Broadband Demand Analysis for Network Building

An increase of broadband demand is forecasted by transitional methods that consider the effect of this increase through many factors, such as customer requirement diversification, and new service introduction and deployment under competition. Broadband demand forecasting has become important for closing the digital divide, promoting regional developments, and constructing networks economically; therefore, a demand forecast model that considers the mechanisms of market structure is necessary. In this paper, a demand analysis method for broadband access combining macro- and micro-data mining is proposed, and the service choice behaviour of customers is introduced as a customer model not only to express the macro trend of market structure, but also to consider area marketing. The proposed method can estimate the potential demand, determine the point at which broadband demand growth peaks in a specified area, and support a decision for ultra high-speed broadband access facility installation.     

Output Expectations and Forecasting of UK Manufacturing

This paper analyses both quarterly data from the Confederation of British Industry (CBI) Survey on respondents’ expectations of recent and forthcoming manufacturing output and monthly Office of National Statistics (ONS) figures on actual manufacturing output within the UK. Quarterly output expectations of the CBI manufacturers are explained from the monthly ONS observations using a bounded rationality approach. The logistic formulation models the diffusion process across respondents. There is a backward-looking CBI Survey perspective, explained by past ONS observations, and a forward-looking perspective, explained from future ONS statistics. Also, the forecasting of monthly manufacturing output from earlier values, along with the quarterly CBI Survey information, is examined and tested against the alternative Pesaran/Thomas method. The study provides econometric evidence for the validity of the logistic model and shows that bounded rationality can explain the formation of predictions among business managers in the UK manufacturing sector. The emerging consensus from the literature, supported by this paper, is that the logistic format is a superior approximation to the true data generating process compared with the earlier standard Anderson/Pesaran/Thomas approach. An adjustment to the Survey is used, which achieves perfect symmetry with up and down versions of the data. The benefits of this adjustment are tested in the forecasting section.

Estimating Key Economic Variables: The Policy Implications

The current monetary policy debate has focused on current estimates and the future path of the natural rate of unemployment and the equilibrium interest rate. Estimates of the natural rate of unemployment should vary over time with changes in demographics and improvements in human capital. However, these changes should be gradual. This paper shows that the estimates of the natural rate of unemployment by Federal Reserve officials and private-sector economists seem to move pro-cyclically, potentially showing too much weight given to short-term fluctuations in economic variables. As with the natural rate, there are good reasons to expect the equilibrium interest rate to change over time. In fact, the level may actually be more responsive to current economic data, reflecting changes in aggregate savings and investment. Yet, we see that equilibrium interest rate estimates by both Federal Reserve officials and private-sector economists have declined quite dramatically over the past five years. A potential concern raised in this paper is that estimates of these critical economic variables for policy determination appear to be overly sensitive to high frequency economic data.