Dealing with Uncertain Budget Forecasts

Penner, Rudolph G.

doi:10.1111/1540-5850.00062

Cited by 16 publications

(14 citation statements)

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“…They also figure centrally in the deliberations that go into the development of policy options. Recently, Aaron (2000) and Penner (2002) have highlighted the policy problems of and some possible policy reactions to uncertainty in budget projections. Although they focus a great deal on general macroeconomic forecasting, they also address the problems of predicting the effects of policy…”

Section: Introductionmentioning

confidence: 99%

“…However, as models get increasingly complex, it is difficult, if not impossible, to even compare the assumptions of different approaches or have any sense of what drives the different predictions. Penner (2002) discusses how difficult it is to understand what drives the predictions of large-scale time series macroeconomic models or to relate them to more structural models. Similar problems occur when comparing different approaches in other modeling areas.…”

Section: Introductionmentioning

confidence: 99%

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Modeling Health Insurance Expansions: Effects of Alternate Approaches

Remler¹,

Zivin²,

Glied³

2002

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Estimates of the costs and consequences of many types of public policy proposals play an important role in the development and adoption of particular policy programs. Estimates of the same, or similar, policies that employ different modeling approaches can yield widely divergent results. Such divergence often undermines effective policy-making. These problems are particularly prominent for health insurance expansion programs. Concern focuses on predictions of the numbers of individuals that will be insured and the costs of the proposals. Several different simulation modeling approaches are used to predict these effects, making the predictions difficult to compare. In this paper, we do the following: (1) We categorize and describe the different approaches used; (2) we explain the conceptual and theoretical relationships between the methods; (3) we demonstrate empirically an example of the (quite restrictive) conditions under which all approaches can yield quantitatively identical predictions; and (4) we empirically demonstrate conditions under which the approaches diverge and the quantitative extent of that divergence. All modeling approaches implicitly make assumptions about functional form that impose restrictions on unobservable heterogeneity. Those assumptions can dramatically affect the quantitative predictions made.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling Health Insurance Expansions: Effects of Alternate Approaches

Remler¹,

Zivin²,

Glied³

2002

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“…Early estimates of the premiums for the Clinton administration's health insurance proposal, for example, varied by about 35 percent (Rivlin, Cutler, and Nichols 1994). Errors in estimates of the cost growth of Medicaid and Medicare accounted for much of the CBO's overall budget forecast errors during the 1990s (Penner 2002). These errors are inevitable.…”

Section: Resultsmentioning

confidence: 99%

Inside the Sausage Factory: Improving Estimates of the Effects of Health Insurance Expansion Proposals

2002

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Many policy proposals address the lack of insurance coverage, with the most commonly discussed being tax credits to individuals, expansions of existing public programs, subsidies for employers to offer coverage to their workers, and mandates for employers and individuals. Although some policy options may be favored (or disfavored) on theoretical or ideological grounds, many debates about policy center on empirical questions: How much will this option cost? How many people will obtain insurance coverage? Estimates of costs and consequences influence policy in three ways. First, the Office of Management and Budget, the Congressional Budget Office, the Centers for Medicare and Medicaid Services, the Treasury Department, and other government agencies incorporate estimates of the costs of proposals in their budget calculations. Particularly in times of fiscal restraint, the cost of a proposal is central to its legislative prospects. Second, recognizing the importance of final budget numbers, policy advocates include estimates in their advocacy. The fate of a proposal to expand health insurance is influenced by predictions of the proposal's effects on the number of newly insured and the cost of new coverage. Estimates vary widely, for reasons that are often hard to discern and evaluate. This article describes and compares the frameworks and parameters used for insurance modeling. It examines conventions and controversies surrounding a series of modeling parameters: how individuals respond to a change in the price of coverage, the extent of participation in a new plan by those already privately insured, firms' behavior, and the value of public versus private coverage. The article also suggests ways of making models more transparent and proposes "reference case" guidelines for modelers so that consumers can compare modeling results.

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“…Penner (2002), par exemple, évalue la difficulté de prévoir les coûts budgétaires en citant des exemples concernant les États-Unis. Les coûts peuvent être sous-estimés si les prévisions concernant l"adoption d"un programme sont trop faibles (auquel cas les programmes ne disposeront pas de crédits suffisants) ou surestimés (auquel cas l"efficacité du programme peut être remise en cause).…”

Section: Coûts De Transactionunclassified

Déficits d'information dans l'élaboration, la mise en oeuvre et le suivi des politiques agricoles.

Blandford

2007

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L'élaboration, la mise en oeuvre, le suivi et l'évaluation des politiques agricoles doivent être guidés par des informations précises et complètes. Il est essentiel de disposer d'informations qualitatives et quantitatives pour pouvoir bien cibler les mesures gouvernementales et en assurer l'efficience et le bien fondé économique. L'analyse coûts-avantages et l'évaluation quantitative de l'impact des politiques supposent de disposer d?informations de qualité en quantité suffisante. Or cette tâche est de plus en plus difficile en raison de l'accroissement de l?éventail et de la complexité des questions associées à l'agriculture. Le manque de connaissances sur les relations techniques qui sous-tendent certains processus clés, les incertitudes quant aux effets produits ou la difficulté de les suivre, de même que l'asymétrie de l'information (lorsque l'information nécessaire aux responsables des politiques existe mais qu'il est difficile ou coûteux de se la procurer) sont autant de problèmes à surmonter. La présente étude passe en revue les besoins d'informations nécessaires pour guider l'élaboration, la mise en oeuvre, le suivi et l'évaluation des politiques agricoles, met en évidence les déficits, préconise différentes mesures destinées à améliorer la disponibilité, la qualité et la pertinence des données pour répondre aux priorités de l'action publique et propose des options pour y parvenir. Elle propose également des méthodes pour combler les lacunes persistantes lors de l'élaboration et de la mise en oeuvre des politiques.

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Dealing with Uncertain Budget Forecasts

Cited by 16 publications

References 1 publication

Modeling Health Insurance Expansions: Effects of Alternate Approaches

Modeling Health Insurance Expansions: Effects of Alternate Approaches

Inside the Sausage Factory: Improving Estimates of the Effects of Health Insurance Expansion Proposals

Déficits d'information dans l'élaboration, la mise en oeuvre et le suivi des politiques agricoles.

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