CREDIBILITY, MACROECONOMIC FUNDAMENTALS AND MARKOV REGIME SWITCHES IN THE EMS

The main objective of this paper is to use the Markov regime‐switching modelling framework to describe and analyse the credibility of a number of countries participating in the European Monetary System during 1980–1998. Our credibility indicator, based on Hughes Hallet et al.'s (1997) methodology, is subject to discrete regime shifts and is made dependent on macroeconomic fundamentals. We carry out extensive testing to assess the specification of the Markov regime‐switching model and the potential existence of permanent breaks. A contribution of our paper is the specification of a multivariate Markov switching model that allows us to examine whether macroeconomic variables have asymmetric effects on credibility. Another contribution is the specification of a regime‐switching model with time‐varying transition probabilities, which enables us to determine whether changes in macroeconomic variables can trigger switches between the low and high credibility regimes. We find strong evidence of regime switching behaviour in all countries. Both the level of credibility and the transition probabilities display an asymmetric response to changes in macroeconomic variables, with the stance of fiscal policy exerting the most systematic influence in all countries.     

UNEMPLOYMENT, HYSTERESIS AND TRANSITION

In this paper, we quantify the degree of persistence in the unemployment rates of transition countries using a variety of methods benchmarked against the EU. Initially, we work with the concept of linear ‘Hysteresis’ as described by the presence of unit roots in unemployment as in most empirical research on this area. Given that this is potentially a narrow definition, we also take into account the existence of structural breaks and nonlinear dynamics in unemployment. Finally, we examine whether CEECs' unemployment presents features of multiple equilibria, that is, if it remains locked into a new level whenever some structural change or sufficiently large shock occurs. Our findings show that, in general, we can reject the unit‐root hypothesis after controlling for structural changes and business‐cycle effects, but we can observe the presence of a high and low unemployment equilibria. The speed of adjustment is faster for CEECs than the EU, although CEECs tend to move more frequently between equilibria.     

纽约股票市场对中国A股市场的影响

首先，本文考察了纽约股市波动对中国A股市场的影响。一般认为，中国的A股市场由于严格的资本控制而免受外国影响。但是，通过月度、每周、每日的样本数据（1992年到2004年），经过季节性调整和汇率变动调整后，我们发现上海和深圳A股市场的变动与美国股票价格指数变动相一致。其次，我们考察国家贝塔值（country beta）在马尔可夫转换误差修正模型中的动态关系。对中国市场来说，国家贝塔值和错误纠正项的重要性紧密相连。在东亚金融危机之前，美国市场对中国A股市场的影响普遍存在，而东亚金融危机产生后，则是通过国家贝塔值来影响中国股市的收益。     

Estimating the Size of a Criminal Population from Police Records Using the Truncated Poisson Regression Model

The truncated Poisson regression model is used to arrive at point and interval estimates of the size of two offender populations, i.e. drunk drivers and persons who illegally possess firearms. The dependent capture–recapture variables are constructed from Dutch police records and are counts of individual arrests for both violations. The population size estimates are derived assuming that each count is a realization of a Poisson distribution, and that the Poisson parameters are related to covariates through the truncated Poisson regression model. These assumptions are discussed in detail, and the tenability of the second assumption is assessed by evaluating the marginal residuals and performing tests on overdispersion. For the firearms example, the second assumption seems to hold well, but for the drunk drivers example there is some overdispersion. It is concluded that the method is useful, provided it is used with care.     

Multiple generation product life cycle predictions using a novel two-stage fuzzy piecewise regression analysis method

Product life cycle (PLC) prediction plays a crucial role in strategic planning and policy definition for high-technology products. Forecast methodologies which can predict PLCs accurately can help to achieve successful strategic decision-making, forecasting, and foresight activities in high-technology firms, research institutes, governments, and universities. Over the past few decades, even though analytic framework strategies have been proposed for production, marketing, R&D (research and development), and finance, aiming at each stage of PLCs, forecast methodologies with which to predict PLCs are few. The purpose of this research is to develop a novel forecast methodology to allow for predictions of product life time (PLT) and the annual shipment of products during the entire PLC of multiple generation products. A novel two-stage fuzzy piecewise regression analysis method is proposed in this paper. In the first stage, the product life-time of the specific generation to be analyzed will be predicted by the fuzzy piecewise regression line that is derived based upon the product life-time of earlier generations. In the second stage of the forecast methodology, the annual shipment of products of the specified generation will be predicted by deriving annual fuzzy regression lines for each generation, based upon the historical data on the earlier generations' products. An empirical study predicting the life-time and the annual shipment of the 16 Mb (Mega bit) DRAM (Dynamic Random Access Memory) PLC is illustrated to validate the analytical process. The results demonstrate that two-stage fuzzy piecewise regression analysis can predict multiple generation PLT and PLC precisely, thereby serving as a foundation for future strategic planning, policy definitions and foresights.     

