Spectrum allocation in Latin America: An economic analysis

As elsewhere, wireless markets play a crucial role in Latin American economic growth. Mobile telephone networks increasingly provide the communications infrastructure that has largely been lacking throughout the region. Yet, governments have generally made only modest allocations of bandwidth available to Latin American wireless operators, either absolutely (in terms of spectrum each country could allocate at modest opportunity cost) or relative to countries in North America, Asia and the European Union. Using an empirical model estimated on mobile phone data for international markets, we show that very large social benefits are available to countries that make more spectrum available for mobile phone markets. We conduct simulations using our calibrated model to provide lower bounds for country-by-country gains from larger allocations. We also discuss the impact of alternative regulatory regimes on the feasibility to achieve those social gains.     

Analysis on the growth of telecommunication services: a global comparison of diffusion patterns

With the development of the Internet, the telecommunication market has seen a rapid shift from voice-based services to data-based services. Relationships of substitutability and complementarity have emerged among communications technology services such as Internet service, mobile phone service and fixed telephone service. The article analyses the diffusion patterns of communication services in different continents. A modified logistic growth model is estimated using panel data for the years 1975–2004. The research forms a valuable framework for forecasting demand for new services based on the diffusion of incumbent services and can inform strategies for entering the communications network industry.     

Forecasting technology diffusion: a new generalisation of the logistic model

The present research proposes a new generalisation of the logistic model aiming at technology diffusion forecasting. Regarding criticisms and failures reported in the literature to apply logistic function for long-term forecasting, in our work we focused on short-term accuracy of forecast. To formulate the model, based on mathematical approximation, at first the differential equation governing the diffusion process is found and then by solving the derived differential equation, the forecast function is obtained. In all steps, mathematical tools from numerical analysis are used. We compared the New Generalized Logistic Model with eight of the most renowned models in the literature. The model led to more accurate fits and forecasts than those obtained from other models we applied for comparison.     

农村—城市移民率的变动与中国城市化的关系

在我国的经济发展过程中,城市化水平不断提高,并伴随有大量的农村人口向城市转移。本文通过构建一个理论分析框架,在城市化水平与农村—城市移民率的变动之间建立一个模型,发现在农村—城市移民率和城市化水平、农村人口与总人口自然增长率之间存在着联系。通过城市化数据分析我国的农村—城市移民率的变化情况,并应用城市化的logistic方程对城市化水平以及农村—城市移民率进行进一步的估计,最后预测它们未来的发展趋势。     

Technology product evolution and the diffusion of new product features

The evolution of technology products can be analysed on multiple levels. Product categories go through continuous evolution determined by the cumulative changes in the features of new product models. This is manifested in the diffusion of new product features and in the increasingly vague boundaries between different product generations. This article develops an approach for planning and forecasting technology product evolution and the diffusion of new product features. This is achieved by isolating the phenomena underlying the evolution process, and formulating the process at the product category, product feature, and product model levels. The approach is derived from these formulations combining the primarily demand-driven product category diffusion and product unit replacement behaviour, and the more supply-driven product feature dissemination. The approach enables meaningful sensitivity analysis including the analysis of discontinuities. The developed approach is applied to characterise the evolution of an example product category of mobile handsets and to forecast the diffusion of mobile handset features using extensive longitudinal and cross-sectional data collected from Finland. In consequence, the process of technology product evolution and the phenomenon of product feature dissemination are suggested as extensions to research on product category diffusion and replacement.     

A product diffusion model incorporating repeat purchases

A logistic-based model for forecasting the rate of product diffusion given aggregate time series data was constructed. The model differs from earlier models based on fitting the logistic to aggregate data in that it includes a submodel to separate replacement demand from first-time sales. We fit the theoretical model to data and show that forecasts will be significantly more accurate using this model instead of the logistic curve.     

Diffusion of mobile telephony in India: An empirical study

Diffusion of new technology is an important driver of economic growth. In this paper, diffusion of mobile telephony in India is studied. There is a vast diffusion potential in this country which needs to be exploited efficiently and in a rational way. This paper investigates the social, technological, economical and political (STEP) factors that have influenced the diffusion process of mobile telephony especially the diffusion speed. The epidemic model, which is widely employed in the diffusion studies of mobile telephony, is used for the study. The data is fitted into logistic, gompertz, and bass models by nonlinear least squares and it is found that gompertz model best describes the diffusion process of mobile telephony in India. The study reveals that competition and government intervention played a significant role in accelerating the diffusion speed of mobile telephony by making the technology affordable. It is found that mobile telephony is a substitute for fixed line telephony in India. The findings will be useful in taking managerial decisions with respect to factors in forecasting and controlling the diffusion process of emerging technologies.     

