Does Gibrat's Law hold among young,small firms?

According to Gibrat's Law of Proportionate Effect, the growth rate of a given firm is independent of its size at the beginning of the examined period. Aimed at extending this line of investigation, the present paper uses quantile regression techniques to test whether Gibrat's Law holds for new entrants in a given industry: that is for new small firms in the early stage of their life cycle. The main finding is that for some selected industries in Italian manufacturing Gibrat's Law fails to hold in the years immediately following start-up, when smaller firms have to rush in order to achieve a size large enough to enhance their likelihood of survival. Conversely, in subsequent years the patterns of growth of new smaller firms do not differ significantly from those of larger entrants, and the Law therefore cannot be rejected.JEL Classification: L11, L60Previous versions of this paper were presented at the 27th Annual EARIE Conference (Lausanne, 7-10 September 2000) and at seminars held between 2000 and 2003 at the Economics Department of Harvard University, the Catholic University of Milan, the University of Ferrara, the University of Bologna, the Bank of Italy, and Athens University of Economics & Business. We would like to thank Carlo Bianchi, Giuseppe Colangelo, Giovanni Dosi, Steven Klepper (Editor), Stephen Martin, Ariel Pakes, Aman Ullah and, in particular, Helen Louri and two anonymous referees for their valuable comments on earlier drafts. Financial support from MIUR (Year 2000; protocol #MM13038538_001; project leader: E. Santarelli) is gratefully acknowledged.Correspondence to: E. Santarelly     

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.     

Asymptotic behaviour of regression pre-test estimators with minimal Bayes risk

Pre-test estimators (PTE) are considered which are optimal under a Bayes risk among PTE with general measurable sets as “regions of significance” for the test statistic t associated with the estimate of a given regression coefficient. Asymptotic and some finite sample results are stated and numerical experiments are commented on.     

基于高频数据的深圳基金市场日内周期性研究

本文利用深市基金指数高频数据,采用Anderson和Bollerslev(1997)提出的弹性傅立叶回归(FlexibleFourierFormregression,即FFF回归)方法首次对深市基金市场进行了日内周期性的研究。通过对高频收益的定性分析,发现基金市场具有同股票市场相似的周期性,并对这一周期性进行了初步的理论解释。通过FFF方法,将该周期因子进行滤波处理以后,基金指数高频绝对收益不再具有明显周期性。FFF回归能较好地确定日内周期因子。     

轻型汽车悬架侧倾角刚度分析

文章通过对某轻型汽车独立悬架和非独立悬架侧倾运动特性的分析,建立了侧倾角刚度的数学模型。     

分数布朗运动环境下的美式看涨期权的定价方法

在分数布朗运动模拟算法基础上,提出了分数布朗运动环境下标的资产价格过程的一种数值模拟方法。然后应用于欧式和美式看涨期权定价。结果表明,该方法具有很快的收敛速度,而且基于最小二乘方法和偏最小二乘方法的美式看涨期权价格,都与对应的欧式看涨期权价格几乎完全一样。这恰恰验证了不支付红利的条件下,美式看涨期权不应该提前执行的理论论断。     

Do investors in Green Bond market pay a premium? Global evidence

We examine the pricing difference of Green Bonds (GB) and conventional bonds (CBs) in capital markets worldwide. Credit spread is used to observe whether investors would like to pay a premium for GBs over CBs. This study uses panel data regression with hybrid model to analyse daily observations over the period 2016 to 2017. We employ Option-Adjusted spread (OAS) to measure the credit spreads of bonds while controlling for bond specific, macroeconomic and global factors that influence the spread. With the hybrid model used in the panel data analysis, we were able to capture the fixed-effects of variables in a random effect model. We find that GBs are traded at a premium of 63 basis points (BPS), compared with a comparable corporate bond issue. We find that the green label provides issuers an incentive to raise funds through issuing GBs while providing investors an opportunity to diversify their investments returns. Our findings provide several implications to the major stakeholders driving the GB market to scale up the market to finance the required level of global green investment needs. We stress an urgent need to support the growth of the GB market to achieve sustainable development through mitigating climate change challenges.

Abbreviation GB: Green Bond; CB: Conventional Bond; YS: Yield Spread; BPS: Basis Points; OAS: Option-Adjusted Spread; PCSE: Panels Corrected Standard Errors; CPI: Consumer Price Index; GBPs: Green Bond Principles; CBS: Climate Bond Standard     

考虑违约距离的上市公司危机预警模型研究

在上市公司财务危机预警中,违约距离起着重要的不可替代的作用,仅考虑财务指标并不足以完全解释企业财务危机发生的原因.文章应用Merton模型对2002～2004年ST公司和相应配对公司的危机发生之前的违约距离进行了研究,发现危机公司违约距离在危机发生前第三年明显低于正常公司的相应值,违约距离比传统财务指标能更早地预警到企业财务危机的发生.结合违约距离因素的危机预警模型能更明显地提高模型的危机判断正确率.     

宏观投资的影响因素与实证分析

在界定宏观投资的基础上，选择储蓄、价格、利润和利率等影响因素的代表变量，建立固定资产投资的理论模型；以1985－1999年为样本区间，采用SPSS统计分析软件包，对变量数据进行相关性分析和主成分分析，构建我国固定资产投资的回归模型；通过实证分析得出我国固定资产投资各影响因素的结论并给出相应的政策含义。     

基于主成分分析的多元线性回归用水量模型研究——以安徽省为例

用水量的准确预测对水资源规划具有重要意义。根据统计资料,选取了八项主要影响用水量变化的指标。按照主成分分析法原理,运用少数综合因子对影响用水量变化的原有八项指标进行了综合和简化,并研究其贡献率及综合效应;分析了用水量增长的特点,选用Logistic方程对综合因子进行回归分析;结合多元线性回归方法,建立了安徽省用水量模型;拟合结果表明,模型具有较高的精度;运用该模型,对安徽省2010年的用水量进行了预测;为水资源规划与管理提供参考依据。