Economics & New technologies

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Economics & new technologies

Objectives

The use of new technology broaden the scope of economics analysis, and allow the practitioner to elaborate different strategies.

Therefore, I had in mind to do a presentation in order to show how we can leverage technology to get the best of the data. The presentation is not meant to learn how to code, instead, to see the possibilities with the new technologies.

In the presentation, you will see:

How to use an API to get more and accurate information: example from

Semantic Scholar⁠

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How to use Deep Learning to create new features:

LSTM architecture⁠

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How to convert text into

word embedding⁠

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How to extract verbs, nouns and adjectives in a document:

NLTK⁠

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How to leverage state-of-the-art

Pre-trained Classification Model⁠

to predict sentiment from a document

How to convert

table⁠

in a PDF into a dataframe

Search data with

Polymer⁠

⁠

Tool:

Python

Requirement

There is no prior requirement. The basic idea behind the presentation is to see somehow what can be done using new tools and how an economist can borrow techniques from the data science world.

Registration

if you are interested to participate in the presentation, fill the information below

5 participants minimum to open the presentation

Current number of participants:

5

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if you have any question, feel free to contact me:

t.pernetcoudrier@gmail.com⁠

To share the document, use this link:

https://coda.io/@thomas-pernet/economics-new-technologies⁠

⁠

Details

The presentation will use a recent research I’m doing about “Environmental, Social, and Governance”

The workflow is the following:

Download data and predict gender

Flag ESG papers

Compute sentiment and cluster papers using the abstract

Compute ESG expertise score

Combine all information

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I wrote a post on Medium about the data pipeline. The post is available here:

Environmental, Social, and Governance and Financial performance: introduction to data construction with Semantic Scholar⁠

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and the Jupyter Notebook is available in this URL:

00_meta_analysis.html⁠

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To see my data science project portfolio, check this link:

https://coda.io/@thomas-pernet/thomas-portfolio⁠

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