Endogeneity in stochastic frontier models:copula approach without external instruments

This papers considers an alternative estimation procedures for estimating stochastic frontier models with endogenous regressors when no external instruments are available. The approach we propose is based on copula function to directly model the correlation between the endogenous regressors and the composed errors. Estimation of model parameters is done using maximum likelihood. Monte Carlo simulations are used to assess and compare the finite sample performances of the proposed estimation procedures

Capital structure and firm performance: Agencytheory application to Mediterranean aquaculturefirms

The study uses firm level panel data to determine perform-ance-leverage relationships among Mediterranean aquaculture production firms in Croatia, Italy, Spain, France and Greece. Astochastic frontier production function is used to determine and define performance through firm level efficiency estimates. The multilevel internal instrument variable approach is employed to identify the causal relation ships between performance and leverage. Our results show that technical efficiency has been increasing across all firms over the period 2008-2016. The agency-cost hypothesis holds such that leverage has an inverted U-shaped relationship with performance.This implies that leverage increases with efficiency, but efficiency begins to decrease at sufficiently higher levels of leverage. The reverse relationship confirms the franchise-value hypothesis, which states that firms with high efficiency will try to protect the value of their high income by holding more equity capital. Implications for the results are drawn for the Mediterranean region.The authors would like to thank the MedAID (Mediterranean Aquaculture Integrated Development) project, under which this research was conducted.The MedAID project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement [no. 727315] (http://www.medaid-h2020.eu/)

Goal Size Signaling in Entrepreneurial Finance: Evidence for Costless and Simultaneous Signaling in Initial Coin Offerings

Initial Coin Offerings (ICOs), a novel form of entrepreneurial finance, are characterized by extreme information asymmetry. To reduce this asymmetry and attract potential investors, entrepreneurs send signals about unobservable characteristics of their ventures to investors. This paper examines the signaling effects of entrepreneurs’ fundraising goals in ICOs. Using a hand-collected dataset of more than 400 ICOs, we show that the relationship between the size of fundraising goals and actual funding obtained follows curvilinear shapes. We also find that these curvilinear shapes are contingent on the presence of simultaneously sent, costless signals. Our findings enhance understanding how fundraising goals affect fundraising success and provide evidence that in ICOs costless signals are interpreted by investors in conjunction with each other

Indicators of opinion leadership in customer networks:self-reports and degree centrality

In this paper, we assess two alternative indicators of opinion leadership, self-reported opinion leadership and degree centrality, on the same dataset. We also investigate the interaction effect of these two indicators and the social network environment on opinion leadership. We use social network and survey data from the mobile telecom industry to analyze opinion leadership in smartphone adoption. We find that degree centrality indicates opinion leadership, but that self-reported opinion leadership indicates opinion leadership only under the right social circumstances. In case of weak to moderate network ties, the effect of self-reported opinion leadership is not significant. However, self-reported opinion leaders more effectively influence their strong ties. This study sheds light on indicators of opinion leadership and provides insights for managers to improve their social marketing campaigns

The role of inclusive leadership in fostering organisational learning behaviour

Purpose: Organisational learning is fundamental in establishing a fearless organisation, creating a competitive advantage and maintaining a sustained growth. While research suggests that leaders can influence organisational learning, there is currently no empirical evidence on how inclusive leadership fosters organisational learning behaviour. Therefore, the purpose of this study is to investigate the relationship between inclusive leadership and organisational learning behaviour. It also seeks to explore the mediating role of psychological safety and climate for initiatives in the mentioned relationship. Design/methodology/approach: The study used a two-wave quantitative examination with 317 respondents. Online survey was used to collect data from randomly selected full-time Australian employees in two times. The data were then analysed using partial least squares structural equation modelling to provide insights. Findings: The study found empirical evidence on the positive association of inclusive leadership and organisational learning behaviour. Moreover, the two mediation paths of psychological safety and climate for initiative were supported for the relationship between inclusive leadership and organisational learning behaviour. Research limitations/implications: The current study contributes to theory by examining the role of inclusive leadership on organisational learning behaviour through two relatively unexplored mediating paths. It suggests how inclusive leadership can create a fearless organisation through fostering learning behaviour within the organisation which empowers organisations to sustain growth. Despite controlling for and assessing endogeneity, due to the cross-sectional design of the study, it is limited in demonstrating causal links. Originality/value: The current study provides empirical evidence on the role of inclusive leadership in fostering organisational learning behaviour through two mediating paths of psychological safety and climate for initiatives. The proposed model sets the ground for future research to further develop insights on positive impacts of inclusive leadership within organisations

