Alternative procedures for converting qualitative response data to quantitative expectations: An application to Australian manufacturing

This paper analyses and extends alternative procedures for converting qualitative expectations responses to quantitative expectations. A number of conversion procedures is investigated, including the probability model, the time-varying parameter probability model, and the regression approach. The informational content of the survey expectations is compared with simple time series models. It is found that the expectations models are superior for many series, both in terms of producing lower forecast root mean square error (RMSE) values and in detecting turning points in the actual data. Survey expectations are also tested for rational expectations in aggregate using the orthogonality test.     

Institutional investors and industrial relations data: an empirical survey

Financial institutions play a major role in investing funds in the shares of individual companies. To what extent do investment managers and analysts take account of industrial relations information when making their decisions?     

Combining forecasts: An application to elections

We summarize the literature on the effectiveness of combining forecasts by assessing the conditions under which combining is most valuable. Using data on the six US presidential elections from 1992 to 2012, we report the reductions in error obtained by averaging forecasts within and across four election forecasting methods: poll projections, expert judgment, quantitative models, and the Iowa Electronic Markets. Across the six elections, the resulting combined forecasts were more accurate than any individual component method, on average. The gains in accuracy from combining increased with the numbers of forecasts used, especially when these forecasts were based on different methods and different data, and in situations involving high levels of uncertainty. Such combining yielded error reductions of between 16% and 59%, compared to the average errors of the individual forecasts. This improvement is substantially greater than the 12% reduction in error that had been reported previously for combining forecasts.     

Comparisons of aggregation procedures for interaction data: An illustration using a college student international flow table

Various approaches for developing regional schemes on the basis of geographic interaction data are discussed, using a 46 × 46 international flow table of college students as an example. The hierarchical clustering procedure employed by Masser and Brown to study movement data for London and Liverpool is compared with that utilized by Slater to analyze internal migration in several nations and is found to be more successful in the sense of explained interaction, a criterion Masser and Brown maximize in a stepwise—not necessarily optimal—manner. Slater's method, however, appears to be less subject to chaining—the sequential growth of a cluster— and more productive of distinct subgroups. It can also be interpreted as the fitting of a tree structure to a dissimilarity matrix. Both techniques are shown to yield highly significant functional regions, by comparing their results with those obtained through a large number of random partitionings of the 46 nations. The substantial value of the Ford-Fulkerson network flow algorithm in optimal partitioning and hierarchical clustering is discussed. This algorithm can also be used to define nodal in- and out-migration regions—i.e. collections of nations that have fewer people entering or leaving them as a whole than their nodal nations. To determine functional regions, the flow table is first doubly-standardized to have all row and column sums equal. Nodal regions—which cannot be hierarchically ordered—are found through study of the unadjusted flows themselves. Political, linguistic and geographic influences explain many of the international groupings obtained.     

大数据在工业制造业的应用与研究

大数据时代,工业领域将会以想像不到的速度创新,呈现出新的技术、新的产品、新的服务和新的业态。各行各业的决策正在从业务驱动转变数据驱动。事实上,无论工业4.0还是工业互联网,其主要特征都是智能和互联,而主旨都在于通过充分利用信息通讯技术,把产品、机器、资源和人有机结合在一起,推动制造业向基于大数据分析与应用基础上的智能化转型。智能制造时代的到来,也意味着工业大数据时代的到来。工业大数据的应用,将成为未来制造业大创新的关键要素,也是目前全球工业转型必须面对的重要课题。     

数据挖掘在证券经纪人管理系统中的应用

证券市场的持续低迷对证券公司的经营策略提出了新的要求，客户关系管理理念也随之流行。文章首先从应用角度出发介绍了数据挖掘技术的基本概念，以及证券行业对客户关系管理方面的需求。然后用实例说明了数据挖掘技术在证券经纪人管理系统中的实际应用。     

热电偶、热电阻在工业生产中的应用

文章指出现代工业生产中关于热电偶、热电阻使用的方法和使用中出现的一些问题,并从生产安全以及产品质量要求方面着重说明了热电偶、热电阻类型匹配所需使用温度范围的重要性。同时也对热电偶、热电阻运行过程中出现的问题提出了解决方案,确保生产安全。     

数据挖掘在证券经纪人管理系统中的应用

证券市场的持续低迷对证券公司的经营策略提出了新的要求,客户关系管理理念也随之流行。文章首先从应用角度出发介绍了数据挖掘技术的基本概念,以及证券行业对客户关系管理方面的需求。然后用实例说明了数据挖掘技术在证券经纪人管理系统中的实际应用。     

Efficiency aggregation with enhanced Russell measures in data envelopment analysis

In aggregation for data envelopment analysis (DEA), a jointly determined aggregate measure of output and input efficiency is desired that is consistent with the individual decision making unit measures. An impasse has been reached in the current state of the literature, however, where only separate measures of input and output efficiency have resulted from attempts to aggregate technical efficiency with the radial measure models commonly employed in DEA. The latter measures are “incomplete” in that they omit the non-zero input and output slacks, and thus fail to account for all inefficiencies that the model can identify. The Russell measure eliminates the latter deficiency but is difficult to solve in standard formulations. A new approach has become available, however, which utilizes a ratio measure in place of the standard formulations. Referred to as an enhanced Russell graph measure (ERM), the resulting model is in the form of a fractional program. Hence, it can be transformed into an ordinary linear programming structure that can generate an optimal solution for the corresponding ERM model. As shown in this paper, an aggregate ERM can then be formed with all the properties considered to be desirable in an aggregate measure—including jointly determined input and output efficiency measures that represent separate estimates of input and output efficiency. Much of this paper is concerned with technical efficiency in both individual and system-wide efficiency measures. Weighting systems are introduced that extend to efficiency-based measures of cost, revenue, and profit, as well as derivatives such as rates of return over cost. The penultimate section shows how the solution to one model also generates optimal solutions to models with other objectives that include rates of return over cost and total profit. This is accomplished in the form of efficiency-adjusted versions of these commonly used measures of performance.     

