arrived at the University of Wisconsin's Real Estate Program in 1990, Jim was one of the Graaskamp-era alums who greeted me and my new colleagues Kerry Vandell, Jim Shilling and Richard Green.  Over the years I relied a lot on Jim's advice, which he gave freely, especially when I took on roles as Department Chair and Center Director.  He supported UW Real Estate -- and many other institutions, including the Urban Land Institute -- unstintingly.  Some of his support was financial, much of that was on the QT, but for someone with so many irons in the fire, I was always most impressed with Jim's commitment of his most precious resource, his time.  If I sent him a draft strategy document, it invariably returned with pages of detailed and invaluable comments.  If anyone asked him to come speak to a class or a real estate club meeting, he was there.

In my favorite Bond movie, Skyfall, another James is asked to provide some word associations.  Say the word "Curtis" to me and the first word that comes to mind is "passion."  Other words follow, including "commitment," "integrity," and "values."

Like so many, I was shocked to hear about Jim's health problems.  I sent a letter to Jim in February 2019.  Later in the year I was in the Bay area, and despite his illness Jim and his wife Melanie Duke were kind enough to invite me to their home where we had an hour together, an hour I remember and treasure.

Here are some edited selections from the letter, suitably transformed, e.g. I now refer to Jim in the third person.  I’ve extended the remarks in a few places, too.

By the way, over three decades, while everyone around me called him “Curtis,” I called him “Jim.”  Even his obituaries mention the fact that most called him Curtis.  There are a lot of Jims that have played important roles in the program, not limited to Curtis and Graaskamp; and I’ve got a brother by that name.  As I did for 30 years, in this note and elsewhere, I’ll continue to stick to Jim.

I was, as you’d imagine, shocked and saddened when I first heard about Jim’s health. I know ALS is a difficult disease and the outlook is never good.  Ron Shaffer, a friend of mine in Applied Economics, was dealt the same lousy cards some years ago. Ron was a leader in community economics.  When Jim Curtis and I had our conversation a few months after the letter, it turned out their paths had not crossed, but I’m sure Jim Graaskamp knew Ron and his work. 

Ron taught me a little bit about community economics, but he taught me some deeper lessons throughout his illness.  Ron stayed active as long as he could, intellectually and to the extent he could, physically.  Jim G. was not the only “materials handling problem” to face Wisconsin winters in a wheelchair!  I asked Ron once how he could handle his situation with a mostly positive outlook.  His answer was something along these lines.  “I decided that I could spend my days doing my best to treat people well and make them glad I was still around.  Or I could be a pain in the ass and make them think the reverse.” Ron chose the former path, as did my illustrious predecessor and Jim’s mentor.

I wrote Jim to express my thanks for his friendship and guidance over the years – even if sometimes I might have paid much more attention to the guidance part!

I have a vivid memory of our first meeting in Fall 1990 at a picnic table after some event or other involving alumni. To be honest at first I thought Jim had been drinking a bit. My mistake.  Before long I realized that it was rather a combination of deep nonlinear thinking and an awful lot of passion, about real estate and especially about our program.

I had never been to Wisconsin before 1990, and I never knew Graaskamp personally, though of course I met many others who played important roles in the University and in our program.  Over the years I developed a strong attachment to the program, one that went beyond the normal employment contract. That was some combination of deep connection to probably the greatest real estate faculty ever assembled over time, Kerry Vandell, Jim Shilling, Richard Green, Tim Riddiough, Morris Davis, Rod Matthews … well,  the list is long.  Staff at all levels: Sharon McCabe, Phyllis Miller, Lee Gottschalk, too many to list once again.  And great colleagues outside the Department, like Don Hausch, Joan Schmit, Dan Bromley, Antonio Mello, again far too many to list here. Mike Brennan.  See  the T&I paper for more names and details.

So the thing that attracted me to Wisconsin wasn’t Graaskamp, or the program’s history – I’d heard a little bit about it but not so much. It was that I knew Kerry and Jim for a number of years from conferences and other interactions over research. I had a great job at the World Bank and I had the equivalent of tenure there. But I was coming up on a decade at the Bank after five years at the Urban Institute, and I knew that if I stayed a few more years I would be a lifer. Which would’ve been fine, but I thought it was a good time to test out a different path since I always had an academic bent. When I saw that Kerry and Jim were rebuilding a program at a great university, and that they wanted me to join, I knew that was something I couldn’t pass up. Of course, having Richard join us shortly after I signed on, and finding Rod Matthews upon arrival, that was icing on the cake.

We were also lucky to have a group of committed PhD students that helped us a lot during the transition.  In my own case, Mark Eppli, Dan Knox, and Tony Ciochetti served as my TAs out of the box, and they and others (Elaine Worzala , Tim Riddiough, Chuck Carter) took on a lot of extra work during the transition.

I was more or less prepared for, and looked forward to, great academic colleagues and a great university. I expected, and found, great students. But nothing had prepared me for the intensity of alumni commitment to the program, to its place in the commercial real estate firmament, and of course to its deep history reaching back to the very establishment of real estate as an academic discipline a century ago.

Another part of my education in 1990 was my own first year’s teaching. In addition to urban economics (for which I was pretty well prepared intellectually) I dove into the deep end of the pool with 300 students in Real Estate Process in room B-10; a course in Local Public Finance; and Richard Andrews’ course in “History and Theory of Urban Land Economics.” The latter course was particularly important to my development. We dropped the course from the curriculum given other teaching needs after one semester, but teaching it that one time got me to delve into writings by Ely, Ratcliff, Andrews, and Graaskamp among others. Adam Smith, David Ricardo and other usual suspects were also on that reading list. Those readings were put to good use later when preparing the teaching note that morphed into the Tradition & Innovation paper. 

Jim became a huge fan of the T&I paper (as did Mike Brennan, I think a number of others).  Jim appreciated how it carried on the Graaskampian tradition, but he also emphasized how it was important, in his opinion, that the paper put the Graaskamp era and his contributions into a larger perspective, of the world that Richard Ely and Richard Ratcliff and Richard Andrews also played such a huge role in.

Alumni engagement was one of the things that impressed me early on, as I’ve already indicated.  It wasn’t just talk and advice, valuable as those can be.  Jim knew better than I the role alums played in keeping the real estate program alive after 1988, and getting Kerry and the rest of us on board.  And remember what the markets were like during my first few years.  More than one alum would tell me how their business was frankly struggling, then pull out a checkbook and provide some funds for scholarships or whatever was needed.  Beyond financial contributions, everyone was generous with their time. Any time we were looking for help on case study materials, outside speakers, whatever was needed, Jim and his friends, among many others, came through.

As years passed and I filled in some of my gaps in my knowledge of real estate, I never sought leadership positions, but I did try to step up when I saw it was needed. Much of the credit for any success I had along those lines has to be shared with colleagues, both faculty and staff, and in no small part people like Jim. 

Jim’s contributions stood out from the beginning.  An academic’s highest praise is, “I learned a lot from that –.” (Paper, presentation, colleague, whatever).  I learned a lot from Jim.

I tried to pass to students and others some of what I learned from Jim, and so many other real estate professionals like Craig Manske, Jim Smith, Jim Haft, Jill Hatton, Kelley Smith, Mike Arneson, Mike Komppa, Paul Gilbert, Fred Petri, Dianne Orbison, Wendell Kurtz… too many to list fully here. Many aren’t alums of course, here I’d have to put Mike Brennan at the top but Fred Cooper, Brad Olsen, E.J. Plesko, so many others contributed to my education.

When I think about Jim’s contributions I could list many specifics – his contributions to our strategic plan and fundraising, AREIT, helping me sharpen my reunion presentations.  But the one that always comes to mind first is a particular half hour of our day at House of Blues in Chicago when about 10 of us – senior faculty, a few key alums and other professionals, including, of course, Jim – hammered out a framework for communicating the values of the Wisconsin Real Estate Program to future students and many other friends of the program.  It wasn’t just the list itself, though that was important. It was also that Jim helped me see just how important values were as part of our education, and that I could and would have to ramp up that part of the curriculum, even if it did not come naturally to me at first.

A few pages about those values can be found in the T&I paper.  Here’s the briefest summary of the values that Jim and I and our colleagues drafted years ago:

 

There’s a lot that can be said about each of these; and effective teaching requires that we revisit each of them from time to time during a semester and during a program.  Here's a little more elaboration in another blog post.

It’s very important to note that this is a bottom-up list.  This is not Steve’s or Jim’s list of our personal favorites, at least we try not to make it that.  We are trying to report the values we see brought up repeatedly within the program, especially in what happens after somebody graduates.

