基于Visual Basic6.0的测控软件设计

对VisualBasic6.0在测控系统软件编程方面的应用进行了探讨,并对其数据处理,I/O操作,动态链接库DLL的编制与调用,数据库管理系统的接口设计、建立、数据格式的转换等方面进行了研究。给出了Windows应用程序建立DLL的方法与步骤,对于在VisualBasic程序中如何应用DLL进行了讨论。     

The Global Determinants of Direct Office Real Estate Returns

We investigate the determinants of direct office real estate returns by analyzing rents, capital appraisals, and total returns. A recently compiled global database of major cities in Asia, Europe, and the United States provides a unique opportunity to give a macro-view on the effects of economic growth and supply and demand factors on nominal real estate returns. The global database provides quarterly observations from 1986 to 1999. To address the smoothness problem of appraisal-based price data and regulated rents, we employ the Generalized Method of Moments to estimate a dynamic panel-data model. The model allows us to combine the cross-sectional and time-series dimension in our quarterly data. We find that gross domestic product, inflation, unemployment, vacancy rate, and the available stock all have an effect on real estate returns.     

异步电机教学实验数据处理系统

本文介绍异步电机空载、短路、负载实验数据处理的数学方法和软件设计方法步骤,形成了实验教学软件。     

Real estate return correlations: Real-world limitations on relationships inferred from NCREIF data

Correlation estimates for returns between individual properties are subject to large inherent uncertainties due to limits on the amount of data that is likely to be available for the foreseeable future. After allowance for correlation sampling error, it is impossible to distinguish on an ex ante basis between the risk-reduction capabilities of mean-variance portfolio selection models and naive diversification without regard to property type or geographical location. The naive portfolio diversification strategies of typical institutional real estate portfolio managers are rational responses to limitations on the informational content of statistical analyses of historical real estate data.     

Reduced Tax Progressivity in Norway in the Nineties: The Effect from Tax Changes

The inequality in pre-tax income increased in Norway in the 1990s, while the concentration of taxes remained largely unaltered. This means that tax progressivity has decreased in the period, as measured by summary indices of tax progressivity. In this paper I analyze individual income data to ascertain whether tax changes in the period can explain the observed decrease in tax progressivity. As marginal tax rates at high income levels have been substantially reduced in the period, for instance through the tax reform of 1992, it is expected that tax changes may have influenced the degree of inequality in pre-tax incomes. This behavioral effect is examined by deriving estimates of the elasticity of gross income with respect to the net-of-tax rate, obtained from various panel data regressions. The tax changes may also have shifted the distributional burden of taxes for unaltered level of pre-tax income inequality. In order to identify this (direct) effect of tax-law alterations, the same fixed distribution of pre-tax income is exposed to various tax-laws in the period.     

Industry aspects of takeovers and divestitures: Evidence from the UK

This paper examines takeover and divestiture activity at the industry level for the population of UK firms over the period 1986–2000. Consistent with US research, takeovers in the UK cluster both across industries and over time. The evidence for divestitures indicates clustering across industries only. The paper further investigates whether broad and specific industry shocks (e.g., growth, free cash flow, concentration, deregulation, foreign competition, technology, stock market performance) explain takeover and divestiture clustering at the industry level. The results suggest that broad shocks increase (decrease) the likelihood of takeovers (divestitures), although not significantly for takeovers. Specific industry shocks that increase the likelihood of takeover activity include low growth, the threat of foreign competition and high stock market performance. For divestitures, high industry concentration and deregulation increase activity. Little evidence is found for deregulation as a significant factor in explaining takeover activity.     

Machine learning in individual claims reserving

Machine learning techniques make it feasible to calculate claims reserves on individual claims data. This paper illustrates how these techniques can be used by providing an explicit example in individual claims reserving.     

Financial System and Housing Price

The 2007/2008 US financial crisis is related to the securitization of mortgage loans and the housing-price boom and bust. In this article, we test the hypothesis that housing-price change is related to the development of the financial system. Using panel data for 23 countries from 1988 to 2012, we have found that the housing-price growth rate increases as the financial system moves a bank orientation to a market orientation. The policy implication is that the government should beware sudden increases in the capital market relative to the banking sector. Especially, more sophisticated financial supervision with respect to housing-price movement is required when a bank-based financial system progresses quickly to a market-oriented financial system.     

Dynamic Currency Linkages and Their Determinants: An Empirical Study for East Asian Economic Community Region

In this article, Copula GARCH models have been employed to study the inter-temporal process of currency market co-movements between ASEAN+6 countries (referred to in this study as East Asian Economic Community) and ASEAN+6 currency market index. Empirical results show that the sample countries of the region exhibit varying levels of currency co-movements with the Asian benchmark. Markov regime switching results show that many of the countries which had high dependences with the regional currency index as was found in copula estimations had also overlapping currency market cycles. Using Principal Component Analysis, we find that three statistical factors explain exchange rate co-movements which came out to be trade linkages, economic risk, and currency market openness in our dynamic panel data estimation.