Agricultural Prices and Commodity Market Analysis / Edition 1

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Overview

This book features the application of economic theory to agriculture and the food industry, using quantitative tools. The blend of theory and application is unique in detailing how demand and supply can be measured and how econometric simulation models may be constructed and evaluated. The volume focuses on forecasting and generating long-term projections as well as discussing the relatively unexplored area of stochastic modeling, which is critical in handling crop yield variability. Other topics covered in the text include agricultural policy analysis and futures/options markets. The role of time series models in improving structural equations and forecasting techniques provides a capstone for this book.

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Product Details

  • ISBN-13: 9780870137518
  • Publisher: Michigan State University Press
  • Publication date: 7/28/2005
  • Edition description: REV
  • Edition number: 1
  • Pages: 361
  • Product dimensions: 7.00 (w) x 10.00 (h) x 1.00 (d)

Meet the Author

John N. Ferris is a Professor Emeritus in the Department of Agricultural Economics at Michigan State University. Ferris has received numerous awards for his extension programs, five "Premiere Forecaster Awards" from the American Agricultural Economics Association, and "Distinguished Service to Agriculture Award" from the Michigan Farm Bureau.

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Table of Contents

1 Introduction 1
2 Theoretical concepts of demand and supply 7
3 Measuring demand for domestic consumption 21
4 Measuring demands for storage, speculation, and exports 42
5 Measuring price spreads and derived demand for agricultural products and inputs 53
6 Measuring farm supply 72
7 Recursive and simultaneous supply-demand models 99
8 Building econometric/simulation models 121
9 Forecast evaluation 142
10 Stochastic modeling 154
11 Generating long-term projections and forecasts 171
12 Spatial commodity analysis and trade 189
13 Application of models to long-range planning and policy analysis 208
14 Seasonals 219
15 Commodity futures and options markets 233
16 Forward pricing with futures and options 253
17 Technical analysis 282
18 Time series models 305
19 Sources of agricultural data and market analysis 330
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