10Īlternatively, one can estimate the production function without public capital, compute TFP residually, and then regress TFP on KT, as in the study by Holl (2016) on the effects of access to highways on firms' productivity in Spain. 9 The advantage of this specification is that we do not have to estimate α and β, although we need to impose some structure on the data using theoretical assumptions that might be invalid, such as constant returns to scale in private inputs and perfect competition. 8īringing in further assumptions on technology and firm behavior, namely constant returns to scale in private inputs ( α+ β = 1), perfect competition in input and output markets, no externalities, as well as profit maximization, it can also be shown that the log level of TFP (obtained as the difference between the log of output and the average of the logs of private inputs, weighted by their respective shares in value added) depends on the level of KT. (6.10), we can distinguish the effect of TK on GDP that goes through higher A ( γ), from this that passes through higher effective labor ( β). In other words, if we assume that the economic model generating our data is that in Eq. In turn, this very same elasticity in Eq. (6.8) measures the elasticity of GDP with respect to KT. However, the economic interpretation is slightly different. (6.10) we end up with the same elasticity of GDP with respect to KT. The outputs have centered around a variety of different health care services, ranging from hospitals, to physicians and specialty care treatment centers. More recently, interest has focused on the relationship between inputs and the quality of output, but this is an area deserving much greater attention.
One approach examines the technological relationship between inputs (such as employment of different types of health care workers, physical capital, and possibly other inputs) and output or outputs, which can include client counts (admissions or discharges), relative value units, or others. In contrast, two other major strands of production function estimation have examined the technology and efficiency associated with production of medical care, which is the primary focus of this article. Health expenditures significantly affect life expectancy at the age of 65 years in OECD countries.
One recent example of this approach is production function estimation for health in the Organization for Economic Co-operation and Development (OECD) countries, which postulates that life expectancy at the age of 65 years depends on health expenditures, medical technology, and lifestyle. Findings in this literature include a positive relationship between medical care and health demographics (such as education and income) and health and avoiding risky behaviors (such as smoking and other substance abuse) and health. The production of health approach involves a more general specification of the production process, including a variety of societal factors as inputs, such as consumption of medical care, technology, demographics, and personal health habits. This article describes all three approaches with a primary focus on production functions and on efficiency analysis.
A third approach examines medical care production efficiency more specifically through stochastic frontier or data envelopment analysis techniques. Another strand examines the technological relationship between medical care and the inputs that are used to produce medical care. Some of these studies focus on the production function for general and regress health (such as reduced mortality) against a variety of factors. Production function studies in health economics have taken three divergent approaches. Cohen, in Encyclopedia of Health Economics, 2014 Introduction: Distinction between Production Functions for Medical Care versus Production Functions for Health