It’s also important to note that the list is aspirational.  We are all human, and none of us measure up all the time to all our values.  But we do our best.

One important value was later added, thanks to another great friend of the program, David Shulman.  David reminds us of the importance of curiosity.

Jim leaves quite a legacy, and of course I only know about some of that legacy.  I told Jim even he only knows about some of his own legacy.  Jim Curtis’ passion, his honesty, his love for the program, his focus on the importance of values, all made a difference in how I and many others think about real estate, and beyond. For this and more, I’m in Jim’s debt.

Finally, why not hear from the man himself.  Here's a short interview clip, courtesy of ULI; and here's a longer version.

Economic Impact of COVID-19 on the Housing Market (Second Draft)

 

For someone often labeled a "housing economist," I've been slow to post much specifically on this topic (though there are plenty of housing-related slides in my larger PowerPoint library on the coronavirus.)

There's a lot to unpack, lots of data to collect and analyze.  And I'd be deceiving you if I didn't admit I have been surprised at the strength of some (not all!) housing markets.

Housing and the pandemic:  I'm working on it.  It's handy to have some commitments that help to focus the mind, provide some deadlines.

Recently I presented some of my preliminary work to the Collateral Risk Network, thanks to a kind invitation from Joan Trice and colleagues.  I presented this version in mid-February.

Now I'm excited to present an extended version of that material to the urban economics course I taught for years at the University of Wisconsin.  The course is now in the more-than-capable hands of my friend and colleague Yongheng Deng.  

Among other improvements to the presentation, I've added discussion of the "Four Quadrant Model" of real estate stocks and flows developed by Denise DiPasquale and Bill Wheaton, and sketched out how students might apply that model to pandemic-affected rental housing markets.

Here is the PowerPoint deck for the presentation to our urban economics students.  There are notes below many of the slides that provide explanation and commentary.

If you're checking these out on a phone, you might have better luck with the pdf version of the slides.  But the pdf does not include the notes, so I recommend using the PowerPoint version if your device can handle it!

These presentations included some exploratory data analysis of Federal Housing Finance Administration metropolitan-level house price indexes, and coronavirus data from Johns Hopkins.  Those data can be downloaded in spreadsheet form here.

Still a work in progress -- comments and corrections always welcome!

Thoughts on the Post-storm Power Shortages in Texas

 

Exhibit 1

Photo from MSNBC

In mid February 2021,Texas (and several other states) are still reeling after a terrible and unusual (but far from unprecedented) winter storm.

This storm came while I was organizing materials for The Future of Real Estate. FoRE, as we abbreviate it, is a project begun in 2018 with my colleagues Morris Davis and Julia Coronado; I have worked on it off and on since then.  As the storm hit I was preparing some material on infrastructure, focusing for the moment on energy.

Given the connection between my recent reading and writing on FoRE and recent events in Texas and elsewhere, I decided to take a time out and do this post.

FoRE and my own interests in general tend to focus long run. But sometimes it’s important to look at the short run, obviously including emergencies and disasters. Some of my most “learnable moments” spent with my students at Wisconsin came when students chose to do projects on disasters such as the Fukushima nuclear reactor, the earthquake in Haiti, and Hurricane Katrina. Disasters and emergencies (including the current pandemic) are obviously important in their own right.  But they can also clarify weaknesses and issues that affect cities and real estate markets and infrastructure in the long run as well.

Some Basics

Exhibit 2

Photo from Teen Vogue

As I write this on February 21, much of Texas has electricity again, but some 14 million Texans are still waiting for the return of safe water supply.

Exhibit 3

Graphic from the New York Times

The February 2021 storm certainly was not limited to Texas; severe cold and often snow struck much of the central U.S., from Minnesota and the Dakotas down through Texas and Oklahoma and Louisiana, as Exhibit 3 shows. As the storm hit in mid-February about 150 million people or a bit less than half the U.S. population was under storm warning. The first day of the storm Austin recorded a temperature of 8° F and about 7 inches of snow. That’s weather that Boston or Milwaukee would shrug off, but it was the largest recorded snowfall in Austin in 55 years. 

The mid-February shortages are unusual and extreme but not unprecedented and like the COVID pandemic, no black swan; perfectly anticipatable except for the timing. Texas has been through dress rehearsals for this, e.g. in the “Groundhog Day” storm of 2011, but failed to heed the warnings. And if you think that single digit temperatures like the ones recorded in Austin wreak havoc remember, that Texas has had much colder episodes in the past including the 1994 record cold snap in West Texas that reached 20°F below zero. 

Exhibit 4

Graphic by Statista

Exhibit 4 shows that the number of  Texas customers disconnected at the peak of the blackout, over 4 million, dwarfed the number reported from other states.  The graphic above, while correct, is a bit misleading because Texas' population also dwarfs the other states listed.

The 4.3 million could be compared to Texas' population of 29 million, while neighboring Oklahoma's 200K compares to a population of 4 million.

Assuming all the disconnects are retail customers, and a household size of 2, at the peak about 30 percent of Texas' population was off the grid, while Oklahoma's ballpark estimate comes in at about 10 percent.  There's a huge difference, though: many, at first most, of Texas outages continued for days, while most of Oklahoma's were back online in a reasonable time.  Why?  To some extent because Oklahoma had winterized more effectively, but even more so because Oklahoma was a medium-sized state well-connected to the national grid, unlike Texas.  More on this below.

For the record, our ballpark estimates of the percentage of a state's population initially disconnected are about 10 percent for Oregon; 6 percent for Louisiana; 6 percent for Kentucky; 12 percent for West Virginia; 4 percent for Missouri and 2 percent for Virginia.

(Thanks to my colleague Meagan McCollum of Tulsa University, who pointed out my howling error in the first posting: I mixed up Oklahoma City and state populations.  Keep those comments and corrections coming!)

The Human Cost

Exhibit 5

Photo from the New York Times

"Workers helped Dori Ann Upchurch into a warming station at University Avenue Church of Christ in Austin. She evacuated her home after she lost her water supply."

This photo is one of a number of remarkable photos available at a New York Times photo essay that I highly recommend.  Let me comment on just a few of them.

Exhibit 6

Photo from the New York Times

I’ve had the opportunity to work in a number of low-income countries and learn from many colleagues and friends in such environments. One of the important but underappreciated problems in many informal settlements in Africa, South Asia, and elsewhere stems from the use of indoor fuels for cooking and heating. Globally 3 billion people use open fires or simple stoves that give off noxious fumes; close to four million people die prematurely every year from illnesses attributable to such pollution.  

This photo of a Texan family from the New York Times collection brought to mind these tragic issues although I took some comfort from the reporting that this particular family was only cooking indoors very temporarily. 

A number of the fatalities attributed to the storm are from carbon monoxide poisoning from dangerous indoor heating.

Exhibit 7

Photo from the New York Times

Anyone who works in informal settlements and low-income countries (“slums”) in countries like Kenya India Brazil familiar with pictures of residents filling bottles and buckets from standpipes and water trucks. This photo from the New York Times photo essay brought back those memories.

Exhibit 8

Source: Twitter

As the Axios  and the New York Times reported, Texas power shortages often hit minority neighborhoods particularly hard.  

This is not a new phenomenon.  Poor infrastructure provides fertile initial conditions for such reductions in service.  In states like Texas, poor neighborhoods are often located near industrial sites.  These sites can release additional pollutants during some emergencies, like floods, raising additional health concerns. 

Many urban poor lack access to automobiles and rely on public transit, as Glaeser and Kahn have documented, which can trap them in affected areas.  For example, several years ago during Wisconsin debates on voter ID, I calculated that 20 percent of Milwaukee city residents had no access to cars.  Two-thirds of Milwaukee's population is minority (Black, Hispanic or Asian).

Such lack of access to automobiles can limit a family's ability to seek shelter from friends and neighbors during emergencies.  To quote Kromm and Sturgis, 

“While about 80 percent of New Orleans residents heeded the mandatory evacuation order issued before Katrina, tens of thousands stayed behind—and the number-one reason they gave was that they lacked cars. Indeed, at the time of the storm, about one-third of New Orleanians—approximately 120,000 people—did not own automobiles.”

The Disinformation Machine at Work

Exhibit 9

Sources: Fox, OAN, Twitter

We could post dozens of quotes from politicians and media that put forward the canard that wind and/or renewable energy is primarily if not uniquely responsible for the Texas energy debacle.  

