Since the seminal papers of Schultz (1961) and Becker (1962), a vast literature emerged analyzing the role of human capital on productivity growth rate. Using Griliches (1963, 1964) and Mincer (1974) theoretical developments, empirical research at a micro level concluded that indeed improvements in human capital account for significant gains in observed productivity rates among individual firms (e.g., Bartel and Lichtenberg,1987; Katz and Murphy, 1992). At the same time studies based on the endogenous growth model of Lucas (1988) and Romer (1986) attributed significant productivity improvements to human capital accumulation for a broad set of countries around the world (e.g., Hall and Jones, 1999; Bils and Klenow, 2000). A common ground throughout this literature, is that human capital is mainly determined by two factors: worker's educational level and health status. The intuition behind this assertion is simple. Formal or informal education decreases the marginal cost of acquiring production related information and the benefit of such information improves the allocative ability of firm workers. On the other hand, improved health status enhance workers' (skilled and unskilled) productivity by increasing their physical capacities, such as strength and endurance, as well as their mental capacities, such as cognitive functioning and reasoning ability.
Another common feature of these empirical studies, is that they all assume that workers' health status is determined exogenously. Regardless the choice of variables used to proxy individual health status, this is assumed to be independent of working environment and production decisions made within the firm. The majority of empirical work commonly hypothesizes a strong relationship between nutritional intakes and wages to examine the effects of health on labor productivity mainly in rural areas in both developed and developing countries (Bliss and Stern, 1978; Deolalikar, 1988; Croppenstedt and Muller, 2000). A set of wage function estimates provides solid evidence that higher nutrition leads to increased productivity rates. This nutrition-productivity hypothesis is further confirmed by production function approaches using instrumental variables to correct for simultaneous equation bias (Strauss, 1986). Using different proxies for workers' health status, more recent micro-level research verifies the positive relationship between health variables and productivity for both skilled and unskilled workers (Strauss and Thomas, 1998; Schultz, 2002).
However, empirical evidence worldwide rather suggests the opposite. In many sectors (if not all) workers' health status is not irrelevant to the workplace conditions and individual firm decisions. Evidence from medical studies indicates that health impairments account for 12-28 per cent productivity losses in construction sector (Meerding et al., 2005), while the relative figure in Information and Communications Technology (ICT) industry is 15 per cent (Hagberg et al., 2002). Further, according to the International Labour Organization (ILO), every year 160 billion workers suffer globally from illnesses due to work-related causes, while the relative total cost of these diseases accounts for approximately 4 per cent of world's GDP. According to a recent study by Eurostat (2010), about 8.6 per cent of the workers in the EU-27 face at least one work-related health problem in a period of 12 months, while the total time of lost work due to work-specific health impairments is approximately 367 million calendar days. There are two ways that workplace conditions are affecting workers' health status. First, the nature of working activities involved in firm production (e.g., construction sector) and second, the technological conditions that require the use of specific inputs that are at the same time hazardous for firm workers. Ensuring strict safety standards in a construction site (such as the height of handrails, shoring of trenches, and safe handling procedures) may reduce the adverse effects in workers health status from a potential accident. This is an instantaneous decision made by the firm (mostly imposed by the regulatory framework) and it's impact on individual productivity rates depends on the incidence of work accidents in the future.
In terms of productivity improvements though, it is more important to analyze workers' health status when firms utilize specific inputs in their production process that are at the same time (directly or indirectly) harmful for individual workers, i.e., health-damaging inputs. This type of inputs entails a trade-off between firm production and workers' health status. This is particularly acute for hazards that do not have an immediate and recognizable effect. For instance pesticides materials in crop production, chemical substances in many manufacturing sectors, plastic or paint manufacturing, are all cases where health-damaging inputs are extensively used by firms posing serious health risks for their employees. In these sectors, workers seldom have perfect information about the health implications of their jobs and the use of this specific type of inputs. For many hazards, the true probabilities of being killed or getting ill are not known by anyone. Due to the retarded state of occupational medicine, even the underlying medical ramifications of different exposures to aspects of the workplace such as radiation, noise, high temperatures, and chemical vapors are little understood. This uncertainty is compounded by uncertainty with regard to the characteristics of the work situation, for example, the concentration of asbestos fibers in the air.
Hence, in many instances safety application rules are not always followed by individual workers due either to improper firm management or lack of individual knowledge. Although the social cost of such health impairments might not be of the interest of the firms, the associated reductions in effective labor do matter for them since such reductions are accompanied by lower productivity rates. Hence, measuring the indirect effect of health-damaging inputs, through human capital deterioration, may indirectly enforce safety standards in working environments. If these productivity losses are important for individual firms, then indeed improving workers' knowledge or applying more effective management practices would result to significant gains for them.
Along these lines, this paper contributes to the relevant literature by suggesting a theoretically consistent framework to analyze both the direct and the indirect effect of health-damaging inputs on total factor productivity growth. The decomposition framework is based on a primal approach requiring no assumptions about the structure of labor markets. It is applied to a panel of greenhouse producers from Western Crete, Greece observed during the 2003-07 cropping period. Due to the extensive use of chemical pesticides, farming is a particularly interesting example for measuring the adverse effects of health-damaging inputs on individual productivity rates. For measuring employees' health status, individual health indices are estimated using recently developed generalized propensity score (GPS) methods in a continuous treatment setting (Hirano and Imbens, 2004). To our knowledge this is the first attempt to construct an index of workers' health status that is endogenously determined, enabling the analysis of both direct and indirect effects of health damaging inputs on individual total factor productivity growth rates. Our empirical results may contribute to the ongoing debate for improving working conditions and reducing work-specific health impairments in many sectors.