Socio-Economic Statistics and Public Policy: A New Role for Microsimulation Modeling

Abstract

Users of socio-economic statistics typically want more and better information. Often, these needs can be met simply by more extensive data collections, subject to usual concerns over financial costs and survey respondent burdens. Users, particularly for public policy purposes, have also expressed a continuing, and as yet unfilled, demand for an integrated and coherent system of socio-economic statistics. In this case, additional data will not be sufficient; the more important constraint is the absence of an agreed conceptual approach. In this paper, we briefly review the state of frameworks for social and economic statistics, including the kinds of socio-economic indicators users may want. These indicators are motivated first in general terms from basic principles and intuitive concepts, leaving aside for the moment the practicalities of their construction. We then show how a coherent structure of such indicators might be assembled. A key implication is that this structure requires a coordinated network of surveys and data collection processes, and higher data quality standards. This in turn implies a breaking down of the stovepipe systems that typify much of the survey work in national statistical agencies (i.e. parallel but generally unrelated data--production lines). Moreover, the data flowing from the network of surveys must be integrated. Since the data of interest are dynamic, the proposed method goes beyond statistical matching to microsimulation modeling. Finally, these ideas are illustrated with preliminary results from the LifePaths model currently under development in Statistics Canada.