MSE-improvement of the least squares estimator by dropping variables

It is well known that dropping variables in regression analysis decreases the variance of the least squares (LS) estimator of the remaining parameters. However, after elimination estimates of these parameters are biased, if the full model is correct. In his recent paper, Boscher (1991) showed that the LS-estimator in the special case of a mean shift model (cf. Cook and Weisberg, 1982) which assumes no “outliers” can be considered in the framework of a linear regression model where some variables are deleted. He derived conditions under which this estimator outperforms the LS-estimator of the full model in terms of the mean squared error (MSE)-matrix criterion. We demonstrate that this approach can be extended to the general set-up of dropping variables. Necessary and sufficient conditions for the MSE-matrix superiority of the LS-estimator in the reduced model over that in the full model are derived. We also provide a uniformly most powerful F-statistic for testing the MSE-improvement.     

New development: Regression-to-the-mean explains the otherwise puzzling coefficients in NHS England’s formula for funding CCGs

This paper reviews NHS England’s recent report on the formula that guides the allocation of tens of billions of pounds to clinical commissioning groups (CCGs). It finds deficiencies and errors in the unprincipled construction of the formula and substitutes Sir Francis Galton’s logical concept of ‘regression to the mean’ for the report’s ad hoc conjectures about striking patterns of certain coefficients.     

Economic contribution of essential air service flights on small and remote communities

The Essential Air Service Program (EAS) has attracted considerable criticism and has been a target for either modification or complete termination almost since its inception through the Airline Deregulation Act in 1978. Although its opponents emphasize the program's inefficiency, its supporters claim that the program is crucial to accessing small and remote communities, which helps them develop economically and socially. This paper demonstrates the economic contributions of EAS flights to small and remote communities. Using a two-stage least squares estimation, the major findings indicate that a 1% increase in air passenger traffic in EAS airports with a minimum annual air passenger traffic of 1000 likely leads to a 0.12% increase in per capita income of the community served by that airport. Our results also suggest that EAS communities that are able to sustain their subsidized flights experienced higher per capita income growth in the 1999–2011 period than did ex-EAS communities that lost their flights as a result of non-eligibility.     

Health and cosmetics: Investigating consumers’ values for buying organic personal care products

In investigating consumers’ intentions to re-purchase organic personal care products (PCP), this study extends the theory of planned behaviour by including perceived value dimensions as the antecedents of attitude in the model. The findings revealed that most of the hypothesised relationships linking the consumer perceived value constructs (namely, health, safety, hedonic and environmental) with attitude towards the rebuying of organic PCP, were supported. Also, better product knowledge about organic PCP would lead to more positive attitudes towards re-purchasing the product. In contrast, social value was not important in predicting attitude. Similarly, the influence of subjective norm on rebuying intention was not supported. In terms of ranking of importance with regards to prediction of re-purchasing intention, attitude was the most important predictor followed by perceived behavioural control, product knowledge, hedonic value, environmental value and safety value.     

Bridging the Gap Between Strategy and Performance: Using Leadership Style to Enable Structural Elements

Successful leaders create structural elements in order to achieve the performance objectives set forth by organizational strategy. Supply chain oriented structural elements are reflected in an organization's relationships, both within the firm and with supply chain partners. In this research effort, we examine how such structural elements can be created as a means through which to enhance performance. Our hypothesized model is rooted in strategy‐structure‐performance theory and integrates elements of servant leadership theory and social exchange theory to explain how building organizational commitment via servant leadership behaviors can ultimately impact performance. We use a survey method to collect data from 158 motor carriers. The results of our structural equation model support our hypotheses and serve to extend the discussion of supply chain structural elements and the role of leadership style in achieving organizational performance.     

