- Dirty Air and Clean Investments: The impact of pollution information on ESG investment (with R. Fisman, P. Ghosh and A. Sarkar).
Abstract
We study exposure to pollution information and investment portfolio allocations, exploiting the rollout of air quality monitoring stations in India. Using a triple-differences framework, we show that retail investors' investments in ``brown'' stocks are negatively related to local air pollution after a monitoring station appears nearby, with particularly pronounced effects on ``alert'' dates when air quality is listed as harmful to the general population. The effect of pollution information on investment choices is most prominent amongst tech-savvy investors who are most plausibly ``treated'' by real-time pollution data, and by younger investors who tend to be more sensitive to environmental concerns. Overall, our results provide micro-level support for the view that salience of environmental conditions affect investors' tastes for green investments.
- Co-Collateral and the Shadow Cost of Margin Constraints (with M. Massa, C. Wang and H. Zhang).
Abstract
We propose a novel stock-level measure of the tightness of margin constraints by decomposing a stock’s cash collateral requests in the short-selling market into two components: comovements with the market (co-collateral) and idiosyncratic movements. Consistent with the notion that co-collateral tightens margin requests, we find that co-collateral reduces short-selling activities and is associated with a positive return premium. Moreover, this premium peaked during the crisis (especially the Lehman bankruptcy) and is unexplained by traditional asset pricing factors or mispricing. Our results highlight the importance of collateral requests and the associated shadow costs in influencing asset prices.
- Opioid Crisis and Local Economic Pain: Evidence from Commercial Real Estate Loan (with Y. Yildirim and B. Zhu).
Abstract
This study examines the local economic impacts of the opioid epidemic by focusing on the performance of commercial real estate loan. We establish causal identification by leveraging plausible exogenous variation in primary physicians per capita and staggered adoption of state-level Opioid Misuse Prevention Legislation. Our findings indicate that opioid abuse decreases net operating income and increases vacancy rates, leading to a surge in loan defaults. We present direct evidence for economic channels showing that opioid abuse disrupts local economies through reduced business sales and eroded neighborhood desirability, which decreases net operating income and lowers occupancy rates of commercial real estate properties, ultimately leading to higher default rate. The effect is more severe in residential and retail properties, areas with weaker economic conditions, communities with higher proportions of Black and Asian populations, younger individuals, and Republican states. Our study underscores a new negative externality of the opioid crisis on local economies and its spillover effects on financial markets.
- The Digital Revolution: Bridging the Information Gap in the Consumer Credit Market (with S. Agarwal and Y. Wang).
Abstract
We analyze how an information communication technology shock resolves information friction in the largest and most significant consumer credit markets. Using granular spatial variation of broadband diffusion, we find that high-speed Internet access enables consumers to save an average of 327 – 738 dollars on mortgage broker fees. These savings are economically meaningful and can partially offset the annual broadband subscription cost of $444. The effect is more pronounced for well-educated, high-FICO, and high-income customers, and in areas with a competitive broker market ex-ante. We identify greater bargaining power and reduced search costs as mechanisms behind the fee reductions.
- Does Geopolitical Risk Exposure Lead to Higher Cost of Debt? Evidence from Multinational Companies (with F. Hu, T. Lin and W. Tan).
Abstract
Multinational companies (MNCs) listed in the U.S. and their global subsidiaries with greater exposure to geopolitical risk (GPR) have higher bank loan costs. The effect is robust to alternative model specifications, interpretations, and measurements. Horserace tests suggest that GPR is a distinct and superior proxy for host-country-level risk factors and has a more robust effect on a firm's cost of debt. We find consistent results when employing two identification strategies – a Bartik-type instrument and a difference-in-differences design around the 2014 Russia-Ukraine conflict and 2022 Russia-Ukraine War – to isolate exogenous variations in GPR exposure. We also identify two economic channels, i.e., operational flexibility and currency risk, that explain our findings. The effect is stronger among MNCs which have larger geo-political risk exposure, higher credit risk, no prior banking relationship and facing weaker formal institutions. Finally, we document a positive relation between global subsidiaries’ GPR and an MNC’s cost of equity.
- A Tale of Two Zoos: Machine Learning Insights on Retail Investors (with P. Ghosh, H. Lu and H. Zhang).
Abstract
We employ various machine learning models to analyze the returns for millions of retail investors in India. We observe that Neural Networks outperform other machine learning and OLS models in uniquely predicting both good and bad out-of-sample performance. Behavioral biases exert a more significant influence on their returns than holding-weighted firm characteristics.
- When Human Met Algorithm: Evidence from Retail Investor Trading (with P. Ghosh and Y. Li).
Abstract
We study the adoption and economic impact of artificial intelligence technology by retail investors in a developing economy. We document new facts to characterize the human-algorithm interaction in the context of retail investor trading using administrative account-level data of all individual investors from National Stock Exchange of India, the world's 8th largest stock exchange. While the retail algorithmic trading market is dominated by male investors, the relative share of female algorithmic participation increases steadily from 5% in 2012 to 10% in 2019. We find that algorithmic trades by male-young investors take up most of the overall increase in recent years and are highly procyclical to the market condition. Investors adapting to algorithmic trading experience better performance as measured by higher market-adjusted return and Sharpe ratio. The benefit is greater for less wealthy investors and those who are holding less diversified portfolio or exhibit more behavioral bias ex ante. We find evidence that improved performance is likely due to enhanced trading responsiveness to new market information and reduced behavioral biases. Consistent with “learning by algorithmic trading”, unprofitable algorithmic traders are more likely to quit than profitable traders. Algorithmic trade size is also sensitive to past performance and retail algorithmic investors initially execute very small trades during the first few trials and increase trade size significantly after profitable trades.
- Value Added Tax and Corporate Product Mix Decisions (with P. Ghosh, Y. Kang and M. Jacob).
Abstract
This paper investigates the effect of consumption taxes on firms’ product mix decision. Using a stacked difference-in-differences approach that exploits the staggered transition from a sales tax with the risk of tax cascading to a value added tax (VAT) with credits on inputs across states in India and detailed data on listed manufacturing firms’ production decisions, we document that the switch to a VAT system induces affected firms to narrow their product scope. That is, firms cut the internal production of input goods and instead focus their production toward their best-performing products. Firms affected by the switch to the VAT reduce their firm size and are more likely to outsource production of input goods, consistent with vertical disintegration following VAT adoption. We also show that this VAT-induced vertical disintegration results in lower manufacturing costs, higher profitability and firm value, and increased investment efficiency for affected firms. Overall, the paper shows that VAT adoption can reduce investment and productivity distortions induced by a sales tax that bears the risk of tax cascading.
- The Surprising Green Performance of Retail Investors: A New (Behavioral) Channel (with S. Agarwal, Y. Bao, P. Ghosh, and H. Zhang).
Abstract
Contrary to the prevailing wisdom that green investors willingly accept lower returns for sustainable investment, our analysis of account-level data from a major Indian bank indicates the opposite. We find that investors with a higher proportion of green stocks in their portfolios achieve superior risk-adjusted portfolio returns. To explain this surprising observation, we hypothesize—and empirically verify—that green investments may help investors mitigate detrimental behavioral bias, such as the disposition effect and under-diversification. Alternative mechanisms related to stock selection ability, aggregate demand shocks, and risk mitigation fail to explain green performance. Instead, tests utilizing abnormal temperatures as exogenous shocks support a causal interpretation of our findings. These results suggest a novel behavioral channel for fully understanding the implications of green preferences.
