Author: Ed Egan

Dr. Edward J. Egan is an applied micro-economist. He received his Ph.D. from the Haas School of Business, U.C. Berkeley, in 2012, where he specialized in business economics, finance, and public policy. He currently lives in Stowe, Vermont, with his wife, Lauren, and his two Border Collies, Noodles and Ralph.

Categories
AI Econ Consulting

Exploring Economic Consultants’ AI Capabilities for Litigation 

AI’s Value for Litigation Experts

This article compares 12 US economic consulting firms’ Artificial Intelligence (“AI”) capabilities, particularly those used to support litigation engagements. It uses the umbrella term AI to include Machine Learning (“ML”), computational economics, and other modern computer science methods.1

In litigation engagements, leveraging AI can create valuable additional insights and reduce analysis costs, increasing the chances of winning a case and making cases more profitable. So, it is unsurprising that around half of US economic consulting firms have begun hiring in-house engineers and scientists and adding new management to embrace modern computer science methods to support their antitrust, bankruptcy, IP, M&A, securities, regulatory, and other practices.

The integration of AI in litigation, disputes and investigations has undoubtedly altered legal practices, offering unprecedented efficiencies and findings.

Jon Chan, Senior Managing Director, FTI Consultants

The State of Economic Consultants’ AI Capabilities

Economic consultants’ AI capabilities for litigation currently appear nascent and mixed. None of the firms I reviewed had anything like McKinsey’s Quantum Black, BCG’s X, Bain’s Vector Digital, or even FTI’s Digital, which are closer to the Big Four Accounting Firm‘s AI groups and joint ventures.2

Nevertheless, economic consulting firms do seem to be racing to build AI capabilities.

Almost all economic consulting firms now have big data analytics capabilities (in-house or in the cloud), most offer data visualization, and around half have used some AI, broadly defined. Among those using AI, the most popular application was Natural Language Processing (NLP) for semantic or sentiment analysis. Likewise, around a third of firms have performed ML-based optimizations or simulations or offer predictive analytics. Out of the 12 firms I reviewed, four mention generative AI, three mention geospatial analysis, and just one mentions Bayesian methods.

Cornerstone recently started the first applied research group in this area, and, at present, just three firms – Cornerstone, Brattle, and AG – have material AI capabilities. However, none appear to fully understand the very large and rapidly expanding AI space. Keystone‘s recent aggressive hiring might change things over the next few years, either directly or (more likely) by spurring competition, but it is starting as one of the smallest firms. For now, the best economic consulting AI group is still learning to use modern methods; they are far from contributing to their development.

Ranking Economic Consultants’ AI Capabilities

The table below ranks 12 US economic consulting firms using a subjective score from one to five to measure their AI capabilities in litigation support. (See the Methodology section for more information). The table doesn’t include NERA or HKA because I couldn’t find any information about their AI efforts in any context.

RankScoreFirmEst. EmployeesGroup/Center
14.8Cornerstone Research700+Data Science Center, Applied Research Center
24.7The Brattle Group500+Data Analytics
34.5Analysis Group1,200+Data Science & Statistics
44.2Compass Lexecon800+Data Science
54.1Econ One Research100+Data Analytics
64*Berkeley Research Group1,200+AI/ML
64*Keystone Strategy150+Core AI
83.8Bates White300+Data Science & Statistics
93.7AlixPartners2,000+Artificial Intelligence
103.3**Charles River Associates800+Analytics
112.7**Secretariat300+Data Analytics & Strategy
122.5Edgeworth Economics100+Data Analytics

*Score is based mainly on private knowledge.
**Score is driven primarily by the lack of readily available material online.

The subjective scores fall somewhat naturally into four groups:

  • Cornerstone, Brattle, and AG are in the leading group and have material AI capabilities;
  • Compass, Econ One, BRG, and Keystone are in the second group and are rapidly developing AI capabilities;
  • Bates White and AlixPartners are in the third group with nascent AI capabilities, at least for litigation support;
  • And the remaining firms either have yet to enter the race or do not publicly disclose their capabilities.

The Best AI Capabilities: Cornerstone

Cornerstone Research stands out from the other economic consulting firms with its two Centers of Excellence, one in Data Science and the other in Applied Research. These centers support every aspect of Cornerstone’s business, and I quickly found many clear descriptions of how they have used cutting-edge AI/ML to support litigation.

Although Cornerstone was one of just two firms that provided content mentioning neural network transformers as a building block technology, there’s a strong sense of early days. For example, their Applied Research Center, which has a (small) team of in-house data science PhDs, doesn’t mention any academic experts in AI/ML, computational economics, Bayesian statistics, information theory, or related fields.