Assessing inherent model bias: An application to native displacement in response to immigration

There is a long-standing debate among academics about the effect of immigration on native internal migration decisions. If immigrants displace natives this may indicate a direct cost of immigration in the form of decreased employment opportunity for native workers. Moreover, displacement would also imply that cross-region analyses of wage effects systematically underestimate the consequences of immigration. The widespread use of such area studies for the US and other countries makes it especially important to know whether a native internal response to immigration truly occurs. This paper introduces a microsimulation methodology to test for inherent bias in regression models that have been used in the literature. We show that some specifications have built biases into their models, thereby casting doubt on the validity of their results. We then provide a brief empirical analysis with a panel of observed US state-by-skill data. Together, our evidence argues against the existence of native displacement. This implies that cross-region analyses of immigration’s effect on wages are still informative.     

Frontier production functions,technical efficiency and panel data: With application to paddy farmers in India

Frontier production functions are important for the prediction of technical efficiencies of individual firms in an industry. A stochastic frontier production function model for panel data is presented, for which the firm effects are an exponential function of time. The best predictor for the technical efficiency of an individual firm at a particular time period is presented for this time-varying model. An empirical example is presented using agricultural data for paddy farmers in a village in India.This article is a revision of the Invited Paper presented by the senior author in the Productivity and Efficiency Analysis sessions at the ORSA/TIMS 30th Joint National Meeting, Philadelphia, Pennsylvania, 29–31 October 1990. We have appreciated comments from Martin Beck, Phil Dawson, Knox Lovell and three anonymous referees. We gratefully acknowledge the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) for making available to us the data obtained from the Village Level Studies in India.     

Scanner data, time aggregation and the construction of price indexes

We examine the impact of time aggregation on price change estimates for 19 supermarket item categories using scanner data. Time aggregation choices lead to a difference in price change estimates for chained indexes which ranged from 0.28% to 29.73% for a superlative index and an incredible 14.88%-46,463.71% for a non-superlative index. Traditional index number theory appears to break down with weekly data, even for superlative indexes. Monthly and (in some cases) quarterly time aggregation were insufficient to eliminate downward drift in superlative indexes. To eliminate drift, a novel adaptation of a multilateral index number method is proposed.     

An index aggregation approach to comparing the overall performance of emerging and developed countries

An index aggregation approach is proposed to carry out comparisons of BRICSAM, a populous rapidly growing economic group consisting of Brazil, Russia, India, China, South Africa, Association of South-East Asian Nations (ASEAN), and Mexico with Group of Seven (G7), the most developed country club including Canada, France, Italy, Japan, Germany, United Kingdom and the United States. It is estimated that by 2050 the accelerated economic activity of BRICSAM could have significant impact on investment flows, legal and regulatory frameworks, the stability of political institutions, human capital and migration flows, competition policy, intellectual property rights, and social and environmental policies. The comparison analyses of BRICSAM and G7 countries could assist people to better understand the status quo of these countries in the global economy and international system, particularly in the areas of economics and responsible activities such as sustainable development, global commitments and transparent practices. Many country-ranking indices, such as the indices given in the global competitiveness report by the World Economic Forum, and the environmental sustainability index by Yale University, constitute evaluations of countries from different perspectives. This paper proposes a data envelopment analysis-based approach to aggregate different ranking indices for BRICSAM and the G7 countries. The approach can provide a fair overall assessment of a country's standing by maximizing its possibility of obtaining the best possible result.     

Housing prices and the business cycle: An empirical application to Hong Kong

This paper develops a two-agent, two-sector, open-economy DSGE model with a housing-market sector and a borrowing constraint. Contrary to standard conventions, domestic households are allowed to invest in foreign housing and vice versa. Using Bayesian methods, the model is applied to data for Hong Kong. We identify strong and robust housing wealth effects, and show that property prices are mainly driven by intratemporal preference perturbations rather than by disturbances in financial frictions or price mark up shocks. These disturbances also explain a non-negligible part of the volatility of consumption, GDP and employment.     

Productivity differences in multiple output industries: An empirical application to electricity distribution

Given that electricity distribution is undertaken via a network, it is expected that costs of production are affected both by the nature of the network and the volume of physical output distributed via the network. This two-dimensional concept of firm size, that is involving network size (number of customers) and the level of physical output (kWh), also corresponds to the distinction between productivity measures of returns to density and returns to scale.This approach has been used to specify a restricted multioutput cost function and to estimate this function for the Norwegian electricity distribution industry through the use of a flexible functional form (translog). The results indicate that no economies of scale are present in the industry even for small plants when measured correctly, but that economics of density are present.