Actually the data presented shows nothing of the sort.
Sigh - for this example or other future references to "data trends" keep this in mind for a critical analysis.
The author shows a graph of spending by quarter - where each quarter goes up and the last quarter goes up a bit more - then announces that the difference from the third to the fourth quarter is a trend due to raising parking meter times at night.
--one data point is not a trend - never
--the author has no idea if this is a statistically significant difference - that is, is it just due to random variation or is it due to an influencing variable?
--since no statistical test was performed - this is nothing but speculation
--for a true analysis you would need a wider sample - just conducting a one-tailed statistical test on two data points would give you a huge standard error and make results meaningless.
--if interested in the difference in spending between the 3rd and quarter you would need to look at the same patterns going back 5 to 10 years and compare them with the current year.
--simailarly, to direct if there is a true trend you would need to compare the 3rd to the 2nd, the 2nd to the 1t quarter over the course of the data set - which might best be set up using an analysis of variance.
--are the data normally distributed? If not you could transform them for a more commonly used statistical test.
--how is the study designed, what are the bounds of the areas used for calculating spending vs that used for designating the metering study area - the same?
--how are the economic data collected? Is this a sample all is it based on all tax receipts of all food establishments in the area? Is there a definition of what is considered a food establishment?
--importantly - let's say you went thru this exercise, your data were good, and the test shows a the difference between this year's 3rd and 4th quarter shows a difference that is statistically significantly different than those between the same quarters in your 5 yr set. Assuming it is significant at a decent probability (say 95%) - then, and only then can you say the difference is due to some influencing variable or set of variables beyond a random variation.
--Now the crux of the statistical test that considers human behavior patters - in this case, spending. This could be caused by any number of factors - sporting events, concerts, school breaks, going back to school for kids, on, and on and on.
--One would either have to make a good faith effort to look at the competing factors - or conduct a sophisticated analysis of variance on those variables that you could quantify - say the extra number of people downtown for a particular event.
--it would be more appropriate to look at this data after several more quarters
So in this case - or any case where someone flashes a bar graph to make their point - be skeptical. Better yet, take an introduction to statistics class. Cheers.