Estimating permanent and transitory income elasticities of education spending from panel data

We use a twenty-one year panel of data to examine the role of past income and aid, and expectations of future income, in regressions explaining state and local education spending. We show that simple estimates of the elasticity of spending with respect to financial resources are not robust to specification changes because the variables are non-stationary over time, causing inconsistent estimation of model parameters. Estimation in first differences (or equivalently, in growth rates) solves the time-series problems and produces robust estimates of the model's parameters. We then show that current spending by states responds to changes in expected future income. This explains why using fixed effects in simpler models reduces estimated income elasticities; fixed effects partially capture permanent income effects on spending. Estimates of lagged income are significant when used in models that do not explicitly model the expectations process, but present and past aid both have no effect on education spending. Models with structural assumptions about expected income produce estimates very similar to simpler models which include lagged information on income as a control variable. We conclude with recommendations for estimating models when only cross-section data or only short panels are available.