Management Forecast Quality and Capital Investment Decisions

By Theodore H. Goodman, Monica Neamtiu, Nemit Shroff, Halbert White. 2014

350 citations recorded by the source corpus.

ABSTRACT: Corporate investment decisions require managers to forecast expected future cash flows from potential investments. Although these forecasts are a critical component of successful investing, they are not directly observable by external stakeholders. In this study, we investigate whether the quality of managers' externally reported earnings forecasts can be used to infer the quality of their corporate investment decisions. Relying on the intuition that managers draw on similar skills when generating external earnings forecasts and internal payoff forecasts for their investment decisions, we predict that managers with higher quality external earnings forecasts make better investment decisions. Consistent with our prediction, we find that forecasting quality is positively associated with the quality of both acquisition and capital expenditure decisions. Our evidence suggests that externally observed forecasting quality can be used to infer the quality of capital budgeting decisions within firms. JEL...

Subfields: Accounting, Finance, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/a1486aed73f4a7ba176ad50ded25d1c5ec86b3c0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Accounting

  1. Christian Leuz
  2. Peter D. Wysocki
  3. Nemit Shroff
  4. Rodrigo S. Verdi
  5. Luo Zuo
  6. Karthik Balakrishnan
  7. Gwen Yu
  8. Luzi Hail

In Finance

  1. Christian Leuz
  2. Peter D. Wysocki
  3. Nemit Shroff
  4. Gwen Yu
  5. Rodrigo S. Verdi
  6. Luo Zuo
  7. Karthik Balakrishnan
  8. Halbert White

In Strategy and Management

  1. Christian Leuz
  2. Peter D. Wysocki
  3. Nemit Shroff
  4. Luo Zuo
  5. Halbert White
  6. Rodrigo S. Verdi
  7. Karthik Balakrishnan
  8. Ross L. Watts

Citations in the corpus