Estimating the Binary Endogenous Effect of Insurance on Doctor Visits by Copula-Based Regression Additive Models

This paper seeks to estimate the causal effect of having health insurance on health care utilization, while accounting for potential endogeneity bias. The topic has impor- tant policy implications, because health insurance reforms implemented in U.S. in recent decades have focused on extending coverage to the previously uninsured. Consequently, understanding the effects of those reforms requires an accurate estimate of the causal effect of insurance on utilization. However, obtaining such an estimate is complicated by the discreteness inherent in common measures of health care usage. This paper presents a flexible estimation approach, based on copula functions, that consistently estimates the coefficient of a binary endogenous regressor in count data settings. The relevant numeri- cal computations can be easily carried out using the freely available GJRM R package. The empirical results find significant evidence of favorable selection into insurance. Ignoring such selection, insurance appears to increase doctor visit usage by 62%, but adjusting for it, the effect increases to 134%

The organization of R&D work and knowledge search in intrafirm networks

The study investigates the effects of the organization of industrial Research & Development on industrial researchers’ knowledge acquisition behavior. Specifically, we test a model about how the fit of individuals with their research tasks affects whether industrial researchers acquire knowledge from outside their assigned projects. Empirical analyses from the R&D laboratory of a global pharmaceutical company show that person-task-fit has a non-linear effect on the knowledge content exchanged through interpersonal interactions. Implications for the management and organization of R&D activities are discussed

Endogeneity in Stochastic Frontier Models

Stochastic frontier models are typically estimated by maximum likelihood (MLE) orcorrected ordinary least squares. The consistency of either estimator depends on exogeneity of the explanatory variables (inputs, in the production frontier setting). We will investigate the case that one or more of the inputs is endogenous, in the simultaneous equation sense of endogeneity. That is, we worry that there is correlation between the inputs and statistical noise or inefficiency. In a standard regression setting, simultaneity is handled by a number of procedures that are numerically or asymptotically equivalent. These include 2SLS; using the residual from the reduced form equations for the endogenous variables as a control function; and MLE of the system that contains the equation of interest plus the unrestricted reduced form equations for the endogenous variables (LIML). We will consider modifications of these standard procedures for the stochastic frontier setting. The paper is mostly a survey and combination of existing results from the stochastic frontier literature and the classic simultaneous equations literature, but it also contains some new results

Endogeneity in Stochastic Frontier Models

Stochastic frontier models are typically estimated by maximum likelihood (MLE) orcorrected ordinary least squares. The consistency of either estimator depends on exogeneity of the explanatory variables (inputs, in the production frontier setting). We will investigate the case that one or more of the inputs is endogenous, in the simultaneous equation sense of endogeneity. That is, we worry that there is correlation between the inputs and statistical noise or inefficiency. In a standard regression setting, simultaneity is handled by a number of procedures that are numerically or asymptotically equivalent. These include 2SLS; using the residual from the reduced form equations for the endogenous variables as a control function; and MLE of the system that contains the equation of interest plus the unrestricted reduced form equations for the endogenous variables (LIML). We will consider modifications of these standard procedures for the stochastic frontier setting. The paper is mostly a survey and combination of existing results from the stochastic frontier literature and the classic simultaneous equations literature, but it also contains some new results