A quote from Tucker Carlson represents this view: “Global warming is no longer a pressing concern here. The windmills froze, so the power grid failed.” In the first sentence, Carlson has confused climate and weather a surprisingly common mistake in some quarters.  Readers seeking guidance on the difference can consult many sources, e.g., the National Ocean Administration, or NASA.  This post is more directly concerned with the second sentence.  Carlson’s claim that reliance on wind power was a principle cause of failure of the Texas power grid, repeated by Larry Kudlow, Rick Perry among others  is facile and incorrect.

Or to quote Governor Greg Abbott:

"This shows how the Green New Deal would be a deadly deal for the United States of America. ... Our wind and our solar got shut down, and they were collectively more than 10 percent of our power grid, and that thrust Texas into a situation where it was lacking power on a statewide basis."

Well, there's room to debate reported specifics of the Green New Deal even if you support a speedy transition to renewables.  For the record, I'm a fan of the latter, not so much of the former  (especially in its first drafts).  For example, I don't see a total shutdown of fossil fuels by 2030 as a realistic proposition, and I think the GND's claims to solve tough problems of growth and distribution are grossly overstated, at best.  But politicians and pundits should be called out when they use the GND as a red herring to push back against a transition to renewables that is, sooner or later, inevitable. 

Oh, and while we're thinking of environmental policies, did I mention -- a carbon tax?  (Be still, my heart).

Texas' Energy System

Exhibit 10

Source: Statista

Texas does indeed obtain a significant portion of its electricity from wind.

Much of the growth in windpower came under the governorship of -- wait for it -- Rick Perry.  (The same Rick Perry who couldn't remember the name of the Department of Energy, who later ran it, surprised to find the breadth of DoE's responsibilities, including nuclear safety.

Exhibit 11

Source: ERCOT

Texas set up a statewide grid largely unconnected to the rest of the country to avoid regulatory and other costs.  This did lower short-run costs, but also limited Texans ability to draw on resources from other states in an emergency.  Texas also chose to save money in the short run by failing to weatherize windmills.  In fact, they failed to weatherize many parts of their energy infrastructure, including but not limited to critical components of gas production and distribution. 

The Texas electricity regulator estimated peak winter demand at 67,000 megawatts.  But as people resorted to space heaters and other electric devices to try to warm up, demand for electricity hit 69,000 megawatts at a time when 30,000 megawatts of power went off-line. This 30,000 MW off-line was twice the level that the Electric Reliability Council of Texas (ERCOT) used as their extreme generator outage for scenario planning. 

Exhibit 12

Source: EIA data mapped by howmuch.net

Texas does indeed have electricity rates somewhat below the national average -- but actually higher than neighboring Louisiana and Oklahoma, who manage to run their systems while connected to the national grid and subject to the resulting regulations.

Exhibit 13

Source: theedgemarkets.com

It’s true that icing did force many turbines to shut down in Texas and elsewhere throughout the South and Midwest during this freeze. But Texas was hit much harder than other states.  According to a Bloomberg report, in Texas wind shutdowns accounted for about 13 percent of the 30 to 35 gigawatts of total outages. 

Exhibit 14

Source: Texas Tribune

Wells and pipelines froze, pumps failed. Texas’s thermal plants – plants that generate electricity using heat from gas, coal, petroleum or nuclear energy – went off-line.  The decline in thermal sources was the largest source of supply shortfalls. 

Exhibit 15

Source: Powermag.com

This photo is not from Texas, and not from 2021. 

It is taken from my urban environmental teaching library, and represents damage to the power lines in other elements of the grid itself.

Exhibit 16

Source: Denver CBS Affiliate

Keeping the grid in repair during and after storms requires extreme and sometimes heroic efforts from utility workers. In fact, it’s often no easy job in “normal” times.

Many deserve credit for their response to this and similar emergencies, year in and year out, including utility workers but also emergency responders, the people who run shelters, those who keep retail establishments open, those who represent "the kindness of strangers..." in fact far too many others to enumerate here. 

And of course, all credit to those bellwether supporters of society during emergency conditions in much of the country: the operators and staff of Waffle House.

Exhibit 17

Source: The New York Times

Before we examine the pre-and post-storm performance note the following features. Solar generation (not including most home installations) are a small part of Texas' electricity generation, a few gigawatts (GW) or about 2 percent of generation according to the 2019 EIA data. And of course, as the cycle clearly visible in this chart shows, solar electricity is only generated when the sun is out.

Nuclear power provides about 5 GW of Texas electricity and coal 10 GW; these two sources are in normal times the rock steady-state providers.

Wind averages about the same generation as nuclear, but is more volatile.

Natural gas is by far the most important single fuel, providing 30 to 40 GW of power, more or less. Gas is not only the largest source, but is also the swing provider in normal times.

As the extreme cold hit after Valentine’s Day, gas and wind (the major swing providers) initially peaked:  gas provided energy in the mid-40’s GWs while wind approached 10 GW. 

But as the storm progressed, and elements of all power sources faced operational problems, gas fell down to the high 20s and wind felt down to about a GW.

Notice that solar actually picked up a little bit of the slack when the sun was shining.

Exhibit 18

Source: data from EIA and from NOAA.

These data on wind and solar are annual averages.  I obtained data on 2019 state electricity generation by source from the energy administration an average winter temperature from weather data. Those data are used to construct Exhibit 18.

No surprise, Hawaii is the warmest state on average during the winter. Florida is also quite warm on average, followed by Louisiana, Georgia, Texas, California and some other southern and southwestern states.

Alaska is the coldest state. I lived in Wisconsin for 26 years which I found to be plenty cold. But I don’t really mind cold weather is much as heat and humidity. If it’s cold, I can wear my down coat, and most of the places I’ve lived had had central heating.  Nevertheless, the chart shows why I always felt just a bit sorry for my friends in Minnesota. And Iowa. North Dakota’s pretty cold as well.

The vertical axis measures the percentage of state electricity generated from wind and solar combined, the renewables that so concerned Tucker Carlson above. Actually in virtually all the states the majority of that renewable energy comes from wind, which to date is generating more for the grid than solar. You can download a small spreadsheet with some of the details of this data here.

The central finding for our purposes today is obvious. Texas averages about 20 percent of its electricity generation from renewables, primarily wind. Plenty of states with much colder climates including Kansas Iowa, the Dakotas, Minnesota, Maine, and Vermont have similar or higher levels of electricity from renewables.  Because they insulate and maintain their equipment better than Texas, and because they are plugged into a larger grid for backup, these states have fewer problems under much more challenging weather conditions. 

Of course, that doesn’t mean there are never outages or problems when storms hit Kansas or Iowa, far from it. But it’s clear from many sources that Texas had a clear path to prepare for such events and chose not to take it.

One roadmap for such preparations was prepared after a 2011 extreme cold event, and is available here.

(By the way, there are some differences between data in this chart, and seasonal data cited above.  Wind and solar are more heavily utilized during summer, when air conditioning and other demand peaks, and their production usually falls during the winter. For example, in Texas wind can produce as much as 60 percent of Texas’s total electricity production during peak seasons; but wind turbines generally drop to 20 to 40 percent of their maximum output during winter under normal lower-demand winter conditions.)

Exhibit 19

Source: Lake Erie Energy Development Corporation

Exhibit 19: The Pori 1 Turbine installed in Finland demonstrates that turbines can manage under extreme conditions, if properly designed and maintained.

Texas' system for producing and distributing energy can, of course, be weatherized. As Jesse Jenkins summarizes in “A Plan to Future Proof the Texas Power Grid,” 

“Pipelines can be buried deeper to insulate against the ground’s cold surface. When gas supplies are disrupted, dual fuel power plants can switch from gas to petroleum stored on site. Wind turbines can be equipped with heaters to keep blades free of ice. Sensors, valves and coolant intakes can be protected against freezing. Long-distance powerlines can connect to other regions power system and draw from their supplies during times of need.” 

But up until now Texas has eschewed these measures because of their cost. 

The Transition from Fossil Fuels to Renewables is Underway

Exhibit 20

Source: San Juan Citizens Org.

For an interesting and entertaining account of the very long run, see William Nordhaus' account of energy sources over a millennium.  We appear to be on the cusp of another major transition: from fossil fuels to renewables.

Such transitions are by no means limited to energy.  Here's another well-known transition, that took place about a century or so ago:

Source: 21

Source: Docsteach.org, from Bureau of Indian Affairs

Exhibit 22

Source: Grubler et al.

Exhibit 22 shows how rapidly a change in technology can take place, once technical and economic thresholds are reached. In just a few decades after the development of mass-market automobiles, the horse went from a major mode of transport, to a hobby.

The pace of technical change is much more rapid than a century ago.  The ongoing transition to renewables will take some time, though it's hard to put an exact timeline on it.  It is well-known that current storage technology is low-capacity relative to total loads, and is very expensive.  Improvements in storage technology are underway and will be required for intermittent energy sources including wind and solar to successfully transition to a large part of total energy production.  

