Ken Simons

Associate Professor and HASS Associate Dean for Research and Graduate Studies
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About

Kenneth L. Simons researches the dynamics of industrial organization and technological change. His work has probed the causes of industry shakeouts, testing between alternative theories and exploring issues including sources of advantage to surviving firms and the role of technological innovation. He also explores the frequency and nature of disruptive technological change, impacts of new information technologies, energy technology evolution, benchmarking needs for environmentally beneficial technologies, process innovation driving the experience curve's cost reductions, commercialization decisions of independent inventors, and effects of corporate acquisitions on firm productivity.

He is Director of the Fashion Innovation Center, a multi-institution effort led by RPI to nurture a New York State sustainable fashion industry. The core focus is to advance natural textile products including bast fibers (notably hemp) and wool, and new-technology sustainable fibers and materials, so that they are manufactured in New York State from raw materials to final fashion products. The FIC innovates sustainable fashion technologies, accelerates sustainable fashion business innovations, engages through meetings and FIC activities, nurtures to spread knowledge and target supply chain gaps, and markets New York State's sustainable fashion industry. Primary collaborators are Rensselaer Polytechnic Institute (lead organization), SUNY Morrisville, Hudson Valley Textile Project, Field to Fiber, Made X Hudson, and the Fashion Institute of Technology.

He is Associate Dean for Research and Graduate Studies in Humanities, Arts, and Social Sciences at Rensselaer. The School has departments of Economics, Science and Technology Studies, Cognitive Studies, Communication and Media, and Arts, plus a program in Games and Simulation Arts and Sciences. He is pleased to work with so many great faculty and PhD students and to have the chance to help spur research across these essential disciplines. It is a particular pleasure to champion the role of these disciplines in the US's oldest technological university, celebrating its 200th year in 2024. The School has world-class leaders in diverse fields, with artists and composers and filmmakers who don't just write about the crafts but exhibit worldwide—just the PhD students exhibit regularly in prestigious venues like the Venice Biennale and get their films into top festivals; with game designers both explaining games' use and development and making breakthroughs from new boardgames and video games to new medical treatments; with communications experts researching disinformation on the internet and writing poetry, fiction, and nonfiction; with cognitive scientists leading in areas from motor control and driving to language models to the psychology of reinforcement learning; with science and technology studies researchers moving ahead community solution methods to lead-poisoned soils, advancing understanding of how the US opioid epidemic is being handled, and exploring social issues from waste handling and mining to the explosion of rap music; and with economists studying US national health care policy, discrimination against LGBTQ persons, fisheries, and patent-versus-secrecy tradeoffs in international trade.

Simons has received funding from the Ewing Marion Kauffman Foundation, the U.S. National Science Foundation, the U.S. Department of Energy, New York State through Empire State Development, the Economic and Social Research Council, and other organizations. This aid has in part supported his ongoing efforts to developed expansive novel data on industry evolution and technological change. His micro-detailed (some would say "nanoeconomic") analyses of industry and technology dynamics probe evolving firm decision making and industry outcomes, using global patent and innovation data.

Simons has organized numerous conferences related to industrial organization and technological change. He has served as Associate Editor of the International Journal of Industrial Organization, editorial board member of the Journal of Technology Marketing, and Chairman of the Network of Industrial Economists. His work is primarily empirical but also includes theoretical industrial organization, simulation, and computational methods.

Education & Training

Ph.D. in Social and Decision Sciences, Carnegie Mellon University, 1995

M.Sc. in Industrial Organization Economics, Carnegie Mellon University, 1993.

B.S. in Planning, Massachusetts Institute of Technology, 1990.

Research

Foci: Economics of innovation and new technologies; Industrial organization and industry evolution; Economic dynamics.

Kenneth L. Simons's research examines the processes that drive industries' technological innovation.  Data-rich investigations of decades to a century, coupled with theoretical modeling, yield insights and patterns that transcend short-period studies.

Industry Shakeouts

Most product industries have an initial rise and then a drop-off in their number of manufacturers.  Drop-offs of 30-80% are common, although some industries have no drop-off or more dramatic drop-off.  The U.S. automobile industry, for example, had a 97% drop in number of companies, and 99% of companies eventually were driven out of the business.  Simons's research probes the reasons for industry shakeouts, particularly the role of technological innovation in shakeouts.

 

US tire manufacturers rose from about 10 in 1905 to 274 in 1922 before falling off into the 1970s.

