\documentclass{beamer}
\usepackage{graphicx}
\usepackage{setspace}
\usepackage{comment}
\usepackage{amsmath}
\usepackage{natbib}
\usepackage[dvips]{rotating}
\usepackage{url}
\usepackage{hyperref}
\usepackage{booktabs}
\usepackage{tabulary}
\usepackage{subfigure}
\usepackage{ragged2e}
\usepackage[justification=centering]{caption}[2007/12/23] 
\usetheme{Boadilla}

\newcounter{saveenumi}
\newcommand{\seti}{\setcounter{saveenumi}{\value{enumi}}}
\newcommand{\conti}{\setcounter{enumi}{\value{saveenumi}}}

\resetcounteronoverlays{saveenumi}

\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]
\end{comment}

\title[]{Innovation: Market Failures and Public Policies} 
\subtitle{Lecture 8: Innovation and inequality \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{} 

\graphicspath{{graphics/}}

\begin{document}
	
\frame{\titlepage}

\begin{frame}{Introduction}
    
In recent decades, income inequality has risen in the US and other developed countries {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Piketty and Saez 2003]}}

\vspace{3mm}

Links between innovation and inequality:
\begin{itemize}
    \item Has innovation contributed to the observed rise in inequality?
    \item How do policies like the patent system - which divide returns to new inventions among inventors, firms and consumers - affect inequality?
    \item Does inequality in opportunity lead us to lose potential innovators?
\end{itemize}

\vspace{3mm}

The economic literature on these questions is still very much in its infancy, but we here highlight some relevant work with an eye towards highlighting areas with particular promise for future work
\end{frame}

\section{Does innovation increase inequality?}

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

\begin{frame}{Innovation and inequality}
    
Theoretically, innovation affects inequality across a variety of models

\vspace{3mm}

\begin{itemize}
    \item The Schumpeterian growth model of Aghion et al. (2019) predicts that easier quality improvements by either the incumbent or entrants allow higher markups, hence increasing inequality
    \begin{itemize}
        \item It also predicts that entrant innovation increases social mobility
    \end{itemize}
    \item Jones and Kim (2018) only allows incumbents to improve existing technology over time, occasionally getting replaced by disruptive technology
    \begin{itemize}
        \item In the short run: when incumbents easily build on existing ideas, inequality increases
        \item In the long run: more incumbent innovation $\rightarrow$ more variance in entrant R\&D payoffs $\rightarrow$ risk-averse inventors shy away from investment in innovation
        \item Consequently, sclerotic economies with powerful incumbents have high inequality and low growth
    \end{itemize}
\end{itemize}
    
\end{frame}

\begin{frame}{Macro approaches: Aghion et al. (2019)}

Aghion et al. (2019) utilize a macro-level approach to investigate innovation and inequality

\vspace{3mm}

\begin{itemize}
    \item The authors document that state-level changes in innovation (as measured by log patent citations per capita) are correlated with increases in the top 1\% income share
    \item The paper uses an IV strategy to test for causality, arguing that the composition of the US Senate Committee on Appropriations affects patenting and innovation at the state level
    \item IV estimates: an increase of 1\% in patents increases the top 1\% income share by 0.2\%
\end{itemize}
    
\end{frame}

\begin{frame}{Micro approaches: Cutler et al. (2012)}

Cutler et al. (2012) asks how a social planner allocating funds for medical research can maximize social welfare by minimizing mortality rates, subject to a fixed budget constraint

\vspace{3mm}

Equalizing expected marginal benefit of research across diseases:
\begin{enumerate}
    \item Initial death rates positively correlated w/ subsequent research efforts
    \item Innovation associated with more rapid mortality declines
    \item Induced innovation will increase mortality disparities between minorities and the majority group if the groups differ in their shares of deaths from ``leading causes''
\end{enumerate}

\vspace{3mm}

Find evidence for these predictions in the context of US infant mortality\\
\vspace{3mm}
Results suggest that public research support responds to aggregate medical need and improves aggregate outcomes 
\begin{itemize}
    \item In focusing on diseases that are most prevalent in the population as a whole, disproportionate share of benefits accrued to white infants 
\end{itemize}
\end{frame}

\begin{frame}{Micro approaches: Jaravel (2019)}

Jaravel (2019) contrasts two narratives about who benefits from innovation, and tests them empirically

\vspace{3mm}
    
\begin{enumerate}
    \item Everyone benefits: innovation is initially aimed at the rich, but a trickle-down process eventually brings products to the mass market
    \item The rich benefit: rising income inequality implies that demand will grow faster for ``premium'' products (e.g. organic products) that are disproportionately consumed by richer households
    \begin{itemize}
        \item Entry of new products increases product variety and reduces prices in premium categories, generating disproportionate benefits for consumers of those goods
    \end{itemize}
\end{enumerate}

\vspace{3mm}

Jaravel uses scanner data to test the second narrative, finding that high-income households experience faster increases in product variety and lower inflation in the US retail sector
    
\end{frame}

\begin{frame}{Micro approaches: Van Reenen (1996), Kline et al. (2019)}

Well-established economic literature documents evidence that some firms appear to pay higher wages than others

\vspace{3mm}

\begin{itemize}
\item Van Reenen (1996) uses quasirents earned by firms developing innovations as a source of quasi-experimental variation in firm rents
\item Are firm rents passed through to workers in the form of higher wages?
\begin{itemize}
    \item Unfortunately, limited data prevented Van Reenen from testing for a causal relationship between innovation-generated rents and wages
    \item Kline et al. use USPTO data, US Treasury tax filings, and variation in USPTO allowance decisions to identify causal effects of patent allowances on firm/worker outcomes
\end{itemize}
\item Patent allowances raise average earnings at the firm level, but increases are concentrated amongst top earners, and stronger for males.
\end{itemize}
    
\end{frame}

\section{Is inequality causing society to lose potential innovators?}

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

\begin{frame}{Measuring of innovation losses from inequality}

\begin{itemize}

\item Does inequality result in ``missed opportunities'' where individuals who could contribute socially valuable ideas fail to have the opportunity to realize their potential?

