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

By: Schroeder, Douglas A [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Springer Series in Accounting Scholarship: 5Publisher: New York, NY : Springer New York, 2010Description: XXVI, 462 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9781441972255.Subject(s): Economics | Economics -- Statistics | Econometrics | Auditing | Economics/Management Science | Accounting/Auditing | Econometrics | Statistics for Business/Economics/Mathematical Finance/InsuranceDDC classification: 657 Online resources: Click here to access online
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 eBooksSummary: 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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