 

The Typical Mechanism of Industry Shakeouts: Racing to Keep Up in Innovation

An initial way to study industry shakeouts is to look at extreme cases, as reasons might stand out.  He therefore chose four product industries with large percentage drop-offs in number of companies, and for which data were obtainable.  Comparing views about how industry competition plays out and why shakeouts might happen yielded a list of testable predictions to distinguish between theories and observe mechanisms at work in shakeouts.  The whole process involved years carting dollies of incoming loan books, visiting distant libraries, hiring and egging on research assistants, codifying data, finding and fixing data problems, developing models, and running computer clusters overnight on econometric models.  The work was in collaboration with Steven Klepper, who continually traded ideas on approach and methods and who provided a first version of the tire industry company data, and is best understood through three key papers:

Steven Klepper and Kenneth L. Simons, "Technological Extinctions of Industrial Firms: An Inquiry into their Nature and Causes," Industrial and Corporate Change, vol. 6 no. 2, March 1997, pp. 379-460.  Working paper.  Published version.

Steven Klepper and Kenneth L. Simons, "Industry Shakeouts and Technological Change," International Journal of Industrial Organization, vol. 23 no. 1-2, February 2005, pp. 23-43.  Working paper.  Published version.

Steven Klepper and Kenneth L. Simons, "The Making of an Oligopoly: Firm Survival and Technological Change in the Evolution of the U.S. Tire Industry," Journal of Political Economy, vol. 108 no. 4, August 2000, pp. 728-760.  Published version.

Industries with strong shakeouts, to vastly simplify the above papers, involve a race to keep up in innovation.  Firms in the lead—those producing the most and with the greatest technological prowess—expect to sell the most in future, and therefore benefit most by investing in formal and informal R&D to improve the features and quality of the product and to reduce the unit cost of production.  The leading firms therefore invest heavily in innovation, and their products and processes keep getting more and more polished.  Hopeful and interested firms pile into the industry for a while, until it becomes clear that even the best of them can't make money at it any more, so that eventually entry stops.  Meanwhile some firms are steadily being driven out of business, because their rivals keep expanding and driving the price down and quality up.  Thus the rise and fall in number of firms is driven by the continual efforts to innovate and improve products and processes.

Some common views are wrong.  Everyone in industrial organization wants to focus on firms colluding to raise prices, but this research triggers a more traditional Chicago school view on industries: every one of the four industries was investigated by the government or courts for anti-trust or competitiveness concerns, but in every case the concentration of the industry was driven by the circumstance of racing to stay ahead in innovation.  People often want to think of technological progress as driven by patents, but looking at the details suggests that patents were more often an impediment to progress, and in three of the four industries patent rights were wholly (automobiles) or partly (televisions, penicillin) suspended and yet technological progress was roaring.  People look at shakeout graphs and presume that some event caused the number of firms to drop off, but events at this time turn out not to be outstandingly important, and the drop in number of firms is in fact driven by entry falling while the percentage exit rate remains roughly constant, causing the number of firms to fall not just until firms adapt to some event but typically for decades.  Some researchers try to link the truism that product standards emerge over time to the idea that a dominant product standard triggers industry shakeouts, but the evidence does not support this view; process improvement was critical well before supposedly dominant product standards were introduced, and it's easy to pick standards that happen to gel when the number of firms started to fall or at any other time but these standards in practice were not especially relevant to competition nor did they necessarily persist.  People want to think of technological progress as driven by a few great inventors and inventions, but these industries were among the greatest in technological progress—the tire industry had the fastest productivity advance of any U.S. government classified industry in the early 1900s—and their rip-roaring progress was driven by a vast flood of innovations not by races to be first with one or a few major new technologies.

 

While exit rates varied over time in industries, exit rates were not systematically higher at the times of shakeouts.  Exit persisted over the history of an industry.

 

Prior Experience and Advantage in Industry Shakeouts

When prior industry experience gives a strong advantage in a new industry, Simons observed, the firms established in the previous industry end up well in the lead in the new industry.  Given the spiral of advantage among firms racing to innovate in the new industry, the advantaged firms from the prior industry end up ahead while others drop out rapidly in the new industry's shakeout.  This pattern was clear in his analysis of television receiver manufacturers based on their prior experience in radio manufacturing.  "Dominance by birthright," Simons called this, in a widely cited strategic management paper:

Steven Klepper and Kenneth L. Simons, "Dominance by Birthright: Entry of Prior Radio Producers and Competitive Ramifications in the U.S. Television Receiver Industry," Strategic Management Journal, vol. 21 no. 10-11, October-November 2000, pp. 997-1016.  Working paper.  Published version.

 

In television manufacturing, non-radio producers were driven extinct first.  Smaller prior radio producers went extinct later.  Big radio producers lasted longest.

 

Simons also uses television manufacturers' prior radio manufacturing experience as an econometric identification method, to confirm causality when analyzing—in a paper described below—how innovation causes and impacts unit cost reduction curves.

Additional Work on Industry Shakeouts

Simons continues to extend the study of industry shakeouts theoretically and empirically.  Ongoing work includes an optimal control analysis of competing firms' simultaneous optimal decisions and resulting industry outcomes, and cross-industry and -country empirical research that further probes the causes and role of technological innovation in industry shakeouts.

