The objective of this study is to assess the importance of short- and long-run liquidity or debt risk on technical inefficiency and productivity. An alternative panel estimator of normal-gamma stochastic frontier model is proposed using a simulated maximum likelihood estimation technique. Empirical estimates indicate a difference in the parameter coefficients of gamma stochastic production function, and heterogeneity function variables between the pooled and the Swamy–Arora panel models. The results from this study show short and long run risk or variations in liquidity or debt-servicing ratio play an important role in explaining the variance in efficiency and productivity. 
Impact of liquidity risk on variations in efficiency and productivity: A panel gamma simulated maximum likelihood estimation