Non Updating Household Consumption with Fuzzy Social Accounts

Many techniques are available for updating Social Accounting Matrices (SAMs). Here we use a semi-qualitative approach based on the fuzzy set theory. Essentially, we restrict estimates of interindustry coefficients to just seven possible size categories when they are updates. These rough categorical estimates are transformed to some quantitate functions (domains that define ranges of coefficients sizes). We then use the fuzzy matrix that results to model the impacts of various exogenous shocks on the composition of household expenditures. These resulting model functions are interpreted as quasi probability density functions so a quasi-stochastic programming problem is used to estimate fuzzy impacts. The fuzzy results are compared to results estimated via a classically created SAM. In an empirical exercise, we use a 57-industry 2010 SAM for New Jersey and increase each exogenous factor, in turn, by 10 percent. The difference in estimates between the fuzzy and classical approaches on total household expenditures never exceeds 0.044 percent. This suggests the fuzzy approach is a promising way to update SAMs, at least those used to estimate economic impacts.