Some early working papers on the topic, now in later iterations not ready to show yet, are:

Kenneth L. Simons, "Product Market Characteristics and the Industry Life Cycle," working paper.

Kenneth L. Simons, "On the Theory of Product Market Characteristics and the Industry Life Cycle," working paper.

Additional works on industry life cycles with shakeouts are:

Kenneth L. Simons, "Shakeouts, Innovation, and Industrial Strategy and Policy," Australian Economic Review, vol. 40 no. 1, March 2007, pp. 106-112.  Working paper.  Published version.

Kenneth L. Simons, "Predictable Cross-Industry Heterogeneity in Industry Dynamics," in Albert N. Link and F. M. Scherer, eds., Essays in Honor of Edwin Mansfield: The Economics of R&D, Innovation and Technological Change, Springer, 2005, pp. 275-279.  Working paper. Published version.

Steven Klepper and Kenneth L. Simons, "Innovation and Industry Shakeouts," Business and Economic History, vol. 25 no. 1, Fall 1996, pp. 81-89.  Working paper.  Published version.

Kenneth L. Simons, "Shakeouts: Firm Survival and Technological Change in New Manufacturing Industries," PhD dissertation, Carnegie Mellon University, Department of Social & Decision Sciences, September 1995.

Two of Simons's works on shakeouts have been reprinted in collections of key papers:

Steven Klepper and Kenneth L. Simons, "Technological Extinctions of Industrial Firms: An Inquiry into their Nature and Causes," reprinted in David B. Audretsch and Steven Klepper, eds., Innovation, Evolution of Industry and Economic Growth, Edward Elgar, 2000.  Working paper.  Published version.

Steven Klepper and Kenneth L. Simons, "Dominance by Birthright: Entry of Prior Radio Producers and Competitive Ramifications in the U.S. Television Receiver Industry," reprinted in Constance E. Helfat, ed., The Blackwell/Strategic Management Society Handbook of Organizational Capabilities: Emergence, Development and Change, Blackwell, 2003, pp. 15-42.  Working paper.  Published version.

Steven Klepper and Kenneth L. Simons, "Dominance by Birthright: Entry of Prior Radio Producers and Competitive Ramifications in the U.S. Television Receiver Industry," reprinted in Catherine A. Maritan and Margaret A. Peteraf, eds., Competitive Strategy, Edward Elgar, 2011.  Working paper.  Published version.

Cost Reduction Curves

A long literature has documented so called "experience curves" or "learning curves," in which firms' unit cost of manufacture decreases over time.  This is traditionally modeled as a function of cumulative output, as if the very fact of having produced more causes a firm magically to produce at lower cost.  On an individual person level, efficiency of output does rise with task learning, but inside firms the cost reduction typically continues for decades while production line employee learning typically maxes out on in weeks or at least months.  This begs the question of in what sense an organization learns, and what drives cost down.  Some studies have looked at R&D and unit cost, but statistical studies of learning are hampered by the fact that most formal R&D is about products not processes, and most tweaking of production processes—while it may go on continually across many employees—is not formally measured as R&D and therefore goes unreported, making it near impossible to find innovation effects in the available statistics.  Nonetheless, several studies in the 2000s have managed to dig into specific cases enough to collect evidence on sources of cost reduction in industries, and have pointed to R&D or innovation or deliberate "tweaking" as driving most cost reduction.  Simons built iteratively on process innovations data that he personally hand-assembled from hundreds of trade articles on television manufacturing to painstakingly codify characteristics of innovations and understand how innovation drove cost reduction and the nature of manufacturing:

Kenneth L. Simons, "Directed Innovation in Manufacturing Cost Reduction," working paper.

Disruptive Technologies

Disruptive technologies, or competence-destroying technologies, are defined in management research as technologies that disrupt establish businesses.  Similar technologies are known in economics research as radical innovations (which cause established firms to cease production) and general-purpose technologies (which have widespread and transformative applications across the economy).  Disruption is opposite the normal effect of technologies, because most technologies in industries are readily developed by the established businesses.

Simon's research confirms the statement of strategic management guru Michael Porter that "transformational technologies are very rare - on the order of every three or four decades.... There has been a tendency to dramatically overstate the disruptive impact of technologies" (Argyres and McGahan 2002, p. 48).  If one thinks of disruptive technologies as causing a wave of entrepreneurial companies to enter an industry and take over from established firms—as suggested by classic (and since questioned) work on hard disk drives—one approach is to look for a wave of entry followed by an increased incumbent exit rate, repeatedly in many different industries.

