Monday, May 18, 2009

The Influence of Accounting Information Use on Small Farm Inefficiency

Wilson, Hadley and Ashby (2001) provide evidence that wheat farmers in eastern England who seek information, have more years of managerial experience, and have a large farm are associated with higher levels of technical efficiency. To our knowledge, this is the only empirical study in the economic literature that explains the influence of management on technical efficiency by including variables that relate both personal aspects and aspects of the decision-making process of the farmer. These authors constructed an “information seeking” variable by summing the number of information sources the farmer declared to use out of the 16 listed in a questionnaire (personal, written, electronic and other sources). However, the decisionmaking process and the use of accounting information in the decision-making process were not explicitly considered in this study. The scale, scope and quality of information are a crucial element in the decisions managers make. One important component of a modern information system is accounting information. It plays an important role in planning, implementation and control that may greatly influence farm decisions, practices and performance. This is a generalized assumption applied to agriculture, despite the low use of accounting in this sector (Poppe, 1991). For example, Luening (1989) states that farm accounting provides information on the farm’s financial position and performance, a diagnostic tool for identifying strengths and weaknesses, and a planning tool. However, little empirical research has been done to verify that accounting will improve farm performance. This lack of empirical research is also applicable to small firms (Mitchell et al., 2000). Verstegen et al. (1995, 1998), Lazarus et al. (1990) and Tomaszewski et al. (2000) performed regression analysis to demonstrate that the use of management information systems improves profits and performance in sow-herd and dairy farms. However, to our knowledge no previous production frontier studies have included the use of accounting information by farmers to explain technical farm efficiency. Trip et al. (2002) showed positive associations between the efficiency of commercial greenhouse growers and monitoring and firm evaluation.

The principal aim of this paper is to estimate a translog stochastic frontier production function in the analysis of 147 mixed Catalan farms in the period 1989-1993, in order to attempt to measure and explain variation in inefficiency scores with a one-stage approach. The model uses gross value added as the output aggregate measure, instead of the physical output quantities or total revenues used in other studies. Total employment, fixed capital, current assets, specific costs and overhead costs are introduced into the model as inputs in order to obtain a detailed modelling of the production function. Monetary output and input measures are obtained following the methodology of the Farm Accountancy Data Network (FADN) procedures established by the European Commission. The model allows efficiency scores to vary over time, and inefficiency effects to be a function of a wide set of explanatory variables, in which farm management capacity and farm environment play an important role. The main focus of this study is to explain the influence of an important aspect of the decision-making process, accounting-based information, on output efficiency of mixed farms in Catalonia. The hypothesis to be tested is that the use of accounting information in the farm decision-making process as a planning and a control tool may positively contribute to increasing their output efficiency.

This paper differs from much previous research by estimating the sources of inefficiency with a stochastic production frontier model for a balanced panel data set of farms located in a European Union country. The model is specially designed to obtain evidence regarding the influence of the use of accounting information in the decision-making process on farm efficiency variation.

The paper continues with the following structure. Section 2 outlines the stochastic frontier approach with the inefficiency effects model. The empirical specification of the model is presented in Section 3. Empirical results derived from this model and discussion is presented in Section 4. The empirical results allow us to present efficiency scores, and factors explaining efficiency. The final section summarizes the findings of this research.

Download journal paper of accounting information: ziddu


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