U.S. economic policy stuck in pre-1970s era

Before the 1970s, U.S. policy makers were able to always count on growing GDP and population.

However, the U.S. population growth has slowed since then from expanding about 1.5 percent annually to about 1 percent annually. Further into the 21st century, the growth rate will slow even more.

Despite this demographic shift, U.S. policies makers still want the same rate of GDP growth.

Bill Gross, co-CIO of PIMCO, said GDP and population growth are integrally linked because growing population means the need for more goods, services, and infrastructure. The economy then grows naturally by meeting this demand.

Without this natural demand generator, economic growth after the 1970s depended on artificial asset price stimulation, said Gross. During this time, the U.S. accumulated staggering levels of debt. Now, after 2008's global financial crash, that policy can no longer work.

Unfortunately, Washington doesn't get this.

U.S. officials are still trying to fix the ailing economy by stimulating demand through loose monetary policy and trying to make China appreciate the yuan, said Andy Xie, the former chief Asia Pacific economist at Morgan Stanley, in a Caixin op-ed.

In fact, Xie said not only does the U.S. not lack demand, its large debt and trade deficit proves its demand is actually too high relative to demographics.

Another way of looking at it is this : businesses, with access to foreign cheap labor, don't think it's worth it to pay U.S. workers such high wages, so America as a country needs to consume less.

This is the reality for many developed countries. For them, Xie said the best policy is to maintain living standards by preserving wealth and redistributing some of it to protect low-wage earners.

Europe and Japan are already doing this, according to Xie, while the U.S. is still trying to fix its low wages and unemployment problem with GDP growth.

He said U.S. economic policies are irrational and scare the whole world to death.

Email Hao Li in New York at hao.li@ibtimes.com.