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Accounting and Causal Effects [electronic resource] : Econometric Challenges / by Douglas A Schroeder.

By: Contributor(s): Material type: TextTextSeries: Springer Series in Accounting Scholarship ; 5Publisher: New York, NY : Springer New York : Imprint: Springer, 2010Edition: 1st ed. 2010Description: XXVI, 462 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781441972255
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 657
LOC classification:
  • HF5601-5688
  • HF5667-5668.252
Online resources:
Contents:
Accounting choice -- Linear models -- Loss functions and estimation -- Discrete choice models -- Nonparametric regression -- Repeated-sampling inference -- Overview of endogeneity -- Treatment effects: ignorability -- Treatment effects: IV -- Marginal treatment effects -- Bayesian treatment effects -- Informed priors.
In: Springer Nature eBookSummary: While there is a substantial literature in labor economics and microeconometrics directed toward endogenous causal effects, causal effects have received relatively limited attention in accounting. This volume builds on econometric foundations, including linear, discrete choice, and nonparametric regression models, to address challenging accounting issues characterized by microeconomic fundamentals and equilibrium reporting choices. Both classical and Bayesian strategies for identifying and estimating accounting treatment effects are discussed extensively. This distinctive resource for researchers and students explores interactions among theory, data, and model specification considerations, and complements contemporary econometrics and statistics, as well as accounting.
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Accounting choice -- Linear models -- Loss functions and estimation -- Discrete choice models -- Nonparametric regression -- Repeated-sampling inference -- Overview of endogeneity -- Treatment effects: ignorability -- Treatment effects: IV -- Marginal treatment effects -- Bayesian treatment effects -- Informed priors.

While there is a substantial literature in labor economics and microeconometrics directed toward endogenous causal effects, causal effects have received relatively limited attention in accounting. This volume builds on econometric foundations, including linear, discrete choice, and nonparametric regression models, to address challenging accounting issues characterized by microeconomic fundamentals and equilibrium reporting choices. Both classical and Bayesian strategies for identifying and estimating accounting treatment effects are discussed extensively. This distinctive resource for researchers and students explores interactions among theory, data, and model specification considerations, and complements contemporary econometrics and statistics, as well as accounting.

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