In the short run, I would imagine over several decades, fossil fuels will remain a significant energy source.  During this transition, cleaner fossil fuels like gas (with technical and regulatory changes that reduce their climactic impact, e.g. reducing methane escape during production and transport) will become increasingly important for a few decades. Nuclear power is another baseload power source which faces technical and political challenges, each difficult but neither insurmountable in principle.  The forecast that nuclear-generated electricity would be "too cheap to meter" reminds us to have some humility about our ability to foresee all the elements and timing of future electrical generation.  

Learning more about infrastructure

Here’s some sources on energy-related infrastructure.  Some have been consulted for the posting above, others are sources as we prepare the section on infrastructure for the forthcoming Future of Real Estate project.

Borck, Rainald, and Jan K Brueckner. "Optimal Energy Taxation in Cities." Journal of the association of environmental and resource economists 5, no. 2 (2018): 481-516.

Federal Energy Regulatory Commission and the North American Electric Reliability Corporation. "Report on Outages and Curtailments During the Southwest Cold Weather Event of February 1-5, 2011." 2011.

Ferguson, Charles D. Nuclear Energy: What Everyone Needs to Know. OUP USA, 2011.

Gilbert, Alan. "The Return of the Slum: Does Language Matter?". International Journal of Urban and Regional Research 31, no. 4 (2007): 697-713.

Glaeser, Edward L, Matthew E Kahn, and Jordan Rappaport. "Why Do the Poor Live in Cities? The Role of Public Transportation." Journal of Urban Economics 63, no. 1 (2008): 1-24.

Grübler, Arnulf, Nebojša Nakićenović, and David G Victor. "Dynamics of Energy Technologies and Global Change." Energy policy 27, no. 5 (1999): 247-80.

Irvine, Maxwell. Nuclear Power: A Very Short Introduction. OUP Oxford, 2011.

Kahn, Matthew E, Nancy Lozano‐Gracia, and Maria Edisa Soppelsa. "Pollution's Role in Reducing Urban Quality of Life in the Developing World." Journal of Economic Surveys 35, no. 1 (2021): 330-47.

Kahn, Matthew E, and Erin T Mansur. "Do Local Energy Prices and Regulation Affect the Geographic Concentration of Employment?". Journal of Public Economics 101 (2013): 105-14.

Kromm, Chris, and Sue Sturgis. "Hurricane Katrina and the Guiding Principles on Internal Displacement." Institute for Southern Studies, 2008.

Levi, Michael. The Power Surge: Energy, Opportunity, and the Battle for America's Future. Oxford University Press, 2013.

Nordhaus, William D. The Climate Casino: Risk, Uncertainty, and Economics for a Warming World. Yale University Press, 2013.

———. "Do Real-Output and Real-Wage Measures Capture Reality? The History of Lighting Suggests Not." In The Economics of New Goods, edited by Timothy Bresnahan and Robert J Gordon, 27-70: University of Chicago Press, 1996.

Raimi, Daniel. The Fracking Debate: The Risks, Benefits, and Uncertainties of the Shale Revolution. Columbia University Press, 2017.

Thompson, William L. Living on the Grid: The Fundamentals of the North American Electric Grids in Simple Language. iUniverse, 2016.

Usher, Bruce. Renewable Energy: A Primer for the Twenty-First Century. Columbia University Press, 2019.

Willrich, Mason. Modernizing America's Electricity Infrastructure. MIT Press, 2017.

Yergin, Daniel. The New Map: Energy, Climate, and the Clash of Nations. Penguin Press, 2020.

A first look: Do presidents drive the economy? What will divided government mean for the economy?

Exhibit 1

Prologue

As an economist with some undergraduate and graduate training in political science. and an abiding interest in the intersection between politics and economics, a few months ago I began to collect some of my old teaching materials relevant to this post. I began to write the post itself a few weeks after President Biden's November 2020 electoral victory.  I was inspired to do so by many comments in media and elsewhere about the pros and cons of a "divided government" for the economy. something I had discussed in classes years ago.

I thought (and still think) that some of these points would be of interest no matter what the outcome of the January 5 Georgia election that would decide whether the Senate would be a closely divided Republican-led body, or a closely divided Democratic-led body. As it happens, of course, the January 5 Georgia election swung the Democrats' way, when I was about halfway through this entry. That result has profound implications for our politics and indirectly for our economy. But whether the results favored R's or D's, with such a closely divided Senate and such a polarized political environment. I thought a blog post exploring divided government would be an interesting one.

Exhibit 2

I was still in the middle of drafting, on January 6, 2021, when a news flash crossed my PC that a violent riot had broken out at the U.S Capitol after Donald Trump had egged on his supporters to march on Congress to "Stop the Steal."   A "steal" which, of course, had never happened.

Well, there went my productivity. such as it is, for a couple of days, while I was transfixed by these developments.  More on those developments some other day. For now. though I never would have seen this coming, I'll say Arnold Schwarzenegger speaks for me.

Here we'll continue with the post as originally planned. I'll have more to say about the January 6 events and other matters in a future post. This post will focus on the following questions:

• Do presidents drive the economy? 
• Does presidential party matter?
• Do our political views color our economic outlook?
• Is divided government good for the economy?

Day-After Posting News Flash:  Do "Great" Minds Think -- Somewhat -- Alike?

I posted the original version of this blog entry on February 1.  Bob Buckley emailed me the next day, before I had the opportunity to read through my New York Times, with a head's-up. On February 2, David Leonhardt has just published a related op-ed:

The Economy Does Much Better Under Democrats. Why?  G.D.P., jobs and other indicators have all risen more slowly under Republicans for nearly the past century.

There's a lot of overlap between Leonhardt's op-ed and this blog. That's not a surprise, given years of interest in the subject. We both use the classic work by Alan Blinder and Mark Watson as a jumping-off point.  We both look at GDP, but while I look at stock prices and inflation, Leonhardt looks at employment.  Unsurprisingly, there's some overlap in our interpretation as well, but also some difference.  It's not a bad idea to read our two efforts as complements.

Original motivation

Media as well as casual conversations often refer to the ''Trump economy,'' or the '"Obama economy," or the "Bush economy.... " To be fair, I've rarely heard anyone refer to the "George Washington economy" or the "John Quincy Adams economy." Nevertheless for many decades the practice has seemed firmly entrenched.

Here are a baker's dozen links, more-or-less randomly selected from hundreds available via a quick Internet search on "presidents and the economy:

• Bloomberg, "Economy Breaks Record on Trump's Watch.  He Wants All the Credit."
• House Budget Committee, "President Trump Has Failed the American Economy'"
• The Economist, "How to Judge President Trump's Economic Record"
• Bloomberg, 'Trump's Economy Really Was Better Than Obama's"
• Forbes, "Obama's 2009 Recovery Act Kicked Off Over 10 Years of Economic Growth"
• Wall Street Journal, "His and Her Clintonomics"
• The Economist, "Economic History: FDR for Beginners"
• Mises Institute, "How FDR Made the Depression Worse"
• Carl Piven, "Jimmy Carter's Economy"
• 5 Minute Economist, "Which Presidents were Best and Worst for the US Economy"
• The New Yorker, "Hating on Herbert Hoover"
• Peter Temin, "The Jacksonian Economy"
• Robert Hormats, "'Abraham Lincoln and the Global Economy"
• George Washington Colonial Life (Mt Vernon), "Ten Facts About the American Economy in the 18th Century"

Try your own search, including the names of your favorite among the 45 presidents (46 presidencies -- see Grover Cleveland, the 22nd and 24th president), and you'll find many dozens more.

As a good (if informal) Bayesian, I should reveal my priors on this subject  My reading of the evidence, scholarly and otherwise, is that (1) presidents and their policies do have important effects on the economy: but (2) these operate with long lags and are extremely hard to disentangle; and (3) the common attribution of economic success and/or failure to a president and/or his party is a gross simplification at best. 

Thus I will argue that Joe Biden's actions will have profound effects on the economy, but that over the next four years the U.S. economy will be also driven by decisions taken by Donald Trump. And Barack Obama. And a couple of Bushes. Clinton. Carter. .... Eisenhower. FDR. Hoover ... Lincoln ... all the way back to George Washington. 