The subject matter experts at our Applied Research Center work closely with the data scientists at our Data Science Center on critical issues surrounding AI, including using AI methods to produce new evidence on cases, and understanding its implications on the policy and litigation landscape.

Cornerstone Research, Applied Research Center

The Next Best: Brattle and AG

The Brattle Group and Analysis Group (AG) were the next clear leaders among economic consultants in adopting and using AI methods. They appear not far behind Cornerstone and may be competitive or even ahead, but their offerings, especially AG’s, are less well-branded.

Both Brattle and AG were explicit that they integrate their AI capabilities across their practices and provided good examples for litigation support.

These statistical techniques [including machine learning, natural language processing (NLP), and data visualization] can be applied in litigation related to antitrust and competition; intellectual property; general causation assessment; and securities, financial products, and institutions; among other areas.

Analysis Group, Data Science & Statistical Modeling

Brattle and AG have used NLP and related technologies extensively, and it seems likely that consideration of their application to litigation is now well practiced. However, the application of other AI/ML technologies seemed less systematic. Brattle has used simulations and generative AI; AG has done projects using optimization and predictive analytics.

The Rest: A Scattering of AI Capabilities

From Compass Lexicon in 4th place down to Keystone Strategy in 8th, these economic consultants provide only a scattering of AI capabilities and notably fewer litigation support applications.

  • Compass’s Data Science page has a nice diagram, three other media items, and nine sentences of text. Even with a picture worth 1,000 words, it is underwhelming. However, if you search hard enough, you can find useful descriptions of their work using Big Data, NLP, LLMs, and GIS.
  • Econ One‘s Data Analytics page has lots of text and images, hitting a fair number of the terms of interest, but is light on semantic content. Its blog posts are in the same vein.
  • BRG‘s Artificial Intelligence & Machine Learning page has an asterisk next to its “Our Experience” heading, which leads to a footnote saying, “Includes professionals’ experience prior to joining BRG.” Nevertheless, BRG has been hiring AI and data engineers in recent months. (It hasn’t announced new leadership in AI as yet.). BRG is a firm that understands dynamic capabilities and absorptive capacity; as the third biggest economic consultancy in the sample, it is one to watch.3
  • Keystone has a press release describing its new Core AI group, which launched in 2023. Three former Amazon executives lead the group: Pat Bajari directs the economic experts, Devesh Mishra presides over the technologists, and Aarif Nakhooda is the finance chief. Keystone states that Core AI supports clients of their Global Economic and Technology Advisory (ETA) group. Anecdotally, however, they are currently working on forecasting and big data projects for strategy clients.

On the Bench: Yet to Embrace AI

With scores below four, I rate the next two economic consultants as “on the bench” for their AI capabilities for litigation.

Bates White appears to be the best of this set. Its Data Science page links to five topic area pages, four with case highlights. The pages have good, concise writeups and settlement descriptions. Bates White leverages high-level products from Google, Amazon, Apache, Adobe, and others rather than building things in-house. However, the products they have used are often five to ten years behind the frontier, and AI/ML doesn’t get a mention.

AlixPartners is a stark contrast to Bates White. The page advertising its AI division says AI/ML everywhere and mentions optimization, predictive analytics, and Bayesian methods (yay!). However, AlixPartners’ Economic Consulting team, which falls under its Investigations, Disputes & Advisory Services practice, only makes vague allusions to its use of modern methods.

No AI or Too Little Information

The final three economic consultants either haven’t embraced AI or don’t provide helpful information about their use of modern methods.

Charles River Associates‘ Analytics in Disputes & Investigations page has remained unchanged since January 2021, and Secretariat‘s website is in flux after a series of acquisitions.4 Both firms surely have much greater sophistication than the support for “big data and algorithms” that their websites imply.5 However, I couldn’t find AI engineer job postings or other indications of developing capabilities either.

CRA expertly tackles the daunting volume of social media by employing unique social media analytics tools which efficiently and algorithmically capture relevant information to provide our clients with a deeper understanding of topics and individual subjects of investigation.

CRA, Analytics in Disputes & Investigations

Edgeworth Economics is the only consultancy that mentions working with decommissioned mainframes.6 If you need to access some “big” data from the 1950s, these are your people.

We have extensive experience and expertise working with a variety of systems, including decommissioned mainframes, legacy systems, SAP, and Oracle.

Edgeworth Economics, Data Analytics in Litigation and Compliance

Finally, I couldn’t find any helpful information about AI/ML use at NERA or HKA, so I omitted them from this analysis.

Methodology

I generated a list of US economic consulting firms providing economic experts for litigation and used Perplexity.ai to estimate their employees.7 I excluded firms with less than 100 employees. I also excluded management consulting, accounting, or other firms with a primary purpose other than economic consulting, although such firms often provide economic litigation experts. If a firm is missing, please let me know.

