Discover and read the best of Twitter Threads about #econometrics
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Hi #EconTwitter!
Interested in the #econometrics of ๐๐๐ฎ๐ฌ๐๐ฅ ๐ข๐ง๐๐๐ซ๐๐ง๐๐? ๐
Here's a thread with some great lecture notes, slides, and books on this topic - freely available on the web - which I've happily tweeted about! ๐๐
Hope you'll find it useful!
Interested in the #econometrics of ๐๐๐ฎ๐ฌ๐๐ฅ ๐ข๐ง๐๐๐ซ๐๐ง๐๐? ๐
Here's a thread with some great lecture notes, slides, and books on this topic - freely available on the web - which I've happily tweeted about! ๐๐
Hope you'll find it useful!
๐๐๐ฎ๐ฅ ๐๐จ๐ฅ๐๐ฌ๐ฆ๐ข๐ญ๐ก-๐๐ข๐ง๐ค๐ก๐๐ฆ'๐ฌ (@paulgp) ๐๐ฉ๐ฉ๐ฅ๐ข๐๐ ๐๐ฆ๐ฉ๐ข๐ซ๐ข๐๐๐ฅ ๐๐๐ญ๐ก๐จ๐๐ฌ
PhD-level slides covering econometrics, ย from causal inference to applied MachineLearning.
github.com/paulgp/appliedโฆ
PhD-level slides covering econometrics, ย from causal inference to applied MachineLearning.
github.com/paulgp/appliedโฆ
๐๐๐ง๐ ๐๐ข๐ง๐ '๐ฌ (@pengding00) ๐๐๐ฎ๐ฌ๐๐ฅ ๐ข๐ง๐๐๐ซ๐๐ง๐๐
Undergrad notes about the #statistics and #econometrics of causal inference.
arxiv.org/abs/2305.18793
Undergrad notes about the #statistics and #econometrics of causal inference.
arxiv.org/abs/2305.18793
New research from Meta highlights the importance of long term advertising effects. Econometric analysis of over 3,500 campaigns reveals that 60% of the payback comes from long term effects, and only 40% from the short term.
#brand
#advertising
#marketing
#econometrics
#brand
#advertising
#marketing
#econometrics
This means that short term measurement measurement systems (which include most digital attribution models) probably underestimate ROI by a factor of ~2.5.
Short term measurement approaches tend to favour direct response channels, but this study shows that brand-building channels actually generate more sales in the long term.
I'm excited about this next session at #ExploreSAS => "Super Demo: The Science Behind the Batting Lab" by @SASsoftware <= #DataLiteracy At Bat
sas.com/gms/redirect.jโฆ
โโ
#SportsAnalytics #BigData #Analytics #AI #MachineLearning #DataScience #SASVisionary #Data4All #Analytics4All
sas.com/gms/redirect.jโฆ
โโ
#SportsAnalytics #BigData #Analytics #AI #MachineLearning #DataScience #SASVisionary #Data4All #Analytics4All
Live session at #ExploreSAS => "Super Demo: The Science Behind the Batting Lab" by Gunce Walton,
Manager for Advanced Analytics R&D at @SASsoftware
โโโโ
#DataLiteracy #SportsAnalytics #BigData #Analytics #AI #MachineLearning #DataScience #SASVisionary #Data4All #Analytics4All
Manager for Advanced Analytics R&D at @SASsoftware
โโโโ
#DataLiteracy #SportsAnalytics #BigData #Analytics #AI #MachineLearning #DataScience #SASVisionary #Data4All #Analytics4All
The Batting Lab Model-building Process uses SAS Econometrics on #SASViya: sas.com/en_us/softwareโฆ by @SASsoftware #ExploreSAS
โโโโ
#MarkovModel #PredictiveAnalytics #SportsAnalytics #BigData #Analytics #AI #MachineLearning #DataScience #SASVisionary
โโโโ
#MarkovModel #PredictiveAnalytics #SportsAnalytics #BigData #Analytics #AI #MachineLearning #DataScience #SASVisionary
MBAs and even DBAs find it very tough to publish in high impact factor journals.
