Econometric Model Building Research Articles

Working Paper Containing Excerpts of Several Leading Upcoming Books Being Written by the Author Thileni Rasadarie Dodangodage Wickramaratne and Some Excerpts of a Book Proposal by the Said Author

In this Working Paper containing excerpts of my Upcoming books I critique the economic growth theory of Robert Solow and I newly introduce my simple production function where income is a function of demand and state the application of differential equations to the calculation of economic growth. In these excerpts I also demonstrate econometric model building and calculation of probability with my own examples of coin tossing and dice rolling.

Econometrics and equilibrium models

ABSTRACTIn Rational Econometric Man, Edward Nell and Karim Errouaki present a welcome and timely case for the view that econometrics and econometric model-building may not be the magic tools to solve all empirical questions despite what many seem to have thought they were in the 1960s. Here I examine some possible problems with econometric models that have to do with their usually taking the form of equilibrium models. Some of these problems were recognized by Trygve Haavelmo decades ago. And as Aris Spanos has recently discussed, the problems are often the result of what we say in our textbooks. Some problems have to do with what we mean by econometric parameters and others with how we use probabilities.

Lives of the laureates: twenty-three nobel economists

Lives of the Laureates offers readers an informal history of modern economic thought as told through autobiographical essays by twenty-three winners of the Nobel Prize in Economics. The essays not only provide unique insights into major economic ideas of our time but also shed light on the processes of intellectual discovery and creativity. This fifth edition adds five recent Nobel laureates to its list of contributors: Vernon L. Smith (2002), Clive W. J. Granger (2003), Edward C. Prescott (2004), Thomas C. Schelling (2005) and Edmund S. Phelps (2006). Also included is the editors' revised afterword, Lessons from the Laureates. Lives of the Laureates grows out of a continuing lecture series at Trinity University in San Antonio, which invites Nobelists from American universities to describe their evolution as economists in personal as well as technical terms. Each laureate achieves the goal of clarity without sacrificing inherently difficult content: Kenneth Arrow makes grasping the essentials of his impossibility theorem painless; Lawrence Klein clearly presents what goes into econometric model building; George Stigler masterfully describes his information theory; and so on. These lectures demonstrate the richness and diversity of contemporary economic thought. The reader will find that paths cross in unexpected ways -- that disparate thinkers were often influenced by the same teachers--and that luck as well as hard work plays a role in the process of scientific discovery.

Asymmetry in Volatility: A Comparison of Developed and Transition Stock Markets

ARCH modelling framework of Engle (1982) and its GARCH generalization of Bollerslev (1986) gave a huge impetus to econometric model building in the field of financial time series with time-varying variance. The main idea of the models was to describe the most typical features of capital markets like volatility clustering, excess kurtosis and fat tails. As empirical evidence shows asymmetry is also a prominent feature of stock market returns volatility. The reaction of risk if stock returns go off the long run trajectory is different in case of positive and negative market news. Thus it is indispensable to employ asymmetric models being a modification of a traditional GARCH. In the paper we used an approach of Engle and Ng (1993) to test for asymmetric effects in stock indices of developed and Central European stock markets.

In memory of Clive Granger: an advisory board member of the journal

In memory of Clive Granger: an advisory board member of the journal

A macroeconomic model for South Africa: A non-linear econometric modelling approach

Econometric models are often made up of assumptions that never truly match reality. One of the most challenged requirements is that the coefficients of econometric models remain constant over time, in the sense that it is assumed that the future will be similar to the past. If the assumption of constant coefficients is not satisfied, any conclusions reached from normal (constant coefficient) models will be biased. Another, very closely related, contested assumption is that the functional form (usually linear) of a model remains unchanged over time. The theory of linearity has long been the centre of all econometric model-building. According to Teräsvirta (1994), if linear estimates were not successful in practice, they would have been forsaken long ago, and this has certainly not been the case. Quite the opposite has been experienced: some very influential ideas based on the linear relationships between variables, like cointegration analysis, have been established. Nonetheless, there are definite situations in which linear models are unable to grasp the underlying economic theory of the data accurately. This article addresses the problem of non-linearity by applying smooth transition autoregressive (STAR) specifications to an existing simultaneous macroeconomic model of the South African economy. The results support the view that non-linear models provide better forecasts than linear specifications of equations.

