How to find the causality of a periodic behaviour The 2019 Stack Overflow Developer Survey Results Are In Announcing the arrival of Valued Associate #679: Cesar Manara Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern)Showing probable causalityCovariance for periodic weakly stationary processLogistic functions - how to find the growth rateHow to find the Autocorrelation function and CovarainceCausality MA(1) processDetecting periodic patterns in data - how often are the meetings held?How do I find the missing sample points with the Mean and Sample Standard Deviation?How do correlation and causality effect this scenario?How to approach a regular unevenly-spaced time series?How to find the point estimate for a question with given mean and s.d.
He got a vote 80% that of Emmanuel Macron’s
Does Parliament need to approve the new Brexit delay to 31 October 2019?
Why is superheterodyning better than direct conversion?
The following signatures were invalid: EXPKEYSIG 1397BC53640DB551
Simulating Exploding Dice
I could not break this equation. Please help me
Do warforged have souls?
How do you keep chess fun when your opponent constantly beats you?
Searching for a differential characteristic (differential cryptanalysis)
Typeface like Times New Roman but with "tied" percent sign
Create an outline of font
How can I define good in a religion that claims no moral authority?
Change bounding box of math glyphs in LuaTeX
What is this lever in Argentinian toilets?
In horse breeding, what is the female equivalent of putting a horse out "to stud"?
What do you call a plan that's an alternative plan in case your initial plan fails?
Segmentation fault output is suppressed when piping stdin into a function. Why?
Road tyres vs "Street" tyres for charity ride on MTB Tandem
Scientific Reports - Significant Figures
How do I add random spotting to the same face in cycles?
system() function string length limit
Can smartphones with the same camera sensor have different image quality?
Wall plug outlet change
How should I replace vector<uint8_t>::const_iterator in an API?
How to find the causality of a periodic behaviour
The 2019 Stack Overflow Developer Survey Results Are In
Announcing the arrival of Valued Associate #679: Cesar Manara
Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern)Showing probable causalityCovariance for periodic weakly stationary processLogistic functions - how to find the growth rateHow to find the Autocorrelation function and CovarainceCausality MA(1) processDetecting periodic patterns in data - how often are the meetings held?How do I find the missing sample points with the Mean and Sample Standard Deviation?How do correlation and causality effect this scenario?How to approach a regular unevenly-spaced time series?How to find the point estimate for a question with given mean and s.d.
$begingroup$
If you use Google Trends (a tool to illustrate the frequency of search terms) and search for the word "war" with USA as geographic region, you will be presented with the graph below showing monthly data from 2004 - 2019 (I have added the dates for emphasis);
The trend appears to be very periodic, on the same scale as "job," which economists will often say is closely related to the annual economic cycle of employment. As can be seen in the graph below;
However, if you search for the word "peace," there is no such periodicity;
If you change the region to another English speaking country such as the United Kingdom, the periodicity of "war" is still somewhat present but less pronounced, appears to be decaying and is instead shifted to peak around September - November.
What would be an efficient way, from a statistical point of view, to determine what is the cause to the periodicity of "war" in the region of USA?
Since correlation does not imply causation, I don't know how to effectively tackle this problem mathematically. Any ideas/approaches would be much appreciated!
statistics data-analysis time-series
asked Mar 30 at 14:43
litmuslitmus
309318
$endgroup$
add a comment |
$begingroup$
If you use Google Trends (a tool to illustrate the frequency of search terms) and search for the word "war" with USA as geographic region, you will be presented with the graph below showing monthly data from 2004 - 2019 (I have added the dates for emphasis);
The trend appears to be very periodic, on the same scale as "job," which economists will often say is closely related to the annual economic cycle of employment. As can be seen in the graph below;
However, if you search for the word "peace," there is no such periodicity;
If you change the region to another English speaking country such as the United Kingdom, the periodicity of "war" is still somewhat present but less pronounced, appears to be decaying and is instead shifted to peak around September - November.
What would be an efficient way, from a statistical point of view, to determine what is the cause to the periodicity of "war" in the region of USA?
Since correlation does not imply causation, I don't know how to effectively tackle this problem mathematically. Any ideas/approaches would be much appreciated!
statistics data-analysis time-series
asked Mar 30 at 14:43
litmuslitmus
309318
$endgroup$
$begingroup$
It's monthly data, ranging from 2004 - 2019
$endgroup$
– litmus
Mar 30 at 14:46
$begingroup$
I see, I misunderstood the labels (and didn't look at the axes).
$endgroup$
– Servaes
Mar 30 at 14:47
$begingroup$
No worries, I've edited the question to make it more clear
$endgroup$
– litmus
Mar 30 at 14:48
add a comment |
$begingroup$
If you use Google Trends (a tool to illustrate the frequency of search terms) and search for the word "war" with USA as geographic region, you will be presented with the graph below showing monthly data from 2004 - 2019 (I have added the dates for emphasis);
The trend appears to be very periodic, on the same scale as "job," which economists will often say is closely related to the annual economic cycle of employment. As can be seen in the graph below;
However, if you search for the word "peace," there is no such periodicity;
If you change the region to another English speaking country such as the United Kingdom, the periodicity of "war" is still somewhat present but less pronounced, appears to be decaying and is instead shifted to peak around September - November.
