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This paper introduces a method by which researchers can assess the strength of their status manipulations in experimental research by comparing them against Monte Carlo simulated distributions that use aggregate Status Characteristics Theory (SCT) data.

This paper uses Monte Carlo methods to simulate the m and q parameter distributions and the proportion of stay (P(s)) score distributions for four commonly used status situations. It also presents findings from an experiment that highlight the processes by which researchers can utilize these simulated distributions in their assessment of novel status manipulations.

Findings indicate that implicitly relevant status manipulations have considerably more overlapping P(s) scores in the simulated distributions of high and low states of a status characteristic than explicitly relevant status manipulations. Findings also show that a novel status manipulation, the handedness manipulation, sufficiently creates high- and low-status differences in P(s) scores.

Future researchers can use these simulated distributions to plot the mean P(s) scores of each of their experimental conditions on the overlapping distribution for the corresponding status manipulation. Manipulations that produce scores that fall outside of the range of overlapping values are also likely to create status differences between conditions in other settings or populations.

In this chapter, I detail a procedure for incorporating status characteristics with more than two ordered states, or graded status characteristics, into status characteristics theory. I revise theoretical definitions and assumptions accordingly. The new procedure adds a weighting function to the existing mathematical structure of the theory. I show that estimates using the new procedure are consistent with findings drawn from four experiments that were run in the standard setting for status characteristics theory. I also show that the procedure explains more variation and improves global model fit when predicting expectations using newly collected vignette data. I conclude with a general discussion of the procedures and implications for other expectation states theories and for research conducted outside the laboratory.

This chapter aims to provide nuance into the issue of generational cohort differences at work by focusing on the role of contextual moderator variables. Theory and hypotheses derived from the research on generational differences, psychological contracts, and work values are contrasted to a countervailing set of hypotheses derived from theory and research on the confluence of age and Person-Environment (P-E) fit. Complex patterns of interactive effects are posited for both alternatives. The results favored a generational hypothesis regarding the positively valenced construct of job satisfaction but an age-based hypothesis for the negatively valenced construct of turnover intentions. Results are tested using a subset from a large and nationally representative sample of adults from the US workforce (n = 476). Results offer mixed support for both age and generational cohorts, qualified by the specific type of outcome at hand.

Critical mass theory suggests that attaining a certain proportion of a minority group triggers transformation that improves conditions for minority group members. Using faculty gender composition as a continuous rather than categorical predictor, the present research discerns whether the proportion of women influences perceptions among STEM faculty.

STEM faculty completed a survey examining perceptions of department climate for women (i.e., advancement and discrimination) and division of work time. The proportion of women in each department was calculated.

Using multilevel modeling, we found that women (vs. men) faculty perceive less departmental advancement of women, but that a greater proportion of women in a department is related to increased perceptions that the department advances women. We did not find differences in time male or female faculty reported spending on research, teaching, or service; however, as the proportion of women in a department increases, there is a decrease in the amount of time individual male and female faculty spent on research and an increase in time spent on service. Contrary to critical mass theory, we found a linear rather than quadratic effect of proportion of women on perceptions of department climate and division of work time.

These effects may not be attributable to gender proportion alone.

Given our finding of incremental effects of proportion of women, a critical mass is not necessary or sufficient for change. Underlying problems of discrimination and stereotyping need to be addressed while recognizing that each woman hired has a positive impact.

In an omnichannel environment, customers switch channels from product discovery to eventual purchase decision strategically. Hence, the biggest challenge for retailers nowadays is how to operate an effective omnichannel strategy. To improve inventory operational efficiency, this chapter investigates the influences of price setting and customers’ return probability on inventory forecasting. Subsequently, we explore how retailers participate in providing appropriate information delivery and product fulfillment. Specifically, a stylized newsvendor model, which incorporates customers’ showrooming behavior, is developed to address retailers’ inventory problem. Furthermore, we compare the benefits of buy-online-and-pick-up-in-store (BOPS) and showroom strategy which originates offline but is completed online. Three main findings are obtained as follows: (1)online and offline inventory order quantities augment with the ascending of pricing offline and online, respectively. Meanwhile, the inventory decisions increase when customers’ return probability declines; (2) the implementation of showroom helps retailers expand their pure online market coverage than BOPS, while it reduces the total inventory quantity if the proposition of unit online inventory cost accounting for product price exceeds physical store; and (3) showroom strategy is more profitable than BOPS option as long as unit online inventory cost is small enough. In addition, we find this boundary where showroom increases total profit expands with the attenuating of return probability.