I reviewed each firm’s AI/ML capabilities, partnerships, and experts, focusing on whether and how they had applied AI/ML in litigation support. In most cases, my assessment was based on a review of a firm’s web pages, LinkedIn pages, and other publicly available information. However, I had some private knowledge of firms’ efforts in a few cases, particularly for Keystone and BRG.

I assigned each firm’s AI capabilities a subjective score on a scale of one to five, with five being the best. No firm got a one because of grade inflation. Online information can be outdated and incomplete, so these scores represent the firm’s apparent capabilities rather than actual ones. Nevertheless, they contain valuable information, especially in conjunction with the text descriptions and links.

I was particularly interested in specific capabilities: AI (including ANNs, generative AI, etc.), Machine Learning (“ML”), computational economics, predictive analytics, Big Data, cloud computing, optimization, simulation, geospatial or GIS, visualization, NLP (including content/sentiment analysis, use of LLMs, applications to eDiscovery, etc.), unstructured/semi-structured/structured data, and so forth. In general, the more terms a firm mentioned, the more coherent and detailed they were in their explanations, and the greater the evidence that they have actually used the technology to support litigation, the higher their score.8

Footnotes
  1. There’s a great debate on nomenclature around AI, ML, computational economics, predictive analytics, (big) data science, and other technologies. The distinction matters for economic consultants, particularly those supporting the litigation process, as they enhance or argue economic efficiency, profit, and welfare; their foundation is truth grounded in economics. Nevertheless, AI is a de facto standard umbrella term, and black-box AIs, like LLMs, can create measures used in meaningful economic analyses. ↩︎
  2. Economic consultancies are smaller firms with a few hundred to several thousand employees. In contrast, management consultants have tens of thousands of employees, and the accounts have hundreds of thousands. ↩︎
  3. BRG’s eDiscovery service was developed in-house before many component tools became available as online services, suggesting deep capabilities in this space. ↩︎
  4. Secretariat acquired Economists Incorporated in July 2021 and Intensity Corporation in Feb 2023. ↩︎
  5. I found CRA’s AI page, their eDiscovery service, and a page discussing a merger simulation model. For Secretariat, I found evidence of big data capabilities, their eDiscovery, and merger simulation services. ↩︎
  6. NASA powered down its last mainframe in 2012, three years before OpenAI was founded. ↩︎
  7. It was clear that some of Perplexity’s employee counts were out-of-date, but I couldn’t readily find anything that was better without a subscription. ↩︎
  8. I treated some terms as partially relevant – for example, almost half of all firms mentioned doing merger simulations, which generally do not require modern AI/ML. ↩︎
Categories
Macroeconomics Vermont

A Solution to Vermont’s Declining Economy

Small, Dwindling, and Dead Last

Vermont has pockets of prosperous haves in amongst fields of withering have-nots. Overall, though, the state’s economy has foundered for a long time. If you order America’s states on almost any economic measure, including those per capita or relative to the U.S. average, you’ll find Vermont near the bottom.

For Gross Domestic Product (GDP), the foremost of economic measures, data from the U.S. Bureau of Economic Analysis shows Vermont ranked 51st – dead last – for 18 years now. (This will change in 2027 when Wyoming, which has been contracting almost continuously since 2008, will take the trophy as America’s smallest economy.) Vermont’s small and dwindling population barely helps its GDP per capita, which is ranked 36th and falling. A decade ago, Vermont produced more per person than Utah; today, Vermont is being overtaken in per capita production by Missouri.

Bad and Low-Quality Policy

Graph showing Vermont's declining economy with growth relative to the US average rate heading below 50%.

Economists describe a part of Vermont’s woes as “structural.” The Green Mountain state has a small population, is predominantly rural, has no seaport or major commercial transport route, isn’t endowed with oil and gas or mineral wealth, and so on. No policy can change these things, but none of these constraints are fatal in an innovation economy.

A structural disadvantage makes adopting good, high-quality policies to grow Vermont’s economy all the more crucial. Unfortunately, the state’s current policies mostly don’t foster development and are almost always poorly designed and implemented. Bad policy is a crucial part of why Vermont languishes at the bottom of startup rankings.

Solving Vermont’s Declining Economy

Vermont has teetered on the edge of permanent recession for a decade… A data-driven, evidence-based policy process can maximize growth.

Over the last two decades, Vermont grew 2.6% slower than America as a whole and had the 10th worst long-term growth rate among the American states. This crisis long predates the pandemic, which caused a greater contraction in Vermont than in most other states. From 2009 to 2019, the state’s annual growth exceeded inflation by less than one percent: Vermont has teetered on the edge of permanent recession for a decade.

