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[ 3.1 ms ] story [ 17.7 ms ] thread
Who keeps submitting these stories with clear political biases to HN?
The last paragraph of this article exemplifies what is wrong with political discourse in this country. I'm a right leaning individual, and I was interested in the data in the article, but the insult at the end of the article was unneeded. It was a great way to take a relevant story with good data, and turn off any reader who leans right with a petty insult at the end.
> It's a great story, and shows that the protectionist right-wing creed of low taxes, and low pay for employees, along with minimal public investment, is bunk. Perhaps, if the right is serious about "making the country great," and about promoting business, instead of just adhering to anti-left dogma, then we'll see more states that follow governor Dayton's business-friendly lead.

Is that the "insult" you're talking about?

(comment deleted)
A factor in my leaving the state was the tax rate.
People have downvoted my comment which was a simple factual statement.

Just because data doesn't fit ones narrative doesn't mean you should reject the data.

The problem with articles like this is that there are just too many variables that affect the budget, employment, etc. For example, the current governor has been in office for five years. That means the previous one was in office from 2003-2011, in other words when the 2008-2009 recession hit. That puts his economic performance in perspective.

Another example, my country Germany is doing really well economically not because of what the current government is doing, but because of what the 1998-2005 government did. And because we benefit from a relatively weak Euro and low interest rates. It makes the current government look good but they don't really deserve it (and they don't plan ahead for when times are worse again, imo).

So it may well be that the policies that the current governor has put in place have contributed to the good economic situation in the state. But a lot of other factors may also be responsible.

tldr correlation != causation (it might be, and it might not be)