Incorporation of heat exchangers into pile foundations is a relatively novel sustainable technology for the intermittent storage of energy in soils. Energy can be utilised in this way for space heating and cooling of buildings by means of suitable systems integrated into buildings. This paper relates to an ongoing study on the impact of coupled thermo-mechanical loads on heat exchanger pile foundations. This study evaluates the performance of a laboratory scale energy pile under different vertical stress levels, temperature gradients and heat transfer modes and presents the full-scale in situ energy pile setup equipped with ground loops for heating/cooling and multi-level Osterberg cells for static load testing

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Multilateral methods are increasingly being used in the computation of official price indexes such as the consumer price index (CPI). This reflects the growing use of scanner data by statistical agencies and the fact that fixed‐based or chained price comparisons perform poorly in this context. A range of multilateral approaches have been pursued by different statistical agencies. Yet, it can be shown that some of these methods, at least theoretically, could suffer from substitution bias. We investigate this as well as the drivers of chain drift. We adopt a simulation‐based approach using actual scanner data prices with the corresponding quantities being generated assuming constant elasticity of substitution (CES) preferences. We find that most methods systematically deviate from the exact CES benchmark index. This is even the case for the superlative index methods, which should not exhibit substitution bias. Interestingly, we also find significant chain drift even in the exact CES indexes. We argue this reflects life cycle pricing and particularly run‐out sales at the end of a product's life.

This article describes methods for decomposing price indexes into contributions from individual commodities, to help understand the influence of each commodity on aggregate price index movements. Previous authors have addressed the decomposition of bilateral price indexes, which aggregate changes in commodity prices from one time period to another. Our focus is the decomposition of multilateral price indexes, which aggregate commodity prices across more than two time periods or countries at once. Multilateral indexes have historically been used for spatial comparisons, and have recently received attention from statistical agencies looking to produce temporal price indexes from large and high frequency price data sets, such as scanner data. Methods for decomposing these indexes are of practical relevance. We present decompositions of three multilateral price indexes. We also review methods proposed by other researchers for extending multilateral indexes without revising previously published index levels, and show how to decompose the extended indexes they produce. Finally, we use a data set of seasonal prices and quantities to illustrate how these decomposition methods can be used to understand the influence of individual commodities on multilateral price index movements, and to shed light on the relationships between various multilateral and extension methods.