Dynamics of the total factor productivity in lithuanian family farms with a statistical inference: The bootstrapped malmquist indices and multiple correspondence analysis

Abstract

The paper combines the bootstrapped Malmquist productivity index and the Multiple Correspondence Analysis to measure the changes in the total factor productivity. The bootstrapped Malmquist productivity index enables us to identify insignificant change in the total factor productivity, whereas the Multiple Correspondence Analysis relates the estimates to the environmental variables. A sample of Lithuanian family farms is utilised to test the proposed framework. Specifically, the research covers 200 family farms and the period of 2004-2009. The analysis showed that the total factor productivity decreased by some 15-18% during 2004-2009 depending on the farming type. Multiple Correspondence Analysis suggested that all of the farming types exhibited change in the total factor productivity close to the average, although the crop farming was located in the more stochastic area.