What would be an efficient way, from a statistical point of view, to determine what is the cause to the periodicity of "war" in the region of USA?
Since correlation does not imply causation, I don't know how to effectively tackle this problem mathematically. Any ideas/approaches would be much appreciated!
statistics data-analysis time-series
asked Mar 30 at 14:43
litmuslitmus
309318
$endgroup$
If you use Google Trends (a tool to illustrate the frequency of search terms) and search for the word "war" with USA as geographic region, you will be presented with the graph below showing monthly data from 2004 - 2019 (I have added the dates for emphasis);
The trend appears to be very periodic, on the same scale as "job," which economists will often say is closely related to the annual economic cycle of employment. As can be seen in the graph below;
However, if you search for the word "peace," there is no such periodicity;
If you change the region to another English speaking country such as the United Kingdom, the periodicity of "war" is still somewhat present but less pronounced, appears to be decaying and is instead shifted to peak around September - November.
What would be an efficient way, from a statistical point of view, to determine what is the cause to the periodicity of "war" in the region of USA?
Since correlation does not imply causation, I don't know how to effectively tackle this problem mathematically. Any ideas/approaches would be much appreciated!
statistics data-analysis time-series
statistics data-analysis time-series
asked Mar 30 at 14:43
litmuslitmus
309318
asked Mar 30 at 14:43
litmuslitmus
309318
edited Mar 30 at 15:11
litmus
asked Mar 30 at 14:43
litmuslitmus
309318
asked Mar 30 at 14:43
litmuslitmus
309318
asked Mar 30 at 14:43
litmuslitmus
309318
309318
$begingroup$
It's monthly data, ranging from 2004 - 2019
$endgroup$
– litmus
Mar 30 at 14:46
$begingroup$
I see, I misunderstood the labels (and didn't look at the axes).
$endgroup$
– Servaes
Mar 30 at 14:47
$begingroup$
No worries, I've edited the question to make it more clear
$endgroup$
– litmus
Mar 30 at 14:48
add a comment |
$begingroup$
It's monthly data, ranging from 2004 - 2019
$endgroup$
– litmus
Mar 30 at 14:46
$begingroup$
I see, I misunderstood the labels (and didn't look at the axes).
$endgroup$
– Servaes
Mar 30 at 14:47
$begingroup$
No worries, I've edited the question to make it more clear
$endgroup$
– litmus
Mar 30 at 14:48
$begingroup$
It's monthly data, ranging from 2004 - 2019
$endgroup$
– litmus
Mar 30 at 14:46
$begingroup$
It's monthly data, ranging from 2004 - 2019
$endgroup$
– litmus
Mar 30 at 14:46
$begingroup$
I see, I misunderstood the labels (and didn't look at the axes).
$endgroup$
– Servaes
Mar 30 at 14:47
$begingroup$
I see, I misunderstood the labels (and didn't look at the axes).
$endgroup$
– Servaes
Mar 30 at 14:47
$begingroup$
No worries, I've edited the question to make it more clear
$endgroup$
– litmus
Mar 30 at 14:48
$begingroup$
No worries, I've edited the question to make it more clear
$endgroup$
– litmus
Mar 30 at 14:48
add a comment |
1 Answer
1
active
oldest
votes
$begingroup$
In economics/econometrics there are some approaches to establish causality, but all of these approaches require you to have an idea/hypothesis about what a potential cause is (and to get data on them). It seems to me you are not there yet, so that's the first step: Get some ideas of potential causes.
Then, correlation does not imply causation, but causation does imply correlation. So in a first test you could check your potential causes against the data. Say there is a TV series in the US with the name "war" in it. Check the broadcasting dates and compare them to the spikes in the google trend data. If there is a correlation you passed the first test. To really nail a causal relationship you will have to do more, of course, but this might get you pretty far. If there is no correlation then the candidate is not the cause.
To efficiently do this step, you could export the google trends data and get time series for all of the potential causes. Then run a time series multiple regression, or some Granger causality tests, to help you quickly determine which among the potential causes have explanatory power (i.e., are correlated). Again, while this does not necessarily establish causation, it helps you rule out many potentials and narrow down the list.
answered Apr 8 at 13:10
NamelessNameless
2,7531333
$endgroup$
add a comment |
Your Answer
StackExchange.ready(function()
var channelOptions =
tags: "".split(" "),
id: "69"
;
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function()
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled)
StackExchange.using("snippets", function()
createEditor();
);
else
createEditor();
);
function createEditor()
StackExchange.prepareEditor(
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
bindNavPrevention: true,
postfix: "",
imageUploader:
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
,
noCode: true, onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
);
);
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function ()
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3168356%2fhow-to-find-the-causality-of-a-periodic-behaviour%23new-answer', 'question_page');
);
Post as a guest
Required, but never shown
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
In economics/econometrics there are some approaches to establish causality, but all of these approaches require you to have an idea/hypothesis about what a potential cause is (and to get data on them). It seems to me you are not there yet, so that's the first step: Get some ideas of potential causes.
