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Presents a three-legged econometric strategy of theory, data, and model specification, as applied to accounting research and analysis
Synthesizes linear, nonlinear, and Bayesian models and their implications for causal effects
Can be adapted for graduate/doctoral courses in accounting research and methodology, econometrics, and statistics
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.