A Comparative Analysis of Agricultural Tractor Investment Models

Abstract

An implicit rental price approach is used to analyse the determinants of farm tractor investment at the aggregate level. Three models, based on different assumed factor substitutabilities, are compared. Variations in the rental price of tractors appear to have less effect on demand than variations in factors affecting the profitability of the cropping enterprise as a whole. The implications for forecasting and for policy instruments, such as the investment allowance, are discussed.There has been a profusion of economic analysis of both investment behaviour and of the determinants of investment decisions. Most of this analysis has dealt with aggregate investment for the entire economy or for particular sectors, rather than with decisions relating to individual types of capital equipment.In this paper, the focus is on investment determinants at the firm level. Three distinct approaches to investment analysis are identified. These are developed at the microeconomic level, by considering the basis of individual decisions, and tested empirically at the aggregate level. Tractors are of interest because of the size of the capital outlay required and the range of different investment theories that have been used to model this decision. In addition, data pertaining to tractors are superior to those relating to other durable farm inputs.Tractors are a significant component of the capital cost of farm machinery (about 40 per cent), which in turn account for about 10 per cent to 15 per cent of total farm costs. Normally, about 12 000 to 14 000 tractor units are sold annually. The average size has trended upward over time. The aggregate investment expenditure in farm tractors was about $400m in 1983-84.Tractor sales have been analysed inter aka by Penson, Hughes, and Nelson (1977), Penson, Romain, and Hughes (1981), Rayner and Cowling (1 967, 1968), Griliches (1 960), and by Filmer and Ferris (1 976). Although a range of approaches has been used, the majority of recent studies have adopted the rental price approach, as expounded by Jorgensen and Stephenson (1 967) and Coen (1 975). This approach has also been used to model aggregate rural sector investment (Fisher 1974).In this paper, a putty-putty model is compared to putty-clay and clayclay models. In the first model, it is assumed that factor proportions are flexible and responsive to relative price movements both before and after the installation of the capital item. The putty-clay model implies fixed factor proportions once the capital has been installed, while the clay-clay alternative is based on the premise that factor proportions are determined by the nature of the production process and are not responsive to relative prices either before or after installation. 122

On‐farm Factors Influencing Investment in Crop Sowing Machinery*

“…Although timeliness costs have received the most attention in the literature, other influences upon investment decisions such as taxation Bradford 1983, Smith 1990), the lumpiness of investment decisions (Danok et al 1980), changes in technologies (Stoneham andOckwell 1981, Epplin et al 1982), investment allowances (Chisolm 1974, Vanzetti andQuiggin 1985) and crop sowing tactics (Bathgate 1993) have all received some attention. No model reported in the literature claims to examine all factors likely to affect machinery selection.…”

“…The techniques employed to examine cropping machinery investment have been simulation (Sorenson and Gilheany 1970, Van Kampen 1971, Donaldson 1975, Edwards and Boehlje 1980, Epplin et al 1982, Whan and Hammer 1985, Wetzstein et al 1990, Fraser and Batterham 1995, a variety of programming methods (Boisvert 1976, McCarl et al 1977, Danok et al 1980, Reid and Bradford 1987, Bathgate 1993 and econometric approaches (Vanzetti andQuiggin 1985, Cooper 1994).…”

“…If other factors such as the effects of marginal tax rates and investment allowances (see Vanzetti and Quiggin 1985) and non-linearities in machinery cost and grain yield functions were to be considered then non-linear programming would be a preferable analytical tool. It is not surprising, given the many factors influencing machinery investment decisions, that programming models have often been employed in examining machinery use and investment (e.g., Gustafson 1993).…”

Farm Mechanization in Indian Agriculture with Focus on Tractors

“…Since tractors compete with labor in agriculture (Vanzetti & Quiggin, 1985), the cost of labor measured as real farm wages is assumed to capture the substitution price effect on the demand for tractors. We calculate the relative price of tractors as the ratio of the Wholesale Price Index of tractors to the real wage rate.…”

A business model in agricultural production in Serbia, developing towards sustainability

“…The elasticity indexes in the Cobb-Douglas function is in detail described in the article written by Pandey et al, 1982, in which the annual time series data for the period 1950-76 are used to estimate the price elasticity of aggregate Australian agricultural supply. In the paper written by Vanzetti and Quiggin, 1985, the investment analysis is identified at the microeconomic level, by considering the basis of individual decisions, and tested empirically at the aggregate level.…”