You are here

Tahmin çıktıları ile ekonomik modelleri degerlendirmeme üzerine

On not evaluating economic models by forecast outcomes

Journal Name:

Publication Year:

Abstract (2. Language): 
Even in scientific disciplines, forecast failures occur. Four possible states of nature (a model is good or bad, and it forecasts well or badly) are examined using a forecast-error taxonomy, which traces the many possible sources of forecast errors. This analysis shows that a valid model can forecast badly, and a poor model can forecast successfully. Delineating the main causes of forecast failure reveals transformations that can correct failure without altering the ‘quality’ of the model in use. We conclude that judging a model by the accuracy of its forecasts is more like fools’ gold than a gold standard.
Abstract (Original Language): 
Tahmin basarısızlıkları bilimsel disiplinlerde dahi gerçeklesmektedir. Bu çalısmada tahmin hatalarının pek çok olası kaynagını izleyen tahmin-hata sınıflandırması kullanılarak dört olası durum (bir model iyi ya da kötüdür ve iyi ya da kötü tahminler) incelenmistir. Bu analiz, geçerli bir modelin kötü tahmin yapabilecegini ve zayıf bir modelin basarılı tahmin yapabilecegini göstermektedir. Tahmin basarısızlıgının temel sebeplerini tarif etmek, kullanılan modelin ‘kalitesi’ni arttırmadan basarısızlıgı düzelten dönüsümleri ortaya çıkarmıstır. Sonuç bölümünde, bir modeli tahminlerinin geçerliligine dayanarak degerlendirmenin göz boyamaktan ibaret oldugu üzerinde durulmustur.
1-14

REFERENCES

References: 

