|London||UK »||Dec 2014 »||Stata »||Intro »|
Econometrics Basics using Stata
17-18 December 2014
Cass Business School, City University London, UK (View map)
General Econometrics & Statistics (Introductory)
Erin Hengel, University of Cambridge (View profile)
|Overview||Agenda||Prerequisites||Testimonials||Prices||Registration||Terms & Conditions|
Timberlake Consultants invite you to attend the following two day course to be held at Cass Business School, London, UK on 17-18 December 2014. The course will be delivered interactively using Stata 13.
Stata is a powerful statistical software package that provides a broad range of sophisticated tools to conduct advanced econometric analysis, manipulate large datasets and create publication quality tables and graphics. This 2-day course introduces participants to many of Stata’s features for managing data, manipulating variables, repeating tasks and conducting statistical analysis. Each session is accompanied by extensive notes, numerous exercises and several practical examples derived from actual data.
The course is highly interactive: participants are encouraged to implement commands as they are being taught, and particular emphasis is made on using data to transform theoretical concepts into real-world problems. Afterwards, participants should be well equipped to use Stata to conduct basic statistical inference on their own data and pursue more advanced econometric topics, including time-series and panel data.
The course is designed for new Stata users and those with no more than a basic understanding of econometrics. There are no prerequisites beyond a desire to learn both.
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Day 1: Stata Fundamentals
The first day provides a flexible and comprehensive introduction to Stata, the powerful, sophisticated and constantly evolving statistical software. Taking a “learning-by-doing” approach, it aims to turn novice users into confident ones employing plenty of examples and a constant stream of challenging exercises. Given Stata’s scope -- there are thousands of available commands -- the course concentrates on understanding basic syntax and deciphering Stata’s extensive and coherent (yet underrated) help files and documentation. Participants leave with the know-how and courage to independently solve their own statistical puzzles.
Since no two students have the same experience and individuals learn different subjects at different speeds, the course is highly flexible: the agenda emerges dynamically and depends on the group’s prior background and knowledge of Stata. By the end of the course, however, all participants will feel comfortable undertaking the following tasks:
- Opening, browsing, saving and importing datasets;
- Renaming, labelling, ordering and creating data;
- Summarising data;
- Creating basic tables and graphs;
- Automating tasks with do-files.
Having mastered the basics (and time permitting), the course then turns to more sophisticated topics. To ensure they match actual need, participants are encouraged to discuss their own real world data issues. Remaining time is spent introducing commands and concepts which resolve these problems, e.g., advanced data transformations, creating publication quality tables and basic looping structures.
Day 2: Regression Analysis
Day 2 considers the economic and econometric models underpinning statistical analysis in Stata. Our point of departure are the distinctions between conditional and unconditional inference and between correlation and causality. We then discuss ordinary least squares (OLS) and the Gauss Markov (GM) assumptions, which determine whether OLS is, indeed, the best linear unbiased estimator.
We turn next to testing for violations of the GM assumptions and conducting statistical inference. This involves an understanding of regression parameters, standard errors and measures of fit. We also examine tests of functional form and residual normality.
The day concludes by illustrating how the presence of endogeneity precludes causal inference with the OLS regression model. This last section concentrates on the sources of endogeneity, seeing first-hand its impact using example data, and, time permitting, the genius -- and danger -- of employing instrumental variables to correct for it.
As per Day 1, the speed with which the topics are covered and exact scope of material taught emerge dynamically and depend on the group’s past econometric experience. Nonetheless, by the end of Day 2, all participants will feel comfortable:
- Distinguishing causation from correlation;
- Knowing when, and when not, to use the OLS estimator;
- Using Stata’s regress command;
- Interpreting Stata’s regression output;
- Determining when endogeneity is likely present.
Estimating a linear regression model in Stata is almost effortless. The tricky part is understanding exactly when and why such a model is appropriate. Day 2 illustrates this both theoretically and practically using empirical examples in Stata. Afterwards, participants applying OLS to their own data should feel confident in their choice of estimator and the statistical inference it implies.
This course has a learning ratio of approximately 80% practical to 20% theory.
- Angrist, J., and Pischke, J.-S., (2008). Mostly Harmless Econometrics: An Empiricists Companion, Princeton University Press.
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No prior knowledge of Stata is needed. Basic statistics knowledge is required.
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Cost (per participant):
|Registration type||Price (inc. VAT)|
|Commercial / Government||£840.00|
|Academic / Non-profit research||£600.00|
|Click here for Pricing FAQs »|
- Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrolment).
- Additional discounts are available for multiple registrations.
- Cost includes course materials, lunch and refreshments.
- Delegates are provided with temporary licences for the software(s) used in the course and will be instructed to download and install the software prior to the start of the course. (Alternatively, we can also provide laptops free of charge to attending delegates).
- If you need assistance in locating hotel accommodation in the region, please notify us at the time of booking.
The number of delegates is restricted. Please register early to guarantee your place.
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We welcome delegates to find out more and register for the course by contacting our sales and training team either by email: email@example.com, phone: +44 (0) 20 8697 3377 or by filling out an online registration form.
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For full Training Courses Terms & Conditions please click here.
Payment of course fees required prior to the course start date.
Registration closes 5-calendar days prior to the start of the course.
- 100% fee returned for cancellations made over 28-calendar days prior to start of the course.
- 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
- No fee returned for cancellations made less than 14-calendar days prior to the start of the course.
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