Simons takes this approach in a sample of thousands of years of industry data on single product industries, similar to classic disruption studies of product industries such as cement, minicomputers, hard disk drives, and semiconductor photolithographic aligners.  Across the thousands of years of data, he finds zero to a few disruptions that have a substantial wave of entry followed by an increased incumbent firm exit rate, within the leading large-country entrepreneurial economy that is the US.  The results do not rule out disruptions triggered by one or a very small number of incumbents, nor by cross-national competition from disruptors outside the US.  Notwithstanding these constraints on the findings, the results rule out a common view for the norm of industry disruption.  Rather, industry disruptions tend to follow more complex patterns, often take many decades to arise, and apparently occur more often between (e.g., from vacuum tubes to transistors) not within product industries as usually defined.  Simons has been at work on between-product industry comparisons.

Simons finds similar insights from a study of IT consultancies, which mediated IT revolutions. Although people often jump to assumptions that new technologies such as desktop computers or the internet should cause disruptions to most established businesses, the story is often more complex.  For example, early adopters of desktop computers did not necessarily find them more advantageous and often went back to using mainframes, and early adopters of software for these computers did not necessarily gain an advantage as firms that waited to adopt computer software did not have to custom build their own programs but could purchase high-quality commercial software at much lower cost.  Similarly, Simons finds that IT consultancies that led in serving these new technology areas did not experience higher growth or survival than other IT consultancies.

In another study, Simons finds that contrary to established views of technological disruption, traditional lighting firms all recognized a coming disruption of the incandescent and fluorescent light bulb industry by the new technology of LED light bulbs.  They successfully transitioned to the new technology, becoming leading firms in LED light bulb manufacture.  Yet as the study intimates, the leading light bulb manufacturers would all regret their decision to pursue the new technology.  Contrary to most of the established management literature on disruptive technologies, attempting to navigate the disruption and transition to making the new technology turned out to be a dangerous strategy given the highly competitive market, and all of the leading traditional light bulb firms owners' sold out to other businesses.

Kenneth L. Simons, "Two Roads to Riches? The (In)Frequency of Strongly Disruptive Technological Change," working paper.

Kenneth L. Simons, "Entrepreneurial Entry and Information Technology Shocks: The Unvarying Experience of IT Consultancies," working paper.  Slides.

Susan Walsh Sanderson and Kenneth L. Simons, "Light Emitting Diodes and the Lighting Revolution: The Emergence of a Solid-State Lighting Industry," Research Policy, vol. 43 no. 10, December 2014, pp. 1730-1746.  Working paper.  Published version.

Emergence of New Technologies

A few studies have analyzed the emergence of industries, potentially over many years leading up to the creation of an industry, but this kind of research is difficult and rare.  Simons added to research on technology and industry emergence through several papers, including the just-mentioned study, on how evolving LED and lighting technologies led up to the emergence of LED light bulbs (also called "solid-state" lighting):

Susan Walsh Sanderson and Kenneth L. Simons, "Light Emitting Diodes and the Lighting Revolution: The Emergence of a Solid-State Lighting Industry," Research Policy, vol. 43 no. 10, December 2014, pp. 1730-1746.  Working paper.  Published version.  (Also listed above.)

Susan Walsh Sanderson, Kenneth L. Simons, Judith Walls, and Yin-Yi Lai, "Lighting Industry," in Innovation in Global Industries - U.S. Firms Competing in a New World, National Academies Press, 2008, pp. 163-205.  This volume is a focus report of the National Academies.  Covered in Business Week (slide show gives industry-specific coverage).  Working paper.  Published version.

Kenneth L. Simons and Susan Walsh Sanderson, "Global Technology Development in Solid State Lighting," International Journal of High Speed Electronics and Systems, vol. 20 no. 2, June 2011, pp. 359-382.  Working paper.  Published version.

Kenneth L. Simons and Susan Walsh Sanderson, "SSL Technology Development and Commercialization in the Global Context," in Ian Ferguson, Christoph Hoelen, Jianzhong Jiao, and Tsunemasa Taguchi, eds., Proceedings of SPIE: Ninth International Conference on Solid State Lighting, SPIE, 2009, pp. 74220X-1-15.  Working paper.  Published version.

Inventors and Invention Commercialization

Economic research has uncovered many oddities about entrepreneurs.  Entrepreneurs would appear to be unrealistically optimistic, wishful thinkers, risk seekers, or just plain driven by their own interests.  Moreover, human subject experiments suggest ordinary people—and by implication entrepreneurs—overestimate their own chances of success, and so enter markets despite predicting that entrants will typically lose money.  Indeed real entrepreneurs do lose money, relative to what similar people make in corporate jobs.  With all these findings, it would seem we should be pessimistic about the way entrepreneurs operate.  Yet the empirical evidence on entrepreneurs has largely been based on aggregate patterns, and there has been little attempt to find out how much entrepreneurs respond to profit-related incentives.

