Ramu Ramanathan Author of Introductory Econometrics with Applications Eric Zivot F Savery Hall This course is a continuation of Econ Econometric Theory I and covers a number of topics in econometrics including maximum likelihood estimation, nonlinear least squares and nonlinear optimization, multivariate regression, simultaneous equations models, dynamic regression models, and limited dependent variables models. This course will stress models and methods over proofs for proofs etc. We will spend a great deal of time on the computer doing applied econometrics and we will use the econometrics program EVIEWS for most of our assignments. There will be Friday discussion sessions with the teaching assistant, Clarisse Messemer. Traditionally, computer and software applications have been used by economists to off-load otherwise complex or tedious tasks onto technology, freeing up time and intellect to address other, intellectually more rewarding, aspects of research. On the negative side, this increasing dependence on computers has resulted in research that has become increasingly difficult to replicate.

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Working through Intro. Econometrics with Applications was learning what all the math based stats in grad school, but actually understanding it. And the computer package Gretl makes the learning interactive. And his example applications do not stop at working through methodology.

He uses the computer output to build intuition, asking the question of why this variable is what it is, or why two models are different. The use of Gretl enhances this. The scripts and data sets make it easy to see the examples at work, but also make it very easy to explore. I found myself running the scripts, then exploring the data sets in Gretl to further analysis, and building my understanding.

The mathematical derivations are there, but having both the theory and the computer outputs for discussion make for a good match. The book datasets and examples are bundled into the econometrics package Gretl, which is an open source program available for Windows, Mac, Linux. And more flexible then the menu based packages like Minitab or Excel based statistical packages. Great for programming, but harder for exploring data to the neophyte. I think that texts like this that are integrated with a full fledged statistics package as opposed to purely math or a demo version make the learning and applying of statistics different.

The chapter summaries become short forms of methodology as opposed to formula with the assumptions that the various methods repeated as well. I found this to be a particularly effective format for a first book on a subject assumes a first sequence in undergrad statistics has been completed.

As I do this, I am learning a lot about analysis, that is going to inform a project I am starting up. That is probably the best testimony for a book of this type.


Introductory Econometrics With Applications

Dailrajas Garima marked it as to-read Dec 04, Papusson marked it as to-read Aug 27, By including background information on mathematics, probability, statistics, and software applications, readers have all the information they need in one place. Isabella rated it really liked it May 29, Aaa added it Mar 08, He uses the computer output to build intuition, asking the question of why this variable is what it is, or why two models introductody different. Kshitij added it Mar 20, Dan Hilderman rated it liked it Nov 17, He uses a logical step-by-step approach to walk students through numerous real-world examples of model Introductory Econometrics with Applications offers an ideal combination of econometric theory and hands-on practical training for undergraduate and graduate courses. Amazon Rapids Fun stories for kids on the go. This book is absoulutely awful, it caused me to fail my first exam in my college carreer, Ramanathan is incable of clarifying anything, the book is really vague. See 1 question about Introductory Econometrics with Applications….


Ramanathan introductory econometrics with applications pdf





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