This study shows that the propensity to gamble and investment decisions are correlated. At the aggregate level, individual investors prefer stocks with lottery features, and like lottery demand, the demand for lottery-type stocks increases during economic downturns. In the cross-section, socioeconomic factors that induce greater expenditure in lotteries are associated with greater investment in lottery-type stocks. Further, lottery investment levels are higher in regions with favorable lottery environments. Because lottery-type stocks underperform, gambling-related underperformance is greater among low-income investors who excessively overweight lottery-type stocks. These results indicate that state lotteries and lottery-type stocks attract very similar socioeconomic clienteles.

This study shows that individual investors systematically shift their preferences across extreme style portfolios (small vs. large, value vs. growth). These preference shifts are influenced by past style returns and earnings differentials, and advice from investment newsletters, but are unaffected by innovations in macroeconomic variables or shifts in expectations about future cash flows. Furthermore, investors’ dynamic style preferences influence returns along multiple dimensions: i) the contemporaneous relation between style returns and style-level preference shifts is strong, ii) there is weak evidence of style return predictability, and iii) the correlations among stocks within a style increase when investors move into or out of the style with greater intensity. Overall, the results indicate that stock categorization influences investors’ portfolio decisions and stock returns.

This paper uses investor-level data to provide direct evidence for an intuitive but surprisingly untested proposition that investors make larger investment mistakes when valuation uncertainty is higher and stocks are more difficult to value. Using multiple measures of valuation uncertainty and multiple behavioral bias proxies, I show that individual investors exhibit stronger behavioral biases when stocks are harder to value and when market-level uncertainty is higher. I also find that informed trading intensity is higher among stocks where individual investors exhibit stronger behavioral biases. Collectively, these results indicate that uncertainty at both stock and market levels amplifies individual investors’ behavioral biases and that relatively better informed investors attempt to exploit those biases.

Many stock exchanges choose to reduce market transparency by allowing traders to hide some or all of their order size. We study the costs and benefits of order exposure and test hypotheses regarding hidden order usage using a sample of Euronext-Paris stocks, where hidden orders represent 44% of the sample order volume. Our results support the hypothesis that hidden orders are associated with a decreased probability of full execution and increased average time to completion, and fail to support the alternate hypothesis that order exposure causes defensive traders to withdraw from the market. However, exposing rather than hiding order size increases average execution costs. We assess the extent to which non-displayed size is truly hidden and document that the presence and magnitude of hidden orders can be predicted to a significant, but imperfect, degree based on observable order attributes, firm characteristics, and market conditions. Overall, the results indicate that the option to hide order size is valuable, in particular, to patient traders.

This study shows that the propensity to gamble and investment decisions are correlated. At the aggregate level, individual investors prefer stocks with lottery features, and like lottery demand, the demand for lottery‐type stocks increases during economic downturns. In the cross‐section, socioeconomic factors that induce greater expenditure in lotteries are associated with greater investment in lottery‐type stocks. Further, lottery investment levels are higher in regions with favorable lottery environments. Because lottery‐type stocks underperform, gambling‐related underperformance is greater among low‐income investors who excessively overweight lottery‐type stocks. These results indicate that state lotteries and lottery‐type stocks attract very similar socioeconomic clienteles.

The increasing body of evidence from high income countries linking pollution to health outcomes (Ken Chay and Michael Greenstone 2003; Janet Currie and Matthew Neidell 2004), has raised concerns about the health impact of adverse air quality in developing countries, where, in general, environmental regulation is less stringent and health monitoring and treatment are less accessible. These concerns have, in turn, encouraged consideration of the effectiveness of alternative mechanisms for improving air quality while limiting the adverse impact on economic growth. However, the analysis of both the effects of pollution on health and the effectiveness of pollution abatement policies faces particular empirical challenges in low- and middle-income contexts, given the scarcity of reliable measures of pollution concentrations. The primary source of good quality data on air quality, ground monitoring, tends to be limited to larger metropolitan areas with monitors placed at sentinel sites that may or may not yield a representative picture of population exposure. This paper calls attention to, and makes use of, newly available procedures for extracting measures of air quality from satellite imagery. In particular, satellite-based measures of aerosol optical depth (AOD) are used to obtain estimates of air quality for the whole Mexican territory at a detailed geographic scale, and these estimates are related to measures of participation in a voluntary certification program at the level of the county. The resulting estimates are then combined with estimates of the relationship between participation in the certification program and infant mortality due to respiratory causes to obtain a rough estimate of the relationship between air quality and infant health in Mexico.