结构异质性对中国能源高质量发展的影响研究

基于结构异质性对能源高质量发展影响的理论分析,使用稀疏主成分分析方法测度中国能源高质量发展水平,构建中国和八大经济区域面板分位数回归模型,实证研究了结构异质性对中国能源高质量发展的影响。结果表明：2003—2020年中国能源高质量发展水平有所提升,但仍存在明显的区域发展不平衡问题,西部地区和北部沿海地区的能源高质量发展水平更高。产业结构与能源高质量发展水平呈负相关关系,能源消费结构、资本配置结构与能源高质量发展水平呈正相关关系。     

回归分析在土地估价中的应用

回归分析是一种统计学方法，在地价分析与测算中得到广泛应用。本文从统计学的角度阐明了回归分析的原理，并介绍了如何建立回归方程解决土地估价中出现的有关问题。     

探究“新零销售”模式下影响销售量的相关因素

在新零销售模式的推动下,客户越来越倾向于消费个性化的商品。为了精准预测客户的消费需求,论文以单款单色产品为研究对象,通过建立多元回归分析的数学模型,来探究影响商品销售量的相关因素。经过分析发现,除了一些定性因素外,定量因素对销售量也产生了一定的影响,其中实际花费总金额、实际销售单价、库存数等定量因素对销售量的影响较大,且各个变量之间具有相关性,所以电商平台应特别关注这三个变量的影响。     

Prediction of the Indian summer monsoon using a stacked autoencoder and ensemble regression model

The study of climatic variables that govern the Indian summer monsoon has been widely explored. In this work, we use a non-linear deep learning-based feature reduction scheme for the discovery of skilful predictors for monsoon rainfall with climatic variables from various regions of the globe. We use a stacked autoencoder network along with two advanced machine learning techniques to forecast the Indian summer monsoon. We show that the predictors such as the sea surface temperature and zonal wind can predict the Indian summer monsoon one month ahead, whereas the sea level pressure can predict ten months before the season. Further, we also show that the predictors derived from a combination of climatic variables can outperform the predictors derived from an individual variable. The stacked autoencoder model with combined predictors of sea surface temperature and sea level pressure can predict the monsoon (June-September) two months ahead with a 2.8% error. The accuracy of the identified predictors is found to be superior to the state-of-the-art predictions of the Indian monsoon.     

Distributional assumptions and a test of the dual labor market hypothesis

Recent application of the switching regression model to allocate workers into the primary and secondary labor markets is considered to be the best solution to the classification problem of the empirical testing of the dual labor market theory. In such models, normality of the error terms is assumed. This paper adopts the switching regression model to test the dual labor market theory by assuming different distributions of the error terms. The test results strongly support the dual labor market theory regardless of the assumption one makes about the error terms. However, the results indicate that different distribution can lead to different percentage distributions of workers in the two segments. In particular, the normal distribution generates more workers in the primary segment than the non-normal distributions. Therefore, care must be taken not to generalize the type of industries or occupations that fall under the primary and secondary segments. First version received: October 2000/Final version received: March 2002 RID="*" ID="*"  I would like to thank Kevin Lang, Robert Marshall, and two anonymous referees for their helpful comments. I am grateful for comments received from the session participants of the Western Economic Association International Conference, San Francisco, CA, June 28–July 2, 1996, and the Midwest Economic Association Conference, Kansas City, 1997. I thank George Bonney, the Chief Statistician of Fox Chase Cancer Center, Philadelphia for his comments. Any remaining errors are my responsibility. I gratefully acknowledge financial support from Penn State Research and Development Grant, 1995.