Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/97422 
Year of Publication: 
2013
Series/Report no.: 
cemmap working paper No. CWP46/13
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
Widely used convolutions and deconvolutions techniques traditionally rely on the assumption of independence, an assumption often criticized as being very strong. We observe that independence is, in fact, not necessary for the convolution theorem to hold. Instead, a much weaker notion, known as subindependence, is the appropriate necessary and sufficient condition. We motivate the usefulness of the subindependence concept by showing that is arguably as weak as a conditional mean assumption. We also provide an equivalent definition of subindependence that does not involve Fourier transforms and devise a constructive method to generate pairs of subindependent random variables.
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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