The independent inventor is the quintessential entrepreneur.  Simons and coauthor Thomas Åstebro used data on advance estimates of profit-related characteristics of inventions, and matched the data to inventors' actual decisions whether to commercialize the inventions (and later whether to exit), as well as the inventors' stated reasons for their decisions.  By using a very general yet simple theoretical model, they predicted how inventors should behave if they respond rationally with profit-seeking motives.  It turns out that the financial incentives really do matter in inventors' decisions, and in fact the evidence suggests that independent inventors are averse to risk, just like most people.

Kenneth L. Simons and Thomas Åstebro, "Entrepreneurs Seeking Gains: Profit Motives and Risk Aversion in Inventors' Commercialization Decisions," Journal of Economics and Management Strategy, vol. 19 no. 4, Winter 2010.  Working paper.  Publication.  Mathematical proofs.

Policy-Driven Demand and Innovation

With PhD student Yu-li Ko, Simons analyzes how shifting European subsidies for solar photovoltaic panels caused a dramatic shift in solar photovoltaic R&D in Asia:

Yu-Li Ko and Kenneth L. Simons, "The Cross-Border Impact of Demand-Pull Policies on R&D: A Firm-Level Analysis," working paper.

Mergers and Manufacturing Plant Productivity

Plant productivity declines on average 1% or more per year before the average plant is acquired by a new owner, but beginning immediately after acquisition, productivity rises even more rapidly.  Simons assesses total factor productivity in a study of nearly all Swedish manufacturing plants. The productivity shifts coincide with reductions in output and especially employment. The workforce of the average acquired plant shifts to involve more old-time employees, and the reductions in workforce tend to leave a slightly smaller percentage of women employees, non-native-born employees, and less-educated employees.

These conclusions provide new evidence on what goes on during the average plant or company acquisition.  Detailed breakdowns by types of ownership change, including part- and whole-firm acquisitions and divestitures and related and unrelated diversifications, also provide a focused analysis of how the benefits and processes of ownership change vary according to the circumstances of acquisition.  The data from this study provide, apparently, the first plant-level evidence on ownership change and productivity in continental Europe, and one of the first analyses of ownership-change related fluctuations in composition of the workforce.

 

Total factor productivity fell by about eight percent over the seven years preceding ownership change of a plant.  With the new owner in place, total factory productivity then rose by about eight percent.

 

This study and related work include:

Donald S. Siegel, Kenneth L. Simons, and Tomas Lindstrom, "Ownership Change, Productivity, and Human Capital: New Evidence from Matched Employer-Employee Data in Swedish Manufacturing," in Producer Dynamics: New Evidence from Micro Data, University of Chicago Press for the National Bureau of Economic Research, 2009, pp. 397-442.  Working paper.  Published version.

Donald S. Siegel and Kenneth L. Simons, "Assessing the Effects of Mergers and Acquisitions on Firm Performance, Plant Productivity, and Workers: New Evidence from Matched Employer-Employee Data," Strategic Management Journal, vol. 31 no. 8, August 2010, pp. 903-916.  Working paper.  Published version.

John Marsh, Donald S. Siegel, and Kenneth L. Simons, "Assessing the Effects of Ownership Change on Women and Minority Employees: Evidence from Matched Employer-Employee Data," International Journal of the Economics of Business, vol. 14 no. 2, July 2007, pp. 161-178.  Working paper.  Published version.

Donald S. Siegel, Kenneth L. Simons, and Tomas Lindstrom, "Assessing the Effects of Ownership Change on Careers: New Evidence from Matched Employer-Employee Data," working paper.

The US National Innovation System

A country's national innovation system consists of policies, practices, infrastructure, and people who make new technologies and products come into use. Because technological innovation propels corporate success, national economic growth, incomes, and quality of life, it is crucial to have a good understanding of the national innovation system of one's country. When Simons was asked to create an overview of the U.S. national innovation system, for a new encyclopedia of technology and innovation management, he said no way—the subject was vast, too long a project, and too big for a few pages in an encyclopedia to survey in the scope of an encyclopedia. The last serious "academic" survey of the U.S. national innovation system had been by David Mowery and Nathan Rosenberg way back in 1993, and clearly had taken lots of work. Somehow Simons gave in to the nagging, the editors allowed many many more pages, and he lined up a good Ph.D. student as a coauthor, and wrote a more modern (2008 published 2010, update in 2012) overview of the U.S. national innovation system. The paper analyzes what makes the country's innovation system successful; key government policies, their effects, and suggested changes; overviews of corporate, government, and university spending flows; patent policies and trends; and culture, politics, education, and immigration in relation to national innovation.

Kenneth L. Simons and Judith Walls, "U.S.A.'s National Innovation System" [thoroughly updated edition of the paper below], in V.K. Narayanan and Gina Colarelli O'Connor (eds.), Wiley Encyclopedia of Management, vol. 13, Technology and Innovation Management, Wiley, 2015, 32 pp.  Working paper.  Published version.

