DECOMPOSING PRODUCER PRICE RISK: A POLICY ANALYSIS TOOL WITH AN APPLICATION TO NORTHERN KENYAN LIVESTOCK MARKETS

This paper introduces a simple method of price risk decomposition that determines the extent to which producer price risk is attributable to volatile inter-market margins, intra-day variation, intra-week (day of week) variation, or terminal market price variability. We apply the method to livestock markets in northern Kenya, a setting of dramatic price volatility where price stabilization is a live policy issue. In this particular application, we find that large, variable inter-market basis is the most important factor in explaining producer price risk in animals typically traded between markets. Local market conditions explain most price risk in other markets, in which traded animals rarely exit the region. Variability in terminal market prices accounts for relatively little price risk faced by pastoralists in the dry lands of northern Kenya although this is the focus of most present policy prescriptions under discussion. Producer price volatility concerns producers and governments in a wide range of industries and nations. In settings where producers have little or no access to financial markets through which they can effectively hedge against price risk, governments are often keen to find cost-effective means to reduce producer price volatility. Yet such volatility can arise from any of several sources, so identification of effective intervention strategies depends fundamentally on locating the source(s) of variability in producer prices. This paper introduces a simple method of price risk decomposition intended to serve as a policy analysis tool for precisely that purpose. This method determines the extent to which producer price risk is attributable to volatile inter-market margins, intra-day variation, intra-week (day of week) variation, or variability in terminal market price. We apply the method to livestock markets in northern Kenya, a setting of dramatic price volatility where price stabilization is a live policy issue. The remainder of the paper proceeds as follows. Section I introduces our price risk decomposition method. We then demonstrate its utility with an application to livestock markets in the drylands of northern Kenya in a series of three sections. Section II describes the context and some of the current policy debate surrounding livestock price stabilization in Kenya. Section III presents the data and key limitations of this particular sample. The empirical results appear in Section IV along with discussion of these estimates. Section V concludes.