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We analyze Lagrange Multiplier (LM) tests for a shift in trend of a univariate time series at an unknown date. We focus on the class of LM statistics based on nonparametric kernel estimates of the long run variance. Extending earlier work for models with nontrending data, we develop a fixed-b asymptotic theory for the statistics. The fixed-b theory suggests that, for a given statistic, kernel, and significance level, there usually exists a bandwidth such that the fixed-b asymptotic critical value is the same for both I(0) and I(1) errors. These “robust” bandwidths are calculated using simulation methods for a selection of well-known kernels. We find when the robust bandwidth is used, the supremum statistic configured with either the Bartlett or Daniell kernel gives LM tests with good power. When testing for a slope change, we obtain the surprising finding that less trimming of potential shift dates leads to higher power, which contrasts the usual relationship between trimming and power. Finite sample simulations indicate that the robust LM statistics have stable size with good power.

Measurement of diminishing or divergent cross section dispersion in a panel plays an important role in the assessment of convergence or divergence over time in key economic indicators. Econometric methods, known as weak σ-convergence tests, have recently been developed (Kong, Phillips, & Sul, 2019) to evaluate such trends in dispersion in panel data using simple linear trend regressions. To achieve generality in applications, these tests rely on heteroskedastic and autocorrelation consistent (HAC) variance estimates. The present chapter examines the behavior of these convergence tests when heteroskedastic and autocorrelation robust (HAR) variance estimates using fixed-b methods are employed instead of HAC estimates. Asymptotic theory for both HAC and HAR convergence tests is derived and numerical simulations are used to assess performance in null (no convergence) and alternative (convergence) cases. While the use of HAR statistics tends to reduce size distortion, as has been found in earlier analytic and numerical research, use of HAR estimates in nonparametric standardization leads to significant power differences asymptotically, which are reflected in finite sample performance in numerical exercises. The explanation is that weak σ-convergence tests rely on intentionally misspecified linear trend regression formulations of unknown trend decay functions that model convergence behavior rather than regressions with correctly specified trend decay functions. Some new results on the use of HAR inference with trending regressors are derived and an empirical application to assess diminishing variation in US State unemployment rates is included.

The author develops and extends the asymptotic F- and t-test theory in linear regression models where the regressors could be deterministic trends, unit-root processes, near-unit-root processes, among others. The author considers both the exogenous case where the regressors and the regression error are independent and the endogenous case where they are correlated. In the former case, the author designs a new set of basis functions that are invariant to the parameter estimation uncertainty and uses them to construct a new series long-run variance estimator. The author shows that the F-test version of the Wald statistic and the t-statistic are asymptotically F and t distributed, respectively. In the latter case, the author shows that the asymptotic F and t theory is still possible, but one has to develop it in a pseudo-frequency domain. The F and t approximations are more accurate than the more commonly used chi-squared and normal approximations. The resulting F and t tests are also easy to implement – they can be implemented in exactly the same way as the F and t tests in a classical normal linear regression.

The collection of chapters in this 30th volume of Advances in Econometrics provides a well-deserved tribute to Thomas B. Fomby and R. Carter Hill, who have served as editors of the Advances in Econometrics series for 25 and 21 years, respectively. Volume 30 contains a more varied collection of chapters than previous volumes, in essence mirroring the wide variety of econometric topics covered by the series over 30 years. Volume 30 starts with a chapter discussing the history of this series over the last 30 years. The next five chapters can be broadly categorized as focusing on model specification and testing. Following this section are three contributions that examine instrumental variables models in quite different settings. The next four chapters focus on applied macroeconomics topics. The final chapter offers a practical guide to conducting Monte Carlo simulations.

New asymptotic approximations are established for the Wald and t statistics in the presence of unknown but strong autocorrelation. The asymptotic theory extends the usual fixed-smoothing asymptotics under weak dependence to allow for near-unit-root and weak-unit-root processes. As the locality parameter that characterizes the neighborhood of the autoregressive root increases from zero to infinity, the new fixed-smoothing asymptotic distribution changes smoothly from the unit-root fixed-smoothing asymptotics to the usual fixed-smoothing asymptotics under weak dependence. Simulations show that the new approximation is more accurate than the usual fixed-smoothing approximation.

