Quantitative Research Methods

Description

Research designs and quantitative methods
The topics below outline the range of methods and research designs covered in the course. Not all topics will be treated with the same level of depth or intensity. The emphasis placed on particular topics will depend, in part, on students’ interests and preferences, as well as their relevance to the research questions addressed in the course.
 

• Hypothesis testing and statistical inference: conceptual foundations, Type I and Type II errors, sampling distributions, statistical power

• Revision of the linear regression model: least-squares estimation, inference, and bootstrap methods

• Multiple regression as a modeling framework: interactions (moderation), recursive systems of equations (mediation), and moderated mediation, with bootstrap inference on indirect effects

• Estimation principles beyond least squares: maximum likelihood and the generalized method of moments (location, scale and regression parameters; overidentification tests)

• Causal identification with observational data: endogeneity, instrumental variables, two-stage least squares, tests for weak instruments

• Model specification and functional form: non-linear least squares, polynomial adjustment, kernel regression, splines

• Flexible treatment of control variables: semi-parametric (partially linear) regression, fractional polynomials, Yatchew and Robinson estimators

• Data quality, outliers, and measurement issues: robust regression (M-, S- and MM-estimators)

• Qualitative outcomes in management research: binary, ordered and unordered polychotomous models, count data, marginal effects

• Limited dependent variables and sample selection: censoring, selection models, treatment effects, marginal effects

• Longitudinal and multilevel designs: panel data, pooled, fixed and random effects, dynamic models, conditional fixed-effects logit

• Experimental and quasi-experimental research: difference-in-differences and related policy-evaluation designs

• Time series in management research: stationarity, stationarity tests, cointegration

3 ECTS

Prof. Vincenzo Verardi

See the full course description here