Bear River Location Quotients

Tyson Smith, Regional Economist

In the summer issue of Local Insights we discussed the value of economic diversity and the Hachman Index (a method used to measure industry diversification in the labor market)[1]. The article states that:

The Hachman Index is derived from the weighted average of the industry Location Quotients (LQ) in a region. A LQ measures the regional concentration of employment in a given industry relative to a larger geography. As a rule of thumb, an LQ of 1.2 or higher represents an industry with a relatively high concentration of regional employment, while a score of 0.8 or lower indicates sparse regional employment… Breaking the Hachman Index into individual components provides insight into the distribution of employment in a local economy.

Figure 2 in that article resembles the charts to the right, except that the data in the article was aggregated to the regional level. Combining the employment counts for all three Bear River counties obscures the concentration of employment in certain industries at the county level. This article sheds light on the relative density of employment in each county.

When examining the three charts, note the scale on the horizontal axis. In 2012, Cache County had very few location quotient outliers. Four industries were within the “normal” location quotient range, and only two industries had LQs greater than 1.2. Furthermore, the industries with above normal concentration of employment in Cache (manufacturing and educational services) registered LQs substantially lower than the highly concentrated industries in Box Elder and Rich counties.

Box Elder County had five industries in the “normal” LQ range, but three of the four high-density industries recorded LQs above 2. This means that the proportion of the workforce employed in manufacturing, transportation & warehousing and agriculture, forestry, fishing & hunting more than doubled the national percentage.

Lastly, Rich County had the lowest Hachman Index among the Bear River counties. Among the 10 industries that meet disclosure standards, only two industries had employment LQs in the “normal” range.

In Utah, there is a correlation between the size of a county’s labor force and the degree of industrial diversity in the county; in general, this means the more workers in a county the more diverse the economy of that county.  So it is not surprising that Cache County has less variance in its respective LQs compared to Box Elder and Rich counties.

Understanding the relative concentration of employment by industry lends some insight into the comparative advantages of a region. In terms of Bear River, we see that the labor economy is moderately diverse compared to other counties in the state.

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[1] Article titled: Economic Diversity in Bear River

Economic Diversity: Further Analysis of the Hachman Index

Tyson Smith, Regional Economist

In the summer issue of Local Insights we explored local area industry diversity using the Hachman Index. As stated in the article, many economists believe that economic diversification promotes stability in local markets. The article also touches on the difficulty of identifying an exact index value that denotes an appropriately diverse economy. One way to examine Hachman Index values is described below:

Click Image to Enlarge

“It is difficult to determine exactly what index value constitutes a highly diversified region when there are large differences in total employment [among the regions]. However, if a county’s Hachman Index ranks considerably higher than its total employment count – relative to the other counties in the state – that is an indication that the county is relatively diverse. Using this method reveals that Rich County had the fourteenth highest Hachman Index and the 27th largest employment base in the state, making it more diverse than counties of similar size. Conversely, both Box Elder and Cache’s index values ranked three spots below their total employment ranks of fifth and eighth, respectively.”

This simple comparative method highlights the correlation between the size of the workforce in a given county and the industrial diversity in that area. In general, counties with larger populations do not rely on one or two key industries for employment. On the other hand, small communities in less populous counties often exist because their region has (or had) a comparative advantage in a single industry. The relationship between employment count and economic diversity allows us to identify counties that are more or less diverse[1] than expected using the matching exercise in the chart to the right.

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[1] Counties where the Hachman Index ranks more than two spots higher or lower than the Total Employment ranking are identified as “More Diverse” or “Less Diverse”, respectively. The "two spot" difference as a means of identifying notable incongruities does not represent a scientific methodology, it is only meant to give directional insight into the data.