The impact of changes in the AgriStability program on crop activities: A farm modeling approach

Abstract

To analyze the production impacts of changes made in 2013 to Canada's AgriStability risk management program, we calibrate a crop allocation model using positive mathematical programming (PMP).Because PMP is not straightforward if farmers are assumed to maximize expected utility (as a risk parameter also needs to be calibrated), we consider possible ways to address this issue but settle on a traditional approach used in the EU's Farm System Simulator. We calibrate farm management models for six different Alberta regions and use it to determine how changes in the AgriStability's payment trigger affect production incentives. Results indicate that, although the

The impact of price hedging on subsidized insurance: Evidence from Canada

“…Turvey (2012) finds that the Canadian Agricultural Income Stabilization (CAIS) program (a predecessor to AgriStability) substantially alters acreage decisions for a representative farm in Manitoba, encouraging producers to adopt riskier, more profitable crops. Liu et al (2018) show that changes in AgriStability (which took effect in 2013) had only a marginal impact on crop choice for representative farms in Alberta. Schaufele et al (2010) analyze the impact of AgriStability on farm profits for cattle producers in Alberta.…”

“…Finally, there are a handful of papers that have used numerical simulations to model the impacts of AgriStability and other publicly funded risk management programs in Canada. Turvey (2012) and Liu et al (2018) both investigate the impact of government programs on crop choice. Turvey (2012) finds that the Canadian Agricultural Income Stabilization (CAIS) program (a predecessor to AgriStability) substantially alters acreage decisions for a representative farm in Manitoba, encouraging producers to adopt riskier, more profitable crops.…”

“…Adjustment to this average is dictated by the parameters in the vector 𝜷. Mean reversion has been commonly found in commodity prices (Bessembinder et al, 1995;Wang & Tomek, 2007;Hart et al, 2016) and this type of mean-reverting process was used by Liu et al (2018) in a previous simulation of AgriStability.…”

“…Annual yield data for Saskatchewan RMs is taken from the Saskatchewan Ministry of Agriculture. 10 Following conventional assumptions, I use the distribution of average yields in each RM as a proxy for the the distribution of farm-level yields (Turvey, 2012;Liu et al, 2018). Given that individual yields may be more variable than RM level yields, I also test how sensitive the results are to a larger variance in these distributions.…”

Calibration of agricultural risk programming models using positive mathematical programming

“…If the calibration in the first step is not exact (which is highly unlikely to be the case because then only risk attitude explains crop choice), the value of φ determined in the first step is used to calibrate the cost function in a second step in the same way as the PMP method with elasticity adjustment (Louhichi et al 2010;Jeder et al 2011Jeder et al , 2014. However, because the marginal crop from the utility perspective may not be the least profitable crop in the expected utility framework, directly applying the standard PMP method cannot guarantee the perfect recovery of the observed land allocation (see Liu et al 2018). Cortignani (2010, 2012) extend an ME approach proposed by Heckelei and Wolff (2003) to calibrate simultaneously all the parameters needed within a PMP framework, including the parameters of the quadratic cost functions and CARA coefficients.…”