Kenneth L. Simons and Judith Walls, "The U.S. National Innovation System," in V.K. Narayanan and Gina Colarelli O'Connor (eds.), Encyclopedia of Technology and Innovation, Wiley, 2010, pp. 445-467.  Working paper.  Published version.

Kenneth L. Simons, "The U.S. National Innovation System: Potential Insights for Russia" (in Russian, by translation), in I. Danilin and E. Klochikhin (eds.), Innovative Development: International Experience and Russia's Strategy, Moscow: MGIMO-University Press, 2009, pp. 97-119.  Working paper.  Published version.

Technology Benchmarks to Allow Growth Given Environmental Constraints

There's been a long discussion about the environment and growth—do we need to slow growth to avoid famines or economic collapse?  Opponents of growth such as the Limits to Growth authors from the 1970s never came to agreement with proponents such as the late Julian Simon.  The lack of serious dialogue on the issue—and the extent to which economists have let it lapse—is unfortunate.  It's hard to think of more important issues than the healthy and enjoyable lives of the eight billion (and growing) people on our planet.

Simons's solution to the issue is to focus on environmental technology.  Both opponents and proponents of growth agree that appropriate use of environmental technology is crucial to the continuance of human lives and lifestyles as we know them.  And growth is continuing its way regardless of either camp.  So we need an alternative approach.

Simons's work shows such an approach theoretically, then examines how technologies have been changing in practice, and finally computes crude estimates of real-world technology benchmarks.

He defines technology benchmarks as minimum amounts of specific environmental technologies required to allow a continued path of population and economic growth.  In a general model of economic growth and environment, he proves that:  1. With no environmental problems, growth could continue indefinitely.   2. With environmental impacts, if we don't know the form of the impacts, economic output might fall below any desired level.  3. Environmental technology can ensure a desired minimum growth path.  Robust minimal technology paths are also defined, so that amounts of technology greater than or equal to the paths yield desired growth.  This accounts for feedback of environmental quality on growth.

Environmental technology progress is estimated by alternative measures in 1970-2004.  Crop yields typically have improved roughly 1-2% per year.  Pollutant emissions per unit of industry or agriculture typically have fallen 2% to 6% per year.  Metal and mineral extraction worldwide per unit of industry typically has fallen by about 3% per year.

To illustrate how technology benchmarks can be estimated using global change models developed by teams of scientists, the World3 model is used to estimate specific minimum environmental technology improvements.

Kenneth L. Simons, "Technology Benchmarks for Sustained Economic Growth," working paper.

See also:

Kenneth L. Simons, "Technology Requirements for Population and Economic Growth," working paper.

Simons also developed software to make models of global change more accessible.  See:

Kenneth L. Simons, "Making Global Models Accessible: The Earth Systems Project," The Earth Simulation Newsletter, vol. 1 no. 1, 1994, pp. 3-5. (Not peer-reviewed.)  Published version.

Kenneth L. Simons and Peter J. Poole, "Software to Communicate Global Models," in Crookall, David and Kiyoshi Arai, eds., Global Interdependence, Springer-Verlag, 1992, pp. 57-65.  Published version.

Kenneth L. Simons, "New Technologies in Simulation Games," System Dynamics Review, vol. 9 no. 2, Summer 1993, pp. 135-152.  Published version.

Ratchet Effect and Firm Regulation

Studies of environmental regulation have argued that regulators are better off with more power rather than less, for example by being able to tailor regulatory standards to specific types of firms or even to individual firms.  These views ignore the "ratchet" effect, whereby what the regulator finds out about firms leads it to increase regulation in future, sometimes causing firms not to use the best possible methods for fear of the dreaded ratchet.  A joint paper by Simons and Anthony Heyes proves that ratchet effects can indeed apply to environmental regulation of firms, through a simple model of optimally behaving firms and a regulatory agency that works to optimize social welfare.  The ratchet effect means that the regulator would prefer not to have the ability to tailor standards for some industries, in order to achieve higher social welfare.  This is because "pooling" or "partial separation" equilibria may result in which some firms use inefficient technology in order to avoid heightened regulation.  Whether dread of the ratchet really matters depends on industry and technology characteristics, the relative social costs of pollution and output, and the actual (presumably non-optimal) behavior patterns of firms and regulators.  The paper's contribution is that we need to pay attention to the ratchet, not ignore it, when planning environmental regulation of firms.

Anthony G. Heyes and Kenneth L. Simons, "The Strategic Benefits of Uniform Environmental Standards," Strategic Behavior and the Environment, vol. 1 no. 1, January 2011.  Working paper.  Published version.