I have other relevant priors.  Perhaps the most salient is that of course presidents don't act alone. Federal Reserve presidents, in fact the entire Fed Board of Governors, Regional Presidents, and the Fed's bureaucracy play important roles.  Many cabinet members, other staff. and bureaucrats have made important contributions (and, sadly, more than a few subtractions) to U.S. economic performance.  Alexander Hamilton immediately comes to mind, but so many others; to name just a few, Harry Dexter White (influential in the design of the post WWII Bretton Woods institutions when he wasn't feeding information to the Soviets).  Many in Congress have had their impact, for example Justin Smith Morrill (sponsor of the Land Grant Act of 1862 signed by Abraham Lincoln, which created the system of land grant colleges including the University of Wisconsin), or Carter Glass, who co-sponsored the Federal Reserve Act as well as the Glass-Steagall Act which (until recent decades) separated investment and commercial banking, and created the Federal Deposit Insurance Corporation.

In this note we focus on two branches of the federal government, the presidency and the legislature. The third branch, the Supreme Court, is easily worthy of its own post. No court term goes by without the Supreme Court, to say nothing of the hundreds of lower courts, putting their stamp on the economy. Just a few landmark cases will be mentioned here as examples. In McCulloch versus Maryland (1819) the court took an expansive view of the Constitution’s stricture that 

“The Congress shall have Power…To make all Laws which shall be necessary and proper for carrying into Execution the foregoing Powers, and all other Powers vested by this Constitution in the Government of the United States, or in any Department or Officer thereof.”

This particular case revolved around the establishment of the Second Bank of the United States. Even though the Constitution did not specifically enumerate the power to establish such a bank, the Court ruled that it was shown to be “necessary and proper.” The door was thus opened for a wide range of implied powers in addition to those explicitly granted in the Constitution.  McCulloch versus Maryland also forbade states from taxing federal entities.

Gibbons versus Ogden (1824), known as “the steamship cases,” established federal primacy in the regulation of interstate commerce. Another riparian case, Charles River Bridge versus Warren Bridge (1837) established limits on contracts to create monopolies.  The Court ruled that a charter granted to the first company did not confer an enforceable monopoly on bridges between Boston and Cambridge.  The deciding opinion also highlighted the responsibility of government to promote “the happiness and prosperity” of the American people.

"Real Estate and Urban Development Viewpoint" obviously has an urban focus.  Many cases also have helped construct the framework for urban development especially land use. The canonical case of Euclid v. Ambler (1926)  is where most discussions of this legal framework start; in Euclid, the Court famously held that even if it reduced the value of a property, zoning and other regulations were not “takings” requiring compensations (see the Constitution’s 5th Amendment) but were exercises of the government’s police power so long as it had some "reasonable relation" to the promotion of "health, safety, morals, and general welfare."  Over the years, dozens of other cases – Pennsylvania Coal v. Mahon (1922), Southern Burlington Co. NAACP v. Mount Laurel (1975) Lucas v. South Carolina (1992) and Kelo v. New London (2005), to name just a few – filled in and, at times adjusted, this framework.

In this note we focus on two branches of the federal government but of course state and local governments have profound implications for the economy and our populace’s well-being. Malpezzi (2007, 2012) provide a brief discussion and some references.

Finally, since this post focuses on the relative performance of Democrats and Republicans, readers may wish to know if I bring any political biases.  Personally, I only ascribe to the first half of Will Rogers' famous epigram:  "I am not a member of any organized political party."  I have been registered as an Independent since the 1970s, and have been a ticket-splitter ever since.  I often lean classical liberal in my opinions (which is not the same as most Americans use the term liberal today).  Think the Adam Smith of both The Wealth of Nations (concerned with growth and efficiency) and The Theory of Moral Sentiments (concerned with our social nature and with equity and fairness).  I'm fine with paying taxes and with income redistribution, though I think we need to spend at least as much time thinking about incentives, human capital formation, and widening opportunities.  It is fair to say -- it's a gross understatement, actually -- that I've not been a fan of Donald Trump, since I first began to pay some attention to him while teaching about commercial real estate three decades ago.  I won't bother with details, but shortly before the 2016 election Mitt Romney summarized many of my views; and four years or so later, things turned out even worse, much worse, than I had expected. 

Whatever my political opinions, I do my best to keep my facts tethered to the real world.  I try to stay away from the post-modern ideas of such "philosophers" as Michel Foucault (truth is determined by power), Jacques Derrida ("the deconstruction of narratives"), Donald Trump himself, and, yes,  Rudolph Giuliani ("truth isn't truth.")  Put me in the camp of Daniel Patrick Moynihan: "everyone is entitled to his own opinions, but not his own facts."  Let's look at some evidence.

So: Do presidents drive the economy?  What does the evidence show?

Exhibit 3

Economists and political scientists alike have long found support for the hypothesis that economic conditions affect elections, especially presidential elections. In fact, I recently re-posted a blog post on this subject, from 2010.  For a more detailed discussion, see Fair (1978, 2011). 

Is the converse true? Do presidents have a more or less contemporaneous effect on the economy?

The best-known paper among economists is by Blinder and Watson. Their tabulations lead them to claim that "the U.S. economy has performed better when the president of the United States is a Democrat rather than a Republican, almost regardless of how one measures performance." A later working paper by Tim Kane shows that specific results of such tabulations are sensitive to assumed lags between the dates politicians take office and their actions may directly affect the economy.  Taking either Blinder and Watson's, or Kane's results (or any other result on such relationships) at face value - even asking the question - leads immediately to other, deeper, questions. Why would any president matter for U.S. economic performance? Why would their political party matter? And by the way, what is economic performance?

In this brief note we will focus on gross domestic product as our main measure of economic performance. This is not because GDP is anything like a sufficient statistic for overall performance. We could quickly name a few dozen additional informative indicators, including measures of inflation (which we will briefly consider), employment, the structure of production, environmental conditions, the ability to enjoy leisure, and measures of poverty and the distribution of income and wealth. among others. To keep this a blog post instead of a book, we will limit ourselves today to GDP and just a few other indicators.

As it happens a number of other potential measures, including employment, are often - not always - correlated with GDP. Distributional measures in particular are more complex. Fully considering other measures awaits another day.

Does a president's party matter?  In is not entirely clear how much Democrats Harry Truman, LBJ, and Bill Clinton have in common regarding their stewardship of the economy.  Certainly Republicans Dwight Eisenhower, the Bushes pere and fils, and Donald Trump have followed very different economic and social policies. For that matter, why would the president's party, as opposed to their individual policies and circumstances, matter so much over time? Especially when we've recently learned, once again, that what it means to be a Republican or a  Democrat can change profoundly over less than a decade.

Results in the literature including Blinder and Watson, Kane, and others, can be boiled down to a few stylized facts:

• At first glance, many but not all indicators seem to perform better under Democrats than Republicans. (Note the emphasis on seem).
• These simple relationships are not robust when we account for lags between politics and policies, and the measures of economic performance.
• None of this should be a surprise after careful thought. Today's economy is affected by the lagged effects of the policies of 45 presidents and 117 congresses. Among many other things.
• Most analyses (including ours, below) focus on a necessarily small sample of postwar presidents and legislatures. The law of small numbers applies.

Without ascribing causality, what do the averages of economic indicators look like, by presidential term?

This chart breaks down basic data by presidential term: inflation-adjusted GDP growth, real GDP growth per capita, a measure of the rate of inflation, and the change in the S&P 500 index deflated with the GDP deflator. I have also included the number of quarters each presidential term spans.

Exhibit 4

Here are just a few highlights. These are purely descriptive and quite simplistic.

At the end of the first Harry Truman term the U S. was coming out of a sharp and severe recession that hit at the end of World War II. 

The official Bureau of Economic Analysis' National Income and Product Accounts data begins in 1947. I'm using the post-1947 BEA data here, although economic historians have estimated GDP for earlier periods. If we included the full Truman first term, his growth data would look much worse, because of the short sharp post WWII recession omitted from this dataset.

The S&P 500 stock index was created in the mid·1950s, and I have data beginning in 1950. Apparently. some other sources have backfilled the data to earlier years but I haven't obtained that as of this writing.

The second Truman term was characterized by rapid growth as the economy bounced back from the post World War II recession. When Dwight Eisenhower took office the economy began to slow down; the slow growth during Ike's second term is widely considered to have contributed to John F. Kennedy's victory over Richard Nixon in the 1960 election.

Kennedy's term was characterized by robust growth and low inflation, but of course was cut tragically short by his 1963 assassination.

Johnson's first term comprised only 5 quarters between his assumption of the presidency in November 1963 and the 1964 election. In the latter year Johnson won election in his own right of course, and presided over rapid growth; but also the beginnings of accelerating inflation as we ran large deficits during the "guns and butter" period of the Great Society and the Vietnam War.  During this period Johnson famously bullied Fed chairman William McChesney Martin to follow a loose money policy, exacerbating price instability.  In 1968 Johnson was eligible to run again, but the Vietnam War proved a political albatross; Johnson declined to run, and his vice-president Hubert Humphrey then lost to Richard Nixon.

