University teaching of econometrics a personal view

University teachers of economics have generally been keen to propound, discuss and criticise alternative points of view on ways of structuring courses in their discipline. Econometricians, by contrast, have in this respect been very neglectful - though their subject has been a university discipline for over a quarter of a century.

This paper appraises broadly the issues relevant to the design of an academic program in econometrics, at both undergraduate and graduate levels, and proposes ways in which a blended education in economics and econometrics may best be offered.     

经济统计学与计量经济学等相关学科的关系及发展前景

本文从统计学和经济学统一的视角,分析与阐述经济统计学与计量经济学等相关学科——概率论、数理统计学、计量经济学以及经济理论（包括数理经济学）之间的相互关系及发展前景。作为从样本信息推断母体特征的一般方法论,数理统计学由于符合人类科学研究的过程与需要,因而在自然科学和社会科学的很多领域得到了广泛应用。计量经济学是经济实证研究的推断方法论。经济统计学与计量经济学一起,构成经济实证研究完整的方法论,其中,作为经济测度方法论,经济统计学不仅提供定量描述经济实际运行的理论、方法与工具,它也是经济实证研究的先决条件与基础,是计量经济学理论发展的一个重要推动力量。经济统计学面临不少挑战,但有深厚的学科根基与巨大的发展空间,其作用是任何相关学科均不能替代的。统计学各个分支的交叉融合,将推动经济统计学和计量经济学的共同发展,从而进一步提升中国经济学实证研究的水平与科学性。     

Peter Schmidt: Econometrician and consummate professional

Peter Schmidt has been one of its best-known and most respected econometricians in the profession for four decades. He has brought his talents to many scholarly outlets and societies, and has played a foundational and constructive role in the development of the field of econometrics. Peter Schmidt has also served and led the development of Econometric Reviews since its inception in 1982. His judgment has always been fair, informed, clear, decisive, and constructive. Respect for ideas and scholarship of others, young and old, is second nature to him. This is the best of traits, and Peter serves as an uncommon example to us all. The seventeen articles that make up this Econometric Reviews Special Issue in Honor of Peter Schmidt represent the work of fifty of the very best econometricians in our profession. They honor Professor Schmidt's lifelong accomplishments by providing fundamental research work that reflects many of the broad research themes that have distinguished his long and productive career. These include time series econometrics, panel data econometrics, and stochastic frontier production analysis.     

从诺贝尔经济学奖看计量经济学的发展

文章认为从诺贝尔经济学奖得主的工作可以看出经济科学的发展趋势:即日益朝着用数学表达经济内容和统计定量的方向———计量经济学发展。     

计量经济学中的潜变量模型：一个方法论角度的考察

上世纪中叶,因子分析和典型相关分析方法的发展完善,解决了潜变量的测度及其相关关系衡量问题,奠定了潜变量因果模型的方法论基础。此后,潜变量模型被引入到计量经济学研究领域,依次经历了共同结构范式模型、经典潜变量模型和非经典潜变量模型三个阶段,逐步成为现代计量经济模型的重要组成部分。本文从方法论角度对计量经济学中的潜变量模型发展过程进行了全面考察,比较了各个阶段建模方法论的特征,归纳总结了其发展演化规律,并对下一步研究的重点领域进行了展望。     

Developments and new dimensions in econometrics

Summary This special issue of the Journal of the German Statistical Society presents 14 papers with surveys on the development and new topics in econometrics. The articles aim to demonstrate how German econometricians see the discipline from their specific view. They briefly describe the main strands and emphasize some recent methods.     

空间计量经济学理论体系的解析及其展望

随着空间经济理论研究出现重大突破,空间计量经济学也从边缘走向现代计量经济学的主流。重点对空间计量经济模型的设立包括空间横截面数据模型、空间面板数据模型以及空间离散数据模型进行讨论,对模型参数估计方法包括最大似然估计法、两阶段最小二乘法和矩估计法等进行分析,对模型检验方法包括Moran’s I方法和LM/RS方法等内容进行总结,最后展望了该理论研究未来的发展趋势。     

我国统计学科建设史上的一次重大变革

统计学向来被认为是社会科学,是经济学下属的二级学科。对此我国统计学界早有不同认识,但一直未能受到理论界和有关部门的重视。直到二十年前,由中国统计学会和国家统计局统计科学研究所发起,组织的“大统计”的大讨论,才受到学界乃至政界的关注,从而推动和促进了社会经济统计学从经济学中分离出来,与数理统计学一起,共同形成独立的统计学一级学科,这是我国统计学科建设史上的一次重大变革,我国统计学界的一件大事。它对我国统计理论和实践的发展产生了深远影响。 本文对上述情况作了全面评述,并对统计学从经济学中分离出来上升为一级学科的来龙去脉,和统计学科类目框架的形成过程作了详细介绍,它有助于读者了解这一重大事件的全过程。     

Econometrics exams and round numbers: Use or misuse of indirect estimation methods?

