R&D investment intensity and jump volatility of stock price

Review of Quantitative Finance and Accounting - This paper studies the important but unexplored relationship between R&D investment intensity and different components of stock price...     

Using inverted Engel curves to estimate material standards of living in a household

This article demonstrates how to estimate latent total consumption expenditure or material standard of living in households by inverting estimated Engel curves. While the conventional estimator, total purchase expenditure, is unbiased for latent total household consumption expenditure, it is not variance minimizing since it is an un-weighted sum. In two stages, this article derives a variance-minimizing, unbiased estimator by first estimating and inverting Engel curves; then combining the estimators from the inverted Engel curves. The employed latent variable method allows for utilization of non-expenditure relations. The suggested method may help improve the accuracy in studies of consumption inequality and tax evasion.      

The Value of Changes in Deer Season Length: An Application of the Nested Multinomial Logit Model

Increasing deer populations can be controlled through manipulatingharvest limits or season length. While such actions often result in benefitsto hunters, both motorists and the agricultural sector also benefit as alower deer population leads to fewer incidences of harmful human-deerencounters. Traditional recreation demand models are often employed toexamine the welfare implications of changes in daily hunting bag limits.Studies measuring the effects of changes in season length, however, arenoticeably absent from the literature. This study uses a nested randomutility model to examine hunter choice over site and season selection toderive the values of changes in season length.     

Quality in reflective thinking: elicitation and classification of reflective acts

The concept of reflective thinking needs to be instantiated for more effective educational implementations and practice in the process of thinking and learning. This article therefore expounds on the elicitation and classification of the Reflective Acts derived primarily from various studies conducted on reflective practice, student reflections and metacognition. In order to elicit and classify the Reflective Acts, the study employed three sequential phases of analyses: qualitative meta-analysis, purport analysis and Intention Clustering Method. As a result, 17 types of reflective acts were identified and classified into four main categories: Interpretive, Associative, Transformative and Affective. It is concluded in the article that through the presence and awareness of Reflective Acts, the concept of reflective thinking will be better comprehended, perceived and retained, engendering the process of reflective thinking into a straightforward practice to guide individuals to perform structured, efficacious and successful reflective acts in order to improve the quality of their reflective thinking and learning.     

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Seasonality in firm-size portfolio returns: A nonparametric analysis

In this study the author uses stochastic dominance, a nonparametric method of portfolio performance analysis, to test for seasonality in firm-size portfolio return behavior. Stochastic dominance confirms the January effect, found in previous parametric studies, only for the smallest firm-size portfolio. It statistically eliminates the size effect for the larger firm-size portfolios in January and for all firm-size portfolios in the other months of the year. It is demonstrated that a market proxy problem and normality assumption violation may bias the parametric results. Nonparametric analysis, therefore, suggests that markets may be more efficient than parametric methods imply when model violations exist.     

March Market Madness: The Impact of Value‐Irrelevant Events on the Market Pricing of Earnings News

Each year, the NCAA basketball tournament (March Madness) is a daytime distraction for millions of people, providing a largely exogenous shock to investor attention. We investigate whether March Madness influences the market response to earnings by diverting investor attention away from earnings news. We find that the price reaction to earnings news released during March Madness is muted. This result generally holds across several samples and additional analyses. We also find that the result is more muted for low institutional ownership firms, consistent with the effect being driven by less‐sophisticated investors. Furthermore, we find that it takes the market 30 to 60 days to correct for the distraction effect. Overall, we provide a unique test of the theory of limited attention by documenting that extraneous events can have a significant impact on the pricing of earnings.