Inflation picked up further during Nixon's full first term. The second term was cut short by his Watergate-related resignation. Inflation continued to accelerate during the Gerald Ford and Jimmy Carter administrations, two single-term presidencies that were characterized by modest growth, high inflation, and political weakness.

Of course it wasn't just the economy that contributed to their failures to win a second term. Among other challenges, Gerald Ford faced serious blowback from his pardon of Richard Nixon post-Watergate, and Jimmy Carter faced energy shortages and the Iran hostage situation.

While Carter's inflation number is the worst in the chart. it was Jimmy Carter who took the politically difficult decision to bring in Paul Volcker as Federal Reserve chairman, and backed Volcker as he instituted a severe! tightening of monetary policy that pushed the U.S. into recession but also finally wrung inflationary expectations out of the system, at least for the time being. Paul Volcker's Fed presidency spanned more than one presidential administration as he finished the job near the end of Ronald Reagan's second term

After a rocky start, including the largest tax cut in U.S. history (sorry Donald!) Ronald Reagan initially saw strong growth and slowing inflation. But his initial tax cut was soon moderated by a series of less famous tax increases, put in place in response to burgeoning budget deficits As the deficits moderated and Volcker continued at the helm of the Fed, GDP growth picked up and the stock market boomed in Reagan's second term.

A relatively weak economy was problematic for George Herbert Walker Bush, who was limited to a single term by Bill Clinton. The economy was one issue that helped Clinton along with Republican disaffection with Bush's reversal on tax increases during his first term. Bush also finally bit the bullet and began to wrap up the Savings and Loan crisis near the end of his term. 

(Conventional wisdom claims Clinton was also aided by the strong if somewhat strange third party run by Ross Perot,  Careful analysis by political scientists such as Alvarez and Nagler suggests Perot took votes from both candidates and may even have harmed Clinton more than Bush in the end).

Clinton benefited from previous policies including Volcker's conquest of inflation and Bush's initiation of S&.L reform. Volcker's hard-won shift in inflationary expectations allowed his successor Alan Greenspan to follow a much looser monetary policy without igniting inflation. As the Soviet Union collapsed, defense spending fell substantially. Tax increases on higher income taxpayers failed to put a dent in growth or the stock market.  After the Reagan stock market boom and a lull that coincided with much of Bush's term, a second stock market boom accompanied much of Clinton's two terms

As George W Bush took office there was room for optimism, as he came in with solid growth, low inflation and a budget surplus. But the Tech Bubble burst in 2000, and the terrorist attacks of September 11, 2001 provided both an initial shock to the economy and a large increase in defense spending as the U.S. went to war in Afghanistan and, eventually, Iraq. Budget woes were compounded by a large unfunded tax cut. And then, of course well into the second Bush 43 term the housing bubble burst. Lehman Brothers and other financial entities defaulted. and we went into the Great Financial Crisis/Great Recession.

Barack Obama's first term growth numbers were pulled down by the aftermath of the events above, but growth resumed in summer 2009, albeit at a slower pace than some expected. The U.S. embarked on a long but subpar growth expansion that carried over into Trump's presidency; at least until the pandemic hit the economy and more, early in 2020.

Donald Trump was fond of claiming that he presided over "the greatest economy in history," until the 2020 coronavirus. Fair enough that SARS-CoV-2 was a huge negative shock which would have challenged any president, although with some exceptions (Operation Warp Speed) the response of Trump and his administration was dismal.  A recent report by GAO provides a detailed and comprehensive review.  In the event, before the pandemic, GDP growth under Trump, overall or per capita, as well as stock market performance and inflation, largely continued the same trends as under the prior Obama administration. 

The pandemic year 2020 was and remains an economic as well as human disaster.  To take one bellwether indicator, quarterly per capita GDP fell by 1.5% in the first quarter, fell by 9.2% in the second quarter, bounced back by 7.3 percent in the third quarter, and grew by 0.8 percent in the fourth quarter.  Overall GDP is down 3 percent over the year, employment is still down by 10 million, and with coronavirus deaths running 3,000+ per day we are far from out of the woods.

Now, as I write this post in January 2021, Trump's presidency has ended.  Joe Biden embarks on the twin tasks of containing the pandemic, and facilitating recovery from the deepest recession since the Great Depression, all in an environment of political polarization greater than we've seen in over a century.

Do our political views color our economic outlook?

Political scientists and psychologists have long studied how political views can predispose us to different perceptions of economic and social reality.  Robert Shiller's recent book on Narrative Economics summarizes some of this literature for economists, and tells a good story about how we rely on stories to make sense of our economy.

Exhibit 5

In February 2020, Pew Research published a blog entry on Views of the Nation's Economy Remain Positive though Sharply Divided by Partisanship. Exhibit 5 presents one of their central findings.

A representative sample of U.S. adults polled in January 2019, well before the election, found that a bit less than half of Democrats had a positive view of the economy. Republicans, still on the outs politically at that date, took a much dimmer view.

Taking these results al face value, it's perhaps ironic that Democratic views of the election look remarkably like Trump's personal poll numbers (before the January 6 2021 Capitol riot).  Both were fairly stable, somewhere under 50 percent. But Republican views of the economy took off like a rocket after the 2016 election and well into Trump's term.  (And Trump's poll numbers finally did drop after four years of relative stability after his supporters stormed the Capitol, resulting in five deaths and numerous injuries, to say nothing of a shock to the body politic).

Everyone reads the same BEA and S&P data. Not everyone experiences them the same, of course.  Nevertheless, the variation in perceptions is remarkable, and a little hard to explain with any rational model.  Politics seems to provide an emotional filter though which we see the data.

Exhibit 6

Exhibit 6 presents another interesting, somewhat puzzling chart from Pew, with a longer time frame. For much of the 90s, as expectations about the economy turned increasingly optimistic, party didn't seem to matter so much.

During the Bush fils years, Republicans took a much more sanguine view. But when the economy went south in 2007-9, everyone felt the pain.

During the Obama years, 2009 through 2016, Democratic perceptions began to diverge from Republican.  When Trump unexpectedly won the 2016 election, Republicans suddenly decided economic conditions were doing great, while Democrats' perceptions nose-dived.  Any examination of GDP, stock prices, employment, interest rates over, say, 2015 through 2018 (including the limited data we examine below) would find only modest differences in economic trends. Politics seems to be driving perceptions of economic performance, with a vengeance.

Is Divided Government Good for the Economy?

Exhibit 7

It's easy to find dozens of articles in the financial press and elsewhere that suggest divided government might actually be better for the stock market and/or the economy, than having the presidency and both legislative bodies held by the same party. For example:

• NPR "Wall Street Bet On A Blue Wave. But Divided Government Suits It Just Fine Too"
• Charleston Currents, "Divided Federal Government May Help Economy"
• New York Times, "As 'Blue Wave' Chances Crash Wall St. Warms to Divided Government"
• Barron's, '"Divided Government is a Plus for Investors"
• Fortune, "Stocks historically perform better under a divided Congress"
• Business Insider, "A split Congress and Biden presidency will be 'excellent' for the economy and stock market, Wharton Professor Jeremy Siegel says"
• New York Magazine, "The Stock Market Loves the Idea of McConnell Blocking Biden's Plans"

But there is certainly no unanimity of opinion on this. Examples of media pushback include:

• Washington Post, "Divided government is a path to disaster. Why won't voters admit it?"
• The Atlantic, "Divided Government Will Doom the Economy'"
• Wall Street Journal, "'Divided Governments Are Supposed to Be Good for Stocks. The Data Don't Support That"

Do Americans Prefer Divided Government? The Evidence is Mixed.

The links above refer to “the markets” and “the economy,” and representative opinions by various media pundits. What do we know about the direct preferences of our people? 

Exhibit 8

One survey taken roughly a week after Joe Biden's presidential victory (Exhibit 8) suggests that, at least at that time, a plurality (41 percent) of voters expressed a preference for divided government. Unsurprisingly, with a Democratic House but the Senate still in play at the time (Georgia's runoff wins for two Democrats would resolve who held the Senate two months later), Democrats expressed a preference for unified government, i.e. a Democratic Senate. Republicans liked the idea of a Republican Senate and divided government.  Quel suprise.