However, there is a solution to Vermont’s declining economy: A data-driven, evidence-based policy process can maximize growth. Simply put, Vermont should use economic science to evaluate policies and choose the best. However, there are big challenges in implementing this kind of policy process in the Green Mountain State.

Taking on Economic Corruption

Vermont has a long history of not doing the math. So, when Vermonters start using economics to analyze policy, they will find glaring past mistakes. Moreover, economic corruption thrives when things aren’t measured and assessed. In 2015, Vermont was ranked 37th and received a D grade for State Integrity; it has made little progress in reform. So, some institutions and individuals have strong incentives to resist changes that bring accountability.

A similar argument applies to Vermont’s policymakers. Some officials have implemented policies that undermine markets, destroy value for Vermonters, or waste taxpayer money. Some legislators have campaigned on or voted to support policies that make Vermont worse off or offer little benefit compared with their cost. And some administrators have ignored or abandoned policies grounded in economic science because their departments cannot understand them. Moreover, policies further from the political middle are less likely to be backed by science, which politicizes science’s application. Vermont would have to rise above the ensuing politics.

Recruiting Economists

Vermont can do the math and grow the pie!

Vermont has limited capabilities to design, implement, and assess policies in a data-driven and evidence-based fashion. None of its legislators or executive officers hold a Ph.D. in economics. Vermont has no Council of Economic Advisors to the Governor nor a Legislative Budget Office ready to analyze data and model solutions. Even the Department of Economic Development and the Vermont Economic Progress Council have no economists.

Fortunately, Vermont doesn’t need to be a policy innovator to improve; it just needs to avoid proven mistakes and embrace well-established best practices. There are enough economists in the state’s colleges and private sector to make a noticeable impact. Many will provide help pro bono, in both main senses of the phrase, and the same changes that reduce economic corruption lower the barriers to their participation. In summary, Vermont can do the math and grow the pie!

Categories
Rankings Startup Ecosystems

The Top 200 U.S. Startup Cities for 2020

The 200 top U.S. startup cities for venture capital (VC) investment for 2020 provide few surprises. The top four startup cities are the same for the third year in a row, and San Francisco holds on to its top spot for its 14th year. However, there are some changes to explore from the industry’s ongoing evolution and the COVID-19 crisis.

