Individuals in the public and private sectors rely heavily on accounting information during decision-making processes. A field with far-reaching influence, accounting requires users to understand and apply economics, finance, behavioral science, decision theory, and statistical methods. The Accounting curriculum demands interdisciplinary training that prepares individuals to interpret a wide variety of data, design and execute quality research in a specific area, and teach within the accounting discipline. Although broad-based in scope, the Accounting major field area is by nature quantitative. Experience has shown that students with a strong quantitative background enjoy the most success in this area.

Courses taken during the first two years of the program provide a strong research foundation. Finance, mathematics, and probability and statistics courses required by the Accounting area can be used to fulfill the Doctoral Program's overall breadth and research course requirements. The course work helps develop the ability to understand, integrate, and conduct accounting research. Students are required to enroll in Management 229X, 229Y, and 229Z, a workshop series in which leading scholars present papers on issues relevant to the field. Through active participation and intellectual interchange, students develop the ability to critically evaluate current research in accounting. After successful completion of the major field examination, the student must meet the Doctoral Program research paper requirement and then design and execute a dissertation that makes a contribution to the accounting field.

This field is undergoing dramatic, if not revolutionary, changes. Recently, there have been both challenges to the theoretical underpinnings of the discipline and major crises in accounting practices, including issues regarding legal liability and governmental criticism. UCLA Anderson School of Management's Accounting Research Program, which supports doctoral student research assistantships, responds to these challenges by researching and developing new theory and practice in the field. Funded by major accounting firms, the program offers numerous opportunities for students to work with faculty on current research projects.

Doctoral students in Accounting are required to take the following courses:

**Mgmt. 229A - Special Topics in Accounting**

Examination in depth of problems or issues of current concern in accounting, such as application of information economics and principal-agent model to accounting.

**Mgmt. 229B - Empirical Research in Accounting**

Preparation: training in econometrics. Introduction to empirical accounting literature, focusing on role that accounting information plays in formation of capital market prices.

**Mgmt. 229X, 229Y, 229Z - Accounting Workshops**

Intended to develop ability to critically evaluate research in fields relevant to study of accounting. Papers presented in colloquium format by leading scholars in accounting. Active participation and intellectual interchange encouraged through discussion of papers during colloquium.

**Mgmt. 230 - Theory of Finance**

Requisite: course 408. Primary focus on valuation of corporate liabilities and other securities under uncertainty. Capital asset pricing model presented rigorously and compared with more recent theories of asset pricing such as arbitrage pricing theory and option pricing model, using empirical evidence. Secondary focus on analysis of problems in corporate finance such as optimal financing of the corporation and the market for corporate control.

**Econ. 201A, 201B, 201C - Microeconomics**

201A - Theory of the Firm and Consumer. Two input/two output model Walrasian equilibrium and Pareto efficiency. Choice over time - consumer savings and firm investment decisions. Choice under uncertainty - state claims model, asset pricing.

201B - Basic Concepts and Techniques of Noncooperative Game Theory and Information Economics. Nash equilibrium and subgame perfection. Games with incomplete information. Models of strategic market behavior. Screening and signaling. Bargaining models. Theory of the firm.

201C - General Equilibrium and Welfare Economics. Meaning of competition in general equilibrium. Decentralization and appropriation roles of prices. Increasing return. Public goods. Pecuniary and nonpecuniary externalities. Mechanism design.

**Math 115A - Linear Algebra**

Requisite: course 33A. Abstract vector spaces, linear transformations, and matrices; determinants; inner product spaces; eigenvector theory.

**Econ. 203A - Probability and Statistics for Econometrics**

Provides statistical tools necessary to understand econometrics techniques. Random variables, distribution and density functions, sampling, estimators, estimation techniques, hypothesis testing, and statistical inference. Use of econometric problems and examples.

**Econ. 203B - Introduction to Econometrics: Single Equation Models**

Estimation of basic linear regression model, testing hypotheses, generalized least squares, serial correlation, heteroskedasticity, multicollinearity, error-in-variables, distributed lags, qualitative dependent variables, and forecasting.

**Econ. 211A - Economics of Uncertainty, Information, and Games**

(may be substituted for either Econ. 201C or Mgmt. 213C)

Preparation: introductory probability. Requisite: course 201C. Theory of individual decision making under uncertainty, applied to topics such as asset pricing models, adverse selection, moral hazard, bargaining, signaling, auctions, and search.

Recommended electives include the following:

**Mgmt. 239A - Theory of Exchange under Uncertainty**

Requisite: course 230. Foundations of theory of exchange developed as introduction to theoretical literature on pricing or capital assets.

**Mgmt. 239B - Theory of Investment under Uncertainty**

Requisites: courses 230, 239A. Foundations of theory of firm capitalization and investment decisions, with special attention to questions of exchange and allocative efficiency.

**Mgmt. 239C - Empirical Research in Finance**

Preparation: training in econometrics. Requisite: course 230. In-depth study of empirical research in the field of finance, statistical methodologies applied to test market efficiency, and asset pricing theory.

**Econ. 211B - Economics of Uncertainty, Information, and Game**

Preparation: introductory probability. Requisite: course 201C. Theory of individual decision making under uncertainty, applied to topics such as asset pricing models, adverse selection, moral hazard, bargaining, signaling, auctions, and search.

**Econ. 231A - Econometrics: Single Equation Models**

Linear regression model, specification error, functional form, autocorrelation, nonlinear estimation, distributed lags, nonnormality, univariate time series, qualitative dependent variables, aggregation, structural change, and errors-in-variables.

**Econ. 231B - System Models**

Multivariate regression, errors-in-variables, simultaneous equations, identification, proxy variables, latent variables, factor analysis of panel data, asymptotic distribution theory.

**Math 131A, 131B - Analysis**

131A - Requisites: courses 32B, 33B. Rigorous introduction to foundations of real analysis; real numbers, point set topology in Euclidean space, functions, continuity.

131B - Requisites: courses 33B, 115A, 131A. Derivatives, Riemann integral, sequences and series of functions, power series, Fourier series.

**Math 245A - Real Analysis**

Requisites: courses 121, 131A-131B. Basic measure theory. Measure theory on locally compact spaces. Fubini theorem. Elementary aspects of Banach and Hilbert spaces and linear operators. Function spaces. Radon/Nikodym theorem. Fourier transform and Plancherel on Rn and Tn.

**Mgmt. 210B - Applied Stochastic Processes**

Requisite: Mathematics M170A or Electrical Engineering 131A. Fundamentals of stochastic processes, including Poisson processes, renewal theory, and Markov chains. Sequential stochastic (usually Markovian) decision processes in discrete and continuous time. Emphasis on problem formulation and characterization and computations of optimal policies, often via dynamic programming, applications to inventory, queueing, maintenance, reliability, and replacement problems.

For information on admission to the Ph.D. program, please go to http://www.anderson.ucla.edu/degrees/phd/apply.