 

Depending on parameter values, the ratchet effect can yield pooling, full separation, or partial separation equilibria, determining the mix of behaviors across firms.

 

Bodyshopping

Among Simons's analyses of the information technology industry is this joint paper analyzing choices between "bodyshopping" of employees, flying them from India to the US, versus hiring people in India:

Sumit K. Majumdar, Kenneth L. Simons, and Ashok Nag, "Bodyshopping versus Offshoring among Indian Software and Information Technology Firms," Information Technology and Management, vol. 12 no. 1, March 2011, pp. 17-34.  Working paper.  Published version.

Wage and Employment Policy Dynamics

Why do some companies pay employees little at first but give them big salary increases in later years?  Could they afford to keep honest employees for life, and how?  How can they build up employees' skills to turn the good ones into top management?  And if they are bank employees, what keeps them from running off with the cash?

Simons teamed with economic historian Andrew Seltzer for a study on Australian banking.  Australian banks in the 1800s and early 1900s had to attract the few highly-educated school graduates, and keep them in the bank in the long term.  Steeply graded salary scales and big old-age pensions gave an incentive to stay with the bank.  Not all employees turned out to be geniuses, so while the best went on to top management, the rest became long-term clerks doing routine work in big city offices.  Promising employees were rotated through different jobs, and if they were good enough they would not get stuck forever managing small rural branches.  The frequent job changes not only built experience; they also promoted honesty.   If someone else would inherit the books soon, cheating was hard, particularly with mandatory vacations when employees were not allowed to step into the office.

The paper provides a chance to reflect on some fundamental facets of employee policy.  These policies will not all make sense for a given modern company, but it is wise to reflect on how workplace policies like these and their alternatives affect a company.

Andrew Seltzer and Kenneth L. Simons, "Salaries and Career Opportunities in the Banking Industry: Evidence from the Personnel Records of the Union Bank of Australia," Explorations in Economic History, April 2001, vol. 38 no. 2, pp. 195-224.  Published version.

 

A graph shows the increasing average real wage of employees who began work in the Union Bank of Australia circa 1877.  From 1877 to 1915, these employees' wages rose by about a multiple of seven.

 

Economic Growth in Dictatorships

It has been well known that some dictatorships achieve rapid economic growth while others suffer rapid decline. A study coauthored by Simons is apparently the first attempt to explain this phenomenon in a formal economic framework.  The study seeks to explain both rapid growth and decline in terms of optimal survival strategies for dictators in different circumstances.

The study's model of economic growth involves a tricky dynamic optimization problem.  (Technically, it is not time-separable.)  Simons solved it computationally, using intensive sensitivity analyses around the range of plausible parameter values.  The model dictatorships turn out to have bifurcation points, with a spiral of deterioration below the bifurcation and a too-rapid spiral of growth above the bifuraction.  The results fit with the limited available empirical evidence, and provide an explanation for the previously noted but unexplained high variance of growth rates among dictatorships.

Jody Overland, Kenneth L. Simons, and Michael Spagat, "Political Instability and Growth in Dictatorships,"  Public Choice, vol. 125 no. 3-4, December 2005, pp. 445-470.  Published version.

 

Primary Research Focus
Economics of innovation and new technologies; Industrial organization and industry evolution; Economic dynamics.
Research Centers

Teaching

Kenneth L. Simons currently teaches courses on the economics of innovation and new technologies.  PhD course ECON-6770 Economics of Innovation I is a core requirement in Rensselaer's Applied Economics and Policy PhD program.  Technological change is responsible for most of economic growth, and is essential to societal goals such as climate change mitigation and energy security.  The course analyzes how innovations and new technologies emerge, core influences on amounts of invention and innovation, how innovation simultaneously affects and is determined by the activities of companies and industries, methods to encourage innovation, regional innovation, and policy.  The course is micreconomic, and involves a mix of mathematical models, empirical analyses, and research methods on science and innovation.  A follow-on PhD course focused on macroeconomic and trade analyses of innovation.  Dr. Simons also teaches, as his schedule allows, ECON-4110/6110 Economics of Innovation and New Technologies, for undergraduate or Master's level study of innovation and technology issues.

He previously taught PhD courses in Advanced Econometrics and Advanced Microeconomics, an undergraduate Seminar in Economics research thesis course, and undergraduate-graduate combined courses in Structure of American Industry, Econometrics, and Quantitative Analysis and Advanced Quantitative Analysis, at Rensselaer Polytechnic Institute.  At Royal Holloway College of the University of London, he previously taught undergraduate courses in Industrial Growth and Competition, Industrial Economics, Quantitative Methods of Economics II, and ran the undergraduate thesis Extended Essay course system for all students; and he taught PhD coursework in Industrial Economics, Quantitative Methods for Economics Refresher Course (a new PhD student boot camp), and Quantitative & Econometric Analysis.  At MIT while an undergraduate, he taught (for full MIT undergraduate course credit to small numbers of students as part of MIT's Experimental Study Group) Principles of Chemical Science and Differential Equations, he was a TA for graduate courses in Systems Thinking and in System Dynamics, and a TA for an Executive Course in System Dynamics, and he was awarded MIT's Carl Taylor Compton prize for his contributions to MIT education.

