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What are the main explanations of occupational diseases and accidents at work in the agricultural sector? A panel analysis for Italian regional data

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Abstract

The aim of this paper is to investigate the causes of occupational diseases and accidents at work (ODA) in the Italian agricultural sector. To this end, we proceed with a two-stage analysis of Italian regional data for the period 1976–2004. The first phase of the analysis shows that in the Italian agricultural sector productivity Granger-causes ODA, and not vice versa. The results of the econometric estimates in the second stage of the analysis show that an increase in “productivity pressure” (associated with an increase in production rhythms) will produce, in the long run, an increase in accidents on less serious ODA (or temporary ODA); the same effect will not be observed on the more serious ODA (or permanent ODA). We verify how pro work legislation reduces ODA and how this effect is strengthened in the long-run. In addition, we observe that in the long-run the increase in the “pressure on workers” (associated with a high unemployment rate and a high probability of being fired) is the main cause of the increase in less and more serious ODA. Copyright Springer Science+Business Media Dordrecht 2014

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  • M. Agovino, 2014. "What are the main explanations of occupational diseases and accidents at work in the agricultural sector? A panel analysis for Italian regional data," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(2), pages 1045-1073, March.
  • Handle: RePEc:spr:qualqt:v:48:y:2014:i:2:p:1045-1073
    DOI: 10.1007/s11135-012-9824-y
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    1. Strauss, John, 1986. "Does Better Nutrition Raise Farm Productivity?," Journal of Political Economy, University of Chicago Press, vol. 94(2), pages 297-320, April.
    2. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-1395, November.
    3. Schultz, T. Paul, 2010. "Population and Health Policies," Handbook of Development Economics, in: Dani Rodrik & Mark Rosenzweig (ed.), Handbook of Development Economics, edition 1, volume 5, chapter 0, pages 4785-4881, Elsevier.
    4. Joakim Westerlund, 2007. "Testing for Error Correction in Panel Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(6), pages 709-748, December.
    5. Robinson, J.C., 1988. "The rising long-term trend in occupational injury rates," American Journal of Public Health, American Public Health Association, vol. 78(3), pages 276-281.
    6. Kao, Chihwa, 1999. "Spurious regression and residual-based tests for cointegration in panel data," Journal of Econometrics, Elsevier, vol. 90(1), pages 1-44, May.
    7. Peter Pedroni, 2000. "Fully Modified OLS for Heterogeneous Cointegrated Panels," Department of Economics Working Papers 2000-03, Department of Economics, Williams College.
    8. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    9. Peter Pedroni, 1999. "Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 653-670, November.
    10. repec:bla:obuest:v:61:y:1999:i:0:p:631-52 is not listed on IDEAS
    11. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    12. Choi, In, 2001. "Unit root tests for panel data," Journal of International Money and Finance, Elsevier, vol. 20(2), pages 249-272, April.
    13. Clemente, Jesus & Montanes, Antonio & Reyes, Marcelo, 1998. "Testing for a unit root in variables with a double change in the mean," Economics Letters, Elsevier, vol. 59(2), pages 175-182, May.
    14. Boone, Jan & van Ours, Jan C. & Wuellrich, Jean-Philippe & Zweimüller, Josef, 2011. "Recessions are bad for workplace safety," Journal of Health Economics, Elsevier, vol. 30(4), pages 764-773, July.
    15. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    16. Strauss, John & Thomas, Duncan, 1996. "Measurement and Mismeasurement of Social Indicators," American Economic Review, American Economic Association, vol. 86(2), pages 30-34, May.
    17. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    18. repec:bla:obuest:v:61:y:1999:i:0:p:653-70 is not listed on IDEAS
    19. Boone, Jan & van Ours, Jan C., 2006. "Are recessions good for workplace safety?," Journal of Health Economics, Elsevier, vol. 25(6), pages 1069-1093, November.
    20. Anindya Banerjee & Massimiliano Marcellino & Chiara Osbat, 2005. "Testing for PPP: Should we use panel methods?," Empirical Economics, Springer, vol. 30(1), pages 77-91, January.
    21. Dani Rodrik & Mark Rosenzweig (ed.), 2010. "Handbook of Development Economics," Handbook of Development Economics, Elsevier, edition 1, volume 5, number 6.
    22. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    23. Schultz, T. Paul & Tansel, Aysit, 1997. "Wage and labor supply effects of illness in Cote d'Ivoire and Ghana: instrumental variable estimates for days disabled," Journal of Development Economics, Elsevier, vol. 53(2), pages 251-286, August.
    24. G. S. Maddala & Shaowen Wu, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 631-652, November.
    25. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
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    More about this item

    Keywords

    Labour accidents; Severe and fatality injuries; Sick leave; Agricultural sector; Panel data; J28; J81; Q10; C23;
    All these keywords.

    JEL classification:

    • J28 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Safety; Job Satisfaction; Related Public Policy
    • J81 - Labor and Demographic Economics - - Labor Standards - - - Working Conditions
    • Q10 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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