中国能源需求向量自回归模型的建立与分析

随着我国经济的快速发展,对能源需求日益增加,在未来一段时期内,如何科学地预测我国能源需求量,对于保证经济的可持续发展、小康社会目标的实现与和谐社会的构建具有重要的现实意义。向量自回归模型是基于数据的统计性质建立模型,把系统中每一个内生变量作为系统中所有内生变量的滞后值的函数来构造模型,是处理多个相关经济指标的分析和预测最容易操作的模型之一,常用于预测相互联系的时间序列系统。能源需求量是由煤炭、石油、天然气等一次能源的消费量组成,他们之间存在着密切的联系,基于此,应用VAR模型对我国中长期的能源需求总量、煤炭、石油、天然气的消费量进行预测,为科学地制定能源发展战略提供理论指导。     

The diffusion of mobile telephony in Italy and the UK: an empirical investigation

Since its appearance mobile telephony has shown a remarkably fast diffusion pattern in most advanced countries. This paper investigates technological and economic factors that have influenced the diffusion process of cellular phones, in particular the diffusion speed and the upper limit. The epidemic model widely used in diffusion studies is summarised and discussed highlighting the evolutionary disequilibrium nature of diffusion processes. Moreover, the econometric specification of some of the models distinguishes between long-run relationships and short-run adjustments to a continuously evolving pattern. We find that the new digital technology, which coincides with increased competition in both Italy and the UK, has made the process faster and increased the saturation level in Italy, but not in the UK; in Italy only the decreasing price of the handset has affected the diffusion process, whereas we find that, in addition to that, decreasing tariffs and increasing consumption expenditures have been significant in shaping the diffusion process of mobile telephony in the UK.     

On the forecasting of the challenging world future scenarios

Logistic and power law methodologies for both retrospective and prospective analyses of extended time series describing evolutionary growth processes, in environments with finite resources, are confronted. While power laws may eventually apply only to the early stages of said growth process, the Allee logistic model seems applicable over the entire span of a long range process. On applying the Allee logistic model to both the world population and the world gross domestic product time series, from 1 to 2008 AD, a projection was obtained that along the next few decades the world should experience a new economic boom phase with the world GDP peaking around the year 2020 and proceeding from then on towards a saturation value of about 142 trillion international dollars, while the world population should reach 8.9 billion people by 2050. These results were then used to forecast the behavior of the supply and consumption of energy and food, two of the main commodities that drive the world system. Our findings suggest that unless the currently prevailing focus on economic growth is changed into that of sustainable prosperity, human society may run into a period of serious economical and social struggles with unpredictable political consequences.     

结合新产品扩散特征的实物期权定价模型研究

现有实物期权定价模型未能考虑新产品销售量所呈现的扩散特征,模型的分析结果与实际情况有较大差距。文章假设新产品价格服从几何布朗运动,并以Bass模型预测新产品的销售过程,运用二叉树方法,构建了离散时间状态下结合新产品扩散特征的实物期权定价模型,并得到新技术采用的最优时机。     

Innovation diffusion with generation substitution effects

Markets of high technology products and services, such as telecommunications, are described by fast technological changes and rapid generational substitutions. Since the conventional modeling approaches that are based on diffusion models do not usually incorporate this important aspect into their formulations, the accuracy of the provided forecasts is consequently affected. The work presented in this paper is concerned with the development of a methodology for describing innovation diffusion, in the context of generation substitution. For this purpose, a dynamic diffusion model is developed and evaluated, based on the assumption that the saturation level of the market does not remain constant throughout the diffusion process but is affected by the diffusion of its descendant generation, as soon as the latter is introduced into the market. In contradiction to the conventional diffusion models, which assume static saturation levels, the proposed approach incorporates the effects of generation substitution and develops a diffusion model with a dynamic ceiling. The importance of such an approach is especially significant for markets characterized by rapid technological and generational changes. Evaluation of the proposed methodology was performed over 2G and 3G historical data and for a number of European countries, providing quite accurate estimation and forecasting results, along with important information regarding the rate of generation substitution.     

A model for forecasting the substitution of one technology for another

Most technological changes can be described as a substitution of one material, process or product for another. Each such substitution, if successful, normally tends to follow an S-shaped (or “logistic”) curve: that is, it starts slowly as initial problems and resistances have to be overcome; then it proceeds more rapidly as the competition between the new and the old technology grows keener and the new technology gains an advantage; and finally, as the market for the new technology approaches saturation, the pace of substitution slows down. Sometimes, when the process is completed, the old technology continues to retain some specialized portion of the total market (i.e., a sub-market) for which it is particularly well adapted. In forecasting the course and speed of the substitution process especially when it has already begun and partially taken place, the simplest approach is to project a function having the appropriate S-shaped curve, using historical data to determine the free parameters of the function. While useful, especially where data are not available for a more sophisticated study, the simple curve-fitting techniques fail to take into account several important factors that affect economic and management decisions on the part of producers and intermediate users (as well as “final” consumers) and thereby influence the course which the substitution process is likely to take. To overcome this limitation, a simulation model has been developed at IR&T which allows some of these factors to be evaluated and incorporated explicitly and quantitatively. The model is described and its application is illustrated in the case of the substitution of plastic for glass in bottles. It is most applicable where the competing technologies are rather precisely defined, where a good deal of current technical and economic data are available, and where an in-depth analysis is desired. Because this particular forecast was made before the sudden precipitous increase in petroleum prices, which upsets the price relationships assumed in the forecast, there is discussion of the vulnerability of forecasts to political and other contra-economic developments.     

