Wage and Income Growth: Four Different Sources, Six Different Data/Trend
Recently released data from the Census revealed that in 2019 household income grew by 6.8% to reach $68,703—highest ever since the Census started collecting data. Before you compare your own salary increase in 2019 to the reported number, keep in mind that there are many wage and income growth surveys done by different Government entities that widely vary in the reported number due to methodological differences. For example, the chart above of different wage and income growth series clearly shows a completely different trend and point data for each year. The Correlation Matrix table shows a low correlation between varying wage and income growth series. Furthermore, different wage and income growth on the table above show lows of -20% to highs of 56% correlation with job growth or demand for labor. Let’s proceed with a short description of each series analyzed above.
Average Hourly Earnings Growth: This is also known as a headline wage number released every month with the monthly jobs report. The Current Employment Survey (CES) hours and earnings series are derived from reports of payrolls and the corresponding paid hours for all employees, also for the various types of production employees. Hours and earnings are only for private-sector employees. This series shows an inverse relationship with job growth, meaning when demand for labor increases, prices (or wages) go down and vice versa. This relationship somewhat goes away from the norm, meaning economists expect a direct relationship between the two. However, could it be that the inverse relationship is communicating that as wages go up, companies demand less labor, and may substitute with capital goods or machines? Milton Friedman, a well renowned economist, argued a similar point against increasing minimum wage.
Atlanta Fed’s Wage Growth Tracker: The Federal Reserve Bank of Atlanta has a wage tracker that uses a common sample type approach. The weighted 1997 median is constructed after weighting the sample to be representative of the 1997 population of all wage and salary earners in terms of sex, and age, education, industry, and occupation groups. The average hourly earnings show a high correlation with the Atlanta Fed’s wage growth tracker number, since the base number on both series comes from a same source.
Employment Cost Index (ECI) Growth: This data is available through the BLS website, under the header Employer Costs for Employee Compensation (Wages and Salaries). According to BLS, the index measures changes in the cost of compensation not only for wages and salaries, but also for an extensive list of benefits. As a fixed-weight, or Laspeyres, index, the ECI controls for changes occurring over time in the industrial-occupational composition of employment. This data gives window into inflation in the price of goods and services, as labor is considered an input for production.
Real Median Household Income Growth: The calculation that the Census uses to get this data is quite complicated, so in layman’s terms, it is inflation-adjusted and calculated median data using either Pareto or Linear interpolation. The current series uses linear interpolation. Besides these two massaged methods, the 2019 data point is impacted by the pandemic. The data series have high correlation with real median personal income.
Real Median Personal Income Growth: According to the BEA, personal income is income that people get from wages and salaries, Social Security, and other government benefits, dividends and interest, business ownership, and other sources. These statistics can offer clues to Americans' financial health and future consumer spending. This data series is adjusted for inflation as well. Furthermore, it has over 50% correlation with job growth, the second best among all the data series analyzed.
Real Disposable Personal Income Growth: According to the BEA, disposable personal income is after-tax income. The amount that U.S. residents have left to spend or save after paying taxes is important not just to individuals, but to the whole economy. The formula is simple: personal income minus personal current taxes. This data series is adjusted for inflation as well. The data series has over 55% correlation with job growth, making it the highest among the data series analyzed.
· Each of the wage and income growth series show a different trend, as seen on the chart. The movement of each series, measured by the correlation among them, show low correlation coefficients. Historical annual average wage/income growth from 2006 to 2019 among the series considered for analysis show a large range from 0.9% to 3.3%. The major differences between these series tend to come from data collection methodology and additional massaging of the data by sources.
· The correlation matrix table shows a large range among the wage and income variables. Furthermore, wage and income growth (price of labor) shows low correlation with job growth (demand for labor). Low or an inverse relationship with job growth means when demand for labor increases, prices (or wages) go down and vice versa. This relationship goes away from the norm, in that economists expect a direct relationship between the two. Labor supply tends to have a smaller impact. However, could it be that the inverse relationship is communicating the reality on the work place that when wages go up, companies demand less labor and may substitute with capital goods (or machines)? Milton Friedman, a well renowned economist, argued a similar point against increasing minimum wage and its impact to demand for low skill workers.
· As a worker/employee, given the variety of wage/income data, should you be happy that you got a better raise than the ECI growth of 1.8%, or sad that your increase was well below the real median household income growth of 6.8% during 2019?
· And as an employer, during the first half of 2020, the income growth from different sources vary from lows of about 2% to highs of about 7%. Which salary increase should you consider offering your employees?
· There are many determinants of supply and demand of labor that make an attempt to get to near the equilibrium price of labor (income/wage) but never succeed. In real life, there are just too many complex factors in play. Because income provides the greatest incentive to work, and hardworking employees directly impact a company’s revenue growth, the importance of this variable cannot be minimized.
· We are only analyzing the national wage/income data in this blog, but metro and county or block group level data is available by occupation/industry/job title, which makes it even more complex.
· For employers and employees: Adjusting salaries using headline inflation rate and/or wage/income growth reported by government sources will be wrong as there are many idiosyncrasies surrounding these numbers.
· The secondary effect of income growth benefit the larger economy as 70% of the U.S. economy is dependent upon consumer spending. The more money consumer have the higher the spending. From the real estate perspective, income growth matter for all real estate types but the series tend to have stronger causal relationship with the retail real estate.
· Finally, because of the complexities surrounding salary/wage/income data, employers and employees must have well-vetted data and guidance from an established company like www.ThinkWhy.com. The #LaborIQ by #ThinkWhy have clean salary data and experienced analyst who could help you maneuver through the complexities of wage/income/salary data.