The feedback channels in macroeconomics: analytical foundations for structural econometric model building

We investigate important macroeconomic and macroeconometric feedback channels in models that concern the dynamic interaction of the labor market, product market and the monetary and financial sector. The core of our study is an applied disequilibrium model of monetary growth of a small open economy. After surveying the feedback channels we consider a compact description of the intensive form of the model. We consider various types of subsystems, the integration of which is subsequently compared from the perspective of bifurcation diagrams that separate cases of asymptotic stability from stable cyclical behavior as well as pure explosiveness. In this way we lay out a research strategy, which will show, in contrast to what is generally believed, that applied integrated macrodynamic systems can have a variety of interesting attractors and transient dynamics, which are obtained in particular when locally explosive situations are turned into bounded dynamics by the addition of specifically tailored extrinsic nonlinearities.

THE ET INTERVIEW: PROFESSOR JAN KMENTA

Jan Kmenta is the author of the internationally respected text The Elements of Econometrics [1] and co-editor of several books related to econometric model building. His published research over 40 years relates to many facets of econometric theory and practice, including the estimation of production functions, the evaluation of structural econometric models, and estimation in the face of missing data. This work has appeared in the leading journals of the profession. A 1966 paper [11] is of historical interest for being the second econometric model constructed of the Australian economy. In his work, through both constructive contributions and methodological critique, he has always sought to highlight and advance the evidently close connection between economics and econometrics.Kmenta was born on January 3, 1928, in Prague, the Czech Republic. He was educated at the Jirasek State Gymnasium in Prague (1939–47) and the Czech University of Technology in Prague (1947–49). At the University of Sydney (1952–55), Australia, he graduated with a Bachelor of Economics degree (First Class Honors). He obtained a Master of Arts degree (1959) and a Doctor of Philosophy degree (1964) from Stanford University with a doctoral dissertation entitled “Australian Postwar Immigration: An Econometric Study.” After teaching stints in Australia, Stanford, and Wisconsin, he taught at Michigan State from 1965 to 1973 and at the University of Michigan from 1973 to 1993. He is currently Professor Emeritus of Economics and Statistics, University of Michigan, and Visiting Professor, CERGE-EI, Charles University, Prague.His various academic awards and prizes include the Alexander von Humboldt Foundation Award for Senior U.S. Scientists, the Michigan Economic Society Best Professor Award, the Royal Economic Society Lecturer at the University of Leicester, and the Karel Englis Medal of the Academy of Sciences of the Czech Republic. He was awarded an honorary doctorate from the University of Saarland, Germany, and served as associate editor, Journal of the American Statistical Association (1973–1979 and 1985–1992), associate editor, Review of Economics and Statistics (1975–1992), and associate editor, Metrika (1981–1985). Kmenta was listed as 40th among all economists ranked by the total number of citations (Medoff 1989).This is an edited transcript of two tape-recorded interviews conducted with Professor Kmenta in Sydney on March 12, 2004, as he visited the University of New South Wales to present the seminar Econometrics: A Failed Science? I am indebted to one of Kmenta's former students, Eric Sowey, for suggesting this project and for his enthusiasm and support throughout.

A Computational Approach to Finding Causal Economic Laws

This paper states four realities of econometric model building and shows that an econometric model can be causal only if the interpretations given to its coefficients are consistent with these realities. A numerically stable algorithm for estimating such a model subject to equality and inequality constraints on the model parameters is presented. This algorithm is designed in such a way that it can be applied even when the matrix of observations on the model's independent variables and the covariance matrix of the model's errors are deficient in rank.

Rational expectation variables in macroeconomic models: Empirical evidence for the Netherlands and other countries

Rational expectations have obtained a prominent place in economic theory and econometric model building. However, this holds more for small, theoretical models than for large macroeconomic models. This paper deals with the introduction of rational expectation variables in MORKMON II, a macroeconomic model of the Dutch economy. Model equations with rational expectations are reestimated. Policy and impulse simulations are used to compare the adaptive expectation variant with the rational expectation variant of MORKMON II. It is found that rational expectations constitute a plausible alternative to adaptive expectations, but that the simulation effects only differ in the short run and in case of announcement effects. This result agrees with the findings of an international survey of macroeconomic models with rational expectations, that simulation effects generally differ little when equations with rational expectations are reestimated, but may differ substantially when reestimation has not been carried out.

An Agenda For Econometric Model Building

This article addresses the lack of cohesion in econometric model building. This incoherence contributes to model building based on statistical criteria—correcting residuals—and not theoretical criteria. The models we build, therefore, are not valid replications of theory. To deal with this problem, an agenda for model building is outlined and discussed. Drawing on the methodological approaches of Hendry, Qin, and Favero (1989), Hendry and Richard (1982, 1983), Sargan (1964), and Spanos (1986), this agenda incorporates a “general to simple” modeling philosophy, a battery of diagnostic tests, reduction theory, and the development of models that include short-term and long-term parameters. A comparison is made between a model based on this agenda and a model based on corrected residuals. The findings show that the agenda-based model outperforms the residual correction model.

