Correlating time series for 20 regions (SPSS) I have a question to which I can't find an answer although I spent really awfully lot of time searching.
I have time series data for about 20 regions of a country. Each time series covers 20 years.
I want to measure to what extent the evolution of the variable x followed one pattern in the regions. I'm sure it did to some extent but I want to argue in my paper that they follow a similar pattern, so I need an exact measure. 
I was thinking about just correlating the data for the regions, but the cross-table I receive is not enough for me to conclude how high the similarities were. Any ideas?
I saw the option autocorrelation and crosscorrelation but I guess that's not the thing I'm looking for. It seems that the forecasting option is also not the best way to do that. I want to mention the statistical analysis only at the very beginning of my paper - then I go into qualitative case studies to prove my point, so I don't need to propose a huge model for the the statistical data. 
I will appreciate your help.


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My hypothesis is theory-driven. I assume x and y are causaly linked. Theoretically it makes sense. I've investigated the country qualitatively (historical analysis) and it seems to make sense. I've also checked it with country-level statistical data and there's a huge correlation between x and y, but I only have data for 22 years so I'm afraid the correlation is just a coincidence. I'm asking myself for example whether the correlation is not caused by changes in some, few, regions. That would invalidate by causal explanation. That's why I want to see if the data series are correlated - I've seen charts and all the regions seem to follow the pattern visible in the country-level data, but I want to be sure. 
I would love to check correlations of x and y on the regional level too! No idea how to do that (but that's less important, simply because I have some doubts whether the regional data I found on y is reliable and have no other data source).
 A: Looks like you might want to do a time series similarity analysis. There is a SAS procedure called PROC SIMILARITY which would identify how similar a target variable(y) is with input(x) variable. I'm sure there is an R equivalent, however I'm not sure if there is an SPSS equivalent. See the example in this website, looks similar to what you are trying to achieve. There is a path and cost statistic and would tell you how similar two time series are.
Hope this is helpful
A: I think 20 years of data is plenty.  Let's assume that the variable you are looking at is the Unemployment rate for 20 different regions over a 20 year time series.  You already looked at a correlation table 20 x 20, and found that Unemployment rate at the regional level is highly correlated.  
To analyze their respective patterns, you could run a simple linear regression for each of those regional Unemployment rate (dependent variable) with the National Unemployment rate as the independent variable.  This way you would have a linear regression equation for each of those regional Unemployment rate variable characterized by a slope vs the National Unemployment rate and a constant.  Each regional variable will have a different pattern (different Slope and Constant).  But, directionally they would be similar.  Also, each linear regression would divulge the statistical significance of the relationship between the specific Regional Unemployment rate and the National one... or whatever is the x variable you are looking at... the rational would be the same.     
