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The average Connecticut resident pays twice as much for electricity as the average Tennessee resident. Fortunately for the confused consumer, the federal government now measures these variations.
For a few years now, the agency that tracks gross domestic product, personal income and other economic indicators has also produced what it calls Regional Price Parities, measures of price fluctuations across states and metropolitan areas. That data, published in July by the Bureau of Economic Analysis , shows that a dollar can swing by more than 30 percent in terms of what it can buy. But by incorporating regional price parities RPPs from the Bureau of Economic Analysis, OES can produce a price-adjusted wage that offers data users a standard for comparing wages across Metropolitan Statistical Areas hereinafter referred to as areas.
RPPs, expressed as a percentage of the overall national price level equal to , measure the differences in the price levels of goods and services across areas for a given year. In areas where goods and services are more expensive, actual wages tend to be higher. See table 1. Data users comparing wages for San Francisco—Oakland—Fremont, CA, and the Durham area will notice the following: San Francisco area wages decrease after adjusting for average price level, while wages in the Durham area increase after the adjustment.
But when the actual wages are adjusted for average price level to show purchasing power, the rankings change. The San Jose, San Francisco, and Washington areas remain among the highest paying areas, but the New York area is no longer among the highest paying. Actual wages in the San Jose area are so high that they offset the high cost of living. The San Francisco area falls from 2 to 10 and the New York area falls to Table 1 shows areas with the highest average price-adjusted wages in May The relationship between wages and relative prices becomes even more interesting when occupational data is included in the analysis.
This remains true both before and after adjusting for prices. However, these occupational groups are the exceptions. Out of the occupational groups in the 10 areas with the highest mean wages, the 18 occupational groups listed in table 2 are the only groups that remain among the 10 highest paying areas after adjusting wages for regional prices.
Note: The criterion for inclusion of a major occupational group under an MSA in the table required that the MSA was among the top 10 areas for purchasing power in the group.
Accordingly, not all major occupational groups are included in the table and not all MSAs have a major occupational group listed. Because wages for all occupations in an area are adjusted by the same RPP, relative rankings within an area remain the same after adjusting for prices.
But because actual wages and RPPs differ across areas, pay rankings for specific occupations tend to fluctuate in cross-area comparisons, creating variances. For some occupations, adjusting for regional prices decreases the difference between the highest and lowest paying areas, while for others the difference increases.
This holds true for two related occupations—bookkeepers and accountants. After adjusting wages for regional prices, the difference between the highest and lowest paying areas decreases for bookkeepers and increases for accountants. A sample of this listing is provided in table 3. But after adjusting wages for regional prices, occupational differences tend to have a more pronounced effect on purchasing power than geography alone. In particular, occupations with relatively low wages tend to exhibit the greatest pre and postadjustment change.
For example, food-service workers and cashiers earn more in San Francisco and San Jose than most other areas of the country before adjusting for regional prices. After price adjustments, purchasing power for fast-food workers tends to increase in areas of Illinois, Washington, and Colorado. Figures 1 and 2 show purchasing power and mean wages for team assemblers 3 and police officers, respectively, in selected areas.
The areas in figure 1 all have an RPP of less than Accordingly, the price-adjusted wage for all areas is higher than the mean wage, effectively increasing the purchasing power of team assemblers in these areas. Most of the areas with high wages for police and sheriff's patrol officers had mean wages for all occupations well above the U.
Simply put, police officers are often better off in high-wage, high-RPP areas.
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