Sunday - Wednesday - 8:00 - 17:00, Thursday - 8:00 - 15:30

SEFB : ECONOMETRIC WORKSHOP SERIES 1

Calendar
ARIBF Events and Activities
Date
8:30 am 03.30.2020 - 2:00 pm 03.31.2020

Description

ECONOMETRIC ANALYSIS OF CROSS SECTIONAL DATA USING STATA

DATE : 30 & 31 MARCH 2020
VENUE: SEFB SEMINAR HALL, LEVEL 3, ECONOMICS BUILDING
TIME: 8.30 AM– 2.00 PM

Stata is powerful tool for researcher in applied economics. Stata can help us to analyze research easily and efficiently – no matter what kind of data you are working with – whether time-series, cross-section or panel data. Stata gives us the tool we need to organized and managed our data and then to obtained and analyze statistical results. For many users, Stata is a statistical package with menus that allow users to read data, generate new variables, compute statistical analysesand draw graphs. To others, Stata is commands line-driven package, commonly executed from a do-files of stored command that will perform all the steps above without interventions. Some consider Stata to be a programme language for developing ado-files that define programs or new Stata commands that extend Stata by adding data-management, statistics, or graphics capabilities.
This course reviews some methods in cross-section data, especially how we handles the data with some special commands in Stata and how to analyze the results from Stata. The course covers methods for data management, estimation, model selection, hypothesis testing and interpretation.
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1. Introduction: Data set
• Getting started.
• Load data from Excel.
• Command: describe; summarize
• Data transformation


2. Linear Regression
• Interpreting regression estimates
• ANOVA table
• Recovering Estimation Results
• Diagnostic Test
• Hypothesis Tests
• Prediction
3. Instrumental Variable (IV) and Two-Stage Least Squares (2SLS)
• Introduction to IV
• IV regression
• 2SLS regression
• Simultaneous Equations Model
• Test on validity of IV

3 Method of Moments (MM) and Generalized Method of Moments (GMM)
• OLS and MM Estimation
• IV and GMM Estimation
• The Weight Matrix and Two-Step GMM Estimation
• Exponential (Poisson) Regression Models
• Miss-specification GMM : Hansen-J Test

4 Regression Models for Categorical Dependent Variable
• The Linear Probability Model
• Logistic Regression Estimation
• Logistic Regression Diagnostic
• Likelihood-ratio Test
• Refined Models

 

Flyer Econometric workshop

Where to find us?


Economic & Financial Policy Institute (ECoFI)
School of Economic, Finance & Banking,
Universiti Utara Malaysia,
06010 Sintok,
Kedah Darul Aman, Malaysia

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