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\begin{comment}
Please include the following acknowledgements in any reproductions of this material.
Source document: Kevin A. Bryan and Heidi L. Williams, 2021. 
Figure #: © .  All rights reserved. [Citation with link to source]
Table #: © .  All rights reserved. [Citation with link to source]
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\title[]{Innovation: Market Failures and Public Policies} 
\subtitle{Lecture 1: Introduction \vspace{3cm}}
\institute[]{\justifying The material covered in these slides is drawn from: Bryan, Kevin and Heidi Williams (2021) "Innovation: Market Failures and Public Policies," Chapter 13 in the \emph{Handbook of Industrial Organization Volume 4}, edited by Kate Ho, Ali Hortacsu, and Alessandro Lizzeri.}
\date{} 

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\begin{document}
	
\frame{\titlepage}

\begin{frame}
\frametitle{Introduction}
Innovation is at the core of many fundamental economic problems
\begin{enumerate}
    \item Technical change during the Industrial Revolution {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Mokyr 2010]}}
    \item Tradeoffs between tax-based and innovation-based climate change policies {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Acemoglu et al. 2016]}}
    \item Contribution of innovation to international agricultural development {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Alston and Pardey 2014]}}
    \item The world’s seven largest private companies (as of December 2020) all produce products that had not been invented fifty years earlier
\end{enumerate}
\vspace{3mm}
Growth potential of the modern economy is itself an innovation problem
\begin{itemize}
    \item Are we facing a future of stagnation or is this angst merely a replay of historical worries that technological growth had come to an end? {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Gordon 2017 vs. Mokyr et al. 2015]}}
\end{itemize}
\end{frame}

\begin{frame}
\frametitle{What is innovation?}
\textbf{Innovation}: the invention, development, and diffusion of new goods, services or production processes.  \\
\vspace{4mm}
\begin{itemize}
    \item Economic problem that depends on active choices of agents who respond to incentives
    \item Historically, not treated as a primarily economic concern
\begin{itemize}
    \item Prior to 1960, 11 articles in AER, QJE, ECTA (combined) had ``invention'' or ``innovation'' in title
    \item Development and diffusion of new ideas thought to be psychological, sociological, or simply serendipitous
\end{itemize}
\end{itemize}
\end{frame}

\begin{frame}
\frametitle{What about the economics of innovation?}
``Economics of innovation'' inspired by mid-century developments in industrial practice, government
policy, and economic theory:
\begin{enumerate}
    \item Rise of large-scale industrial research labs {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Hounshell and Smith 1988]}}
    \item Successful directed wartime science efforts
    \begin{itemize}
        \item Led to Vannevar Bush’s \emph{Science, The Endless Frontier} {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Bush 1945]}}
    \end{itemize}
    \item Schumpeter (1942): creation and diffusion of new goods was a fundamental economic problem
\begin{itemize}
    \item Contrast with Neoclassical welfare analysis, which holds technological frontier constant
\end{itemize}
\end{enumerate}
\end{frame}

\begin{frame}
\frametitle{1951 SSRC Conference: a progress report}
In response to newfound interest in innovation, a 1951 conference “Quantitative Description of Technological Change”
was held at Princeton and supported by the Social Science Research Council
\begin{itemize}
    \item Publication of the conference proceedings was abandoned because
“the papers [were] in most cases of a very exploratory character” {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Godin 2008]}}
    \item At the time, data on government R\&D were close to nonexistent, very few papers had analyzed patents to study corporate innovation, and the link between these efforts and economic growth was unclear
\end{itemize}

\end{frame}

\begin{frame}
\frametitle{Solow (1957): ``black box'' of innovation}
\begin{itemize}
    \item Share of long-run economic growth unexplained
by changes in capital and labor inputs (TFP, total factor productivity) as high as 85\%
    \item By construction, TFP is an unmeasured residual
    \item However, subsequent work adjusting for labor quality and capital utilization suggested much of “Solow residual” reflects technological progress
\end{itemize}

