This study introduces a Malmquist-Luenberger (ML) productivity index using non-parametric linear programming (LP) methods as an alternative measure of green growth by taking into account both desirable and undesirable outputs together as opposed to co...
This study introduces a Malmquist-Luenberger (ML) productivity index using non-parametric linear programming (LP) methods as an alternative measure of green growth by taking into account both desirable and undesirable outputs together as opposed to conventional measures considered only desirable outputs. We used a panel data set consisting of agricultural activity in 50 states in the U.S. since 1990 as a case study. We found that 1) ML productivity in U.S. agriculture increased by 1.3% per year across the 50 states, which suggests that U.S. agriculture may be slowly approaching a lower carbon green growth economy, 2) Ignoring undesirable bad outputs overestimates annual productivity growth, 3) The average annual ML productivity varies considerably across states, ranging from a 2% decrease for Alaska to an increase of 7% for Arizona, and 4) The fluctuation of cumulative ML productivity follows similar patterns of technical efficiency during the 1992.2007 periods.