# Questions tagged [spurious-correlation]

Nonzero correlation between variables $x$ and $y$ where neither $x$ causes $y$ nor $y$ causes $x$. May result from both variables having a common cause or the correlation being conditional upon a common effect of both $x$ and $y$. Use also for spurious regression.

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### Variance and empirical distribution

We know that regressing two I(1) time series that are not cointegrated might give rise to spurious results. Indeed, we might have an excess of rejection of the null hypothesis due to the fact that as ...
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### Sample-size-dependent magnitude of spurious correlation?

In my recent research, my computations involve sample-based covariance estimates. As you might know, with an insufficient sample-size, we will encounter spurious correlations: cross-covariances which ...
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### Does it really matter if a correlation is spurious?

Let’s say you are trying to find if there is a correlation between two stock prices, where both are likely non stationary series. You have no concern as it relates to a potentially causal relationship....
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### Non stationarity and forecasting

Let's assume we have estimated a linear regression model on a dataset from 2000 to 2017. The data were stationary. What happens if the data are no longer stationary in the next years? Do the forecasts ...
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### ARDL model as remedy for spurious regression?

Suppose there are two non-stationary time series of integrated order 1. The two time series are not cointegrated. According to conventional econometric theory, "In general, regression models for ...
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### What to do about spurious regression

Say you have two variables with trends in them. It is often said that this leads to spurious regression. My question is, when will regression with ARIMA error (which may involve differencing) ...
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### Spurious regression

I am using regression with ARIMA error which modifies the error terms to generate correct results for time series regression. I know that if two variables have a trend in it then you may get spurious ...
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### Can a confounding factor hide a possible causal relationship? (as opposed to find a spurious one)

I'm a rookie with statistics, and I'm struggling to understand this: it is well known that a confounding factor can cause a spurious association, leading to rejecting a true null hypothesis (i.e. due ...
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### Will the coefficients of an error correction or lasso-penalized model usually reveal spurious correlation?

As time goes by I have learned of more and more ways that correlations can be spurious and more and more tests and correction procedures intended to avoid taking such correlations as meaningful. My ...
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### Spurious relationships: flavours, terminology

The following types of relationships come to my mind when I think of the term "spurious" (as in "spurious regression" or "spurious correlation"): A statistical ...
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### Why does the presence of cointegration solve the problem of spurious correlation?

This question was originally posted on quantstackexchange: https://quant.stackexchange.com/questions/31501/why-does-the-presence-of-cointegration-solve-the-problem-of-spurious-correlation Many of us ...
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### Question about Spurious Relationships of Trending Variables

Why is the answer to this question 'false?' If both X and Y exhibit trending behavior, then regression of Y on X and a trend variable will always generate spurious relationship. What are some ...
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### Impossible effects in a logistic regression. What causes them, and what to do about them

I am currently analysing some data from a psychological experiment. In this experiment participants have to decide between two options based on some information. I can derive a variable indicating ...
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### Avoiding inflated DF - spurious results computational modelling

I have a computer model comparing a number of paired groups of data (reaction time & accuracy for 1 'subject' go together for a number of categories) But since the program runs 500+ subjects for ...
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### Is a High R squared a Sufficient condition for a spurious regression?

I know that a necessary condition for spurious regression is a R squared approaching 1. However, is a R squared approaching unity a sufficient condition? Said another way, if two non-stationary ...
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### Correlation between two time series of sales data

I have two time-series of 2 different products x & y. They belong to the same main category, e.g.: Iphone 6 and Iphone 5. Maybe one product is the predecessor ...
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### Does ARMAX solve the autocorrelated errors and avoid spurious regression?

I have a OLS model looks like this: However, the residuals have auto-correlation like this: It doesn't seem a strong autocorrelation, and the model passes the Engle-Granger cointegration test (...
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### Model residuals pass stationarity test, but Durbin–Watson test fails

I have a OLS model that I try to prove it has cointegration between two regressors and the dependent variable. The model fits well, with a very high $R^2$. The residuals don't seem to be ...
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### How to "statistically adjust" for variables? [duplicate]

I've been trying to understand what means "statistically adjusted" when comparing two variables. For example, when computing the odds ratio for a death after surgery in two hospitals, we compute the ...
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### Can negative relationship between X and Y be spurious

Let's assume I have X and Y and both X and Y have positive relationship. In such case in which both series trend in the same direction, we need to test for cointegration to be sure that relationship ...
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### Is this "strong correlation" definition valid?

This page defines a a "strong correlation" using a formula that combines a standard correlation measure with lag-1 autocorrelation measures. I've never seen a definition of correlation like this ...
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### spurious regression?

I am regressing one variable on 1,500 features. I have 30,000 rows of data. I know some of my features are correlated, but a Ridge regression where I select the ridge parameter $\lambda$ by cross ...
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### Correction methods for spurious correlation

I'm investigating the relationship between A/B and A*. I've found that higher A/B scores lead to lower A scores. Obviously however there is spurious correlation between A/B and A, and if that spurious ...
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### Testing a single time-series for changing variance structure (Heteroscedasticity and Volatility Clustering)

I would like to assess a single time-series for a changing variance structure that might be leading to spurious variance estimates when that time-series is used in regression. In my head two terms ...
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### Avoiding spurious correlation in time series

I am investigating the relationship between monthly macro-economic variables, and monthly indicators of a company's performance and workload. I am doing this for predictive purposes, and I am ...
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### Do we have to model spurious auto-correlation in time series?

I am analyzing a data set of power consumption with the aim of forecasting. The times when there is consumption are rather sparse. If there is consumption then there is likely one in the next time ...
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### Are these nonstationary variables?

If I have understood correctly, computing the correlation of two nonstationary variables can lead to spurious results. For example, computing the correlation of two stock price time series would lead ...
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