The use of Monte Carlo methods to generate exam datasets is nowadays a well-established practice among econometrics and statistics examiners all over the world. Its advantages are well known: providing each student a different data set ensures that estimates are actually computed individually, rather than copied from someone sitting nearby. The method however has a major fault: initial “random errors,” such as mistakes in downloading the assigned dataset, might generate downward bias in student evaluation. We propose a set of calibration algorithms, typical of indirect estimation methods, that solve the issue of initial “random errors” and reduce evaluation bias. Ensuring round initial estimates of the parameters for each individual dataset, our calibration procedures allow the students to determine if they have started the exam correctly. When initial estimates are not round numbers, this random error in the initial stage of the exam can be corrected for immediately, thus reducing evaluation bias. The procedure offers the further advantage of rounding markers’ life by allowing them to check round numbers answers only, rather than lists of numbers with many decimal digits¹.     

Great Expectatrics: Great Papers,Great Journals,Great Econometrics

The article discusses alternative Research Assessment Measures (RAM), with an emphasis on the Thomson Reuters ISI Web of Science database (hereafter ISI). Some analysis and comparisons are also made with data from the SciVerse Scopus database. The various RAM that are calculated annually or updated daily are defined and analyzed, including the classic 2-year impact factor (2YIF), 2YIF without journal self-citations (2YIF*), 5-year impact factor (5YIF), Immediacy (or zero-year impact factor (0YIF)), Impact Factor Inflation (IFI), Self-citation Threshold Approval Rating (STAR), Eigenfactor score, Article Influence, C3PO (Citation Performance Per Paper Online), h-index, Zinfluence, and PI-BETA (Papers Ignored – By Even The Authors). The RAM are analyzed for 10 leading econometrics journals and 4 leading statistics journals. The application to econometrics can be used as a template for other areas in economics, for other scientific disciplines, and as a benchmark for newer journals in a range of disciplines. In addition to evaluating high quality research in leading econometrics journals, the paper also compares econometrics and statistics, alternative RAM, highlights the similarities and differences of the alternative RAM, finds that several RAM capture similar performance characteristics for the leading econometrics and statistics journals, while the new PI-BETA criterion is not highly correlated with any of the other RAM, and hence conveys additional information regarding RAM, highlights major research areas in leading journals in econometrics, and discusses some likely future uses of RAM, and shows that the harmonic mean of 13 RAM provides more robust journal rankings than relying solely on 2YIF.     

An introduction to hypergeometric functions for economists

Hypergeometric functions are a generalization of exponential functions. They are explicit, computable functions that can also be manipulated analytically. The functions and series we use in quantitative economics are all special cases of them. In this paper, a unified approach to hypergeometric functions is given. As a result, some potentially useful general applications emerge in a number of areas such as in econometrics and economic theory. The greatest benefit from using these functions stems from the fact that they provide parsimonious explicit (and interpretable) solutions to a wide range of general problems.     

中国碳排放的环境库兹涅茨曲线分析——基于空间面板模型的实证研究

在环境库兹涅茨曲线理论的基础上,选用30个省域2000—2009年数据,运用空间面板计量经济模型研究碳排放与经济增长的关系,结果表明:利用空间相关性指标检验出经济发展与碳排放之间存在显著的空间效应;利用空间面板自回归和误差模型发现,中国碳排放与经济增长存在倒U形关系,转折点在8.167亿元至11.025亿元人均GDP之间;工业结构比重对碳减排有消极影响,而技术进步、FDI与碳排放之间存在显著的正效应,这说明通过降低工业结构比重、促进新能源技术的革新以及引进外资等能减少中国的碳排放。     

Estimation and Properties of a Time-Varying EGARCH(1,1) in Mean Model

Time-varying GARCH-M models are commonly employed in econometrics and financial economics. Yet the recursive nature of the conditional variance makes likelihood analysis of these models computationally infeasible. This article outlines the issues and suggests to employ a Markov chain Monte Carlo algorithm which allows the calculation of a classical estimator via the simulated EM algorithm or a simulated Bayesian solution in only O(T) computational operations, where T is the sample size. Furthermore, the theoretical dynamic properties of a time-varying-parameter EGARCH(1,1)-M are derived. We discuss them and apply the suggested Bayesian estimation to three major stock markets.     

