Course Outline

Topic 1: Basic Growth Facts
i. Growth over the Long Run
ii. Growth since 1960
iii. Data and Measurement Issues iv. Stylized Facts: Then and Now
    a. Kaldor's Original Facts
    b. Per Capita Output Differences
    c. World Income Distribution
    d. Growth Miracles and Disasters
    e. Convergence
    f. Changes across Time
    g. Volatility
Topic 2: Cross-Country Growth Regressions: From Theory to Empirics
i. Neoclassical Model of Growth Dynamics
ii. Transformation of Neoclassical Growth Model into Regression Form
iii. Control Variables and the Neoclassical Model
    a. Beyond the Solow Growth Model
    b. Identification issues
iv. Interpreting Unobserved Heterogeneity
    a. Introducing Regression Errors
    b. Exchangeability
Topic 3: Convergence
i. Convergence as an Economic Concept: Long Run Effects of Initial Conditions
ii. Convergence
    a. Concept and Findings
    b. Problems with Conventional Approaches
iii. Distributional Approaches to Convergence
    a. -Convergence
    b. Density Estimation
    c. Distribution Dynamics
    d. Conceptual Questions
iv. Time Series Approaches to Convergence
    a. Implied Data Assumptions
    b. Links to other Approaches
Topic 4: Constructing and Evaluating Statistical Models of Growth
i. Empirical Work in the Presence of Model Uncertainty
    a. Typology of Model Uncertainty in Growth Models
    b. Model Averaging: Concepts and Implementation
    c. Decision-Theory: Bayes versus Wald
    d. Policy-Relevant Calculations
ii. Parameter Heterogeneity
iii. Nonlinearity
    a. Tree methods
    b. Mixture Methods
    c. Identification Problems
Topic 5: Econometric Issues in Growth Models
i. Time Series Methods
    a. Use in Evaluating Growth Theories
    b. Vector Autoregressions
ii. Panel Data Methods
    a. Fixed and Random Effects
    b. Use in Addressing Parameter Heterogeneity
    c. Limitations
    d. Conceptual Questions
iii. Endogeneity
    a. Structural Solutions
    b. Instrumental Variables
iv. Cross-Section Error Correlation
Topic 6: Econometrics of Interactions
i. Micro Versus Macro Data and Interaction Effects
ii. Statistical Models of Interactions
    a. Linear-In-Means Model
    b. Discrete Choice Model
iii. Typology of Identification Problems: Reflection Problem, Self-Selection and Unobserved Group Characteristics
iv. Conditions for Identification in Linear Model
v. Conditions Identification in Discrete Choice Model
vi. Partial Identification
vii. Application to Social Capital