During the late 1990s, the United States of America had a strong performance in their economy; this post will focus on the explanation of the performance and the understanding of the shape of the Philips curve at that time. The Phillips curve is a single-equation econometric model, named after William Phillips, describing a historical inverse relationship between rates of unemployment and corresponding rates of rises in wages that result within an economy. Stated simply, decreased unemployment, (i.e., increased levels of employment) in an economy will correlate with higher rates of wage rises. Phillips did not himself state there was any relationship between employment and inflation, although this notion was subsequently made popular by Milton Friedman from 1967.
In the lead up to the late 1990s, America was suffering a jobless recovery from the 1990-1991 recession. The federal government moved interest rates from 6% to 3% in an attempt to increase spending and lower unemployment figures that were sitting above 7% (Ferreira, 2018).
Businesses had suffered massive hits in the 1987 and 1990 recessions and America was moving during that time from a manufacturing based economy to a financial service-based economy, and this led businesses not to invest in new revenue streams but to focus on optimising their current offerings by investing in technology and process improvements. While more affordable capital allowed the businesses to recover, the government didn’t get the response it was after, as no new jobs were created. Businesses merely focused on the return on investment that allowed the highest return on their capital.
From 1992-1996, the returns from creating excellent operational companies drove more profit than investing in people; this allowed the most effective businesses to start scaling throughout America. A new economy focussed on investing more in technology and process to streamline effectiveness, which in turn decreased operational costs, reduced inflation by reducing prices for consumers and increased productivity per person.
The federal government increased the interest rates from 3% to 6%; this initially caused a slower than before growth in 1995 but the market adjusted. During the middle of the 1990s, the US government wanted to tackle their budget deficit. The Clinton administration reduced spending which decreased the supply of government bonds and therefore a demand for investment was created in the private market, driving lower business and consumer credit by increasing supply of that market.
Even though the government had increased interest rates, with the reduction in private capital, the market allowed businesses to get a better ROI from the use of capital and the consumer had lower use of money cost if they wished to purchase more goods and or services.
Economists at the time believed technology was a black hole (Gordon, 1997), as it was subject to diminishing economies of scale. However, by 1997-1999 businesses continued to invest in projects with the greatest ROI and that meant leveraging technology, for each marginal cost they inured, they gained a more substantial gain in marginal revenue or reduction in total value. Further business profits through scale and operational effectiveness, led to further price reductions and allowing consumers across America with more disposable income.
Consumers and businesses were caught up in a multiplier accelerator where the lower the prices and cheaper the access to consumer capital increased the spending and investment into companies that focussed on technology and process improvements, which in turn allowed the business to invest even more and scale further and this did continue while it was profitable to do so.
New technology companies benefited from this invested capital by allowing businesses to lower costs and scale, those who were qualifying with MBAs started to move from heading straight into the financial industry to heading into technology and entrepreneurship. Technology companies could also scale globally as they were not limited by conventional value chains, this allowed job growth in the service based market, helping to contribute to 26 million new jobs throughout this time. Unemployment fell to a low level of 3.8%, and growth rate of labour productivity increased to 2.8% per year, technology multiplier of 1.25 showing the impact of this relationship between businesses and technology improvements (Oliner & Sichel, 2000).
The standard neo-Keynesian Phillips curve helped in explaining the relationship between inflation and unemployment from the 1960s to 1990s. However, during the 1990s, inflation decreased, but so did unemployment, causing a trend line showing that as inflation declined so did unemployment. The opposite of the inverse relationship expected, making it harder for the government to understand the impacts of controlling unemployment via interest rates.
We know what happened next dont we? The lesson should be that philips economics, can not always be relied upon to handle the cost of capital in an economy.