Organizational public value and employee life satisfaction: the mediating roles of work engagement and organizational citizenship behavior

Abstract

Building on Meynhardt’s public value concept, which has been developed to make transparent an organization’s contributions to the common good, we investigate the influence of organizational common good practices in the perceptions of employees (measured as public value) on employees’ work attitudes and life satisfaction. The proposed model is tested on a sample of 1045 Swiss employees taken from the 2015 Swiss Public Value Atlas data-set. Study findings reveal that organizational public value is positively related to employee life satisfaction, and that this relationship is partially mediated by work engagement and organizational citizenship behavior. Further, we show that employee common good orientations strengthen the positive impact of organizational public value on employee work engagement and organizational citizenship behavior. Results also provide evidence that the indirect effects of organizational public value on employee life satisfaction via work engagement and organizational citizenship behavior are stronger at higher employee common good orientation levels.     

Using composite indicators to evaluate the efficiency of health care system

This article produces a system-level composite indicator on population health in publicly provided primary health care. We first summarize information from various indicators of care by principal component analysis (PCA). We then regress the costs of care against these indicators to evaluate whether they are related. The existing health status indicator provides a point of comparison. Our results suggest that PCA can be used to extract information efficiently and thus to reduce the dimensionality of data. Furthermore, the use of the existing health status indicator to estimate cost-efficiency leads to invalid inference on overall efficiency, while the use of composite indicator significantly reduces the bias.     

Robust Small Area Estimation under Spatial Non‐stationarity

The effective use of spatial information in a regression‐based approach to small area estimation is an important practical issue. One approach to account for geographic information is by extending the linear mixed model to allow for spatially correlated random area effects. An alternative is to include the spatial information by a non‐parametric mixed models. Another option is geographic weighted regression where the model coefficients vary spatially across the geography of interest. Although these approaches are useful for estimating small area means efficiently under strict parametric assumptions, they can be sensitive to outliers. In this paper, we propose robust extensions of the geographically weighted empirical best linear unbiased predictor. In particular, we introduce robust projective and predictive estimators under spatial non‐stationarity. Mean squared error estimation is performed by two analytic approaches that account for the spatial structure in the data. Model‐based simulations show that the methodology proposed often leads to more efficient estimators. Furthermore, the analytic mean squared error estimators introduced have appealing properties in terms of stability and bias. Finally, we demonstrate in the application that the new methodology is a good choice for producing estimates for average rent prices of apartments in urban planning areas in Berlin.     

Gemeinschaftsdiagnose: Pandemie verzögert Aufschwung — Demografie bremst Wachstum

Wirtschaftsdienst - Das erste Jahr der Corona-Pandemie stand in Deutschland im Zeichen extremer Schwankungen der ökonomischen Aktivität und einer massiv gelähmten Binnenwirtschaft....     

Gemeinschaftsdiagnose: Ohne russisches Gas droht eine scharfe Rezession in Deutschland

Wirtschaftsdienst - Die deutsche Wirtschaft steuert durch schwieriges Fahrwasser. Die Auftriebskräfte durch den Wegfall der Pandemiebeschränkungen, die Nachwehen der Coronakrise und die...     

Underestimation of mean square error matrix in misspecified linear models

In this paper a necessary and sufficient condition is derived for the mean square error matrix to be overestimated on average by the covariance matrix of the OLS estimator when the linear model is misspecified by omitting at least one independent variable. A sufficient condition for this is also considered and the situation is illustrated by simple examples showing, as previously noted by Gupta and Maasoumi (1979), that underestimation is the prevailing case in practice.     

Enhancement of value investing strategies based on financial statement variables: the German evidence

This paper examines the added-value of combining traditional valuation ratios with each other as well as with some financial statement variables in the German stock markets during the 2000–2015 period. The results show that combination pays off and, moreover, that the benefits of combination are greater in Germany than in most other developed stock markets. Particularly, we find strong evidence of the added-value of using Piotroski’s F-score as a supplementary selection criterion for value stocks as well as for low-accrual stocks. Our results show further that the F-score also boosts the efficacy of other valuation ratios besides the book-to-price ratio. In addition, the inclusion of F-score besides a relative value measure tends to increase the average market equity of portfolio firms. The decomposition of the full-sample-period performance into separate bull- and bear-period performance shows clearly that the better performance of F-score-boosted portfolios is mostly attributable to their outperformance during bearish periods, even though on average, they also generate higher bull-period returns than the comparable value portfolios formed without F-score. The use of F-score as a supplementary criterion also increases the proportion of stocks that earn above-market-average returns during the subsequent holding period. For the first time in the financial literature, we also document a strong relationship between high F-score stocks and momentum stocks.     

Intertemporal efficiency analysis of sales teams of a bank: Stochastic semi-nonparametric approach

The primary role of a bank branch is evolving from a service provider towards a sales channel. Previous branch-level studies of sales efficiency consider a static setting of a single time period, ignoring the stochastic nature of sales outcomes. In this paper, we examine efficiency and performance of sales teams in a bank branch network over time, taking into account the changing demand and operational conditions, as well as random disturbances. The intertemporal sales frontier is estimated from the panel of monthly data over the years 2007–2010 using the stochastic semi-nonparametric envelopment of data (StoNED) method. The efficiency scores of sales teams and the trajectories of performance over time allow managers and the sales force to learn from past events and to develop the managerial and work practices across the network. While this study focuses on the case of a specific bank, some of the innovative features of our approach are applicable to sales efficiency assessment in other banks and financial institutions, as well as other network-based sales organizations.     

Managed Floating as a Monetary Policy Strategy

Although there seems to be a broad consensus among economists that purely floating or completely fixed exchange rates (the so-called corner solutions) are the only viable alternatives of exchange rate management, many countries do not behave according to this paradigm and adopt a strategy within the broad spectrum of exchange rate regimes that is limited by the two corner solutions. Many of these intermediate regimes are characterized by significant foreign exchange market interventions and a certain degree of exchange rate flexibility with non-preannounced exchange rate targets. While academic research in this area usually concentrates on some specific aspects of intermediate regimes (such as the effectiveness of interventions or institutional aspects), managed floating has rarely been analyzed as a comprehensive monetary policy strategy. In this paper, we present a monetary policy framework in which central banks simultaneously use the exchange rate and the interest rate as operating targets of monetary policy. We explain the mechanics of foreign exchange market interventions and sterilization and we explain why a central bank has an interest of controlling simultaneously the two operating targets. We derive the monetary policy rules for the two operating targets from a simple open economy macro model in which the uncovered interest parity condition and the monetary conditions index play a central role.