Most of the management teaching done at business schools relies on the case study method.
The staff is not conversant with modern statistical and mathematical methods used for writing research papers
Most of the management teaching done at business schools relies on the case study method.
The staff is not conversant with modern statistical and mathematical methods used for writing research papers
My advice to all management studies/ old business school style professors and adjunct faculty members is that they should do MOOCs.
At their age, they cannot enrol in a hard science degree program.
At their age, they cannot enrol in a hard science degree program.
The most worrying thing that I have come across is that departments where full-time teaching staff cannot publish articles/ monographs in top peer-reviewed journals, start publication services of their own to accommodate failure.
In-house Discussion Papers Journal, etc
Imposters!
In-house Discussion Papers Journal, etc
Imposters!
Does #COVID19 crowd out care for non COVID patients in the #NHS? Has this led to a loss of lives? Are the numbers negligible? The short answers are: yes, yes & no!
Paper โก๏ธ bit.ly/33XMyHB & a long๐งตon how we capture non COVID19 excess deaths & much more โฌ๏ธ 1/n
Paper โก๏ธ bit.ly/33XMyHB & a long๐งตon how we capture non COVID19 excess deaths & much more โฌ๏ธ 1/n
Lets start with a headline result: we estimate that for every 30 #COVID deaths there is at least one avoidable non COVID excess death in ๐ด๓ ง๓ ข๓ ฅ๓ ฎ๓ ง๓ ฟ hospitals. To arrive at this we use cool #NHS data which makes for a great #EconTwitter #econometrics #DataScience teaching example. 2/n
The #NHS has population individual level hospital episode data (HES) linked to death certificates. For each admitted patient, they predict P(Death|X). This is an out-of-sample prediction coming from Lasso logistic regression model trained on data from the last 3 years. 3/n
Economic Schools as paintings:
Classical
Classical
Mercantilism
Marxism
What are new graduates doing to be attractive to banks entry-level analyst programs?
@ABABankers @TheBanker @CIOonline @RiskDotNet @FT
@ABABankers @TheBanker @CIOonline @RiskDotNet @FT
Interesting question.
Banking sector MTO - Management Trainee Officers Program vary from country to country.
In my country Bank Staff Colleges train young graduates to become bankers.
Banking sector MTO - Management Trainee Officers Program vary from country to country.
In my country Bank Staff Colleges train young graduates to become bankers.
The hired graduates have to undergo an intensive training course by attending several In-house boot camps or lecture hall workshops before they are moved into the formal workplace.
How seriously is past volatility a fair estimate of future volatility or risk useful in financial models?
@GARP_Risk
Historical Volatility based on empirical data sample observations.
@GARP_Risk
Historical Volatility based on empirical data sample observations.
Data Sample Observations can be historic baseline data for a particular asset class/exposure or simulated data derived from iterations using some historical data sets.
Another branch of data which can be used to observe future volatility is exploratory data drawn from within a sample or a population using data #visualization tools.
This technique is becoming popular as data science and machine learning advancements are taking place
This technique is becoming popular as data science and machine learning advancements are taking place
Is doing a graduate degree in risk management and insurance worth the money? Why?
@GARP_Risk @actuarynews
@GARP_Risk @actuarynews
Depends!
#riskmanagement is a broad area which can offer various lucrative roles, especially in the financial sector.
They are a lot of risk management degrees available in the market.
Which one would you like to study?
And where it is being offered?
#riskmanagement is a broad area which can offer various lucrative roles, especially in the financial sector.
They are a lot of risk management degrees available in the market.
Which one would you like to study?
And where it is being offered?
If the degree will focus more on Insurance Underwriting Management and related Risk Financing Courses, I won't advise you to do such a qualification.
The scope of such a degree won't go beyond Life and P&C Insurance Firms.
The scope of such a degree won't go beyond Life and P&C Insurance Firms.
