Thermodynamics describes the physical properties of systems composed of a large number of particles. In the beginning, it was a purely phenomenological science. Its basic notions, like pressure and temperature, where defined via the way they were measured and its only justification was the successful prediction of experimental results. Understanding of why the same notions were useful for the description of different types of matter and why the dynamics of different systems had some universal properties still did not exist.
The situation began to change with the works of Joule and in particular Boltzmann, who tried to establish a link between the theory describing the microscopic dynamics, the dynamics of single constituent particles and thermodynamics, which describes the collective dynamics of a macroscopic number of particles.
The traditional neoclassical real business cycle model assumes that technology arrives as an exogenous process, after which labor productivity immediately responds positively until the economy eventually converges to the new steady state where labor productivity is permanently higher. However, David (1990), Rogers (1995), and Hall (2004), among others, have provided evidence that technology diffuses slowly throughout the economy. This means that a new technology is adopted by agents over time and that all agents do not adopt the technology immediately. This process of adoption and diffusion of technology takes the form of an S-shaped curve. That is, the technology initially diffuses slowly, followed by a period of rapid diffusion until the speed decreases when the technology has been absorbed in the economy. This view of slow diffusion therefore challenges the notion that technology shocks have immediate and positive effects on the economy. Furthermore, Robert Solow’s statement: “You can see the computer age everywhere but in the productivity statistics” clearly states how the literature lacks economic understanding of how productivity is affected by the arrival of new technology.
This paper will show, through use of vector auto regressions and more than a century of U.S. data, that labor productivity may respond negatively in the short run to a technology shock. This case can arise if the arrival of a new technology initiates high installation costs or a learning stage for the productive labor. During this stage labor productivity does not necessarily increase as assumed by the standard neoclassical models. Rather, labor productivity can actually fall below trend temporarily. After a time lag from when the technology was invented, the technology eventually becomes adopted in the economy and the inflection point of the S-shaped diffusion curve is reached. Inputs can then once again be active in the production process and it is likely that labor productivity will increase above trend.
The sub-prime crisis emerged in the United States in mid-2007 and spilled over to Europe and other economies. From mid-2007 to mid-2008, the spillovers were relatively modest. The situation began to change in mid-2008. Then, following the bankruptcy of Lehman Brothers in mid September 2008, developments took a dramatic turn leading to a global financial crisis. During the crisis, the US dollar has seen some remarkable swings against major currencies. For example, from September 2007 to March 2008, it depreciated about 16% against the euro and yen, while between March and September 2008, it gained sharply (22%) against the euro. On the other hand, the dollar depreciated against the yen about 21% from August to December 2008, in particular after the Lehman’s default (see Figure 2 below). During this crisis, banks reportedly faced severe liquidity problems. US dollar funding shortages put intense pressure on the balance sheet capacity of the banking sector due to financial sector deleveraging. In response central banks around the world took unprecedented policy measures to supply funds to the banks (see McGuire and von Peter, 2009).
The purpose of this paper is to investigate any link between the market wide liquidity risk caused by the deleveraging process and exchange rate movements during the crisis. Adrian and Shin (2008) document that aggregate liquidity can be understood as the rate of growth of the aggregate financial sector balance sheet. When asset prices increase, financial intermediaries’ balance sheets generally become stronger, and, without adjusting asset holdings, their leverage declines. The financial intermediaries then hold surplus capital which they use to expand their balance sheets. On the liability side, they take on more short term debt. On the asset side, they search for potential borrowers. Aggregate liquidity is intimately tied to how hard the financial intermediaries search for borrowers, including through the interbank market. Conversely, when asset prices decline during a financial crisis, the financial intermediaries’ balance sheets contract and are thus reluctant to lend. Aggregate liquidity then declines.
