Adjustment costs and efficiency in Polish agriculture: a dynamic efficiency approach

Abstract

This paper aims to understand the state of adjustment process and dynamic structure in Polish agriculture. A dynamic cost frontier model using the shadow cost approach is formulated to decompose cost efficiency into allocative and technical efficiencies. The dynamic cost efficiency model is developed into a more general context with a multiple quasi-fixed factor case. The model is implemented empirically using a panel data set of 1,143 Polish farms over the period 2004 to 2007. Due to the regional disparities and a wide variety of farm specialization, farms are categorized into two regions and five types of farm production specialization. The estimation results confirm our observation that adjustment is rather sluggish implying that adjustment cost are considerably high. It takes up to 30 years until Polish farmers reach their optimal level of capital and land input. Allocative and technical efficiency differ widely across regions. Moreover, efficiency is rather stable over time and among farm specialisations. However, their results indicate that the regions characterized by the larger farms perform slightly better.

Dynamic stochastic analysis of the farm subsidy-efficiency link: evidence from France

“…The connection is established through a distortion factor which captures departure from optimal values (the shadow cost approach is readily available in Stefanou and Saxena, 1988). The model by Rungsuriyawiboon and Hockmann (2015) is an extension of the one developed by Rungsuriyawiboon and Stefanou (2007) which allows accounting for multiple quasi-fixed factors. However, as stated by Serra et al (2011) and recognised by Rungsuriyawiboon and Hockmann (2015), one issue of the shadow cost approach is that it does not specify the production technology directly.…”

“…The model by Rungsuriyawiboon and Hockmann (2015) is an extension of the one developed by Rungsuriyawiboon and Stefanou (2007) which allows accounting for multiple quasi-fixed factors. However, as stated by Serra et al (2011) and recognised by Rungsuriyawiboon and Hockmann (2015), one issue of the shadow cost approach is that it does not specify the production technology directly. The structural model developed by Serra et al (2011) is a dynamic directional input distance function derived from an inter-temporal cost minimisation programme, given the duality between input distance functions and cost functions.…”

A dynamic stochastic frontier approach with persistent and transient inefficiency and unobserved heterogeneity

“…The dynamic SFA literature includes reduced‐form models (e.g., Ahn et al., 2000; Emvalomatis, 2012; Emvalomatis et al., 2011; Galán et al., 2015; Tsionas, 2006) and structural models (e.g., Minviel & Sipiläinen, 2018; Rungsuriyawiboon & Hockmann, 2015; Rungsuriyawiboon & Stefanou, 2007; Serra et al., 2011). These models provide useful insights for efficiency analysis by allowing to model inter‐temporal decisions.…”

Determinants of Cost Inefficiency of Maize Farming in Different Agro-climatic Regions of Sikkim, India

“…Again, taking account of cost efficiency in agriculture, existing studies have come up with mixed findings in the case of farm size. Small farmers of Pakistan’s agriculture sector were more efficient than large farmers (Parikh et al 1995), while reverse statement about agricultural efficiency was made by Paul et al (2004) in USA; Rungsuriyawiboon and Hockmann (2015) in Poland; Asogwa et al (2011) in Nigeria; and Ali et al (1996) in Pakistan. In recent years, studies on cost efficiency in agriculture include a variety of crops such as paddy, maize and other crops.…”