RankLocation$mil.DealsFunded+/-
1San Francisco, CA12,4822161,3280
2New York, NY7,0561951,1780
3Boston, MA3,651413040
4Cambridge, MA4,565402270
5Seattle, WA1,850412302
6San Diego, CA3,230381962
7Palo Alto, CA1,35231259-2
8Mountain View, CA4,645211434
9Los Angeles, CA1,27929248-3
10Austin, TX79927229-1
11Chicago, IL818261891
12San Jose, CA94523127-1
13Irvine, CA3,077145919
14South San Francisco, CA1,78114724
15Philadelphia, PA75713131-5
16Redwood City, CA1,609111111
17Santa Clara, CA76014902
18Denver, CO70916827
19Menlo Park, CA6241695-5
19San Mateo, CA87511103-5
21Atlanta, GA55117102-5
22Houston, TX65613712
23Santa Monica, CA4521294-3
24Berkeley, CA616125412
25Boulder, CO4141373-2
25Oakland, CA4291371-4
27Columbus, OH57395023
27Sunnyvale, CA372985-5
29Waltham, MA49674127
30Salt Lake City, UT4708357
30Washington, DC28110534
32Bellevue, WA657345-5
33Burlingame, CA593531-4
34Dallas, TX268943-6
35Portland, OR181853-9
36Baltimore, MD17265042
37Fremont, CA4044231
38Emeryville, CA41442115
38Pittsburgh, PA2372135-7
40Culver City, CA682225-10
41Somerville, MA2804250
42Durham, NC167539-4
43Campbell, CA2395240
44San Carlos, CA2587200
44Wilmington, DE14192814
46Arlington, VA11392720
47Los Altos, CA158335-7
48Florence-Graham, CA57134833
49Jersey City, NJ30441421
50Nashville-Davidson, TN128341-2
51Miami, FL12052418
52Ann Arbor, MI109341-20
52Tampa, FL32822028
54Indianapolis city, IN80632-20
55Raleigh, NC73733-4
56Milpitas, CA15951448
57Carlsbad, CA114324-16
58New Haven, CT19621813
59Lincoln, NE17721835
60King of Prussia, PA13031640
61Sandy Springs, GA363212-1
62Sacramento, CA10431651
63Walnut, CA1452178
64Charlotte, NC596121-20
64Goleta, CA28221158
66Tysons Corner, VA77226-17
67Newton, MA9621684
68El Segundo, CA102215-3
69Newport Beach, CA45211334
69Phoenix, AZ58218-23
71Rockville, MD128211142
72Cupertino, CA6421740
73St. Louis, MO37235-12
74Hawthorne, CA2,3362553
75Burlington, MA32421-21
76Minneapolis, MN25523-17
77Scottsdale, AZ10311621
78Kirkland, WA52211100
79North Fair Oaks, CA30625147
80Framingham, MA10711512
81Cary, NC1,79316358
82Carmel, IN3231229
83Plano, TX145110-16
84Cleveland, OH1932346
85Eden Prairie, MN26917192
86West Hollywood, CA29213-31
87Pasadena, CA22218-31
88St. Petersburg, FL5726263
89South Plainfield, NJ16034539
90Gaithersburg, MD13817-19
91Newark, CA971895
91Pleasanton, CA17316-28
93Orlando, FL3129121
93Rochester, NY50112-17
95Wellesley, MA12617-24
96Hillsborough, CA23424532
97University, FL18924278
98Madison, WI14230-13
99Santa Barbara, CA69187
100Boca Raton, FL651857
101St. Paul, MN5219156
102Mercer Island, WA1512447
103Mill Valley, CA1931028
104Woburn, MA32114-57
105Albuquerque, NM11320-1
106Alameda, CA2129-17
107Aliso Viejo, CA301121
108New Orleans, LA32111-24
109Addison, TX2228284
110Marina del Rey, CA243692
111Dover, DE2336429
112Boise City, ID20283
113Skokie, IL1638103
114Lake Forest, CA5216355
115Albany, NY114103
116Richmond, VA2411147
117Nashua, NH7115322
118Beverly Hills, CA14210-39
119Bend, OR3517129
120Providence, RI18113-4
121Irving, TX2618307
122Lewes, DE2035169
123Charleston, SC511515
124Chapel Hill, NC2325416
125Solana Beach, CA4615175
126Long Beach, CA2325414
127Centennial, CO2325204
128Birmingham, AL251795
129Reston, VA7218-12
130Fort Collins, CO4215165
131Santa Fe, NM1427-17
132Calabasas, CA271644
133Coral Gables, FL3615137
134Alpharetta, GA9210266
134Santa Clarita, CA6514256
136Stanford, CA112720
137Omaha, NE4423-41
138Provo, UT300014-86
139Greenwood Village, CO1245489
140Eagleview, PA5514109
140Hayward, CA234016-65
142Northbrook, IL2424253
143Lexington, MA220014-81
144Burlington, VT121106
145Gainesville, FL4214232
145Morrisville, NC191662
147Charlottesville, VA1111122
147Westport, CT1916240
149Missoula, MT2315154
150West Palm Beach, FL2315106
151San Antonio, TX8113-63
152Hoboken, NJ1225337
153Draper, UT1534591
154Foster City, CA29308-86
155Winter Park, FL6313473
156Bedford, MA1516-54
157Redmond, WA27208-26
158Fayetteville, AR627135
158Union City, CA1724382
160Basking Ridge, NJ5713245
160Creve Coeur, MO18209-35
162San Bruno, CA25008-1
163Daly City, CA5284
163Tucson, AZ711153
165Industry, CA5213463
166San Ramon, CA7701349
167Fulton, MD1018-33
168Huntington Beach, CA4513321
169Farmington, CT429249
170Memphis, TN222568
171Cottonwood Heights, UT1116-72
171San Juan Capistrano, CA5114197
173Watertown Town, MA13708-91
174Glendale, CA719226
175Portland, ME917-34
176Santa Cruz, CA62505263
177Arlington, MA72558
178Paradise, NV635450
179Lehi, UT619-102
179Mesa, AZ2014128
179Portsmouth, NH2014361
182Chandler, AZ526307
183Newark, DE619-31
183Trumbull, CT1814357
185San Luis Obispo, CA1024443
186Hoover, AL3013222
187Fort Worth, TX171495
188Kansas City, MO221117
189Vista, CA261377
190White Plains, NY11331034
191San Leandro, CA18605147
192Reno, NV518208
193Corte Madera, CA2413435
194Saratoga, CA7906-100
195North Bethesda, MD5912549
195Orem, UT425266
197Silver Spring, MD425-58
198Poway, CA5512546
199Bethlehem, PA22951
200Manhattan Beach, CA51693

Trends for Startup Cities

US Growth Venture Capital 1985-2020
Percentage of VC in the Top 10 Cities
Houston, TX, Startup City Rank 1985-2020
Vermont Startup U.S. State Rank 1985-2020

Breaking Records

Twenty-twenty was a record year in terms of dollars invested, though a small number of very high-value deals enlarged the aggregate amount. A trend of billion-dollar rounds that began with Lyft in 2017 has continued into 2020. (Yes, Facebook had a billion-dollar round in 2011, but there weren’t any others for six years.) Some billion-dollar rounds are, at least notionally, seed or early-stage investments, like those into JUUL Labs, Quibi, and Rivian Automotive. Most are later stage rounds supporting firms like Uber, WeWork, and Epic Games as they try to find their exits.