I am humbled and privilleged to note that my #Research paper; "Sources of #Unemployment in #Lesotho" is now available and can be accessed via the People's Republic of #China's National #Science and #Technology #Library - #NSTL. I give thanks ๐
So far this year, I have successfully published three #Research articles in #Macroeconomics & #Finance, with another two in press. I am currently hammering away at a handful of working papers which will most certainly find a home in reputable #Journals, come 2021 ๐๐ฝ๐
Im currently internalising the very insightful reviewer comments on my latest #Research paper titled; "Investigating Determinants of Commercial Bank Spreads in #Lesotho", from the good folks over at the globally reputable #International #Journal of #Finance & #Economics #IJFE ๐
If your treatment variable has bunching, this is good news! It may be possible to use this bunching to build a correction for endogeneity. We show how this may be done in our new paper. Follow the thread. #EconTwitter #econometrics 1/
We focus here on bunching at one of the ends of the support, which turns out to be very common. For example, TV watching, enrichment activities, maternal labor supply, smoking amounts, all have bunching at zero, and the list of variables where this happens goes on and on. 2/
Take the amount of time children spend watching TV. You can't watch a negative amount of time. Even if your characteristics would place you as a negative watcher, you will still watch zero, and you will be bunched with all the other extreme people. 3/
You can check our new paper in Environmental and Resource Economics with Pierre Dupraz (@SmartLereco, @INRAE_France) in which we measure the productivity of biodiversity and its interaction with fertilizers and pesticides
link.springer.com/article/10.100โฆ
link.springer.com/article/10.100โฆ
We measure biodiversity using habitat indicators (crop diversity and permanent grassland proportion) and estimate several system of production functions (with +/- detailed specifications) in 1000 farms of northwest France #econometrics
Highlights:
1) crop diversity is an input for cereals & milk
2) permanent grassland is an input for cereals when crop diversity is low
3) crop diversity & permanent grassland can substitute each other
4) they can also substitute with pesticides & fertilizers
1) crop diversity is an input for cereals & milk
2) permanent grassland is an input for cereals when crop diversity is low
3) crop diversity & permanent grassland can substitute each other
4) they can also substitute with pesticides & fertilizers
As a student at MIT, I heard the expression, "The Iron Law of Econometrics," referring to OLS coefficients being biased toward zero, due to measurement error attenuation bias and other data issues. #EconTwitter #Econometrics
1/4
1/4
But who coined the term, "iron law of econometrics?"
Hausman (2001 JEP) says, "At MIT I have called this the 'Iron Law of Econometrics' - the magnitude of the estimate is usually smaller than expected."
This would seem to answer the question...
2/4
Hausman (2001 JEP) says, "At MIT I have called this the 'Iron Law of Econometrics' - the magnitude of the estimate is usually smaller than expected."
This would seem to answer the question...
2/4
However, In a blog post, Mankiw attributes the phrase to Franklin Fisher. But the Fisher and Monz (1991) textbook says that the iron law of econometrics is, "data are never available in the form in which one wishes to use them."
3/4
3/4
Time for another #Econometrics thread!
Today I want to talk about my paper with Jun Zhao (absolutely great PhD candidate from Vanderbilt ), "Doubly robust difference-in-differences estimators", which is now forthcoming at the Journal of Econometrics!
sciencedirect.com/science/articlโฆ
1/n
Today I want to talk about my paper with Jun Zhao (absolutely great PhD candidate from Vanderbilt ), "Doubly robust difference-in-differences estimators", which is now forthcoming at the Journal of Econometrics!
sciencedirect.com/science/articlโฆ
1/n
Before I go on, let me make it clear that everything that I say here or that we proposed in the paper can be easily implemented in #R via the package DRDID: pedrohcgs.github.io/DRDID/
I hope you find this easy to use!
2/n
I hope you find this easy to use!
2/n
Now to the paper. First, why should you pay attention to *another* Difference-in-Differences paper?
I think we propose a cool set of new tools that can be very handy. We talk about robustness, efficiency, and inference.
I'll cover the main points here, one-at-a-time!
3/n
I think we propose a cool set of new tools that can be very handy. We talk about robustness, efficiency, and inference.
I'll cover the main points here, one-at-a-time!