\end{frame}

\begin{frame}
\frametitle{Changes in TFP and GDP over time in the US}
    \begin{center}
    \includegraphics[scale=0.6]{figure1_tfp.pdf}
    \end{center}
\scriptsize \textcolor{red!75!green!50!blue!25!gray}{Notes: This figure displays 10-year smoothed averages of annual changes in TFP and GDP. TFP here is the standard decomposition aside from adjusting for changes in labor and capital utilization (e.g., “labor hoarding” with shorter hours during recessions). Source: Fernald
(2012).}
\end{frame}

\begin{frame}
\frametitle{1962 NBER Conference: a progress report}
Core questions of innovation research agenda:
\begin{itemize}
    \item How do inventors choose the rate and direction of the research investments they pursue? 
    \item What market structure leads to high levels of innovation? 
    \item Is innovation optimally generated with laissez faire incentives? 
\end{itemize}
\vspace{3mm}
Raised in groundbreaking 1962 in NBER conference volume on the Rate and Direction of Inventive Activity and related papers published by the economists who attended the event {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[NBER 1962, Machlup 1962, Nelson 1959, Schmookler 1962 and 1966]}} \\
\vspace{5mm}
Despite 60 years of extensive research since the 1962 conference, these questions remain largely open.
\end{frame}

\begin{frame}
\frametitle{This lecture}
Summarize the core problems in the economics of innovation:
\begin{enumerate}
    \item What market failures exist in the production and diffusion of new goods?
    \item How does inefficiency in the production of innovation harm growth?
    \item What makes empirically analyzing innovation policy questions challenging,
and how have economists made progress in measurement and empirical analysis?
\end{enumerate}
\end{frame}

\section{Market failures and innovation}

\begin{frame}
    \frametitle{Outline}
    \tableofcontents[currentsection]
\end{frame}

\begin{frame}
\frametitle{Introducing market failures: Arrow (1962)}
\begin{itemize}
\item {Arrow describes three market failures that prevent laissez faire efficiency in production of new ideas}
\item {Market equilibria are Pareto efficient as long as a set of well-known assumptions behind the general equilibrium welfare theorems hold. Innovation violates three particularly important assumptions:}
\begin{enumerate}
    \item The production transformation set should be convex
    \item The value of the good should not involve externalities
    \item Production should be deterministic 
\end{enumerate}
\end{itemize}
\end{frame}

\begin{frame}
\frametitle{Non-convexity}
The production transformation set for ideas is not convex
\vspace{3mm}
\begin{itemize}
\item Creating the first unit of a piece of knowledge (a new idea) is costly, but ubsequent units are free to replicate
\item Efficiency requires that price equals the cost of the marginal unit of knowledge consumed 
\item If the price of knowledge is zero, who will pay the fixed cost to create it first?
\end{itemize}
\vspace{3mm}
\textit{Bottom line:} The fact that initial inventors incur unique fixed costs means that innovation is either underappropriated or else the product of that innovation will be artificially scarce
\end{frame}

\begin{frame}
\frametitle{Spillovers}
New ideas often generate significant externalities
\vspace{3mm}
\begin{itemize}
\item Ideas today are inputs into inventions tomorrow
\item Inventors may build off of the ideas of previous inventors
\begin{itemize}
    \item Social value of new ideas may exceed private value
\end{itemize}
\item Firm-level: trained workers may move to new jobs with new employers
\end{itemize}
\vspace{3mm}
\textit{Bottom line:} Invention creates spillovers whose value is not incorporated into market prices
\end{frame}

\begin{frame}
\frametitle{Unobservable effort}
The production of new ideas is not fully deterministic
\vspace{3mm}
\begin{itemize}
\item Arrow-Debreu securities: uncertainty does not harm economic efficiency as long as risks can be suitably hedged
\item Research inputs produce knowledge with uncertainty, creating risk that may not be possible to hedge
\begin{itemize}
    \item We are unable to observe efforts of researchers
    \item If researchers receive constant payouts – regardless of success – they can shirk 
\end{itemize}
\item How do we balance the desire to improve efficiency by shifting risk away from individuals with the incentive problem of encouraging initial invention?
\end{itemize}
\vspace{3mm}
\textit{Bottom line:} Invention involves uncertainties which cannot be fully hedged when they depend on unobservable effort by inventors
\end{frame}

\begin{frame}
\frametitle{More on market failures}
Arrow (1962) highlighted various market failures that generally result in the \textit{underproduction} of innovation. Since then, other economists have pointed out market failures in the area of innovation that could cause \textit{overproduction} of innovation
\begin{itemize}
\item Inventors may not account for the fact that their R&D lowers the expected return of others trying to invent the same product 
\begin{itemize}
    \item Can result in races to enter the market first {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Loury 1979; Reinganum 1985]}}
\end{itemize}
\item New inventions may steal market share from other firms without generating much social benefit 
\begin{itemize}
    \item Similar to usual intuition that product entry can be excessive {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Mankiw and Whinston 1986]}}
\end{itemize}
\end{itemize}
\vspace{3mm}
With these other economic forces also in play, is investment in R\&D too high or too low?
\end{frame}

\begin{frame}
\frametitle{Quantifying social and private returns to innovation}
Empirical analyses in recent years have suggested that social returns to R\&D are much higher than private returns
\vspace{3mm}
\begin{itemize}
\item Using a model based on GDP and the social discount rate, Jones and Summers (forthcoming) suggests the social rate of return on R\&D is at least 20\%, and as high as 67\%
\item Using technological and market distance between firms to estimate gross social returns to R\&D, Bloom, Schankerman, and Van Reenen (2013) find social returns at least twice as high as private returns
\end{itemize}
\end{frame}

