UCLA economist blames Hoover’s pro-labour policies for Great Depression

Washington, Aug 30 (ANI): A University of California, Los Angeles economist has blamed former US President Herbert Hoover’s pro-labour policies for Great Depression in 1929.

“These findings suggest that the recession was three times worse – at a minimum – than it would otherwise have been, because of Hoover,” said Lee E. Ohanian, a UCLA professor of economics.

The policies, which included both propping up wages and encouraging job-sharing, also accounted for more than two-thirds of the precipitous decline in hours worked in the manufacturing sector, which was much harder hit initially than the agricultural sector.

“By keeping industrial wages too high, Hoover sharply depressed employment beyond where it otherwise would have been, and that act drove down the overall gross national product,” said Ohanian.

“His policy was the single most important event in precipitating the Great Depression,” he added.

According to Ohanian, Hoover was concerned about two potential crises. He was afraid the stock market collapse of October 1929 would result in a recession with deflation, leading to dramatic wage cuts, as a period of deflation had done just a decade earlier.

And because of a series of recent legislative and court decisions that had expanded the power of organized labour, he also worried about the possibility of crippling strikes if such wage cuts were to come to pass.

“Hoover had the idea that if wages were kept high for workers and they shared jobs instead of being laid off, they would be able to buy more goods and services, which would help the economy improve,” Ohanian added.

After the crash, Hoover met with major leaders of industry and cut a deal with them to either maintain or raise wages and institute job-sharing to keep workers employed, at least to some degree. In response, General Motors, Ford, U.S. Steel, Dupont, International Harvester and many other large firms fell in line, even publicly underscoring their compliance with Hoover’s program.

Designed to placate labour and safeguard workers’ buying power, the step had an unintended effect. As deflation eventually did set in, the inflation-adjusted value of these wages rose over time, effectively giving workers a raise precisely at the time when companies were least in a position to afford such increases and precisely when productivity was beginning to fall.

“The wage freeze effectively raised the cost of labour and, by extension, production,” Ohanian said.

“If you artificially raise the price of production, your costs go way up and you pass them on to the customers, and they buy that much less,” he added.

Reluctant to lower wages due to Hoover’s entreaties, employers in the manufacturing sector responded by reducing the workweek and laying off workers. By September 1931, the manufacturing sector was already hurting: Hours clocked by workers had fallen by 20 percent and employment by 35 percent.

Overall, the economy suffered, with the GDP falling by 27 percent.

“The Depression was the first time in the history of the U.S. that wages did not fall during a period of significant deflation,” Ohanian said.

“In late 1931, industry finally did cut wages, but it was too late. By this point, the economy was in an unprecedented, full-blown depression,” he added.

The findings are slated to appear in the December issue of the peer-reviewed Journal of Economic Theory. (ANI)

Space and robotics technology used to improve forest planning and harvesting

Washington, June 30 (ANI): Space and robotics technology have been combined to develop an advanced Precision Forestry Positioning System, which allows more efficient forest planning and harvesting.

Invented by researchers at the Institute of Man-Machine-Interaction at the RWTH Aachen University in Germany, the system has helped catalogue 240 million single trees in the German region of North Rhine-Westphalia. he system combines remote-sensing maps from airplanes with satellite navigation data to map each tree in a forest.

This information is then used to plan which trees are to be cut, and when.

Finally, the plan is used on harvesters to identify which trees to cut. This helps make the harvesting more efficient, optimises overall wood production and reduces costs.

The system won the North Rhine-Westphalia Region’s 2008 European Satellite Navigation Competition, which was supported by ESA’s Technology Transfer Programme Office.

“We already have one harvester in operation with our system onboard. As the prototype works well, we are fairly close to the stage where we can go into production. Another 6 to 12 months, and we should be there,” said Professor Dr Jurgen Rossmann from RWTH Aachen University, who developed the system together with Petra Krahwinkler, Arno Bucken and Dr Michael Schluse.

The objective of the Precision Forestry Positioning System is to automate and optimize all the work involved in foresting, from the early planning of the forest to the final cutting of single trees, in order to be competitive on the worldwide market, and to overcome efficiency problems related to the forest ownership structure of the region.

“Precision farming is important in today’s agriculture, where farmers can save money with the use of satellite navigation systems,” explained Arno Bucken.

“However, the accuracy of the GPS navigation system, which is of 20 to 30 m, is not enough to identify single trees in a forest. Much higher accuracy is needed,” he added.

“We found a solution to this problem, which increases the accuracy to 50 cm, by using GPS as the initial reference position, and then taking remote-sensing data to identify the single trees in the forest,” he explained.

To help the planning, a virtual computer-based forest has been developed with all trees being identified by their location, based on the GPS and remote-sensing data.
In addition, a fourth dimension, ‘time’, has been added, and is of the utmost importance for this system.

“All trees are not only known by their geo-coordinates, but they are also time-stamped, and all measurement data are archived.

This makes it possible to see ‘how trees grow’, as well as look back to learn from the past,” said Rossmann. (ANI)