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Antecedents and Organizational Effectiveness Outcomes of Employee Stress and Health
Published in Rick Crandall, Pamela L. Perrewé, Occupational Stress, 2020
William H. Hendrix, Timothy P. Summers, Terry L. Leap, Robert P. Steel
Endogenous variables are those that serve as dependent variables or criterion variables and are considered determined by some combination of the variables in the system. These are located to the right of the exogenous variables in a path diagram. The endogenous variables at the right in Figure 1 are the path model’s outcome variables. Three outcome variables are included in this research model: the cholesterol ratio, performance, and absenteeism. The cholesterol ratio in this research serves as a proxy for coronary heart disease (CHD). The remaining two outcome variables (performance and absenteeism) included in the hypothesized model (Figure 1) have been suggested as relevant outcome variables by previous stress and health promotion research (Israel, House, Schurman, Heaney, & Mero, 1989; Motowidlo, Packard, & Manning, 1986).
The structure and performance of U.S. research joint ventures: inferences and implications from the Advanced Technology Program
Published in Cristiano Antonelli, Albert N. Link, Assessing Technology and Innovation Policies, 2020
James D. Adams, Albert N. Link
The econometric method used depends on the outcome variable, but there are common themes to our procedures. First, all equations report standard errors clustered by RJV. This avoids underreporting of standard errors for grouped data.17 Second, three variables appear as covariates but could be correlated with the error term in the regressions, making the variables endogenous and leading to potentially biased coefficients. These are the logarithm of project budget per firm, the logarithm of additional money invested by a firm, and an indicator for RJV expected to yield revenue over the next five years. The Instrumental Variables (IVs) for the endogenous variables are taken from the ‘closest neighbor’ to a project. The instruments (see Section VI.A.2) are subject to two restrictions: the closest neighbor does not share ownership with a project and it is from a different industry. For example, if a project includes firms in biotechnology, the instrument comes from a different set of firms and from projects that are not in biotechnology. The IVs are highly correlated with the original variables but they are free of common shocks due to shared ownership and industry.
Theoretical Framework -- A Vision Beyond Capital and Labor
Published in Shanzi Ke, Beyond Capital and Labor, 2018
The relationships between the variables in groups (i), (ii) and (iv) are the major interest of the study. With respect to these relationships, the variables in group (v), (vi), and (vii) serve as controls. The producer inputs in group (i) and (vi) are endogenous variables that are affected by each other and by variables in group (ii), (v), and (vii). These endogenous variables may cause simultaneous bias in estimating production functions. Simultaneous equations or instrument variables are desirable in mitigating the probable bias. On the other hand, internal validity for growth equations is less likely to be threatened. The effects of regional factors on technological efficiency (TFP, scale economies, and neutral technological change) and technological inputs are also a basic concern, because this reflects the indirect contribution of regional factors to production growth.
Examining the persistence of telecommuting after the COVID-19 pandemic
Published in Transportation Letters, 2023
Motahare (Yalda) Mohammadi, Ehsan Rahimi, Amir Davatgari, Mohammadjavad Javadinasr, Abolfazl (Kouros) Mohammadian, Matthew Wigginton Bhagat-Conway, Deborah Salon, Sybil Derrible, Ram M. Pendyala, Sara Khoeini
Exogenous variables are those that are not described by other variables in the model. In contrast, endogenous variables are those that are directly explained by other variables in the model. Latent exogenous variables () are hypothesized to be normally distributed in which is the covariance matrix, ). We assume that random disturbances have a normal distribution, ), where is the covariance matrix of the random disturbances (). The latent variable model captures the study hypotheses about how telecommuting productivity and perceived risk of exposure to COVID-19 affects preferences toward telecommuting behavior during and after the pandemic and how preferences change as risk perception changes.
Forecasting with strategic transport models corrected for endogeneity
Published in Transportmetrica A: Transport Science, 2022
Thomas E. Guerrero, C. Angelo Guevara, Elisabetta Cherchi, Juan de Dios Ortúzar
Given the above, let us assume that for illustrative purposes of this explanation the qualitative attribute is unknown to the modeller; the modeller's specification will be as in (2), where the new error term contains both and : For explanatory purposes, we will also consider that from (2) the explanatory variables and are endogenous due to three possible sources of endogeneity: measurement errors, omitted variables, simultaneous determination. Guerrero et al. (2020) showed that these variables are usually endogenous in strategic mode choice models. We assume that the endogeneity for is due to measurement error and omitted variables, whereas the endogeneity for is due to its simultaneous estimation process.
Association of organisational factors with work-related musculoskeletal disorders and psychological well-being: a job demand control model study
Published in Theoretical Issues in Ergonomics Science, 2022
Priya Singh, Prabhas Bhardwaj, Sushil Kumar Sharma, Anil Kumar Agrawal
Significance value (p), critical ratio (t), and the direct effect of exogenous variables on endogenous variables (B) were calculated for all 36 paths for the hypothesised path analysis model (Figure 1). In the SEM, an exogenous variable is defined as one whose value is not affected by other variables in the model. An endogenous variable is one whose value is determined or influenced by one or more exogenous variables. So for the model, workload and job control are exogenous variables, while behavioural stress, somatic stress, cognitive stress, and WMSDs are endogenous variables. In the model, paths with a value of p > 0.05 and critical ratio (t) outside the range −1.96 and +1.96 were considered non-significant paths. Accordingly, 23 paths out of 36 were found to be non-significant, as shown in Table 2. The model shown in Figure 1 was modified by showing all the non-significant paths by the dotted lines in Figure 2.