Given the popularity of QuickBooks in the marketplace, there is a strong chance that many of your small business clients use QuickBooks. In this course you will learn how to integrate QuickBooks data files with other market-leading applications such as Microsoft Excel, Word, and QuickBooks Point of sale. Whether working with your own data files or those of clients, the integration techniques discussed in this program are designed to increase your knowledge basic integration concepts and how to use them to your advantage.
There is a fundamental assumption in this course that participants already have a solid working knowledge of QuickBooks operations such as establishing preferences, entering and editing items, and recording transactions such as bills, invoices, and checks. As such, this course is not designed to provide an in-depth review of matters such as these.
Risk management and portfolio allocation deal with two main principles: minimizing portfolio risk and efficient hedging strategies. The literature on the former principle goes back to Markowitz’s theory on portfolio diversification, Markowitz (1952). In a realistic setting with transaction costs and illiquid markets, however, investors deal with practical questions such as how much should be hedged and how to implement hedging. In this paper, we propose a flexible approach to model equity portfolio risk involving exchange rate risks. This model lends itself to adaptable definitions of risk and various structures of hedging. Specifically, we refer to the volatility transmission between exchange rate and equity returns. This approach allows us to specify the interactions between variances / covariances of exchange rate and equity returns and how these relations evolve across time.
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.
