A new family of copulas,with application to estimation of a production frontier system

Journal of Productivity Analysis - In the empirical literature, the analysis of aggregate productivity dynamics using firm-level productivity has mostly been based on changes in the mean of...     

A unified approach to bivariate discrete distributions

Here we introduce a bivariate generalized hypergeometric factorial moment distribution (BGHFMD) through its probability generating function (p.g.f.) whose marginal distributions are the generalized hypergeometric factorial moment distributions introduced by Kemp and Kemp (Bull Int Stat Inst 43:336–338,1969). Well-known bivariate versions of distributions such as binomial, negative binomial and Poisson are special cases of this distribution. A genesis of the distribution and explicit closed form expressions for the probability mass function of the BGHFMD, its factorial moments and the p.g.f.’s of its conditional distributions are derived here. Certain recurrence relations for probabilities, moments and factorial moments of the bivariate distribution are also established.     

A new approach to maximum likelihood estimation of sum-constrained linear models in case of undersized samples

Maximum likelihood procedures for estimating sum-constrained models like demand systems, brand choice models and so on, break down or produce very unstable estimates when the number of categories ( n ) is large as compared with the number of observations ( T ). In applied research, this problem is usually resolved by postulating the contemporaneous covariance matrix of the dependent variables to be known apart from a constant of proportionality. In this paper we develop a maximum likelihood procedure for sum-constrained models with large numbers of categories, which does not require too many observations, but nevertheless allows for n covariance parameters to be estimated freely.     

A sequential procedure to test three values of a binomial parameter

Sequential tests to decide among three binomial probabilities are needed in many situations, such as acceptance sampling used to determine the proportion of defective items and presence and absence sampling to decide whether pest species are causing economic damage to a crop such as corn. Approximate error probabilities associated with Armitage's (1950, JRSS B) method of simultaneously conducting three sequential probability ratio tests (SPRTs) are derived for the binomial distribution. These approximations provide a basis for adjusting the error rates used to establish the individual SPRTs so that the desired overall error rates are attained. Monte Carlo simulation is used to evaluate the revised procedure. Received: September 1998     

浅论一种新的检查算法

利用平均步长的方法,查找给定值的结点位置,使用C语言描述其算法,讨论了该算法的平均检索长度,与其他算法比较,得出了该算法的优劣结论。     

A new method to assess the degree of information rigidity using fixed-event forecasts

We propose a new method to explore the information content of fixed-event forecasts and estimate structural parameters that are keys to sticky and noisy information models. Estimation follows a regression-based framework in which estimated coefficients map one-to-one with parameters that measure the degree of information rigidity. The statistical characterization of regression errors explores the laws that govern expectation formation under sticky and noisy information, that is, they are coherent with the theory. This strategy is still unexplored in the literature and potentially enhances the reliability of inference results. The method also allows linking estimation results to the signal-to-noise ratio, an important parameter of noisy information models. This task cannot be accomplished if one adopts an “agnostic” characterization of regression errors. With regard to empirical results, they show a substantial degree of information rigidity in the countries studied. They also suggest that the theoretical characterization of regression errors yields a more conservative picture of the uncertainty surrounding parameter estimates.     

A new method to verify Bitcoin bubbles: Based on the production cost

As the first kind of digital cryptocurrency, the Bitcoin price cycle provides an opportunity to test bubble theory in the digital currency era. Based on the existing asset bubble theory, we verified the Bitcoin bubble based on the production cost with the application of VAR and LPPL models, and this method achieved good predictive power. The following conclusions are reached: (1) PECR is constructed to depict the deviation degree between the price and production cost, while BC is used to illustrate the bubble size in the price, and both are effective measures; (2) the number of unique addresses is a suitable measure of the use value of Bitcoin, and this result has passed the Granger causality test; (3) PECR and BC are verified via the LPPL model, and the next large bubble is expected in the second half of 2020. Considering that Bitcoin will see 'output halved' in May 2020, this prediction is a high-probability event.     

A new practice-driven approach to develop software in a cyber-physical system environment

Cyber-physical system (CPS) is an emerging area, which cannot work efficiently without proper software handling of the data and business logic. Software and middleware is the soul of the CPS. The software development of CPS is a critical issue because of its complicity in a large scale realistic system. Furthermore, object-oriented approach (OOA) is often used to develop CPS software, which needs some improvements according to the characteristics of CPS. To develop software in a CPS environment, a new systematic approach is proposed in this paper. It comes from practice, and has been evolved from software companies. It consists of (A) Requirement analysis in event-oriented way, (B) architecture design in data-oriented way, (C) detailed design and coding in object-oriented way and (D) testing in event-oriented way. It is a new approach based on OOA; the difference when compared with OOA is that the proposed approach has different emphases and measures in every stage. It is more accord with the characteristics of event-driven CPS. In CPS software development, one should focus on the events more than the functions or objects. A case study of a smart home system is designed to reveal the effectiveness of the approach. It shows that the approach is also easy to be operated in the practice owing to some simplifications. The running result illustrates the validity of this approach.     

Structural production layer decomposition: a new method to measure differences between MRIO databases for footprint assessments

Recent empirical assessments revealed that footprint indicators calculated with various multi-regional input–output (MRIO) databases deliver deviating results. In this paper, we propose a new method, called structural production layer decomposition (SPLD), which complements existing structural decomposition approaches. SPLD enables differentiating between effects stemming from specific parts in the technology matrix, e.g. trade blocks vs. domestic blocks, while still allowing to link the various effects to the total region footprint. Using the carbon footprint of the EU-28 in 2011 as an example, we analyse the differences between EXIOBASE, Eora, GTAP and WIOD. Identical environmental data are used across all MRIO databases. In all model comparisons, variations in domestic blocks have a more significant impact on the carbon footprint than variations in trade blocks. The results provide a wealth of information for MRIO developers and are relevant for policy makers designing climate policy measures targeted to specific stages along product supply chains.     

