Air pollution and stock returns in the US
Introduction
The Air Quality Index (AQI), composed by the US Federal Environmental Protection Agency (EPA), is an index for reporting daily air quality. It indicates the levels of air pollution and the health issues that may be of concern as a result of these levels. Exposure to these pollutants is associated with numerous effects on human health, including mental and mood (emotional) changes. The purpose of the AQI is to help understand what local air quality means to health. The AQI ranges from 0 to 500. The higher the AQI value, the greater the health danger. AQI values between 0 and 100 are defined by the EPA as “Good” (or “Moderate”). At this range air quality is considered satisfactory, and air pollution poses little or no risk. Values between 101 and 500 are considered “Unhealthy”. Though the proportion of Unhealthy days has been relatively low in the US, numerous studies, reviewed below, indicate that air pollution in the US causes various types of negative health-related effects.
Air pollution is a major health and economic concern in industrialized countries. While its health effects have been studied extensively, its impact on stock markets, as far as we know, has not been investigated yet. The relationship between air pollution and mood and that between mood and decision making, documented in the literature, may have implications for the relationship between air pollution and investors’ behavior in the stock market. The goal of this paper is to investigate whether there is a relationship between air pollution and investors’ behavior in the stock market. We hypothesize that unhealthy air quality, mediated by mood, may lead to a collective change in the level of risk aversion, resulting in lower stock returns.
The remainder of this study is organized as follows. Section 2 presents some psychological evidence about the relationship between air pollution, mood and decision making, and about the economic consequences of mood-related decision making. Section 3 discusses the derived hypotheses. Section 4 outlines the methodology and describes the data. Section 5 presents the findings and discusses the results; Section 6 describes a potentially profitable trading strategy and Section 7 concludes the study.
Section snippets
Scientific background
Numerous studies in psychology demonstrate that air pollution can have both direct and indirect effects on psychological and mental states (see, e.g., Bullinger, 1990). These effects can lead to a variety of physical, mental and mood changes. Given these negative effects of air pollution, in the following sections we will discuss three inter-related issues: air pollution and mood, mood and decision making and the relationship between mood-related variables and stock returns established in the
The hypotheses
In formulating the hypotheses in this study, we draw upon the earlier studies reviewed above, which found a relationship between (a) air pollution and bad mood, (b) bad mood and increased risk aversion, and (c) increased risk aversion and negative stock returns. We formulate three inter-related hypotheses for testing the “pollution effect” – namely, the effect of air pollution on stock returns.
The first hypothesis deals with the relationship between air pollution and stock returns. The second
Method
To test whether the level of the air pollution affects stock returns, we employ the following methodology. First, we draw a sample of daily returns. Second, we determine the AQI for each trading day. We then divide the sample into two categories, according to the level of the AQI – Good and Unhealthy. Unhealthy AQI levels, as argued in the literature briefly reviewed above, can have a negative impact on health, mood and decision making. Thus, this AQI level is expected to have a negative impact
The findings for Hypothesis 1
The findings for the five indices are summarized in Table 1 and Fig. 1a. The table shows the descriptive statistics of the daily stock return by the AQI levels in the nearest county (kings) in New York for five indices: the S&P 500, the DJIA, the NASDAQ Composite Index, the AMEX Composite Index and the Philadelphia Stock Exchange (PHLX) Utility Sector Index. The mean daily return for a particular stock index is given as the average of the daily return across all trading days in the sample time
Potential trading strategy
The various findings provided in the preceding section suggest that gains can potentially be made by employing a trading strategy based on (1) the negative relationship between stock returns and air pollution observed in this study, (2) the existence of a strong correlation between air pollution forecasts and actual air pollution (see, e.g., Cogliani (2001)), and (3) the presence of a positive correlation between the *current-day AQI and the previous-day AQI. It thus follows that in practice,
Summary and conclusions
This study builds upon two types of studies. The first type has investigated the impact of air pollution on mood, whereas the second type has dealt with the relationship between stock returns and mood variables. This line of research is extended in this study by investigating whether the psychological effects caused by air pollution (reported in the literature) can potentially have financial implications. Specifically, we confine our investigation to the “pollution effect”; namely, the
Acknowledgement
We would like to express our very special thanks to professor Fergus Bolger. We have received very valuable comments and suggestions from him.
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