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Mokslo publikacijos
2016-07-01

Dynamics of the total factor productivity in Lithuanian family farms with a statistical inference: the bootstrapped Malmquist indices and Multiple Correspondence Analysis

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.

 

ARTICLE HISTORY

Received 5 November 2013

Accepted 4 February 2016

Published online 30 Jun 2016

 

KEYWORDS: Total factor productivity; bootstrapped Malmquist index; Multiple Correspondence Analysis; family farms

 

JEL CLASSIFICATIONS: C43; D24; Q12

 

Baležentis, T.; Baležentis, A. 2016 Dynamics of the total factor productivity in Lithuanian family farms with a statistical inference: the bootstrapped Malmquist indices and Multiple Correspondence Analysis, In Economic Research-Ekonomska Istraživanja, 29(1):643–664. http://dx.doi.org/10.1080/1331677X.2016.1193946  ISSN 1331-677X (print), ISSN 1848-9664 (online). [Social Sciences Citation Index, Social SciSearch, Jornal Citation (Web of Science Thomson Reuters); Taylor & Francis Group; Cab Abstract; EBSCO; Econlit; Scopus (Elsevier); Cabell`s; ABI/INFORM (ProQuest); IndexCopernikus].

 

2015 Impact Factor: 0.466

 

 

Dynamics of the total factor productivity in Lithuanian family farms with a statistical inference: the bootstrapped Malmquist indices and Multiple Correspondence Analysis

 

 




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