He has supervised over 100 undergraduate theses, been advisor and Chair for four PhD graduates in Economics and one PhD graduate in Management, and been on committees of 20 additional PhD students in economics and other disciplines in his own and other universities.

Econometrics Resources

  • Simons's Useful Stata Commands PDF file - summarizes Stata commands for common undergraduate and graduate level econometrics in Stata - this says it's for Stata versions 13, 14, and 15, but pretty much everything should continue to work fine for Stata 16, 17, and 18

 

Publications

The following is a selection of recent publications in Scopus. Ken Simons has 18 indexed publications in the subjects of Business, Management and Accounting, Economics, Econometrics and Finance, Computer Science.

Kenneth L. Simons
Stata Journal
, 16
, 2016
, pp.632-649
.
Susan Walsh Sanderson, Kenneth L. Simons
Research Policy
, 43
, 2014
, pp.1730-1746
.
Kenneth L. Simons, Susan Walsh Sanderson
International Journal of High Speed Electronics and Systems
, 20
, 2011
, pp.359-382
.
Sumit K. Majumdar, Kenneth L. Simons, Ashok Nag
Information Technology and Management
, 12
, 2011
, pp.17-34
.
Kenneth L. Simons, Thomas Åstebro
Journal of Economics and Management Strategy
, 19
, 2010
, pp.863-888
.
Kenneth L. Simons, Susan W. Sanderson
Proceedings of SPIE - The International Society for Optical Engineering
, 7422
, 2009
.
Susan Walsh Sanderson, Kenneth L. Simons, Judith L. Walls, Yin Yi Lai
Innovation in Global Industries: U.S. Firms Competing in a New World Collected Studies
, 2008
, pp.163-206
.
John Marsh, Donald S. Siegel, Kenneth L. Simons
International Journal of the Economics of Business
, 14
, 2007
, pp.161-178
.
Kenneth L. Simons
Australian Economic Review
, 40
, 2007
, pp.106-112
.

Postdoctoral Researcher

Economic and Industry Analyst (Postdoctoral Researcher), Fashion Innovation Center, Rensselaer Polytechnic Institute

Yushuo Pan is Economic and Industry Analyst for the Fashion Innovation Center.  Yushuo is a post-doctoral researcher in economics, studying textile and fashion industry and R&D in the shift to more environmentally sustainable fashion and textile technologies.  The position is in the Fashion Innovation Center at Rensselaer Polytechnic Institute.  We work with industry participants to assemble new and historical data on technological shifts in product and material types (fiber, fabric, dyes, clothing), manufacturing methods, trade, output, price, industry composition (including companies and products), and more, to analyze these patterns, and to draw conclusions appropriate for reports and journal or book publications about industry and technology dynamics and potentially about environment, trade, and regional clusters and networks, and for informing industry and technology development.

Student Job Openings

Undergraduates may apply for job opportunities to help with research and other activities.  Applicants must be continuing RPI undergraduates.  In Spring 2025, there is opportunity for part-time undergraduate employees to help with the Fashion Innovation Center, dealing with issues such as the Center library, reports, web updates, helping with material tests, and information collection.  In any semester, apply in the first week of the semester or earlier to participate in Undergraduate Research Program research projects.

To apply for URP positions while taking classes, please email me this part-time form.

To apply for full-time RPI undergraduate positions, please email me this full-time form.  Full-time opportunities are most likely to be available in summer, but might be available in fall or spring.

Research Resources

Archived Data and Code from Selected Papers

Archive Data on Tire Manufacturers

All the data used in analyses in Steven Klepper and Kenneth L. Simons, "The Making of an Oligopoly: Firm Survival and Technological Change in the Evolution of the U.S. Tire Industry," Journal of Political Economy, vol. 108 no. 4, August 2000, pp. 728-760.

Archive Data on Radio and Television Manufacturers

All the data used in analyses in Steven Klepper and Kenneth L. Simons, "Dominance by Birthright: Entry of Prior Radio Producers and Competitive Ramifications in the U.S. Television Receiver Industry," Strategic Management Journal, vol. 21 no. 10-11, October-November 2000, pp. 997-1016.

Archive C++ Code for Dynamic Programming of Dictators' Optimal Decisions

Code used for analyses in Jody Overland, Kenneth L. Simons, and Michael Spagat, "Political Instability and Growth in Dictatorships," Public Choice, vol. 125 no. 3-4, December 2005, pp. 445-470.

 

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