Modelling technical change in Italian agriculture: a latent variable approach
提出一种基于潜变量衡量技术变化的新方法，通过将技术视为影响投入需求的潜变量并引入测量误差方程，构建MIMIC模型，利用1961-1991年意大利农业数据估计技术变化的性质与水平。
Abstract This paper presents an alternative approach to the measurement of technical change. It is based on the latent variable level of technology that enters explicitly the input demand system and on a hypothesis about the innovation generating process. By adding measurement error equations, the behavioral system can be viewed as a Multiple Indicators/Multiple Causes (MIMIC) model. The parameter estimates are obtained with a maximum likelihood estimator which involves the implicit covariance matrix. The analysis refers to Italian agriculture and the results provide some evidence on the nature and level of technical change during the years 1961–1991.