There were four billion-dollar rounds in 2020. These included investments in Rivian, Waymo, SpaceX, and Epic, who had already taken a billion-dollar round in 2018. Epic Games is the main force behind Cary’s, and North Carolina’s, drive up the rankings.

COVID-19 Bump

Even without the billion-dollar rounds, U.S. venture investment levels are now above the dot-com boom’s heights in both nominal and real terms: Both 2018 and 2019 beat 2000 in nominal investment amounts. Twenty-twenty was the first to boast a higher amount than 2000’s U.S. venture capital investment adjusting for inflation.

There were reasons to think that the COVID-19 pandemic might cause a retrenchment in investment. In particular, the U.S. stock markets collapsed from February 12th to November 16th, 2020. Concern over returns to capital might have led L.P.s to reconsider new investments in alternative assets. There was also speculation that some L.P.s might renege on existing commitments to venture funds. Instead, the market for venture capital seems to have had a COVID-19 bump. 

Concentration Among Startup Cities

America has had a long-term trend towards greater concentration of venture capital dollars, deals, and startups within the top 10 startup cities. Over the last decade, the share of venture capital dollars invested in the top ten startup cities rocketed up. It went from about 30% in 2010 to almost 60% in 2018. Other measures of venture activity followed a similar trend. But this seems to have changed in 2020.

Greater concentration could be problematic if some cities are at or past their efficient capacity. For example, Palo Alto has the highest startup density in the U.S. and seems over-crowded with startups. (New York, though, looks like it still has plenty of room for more.) Then greater equality in venture capital across startup cities would enhance growth. So, it’s somewhat enheartening to see the top 10 startup cities’ share back below 50%. Presumably, lockdowns, travel restrictions, and everyone getting used to teleconferencing reduced the benefits to locating in the Bay Area or Route 128 ecosystems.

Is Houston a Startup City?

Houston, Texas, ranked 22nd among U.S. startup cities in 2020. That’s the Space City’s highest ranking since 2002. In 2016, it was ranked 54th, so Houston’s startup ecosystem has had an astronomical recent rise. Moreover, the city’s 2020 ranking components are now fairly evenly balanced: Houston ranked 19th for new deal flow, 24th for dollars invested, and 25th for active startups. (That new deal flow is driving Houston’s ranking suggests good things to come; follow-on rounds should assure more money and active startups in subsequent years.)

Why am I still reluctant to describe Houston as a startup city? Because Houston is the 4th largest metro area by population, the 7th largest by GDP, and boasts that it is home to 4,600 energy-related firms. It contributes just under half a trillion dollars to the U.S. economy each year.

In 2020, H-town added 13 new startups to its venture ecosystem, bringing its total headcount of actively-financed firms to 71. These firms collectively received a little over $650m. So, until someone works out how high-growth-high-tech and oil-and-gas go together, Houston will remain just the Energy Capital of the World. (Also, the space sector moved to California several decades back.)

A Historic Fall

I have written extensively about Houston’s fall in the rankings and the policy initiatives that exacerbated it, as well as the attempts to reform Houston’s startup economy that followed.

The short story is that Houston realized it had a problem with creating and retaining new high-growth, high-tech firms in the late 1990s. The city’s “solution,” announced in 1998 and launched in 1999, was the Houston Technology Center. The HTC then lead Houston to the largest and fastest ranking decline of any former top 20 startup city.

Fortunately, starting around 2011 and picking up pace in 2014, some new initiatives took hold in Houston. These were a mix of private firms and non-profits that were (mostly) unaffiliated with the HTC. Then, in 2016 a group of VCs and serial entrepreneurs with ties to the city started Station Houston, the city’s first startup hub.

Policy Takes Time

It takes a couple of years for a new initiative to take effect: On average, a startup is just under a year and a half old when it receives its first seed round, and over two and a half if its first round is a Series A. So the effects of policy in 2018 are just now starting to be felt. Twenty-eighteen was a big year for bad startup policy in Houston:

Market Forces

Of course, many other things were going on in Houston’s startup ecosystem in or around 2018, and some of them were positive. So, on balance, it looks like Houston’s prognosis is fair-to-good, despite its abysmal policy history.