Predictors of export performance in developing economies: a longitudinal analysis of Moroccan SMEs

Purpose: To help increase understanding of the export performance, we investigate the influence of firm size, research and development (R&D), advertising expenditures and network relationships, and develop a conceptual model to increase export intensity. Design/methodology/approach: The research involved a four-year longitudinal study of export performance of 168 exporting SMEs in Morocco (672 observations). The two-stage least square estimation (G2SLS) was used to test the hypotheses. Findings: The findings of the two-stage least square estimation (G2SLS) suggest that export sales and domestic sales are interdependent and influence each other. R&D expenditures and network affiliation have positive and significant impact on export sales, while advertising expenditure has a negative and significant influence on export sales. Research limitations/implications: Readers should use caution in generalizing the findings unless verified in other developing contexts. Practical implications: The findings of this study are useful for managers and export policy makers in developing countries. A proper understanding of the predictors of export performance may help them encourage the growth and diversification of exports that is so vital for developing countries. Originality/value: Export performance is a key element in the field of international marketing. Unfortunately, the literature exhibits a lack of empirical studies in developing countries, particularly in Maghreb regions. The empirical testing of the theoretical model in a developing economy is a significant contribution to fill the needed gap in the literature toward generalizing findings.     

Escape dynamics: A continuous-time approximation

We extend a continuous-time approximation approach to the analysis of escape dynamics in economic models with constant gain adaptive learning. This approach is based on the application of the results of continuous-time version of large deviations theory to the linear diffusion approximation of the original discrete-time dynamics under learning. We characterize escape dynamics by analytically deriving the most probable escape point and mean escape time. The approximation is tested on the Phelps problem of a government controlling inflation while adaptively learning a misspecified Phillips curve, studied previously by Sargent (1999) and Cho et al. (2002) (henceforth, CWS), among others. We compare our results with simulations extended to very low values of the constant gain and show that, for the lowest gains, our approach approximates simulations relatively well. We express reservations regarding the applicability of any approach based on large deviations theory to characterizing escape dynamics for economically plausible values of constant gain in the model of CWS when escapes are not rare. We show that for these values of the gain it is possible to derive first passage times for learning dynamics reduced to one dimension without resort to large deviations theory. This procedure delivers mean escape time results that fit the simulations closely. We explain inapplicability of large deviations theory by insufficient averaging near the point of self-confirming equilibrium for relatively large gains which makes escapes relatively frequent, suggest the changes which might help approaches based on the theory to work better in this gain interval, and describe a simple heuristic method for determining the range of constant gain values for which large deviations theory could be applicable.     

Repeated moral hazard and recursive Lagrangeans

This paper shows how to solve dynamic agency models by extending recursive Lagrangean techniques à la Marcet and Marimon (2011) to problems with hidden actions. The method has many advantages with respect to the promised utilities approach (Abreu et al., 1990): it is a significant improvement in terms of simplicity, tractability and computational speed. Solutions can be easily computed for hidden actions models with several endogenous state variables and several agents, while the promised utilities approach becomes extremely difficult and computationally intensive even with just one state variable or two agents.     

Partial least squares structural equation modeling in HRM research

Abstract

Partial least squares structural equation modeling (PLS-SEM) has become a key multivariate analysis technique that human resource management (HRM) researchers frequently use. While most disciplines undertake regular critical reflections on the use of important methods to ensure rigorous research and publication practices, the use of PLS-SEM in HRM has not been analyzed so far. To address this gap in HRM literature, this paper presents a critical review of PLS-SEM use in 77 HRM studies published over a 30-year period in leading journals. By contrasting the review results with state-of-the-art guidelines for use of the method, we identify several areas that offer room of improvement when applying PLS-SEM in HRM studies. Our findings offer important guidance for future use of the PLS-SEM method in HRM and related fields.     

I (Could Have) Told You! Early warning indicators and crisis performance of the 12 “old” Euro-countries under the economic crisis 2008–09

The impact of the economic crisis 2008-09 was remarkably different in the 12 “old” member states in the Euro-zone. Five of them were hit especially badly; four of them even had to be bailed out by the rest in one way or another. This paper asks if one could have foretold, based solely on information available prior to 1999, which of the countries then about to enter the Euro-zone would run into economic trouble once a serious economic crisis occurred. The focus is on the (post)predictive power of three kinds of leading indicators: economic indicators, political indicators (indicating quality of governance), and indicators derived from the theory of optimal currency areas (OCA). Since there are more indicators than cases, PLS-regression is used to gauge the (post)predictive strength of the indicators examined. The results show that political indicators have quite some (post)predictive power in this case, whereas indicators derived from OCA-theory do not do too well. Economic indicators perform better than indicators derived from OCA-theory, but generally less well than the political indicators. Thus, the experience from the latest economic crisis in the Euro-zone suggests that more emphasis should be placed on the quality of governance record of a country when deciding if it should be deemed fit to become a member.