Taking a new contour: A novel approach to panel unit root tests

The paper introduces a novel approach to testing for unit roots in panels, which takes a new contour that is drawn along the line given by the equi-squared-sum instead of the traditional one given by the equi-sample-size. We show in the paper that the distributions of the unit root tests are asymptotically normal along the new contour under both the null and the local-to-unity alternatives. Subsequently, we demonstrate that this startling finding may be exploited constructively to invent tools and methodologies for effective inferences in panel unit root models. Simulations show that our approach works quite well in finite samples.     

A new approach to estimating a profit frontier using the censored stochastic frontier model

The translog profit functional form is widely used to study technical efficiency for banks. Although this functional form is known as being flexible, it is not applicable to those banks incurring economic losses. The recently developed approach, i.e., the censored stochastic frontier model (CSFM), by Tsay et al. (2013) appears to be superior to existing approaches, since CSFM does not need to transform negative profit into positive profit before taking the natural logarithm. The transformation with respect to the profit variable tends to bias the parameter estimates of the profit frontier and the subsequent profit efficiency measure. We show that the parameter estimates of CSFM have the desirable statistical properties. Moreover, empirical results reveal that the mean profit efficiency of CSFM is more robust than those models using transformed profits across the sub-periods 1991–1998 and 1999–2009.     

Modelling the iron ore price index: A new perspective from a hybrid data reconstructed EEMD-GORU model

As iron ore is the fundamental steel production resource, predicting its price is strategically important for risk management at related enterprises and projects. Based on a signal decomposition technology and an artificial neural network, this paper proposes a hybrid EEMD-GORU model and a novel data reconstruction method to explore the price risk and fluctuation correlations between China’s iron ore futures and spot markets, and to forecast the price index series of China’s and international iron ore spot markets from the futures market. The analysis found that the iron ore futures market in China better reflected the price fluctuations and risk factors in the imported and international iron ore spot markets. However, the forward price in China’s iron ore futures market was unable to adequately reflect the changes in the domestic iron ore market, and was therefore unable to fully disseminate domestic iron ore market information. The proposed model was found to provide better market risk perceptions and predictions through its combinations of the different volatility information in futures and spot markets. The results are valuable references for the early-warning and management of the related enterprise project risks.     

A new approach to the existence and regularity of linear equilibrium in a noisy rational expectations economy

This paper gives a new approach to show the existence and regularity of linear equilibrium established by Lou ⓡ al. (2019) for a noisy rational expectations economy. Different from the existing method which essentially requires to find a fixed point of a system of nonlinear algebraic equations, the new approach is operated directly on an alternative form of market-clearing conditions. One main advantage of the new approach is that besides homogeneous-valuation economies, it can also handle the existence of equilibrium in economies with heterogeneous valuations where the existing method for dealing with homogeneous-valuation economies fails to work.     

Stock price reactions to stock dividend announcements: A case from a sluggish economic period

The 2007 financial crisis and the Great Recession that followed resulted in a loss of confidence among investors, and regaining their full trust and confidence has been a challenge for companies. Although economic growth has been volatile throughout the postwar World War II period, recent growth (2008–2015) has been remarkably weaker than in the previous low-growth period (1974–1995). The 2006–2015 period is often characterized by sluggish economic growth. This study investigates stock price reactions to stock dividend announcements, 30 days before and after the announcement dates, of publicly traded companies in the period 2006–2012. We use an event study methodology for 460 events and daily stock price data for companies in the CRSP historical data set. The study shows a significant reaction in stock prices around the event date. On average, stock prices reacted positively to stock dividend announcements. However, compared to previous findings of abnormal returns (5.9%), results from this study show small abnormal returns (about 1.81%) attributable to stock dividend announcements that are cumulative of the announcement day and up to 3-day post-announcement days. Our estimates are even lower than the 2.01% stock price reaction obtained in the 1987–1996 period.     

Relating ultrasonic vocalizations from a pair of rats to individual behavior: A composite link model approach

Ultrasonic vocalizations (USVs) are crucial in the social behavior of rats. We aim to relate USV rates of pairs of rats to individual activity in an automated home cage (PhenoTyper®) where USVs are recorded per pair and not per individual. We propose a composite link model approach to parametrize a mechanistic “sum‐of‐rates” model in which the pair's USV rate is the sum of the USV rates of individuals depending on their own behavior. In generalized linear models (GLMs), the individual's USV rates are multiplied. We verified through simulation that composite link model gave lower Poisson deviance than GLM. We analyzed the data from an experiment in which half of the cages did allow the pairs to interact (Pair Housing) and the other half did not (Individual Housing). The “sum‐of‐rates” model fits best for Individual Housing and GLM for Pair Housing. An additional simulation study strongly suggests that interaction between rats changes the underlying mechanism for vocalization behavior.     

A methodology to rank enterprise application integration platforms from a performance perspective: an analytic hierarchy process-based approach

ABSTRACT

Companies’ software ecosystems comprise applications that support their business processes. Frequently, these applications have been developed with different technologies and with no concern about integration. Integration platforms are tools that facilitate the development and execution of integration solutions. In this article, we propose a methodology to support software engineers in the decision-making process for an integration platform when performance is a central requirement. The proposed methodology adds objective criteria for performance assessment purposes and has been used to rank the five most popular integration platforms in order to prove its feasibility.