Pieter de Jong

The effect of ISO 14001 certification announcements on stock performance

Purpose – This study aspires to explore how the US stock market reacts to ISO 14001 certification announcements.Design/methodology/approach – The paper employs an event‐study methodology on a sample of 140 announcements and matching control firms to study the impact of ISO 14001 certification announcements.Findings – The results suggest that ISO 14001 certification announcements have a negative impact on stock performance. More importantly, they show that the shareholder wealth reduced due to these certifications announcements.Research limitations/implications – This study focuses on short‐term stock market reaction. Future studies should consider the entire sample of ISO 14001‐certified firms within the USA and use certification date to evaluate short‐ as well as long‐term improvements in shareholder wealth.Practical implications – The results suggest that firms will need to educate shareholders about their actions towards the betterment of the environment. Such coordinated communication will ensure that...

Toward a Comprehensive Framework of Study Abroad Intentions and Behaviors

Increased activity by U.S. students to study abroad has invited several studies that have investigated the reasons for U.S. students to study abroad. Literature in the context of study abroad choices has been fragmented, with each study presenting an ad-hoc set of factors the author/s deem as important or that have been shown to be important in previous literature. However, no study to date has attempted to identify a theoretical framework that explains why these factors should be important in explaining the intention to participate in a study abroad program. In this study, we use the theoretical background of the Theory of Planned Behavior (TPB) and trait theory to unify the existing body of literature and arrive at a model that predicts study abroad intentions. We test this model by means of a survey administered in a U.S. university.

Does investment lead to greater output? A panel error-correction model analysis

In this study we attempt to determine the direction of causality between fixed investment spending and output. A literature has been developed which examines this causal structure. The results have been anything but consistent. De Long and Summers (1991) find strong evidence of the traditional causal relationship from investment to output growth. But Blomström et al. (1996) find just the opposite. One problem with these studies is that each fails to recognize the implied long-run relationship between fixed investment and output such that a Vector Autoregressive Representation (VAR) in these variables should be modelled as an error correction mechanism. We employ panel cointegration techniques on data from the Penn World Tables 6.1 covering 98 countries over 40 years. Our results suggest that investment and output are cointegrated and that the direction of causality generally runs in both directions. However, we find that in African- and low-income nations the direction of causality runs from output to investment, supportive of the findings by Blomström et al. (1996). This pattern is found in the short run as well as in the long run.

From Returns to Tweets and Back: An Investigation of the Stocks in the Dow Jones Industrial Average

ABSTRACT A sizeable percentage of investors are using social media to obtain information about companies (Cogent Research [2008]). As a consequence, social media content about firms may have an impact on stock prices (Hachman [2011]). Various studies utilize social media content to forecast stock market-related factors such as returns, volatility, or trading volume. The objective of this article is to investigate whether a bidirectional intraday relationship between stock returns and volatility and tweets exists. The study analyzed 150,180 minute-by-minute stock price and tweet data for the 30 stocks in the Dow Jones Industrial Average over a random 13-day interval from June 2 to June 18, 2014 using a BEKK-MVGARCH methodology. Findings indicate that 87% of stock returns are influenced by lagged innovations of the tweets data, but there is little evidence to support that the direction is reciprocal, with only 7% of tweets being influenced by lagged innovations of the stock returns. Results further show that the lagged innovations from 40 percent of stock returns affect the current conditional volatility of the tweets, while 73 percent of tweets affect the current conditional volatility of stock returns. Moreover, there is strong evidence to suggest that the volatility originating from the returns to the tweets persists for 33 percent of stocks; the volatility originating from the tweets to the returns persists for 73 percent of stocks. Last, 53 percent of stocks exhibit both immediate and persistent impacts from returns to tweets, while 90 percent of stocks exhibit both immediate and persistent impacts from tweets to returns. These results may help traders achieve superior returns by buying and selling individual stocks or options. Also, asset and mutual fund managers may benefit by developing a social media strategy.