Object-oriented econometrics: Matrix programming in C++ using GCC and newmat

Object-oriented programming using C++ offers features that can be as beneficial for econometricians as they are for other programmers. This review considers the standard programming paradigm and then discusses object-oriented programming, in particular the C++ language. Both GCC, a C++ compiler available free of charge from the GNU Project, and the newmat matrix class library are reviewed. An example of a simple econometric program in C++ that uses newmat is included. © 1996 John Wiley & Sons, Ltd.     

Semiparametric econometrics: A survey

Semiparametric econometric models contain both parametric and nonparametric components, reflecting in some fashion what has been learned from economic theory and previous empirical experience, and what remains unknown. They raise such questions as how well the parametric component can be estimated, and how to construct rules of inference with good statistical properties. The paper attempts to survey the econometric and most relevant statistical literature on semiparametric inference, and includes a partial bibliography.     

Philosophy and objectives of econometrics

In this paper, the philosophy and objectives of econometrics are discussed. The roles of induction, deduction and reduction in economic research are explained. Further, the roles of sophisticated simplicity and predictive performance in model building are described. Many examples, drawn from the work of leading scientists, are provided to illustrate general points. In addition, the work that has been done leading to the formulation of a disaggregate Marshallian Macroeconomic Model is briefly described. It is concluded that greater emphasis in teaching to explain the roles of deduction, induction and reduction in economic research would be very beneficial in terms of producing more valuable and useful research results. Also, development and use of many more sophisticatedly simple models and further use of Bayesian inference and decision techniques will do much to promote more rapid progress in economic science.     

Recent developments in financial economics and econometrics: An overview

Research papers in empirical finance and financial econometrics are among the most widely cited, downloaded and viewed articles in the discipline of Finance. The special issue presents several papers by leading scholars in the field on “Recent Developments in Financial Economics and Econometrics”. The breadth of coverage is substantial, and includes original research and comprehensive review papers on theoretical, empirical and numerical topics in Financial Economics and Econometrics by leading researchers in finance, financial economics, financial econometrics and financial statistics. The purpose of this special issue on “Recent Developments in Financial Economics and Econometrics” is to highlight several novel and significant developments in financial economics and financial econometrics, specifically dynamic price integration in the global gold market, a conditional single index model with local covariates for detecting and evaluating active management, whether the Basel Accord has improved risk management during the global financial crisis, the role of banking regulation in an economy under credit risk and liquidity shock, separating information maximum likelihood estimation of the integrated volatility and covariance with micro-market noise, stress testing correlation matrices for risk management, whether bank relationship matters for corporate risk taking, with evidence from listed firms in Taiwan, pricing options on stocks denominated in different currencies, with theory and illustrations, EVT and tail-risk modelling, with evidence from market indices and volatility series, the economics of data using simple model free volatility in a high frequency world, arbitrage-free implied volatility surfaces for options on single stock futures, the non-uniform pricing effect of employee stock options using quantile regression, nonlinear dynamics and recurrence plots for detecting financial crisis, how news sentiment impacts asset volatility, with evidence from long memory and regime-switching approaches, quantitative evaluation of contingent capital and its applications, high quantiles estimation with Quasi-PORT and DPOT, with an application to value-at-risk for financial variables, evaluating inflation targeting based on the distribution of inflation and inflation volatility, the size effects of volatility spillovers for firm performance and exchange rates in tourism, forecasting volatility with the realized range in the presence of noise and non-trading, using CARRX models to study factors affecting the volatilities of Asian equity markets, deciphering the Libor and Euribor spreads during the subprime crisis, information transmission between sovereign debt CDS and other financial factors for Latin America, time-varying mixture GARCH models and asymmetric volatility, and diagnostic checking for non-stationary ARMA models with an application to financial data.     

Canonical ridge and econometrics of joint production

This paper is a continuation of the author's earlier work (1969) in which canonical correlation analysis was used to directly estimate a joint production function as an implicit function of all outputs and inputs. A major difficulty with canonical correlation analysis in this context is its numerical instability when the underlying (economic) data are nearly collinear. This can be partly overcome by considering an adaptation of ridge regression concepts to canonical correlations. The hybrid may be named a ‘canonical ridge’ model. For illustration we discuss a trans-log joint production function based on U.S. (1945-1969) private domestic economy first studied by Christensen, Jorgenson and Lau (1973).     

Applied econometrics rankings: 1989–1995

This paper ranks academic institutions by publication activity in applied econometrics over the period 1989–1995. Fourteen leading international journals that publish applied econometrics articles are used to provide the database. The rankings are based on standardized page counts of articles published in these journals over the stated period. A ‘Hall of Fame’ is developed listing the top 100 individual producers of applied econometrics in the fourteen journals considered. To control for quality differences among the applied journals, separate rankings are provided both for institutions and for individuals according to econometrics publications by journal. Copyright © 1999 John Wiley & Sons, Ltd.     

Aggregation, gerrymandering, and spatial econometrics

Since the work of Cliff and Ord (1973), increasing attention has been paid to the unique statistical and econometric problems associated with the use of spatial or areal data. In this paper it will be shown that the way in which spatial data is aggregated, or gerrymandered, will alter the estimation results of a model. Specifically, a well known model developed by Kain to measure the loss in black jobs in a metropolitan area resulting from residential segregation will be estimated. It will be shown that by alternative areal aggregation, or gerrymandering, of the data it is possible to reach diametrically opposed conclusions (i.e., blacks either gain or lose jobs as a result of residential segregation using the same model.     

Disequilibrium econometrics: 25 years later*

The author concludes that disequilibrium econometrics, as it developed more than 20 years ago, is not suitable for policy analysis. Various new opportunities are outlined that can put this area on the research agenda again.     

Insider econometrics: A roadmap with stops along the way

For the past twenty five years, economists have been building theories of the optimal management of firms. For example, economic models suggest that under some conditions, piece rate pay raises performance, and under other conditions, promotions tournaments raise performance. Some of these theories have been tested, others have not. Economists are now using new empirical research tools, that we label “insider econometrics,” to test the impact of management practices on productivity: to model how much productivity changes; to model why management practices raise productivity; and to examine which firms benefit and why from alternative management practices. The methodology we describe is “insider” because it uses inside knowledge and data from within firms. It is “econometrics” because the methodology is often the application of treatment effects methods to modeling changing management practices within firms. However, the methods and challenges of insider econometrics are unique, and we identify several key features that are important in undertaking empirical studies of workers' productivity. Now that more firms are keeping data on employees, it is time to improve our analysis of the empirical study of the productivity of workers within firms.     

Household survey data, econometrics and economic transition

This paper explores some of the possible uses of household survey data for the analysis of the process of economic transition. It is argued that such data are particularly valuable for work on the distributional effects of transition, using simulation techniques of various kinds. Some examples are given, focusing on: labour supply; indirect taxation; and the cost and effectiveness of the Hungarian personal income tax and social security systems under alternative assumptions about changes in the distribution of gross earnings and the level and incidence of unemployment.     

Optimal experimental design in econometrics: The time series problem

Experiments in economics are expensive in terms of dollars and time. This suggests that efficient design is crucial, and that there is a need for econometricians to extend design theory to handle peculiarities of economic experimentation. This paper concerns optimal experimental design for various time series models. Examples are presented illustrating the improvement in estimation accuracy that can be obtained.