Materialized summary tables and cached query results are frequently used for the optimization of aggregate queries in a data warehouse. Query rewriting techniques are incorporated into database systems to use those materialized views and thus avoid the access of the possibly huge raw data. A rewriting is only possible if the query is derivable from these views. Several approaches can be found in the literature to check the derivability and find query rewritings. The specific application scenario of a data warehouse with its multidimensional perspective allows the consideration of much more semantic information, e.g. structural dependencies within the dimension hierarchies and different characteristics of measures. The motivation of this article is to use this information to present conditions for derivability in a large number of relevant cases which go beyond previous approaches.

This paper reviews the status quo of the empirical and theoretical literature on the determinants of the elasticity of substitution between capital and labor. Our focus is on the two-input constant elasticity of substitution (CES) production function. By example of the U.S., we highlight the distinctive heterogeneity in empirical estimates of σ at both the aggregate and industrial level and discuss potential methodological explanations for this variation. The main part of this survey then focuses on the determinants of σ. We first review several approaches to the microfoundation of production functions, especially the CES production function. Second, we outline the construction of an aggregate elasticity of substitution (AES) in a multi-sectoral framework and investigate its dependence on underlying sectoral elasticities. Third, we discuss the influence of the institutional framework on the determination of σ. The concluding section of this review identifies a number of potential empirical and theoretical avenues for future research. Overall, we demonstrate that the effective elasticity of substitution (EES), which is typically estimated in empirical studies, is generally not an immutable deep parameter but depends on a multitude of technological, non-technological and institutional determinants.