Recent U.S. Treasury yields have been constrained to some extent by the zero lower bound (ZLB) on nominal interest rates. Therefore, we compare the performance of a standard affine Gaussian dynamic term structure model (DTSM), which ignores the ZLB, to a shadow-rate DTSM, which respects the ZLB. Near the ZLB, we find notable declines in the forecast accuracy of the standard model, while the shadow-rate model forecasts well. However, 10-year yield term premiums are broadly similar across the two models. Finally, in applying the shadow-rate model, we find no gain from estimating a slightly positive lower bound on U.S. yields.

This chapter estimates a regime switching Taylor Rule for the European Central Bank (ECB) in order to investigate some potential nonlinearities in the forward-looking policy reaction function within a real-time framework. In order to compare observed and predicted policy behavior, the chapter estimates Actual and Perceived regime switching Taylor Rules for the ECB. The former is based on the refi rate set by the Governing Council while the latter relies on the professional point forecasts of the refi rate performed by a large investment bank before the upcoming policy rate decision. The empirical evidence shows that the Central Bank’s main policy rate has switched between two regimes: in the first one the Taylor Principle is satisfied and the ECB stabilizes the economic outlook, while in the second regime the Central Bank cuts rates more aggressively and puts a higher emphasis on stabilizing real output growth expectations. Second, the results point out that the professional forecasters have broadly well predicted the actual policy regimes. The estimation results are also robust to using consensus forecasts of inflation and real output growth. The empirical evidence from the augmented Taylor Rules shows that the Central Bank has most likely not responded to the growth rates of M3 and the nominal effective exchange rate and the estimated regimes are robust to including these additional variables in the regressions. Finally, after the bankruptcy of Lehman Brothers the policy rate has switched to a crisis regime as the ECB has focused on preventing a further decline in economic activity and on securing the stability of the financial system.

Several official institutions (NBER, OECD, CEPR, and others) provide business cycle chronologies with lags ranging from three months to several years. In this paper, we propose a Markov-switching dynamic factor model that allows for a more timely estimation of turning points. We apply one-step and two-step estimation approaches to French data and compare their performance. One-step maximum likelihood estimation is confined to relatively small data sets, whereas two-step approach that uses principal components can accommodate much bigger information sets. We find that both methods give qualitatively similar results and agree with the OECD dating of recessions on a sample of monthly data covering the period 1993–2014. The two-step method is more precise in determining the beginnings and ends of recessions as given by the OECD. Both methods indicate additional downturns in the French economy that were too short to enter the OECD chronology.

This article examines the history, development, and application of the sandwich estimate of variance. In describing this estimator, we pay attention to applications that have appeared in the literature and examine the nature of the problems for which this estimator is used. We describe various adjustments to the estimate for use with small samples, and illustrate the estimator’s construction for a variety of models. Finally, we discuss interpretation of results.

Second-order expectations refer to an actor's beliefs about what a co-actor believes with respect to their relative abilities on a shared task. The authors describe and compare three alternative programs of research that explain the effects of second-order expectations on behavioral inequalities in task groups. The authors’ overall goal is to work toward improving the precision and generality of theories of second-order expectations.

The authors conduct a thorough review of theory and research on each of the three alternative models of second-order expectations. In so doing, they highlight areas of convergence and divergence in terms of theory, method, and empirical support. They also suggest research designs that can help clarify the effects of second-order expectations in task groups and adjudicate among the models.

New empirical studies are needed that attempt to replicate findings across the three approaches to modeling second-order expectations. In addition, the three approaches need to be directly compared at the same time using a shared experimental design and the same participant population.

This is the first effort to systematically and critically compare and contrast three competing models of second-order expectations in structural social psychology. The authors offer a number of original, specific recommendations for future research.