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Data envelopment analysis (DEA) model has been proved as a useful technique to solve the infeasibility problem encountered in the Malmquist–Luenberger index (MLI). This study provides an alternative to avoid infeasibility under dynamic environments. The availability of new models is verified with a numerical example. In detail, we apply modified MLI models to assess the change of productivity for 28 banks in China from 2007 to 2016. The analysis shows the following: (1) Productivities of most banks were progressive before 2014 and declined since the bad influence of the economic decline in 2015. (2) Time is the main factor that causes productivity differences among the four types of banks. (3) The technical change mainly affects the productivity change for all four types of banks. The results also provide useful guidance for financial regulators and bank managers. For example, the variable change during this period implies that the income structure of the banking system in China is slowly changing to some extent, where corresponding strategies are needed. It also conforms to the law that science and technology is the primarily productive force. [ABSTRACT FROM AUTHOR]