Forward estimates

Abstract: The Chilean government is exploring several important areas of public sector reform. This article discusses performance budgeting (including spending reviews, efficiency reviews, and the Chilean performance management system), mediumterm budgeting (especially the use of forward estimates and fiscal rules), and flexibility and efficiency in budget execution. Chile’s situation as of May 2012 was analysed in the light of OECD country best practices at the annual meeting of the OECD network on performance and results in November 2012, and the article makes several suggestions for reform. JEL classification: H610 Keywords: Chile, budget structure, programme classification, formula-based performance budgeting, performance-based budgeting, evaluation, fiscal space, productivity savings mechanism, medium-term budgeting framework, MTBF, longterm projections

Abstract: This article shows how to combine top-down budgeting – in the core sense of the establishment of a hard aggregate expenditure ceiling at the start of the budget preparation process – with flexibility in the allocation of the aggregate ceiling between spending ministries during budget preparation. It argues strongly against determining spending ministry shares of the aggregate expenditure ceiling without any prior opportunity for them to present formal new spending proposals. The keys to reconciling top-down budgeting with allocative flexibility are: the baseline/new policy distinction; good forward estimates; a government-wide new policy pool; and spending review. JEL classification: E620, H610 Keywords: Fiscal policy, budget preparation process, top-down budgeting, expenditure ceiling, bottom-up spending requests, fiscal space, multi-year ceilings, baseline ceilings, allocative efficiency, aggregate fiscal discipline, budgeting techniques

Abstract: Australia notably was one of the few developed nations to avoid a technical recession subsequent to the Global Financial Crisis (GFC). However, the fact that the nation escaped a technical recession doesn’t mean that citizens and local governments were not subject to some of the measures associated with post-GFC austerity. In particular, intergovernmental grants – an important source of revenue for Australian local governments – were frozen by the federal government seeking to mitigate large deficits over the forward estimates. This chapter compares and contrasts the budgetary outcomes for the local governments of Australia’s two most populous states – New South Wales and Victoria. We find that the disparate regulatory controls in the two municipal jurisdictions were strongly associated with the budgetary outcomes of the individual municipalities: In particular, we present evidence which suggests that taxation limitations and lax investment guidelines in New South Wales can be associated with relatively inferior budgetary positions and higher budgetary volatility. By way of contrast, Victorian councils had the flexibility to vary rates of taxation to the changing conditions and largely avoided investment losses associated with the financial failure of Lehman Brothers. In New South Wales the regulatory response to deteriorating municipal budgets (subsequent to the GFC) has been to execute a radical programme of forced amalgamations. Somewhat ironically, the Victorian state government has recently imposed taxation limitations on its municipalities. In summary, this chapter demonstrates the saliency of regulatory constraints on municipal resilience, in the context of post-GFC economic challenges.

Abstract: Forward estimates of area and delay facilitate effective decision-making when searching the solution space of digital designs. Current estimation techniques focus on modeling the layout result and fail to deliver timely or accurate estimates. This paper presents a novel approach to deriving these area and delay estimates at the RTL level by modeling the layout tool, rather than the layout result. This approach uses machine learning techniques to capture the relationships between general design features (i.e., topology, connectivity, common input, and common output) and layout concepts (i.e., relative placement). Experiments illustrate the formulation of the training set for machine learning in this domain, and also show how we can derive different tool models. Finally, they show how we can use the resultant model to derive forward estimates of area and delay in real-world designs.