\vspace{3mm}
    
\item Obstacle: most large administrative datasets (e.g. USPTO patent records) providing measures of innovative activity list few demographic variables

\vspace{3mm}

\item Without directly-measured data on demographics such as race and gender, researchers attempt to indirectly infer these variables

\end{itemize}
    
\end{frame}

\begin{frame}{Identifying race and gender}
    
\begin{itemize}
    \item Jensen et al. (2018) assigns probable gender of inventors by matching first names of inventors to the gender distribution of those names in administrative data.
    \begin{itemize}
        \item Several other papers use this technique to measure gender differences in innovation {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Kolev et al. 2020, Ewens and Townsend 2020, and others]}}
    \end{itemize}
    
    \vspace{3mm}
    
    \item Cook (2014) identifies African American inventors by hand-linking patent records to surveys, matching patent records to US census data, and curating lists of African American scientists based on qualitative sources like obituaries
    \begin{itemize}
        \item Cook documents that the gap in patenting between African Americans and whites is larger during periods of ethnic and political violence
    \end{itemize}
\end{itemize}

\end{frame}

\begin{frame}{Income and invention}

Three recent papers examine the demographic factors correlated with becoming an inventor, with a particular focus on the role of parental resources

\vspace{3mm}

\begin{itemize}
    \item Bell et al. (2019): links patents to administrative US tax records
    \item Akcigit et al. (2017) links patents to historical US census records
    \item Aghion et al. (2018) links patents to Finnish registry data
\end{itemize}

\vspace{3mm}

The shared conclusion: individuals are 10 times more likely to patent if their father is at the top of the income distribution rather than the bottom

\vspace{3mm}

The similarity of results across all three papers is striking, given that Finland displays much lower income inequality and higher social mobility than the US {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Aghion et al. 2018]}}
    
\end{frame}

\begin{frame}{Parents' income vs. becoming an inventor}

\vspace{-6mm}

\begin{center}
    \includegraphics[scale=0.43]{figure16_parent_income.pdf}
    \end{center}
\scriptsize \textcolor{red!75!green!50!blue!25!gray}{}

\end{frame}

\begin{frame}{More differences between demographic groups}

What could explain differences in likelihood of inventing across demographic groups?

\vspace{3mm}

Several papers have designed empirical tests to help answer this question:
\begin{itemize}
    \item Ellison and Swanson (2020): top girls in American Mathematics Competitions are drawn predominantly from a small group of elite schools, whereas boys come from a variety of backgrounds
    \item Agarwal and Gaule (2020): International Mathematical Olympiads participants from low-income countries produce 34\% fewer publications and 56\% fewer citations in mathematics than same-score participants from high-income countries
    \item Bell et al. (2019) uses a variety of approaches (e.g. analyzing children who move between high- and low-innovation areas) to argue for a causal interpretation between one's ``exposure'' to innovation during childhood and propensity to innovate
\end{itemize}
    
\end{frame}

\begin{frame}{Quantitatively important}

While previous results suggest that change in public policies could increase the supply of inventors from less-advantaged backgrounds, descriptive evidence makes it difficult to infer the quantitative importance of these channels
\vspace{3mm}

Hsieh et al. (2019) observes the convergence in occupations across gender and race during the 20th century
\begin{itemize}
    \item In 1960, 94 percent of doctors and lawyers were white men, compared to 60 percent in 2010
    \item Suggests a substantial pool of women and non-white men may not have been pursuing their comparative advantage in 1960
    \item An estimated 20-40\% of the increase in output per person between 1960 and 2010 can be explained by an improved allocation of talent
\end{itemize}
    
\end{frame}

\begin{frame}{Summing up}

\begin{itemize}

\item Benefits of innovation may disproportionately accrue to high-income, majority groups {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Aghion et al. 2019, Cutler et al. 2012, Jaravel 2019, Kline et al. 2019]}}

\vspace{3mm}

\item Inequality results in ``missed opportunities'' where individuals with valuable ideas don't have the opportunity to innovate
\begin{itemize}
    \item Individuals are many times more likely to become innovators if they grow up in high-income households {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Akcigit et al. 2017, Bell et al. 2019, and Aghion et al. 2018]}}
    \item Students from low-income countries, girls from non-elite schools, and children from low-innovation areas don't innovate as frequently as their peers {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Ellison and Swanson 2020, Agarwal and Gaule 2020, Bell et al. 2019]}}
    \item The convergence in occupation across gender and race in the US has led to large productivity gains {\scriptsize \textcolor{red!75!green!50!blue!25!gray}{[Hsieh et al. 2019]}}
\end{itemize}

\end{itemize}

\end{frame}

\end{document}