The economic impacts of river rehabilitation: A regional Input–Output analysis

Abstract We developed a model to predict the impacts of river rehabilitation activities on the local economy. The model is based on the Input–Output analysis technique and was applied to the planned rehabilitation project for the River Thur in northern Switzerland, along the 4 km stretch between the communities of Burglen and Weinfelden. We estimated changes in local employment and local economic output resulting from government spending on rehabilitation, associated changes in adjacent land use, and increased recreational activity. Accounting for land use changes required a modification of the conventional Input–Output analysis technique which should be of general interest. We accounted for uncertainty in the data and in some of the model assumptions by using a probabilistic formulation and propagating uncertainty through the model equations. As time-consuming local surveys were beyond the scope of this study, we used the Location Quotient non-survey technique to construct the local technical coefficients from national data and local employment data. This implies that the model can be applied quite easily to a different study area in Switzerland as long as local employment data are available. For each CHF 1 million expenditure per year on rehabilitation activities in our study region, we estimate an extra 8 fulltime employment equivalents (standard deviation, σ  = 0.4 fte) and an increased output of CHF 1.4 million ( σ  = CHF 0.05 million). The low uncertainty of these estimates can be partly attributed to the structure of Input–Output analysis and partly to the fact that we estimated changes in the economic output, rather than output itself. In addition to the above impacts, we estimate that increased recreational use of the area will increase output by as much as CHF 0.17 million ( σ  = CHF 0.12 million) and employment by as much as 1.7 fulltime employment equivalents ( σ  = 1.3 fte), depending on the specific rehabilitation option selected.

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