Optimal design of syndicated panels: A mathematical programming approach

A new design concept for syndicated panels is proposed which explicitly handles tradeoffs between the economics of the panel (i.e., costs and revenues) and its econometrics (risk of sampling errors). Economic and statistical criteria are directly incorporated, leading to new mathematical programming formulations for deciding panel composition and size. These models provide insights into the complexities of panel design that are not available from traditional statistical methods. Much of the published literature does not address syndication or panel sampling and attendant complications such as demographic shifts and turnover standards. The present paper provides new methods, with worked examples, for optimizing the design when such conditions are present and thereby extends the range of situations for which optimal designs can be obtained. The traditional 'cost of a sample unit' is disaggregated to separate costs of sample recruitment, retention and maintenance, thus linking the sampling considerations to the optimization of the operation of the panel.