[1] C.W.J. Granger and M.H. Pesaran, A decision-theoretic approach to forecast
evaluation. In W.S. Chon, W.K. Li, and H. Tong, (eds.), Statistics and Finance: An
Interface, Imperial College Press, London, 2000, pp.261–278.
[2] C.W.J. Granger, Evaluation of forecasts. in [41], 93–103, (2001).
[3] D.F. Hendry, The role of prediction in evaluating econometric models. In
Proceedings of the Royal Society, A407, 25–33, (1986).
[4] M.P. Clements, and Hendry, D.F., Evaluating a model by forecast performance.
Oxford Bulletin of Economics and Statistics, 67, 931–956, (2005).
[5] A. Atkeson, and L. Ohanian, Are Phillips Curves useful for forecasting inflation?.
Federal Reserve Bank of Minneapolis Quarterly Review, 25, 1, 2–11, (2001).
[6] D.F. Hendry and G.E. Mizon, On selecting policy analysis models by forecast
accuracy. In Atkinson, A. B., Glennerster, H., and Stern, N. (eds.), Putting
Economics to Work: Volume in Honour of Michio Morishima, London School of
Economics: STICERD, 2000, pp. 71–113.
[7] R.E. Lucas, Econometric policy evaluation: A critique. In Brunner, K., and Meltzer,
A. (eds.), The Phillips Curve and Labor Markets, Vol. 1 of Carnegie-Rochester
Conferences on Public Policy, North-Holland Publishing Company, Amsterdam,
1976, pp.19–46.
[8] J. Aldrich, Autonomy. Oxford Economic Papers, 41, 15–34, (1989).
[9] N.R. Ericsson and J.S. Irons, The Lucas critique in practice: Theory without
measurement. In Hoover, K.D. (ed.), Macroeconometrics: Developments, Tensions
and Prospects, Kluwer Academic Press, Dordrecht, 1995, pp.263–312.
[10] A.A. Carruth, M.A. Hooker and A.J. Oswald, Unemployment equilibria and input
prices: Theory and evidence from the United States. Review of Economics and
Statistics, 80, 621–628, (1998).
[11] M.P. Clements, and D.F. Hendry, On the limitations of comparing mean squared
forecast errors. Journal of Forecasting, 12, 617–637, (1993a).
[12] T.C. Mills, Bradford Smith: an econometrician decades ahead of his time. Oxford
Bulletin of Economics and Statistics, DOI: 10.1111/j.1468–0084.2010.00615.x
(2010).
[13] B.B. Smith, Combining the advantages of first-difference and deviation-from-trend
methods of correlating time series. Journal of the American Statistical Association,
21, 55–59, (1926).
[14] B.B. Smith, Forecasting the volume and value of the cotton crop. Journal of the
American Statistical Association, 22, 442–459, (1927).
[15] B.B. Smith, Judging the forecast for 1929. Journal of the American Statistical
Association, 24, 94–98, (1929).
J. L. Castle and D. F. Hendry / 2stanbul Üniversitesi 2sletme Fakültesi Dergisi 40, 1, (2011) 1-14 © 2011
13
[16] D.F. Hendry and J.F. Richard, On the formulation of empirical models in dynamic
econometrics. Journal of Econometrics, 20, 3–33, (1982).
[17] M.P. Clements, and D.F. Hendry, Forecasting Economic Time Series. Cambridge
University Press, Cambridge, 1998.
[18] M.P. Clements, and D.F. Hendry, Forecasting Non-stationary Economic Time
Series. MIT Press, Cambridge, Mass., 1999.
[19] D.F. Hendry, Mathematical models and economic forecasting: Some uses and misuses
of mathematics in economics. Discussion paper 530, Economics Department,
Oxford University, (2011b).
[20] M.P. Clements, and D.F. Hendry, Economic forecasting in a changing world.
Capitalism and Society, 3, 2, 1, 1–18, (2008).
[21] N.R. Ericsson, Comment on ‘Economic forecasting in a changing world’ (by Michael
Clements and David Hendry). Capitalism and Society, 3, 2, 2, 1–16, (2008).
[22] D.F. Hendry, and G.E. Mizon, An open-model forecast-error taxonomy. Working
paper, Economics Department, Oxford University, (2011a).
[23] N.R. Ericsson, Forecast uncertainty in economic modeling. in [41], 68–92, (2001).
[24] M.P. Clements, and D.F. Hendry, On the limitations of comparing mean squared
forecast errors: A reply. Journal of Forecasting, 12, 669–676, (1993b).
[25] M.P. Clements, and D.F. Hendry, Forecasting from Mis-specified Models in the
Presence of Unanticipated Location Shifts. in Oxford Handbook of Economic
Forecasting (2011b), Ch.10. Forthcoming (2011a).
[26] N.R. Ericsson, Parameter constancy, mean square forecast errors, and measuring
forecast performance: An exposition, extensions, and illustration. Journal of Policy
Modeling, 14, 465–495, (1992).
[27] J.L. Castle, N.W.P. Fawcett, and D.F. Hendry, Forecasting with equilibrium-
correction models during structural breaks. Journal of Econometrics, 158, 25–36,
(2010).
[28] J.L. Castle, N.W.P. Fawcett, and D.F. Hendry, Nowcasting is not just
contemporaneous forecasting. National Institute Economic Review, 210, 71–89,
(2009).
[29] D.F. Hendry, Monetary economic myth and econometric reality. Oxford Review of
Economic Policy, 1, 72–84, (1985).
[30] D.F. Hendry, and N.R. Ericsson, Modeling the demand for narrow money in the
United Kingdom and the United States. European Economic Review, 35, 833–886,
(1991).
[31] J.L. Castle, N.W.P. Fawcett, and D.F. Hendry, Forecasting Breaks and During
Breaks. in [40], Ch. 11. Forthcoming (2011).
[32] P.J. Miller, Forecasting with econometric methods: A comment. Journal of
Business, 51, 579–586, (1978).
[33] D.F. Hendry, The behaviour of inconsistent instrumental variables estimators in
dynamic systems with autocorrelated errors. Journal of Econometrics, 9, 295–314,
(1979).
[34] R. Harré, The Philosophies of Science. Oxford University Press, Oxford, 1985.
J. L. Castle and D. F. Hendry / 2stanbul Üniversitesi 2sletme Fakültesi Dergisi 40, 1, (2011) 1-14 © 2011
14
[35] A. Spanos, Curve-fitting, the reliability of inductive inference and the error-
statistical approach. Philosophy of Science, 74, 1046–1066, (2007).
[36] D.F. Hendry, On detectable and non-detectable structural change. Structural
Change and Economic Dynamics, 11, 45–65, (2000).
[37] D.F. Hendry and G.E. Mizon, On the mathematical basis of inter-temporal
optimization. Discussion paper 497, Economics Department, Oxford, (2010).
[38] D.F. Hendry and G.E. Mizon, What needs rethinking in macroeconomics? Global
Policy, Forthcoming, (2011b).
[39] D.F. Hendry, Empirical economic model discovery and theory evaluation.
Discussion paper 529, Economics Department, Oxford University, 2011a.
[40] M.P. Clements, and D.F. Hendry, Oxford Handbook of Economic Forecasting.
Oxford University Press, Oxford, 2011b.
[41] D.F. Hendry and N.R. Ericsson, Understanding Economic Forecasts. MIT Press,
Cambridge, Mass., 2001.

Thank you for copying data from http://www.arastirmax.com