上海市大中型工业行业专利产出滞后机制研究

本文我们沿用Hausman，Hall和Griliches（1984）对专利产出与R＆D支出之间关系的分析框架，结合上海市大中型工业行业专利产出数据本身的特点，运用了较为适当的计量经济学分析技术——零膨胀泊松回归方法，对上海市大中型工业行业专利产出的滞后机制进行了研究。我们发现了两个有意义的结论：第一，对于上海市大中型工业企业来说，其科技活动的内部支出与专利产出的滞后机制表现为一个2～6期的滞后结构。同时这一结构还有一个不对称的倒U形内部特征，具体表现为上海市大中型工业企业科技活动经费的内部支出对专利产出贡献的滞后作用表现为先增后减，且增快减慢；第二，在这个滞后结构中，存在着一个对专利产出贡献作用最大的科技活动经费内部支出时刻，这个时刻大约出现在专利产出之前第4期的科技活动经费内部支出。     

A local maximum likelihood estimator for Poisson regression

A local maximum likelihood estimator based on Poisson regression is presented as well as its bias, variance and asymptotic distribution. This semiparametric estimator is intended to be an alternative to the Poisson, negative binomial and zero-inflated Poisson regression models that does not depend on regularity conditions and model specification accuracy. Some simulation results are presented. The use of the local maximum likelihood procedure is illustrated on one example from the literature. This procedure is found to perform well. This research was partially supported by Calouste Gulbenkian Foundation and PRODEP III.     

Change-point analysis through integer-valued autoregressive process with application to some COVID-19 data

In this article, we consider the problem of change-point analysis for the count time series data through an integer-valued autoregressive process of order 1 (INAR(1)) with time-varying covariates. These types of features we observe in many real-life scenarios especially in the COVID-19 data sets, where the number of active cases over time starts falling and then again increases. In order to capture those features, we use Poisson INAR(1) process with a time-varying smoothing covariate. By using such model, we can model both the components in the active cases at time-point t namely, (i) number of nonrecovery cases from the previous time-point and (ii) number of new cases at time-point t. We study some theoretical properties of the proposed model along with forecasting. Some simulation studies are performed to study the effectiveness of the proposed method. Finally, we analyze two COVID-19 data sets and compare our proposed model with another PINAR(1) process which has time-varying covariate but no change-point, to demonstrate the overall performance of our proposed model.     

Does time difference between countries reduce bilateral trade? An application of the correlated random effects method using panel data

This article implements the correlated random effects (CRE) panel data technique in a gravity framework to analyse the effect of time difference between countries on bilateral trade. One major advantage of the CRE approach over the fixed-effects approach is that it is able to estimate the effect of variables that remain unchanged within panel clusters (e.g. time difference between countries), while these variables get dropped from regressions that use fixed-effects methods. Regression results based on the CRE Poisson pseudo-maximum likelihood estimator indicate statistically significant negative effect of time difference between countries on bilateral trade. An additional hour of time difference between countries is found to reduce bilateral merchandise exports by approximately 8%, even after controlling for the effect of distance in the regressions.     

Ruin probabilities in multivariate risk models with periodic common shock

We propose a multidimensional risk model where the common shock affecting all classes of insurance business is arriving according to a non-homogeneous periodic Poisson process. In this multivariate setting, we derive upper bounds of Lundberg-type for the probability that ruin occurs in all classes simultaneously using the martingale approach via piecewise deterministic Markov processes theory. These results are numerically illustrated in a bivariate risk model, where the beta-shape periodic claim intensity function is considered. Under the assumption of dependent heavy-tailed claims, asymptotic bounds for the finite-time ruin probabilities associated to three types of ruin in this multivariate framework are investigated.     

On semiparametric estimation of ruin probabilities in the classical risk model

The ruin probability of an insurance company is a central topic in risk theory. We consider the classical Poisson risk model when the claim size distribution and the Poisson arrival rate are unknown. Given a sample of inter-arrival times and corresponding claims, we propose a semiparametric estimator of the ruin probability. We establish properties of strong consistency and asymptotic normality of the estimator and study bootstrap confidence bands. Further, we present a simulation example in order to investigate the finite sample properties of the proposed estimator.     

可控二维平面驻波的边值混合问题

主要研究一类二维Poisson方程的边值混合问题.通过分离变量法,计算混合问题的具有Fourier级数形式的解;寻求边界条件中的函数能够展开成Fourier正弦级数的条件;最后,通过该问题Fourier级数形式解的能量积分定义,说明平面驻波混合问题的可控性.     

Cycles in basic innovations

Basic innovations are believed to be one of the drivers of economic growth. In this paper we examine if cycle periods found for economic data correspond with cycles in basic innovations. For an annual time series of count data on innovations covering 1764-1976, we fit a harmonic Poisson regression model. We find the presence of multiple cycles with periods 5, 13, 24, 34 and 61, and these show a remarkable resemblance with commonly found economic cycles.     

Share Valuation under Geometric Brownian Motion with a Poisson Imputation Tax Change

A share valuation model is developed on the basis of dividends following a geometric Brownian motion. An imputation tax system is chosen, although this can be collapsed into a classical system. The possibility of changes in tax rates and shareholder tax credits is introduced by means of a Poisson jump. Capital gains are assumed to be tax-free through either annual or other exemptions. Using Itô's Lemma, a new share valuation formula is derived. This is recast in terms of the cost of capital and the mean time to the fiscal shock.     

Hidden in plain sight: Correspondent banking in the 1930s*

Abstract

We present novel quantitative evidence on the number and location of correspondent banking relationships in the 1930s, a neglected area of international banking. Our data, collected from Thomas Skinners’ Bankers’ Almanac, captures over 2000 correspondent banking connections primarily based on London and New York and a smaller cohort of multinational banks. We draw on the new institutional economics and international business literature to explain the relative ubiquity of correspondent banking and the relative scarcity of multinational banks. Our argument that bilateral trade flows drive correspondent banking is tested empirically using an instrumental Poisson pseudo-maximum likelihood estimation.