Handbook of Econometrics.

This handbook aims to serve as a source reference and teaching supplement for the field of econometrics the branch of economics concerned with the empirical estimation of economic relationships. It concentrates on statistical problems and economic interpretation issues associated with the modeling and estimation of economic behavioral relationships from already assembled and often badly collected data. The organization of the handbook follows in relatively systematic fashion the way an econometric study would proceed starting from basic mathematical and statistical methods and econometric models proceeding to estimation and computation through testing and ultimately to applications and uses. Part 1 summarizes some basic tools used repeatedly in econometrics including linear algebra matrix methods and statistical theory. Part 2 deals with econometric models their relationship to economic models their identification and the question of model choice and specification analysis. Part 3 takes up more advanced topics in estimation and computation theory such as non-linear regression methods biased estimation and computational algorithms in econometrics. This part also includes a series of chapters on simultaneous equations models their specification and estimation distribution theory for such models and their Bayesian analysis. Part 4 considers testing of econometric estimators including Wald likelihood ratio and LaGrange multiplier tests; multiple testing hypothesis; distribution theory for econometric estimators; and Monte Carlo experimentation in econometrics. Part 5 treats various topics in time series analysis. Parts 6 and 7 present discussions of various special topics in econometrics including latent variable limited dependent variable and discrete choice models; functional forms in econometric model building; economic data issues including longitudinal data issues; and disequilibrium self selection and switching models. Finally part 8 covers selected applications and uses of econometrics.

Quantitative Forecasting—the State of the Art: Econometric Models

Econometric model building for forecasting has developed substantially over the past 15 years. Nevertheless, operational researchers have neglected these new developments. This paper defines nine stages the forecaster must go through when developing an econometric model. Each stage is discussed with reference to the most recent research. The complexity of econometric model building requires the forecaster to adopt a modelling strategy. Two have been proposed in the literature; one moves from a specific model to a more general version, the second goes from the general to the specific. Five recent O.R. studies using econometric methodology are then evaluated, highlighting the common areas of weakness. They are those areas that econometricians have paid most attention to in their recent research. The paper then surveys the effectiveness of econometric models compared to alternative approaches, concluding with some recommendations to the O.R. worker in forecasting. In particular, it recommends that more attempts are made to develop econometric models for O.R. applications.

The Southampton econometric model building unit: Some lessons learned

This paper draws on the author's experience as a research fellow on the Southampton Econometric Model Building Unit in suggesting that there is a case for large-scale, structural, disaggregated econometric models. This is particularly so if, like SEMBU, the aim is to improve both economic theory and economic policy advice rather than simply to forecast actual futures. It is argued that for such an approach to model building to be successful, funding agencies should adopt a long-term view and the Central Statistical Office and other data generating bodies should become much more closely involved with the model-building unit. This latter cooperation could prove mutually beneficial.

Urban Land Use Plan Design Model

The macro land use model, which has the purpose of generating multiple alternatives of quantitative land use plan as a future desirable blueprint in the urban land use planning process, and its model building process are discussed through a systems approach. Although much manpower and costs are generally needed in the econometric type model building, we propose Interpretive Dynamic and Weighted Structural Modeling (IDWSM) in order to efficiently build the econometric type model. The four submodels comprising the macro land use model are described, and the simulation case study is summarized for Kitakyushu City.

An Empirical Study of Politico-Economic Interaction in the United States: A Reply