Then, correlation does not imply causation, but causation does imply correlation. So in a first test you could check your potential causes against the data. Say there is a TV series in the US with the name "war" in it. Check the broadcasting dates and compare them to the spikes in the google trend data. If there is a correlation you passed the first test. To really nail a causal relationship you will have to do more, of course, but this might get you pretty far. If there is no correlation then the candidate is not the cause.
To efficiently do this step, you could export the google trends data and get time series for all of the potential causes. Then run a time series multiple regression, or some Granger causality tests, to help you quickly determine which among the potential causes have explanatory power (i.e., are correlated). Again, while this does not necessarily establish causation, it helps you rule out many potentials and narrow down the list.
answered Apr 8 at 13:10
NamelessNameless
2,7531333
$endgroup$
add a comment |
$begingroup$
In economics/econometrics there are some approaches to establish causality, but all of these approaches require you to have an idea/hypothesis about what a potential cause is (and to get data on them). It seems to me you are not there yet, so that's the first step: Get some ideas of potential causes.
Then, correlation does not imply causation, but causation does imply correlation. So in a first test you could check your potential causes against the data. Say there is a TV series in the US with the name "war" in it. Check the broadcasting dates and compare them to the spikes in the google trend data. If there is a correlation you passed the first test. To really nail a causal relationship you will have to do more, of course, but this might get you pretty far. If there is no correlation then the candidate is not the cause.
To efficiently do this step, you could export the google trends data and get time series for all of the potential causes. Then run a time series multiple regression, or some Granger causality tests, to help you quickly determine which among the potential causes have explanatory power (i.e., are correlated). Again, while this does not necessarily establish causation, it helps you rule out many potentials and narrow down the list.
answered Apr 8 at 13:10
NamelessNameless
2,7531333
$endgroup$
add a comment |
$begingroup$
In economics/econometrics there are some approaches to establish causality, but all of these approaches require you to have an idea/hypothesis about what a potential cause is (and to get data on them). It seems to me you are not there yet, so that's the first step: Get some ideas of potential causes.
Then, correlation does not imply causation, but causation does imply correlation. So in a first test you could check your potential causes against the data. Say there is a TV series in the US with the name "war" in it. Check the broadcasting dates and compare them to the spikes in the google trend data. If there is a correlation you passed the first test. To really nail a causal relationship you will have to do more, of course, but this might get you pretty far. If there is no correlation then the candidate is not the cause.
To efficiently do this step, you could export the google trends data and get time series for all of the potential causes. Then run a time series multiple regression, or some Granger causality tests, to help you quickly determine which among the potential causes have explanatory power (i.e., are correlated). Again, while this does not necessarily establish causation, it helps you rule out many potentials and narrow down the list.
answered Apr 8 at 13:10
NamelessNameless
2,7531333
$endgroup$
In economics/econometrics there are some approaches to establish causality, but all of these approaches require you to have an idea/hypothesis about what a potential cause is (and to get data on them). It seems to me you are not there yet, so that's the first step: Get some ideas of potential causes.
Then, correlation does not imply causation, but causation does imply correlation. So in a first test you could check your potential causes against the data. Say there is a TV series in the US with the name "war" in it. Check the broadcasting dates and compare them to the spikes in the google trend data. If there is a correlation you passed the first test. To really nail a causal relationship you will have to do more, of course, but this might get you pretty far. If there is no correlation then the candidate is not the cause.
To efficiently do this step, you could export the google trends data and get time series for all of the potential causes. Then run a time series multiple regression, or some Granger causality tests, to help you quickly determine which among the potential causes have explanatory power (i.e., are correlated). Again, while this does not necessarily establish causation, it helps you rule out many potentials and narrow down the list.
answered Apr 8 at 13:10
NamelessNameless
2,7531333
edited Apr 9 at 12:15
answered Apr 8 at 13:10
NamelessNameless
2,7531333
answered Apr 8 at 13:10
NamelessNameless
2,7531333
answered Apr 8 at 13:10
NamelessNameless
2,7531333
2,7531333
add a comment |
add a comment |
Thanks for contributing an answer to Mathematics Stack Exchange!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
Use MathJax to format equations. MathJax reference.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function ()
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3168356%2fhow-to-find-the-causality-of-a-periodic-behaviour%23new-answer', 'question_page');
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
$begingroup$
It's monthly data, ranging from 2004 - 2019
$endgroup$
– litmus
Mar 30 at 14:46
$begingroup$
I see, I misunderstood the labels (and didn't look at the axes).
$endgroup$
– Servaes
Mar 30 at 14:47
$begingroup$
No worries, I've edited the question to make it more clear
$endgroup$
– litmus
Mar 30 at 14:48