LQ content analysis
LQ content analysis. You are asked to write a half-page (350-500 word) analysis of the table. Of course, there are more numbers than you have space to write about them. Much like the economic profile assignment, you have to be selective upon what you write. What story are the numbers telling us? What I don’t want is a play-by-play description of the numbers. ex “The agriculture LQ was 0.6, which is low, compared to 1.2 for utilities, which is high.” That may be factually correct, but you are writing to a reader who wants an interpretation of the data, noit a description. Remember what I said at the beginning of the lab: LQs are a tool to show whether the share of people working in a sector in your region is weaker (0<x<1.00) equal (x = 1.00) or stronger (x > 1.00) than the national average. When the LQ value is high (ex. 1.20) or above, this suggests your region is specialized in that sector (industry). The LQ values can be very high or very low in small regions (eg Saint John), but tend not to fl;uctuate so much in very large regions (ex Toronto), so don’t use my 1.20 rule as absolute. LQs will thus help confirm that Toronto is a major financial centre and that energy (utilities) is important to Saint John. My suggestion is therefore to highlight 2 or 3 sectors where LQ values are at their highest. Then, in your analysis, you can either
a) compare your LQ numbers with what you wrote in the economic profile (ex the sources you consulted were talking about diversifying away from agriculture, but your LQ numbers show employment has rather been concentrating in that sector);
b) tell me if there’s a trend between 2004-2014. Is the region further specializing or rather diversifying? Don’t forget to look at all sectors. The LQs for financial services may have been low (0.60) in 2004, but now at 1.10, which may not suggest a stroing specialization, however it is phenomenally hiugher than in 2004. Alternatively, a sector at 1.00 today but at 1.80 ten years ago suggests something dramatic happened in that sector.
c) hypothesize what could be behind the numbers or the changes over time? If there’s a drop in LQ values in resource sectors or manufacturing, what might this be telling us about the global competitiveness ofthese sectors (or technological change). A hypothesis is an educated guess that whose answers yoiu could research at another time
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