First, deal flow surged to record highs in 2018. Houston was getting around six new deals each year from 2010 to 2016. In 2017, Houston got nine first-time venture investments, and in 2018 it got 17, before falling back to 13 new deals each year in 2019 and 2020. The two drivers of this boom were Station’s efforts before its takeover and Houston’s biotech scene, which finally found some legs: Liongard and Arundo Analytics were both Station residents that secured a first-round of VC in 2018 (and went on to raise almost $50m combined), and life science startups Vivante Health, Wellnicity, and Trilliant Surgical all got their first rounds that year. (Data Gumbo, a client of The Cannon, also got its first round in 2018.)

Second, many for-profits, non-profits, academics, and policymakers across the state were working hard to build high-growth, high-tech expertise and capabilities in Houston in 2018. This effort has translated into a wealth of new initiatives, programs, and ecosystem support organizations in 2020. Credit is particularly due to Lori Vetters, who led efforts to reach out to non-Houston accelerators despite being shunned by many Houston startup scene members for her lack of high-growth, high-tech pedigree. (Lori replaced Walter Ulrich and tried to reform the HTC.) Both the Texas Foundation for Innovative Communities in Austin and my team at the McNair Center for Entrepreneurship and Innovation also deserve honorable mentions.

Building Better Biotech

The Texas Medical Center Innovation Institute (TMC-II) got off to a rough start with its various initiatives, which included the TMCx, JLabs@TMC, and the AT&T Foundry. For instance, publicly-traded firms generally don’t attend startup accelerator programs, but Bellicum Pharmaceuticals was an early client of JLabs@TMC. Bellicum was the HTC’s sole IPO and listed on the NASDAQ. (It’s worth noting that JLabs@TMC has removed Bellicum from their publicly-available client lists. And that the TMC-II still appears to report Bellicum’s IPO proceeds in their “raised to date” stat.)

Nevertheless, the TMC-II’s program quality increased materially in late 2016 and reached a decent standard a few years later. Furthermore, John Reale, the former CEO of Station Houston, founded Integr8d Capital and shifted his focus to life science startups in 2018. He later became the entrepreneur-in-residence at the TMC-II as well. J.R. was crucial to Houston’s first market-driven reformation effort and is likely an essential factor in its second one too.

The Green Mountain State

I also keep tabs on things going on in Vermont’s startup scene. Vermont is home to a tiny but growing startup ecosystem. In the 1990’s Vermont got around one new deal a year, and by the 2010s, Vermont averaged two and a half new deals a year. The U.S. doubled its deal flow over the same period, so, proportionately, Vermont is outpacing U.S. national growth. But in absolute terms, Vermont doesn’t have much. Since its first deal almost forty years ago, Vermont has received 125 rounds of VC., totaling just over $400m, into 56 companies. A top 30 city can comfortably achieve those numbers in a few months.

Agglomeration Powers Startup Cities

Historically, Vermont’s startups were mostly spread out down the I-89 east from Burlington. Vermont’s startup success stories include Dealer.com and Seventh Generation in Burlington, SunCommon in Waterbury, Keurig Green Mountain, which was up the road in Stowe, and Northern Power Systems in Barre. The jewel in the Green Mountain crown, though, is Casella Waste Systems in Rutland. (Casella has a surprising number of patents.)

Most of Vermont’s venture capital has gone into companies in Burlington though, which has increasingly dominated the state’s tech scene. This trend towards fewer startups outside of the Queen City is both good and bad. In the long-term, denser agglomeration is a powerful force for startups. But in the short-term, having fewer non-Burlington startups means having fewer startups. Until Burlington ups its game, or non-Burlington startups return, the state looks set to stay in the ebb part of its gentle ebb-and-flow in the bottom end of the U.S. startup state rankings. 

Up and Down

Burlington is the only place in Vermont to make the top 200 startup cities list in recent history, and it has done so every year from 2014 to 2020, except 2016. Rutland, Vermont, made the top 200 list in 1994. Twenty-twenty is Burlington’s second-best year ever. (It has lagged well behind Burlington, Massachusetts since the 1980s, but has bested Burlington, North Carolina, handily every year since 1998.) But, with a rank of 144th and just one new deal and two follow-on rounds, it’s hard to describe the People’s Republic of Burlington as a real startup city.

Among the 50 states, the District of Columbia, and Puerto Rico, Vermont has consistently ranked in the mid to late-thirties. In 2020, there were no new deals and no follow-on rounds outside Burlington, and Vermont takes 40th place in the U.S. startup state ranking. 