\section{Innovation and growth}

\begin{frame}
    \frametitle{Outline}
    \tableofcontents[currentsection]
\end{frame}

\begin{frame}
\frametitle{Innovation and growth}

\begin{itemize}
    \item There are good theoretical reasons to believe innovations are underproduced by the market
    \item Underproduction of innovation is particularly harmful given its cumulative and fundamental dynamic role in economic growth
    \item Economists have attempted to model this relationship in exogenous growth models like Solow-Swan, in endogenous growth models, and in Neochumpeterian models
\end{itemize}

\end{frame}

\begin{frame}
\frametitle{Exogenous growth models}
\begin{itemize}
\item Early models relating economic growth and innovation assume that technological progress is independent of other economic forces
\item The Solow-Swan model from 1956 was among the first and most influential exogenous growth models {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Solow 1956; Swan 1956]}}
    \begin{itemize}
        \item Output is measured as a Cobb-Douglas combination of capital, labor, and technology which scales up output for any level of capital and labor
        \item Once steady state capital per effective unit of labor has been reached, only technological growth can push the economy forward
    \end{itemize}
\item Technological progress is treated as exogenous
\begin{itemize}
    \item Technological ``black box''
\end{itemize}
\end{itemize}
\end{frame}

\begin{frame}
\frametitle{Endogenous growth models: core ideas}
Endogenous growth models built on Solow-Swan by treating technology as dependent on firm R\&D decisions\\
\vspace{3mm}
Stems from two core ideas:
\begin{enumerate}
\item Ideas are nonrivalrous, so existing inventions can be used to spark new inventions {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Marshall 1890]}}
\item In markets without perfect competition, ``quasirents'' can provide incentives to do research {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Chamberlin 1962]}}
\end{enumerate}
Romer (1986): First successful attempt to incorporate increasing returns into a general equilibrium model 
\end{frame}

\begin{frame}
\frametitle{Endogenous growth models: Romer (1986)}
Key idea: each firm’s use of capital creates an externality
\begin{itemize}
    \item Capital use increases knowledge in society through a ``learning-by-doing'' externality
    \item Model generates growth path with constant increases in capital, production, and technological growth
    \item Model supposes that knowledge is non-rivalrous (can be used simultaneously by multiple actors
    \item Focus on non-rivalrousness clarifies key link between non-rivalry and increasing returns
    \item However, the model does not explicitly model knowledge production
\end{itemize}
\end{frame}

\begin{frame}
\frametitle{Endogenous growth models: Romer (1990)}
Romer (1990) explicitly models R\&D
\begin{itemize}
    \item Assumes inventors are not price-takers and can earn quasirents for duration of a (infinitely-lived) patent term
    \item Provides an incentive for firms to invest in R\&D
    \item This model tractably allows analysis of how purposeful market intervention can generate growth that is neither infinite nor zero in the long run
\end{itemize}
Key limitation: treats all inventors as monopolists with no strategic interaction
\end{frame}

\begin{frame}
\frametitle{Neoschumpeterian growth models}
Neoschumpeterian models focus on the competition between existing and new technologies
\begin{itemize}
    \item Invention today makes older varieties of the same technology less valuable
    \item Firm investment in innovation depends on whether it is destroying its own varieties (Arrow's ``replacement effect'') or destroying rival varieties
    \item A firm’s period of market power may depend on the level of inventive effort from other firms trying to produce improvements
\end{itemize}
\end{frame}

\begin{frame}
\frametitle{Key theoretical takeaways}
\begin{itemize}
    \item Endogenous and Neoschumpeterian growth models emphasized that long-run growth depends on incentives for innovation.
    \item The models set up a balance between two suboptimal scenarios:
    \begin{itemize}
        \item Innovation is perfectly competitive, so there are no profits, and thus no incentive to invest in research
        \item Inventors have broad property rights, so they lack competition and fail to innovate.
    \end{itemize}
    \item Thus, we are set up with an interesting trade-off for policy makers between providing strong incentives today and protecting tomorrow's inventors.
\end{itemize}

