Development of a full suite of comprehensive wealth metrics requires methods and estimates of accounting prices, including for assets with no market prices or for which externalities imply a wedge between market prices and social cost. There are large literatures in environmental and cultural economics using various estimation methods (revealed preference, stated preference, hedonic estimation, benefit transfer) and similar approaches have begun to be applied in the case of digital assets.
However, there are limitations in this literature to date, which the project seeks to address. There are theoretical and applied aspects. Much of the environmental and cultural literatures use the approach of ‘Total Economic Value’ (TEV) which is theoretically inconsistent with the economic production function approach of inclusive wealth; for example, there is no constraint on the aggregated value of stated preference estimates. The aim is to develop an extended version of Dasgupta (2021) incorporating a wide suite of assets and to identify the most appropriate and feasible methods for estimation of accounting prices for different categories of asset and taking into consideration an appropriate ‘budget constraint’.
The research will then apply this expanded approach with a range of estimation methods, including a range of stated preference methods (WTA, DCE etc), data science/ML methods of estimation, and time use approaches, with a view to triangulating among them and determining the most appropriate for different categories. It will identify the challenges of aggregation from the microeconomic and local estimates found in the literature, including by comparison of adding of ‘bottom up’ estimates and ‘top down’ regional or national estimates.
