Acreage Response Under Canada's Western Grains Stabilization Program

Abstract

An aggregate acreage supply model for the Canadian prairies is estimated assuming that farmers base short-run acreage decisions on the ex ante rational expectation and variance of per-hectare revenue. To account for the effects of government intervention, a structural model of the Western Grains Stabilization Program is incorporated into the estimation framework. Results indicate the Program contributed to modest increases in cropped acreage between 1976 and 1990.Key words: acreage supply, rational expectations, revenue stabilization, risk response.Our ultimate goal is to estimate the log-linear aggregate acreage supply equationHere, At is millions of hectares planted in western Canada, prior to the beginning of marketing year t, to six major grain crops: wheat, barley, oats, rye, flax, and canola.' R, is the marketing year production-weighted average revenue from the six crops, in real 1986 Canadian dollars per hectare, net of WGSP payments and levy contributions. E, and V, are the expectation and whenever substantive changes in policy alter the structural determinants of market equilibrium. Thus, with the abandonment of the WGSP, the published estimates for the western Canadian grain sector lost much of their utility.To overcome lack of robustness inherent in reduced form models, we estimate a structural acreage supply model for western Canada under the assumption that farmers base acreage allocation decisions on the ex ante rational expectation and variance of per-hectare revenues. In order to account directly for the effects of government intervention, a detailed model of the WGSP is incorporated into the estimation framework. The resulting nonlinear rational expectations model is estimated using a combination of standard econometric methods and numerical integration techniques.(1) Due to the absence of stockholding data, we ignore a seventh Koroluk used Monte Carlo simulation methods to analyze procrop covered under the WGSP: mustard, which on average acposed changes in the WGSP, but did not attempt systematic counted for a negligible 0.2% of total production under the econometric estimation of the underlying structural model. program.Amer.

Effects of Enhancing NISA on Income Stabilization and Support

“…For example, Miranda et al (1994) estimate an acreage response function in which the first two moments of the distribution of producer income are significant explanatory variables. Some of the more significant ones suggest opportunities for further research.…”

“…The assumption of a zero supply response to a change in the income safety net may be inappropriate in light of recent empirical studies. For example, Miranda et al (1994) estimate an acreage response function in which the first two moments of the distribution of producer income are significant explanatory variables. NISA clearly affects both of these moments at the individual producer level.…”

“…4 SeeMiranda, Novak and Lerohl (1994) for an innovative approach to estimating supply response in the presence of an income stabilization program. 2 As reported in the FederalRegister (1996), the U.S. Commerce Department has determined that basic NISA does not provide a specific subsidy for purposes of trade action.3 Gross margin is essentially farm cash receipts less cash costs other than interest, rent, property taxes and wages to family members.…”

Canadian Agricultural Programs and Policy in Transition

“…The WGSP had the effect of stabilizing farm incomes and, therefore, met its objectives. Miranda et al (1994) examine the acreage response of farmers to the WGSP. They find that the WGSP raises the expected returns of the producer and reduces the producer risk, both of which increase the crop acreage.…”

Responsiveness of Rural and Urban Land Uses to Land Rent Determinants in the U.S. South

“…White. and Brannen 1987) and farm product market models (Brandt, Kruse, and Todd 1992;Miranda, Novak, and Lerohl 1994;Shonkwiler and Maddala 1985). Analysts have emphasized measurement of expected output price (Gallager 1978;Gardner 1976;Stein 1981), alternative ways to model the effect of farm commodity price supports (Houck et al 1976;McIntosh and Shideed 1989;Morzuch, Weaver, and Helmberger 1980).…”