The dynamics of government revenue forecasting from an organizational perspective: a review of the literature

Abstract

Over a decade ago, Bretschneider and Gorr proposed two directions for future research in government forecasting: one was to extend the research on developing and evaluating alternative forecasting methods and the other, to look at forecasting as a human activity and examine how organizational factors affect forecasting. What has happened since then? To see partially what has been done and what remains to be done, this paper provides a review of the literature on government revenue forecasting with a primary focus on the state level and identifies areas for future research in government revenue forecasting.

An Open Systems Model of Local Government Forecasting

“…As noted by Wildavsky (1986) and Frank and Zhao (2009), local government decision makers use single source forecasts, which limit their ability to compare and contrast internal forecasts with those from external agencies and researchers as in the state level (Brogan, 2013). Despite this unique context, which may have constrained the ability of local governments to prepare for uncertainty, there remains limited inquiry on the factors associated with forecast accuracy at the local level (Sun, 2005). To empirically examine this research question, this article offers an open systems model of local government forecasting, which suggests that government decision making is a function of both internal and external factors.…”

“…Following Bretschneider and Gorr (1987) and Sun (2005), internal determinants encompass the institutional characteristics of the local government. Internal determinants also incorporate a budgeting dimension, to represent local fiscal characteristics and capacity (Sun, 2005). Each of these internal dimensions collectively reflects how the government reaches a forecast.…”

“…The political context of local government forecasting is a final dimension of this model. At the state level, it is typically hypothesized that political factors contribute to conservative forecast bias, which leads to underforecasting (Cassidy et al, 1989;Couture & Imbeau, 2009;Jordan, Yan, & Hooshmand, 2015;Krause, Lewis, & Douglas, 2006;Rose & Smith, 2011) Although there is mixed empirical evidence that politics influence state government forecasting accuracy in literature prior to the 2000s (Sun, 2005), 2 more recent literature has established that there is a political dimension in local governments (Mikesell & Ross, 2014). At the local level, only one study looks at the effects of politics on local government forecasting, and finds mixed evidence for this hypothesis (Larkey & Smith, 1989).…”

“…This article advances the literature on local government forecasting on four fronts. First, the article develops the understanding of the determinants of forecasting accuracy, an area which has received less attention relative to the question of forecasting methodology (see Sun, 2005). In particular, the model developed in this article can be used in future research, and tested with other types of local governments such as municipalities and counties.…”

“…Special purpose governments such as school districts also faced a similar concern, given the challenges they experienced in responding to lower than anticipated revenues through the recession (Bruck & Miltenberger, 2013). Despite these cases, which reflect the concerns associated with using a single source forecast in local government, research has largely focused on state government forecasting accuracy and the broader question of forecasting methodology (McDonald, 2015; Sun, 2005). This leaves the concern of which factors are associated with local government forecasting.…”