Exhibit 9

Another survey taken some years earlier with a different question structure is presented in Exhibit 9.  This survey separates out Independents from Democrats and Republicans.  This survey was taken a month before the 2014 midterm elections, when Barack Obama held the presidency and Democrats the Senate; with Republicans in charge of the House. Perhaps it's no surprise that with their party holding two of the three elective elements of government, Democrats thought adding the House to their collection would be a good thing; on the other hand, adding two responses, slightly more Democrats thought a split would be better, or it made no difference.

Two other patterns stick out.  At least at this time and place, Independents responded identically to Republicans, in the aggregate.  And while there's no direct information here, we can suspect that most of the 24 percent of Republicans who answered "same party" was preferable were possibly thinking more of a future Republican sweep than a solidly Democratic government across the board.

So, politics affects how we view the economy.  What do the data tell us about "reality?"  We will return to our focus on three indicators: stock prices, GDP, and inflation.  Stock prices are included not because it's one of my top three indicators, but because politicians and media focus on it so much.

Digression: why do we talk so much about the stock market? 

True, the stock market index seems to be Donald Trump’s favorite indicator. And every daily newscast breathlessly tells us what happened to the Dow Jones or S&P that day.  (If we needed a daily indicator on the economy, I'd argue for some bond market indicators like the TED spread.)  

Despite its ubiquity, in recent years the shortcomings of stock indexes as a measure of broader output or welfare, long known to economists, have become more widely appreciated.  Today, media and even someone cheerleading platforms like CNBC have noted “the stock market is not the economy.” 

Well, duh.  The Dow Jones comprises 30 industrial stocks.  The S&P 500 contains (wait for it!) ... 500 companies.  Add the Wilshire 2000 and we’re up to 2500 companies.

There are 30 million business enterprises in the United States, according to the Small Business Administration.  Roughly half the U.S. labor force is employed by small firms with 500 or fewer employers. Firms with fewer than 20 employees employ about 20 million workers.  Even if we're focused on business enterprises, the popular stock market indexes give a very incomplete picture.

Furthermore, most Americans hold little or no wealth in stocks.  Exhibit 10 presents a graphic of Federal Reserve Survey of Consumer Finances data, prepared by the New York Times:

Exhibit 10

Exhibit 10 shows that most U.S. households have negligible holdings of equities, whether one looks at directly held securities, or includes indirect investments through pension funds and the like.

Eight-five percent of stocks are held by the top 10 percent of households, ranked by net worth.  The bottom half of the wealth distribution hold close to zero stocks.

When pension funds etc. are included, the bottom half of the income distribution’s share of the stock market rises from 0% to 1%.  The top 10 percent share falls to 71 percent.

In the event, how do stock prices correlate with the economy's output?  Exhibit 11 presents a simple plot of two indicators.

Exhibit 11 plots the inflation-adjusted S&P 500 and real GDP on the same chart. The data are quarterly, and a log scale is used so the slope approximates the growth rates of each variable. Over 73 years, the real S&P 500 index grew at 8% per annum (average of annualized quarterly growth rates) while real GDP grew at 3%. But stocks have been much more volatile; the standard deviation of stocks, annualized, was 24%, compared to 5% for GDP. And as is well known, in the last 10 years GDP growth has slowed, while stock growth has accelerated. GDP in the last decade has only grown at an annual rate of 1.4%, about half its long-run performance.  During the same decade, the inflation-adjusted S&P 500 index grew at an annual rate of 11%. 

Depending on the year, about 40 to 50 percent of S&P 500 sales come from foreign countries.  In addition, the S&P 500 is heavily over-weighted in manufacturing and high tech, compared to the overall U.S. economy.

As GDP is a flow, and the S&P index is a stock, we might consider charting changes in the S&P index; or even better, total returns or earnings.  All these would be more volatile than the S&P index itself.  But it's the index value that's commonly cited by pundits and politicians, and so we'll stick with that convention here.

Exhibit 12

Let’s examine how strong (or weak) the link is between the stock market and the actual economy.  The stock market is extremely volatile, so we’ll use annual data as an ad hoc smoothing measure.  On the theory that stock markets are forward looking, we lag the stock market index by one year.

When we examine a plot of real stock price changes, and real growth in GDP, there is a very small positive correlation; about 8 percent of the variation in GDP is associated with variation in stock prices.  Taking these results at face value, for every 10 percentage points stock prices rise, GDP growth rises by 0.7 percent.

The bottom line?  The stock market is not the economy.  But these plots suggest that changes in stock prices that persist over a year or so can be viewed as a (weak) signal of economic performance.

Exhibit 13

Exhibit 13 presents the quarterly real S&P 500 index over time, on a background that illustrates the political control of the three units of two branches of government: the Presidency, the House of Representatives, and the Senate. We’ve had divided government for about 44 years, and undivided government for about 20. 

Which presidents faced opposition by two houses of Congress? Eisenhower, Nixon, Ford, Bush 41 all faced such opposition in much if not all of their terms. Bush 43 faced  such opposition at the end of his presidency. Among Democrats, Clinton faced Republican opposition in most of his two terms; Obama at the very end of his second term. 

Who had a "friendly" Congress, with both legislative houses of the same party? Truman was so favored in the beginning of his presidency; JFK and LBJ for most of their presidencies. Obama had both houses of Congress in his first two years. George W. Bush 43 had all Republican legislative houses in his first four and Trump in his first two years. 

How did the stock market behave during these presidencies?  Over time, Eisenhower had a bit of a stock market boom. JFK and LBJ not so much.  

Nixon and Ford had to look at a lot of declining stock prices in their daily briefs. Carter was, at best, "meh."

Reagan and Clinton watched a long boom unfold, the Bushes saw subpar performance.

Obama saw a large boom that continued under Trump.

Exhibit 14

Exhibit 14 is a similar chart, but examining real GDP per capita.  Again, from 1950 to 1980 there’s a lot of blue. For three decades after World War II Democrats dominated national politics, with just a few exceptions. The Reagan revolution ushered in a period where Republicans became much more competitive in presidential and legislative races; albeit competitive, not as dominant as the Democrats had been in the first half of our postwar period. 

In Exhibit 11 above, where we directly compare GDP to stock prices, we used total GDP; both are about the overall size of the economy. Here we have switched to GDP per capita, which strips out variance in population growth.  Population growth has been declining over recent decades. Either way we measure GDP, total or per capita, we find much less volatility in GDP than in the stock market.

Who missed recessions during their presidency? Only LBJ and Clinton. Kennedy and Obama inherited recessions that spanned one and two quarters, respectively, at the beginning of their presidencies. 

Exhibit 15

Exhibit 15 presents the final of our triad of time series presentations by presidency.  In some respects it's the most startling of the three, especially to younger students (or older ones with fading memories).

Truman's presidency spanned a short volatile post-war period; it's remarkable today to see the acceleration of inflation in the sixties and seventies under presidents of both parties (but with Democratic legislatures, most of the time, for what that's worth).  As noted above, Paul Volcker, with support, implicit and sometimes explicit, from Jimmy Carter and Ronald Reagan, wrung inflation out of the system, albeit at a significant cost in lost short run output and employment.

Some highly preliminary bottom lines

So, did Democrats have high growth because they were economic geniuses?

Put another way, is it better to be lucky, or to be good?

(In general, the correct answer: yes.)

Exhibit 16 presents the averages of our three indicators by the control of three units of government.

Exhibit 16

Does divided government matter?  Taking these numbers at face value - which in reality, we SHOULD NOT:

• Democrats are associated with the highest level of growth.
• Republicans appear to be the champs at controlling inflation.
• Divided government shows the best stock market result - if you are talking about 2 R's and 1 D.
• Divided government shows the worst stock market result - if you are talking about 1 R and 2 D's.

My conclusion - tables like these are sources of the myths. The Law of Small Numbers suggests we read too much into tables like this.  The law of small numbers, according to Daniel Kahneman:

"We often think a small sample size is equal to a large sample, even though a small sample is inherently not as trustworthy. We pay more attention to the content of messages than to information about their reliability. and as a result end up with a view of the world around us that is simpler and more coherent than the data justify."

There have been 13 presidents since WWII. Not a very large sample. And a lot going on in the economy besides who's president. Or who controls the House or Senate.  Hey, what's the Fed been up to? OPEC? House prices always go up, right? Pandemic? What pandemic?

The Wall Street Journal quotes UBS Global Wealth Management exec Tom Mcloughlin on these data exercises:

"The bottom line is that the sample size isn't large enough to draw a firm conclusion. As a colleague said to me. 'Come back in 500 years and we'll talk..."

So: Is divided government" good for the economy?

In fact, the fastest average growth occurred under the "All-Democratic" watch; the lowest inflation occurred when the Republicans ruled unchallenged. It's hard to see any real story here, in the simple data analysis, other than to be reminded of the Democrats' postwar political advantage: they held 2 or 3 of the institutions for 184 quarters: the Republicans held 2 or 3 for only 110 quarters.

