Financial Innovation and the Inequality Gap

Financial Innovation and the Inequality Gap Roxana Mihet ∗ Latest version here November 26, 2020 Abstract Information-based models of capital income inequality that link return hetero- geneity to investor sophistication levels need to assume an increase in data costs over time to generate widening inequality. Empirically, this assumption contradicts evidence that investment markets have become more informative over time, and theoretically, it also overlooks the possibility that poorer investors can avoid paying a large fixed cost for research, simply by buying shares in a fund. In this paper, I study the impact of financial innovation on capital income inequality in a theoretical framework where investors, heterogeneous in their sophistication, have a costly choice between not investing, investing through a fund of average quality, and searching for an informed fund. The model predicts that while financial innovation can make the investment sector more efficient and boost financial inclusion, some financial innovation also brings risks. For example, when the cost of financial data processing falls, more investors trade on information. This makes participation less valuable for the uninformed marginal stock market participant, who is a poorer investor in some average fund and who exits the market altogether, fore- going the equity premium. The decrease in the participation of relatively poorer investors amplifies inequality. Empirically, this negative force has been very strong in the last 20 years and it can explain why, in spite of a dramatic reduction in data processing costs and fund fees, the US stock market has become less inclusive and more unequal and the participation rate has declined. JEL codes: E21, G11, G14, L1, L15 Keywords: Quant Analysis, Fintech, Inequality, Participation, Funds. ∗Acknowledgements: I am indebted to my committee members: Laura Veldkamp, Thomas Philippon, Thomas Sargent and Venky Venkateswaran for their invaluable support and encouragement. I am also grateful for many interesting discussions to Jess Benhabib, Andrea Buffa, Jerome Dugast, Paymon Khorrami, Joseba Martinez, Pricila Maziero, Guido Menzio, Cecilia Parlatore, Luigi Pistaferri, Xavier Vives, Ansgar Walther and Desi Volker. I also thank conference participants at the Wharton Women in Business 2018, Chicago Booth Asset Pricing 2018, the Future of Financial Information 2019, the NBER AI Workshop 2018 and 2019, ASSA 2019, the 14th Macro-Finance Society Conference 2019, WFA 2020, EEA 2020, and seminar participants at UT Austin McCombs, BU Questrom, NY FED, FED Board, BIS, Goldman Sachs, McGill Desautels, Copenhagen Business School, HEC Lausanne, University of Luxembourg, IESE Business School, Tilburg University, Amsterdam School of Economics, Columbia University, NYU, and NYU Stern for helpful comments and feedback. This paper was supported by a research fellowship at the Bank of International Settlements under the guidance of Stijn Claessens and Hyun Shin. It was awarded the 2020 Young Economists' Competition Prize (by the ECB), the 2019 European Best JM Paper Special Mention Prize (by the EEA), a Macro Financial Research Initiative Grant (by the BFI), and the 2020 Cubist Prize for Outstanding Doctoral Research (by the WFA). All errors are my own. Contact: [email protected]. 1 1 Motivation Information-based models of capital income inequality that link return heterogene- ity to investor sophistication levels (Arrow(1987), Peress(2004), and Kacperczyk et al. (2018)) need to assume an increase in data processing costs over time to generate an am- plification of inequality. Empirically, this assumption contradicts evidence by Bai et al. (2016) that investment markets have become more informative over time. Theoretically, it also overlooks the possibility that poorer investors can avoid paying a large fixed cost for data acquisition, simply by buying shares in a fund. By investing through a fund, investors can share the cost of research and together, they should be able to replicate the returns of a wealthier investor. Building on a framework similar to Garleanu and Pedersen(2018) where investors search for funds, I extend the classical portfolio choice information-based model to allow heterogeneous investors the choice between non-participating in the equity market, or participating either through some average fund or through an informed fund. I then use the model as a lab to study the effects of financial innovation on households' investment- saving behavior, the efficiency of the equity and investment management markets, and capital income inequality. The main departure from Garleanu and Pedersen(2018) is that investors are heterogeneous in their wealth, which impacts their decision whether to not invest at all or to invest through funds with differential access to information. The asset market consists of a risky security with a stochastic payoff and a riskless asset with a small rate of return. I assume that investors first need to pay a small fixed entry cost to participate in the security market. Many theoretical models appeal to such costs to limit participation because in the data, even relatively low entry costs can keep a large percentage of the population away from financial markets (Haliassos and Michaelides (2003)). In practice, these costs are diverse and comprise of brokerage fees, but also time and money spent acquiring a basic financial education about the investment process. To invest through a good fund, similar to Garleanu and Pedersen(2018), investors have to pay a cost of searching for a good fund and an asset management fee that will depend on the quality of the fund found. While the search process involves many details, this process is time consuming and costly. For instance, there exist more funds than stocks in the United States. Many of these funds charge high fees while investing with little or no real information, claim to be active but in fact track the benchmark, or invest more in marketing than in their investment process. Therefore, finding a good fund is not easy for investors. Lastly, I assume that both investors and fund managers have the possibility to acquire costly private information about the risky security. This represents the process of fundamental research and facilitates a more educated portfolio allocation choice. Within this setting, I model financial innovation as a reduction in the cost of partic- 2 ipation, and in the the cost of data processing, for the investor and the fund, over time. The model is highly tractable despite its apparent complexity and reconciles multiple empirical facts that previous models cannot jointly explain. It also delivers several new predictions that link inequality with the level of efficiency in the security market and with the level of competition in the market for fund management. Wealthy investors benefit from searching for good (informed) funds since their search cost is low relative to capital. Hence, funds with wealthier investors outperform, creating inequality between wealthy and less wealthy investors. The surprising finding is that when the costs of data processing for the investor or the fund fall, inequality gets amplified, even if the efficiency of the equity market increases. The intuition is that financial innovation allows more investors to trade on information. This makes market participation less valuable for the less-well-informed. Because the marginal stock market participant is an uninformed fund investor, not an informed fund investor, the returns to paying the fixed cost for participation fall. Thus, this marginal participant stops participating in the risky asset, forgoing access to the equity premium. This mechanism rationalizes why in the last decades, despite the fact that the cost of individual investor trading has fallen enormously, the overall stock market participation rate has been declining, as well. The key prediction is that, while financial technology reduces barriers to access, and holds out the promise of gains for all, it also deters financial market participation. In so doing, financial technology may be amplifying capital income inequality. In the classical model, a cheaper cost of data processing lowers capital income inequality because it allows more investors access to private information which improves return performance. But in this modified model with a fixed cost of stock market participation, cheaper data processing, for the investor or the fund, does not close the inequality gap. On the contrary, it amplifies it as improvements in financial information technologies make information-based trading more attractive than uninformed trading and low-wealth uninformed investors end up competing with more aggresively informed traders, who drive the returns from uninformed investing down. Thus, uninformed investors no longer find it attractive to pay participation fees just to invest uninformedly so they exit the market. This mechanism amplifies inequality precisely because it lowers participation in the risky asset. However, the mechanism generates an increase in market efficiency and leads to a larger and more concentrated informed fund management sector. Both of these trends are also observable in the US in the last two decades, along with a decrease in overall participation levels, consistent with the theory. My contribution is twofold: Firstly, I provide a tractable way to reconcile several empirical facts by building a theoretical information-based general equilibrium framework where investors can share the costs of information by pooling

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