The Causes of Occupational Accidents and Injuries in Romanian Firms: An Application of the Johansen Cointegration and Granger Causality Test

Abstract

Organizational risks are present in any activity, so it is important to manage them properly. The jobs are dynamic and involve a series of processes and activities. The entire human resource is exposed to several risks. If these risks are approached correctly, the organizational capacity to achieve its objectives and vision will increase considerably. This paper aims to investigate the relationships between work accidents (fatal and non-fatal) and the causes that contribute to their occurrence (causes dependent on the executor, causes dependent on the means of production, workload-dependent causes, and work-dependent causes—the work environment). The augmented Dickey–Fuller (ADF) test is employed to check the data stationarity series, while the Johansen test determines the cointegration relation of variables. The data have been collected from Romanian organizations. The vector error correction model (VECM) and Granger causality test are applied for speed of adjustment, nature, and direction of variables’ relationship. This research demonstrated that both data series are free from the unit-root problem at first difference. The lag length criterions select the third lag for model fitness, and Johansen cointegration declares that variables are cointegrated for the long term. The vector error correction model shows the speed of adjustment from the short to the long run is 83.35% and 42.60% for work and fatal accidents. The study results show that fatal accidents have a series relationship with selected cases for the short run and have a long-run relationship with the means of production. Fatal accidents are directly related to means of production. Fatal accidents are not designed by executors, workload-dependent causes, or work environments in the short run. Fatal accidents are directly related to the means of production and sudden incidents happening in the long run. Fatal accidents are considered by executors, workload-dependent causes, or work environments in the short run. In the long run, fatal accidents are directly related to the means of production and sudden incidents happening.

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“…The stationarity of the data series is checked by the augmented Dickey-Fuller test, which confirmed the stability of the data series for the UK and Spain at the first difference (Rume and 2020;Amankwah-Amoah, 2020;Ozturk et al, 2021). The stationarity corroboration of data series makes them accurate to run the cointegration test because the significance of all variables at first difference is the basic condition for applying the cointegration test.…”

“…The CO 2 emission as a dependent and lockdown, daily new confirmed cases, and deaths of COVID-19 as independent variables have shown their significance at 1% level at first difference. The endogenous and variables have failed to reject the null hypothesis at a level (Ivascu et al 2021;Naseem et al 2021a, b;Sarfraz et al 2021;Mohsin et al n.d). The first column of the table after abbreviations of variable contains unit root integration order.…”

“…information criterion, and Hannan-Quinn information criterion (Hatemi and Hacker 2009;Ivascu et al 2021;Mohsin et al, n.d). The lag 3 is selected by Schwarz information criteria has chosen lag 3 as a suitable lag for both countries.…”

“…The analytical approaches of Amankwah-Amoah (2020) and Rehman et al ( 2021a, b) pointed out the upgrade and demand for environment-friendly aircraft with a lesser carbon emission footprint, i.e., aviation's emission reduction schemes, carbon off-setting, and the European Union Emissions Trading System. The research findings indicated that environmental sustainability could be achieved by meeting environment-friendly commitments, reducing cost pressures and survival threats and prioritizing ecological sustainability initiatives (Ozturk et al 2021;Rehman et al 2021a, b).…”

“…The first two terms, alpha ( ) and beta ( β ), are part of unit root calculations, and rho ( ρ ) are included later to test the significance of the coefficient (MacKinnon et al 1999;Ntshangase et al 2016). The selection of lags is empirically determined by using log-likelihood (LL), likelihood ratio (LR), final prediction error (FPE), Akaike information criterion (AIC), Schwarz information criterion (SC), and the Hannan-Quinn information criterion (HQ) (Hatemi and Hacker 2009;Ivascu et al 2021). After possible removal of autocorrelation among error terms and selection or rejection of null hypothesis, it can be decided either unit root present in data series (reject H 0 ) or data series are stationary (accept H 1 ).…”