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Accounting and Causal Effects:Econometric Challenges
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In this book, we synthesize a rich and vast literature on econometric challenges associated with accounting choices and their causal effects. Identification and esti- mation of endogenous causal effects is particularly challenging as observable data are rarely directly linked to the causal effect of interest. A common strategy is to employ logically consistent probability assessment via Bayes’ theorem to connect observable data to the causal effect of interest. For example, the implications of earnings management as equilibrium reporting behavior is a centerpiece of our explorations. Rather than offering recipes or algorithms, the book surveys our ex- periences with accounting and econometrics. That is, we focus on why rather than how.
The book can be utilized in a variety of venues. On the surface it is geared to- ward graduate studies and surely this is where its roots lie. If we’re serious about our studies, that is, if we tackle interesting and challenging problems, then there is a natural progression. Our research addresses problems that are not well un- derstood then incorporates them throughout our curricula as our understanding improves and to improve our understanding (in other words, learning and cur- riculum development are endogenous). For accounting to be a vibrant academic discipline, we believe it is essential these issues be confronted in the undergrad- uate classroom as well as graduate studies. We hope we’ve made some progress with examples which will encourage these developments. For us, the Tuebingen- style treatment effect examples, initiated by and shared with us by Joel Demski, introduced (to the reader) in chapter 8 and pursued further in chapters 9 and 10 are a natural starting point
Douglas A. Schroeder - Personal Name
1st Edtion
978-1-4419-7224-8
NONE
Accounting and Causal Effects:Econometric Challenges
Economics
English
Springer New York Dordrecht Heidelberg
2010
USA
1-486
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