N modern society, where government has assumed a major role in economic affairs and where the electorate has made it increasingly responsible for material well-being, it has become important to analyse the interaction between economic and political systems. Government should no longer be regarded as exogenous to the economic system. This is particularly the case with respect to econometric model building. As some authors have noted, an econometric model may be subject to serious misspecification if an endogenous variable (such as government expenditure) is treated as if it were exogenous.' The study of politico-economic interdependence also has important consequences for forecasting. As the future course of economic events is strongly dependent on government action, existing macroeconometric models that regard government as exogenous are of limited use for prediction. Furthermore, economic policy advice is often unsuccessful because it does not take political repercussions into account. A deflationary policy, for example, will hardly be adopted by a government just before an election because it carries with it a high risk of leading to government's losing the election. Politicoeconometric modelling helps economists concerned with government advising to advance proposals that have a reasonable chance of being put into action. This study puts forward some simple theoretical hypotheses concerning the nature of the interrelationship between the economy and the polity, particularly with respect to (central) government. The basic relationships are reflected in the popularity function, which describes the impact of economic conditions on government popularity; and in the reaction function, which shows how government uses policy instruments to steer the economy in a desired direction. These relationships are econometrically tested with quarterly data for the United States for the period 1953-1975. In the model both voters and government are assumed to be utility maximizers, and government's behavior is restricted by various economic, political and administrative constraints. The analysis shows that the government's (or in the case here dealt with, the president's) popularity is significantly reduced when the rate of unemployment and/or of inflation rises, and that it is significantly increased when the growth rate of private consumption rises. Government reacts to changes in its popularity because this is taken as an indicator of future electoral outcome. When popularity is low, it tries to steer the economy so as to increase its re-election chances; when popularity is high enough, it can afford to pursue ideologicallyoriented policies, which need not always be popular with the electorate. There have been a number of papers that have dealt with the influence of economic variables on election outcomes and on government popularity, most of which are unsatisfactory on theoretical and statistical grounds. There are, on the other hand, only a few that have been concerned with government reaction functions. Moreover, these studies have been either apolitical and interested only in the implied weights of a welfare function (e.g., Friedlaender, 1973); or they have related to only a particular section of the economy (e.g., Received for publication June 14, 1976. Revision accepted for publication November 30, 1976. * University of Zurich. A first version of this paper was written during a stay at the Cowles Foundation, Yale University. It was revised in the light of comments received when it was presented at the Cowles Foundation Seminar and at seminars at Princeton University, the University of North Carolina at Chapel Hill and the Center for Study of Public Choice, Virginia Polytechnic Institute and State University. The authors are especially grateful to A. S. Blinder, J. M. Buchanan, R. C. Fair, G. M. Heal, D. F. Hendry, C. Goodrich, G. H. Kramer, G. Kirchgaessner, D. MacRae, W. D. Nordhaus, W. E. Oates, E. R. Tufte, G. Tullock, R. Wagner, and to the anonymous referees. ' See Crotty (1973), Goldfeld and Blinder (1972), Blinder and Solow (1974, pp. 69-77).

On Lawrence R. Klein's Contributions to Economics

This survey was originally prepared at the request of the Prize Committee for the Nobel Prize in Economics.** It constitutes a record and assessment of the work and influence of Lawrence Klein. Rather than simply attempting to catalogue his work seriatim, it is divided into three main sections. Section I looks at his work as a chronological story which is intended to put into historical context the vast list of his published work. In Section II his contributions to economics are reviewed under three headings of economic theory, statistical methods and econometric model building. Finally, Section III attempts a broader assessment of his influence on the economics profession.

The Determination of Expenditure On Consumer Durables

This article presents some alternative models of consumers' expenditure on durable goods and examines some general issues of econometric model building. In the preferred model, income, the change in liquid assets and the real cost of credit have a substantial effect on durables expenditure. Hence, both fiscal policy instruments such as a change in the rate of income tax and monetary variables such as nominal interest rates and sterling M3 influence durables expenditure.

Lead-Lag Relationships Between Pork Prices at the Retail, Wholesale, and Farm Levels

Knowledge of the lead-lag relationships among the retail, wholesale, and farm level prices of a livestock commodity is of obvious importance both in econometric model building and in evaluation of packers' and retailers' margins for that commodity. Though the lead-lag relationships for beef prices have been investigated in several previous studies (Barksdale et al.; Franzmann and Walker; King; Miller; National Commission on Food Marketing), the only known previous study of the lead-lag relationships for pork is that made by the National Commission on Food Marketing (hereafter abbreviated NCFM). As that study used data for 1962-1965, changes in the pork marketing system in subsequent years may have in turn occassioned changes in the lead-lag relationships. The changes in the pork marketing system include changes in market structure at the farm, packer, and retail levels, increased use of formula pricing, and the demise of terminal markets, among others. Also, as discussed hereafter, the statistical method used in the NCFM analysis of lead-lag relationships involved certain problems which may invalidate the conclusions drawn in that study.

Granger, C. W. J., and Paul Newbold. Forecasting Economic Time Series. New York: Academic Press, 1977, xiii + 333 pp., $@@‐@@22.00

Economic Theory, Econometrics, and Mathematical Economics, Second Edition: Forecasting Economic Time Series presents the developments in time series analysis and forecasting theory and practice. This book discusses the application of time series procedures in mainstream economic theory and econometric model building. Organized into 10 chapters, this edition begins with an overview of the problem of dealing with time series possessing a deterministic seasonal component. This text then provides a description of time series in terms of models known as the time-domain approach. Other chapters consider an alternative approach, known as spectral or frequency-domain analysis, that often provides useful insights into the properties of a series. This book discusses as well a unified approach to the fitting of linear models to a given time series. The final chapter deals with the main advantage of having a Gaussian series wherein the optimal single series, least-squares forecast will be a linear forecast. This book is a valuable resource for economists.