\end{frame}

\section{Empirical challenges}

\begin{frame}
    \frametitle{Outline}
    \tableofcontents[currentsection]
\end{frame}

\begin{frame}
\frametitle{Empirical challenges}
If innovation is inefficiently under-provided in private markets, government policy may improve efficiency
\vspace{3mm}
\begin{itemize}
\item Requires estimating the magnitude of inefficiency and responsiveness of margins being targeted as potential solutions
\item Measuring the effectiveness of innovation policy poses two key empirical challenges:
    \begin{enumerate}
        \item Measuring the relevant economic phenomena in markets for innovation
        \item Isolating sources of variation which identify compelling counterfactuals
    \end{enumerate}
\end{itemize}
\end{frame}

\begin{frame}
\frametitle{Measurement challenges: spillovers}
Knowledge spillovers are frequently cited as the central market failure justifying government intervention in markets for innovation
\vspace{3mm}
\begin{itemize}
\item Strikingly: evidence of existence and magnitude is quite thin
\item Krugman (1991): \textit{``knowledge flows... are invisible; they leave no paper trail by which they may be measured and tracked''} 
\end{itemize}
\vspace{3mm}
What data have economists used to measure innovation?
\end{frame}

\begin{frame}
\frametitle{Measuring innovation: patent data}
Zvi Griliches was a pioneer in quantifying innovation during the 1960s, spurring multiple efforts to gather patent data into usable form

\vspace{3mm}
\begin{quote}\textit{``In this desert of data, patent statistics loom up as a mirage of wonderful plentitude and objectivity. They are available; they are by definition related to inventiveness, and they are based on what appears to be an objective and only slowly changing standard''} {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Griliches 1990]}}
\end{quote}

\vspace{3mm}
Key patent-related datasets have built on efforts by Hall, Jaffe, and Trajtenberg (2002) to link Compustat data and granted US patents, and the USPTO's expansion of public access to administrative data
\end{frame}

\begin{frame}
\frametitle{Measuring innovation: limitations of patent data}
Despite Griliches’ own enthusiasm about the potential of patent data, he (and others) cautioned:
\begin{itemize}
    \item \textit{``Inventions may be the wrong unit of measurement... and may be a misleading quantum''} {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Griliches 1962]}}
\end{itemize}

\vspace{6mm}
Measuring innovation using patent data has limitations:
\begin{itemize}
\item Many inventions are not patented and the propensity to patent a given invention appears to vary tremendously across industries {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Cohen et al. 2000, Levin et al. 1987]}}
\item Patents vary in their quality and value {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Pakes 1986, Schankerman and Pakes 1986]}}
\end{itemize}
\end{frame}

\begin{frame}
\frametitle{Measuring innovation: non-patent alternatives}
\vspace{3mm}
\begin{itemize}
\item Scientific publications
    \begin{itemize}
        \item Drawback: decision to publish differs by industry, and non-academics will publish less frequently
    \end{itemize}
\item R\&D investments
    \begin{itemize}
        \item Drawback: doesn't provide much insight into the types and value of inventions being pursued by firms
    \end{itemize}
\item Clinical trials and new drug approvals
    \begin{itemize}
        \item Drawback: limited to innovation in health care markets
    \end{itemize}
\end{itemize}
\end{frame}

\begin{frame}
\frametitle{Measuring innovation: returning to spillovers}
Knowledge flows may sometimes leave paper trails
\vspace{3mm}
\begin{itemize}
\item Patent citations – acknowledgements of the use of knowledge in subsequent patents – may capture relationships between inventions
\begin{itemize}
    \item Imperfect measure: citations can serve a legal purpose (disclosing prior art) and can be added by patent examiners (not applicants)
\end{itemize}
\item Literature has focused on using patent citations to measure technological and geographic distance
\begin{itemize}
    \item Jaffe (1986) uses technological distance - based on USPTO-assigned technology classes - to estimate a firm's ``potential spillover pool'' in patent data
    \item Jaffe, Trajtenberg, and Henderson (1993) uses geographic distance between firms to examine whether patent citations are localized
\end{itemize}
\end{itemize}
\vspace{3mm}

One central issue that arises is the distinction between testing for the existence of spillovers versus quantifying the magnitude of spillovers. {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Bloom et al. 2013]}}
\end{frame}

\begin{frame}
\frametitle{Inference challenges}
Even if we can agree on a measure of innovation, in order to understand how policy shapes inventive activity, we need to construct the appropriate counterfactuals
\vspace{3mm}
\begin{itemize}
\item Where there is ample variation within a single policy lever (e.g., tax rates) across similar geographic units (e.g., states), generating counterfactuals is relatively straightforward
\begin{itemize}
    \item For example: inventor mobility in response to tax rates.
\end{itemize}
\item Contrast with: uniformity of patent terms in the United States
\end{itemize}
\end{frame}

\end{document}