On the specification and estimation of large scale simultaneous structural macroeconometric models

Summary This paper surveys the state of the art of the analysis and application of large scale structural simultaneous econometric models (SSEM). First, the importance of such models in empirical economics and especially for economic policy analysis is emphasized. We then focus on the methodological issues in the application of these models like questions about identification, nonstationarity of variables, adequate estimation of the parameters, and the inclusion of identities. In the light of the latest development in econometrics, we identify the main unsolved problems in this area, recommend a combined data-theory-driven procedure for the specification of such models, and give suggestions how one could overcome some of the indicated problems.     

DATA-DRIVEN NONPARAMETRIC SPECTRAL DENSITY ESTIMATORS FOR ECONOMIC TIME SERIES: A MONTE CARLO STUDY

Spectral analysis at frequencies other than zero plays an increasingly important role in econometrics. A number of alternative automated data-driven procedures for nonparametric spectral density estimation have been suggested in the literature, but little is known about their finite-sample accuracy. We compare five such procedures in terms of their mean-squared percentage error across frequencies. Our data generating processes (DGP) include autoregressive-moving average (ARMA) models, fractionally integrated ARMA models and nonparametric models based on 16 commonly used macroeconomic time series. We find that for both quarterly and monthly data the autoregressive sieve estimator is the most reliable method overall.     

Non-Gaussian Ornstein–Uhlenbeck-based models and some of their uses in financial economics

Non-Gaussian processes of Ornstein–Uhlenbeck (OU) type offer the possibility of capturing important distributional deviations from Gaussianity and for flexible modelling of dependence structures. This paper develops this potential, drawing on and extending powerful results from probability theory for applications in statistical analysis. Their power is illustrated by a sustained application of OU processes within the context of finance and econometrics. We construct continuous time stochastic volatility models for financial assets where the volatility processes are superpositions of positive OU processes, and we study these models in relation to financial data and theory.     

Econometric analysis of high frequency data

Summary Owing to enormous advances in data acquisition and processing technology the study of high (or ultra) frequency data has become an important area of econometrics. At least three avenues of econometric methods have been followed to analyze high frequency financial data: Models in tick time ignoring the time dimension of sampling, duration models specifying the time span between transactions and, finally, fixed time interval techniques. Starting from the strong assumption that quotes are irregularly generated from an underlying exogeneous arrival process, fixed interval models promise feasibility of familiar time series techniques. Moreover, fixed interval analysis is a natural means to investigate multivariate dynamics. In particular, models of price discovery are implemented in this venue of high frequency econometrics. Recently, a sound statistical theory of ‘realized volatility’ has been developed. In this framework high frequency log price changes are seen as a means to observe volatility at some lower frequency.     

A Monte Carlo Study of Tests of Blockwise Weak Separability

Separability assumptions on functional structure have received a great deal of attention from econometricians and economic theorists because (a) separability provides the fundamental linkage between aggregation over goods and the maximization principles in economic theory, (b) separability provides the theoretical basis for partitioning the economy's structure into sectors, and (c) separability provides a theoretical hypothesis, which can produce parameter restrictions, permitting great simplification in estimation of large demand systems. The power of the various available tests for separability has never been determined, however. We conduct Monte Carlo studies to examine the capability of currently available methods to provide correct inferences about separability.     

On the Choice of Functional Forms: Summary of a Monte Carlo Experiment

The use of flexible functional forms is a standard practice in applied econometrics. Many flexible forms have been proposed. In this study, we investigate the behavior of three of them—the translog, the symmetric McFadden, and the symmetric generalized Barnett. Based on Monte Carlo experiments, we assess the ability of these forms to test theoretical properties and to measure technological characteristics.     

中国工业产值与利润波动的周期特征比较及协整分析

文章利用统计学中的周期分析方法和现代计量经济学中的协整分析方法,研究了1977-2003年间我国工业利润和工业产值的周期波动问题,得出了尽管二者的周期波动各有其自身的特点,但二者之间存在着显著的长期动态均衡关系和短期误差修正机制的结论,并认为工业产值指标和工业利润指标各有所长, 应该配合使用。