The contextual nature of the predictive power of statistically-based quarterly earnings models

We present new empirical evidence on the contextual nature of the predictive power of five statistically-based quarterly earnings expectation models evaluated on a holdout period spanning the twelve quarters from 2000–2002. In marked contrast to extant time-series work, the random walk with drift (RWD) model provides significantly more accurate pooled, one-step-ahead quarterly earnings predictions for a sample of high-technology firms (n = 202). In similar predictive comparisons, the Griffin-Watts (GW) ARIMA model provides significantly more accurate quarterly earnings predictions for a sample of regulated firms (n = 218). Finally, the RWD and GW ARIMA models jointly dominate the other expectation models (i.e., seasonal random walk with drift, the Brown-Rozeff (BR) and Foster (F) ARIMA models) for a default sample of firms (n = 796). We provide supplementary analyses that document the: (1) increased frequency of the number of loss quarters experienced by our sample firms in the holdout period (2000–2002) vis-à-vis the identification period (1990–1999); (2) reduced levels of earnings persistence for our sample firms relative to earnings persistence factors computed by Baginski et al. (2003) during earlier time periods (1970s–1980s); (3) relative impact on the predictive ability of the five expectation models conditioned upon the extent of analyst coverage of sample firms (i.e., no coverage, moderate coverage, and extensive coverage); and (4) sensitivity of predictive performance across subsets of regulated firms with the BR ARIMA model providing the most accurate predictions for utilities (n = 87) while the RWD model is superior for financial institutions (n = 131).

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Regime Shifts in a Dynamic Term Structure Model of U.S. Treasury Bond Yields

This article develops and empirically implements an arbitrage-free,dynamic term structure model with "priced" factor and regime-shiftrisks. The risk factors are assumed to follow a discrete-timeGaussian process, and regime shifts are governed by a discrete-timeMarkov process with state-dependent transition probabilities.This model gives closed-form solutions for zero-coupon bondprices, an analytic representation of the likelihood functionfor bond yields, and a natural decomposition of expected excessreturns to components corresponding to regime-shift and factorrisks. Using monthly data on U.S. Treasury zero-coupon bondyields, we show a critical role of priced, state-dependent regime-shiftrisks in capturing the time variations in expected excess returns,and document notable differences in the behaviors of the factorrisk component of the expected returns across high and low volatilityregimes. Additionally, the state dependence of the regime-switchingprobabilities is shown to capture an interesting asymmetry inthe cyclical behavior of interest rates. The shapes of the termstructure of volatility of bond yield changes are also verydifferent across regimes, with the well-known hump being largelya low-volatility regime phenomenon.     

Parsing Work Environments Along the Dimensions of Sexual and Non-Sexual Harassment: Drawing Lines in Office Sand

Laws addressing harassment at work have evolved considerably since court systems first recognized that (sexual) harassment is illegal. Now, managers must worry about protected classes other than sex (e.g., race, age, etc.), and the effects of harassment on bystanders as well as victims (i.e., ambient harassment). Understanding these newer conceptualizations of workplace harassment is critical for mangers dealing with an increasingly complex array of possible work environments, only some of which are illegal. Toward this end, we present a taxonomy of eight possible work environments, created by parsing the legal definition of sexual harassment (i.e., the first-recognized type of hostile work environment). The taxonomy illustrates the evolution of law in this area, and highlights the multidimensional nature of workplace harassment. Also discussed are potential complications arising from how a reasonable person and a victim might interpret behavior. Managers using the taxonomy may better assess whether their work environments have crossed the line, or facilitate movement from less- to more-desirable work environments.

Emic and etic interpretations of engagement with a consumer-to-consumer online auction site

This paper provides emic and etic interpretations of engagement with a consumer-to-consumer (C2C) online auction site, based on in-depth interviews with buyers. The study exposes three misconceptions about online C2C auctions; that the interaction between parties occurs exclusively online, that the relation between buyers and sellers is purely transactional in nature, and that the interaction between buyers and sellers does not lead to ongoing business relationships. The paper reveals the utilitarian, hedonic and social benefits that are the bases of engagement with the auction site. Social benefits materialize for auction buyers during offline exchanges. The paper also reveals marketer incentives and structural disincentives for consumers' ongoing use of the auction site.     

Bioelectricity in Malaysia: economic feasibility,environmental and deforestation implications

We investigate the economic feasibility of bioelectricity production from biomass in Malaysia and its impact on greenhouse gas (GHG) emissions and storage, agricultural prices, agricultural employment and deforestation. For this purpose, we develop a partial equilibrium model that projects agricultural prices, production, imports, exports, domestic consumption and land use in 5‐year increments between 2015 and 2065. Our results show that by 2030 biomass‐generated electricity can supply 36.5 per cent of the electricity generated in Malaysia, 16 times more than the 2016 electricity supply from biomass. Increased bioelectricity production from biomass will significantly reduce GHG emissions and will help Malaysia meet its commitment in the Paris Agreement to mitigate GHG emission by 45 per cent before 2030. Our modelling shows that biomass‐generated electricity creates a derived demand for waste biomass that expands the area of oil palm plantations. The expansion lowers agricultural prices, boosts agricultural employment and leads to some deforestation as landowners clear rainforest to plant oil palm trees. Nonetheless, the deforestation does not increase GHG emissions since GHG gains from bioelectricity significantly exceed GHG losses from deforestation.     

Laboratory and large-scale dust explosion research

This paper describes dust explosibility research in full-scale experimental mines and a 20-L laboratory chamber at the U.S. Bureau of Mines and in a 1-m³ laboratory chamber at Fike Corporation. The purpose of this research is to improve safety in mining and other industries that manufacture, process, or use combustible dusts. As part of this work, carbonaceous dusts with a wide range of volatilities and various particle size distributions were studied. Laboratory data on the minimum explosible concentrations of predispersed dusts were comparable to mine data for nominal dust loadings that were dispersed by the aerodynamic disturbance from a gas ignition zone. Recommendations are given on the limitations of small-scale testing such as “overdriving” by too strong of an ignitor. The effect of dust particle size on explosibility data is illustrated for coal and aluminum dusts. For both dusts, the finest sizes were the most hazardous. The inerting requirements for preventing explosions were also measured in both laboratory and large-scale systems. All the data show relatively good agreement between the laboratory and the large-scale tests.