Comparative accuracy of forecasts of inflation: a Canadian study

An inaccurate forecast of inflation is costlier to economic agents when the inflation rate is high and volatile. In this situation, the use of more sophisticated and information-oriented forecasting models become economically efficient. We test this hypothesis by analysing the forecasting accuracy of vector auto-regressive (VAR), auto-regressive integrated moving average (ARIMA) and static expectation models. We use Canadian data and divide the post-sample forecasting period into four sub-periods, based on high/low and volatile/stable inflation. Prediction errors are compared for both short-term and long-term forecasts. Finally, the paper proposes a portfolio approach for obtaining a more accurate forecast of inflation.     

咸宁市经济发展的SWOT分析和预测

在对咸宁市经济发展状况进行SWOT分析的基础上,利用2001—2010年咸宁市GDP统计数据作为原始数据,建立灰色预测数学模型,检验模型的有效性,利用模型预测咸宁市2015年的GDP总量,预测结果：咸宁市2015年的GDP规模将达到1 050亿元。     

Economic policy uncertainty and the Chinese stock market volatility: new evidence

This study investigates the impacts of the economic policy uncertainty (EPU) indexes of China and the G7 countries on Chinese stock market volatility and further constructs a new diffusion index based on these indexes using principal component analysis (PCA) to achieve enhanced predictive ability. The in-sample results indicate that the EPU indexes of China and some of the G7 countries show a significantly negative impact on future volatility. Moreover, our constructed diffusion index also has a significantly negative impact. Furthermore, the out-of-sample results show that this diffusion index exhibits a significantly higher forecast accuracy than the EPU itself and combination forecasts. Finally, various robustness checks are consistent with our main conclusions. Overall, we construct a new and useful indicator that can substantially increase forecast accuracy with respect to the Chinese stock market.     

D-GMDH: A novel inductive modelling approach in the forecasting of the industrial economy

This work proposes a new forecasting model to analyse the economic development of Sichuan province of China. The model, which introduces the concept of diversity, is based on an improvement of the -GMDH algorithm. The new method, called D-GMDH, is compared with two ensemble approaches which are introduced by Dutta (2009), and D-GMDH is better than the two approaches in forecasting accuracy. D-GMDH is also applied to forecast the industrial added value of the Sichuan province. The obtained results are compared with those of the traditional GMDH model, GMDH combination model and the widely used ARMA model. The results show that D-GMDH has good prediction accuracy and is an effective means for economic forecasting when data is contaminated by noise.     

Forecast accuracy of small and large scale dynamic factor models in developing economies

Developing economies usually present limitations in the availability of economic data. This constraint may affect the capacity of dynamic factor models to summarize large amounts of information into latent factors that reflect macroeconomic performance. This paper addresses this issue by comparing the accuracy of two kinds of dynamic factor models at GDP forecasting for six Latin American countries. Each model is based on a dataset of different dimensions: a large dataset composed of series belonging to several macroeconomic categories (large scale dynamic factor model) and a small dataset with a few prescreened variables considered as the most representative ones (small scale dynamic factor model). Short‐term pseudo real time out‐of‐sample forecast of GDP growth is carried out with both models reproducing the real time situation of data accessibility derived from the publication lags of the series in each country. Results (i) confirm the important role of the inclusion of latest released data in the forecast accuracy of both models, (ii) show better precision of predictions based on factors with respect to autoregressive models and (iii) identify the most adequate model for each country according to availability of the observed data.     

IS model: A general model of forecasting and its applications in science and the economy

Expanding the work of Marchetti and Modis on Lotka-Volterra competition systems, a general model of Interaction Systems (IS) is introduced to describe the dynamics of multiple member interactions among different populations concerning not only biological systems but other types of systems as well. The new IS model provides us with a general framework of analysis and forecasting, where all parameters, variables, and interactions have real meaning, by using basic knowledge of each system.The proposed model can be applied to many different fields covering economic, business, social, physical, and other phenomena giving us both numerical estimates and qualitative insights of the system's dynamics. This is illustrated in two case studies. In the first case, the IS model is applied to elementary chemical reactions in order to quantify the reactions' kinetics. The result is the well known rate law of chemical reactions kinetics thus providing evidence of the proposed model's validity. In the second case, the IS model is applied to the global economy. The resulting model is tested against real global GDP data. The new IS model gave reliable estimates and proved to be considerably more accurate as compared to a similar forecast of global GDP based on the logistic growth model. Furthermore, the new model presented a basic framework of understanding the nature of major economic shifts, including the recent global recession of 2009, by studying the dynamic relationship between demand and supply.