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Thomas PERNET

About Me

I am a researcher interested in bringing traditional economics methodologies (econometrics & modeling) with data science (machine learning and deep learning). I am primarily researching environmental economics, finance, and international trade, focusing on the Chinese economy. More recently, I opened up my research interest to the concept of ESG (Environmental, Social, and Governance) and its impact on the economy.


Social media & contact info

WeChat: T2488678626
WhatsApp: 07 69 05 89 47
Academic profile

Skills

Research and scientific abilities
Documentation (programming, methodology, analysis)
Ability to express concepts to any audience
Programming language: Python, R, Google Script
Versioning and code collaboration: Github/Gitlab
AWS Cloud computing

Education

PhD in Environmental Economics and Finance, February 2022

I am expecting to graduate from Paris 1 Panthéon-Sorbonne & ENS Cachan in 2022 for my Ph.D. dissertation entitled “Financial misallocation, pollution and environmental policy in China”

Jury
MAUREL Mathilde, Research Director, Centre d'Economie de la Sorbonne CNRS - Université Paris 1 Panthéon-Sorbonne
CHEN Zhao, Deputy director and professor, China Center for Economic Studies (CCES) - Fudan University, Shanghai China Fudan University
PONCET Sandra, Research Director, Centre d'Economie de la Sorbonne CNRS - Université Paris 1 Panthéon-Sorbonne
AUGIER Patricia, University lecturer and researcher, Associate professor - Aix-Marseille Université, Institut universitaire de technologie
MOTEL-COMBES Pascale, Associate professor - CERDI Centre d'Etudes et de Recherches sur le Développement International
FAN Haichao, Associate professor, China Center for Economic Studies (CCES), Fudan University, Shanghai China Fudan Universit

Master (high honors) in International Trade and Development Economic, 2014

I was awarded a research master from Paris 1 Panthéon-Sorbonne & ENS Cachan

Academic Research

New evidence on the soft budget constraint: Chinese environmental policy effectiveness in SOE-dominated cities,
The impact of Corporate Social responsibility on Corporate Financial Performance: A meta-analysis approach, working paper, 2021

Project

In this part, I expose most of the data projects I have conducted over the years. I worked for different industries such as e-commerce, telecom, finance, retail or insurance.

All projects coloured in
blue
refer to business, while those in
green
are academic projects.

All the data pulled to construct the cards display (and subsequently the details) comes from another Coda document that I use to manage the projects. I use different tools like
to track my time,
and
to document and take notes. I use
to centralise and access the information. In the end, the cards display and dashboard are updated automatically using different integration scripts (Python-AWS Lambda or Google Script).

⚠️ To open the project’s detail, click on the card.

Number of projects:
20
TIMELINE
1
FINANCE
8
5-Inspirational-Examples-of-Corporate-Social-Responsibility-in-Marketing.jpeg
Paris 1 Panthéon-sorbonne
3/29/2021
12/5/2021
Is there any statistical relationship between CSR and firm’s performance?
image.png
Critical Future
10/21/2020
6/4/2021
Develop a deep learning algorithm to predict the price of gold and deploy the solution to be fully automated
images.jpeg
Paris 1 Panthéon-sorbonne
10/18/2020
10/15/2021
How a limited access to external finance lead to an increase of firm’s pollution emission in China
download (1).png
Optimum Finance
2/12/2020
11/6/2020
Deploy a system to download UK’s firms financial data (P&N, balance sheet, income statement) and predict the companies with a strong likelihood to use invoice finance
credit-agricole-leasing-factoring.png
Crédit Agricole
2/4/2020
1/4/2021
Build an algorithm to match French open data (INSEE&INPI)
Shanghai.png
Paris 1 Panthéon-sorbonne
8/12/2019
10/17/2021
How the Chinese banking deregulation can help to reduce the firm’s pollution emission
Finance.png
Paris 1 Panthéon Sorbonne
8/12/2019
7/26/2020
How the soft-budget constraint and SOE’s financial favours policy lead to an increase in pollution emission
BPI France
E-COMMERCE
2
000143787_2_mobile.jpeg
Newell
3/25/2021
12/2/2021
Develop a tool to predict Amazon intermittent product demand up to the next year
pic2973872.png
Steamforged
1/5/2020
2/1/2021
Build an tool to pull the data from TradeGecko and display the data through a dashboard
INSURANCE
1
download.png
Degree insurance
3/15/2021
10/7/2021
Predict mu and sigma drawn from a log normal distribution for all university-degree pair (bachelor degree) in the US for the first five year post graduation
TRADE
1
image.png
Paris 1 Panthéon-sorbonne
3/12/2020
11/8/2021
Evaluate the effect of an industrial policy in China on the capacity to engage in product upgrading
RETAIL
2
Calumnet334.png
Calumet
8/6/2021
11/13/2021
Provide a tool to monitor cost variation across all product in the catalogue and predict the price to optimise the pass-through
ecoATM_logo_300px_300x.jpeg
Eco ATM
4/23/2020
12/8/2020
Build a tool to understand the customer journey, more specifically answer the question, “why the customer do not drop its mobile phone against money”
CONFERENCE
2
image.png
Paris 1 Panthéon Sorbonne
9/17/2021
12/4/2021
Organise a conference on sustainable development in partnership with the UN
image.png
Paris 1 Panthéon-sorbonne
2/13/2021
5/21/2021
Organise a conference around the Paris agreement in partnership with the UN
TELECOM
2
download.jpeg
EU networks
9/17/2020
4/7/2021
Create a tool to calculate the financial profitability of all the long haul network in Europe and predict the bandwidth capacity at the end of the year
vodafone.jpeg
Vodafone
9/19/2019
1/24/2020
Build a tool to increase the portfolio penetration rate by highlighting product with potential and connecting sales managers across region
AVIATION
1
1200px-HongKongAirportlogo.svg.png
HK airport
9/3/2019
7/5/2020
Understand the reasons why a Chinese consumer would choose the train over the plain to get to HK
NEW TECHNOLOGY
1
Nubyla
11/20/2021
12/6/2021

