Non Technical Summary
The Biden administration recently released a strategy for augmenting the national accounts used to calculate U.S. Gross Domestic Product with a new set of accounts that measure the abundance and economic value of natural capital. One of these will be a "forest account". The best-available model for quantifying the accounting price of forest natural capital is inadequate for producing a national forest account for two reasons: 1) overly simplistic ecological assumptions; and 2) the lack of a management model for public forests. This project will develop a generalized forest natural capital accounting price (FNCAP) model that improves on current methodology in terms of behavioral scope, ecological and economic realism, and uncertainty quantification. We will first develop an improved private land FNCAP model that includes fire risk in the ecological and behavioral sub-models. Building on this, we will introduce the first public land FNCAP model capable of measuring social forest capital accounting prices. To do so, we will incorporate original estimates of the nonmarket value of forest-provide ecosystem services into the calculation. We will apply the FNCAP model to rich economic and ecological data from forest land in west coast states. Our analysis will also include the first rigorous uncertainty quantification analysis of FNCAP estimates. This research responds directly to priorities of the Environmental and Natural Resource Economics (A1651) program area. We will do so by developing improved methods for valuing forest natural capital and through a novel integration of nonmarket valuation results into natural capital accounting.

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
123	0699	3010	50%
605	0699	3010	50%

Knowledge Area
605 - Natural Resource and Environmental Economics; 123 - Management and Sustainability of Forest Resources;

Subject Of Investigation
0699 - Trees, forests, and forest products, general;

Field Of Science
3010 - Economics;

Goals / Objectives
This project will develop a generalized forest natural capital accounting price (FNCAP) model that improves on current methodology in terms of behavioral scope, ecological and economic realism, and uncertainty quantification. The goals of the project are to:Incorporate fire risk into an FNCAP analysis of private forest landAdd the forest-provided services of carbon sequestration and habitat provision to a FNCAP analysis of public forest land.Develop and implement a method for quantifying uncertainty associated with FNCAP estimates.

Project Methods
We will produce an original choice experiment survey of public prefernces for the conservation of forest-dependent species in western Oregon. The survey will be conducted by mail and will enroll a random sample of households in Northern California, Oregon, and Washington. The survey will employ the Dillman multiple-mailing method. The instrument will be pretested using samples of both undergraduate students and a representative sample recruited by a professional market research firm. A pre-test survey will be used to to construct a choice experiment design that is efficient with respect to a baseline empirical specification. The primary empirical tool use to analyze the final returned sample will be econometric random utility models, which will generate estimates of household willigness-to-pay for marginal and non-marginal changes in survey attributes.FNCAP model construction involves building a numerical dynamic bioeconomic model of forest resource use. A variety of empirical methods will be used to parameterize the various model components, which can be divided into ecological and economic sub-models. The ecological model will represent forest growth, fire, and forest-dependent species biodiversity yield dynamics. To model forest growth, key data sources will include the Forest Inventory Analysis (FIA) database. The economic model components include behavioral models predicting forest harvest decisionas and a reward function capturing extractive (e.g., timber harvest) and non-extractive value flows. Final estimates obtained from the choice experiment survey will be integrated into the reward function corresponding to the public land FNCAP model version.The assembled FNCAP models will be studied using numerical methods to recover the implicit accounting prices. The uncertainty quantification objective will be pursued for each FNCAP model version using Monte Carlo methods, along with sensitivity analyses centered on re-solving the FNCAP equation numerically using alternative model assumptions (e.g., functional form choices).