Startup Cities Ranking Methodology

The startup cities ranking uses an open methodology that anyone can use and recreate, and data on the top 200 startup cities from 1985 to 2020 is freely available.

This article’s results are based on data from Thomson Reuter’s VentureXpert, who survey venture capitalists. The rankings consider only data on “growth venture capital. ” Growth venture capital is seed, early, or later-stage investment into privately-held, (predominantly) high-tech high-growth startups. (The main alternative is transactional venture capital, which includes investments into publicly-traded firms and large non-tech incumbents).

The reported rankings are a rank-of-ranks over three measures that capture related but different aspects of a city’s startup ecosystem:

  • The amount of venture capital dollars invested.
  • The number of new deals (i.e., startups receiving VC for the first time).
  • The number of actively-funded startups (i.e., startups receiving stages of VC and working towards an exit).
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Finance

The Pandemic Stock Market Crash of 2020 Predicted to Worsen

Readers of American financial news might think that the pandemic stock market crash of 2020 happened in March and is over. That’s objectively not true: the pandemic stock market crash is still going on right now, and an analysis of past crashes suggests it’s about to get a lot worse.

A crash is not just a substantial daily or monthly decline. Instead, stock markets have two modes: crash and boom. The market is in a crash from its prior peak until its recovery. And seven out of 12 of America’s last stock market crashes have had at least one faux recovery.

Indices track the market. I use the Dow, but you can use the S&P 500, the Russell 3000, or whatever you like. The Dow’s most recent prior peak, before it suffered substantial declines, was of 29,551 points on February 12th, 2020. It hasn’t sustained that value again yet. Ergo, the U.S. stock markets are in a crash!

Continue reading “The Pandemic Stock Market Crash of 2020 Predicted to Worsen”
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Read the Top U.S. Startup Cities For 2016 Report

The top seven cities in the U.S. for startups in 2016 were San Francisco, New York, Boston, Cambridge, Palo Alto, Austin, and Seattle. These cities each received $2 billion in investment, had 58 new deals, and had 479 active VC-backed startups on average in 2016.

While these well-known startup cities continue to dominate the landscape, startup clusters are forming all over the U.S.  Policymakers in many cities that historically were not associated with high-growth, high-tech firms are now clearing succeeding in cultivating startups, as a strategy to boost their local economies.

 

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Read the Houston Growth vs. Transactional VC Report

Houston’s high-tech ecosystem can only flourish if it attracts more growth venture capital investments, according to the latest McNair Center for Entrepreneurship and Innovation issue brief, “Growth vs. Transactional Venture Capital in Houston, Texas.”

A realistic, but aggressive, goal for Houston would be around a 15 percent year-on-year increase in growth venture capital. This would allow Houston to reach roughly $170 million in growth venture capital by 2022.

According to the report, “Houston would then likely become a top 25 U.S. city for high-growth, high-technology startups, though its ecosystem would still be emerging and startups would remain a very small part of Houston’s economy.”

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Read the Houston Entrepreneurship Pipeline Report

This paper examines the startup training institutions in Houston, Texas, and what they are doing to open up the city’s pipeline of startup firms.

Recent academic research has shown that startup training institutions can have an enormous positive effect on an ecosystem’s growth. A good ecosystem pipeline turns out a large quantity of high-quality startup firms that have received top-tier training. Houston’s accelerators and incubators do not perform at the levels of benchmark institutions. The quality of deal flow coming from its accelerators, incubators, and hubs will be crucial to Houston’s future.

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McNair Center

Welcome to the McNair Center

The McNair Center for Entrepreneurship and Innovation at Rice University’s Baker Institute for Public Policy was founded in 2015 with an $8 million gift from the Robert and Janice McNair Foundation. Dr. Edward J. Egan was chosen as the founding director. He designed the center to provide policymakers, scholars, and the general public with comprehensive analyses of the issues that affect entrepreneurship and innovation at three levels: federal and state policy, municipal ecosystems, and academic entrepreneurship and innovation.

The Center’s foci were naturally on the U.S., Texas, Houston, and Rice University, but it also drew and shared insights from the best practices and policies worldwide. Its philosophy was to combine grounded theory and data-driven causal design to produce peer-reviewed research that stands up to scrutiny. To this end, the center collected and disseminated data, provided open access to informational resources, collaborated with leading academic experts, built understanding, and recommended policy to harness the incredible power of entrepreneurship and innovation.

By 2018, the McNair Center had provided more than 70 undergraduate and graduate students with internships to develop policy research, had a staff of four, and was the largest social science research laboratory on the Rice University Campus. It received offers of an additional $6.2m in funding to hire three more fellows and two more staff members and to roll out its nationwide research affiliate program.

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Visit the McNair Center’s website