Stirling March 24 ’09 A combinatorial optimisation approach to non-market environmental benefit aggregation via simulated populations Stephen Hynes, Nick Hanley, Cathal O’Donoghue

Stirling March 24 ’09 Background  This research considers the use of spatial microsimulation in the aggregation of regional environmental benefit values.  Use matched survey and Census information to produce regional aggregate WTP figures  An application to corncrake conservation on Irish farmland

Stirling March 24 ’09 The Corncrake

Stirling March 24 ’09

Stirling March 24 ’09

Stirling March 24 ’09 The Datasets  The Irish National Farm Survey Collected as part of the Farm Accountancy Data Network of the European Union (FADN) Farmers asked WTP info in conjunction with the usual farm activity info.  The Census of Agriculture identifies every operational farm in the country and collect data on agricultural activities undertaken on them The 2006 NFS contains 1,177 nationally representative farms and the Census contains info on 145,000 farms.

Stirling March 24 ’09 WTP Question in NFS  A payment card showing the bid amounts of €10, €20, €30, €40, €50 and €60 and farmers were asked: “of these bid amounts which would be the maximum you would be willing to pay (€) each year into a conservation fund to aid in the restoration of this bird and bring the singing male population back up to a sustainable population of 900 birds”  Given the nature of the CV elicitation format we use an interval regression to model WTP

Stirling March 24 ’09 The combinatorial optimisation problem  Want to find an optimum configuration (i) of farms satisfying: where denotes the minimum error between the actual census tables of size, system and soil type and the simulated tables constructed using the configuration of NFS farms  But there is a maximum possible number of farm configurations in the matching process and also a computation time constraint  In order to solve this combinatorial optimisation problem we employ what is defined as an approximation algorithm which yields an approximate solution in an acceptable amount of computation time.

Stirling March 24 ’09 Process for a Single ED  Choose a configuration (i) of NFS farms to represent the Census SAP tables for a single ED.  Another configuration j can be obtained by randomly selecting a number of records in configuration i and replaced them with ones chosen at random from the universe of NFS records.  The number of records to be replaced is defined as T.  Letting the probability that configuration j will be the next configuration of farms in a predefined sequence of configurations (the java program sets the number of iterations) is given by 1, if 0.  The acceptance of a new configuration is decided by drawing random numbers from a uniform distribution on [0, 1] and comparing these with. This process continues, with T being lowered at each step until the maximum number of iterations has been hit or the error falls within the desired setting.

Stirling March 24 ’09 Simulating Annealing Process  On completion of the matching process we have a list of farm ids from NFS for each ED in the country  We then simply merge all the information associated with the farms in the NFS (including WTP for corncrake conservation) to characterise our ED population of farms  Now have farm activity information and WTP for each farm in each ED

Stirling March 24 ’09 WTP Aggregation  We calculate the aggregate environmental value of the corncrake conservation program in 3 alternative ways

Stirling March 24 ’09 Results-CV Interval Regression

Stirling March 24 ’09 WTP estimates for the 4 alternative estimation methods

Stirling March 24 ’09 Total WTP estimates per County for the 4 alternative aggregation methods

Stirling March 24 ’09

Stirling March 24 ’09

Stirling March 24 ’09 Conclusions  Using the combinatorial optimisation one can take into account the spatial heterogeneity of the target population in the aggregation process.  The synthetic spatial micro-data can be combined with other GIS datasets for follow on analysis.  Usage in other stated and revealed preference valuation techniques

Stirling March 24 ’09 Thank You!  Hynes, S., Hanley, N. and O’Donoghue, C. (forthcoming). A combinatorial optimisation approach to non-market environmental benefit aggregation via simulated populations, Land Economics  Hynes, S. and Hanley, N. (2009). The ‘‘Crex crex’’ lament: Estimating landowners willingness to Pay for Corncrake Conservation on Irish Farmland, Biological Conservation 142: