Agricultural, Food and Natural Resource Economics - EC571

Location Term Level Credits (ECTS) Current Convenor 2017-18 2018-19
Canterbury Spring
View Timetable
6 15 (7.5) PROF IM Fraser

Pre-requisites

EC500 Microeconomics (for students on Economics degree programmes)

EC313 Microeconomics for Business and EC532 Environmental Economics, Institutions and Policy (for non Economics students)

Restrictions

None

2017-18

Overview

This module introduces you to agriculture, food and natural resource economics and economics generally. A key objective is to help you develop an ability to apply economic thinking to problems in this area. The module considers various aspects of agricultural, food and resource economics including food production, economic theory related to agricultural policy, food supply chains and food prices, food economics specifically food labels and various economic aspects of natural resource management such as forestry and fisheries.

The module is divided into three parts. In Part A we examine the relationship between the economy and the agriculture. In Part B we consider aspects of food economics. In Part C we examine various issues relating to natural resource. The emphasis in all parts of the module is to understand the links between theory and practice.

Details

This module appears in:


Contact hours

11 Lectures (100 minutes)
10 seminars

Method of assessment

10% Short answer assignment
10% Essay (2000 words)
80% Examination (2 hours)

Preliminary reading

The following are some of the texts that we will refer to:

• A Barkley and PW Barkley, Principles of Agricultural Economics, Routledge (2013).
• JM Conrad, Resource Economics (2nd ed), (2010).
• J Williams, Competition and Efficiency in International Food Supply Chains Improving Food Security, Routledge (2013).
• DW Allen and D Lueck, The Nature of the Farm. Contract, Risk and Organisation in Agriculture, MIT (2002).
• D Besanko, D Dranove, M Shanley and S Schaefer, Economics of Strategy (4th ed), John Wiley and Sons (2007).
• DF Heathfield and S Wibe, An Introduction to Cost and Production Functions, MacMillan Press (1987).
• M Mazzocchi, WB Traill and JF Shogren, Fat Economics. Nutrition, Health, and Economic Policy, OUP (2009).
• GW Norton, J Alwang and W Masters, Economics of Agricultural Development. World Food Systems and Resource Use (2nd ed), Routledge (2010).
• B Wansink, Marketing Nutrition. Soy, Functional Foods, Biotechnology, and Obesity, University of Illinois Press (2007).

In addition, papers in top field journals including:
• American Journal of Agricultural Economics
• European Review of Agricultural Economics
• Journal of Agricultural Economics
• Agricultural Economics
• Food Policy
• Ecological Economics
• Journal of Economic Perspectives

See the library reading list for this module (Canterbury)

See the library reading list for this module (Medway)

Learning outcomes

By the end of the module, you will be able to:
• Understand how a variety of microeconomic concepts, such as profit maximisation, asymmetric information, risk and uncertainty, and market failure have been used to investigate various aspects of agricultural, food and natural resource economics;
• Understand how various types of data sources (eg, household surveys, national statistics) can be used to test economic theories and guide economic policies;
• Construct coherent economic arguments by making reference to microeconomic theories and empirical evidence on individual decision-making and business strategy;
• Assess different theories about the behaviour of households, farmers, manufacturers and government in this sector of the economy using existing theories and evidence on individual decision making;
• Discuss the effectiveness of various agricultural, food and resource related policies – eg CAP, commodity price volatility, contractual arrangements – in the context of existing theories and evidence on decision making;
• Solve simple microeconomic models that can shed light on phenomena related to agriculture, food and natural resources;
• Analyse microeconomic data using statistical methods and software (eg, Microsoft Excel).

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