3/n
Here I go, on another #Econometrics related thread.
Today, I want to talk about the "debate" related to health policies, economic growth and the 1918 Spanish flu.
Everything I have to say is here (with codes): pedrohcgs.github.io/posts/Spanish_โฆ
Let's get to it!
1/n
Today, I want to talk about the "debate" related to health policies, economic growth and the 1918 Spanish flu.
Everything I have to say is here (with codes): pedrohcgs.github.io/posts/Spanish_โฆ
Let's get to it!
1/n
Recently, Correia, Luck and Verner (2020) (CLV) put forward a very interesting paper that, among other things, analyze whether non-pharmaceutical interventions helped mitigate the adverse economic effects of the 1918 Spanish Flu pandemic on economic growth.
2/n
2/n
CLV find suggestive evidence that NPIs mitigate the adverse economic consequences of a pandemic.
Although today's society has a different structure from 100 years ago, these findings can help shape the current debate about covid policies.
3/n
Although today's society has a different structure from 100 years ago, these findings can help shape the current debate about covid policies.
3/n
I am excited to share my first working paper! @PHuenermund and I address why the interpretation of control variables in regression analysis should be avoided.
โOn the Nuisance of Control variables in Regression Analysisโ
arxiv.org/abs/2005.10314
#econometrics #causalinference /1
โOn the Nuisance of Control variables in Regression Analysisโ
arxiv.org/abs/2005.10314
#econometrics #causalinference /1
2/The interpretation of control variables is widespread within our research field. We checked the last five years of SMJ issues and found that 47% of papers that use parametric regression models with control variables also interpret or mention the results of their controls.
3/ We argue that this practice should be avoided because control variable estimates are unlikely to have causal interpretation themselves.
Happy 4th of July!!
One area of intergration of ML and econometrics is providing inference after variable selection (Post selection Inference) #rstats #econtwitter #Rladies #ML #econometrics 1/n
One area of intergration of ML and econometrics is providing inference after variable selection (Post selection Inference) #rstats #econtwitter #Rladies #ML #econometrics 1/n
Most popular technique in economics is the 'Double LASSO' which provides inference on the treatment effect after variable selection using LASSO. Check out the R package 'hdm'. cran.r-project.org/web/packages/hโฆ
#rstats #econtwitter 2/n
#rstats #econtwitter 2/n
We are often interested in conducting inference on other selected covariates (controls) as well. Check out R package 'selectiveInference' which conducts inference on multiple covariates. cran.r-project.org/web/packages/sโฆ
#rstats #econtwitter 3/n
#rstats #econtwitter 3/n
#Bigdata vs Machine Learning vs Artificial Intelligence
By Irene Aldridge
โ๏ธauthor High-Frequency Trading: A Practical Guide to #Algorithmic Strategies& #Trading Systems
โ๏ธco-author Real-Time Risk: What Investors Should Know About #Fintech,#highfrequencytrading and FlashCrashes
By Irene Aldridge
โ๏ธauthor High-Frequency Trading: A Practical Guide to #Algorithmic Strategies& #Trading Systems
โ๏ธco-author Real-Time Risk: What Investors Should Know About #Fintech,#highfrequencytrading and FlashCrashes
1. โ๏ธ๐งโฟ๐ข In traditional #statistics or #econometrics, researchers make assumptions about #data distributions ahead of the analysis
2. ๐ฅ๐ช#machinelearning = the 1st discipline to apply #efficiency to #problemsolving brought by #computers & their enhanced computational power
2. ๐ฅ๐ช#machinelearning = the 1st discipline to apply #efficiency to #problemsolving brought by #computers & their enhanced computational power
3. ๐คโฟ๐ข#ML scientists try to reduce #assumptions about the data as much as possible&let the data (&computers) decide what fits best.
4. โพโก๏ธ๐ค๐#Datascience identifies core characteristics of the data, summarized by what has been known as #characteristic values (#eigenvalues)
4. โพโก๏ธ๐ค๐#Datascience identifies core characteristics of the data, summarized by what has been known as #characteristic values (#eigenvalues)
