基于TCP/IP网络的远程监控系统的原理与实现

介绍基于TCP／IP协议的可连接广域网的远程访问控制原理和软件实现．着重解决串行通信类和点对点通信实现两大关键问题，前作不仅提供了通用控件，还专门设计了灵活的自定义类，并附以实现此功能的程序清单；在点对点通信模块，制作了典型的Socket通信流程图，以适应远程监控系统在各个方面的灵活应用．     

Using pilot study information to increase efficiency in clinical trials

It is often necessary to conduct a pilot study to determine the sample size required for a clinical trial. Due to differences in sampling environments, the pilot data are usually discarded after sample size calculation. This paper tries to use the pilot information to modify the subsequent testing procedure when a two-sided t$t$-test or a regression model is used to compare two treatments. The new test maintains the required significance level regardless of the dissimilarity between the pilot and the target populations, but increases the power when the two are similar. The test is constructed based on the posterior distribution of the parameters given the pilot study information, but its properties are investigated from a frequentist's viewpoint. Due to the small likelihood of an irrelevant pilot population, the new approach is a viable alternative to the current practice.     

COMMON FEATURES IN TIME SERIES WITH BOTH DETERMINISTIC AND STOCHASTIC SEASONALITY

This paper extends the notions of common cycles and common seasonal features to time series having deterministic and stochastic seasonality at different frequencies. The conditions under which quarterly time series with these characteristics have common features are investigated, various representations are presented and statistical inference is discussed. Finally, the analysis is applied to study comovements between different components of consumption and income using UK data.     

BAYESIAN ANALYSIS OF A FRACTIONAL COINTEGRATION MODEL

The concept of fractional cointegration, whereby deviations from an equilibrium relationship follow a fractionally integrated process, has attracted some attention of late. The extended concept allows cointegration to be associated with mean reversion in the error, rather than requiring the more stringent condition of stationarity. This paper presents a Bayesian method for conducting inference about fractional cointegration. The method is based on an approximation of the exact likelihood, with a Jeffreys prior being used to offset identification problems. Numerical results are produced via a combination of Markov chain Monte Carlo algorithms. The procedure is applied to several purchasing power parity relations, with substantial evidence found in favor of parity reversion.     

Housing and the business cycle in South Africa

This paper examines the housing-output growth nexus in South Africa by accounting for the time variation in the causal link with a bootstrapped rolling Granger non-causality test. We use quarterly data on real gross domestic product, real house prices, real gross fixed capital formation and number of building plans passed. Our data span 1971Q2–2012Q2. Using full sample bootstrap Granger causality tests, we find a uni-directional causality from output to number of building plans passed; a uni-directional causality from real house price to output and a bi-directional causal link between residential investment and output. However, using parameter stability tests, we show that estimated VARs are unstable, thus full-sample Granger causality inference may be invalid. Hence, we use a bootstrap rolling window estimation to evaluate Granger causality between the housing variables and the growth rate. In general, we find that the causality from housing to output and, vice versa, differ across different sample periods due to structural changes. Specifically speaking, house price is found to have the strongest causal relationship with output compared to residential investment and number of building plans passed, with real house price showing predictive ability in all but one downward phase of the business cycle during this period.     

Does inflation targeting matter for output growth? Evidence from industrial and emerging economies

This paper examines the effects of inflation targeting (IT) on output growth over the “globalization years” of 1986-2004. Employing static panel data methods that control for traditional growth determinants, trade openness and financial globalization, the paper finds that the adoption of a fully fledged IT regime results in higher output income per capita for industrial and emerging economies. However, under dynamic model specifications, the estimated long-run output impact of inflation targeting for emerging market economies is found to be lower than in the case of static models. We argue that this might be due to the long lags until the full effects of greater credibility are felt in the real economy and the fact that emerging market economies adopted the regime much later than industrial economies.     

Involuntary job loss and changes in personality traits

Economists consider personality traits to be stable, particularly throughout adulthood. However, evidence from psychological studies suggests that the stability assumption may not always be valid, as personality traits can respond to certain life events. Our paper analyzes whether and to what extent personality traits are malleable over a time span of eight years for a sample of working individuals. Furthermore, we specifically look at changes in personality traits after a major adverse life event: involuntary job loss. We use data from the German Socio-Economic Panel Study (SOEP) from 2004 to 2014 – a period over which individuals’ Big Five personality inventory was measured three times. Our dataset allows us to exploit detailed employment information, particularly reasons for job termination and unemployment spells. We focus solely on plant closures as a reason for job termination. Job loss due to plant closure is widely used as a relatively exogenous event to identify causal effects. Our results suggest that personality traits are indeed malleable during adulthood. Although the Big Five measures are relatively stable within the overall population of workers, we find an increase in openness, that is, the willingness to seek new experiences, for the average displaced worker. This increase, however, is fully driven by individuals with high educational attainment and by those who find a new job immediately after dismissal. The other dimensions of the Big Five personality inventory remain nearly unchanged after an involuntary job loss. Our findings hold for a number of robustness checks and are supported by the results of a falsification test using a placebo treatment.     

THE EFFECT OF JOINT CUSTODY ON FAMILY OUTCOMES

Since the 1970s almost all US states have introduced a form of joint custody after divorce. I analyze the causal effect of these custody law reforms on different family outcomes. My identification strategy exploits the different timing of reforms across the US states. Estimations based on state panel data suggest that the introduction of joint custody led to an increase in marriage rates, an increase in overall fertility (including a shift from nonmarital to marital fertility), and an increase in divorce rates for older couples. Accordingly, female labor market participation decreased. Further, male suicide rates and domestic violence fell in treated states. The empirical evidence is consistent with the hypothesis that joint custody increased the relative bargaining power of men within marriage.     

Structural vector autoregressive analysis for cointegrated variables

Summary Vector autoregressive (VAR) models are capable of capturing the dynamic structure of many time series variables. Impulse response functions are typically used to investigate the relationships between the variables included in such models. In this context the relevant impulses or innovations or shocks to be traced out in an impulse response analysis have to be specified by imposing appropriate identifying restrictions. Taking into account the cointegration structure of the variables offers interesting possibilities for imposing identifying restrictions. Therefore VAR models which explicitly take into account the cointegration structure of the variables, so-called vector error correction models, are considered. Specification, estimation and validation of reduced form vector error correction models is briefly outlined and imposing structural short- and long-run restrictions within these models is discussed. I thank an anonymous reader for comments on an earlier draft of this paper that helped me to improve the exposition.