The effects of forecast type and performance-based incentives on the quality of management forecasts

Clara Xiaoling Chen, Kristina M. Rennekamp, Flora H. Zhou

Research output: Contribution to journalArticle

Abstract

Understanding forecasts is important because of their pervasiveness in business decisions such as budgeting, production, and financial reporting. In this study we use an abstract experiment to examine how the preparation of disaggregated forecasts interacts with performance-based incentives to influence the accuracy and optimism of forecasts. We manipulate two factors between subjects at two levels each: forecast type (disaggregated or aggregated) and performance-based incentives (present or absent). Consistent with our predictions, we find that (1) preparing disaggregated forecasts leads to greater improvements in forecast accuracy (compared to preparing aggregated forecasts) in the absence of performance-based incentives than in the presence of performance-based incentives, and (2) preparing disaggregated forecasts leads to greater increases in forecast optimism (compared to preparing aggregated forecasts) in the presence of performance-based incentives than in the absence of performance-based incentives. Our study contributes to our understanding of unintentional biases in the forecasting process. Our results have important practical implications for designers of management control systems who elicit internal forecasts from managers. Finally, our results also have important practical implications for those who either prepare or use external management forecasts.

Original languageEnglish (US)
Pages (from-to)8-18
Number of pages11
JournalAccounting, Organizations and Society
Volume46
DOIs
StatePublished - Oct 1 2015

Keywords

  • Disaggregated forecasts
  • Forecast type
  • Management estimates
  • Management forecasts
  • Performance-based incentives
  • Unintentional optimism

ASJC Scopus subject areas

  • Accounting
  • Sociology and Political Science
  • Organizational Behavior and Human Resource Management
  • Information Systems and Management

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