Healthcare production function mapping staff, capital, consumables and technology to provider activity
f(L, K, M, T) = Q
Maps a provider's labour L, capital K, drugs and consumables M and technology and organisation T to the maximum activity Q it can produce in a period, such as consultations or case-mix-adjusted episodes. It is the provider counterpart of the household function HE-FN-HPF-001, in which health itself is the output. The quantities read off the function are held in live records and are cited here, not restated. The Cobb-Douglas form with exponents summing to one is HE-FM-HPF-001 with A = exp(rho_H E), alpha = 1-K and beta = K, K there being the own time share, and the marginal products, each exponent times output over the input, and their ratio, the marginal rate of technical substitution, take the form of those in HE-FM-HPF-002, which computes them only for exponents summing to one; the same form holds for any exponents (derived). Marginal cost as the price of an input over its marginal product, MC = w / MP_L when labour is the only variable input, is Grossman's condition held in HE-SR-HPF-003 and tested in HE-VT-HPF-006, and average variable cost w / AP_L is the unit labour cost w / a_h of HE-FM-BAUM-001. A discrete marginal product from a production schedule is a change in output over a change in input, the same difference-quotient form as HE-FM-ICER-001, and an average product is a partial productivity ratio such as the bed turnover rate of HE-FM-BTO-001. Distance from an estimated frontier is measured by HE-FM-EFF-001 to HE-FM-EFF-003. Average cost, cost functions and the marginal cost of a change in scale belong to the Average Cost, Cost Function and Marginal Analysis pages. This package adds the degree of returns to scale of a Cobb-Douglas function whose output elasticities are estimated freely (HE-FM-HCPF-001). Notation follows the Healthcare Production Function article.
Returns to scale of a Cobb-Douglas hospital production function with free output elasticities
Q = A * L^alpha * K^beta; RTS = alpha + beta; Q_s = A * (s * L)^alpha * (s * K)^beta; g_s = Q_s / Q