Details

Select a project to see the details:
esg_metadata 🐢

The project in numbers

The project began on
3/29/2021
and the last task ended in
12/5/2021
. It lasts
251 days
(
8
months)
Number of unique days worked
:
73
Total hours worked
:
275
Average work per day
:
3.77
Number of tasks:
23
Number of meetings:
18
Number of emails:
196
Number of unique topic:
83
Total cost AWS: $
8.2

MONTH_SUM_DURATION
Total hours work per week
Created with Highcharts 9.3.1MONTHNAMEHOURSMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember0255075100
TOTAL_TIME_PER_WEEK_PROJECT
Total hours work per week
Created with Highcharts 9.3.1DATEWEEKNUMBERHOURSOctoberSeptemberAugustJulyJuneMayAprilMarchNovemberDecember1/34030201348362416440255075
TODOLIST_TASK_DONE
Count tasks achieved per month
Created with Highcharts 9.3.1MONTHNAMENEWUSTITLEJulAugSepOctNov0246810
TODOLIST_TASK_DURATION
Average task duration per month
Created with Highcharts 9.3.1MONTHNAMEDURATIONJulAugSepOctNov0246
DISTRUBTION_TAGS
Total hours by tags, all project
Created with Highcharts 9.3.1#literature-review#prepare-presentat...#empirical-analysis#email#model-estimate#meeting#data-preparation#download-data#documentation#data-transformation#setup-project#prepare-meeting#tutorial#admin#data-analysis#data-exploration#preparation-meeting#medium#paper-writing
DISTRUBTION_DESC
Top ten tasks, hours
Created with Highcharts 9.3.1DESCRIPTIONHOURSUpdate Data prepar...Update Model estim...Standard Describe ...Standard Presentat...Model estimate Est...Standard draw outl...Standard Article M...Standard Document ...create api for gen...Presentation base ...0102030405060
WORLDCLOUD
Most common words across tasks description
Created with Highcharts 9.3.1estimateupdateinformationstandarddatadownloadmodelsigneffectpreparationesgpapersauthorsaddpresentationinstitutionsnewvariablespapermeta-analysisprepareconstructionmethodologytabledocumentdescribesourceseminardesirdrawoutlineempiricalpartcombinejournalsreadmetacreateanalysishighlightcollectsuspiciouscsrmeetingmeta-analysescorporatesocialresponsibility2021taskresultsprojectreplytableserrornormalizespreadsheetapiweeklyprogramextractionbasededonnéesanalysevalueexcelfileversion0102listarticlemediumpolymeranalyticstoolfirstmetadatajournalsusiedraftsign_of_effectfunctionpublication_yearotherssurveytechnologynotebook
AWS_COST
Month AWS EC2 cost
Created with Highcharts 9.3.1MONTHNAMECOSTTOTALMONTHCUMPROJECTAugustSeptemberOctoberNovember02.557.510
GMAIL_EMAIL_OVER_TIME
Number of emails send, stacked by meeting (yellow) vs not meeting (blue)
Created with Highcharts 9.3.1MONTHNAMECLEANSUBJECTfalsetrueJulJunMayAprMarAugSepOctNovDec0204060
GMAIL_TOPIC_MEETING_SCATTER
Relationship between number of emails sent and tasks completed
Created with Highcharts 9.3.1TOTALSUBJECTTOTALTASKCOMPLETEDJulJunMayAprMarAugSepOctNovDec468101214160105
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