From process consultation to a clinical model of development practice

This article argues that two related concepts, process consultation and, in particular, the clinical perspective, developed by the organizational psychologist Edgar Schein, can improve the understanding, teaching and conduct of development practice. Process consultation, which is more than just the application of so-called process approaches, and the clinical perspective are described, and the case for them is put, in relation to contrasts with ethnography and action research and in the light of contemporary debates about the relationship between development studies and development practice. Five particular aspects of the clinical model—the primacy of the ‘helpful intervention’, the subservience of science to helping, its client centredness, its recognition of interventionists’ financial and political status, and its overt normativeness—are seen as particularly relevant to development practice. In conclusion, the clinical model is seen to pose four challenges for development studies: the creation of development's own theory of practice, the establishment of rigorous practitioner training programmes, the consequent institutional change, and an acknowledgement of the implications of development studies’ disciplinary biases. © 1997 by John Wiley & Sons Ltd. Public Admin. Dev. Vol. 17 , 325–340 (1997). No. of Figures: 0. No. of Tables: 0. No. of Refs: 48.     

Forecasting General Fund Revenue: An Analysis of Idaho FY 1998 to FY 2011

Forecasting state general fund revenue (GFR) though business cycles means possibly confusing a cycle with an underlying long‐run trend. Relative to the actual revenue, the mean squared error of the academic, legislative, governor's, the growth path (GP), and Holt‐Winters (HW) forecasts for Idaho GFR was not significantly different than the naïve forecast's; the Combined GP‐HW forecast has significantly smaller mean square error. The GP model (ARIMA 1, 2, 1) produced a short‐run elasticity of revenue with respect to income of 1.05 (±0.05). The best GFR forecasts combined a HW two‐step‐ahead level with a GP one‐step‐ahead trend that provided a forecast of GFR with the smallest root mean square error between FY 1998 and FY 2009. A budget stabilization fund needs to be 34–40 percent of GFR for GFR to sustain growth at the state's long‐run expansion rate during a contraction.