Stochastic frontier analysis

Stochastic frontier analysis (SFA) is a method of economic modeling. It has its starting point in the stochastic production frontier models simultaneously introduced by Aigner, Lovell and Schmidt (1977) and Meeusen and Van den Broeck (1977). Stochastic frontier analysis (SFA) is a method of economic modeling. It has its starting point in the stochastic production frontier models simultaneously introduced by Aigner, Lovell and Schmidt (1977) and Meeusen and Van den Broeck (1977). The production frontier model without random component can be written as: y i = f ( x i ; β ) ⋅ T E i {displaystyle y_{i}=f(x_{i};eta )cdot TE_{i}} the best where yi is the observed scalar output of the producer i, i=1,..I, xi is a vector of N inputs used by the producer i, f(xi, β) is the production frontier, and β {displaystyle eta } is a vector of technology parameters to be estimated. TEi denotes the technical efficiency defined as the ratio of observed output to maximum feasible output.TEi = 1 shows that the i-th firm obtains the maximum feasible output, while TEi < 1 provides a measure of the shortfall of the observed output from maximum feasible output. A stochastic component that describes random shocks affecting the production process is added. These shocks are not directly attributable to the producer or the underlying technology. These shocks may come from weather changes, economic adversities or plain luck. We denote these effects with exp ⁡ { v i } {displaystyle exp left{{v_{i}} ight}} . Each producer is facing a different shock, but we assume the shocks are random and they are described by a common distribution.