And the Democrats dominated in the early postwar periods of high growth and high inflation.  The Republicans have done much better electorally in the recent relatively slow growth, low inflation era.

My bottom line for the moment: I don't see any obvious economic advantage to divided government in the data; nor do I see any obvious disadvantage. Perhaps as we study more of the scholarly literature and look at some other variables like employment, the distribution of income, and changes in our fiscal position, I'll have more to report.

Remember, we haven't said anything about distribution, between labor and capital, between high and low income, by education, by rural and urban, by sector (manufacturing, services. etc.) A future post could examine some of these.  My colleague Richard Green suggests examining the Gini coefficient, a common measure of income distribution.  A related calculation would be to update Exhibit 17, Larry Bartels' tabulations of family income growth by different quintiles of the income distribution.  Bartels found that relative growth at the bottom of the distribution was faster under Democrats.  In addition to adding a few more years of Obama's presidency, and Trump's, it would be useful to address how taxes and transfers (not included in Bartel's Census data) have affected distribution.

   

Exhibit 17

Exhibit 18, from my presentations on the pandemic, reminds us of the dangers of focusing too much on aggregates and not enough about distribution when thinking about the current and future U.S. economy:

Exhibit 18

Are the politics of the past a reliable guide to our future?

Exhibit 19

Let’s borrow the investment banker’s favorite boilerplate: “past performance is not necessarily a guide to future performance.” Remember how much the policies and culture of political parties have changed over the last half-century. 

It’s often observed recently that such prior conservative stalwarts as Ronald Reagan, Richard Nixon or even Barry Goldwater would have a hard time finding a home in today’s Republican Party. 

After the passage of the 1960s Civil Rights acts, LBJ famously observed that passage would mean the South would be lost to the Democrats for a generation or more. That has turned out to be the case for more than half a century. The post-1960s realignment saw the eventual decline of moderate and principled conservative Republicans in the Northeast and Midwest typified by politicians like George Romney, William Scranton, Tom Ridge, Bob Dole, Tommy Thompson and Margaret Chase Smith. Southern Democrats switched wholesale to the Republican Party (e.g. Strom Thurmond, John Tower, John Connolly), despite the fact that the Civil Rights Acts were passed with the aid of moderate midwestern and northeastern Republicans.  Nixon and Bush and others famously followed the “southern strategy” of appealing to racial resentment, exemplified by Lee Atwater. 

Many other examples exist of presidents failing to fit neatly into today's partisan boxes.  Richard Nixon championed several programs that today would be considered progressive, including a (never enacted) universal basic income, extended Social Security and Medicare, and created the Environmental Protection Agency. Bill Clinton pushed through welfare reform in alliance with conservative Republicans in the Congress. 

Today’s Republican Party may be about to experience an event similar to the split of the Whig party in the 1850s, when the party’s slavery and antislavery factions broke apart after the Kansas-Nebraska Act.  Eventually anti-slavery Whigs joined the Republican party.  Still reluctant to defect to Andrew Jackson’s legacy and their traditional rivals, the Democratic party, many pro-slavery Whigs joined the (often) pro-slavery (always) anti-immigrant “Know-Nothing” party. 

Some of the roots of the Trumpist faux-populist wing of today’s Republican party can be seen in Republicans like Patrick Buchanan, Joe McCarthy and Newt Gingrich, but also nominal Democrats like George Wallace, who in turn can trace their roots back to Huey Long, William Jennings Bryan and Andrew Jackson. 

Democrats shouldn't take any comfort from the Republican Party's current (temporary? permanent?) descent into madness.  The Founders famously feared the rise of "factions" (parties), but for over two centuries, competition between two major parties that (mostly) accepted each other's legitimacy has served the country well. A Republican Party that totally splinters, or that finally gives up on serious efforts to appeal to a "bigger tent" than the Trumpist wing, may not only threaten healthy competition but also could well exacerbate serious divisions in the Democratic Party.  As a recent president is fond of saying, we'll see what happens.

Readings and Resources

Readers who would like a PowerPoint deck with the charts used in this posting can download it here.

Acharya, Avidit, Matthew Blackwell, and Maya Sen. "The Political Legacy of American Slavery." The Journal of Politics 78, no. 3 (2016): 621-41.

Ahamed, Liaquat. Lords of Finance: The Bankers Who Broke the World. Penguin Press, 2009.

Alvarez, R Michael, and Jonathan Nagler. "Economics, Issues and the Perot Candidacy: Voter Choice in the 1992 Presidential Election." American Journal of Political Science  (1995): 714-44.

Bartels, Larry M. Unequal Democracy: The Political Economy of the New Gilded Age. Second Edition ed.: Princeton University Press, 2016.

Chernow, Ron. Alexander Hamilton. Head of Zeus Ltd, 2016.

Critchlow, Donald T. American Political History: A Very Short Introduction. Vol. 420: Oxford University Press, USA, 2015.

Easterly, William, Michael Kremer, Lant Pritchett, and Lawrence H Summers. "Good Policy or Good Luck?". Journal of monetary economics 32, no. 3 (1993): 459-83.

Fair, Ray C. "Econometrics and Presidential Elections." Journal of Economic Perspectives 10, no. 3 (1996): 89-102.

Fair, Ray C. Predicting Presidential Elections and Other Things. Second Edition ed.: Stanford University Press, 2011.

Fischel, William A. "An Economic History of Zoning and a Cure for Its Exclusionary Effects." Urban Studies 41, no. 2 (2004): 317.

Janda, Kenneth. A Tale of Two Parties: Living Amongst Democrats and Republicans since 1952. Routledge, 2021.

Kahneman, Daniel. Thinking, Fast and Slow. Farrar, Straus and Giroux, 2011.

Kane, Tim. "Presidents and the US Economy from 1949 to 2016." Stanford, Hoover Institution Working Paper, 2017.

Kuziemko, Ilyana, and Ebonya Washington. "Why Did the Democrats Lose the South? Bringing New Data to an Old Debate." American Economic Review 108, no. 10 (2018): 2830-67.

Lewis, Michael. The Fifth Risk: Undoing Democracy. Penguin UK, 2018.

Lewis-Beck, Michael S, and Mary Stegmaier. "Economic Determinants of Electoral Outcomes." Annual review of political science 3, no. 1 (2000): 183-219.

Lowenstein, Roger. America's Bank: The Epic Struggle to Create the Federal Reserve. Penguin Press, 2015.

Malpezzi, Stephen. "Cities and Economic Success: Some Lessons from the United States." Report to Cities and Communities/Infrastructure Canada, 2007.

———. "Local Economic Development and Its Finance." In Financing Economic Development in the 21st Century, edited by Sammis White and Zenia Z Kotval: M.E. Sharpe, 2012.

———. "Residential Real Estate in the U.S. Financial Crisis, the Great Recession, and Their Aftermath." Taiwan Economic Review 45, no. 1 (2017): 5-56.

———. "The Savings and Loan Crisis of the 1980s: Prequel to the Great Financial Crisis." Wisconsin School of Business, Lecture Notes, 2016.

Mann, Thomas E., and Norman J. Ornstein. It's Even Worse Than It Looks: How the American Constitutional System Collided with the New Politics of Extremism. Basic Books, 2012.

Mead, Walter Russell. "The Jacksonian Revolt: American Populism and the Liberal Order." Foreign Aff. 96 (2017): 2.

Rudolph, Thomas J. "Who's Responsible for the Economy? The Formation and Consequences of Responsibility Attributions." American Journal of Political Science 47, no. 4 (2003): 698-713.

Shiller, Robert J. Narrative Economics: How Stories Go Viral and Drive Major Economic Events. Princeton University Press, 2020.

Silber, William L. Volcker: The Triumph of Persistence. Bloomsbury Publishing USA, 2012.

Snowberg, Erik, Justin Wolfers, and Eric Zitzewitz. "Partisan Impacts on the Economy: Evidence from Prediction Markets and Close Elections." The Quarterly Journal of Economics 122, no. 2 (2007): 807-29.

———. "Party Influence in Congress and the Economy." Quarterly Journal of Political Science 2 (2007): 277-86.

Steil, Benn. The Battle of Bretton Woods: John Maynard Keynes, Harry Dexter White, and the Making of a New World Order. Princeton University Press, 2013.

Tilley, James, and Sara B Hobolt. "Is the Government to Blame? An Experimental Test of How Partisanship Shapes Perceptions of Performance and Responsibility." The journal of politics 73, no. 2 (2011): 316-30.