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A short comment on the JE Open forum essays
KRISHNAKUMAR, Jaya
KRISHNAKUMAR, Jaya. A short comment on the JE Open forum essays. Journal of Econometrics , 2001, vol. 100, p. 77-78
DOI : 10.1016/S0304-4076(00)00060-9
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Journal of Econometrics 100 (2001) 77}78
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A short comment on the JE Open forum essays
Jaya Krishnakumar*
Department of Econometrics, Faculty of Economics and Social Sciences, University of Geneva, 102, bd Carl-Vogt, 1211 Geneve 4, Switzerland
The past century has seen great developments in the use of mathematical and statistical methods in the analysis and comprehension of economic phenomena.
The range of areas in which econometric methods are successfully applied, has steadily widened including more and more behavioral sciences like sociology, political science, psychology and business management, and this has in turn led to many theoretical advances in this"eld. In my opinion this is one of the most important achievements of this new science, which makes one hopeful of the future of this science and look forward to another very exciting century.
Eminent econometricians have presented their expert views in this collection of essays and have discussed a broad spectrum of research topics. Though there is little more to add to their statements and conclusions, I would like to highlight and give further emphasis on two of these directions in particular. I will mainly refer to the essays of Engle, Bollerslev, Tauchen, Granger and Phillips. I will not go into the technical aspects for want of space and will also limit references outside this collection for the same reasons.
Financial econometrics is one area to bet on without any hesitation. As economic growth is making more and more people wealthier (albeit widening the gap between the rich and the poor) and with the rapid progress in informa- tion technology, there will be a continuous need for improving the performance
of "nancial models in forecasting returns, making use of all the information
available, in particular the ultra high-frequency intra daily data, as pointed out by Engle, Bollerslev and Tauchen. I see the development of multivariate and simultaneous extensions of"nancial models as one area where research needs to continue, as the evolution of di!erent asset prices/returns are not only correlated
*Corresponding author. Tel.:#41-22-705-8220; fax:#41-22-705-8299.
E-mail address:[email protected] (J. Krishnakumar).
0304-4076/01/$ - see front matter 2001 Elsevier Science S.A. All rights reserved.
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among one another but also depend on each other. Building multiple simulta- neous systems describing the inter-dependence of such phenomena, that can use panel high-frequency data on numerous inter-related and volatile variables may be very useful in providing greater insight in the understanding of these phe- nomena.
The same is true in the case of macroeconomic analysis. As Phillips mentions, time trends/unit roots have no explanatory power for a phenomenon. Hence, we need to specify structural models that take account of the time series properties of the variables involved. Hsiao (1997) is a leader in this direction and concludes that as long as cointegration properties are veri"ed among the integrated variables of each structural equation, the classical procedures remain valid.
However, the empirical veri"cation of the cointegration properties may itself lead to fundamental speci"cation questions as the cointegrating relation may not re#ect an economic relation and thus an econometrically valid equation may not have an economic meaning and vice versa. Pooling data from several countries (or States within a country) can help in such cases and their poolability needs to be studied, as noted by Granger. Though panel data extensions of simultaneous models are available, they need to be revisited in order to incor- porate the time series properties of the variables appearing in the model, along the lines of Phillips and Moon (1999).
References
Hsiao, C., 1997. Cointegration and dynamic simultaneous equations model. Econometrica 65 (3), 647}670.
Phillips, P.C.B., Moon, H.R., 1999. Linear regression limit theory for nonstationary panel data.
Econometrica 67 (5), 1057}1112.
78 J. Krishnakumar/Journal of Econometrics 100 (2001) 77}78
