Quantitative Analysis of Cross Section Data

 Many decisions in economics, business and government hinge on understanding relationships among variables in the world around us and these decisions require quantitative answers to quantitative questions (Stock and Watson; 2008). Econometric modeling pertains to the application of statistical methods and models in economic and business phenomenon with the purpose of giving empirical content to economic theories. In order to explain the relationship between variables of interest in an economic system, statistical models are employed that enable the generation of forecasts, which, in turn, assist firms, consumers, government planners, and other decision makers in modifying likely outcomes. This course discusses various tools and techniques of quantitative data analysis, especially the linear regression model, binary dependent variable model, corresponding  statistics and tests, various model selection criteria, model diagnostics, and interpretations of outputs from statistical software STATA. Course methodology includes lectures, discussions of case applications and workshops/hands on exercises. What will participants gain? The objectives of this course are for participants to learn and apply the different multivariate techniques commonly used in analyzing cross-section and for the participants to extract useful information for strategy and policy formulation. Who can participate? The target group of this course includes those who work with cross-sectional from household or individual surveys---for example, those who conduct market surveys and analyse them, researchers (e.g. market research agencies), government workers (e.g DBM, DSWD, DOH, NEDA), members of the academic community, private institutions and Non-Government Organizations (NGOs) who work with social survey data and analyse them or researchers who are interested in statistical analysis of real data for policy formulation and evaluation. Course Coverage Introduction to the Econometric Process Structure of Economic Data Regression Analysis Different Functional Forms Important Statistics and Tests Introduction to STATA Use of Indicator Variables in the Regression Analysis Diagnostic Procedures in Regression Analysis Problems of Endogeneity in Econometric Models Use of Instrumental Variable Conditions for Instruments (Relevance and Exogeneity) Two-Stage Least Squares Test for Endogeneity Introduction to Discrete Response Variable Models Linear Probability Model PROBIT and LOGIT Models Applications of Models using Cross Section Data Course Duration: 4 days Registration: To register and further inquiry, please contact the Training Division at Telefax Nos. (632) 436-1426/929-7543 or email it to japebenito@srtc.gov.ph. .