This chapter analyzes the properties of an alternative least-squares based estimator for linear panel data models with general predetermined regressors. This approach uses backward means of regressors to approximate individual specific fixed effects (FE). The author analyzes sufficient conditions for this estimator to be asymptotically efficient, and argue that, in comparison with the FE estimator, the use of backward means leads to a non-trivial bias-variance tradeoff. The author complements theoretical analysis with an extensive Monte Carlo study, where the author finds that some of the currently available results for restricted AR(1) model cannot be easily generalized, and should be extrapolated with caution.

When a parameter of interest is nondifferentiable in the probability, the existing theory of semiparametric efficient estimation is not applicable, as it does not have an influence function. Song (2014) recently developed a local asymptotic minimax estimation theory for a parameter that is a nondifferentiable transform of a regular parameter, where the transform is a composite map of a continuous piecewise linear map with a single kink point and a translation-scale equivariant map. The contribution of this paper is twofold. First, this paper extends the local asymptotic minimax theory to nondifferentiable transforms that are a composite map of a Lipschitz continuous map having a finite set of nondifferentiability points and a translation-scale equivariant map. Second, this paper investigates the discontinuity of the local asymptotic minimax risk in the true probability and shows that the proposed estimator remains to be optimal even when the risk is locally robustified not only over the scores at the true probability, but also over the true probability itself. However, the local robustification does not resolve the issue of discontinuity in the local asymptotic minimax risk.

The purpose of this paper is to examine the impact of workplace bullying on innovative work behavior and neglect with defensive silence as a mediator. The study further examines if the presence of friendship networks in the workplace can weaken the negative impact of workplace bullying.

Data were collected through self-report questionnaires from 835 full-time Indian managerial employees working in different Indian organizations.

Results revealed that workplace bullying negatively related to innovative work behavior and positively related to neglect. Defensive silence mediated bullying–outcomes relationships and effects of workplace bullying on proposed outcomes were weaker in the presence of high workplace friendship.

A cross-sectional design and use of self-reported questionnaire data are few limitations of this study.

The study extended the current research stream of workplace bullying to one of the underrepresented developing Asian countries, India. The study also contributes in terms of its sample characteristics as it covers managerial employees working across different organizations.

The purpose of this paper is to analyse the impact of a leader’s communication style (LCS) on the quality of interpersonal exchanges between leaders and followers (LMX), and how this translates into the employee’s affective organizational commitment (AOC), in the context of Peru.

An integrated model of six dimensions is used to measure LCS. Using multiple hierarchical regressions and the Preacher and Hayes mediation model, the study focuses on determining the direct and indirect effect of each of the dimensions on LMX and organizational commitment.

The dimension preciseness shows a significant direct association to AOC. Four dimensions are significantly related with LMX: expressiveness, preciseness and questioningness with a positive sign, while verbal aggressiveness records an important negative one. The same four dimensions show an indirect effect on AOC through LMX. Emotionality and impression manipulativeness do not record significant results.

The research was carried out with a sample of 253 white-collar Peruvian professionals with high-level studies and managerial experience, which are not necessarily representative of the labor population. This research provides comprehensive evidence on how leaders’ communicative behavior may contribute to desirable outcomes such as employee commitment in a Latin American cultural context, although the findings may apply to other cultures.

This study contributes to clarify that each dimension of the LCS impacts differently on subordinate perceptions; leaders should understand this model and be able to make the necessary adjustments to their communication in order to obtain the desired results of leadership. The leader’s ability to communicate with a style characterized by expressiveness, precision, and questioning makes it easy to build high-quality LMX relationships for Peruvian employees. On the contrary, a communication style characterized by high levels of verbal aggressiveness may negatively affect subordinates, limiting the possibility of building high-quality LMX relationships. This, in turn, affects AOC of employees.

This study is a contribution to clarify that each feature of the LCS has a different impact on the perception of the subordinate, for which the leaders should be trained to understand this model and be able to make the necessary adjustments to obtain the desired results of leadership. The leader’s ability to communicate with a style characterized by expressiveness, precision and questioning makes it easy to build high-quality LMX relationships for Peruvian employees. On the contrary, a communication style characterized by high levels of verbal aggressiveness will negatively impact subordinates, limiting the possibility of building high-quality LMX relationships.

The value lies in revisiting the construct “leader’s communication style” to turn it into an instrument for the exercise of leadership. It is a contribution in favor of leaders becoming aware that their own communication style constitutes an instrument of effective leadership and a lever to optimize the commitment of their collaborators toward the organization.