Forecast Evaluation in Call Centers: Combined Forecasts, Flexible Loss Functions and Economic Criteria
Accurate forecasts of incoming calls are crucial to optimal staffing decisions in call centers. This paper evaluates a wide range of models and forecast combination techniques by means of statistical and economic criteria. Relative to the previous literature, this paper is novel in several respects. In particular, the statistical evaluation of competing models is carried out by using a flexible loss function as input to pairwise and joint forecast diagnostic checks. Informative rankings across alternative single models and different groups of models are obtained. Moreover, models are evaluated from the perspective of a manager, who needs reliable forecasts to dimension the call center. Money metrics of forecasting performance are computed, which are based on the economic value of information and the certainty equivalent.
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- Robert Engle, 2002. "New frontiers for arch models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 425-446.
- Komunjer, Ivana & OWYANG, MICHAEL, 2007.
"Multivariate Forecast Evaluation And Rationality Testing,"
University of California at San Diego, Economics Working Paper Series
qt81w8m5sf, Department of Economics, UC San Diego.
- Ivana Komunjer & Michael T. Owyang, 2012. "Multivariate Forecast Evaluation and Rationality Testing," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1066-1080, November.
- Ivana Komunjer & Michael T. Owyang, 2007. "Multivariate forecast evaluation and rationality testing," Working Papers 2007-047, Federal Reserve Bank of St. Louis.
- Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
- Diebold, Francis X & Mariano, Roberto S, 1995.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 13(3), pages 253-263, July.
- Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Tom Doan, "undated". "DMARIANO: RATS procedure to compute Diebold-Mariano Forecast Comparison Test," Statistical Software Components RTS00055, Boston College Department of Economics.
- Elamin H. Elbasha, 2005. "Risk aversion and uncertainty in cost-effectiveness analysis: the expected-utility, moment-generating function approach," Health Economics, John Wiley & Sons, Ltd., vol. 14(5), pages 457-470.
- Leitch, Gordon & Tanner, J Ernest, 1991. "Economic Forecast Evaluation: Profits versus the Conventional Error Measures," American Economic Review, American Economic Association, vol. 81(3), pages 580-590, June.
- Dorfman, Jeffrey H. & McIntosh, Christopher S., 1997.
"Economic Criteria For Evaluating Commodity Price Forecasts,"
Journal of Agricultural and Applied Economics,
Southern Agricultural Economics Association, vol. 29(02), December.
- Dorfman, Jeffrey H. & Mcintosh, Christopher S., 1997. "Economic Criteria for Evaluating Commodity Price Forecasts," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 29(02), pages 337-345, December.
- Noah Gans & Ger Koole & Avishai Mandelbaum, 2003. "Telephone Call Centers: Tutorial, Review, and Research Prospects," Manufacturing & Service Operations Management, INFORMS, vol. 5(2), pages 79-141, September.
- Franses, Ph.H.B.F. & van Dijk, D.J.C., 2001.
"The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production,"
Econometric Institute Research Papers
EI 2001-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Franses, Philip Hans & van Dijk, Dick, 2005. "The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production," International Journal of Forecasting, Elsevier, vol. 21(1), pages 87-102.
- Robert Neil Collender & James A. Chalfant, 1986. "An Alternative Approach to Decisions under Uncertainty Using the Empirical Moment-Generating Function," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 68(3), pages 727-731.
- Graham Elliott & Allan Timmermann & Ivana Komunjer, 2005. "Estimation and Testing of Forecast Rationality under Flexible Loss," Review of Economic Studies, Oxford University Press, vol. 72(4), pages 1107-1125.
- Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
- Ibrahim, Rouba & Ye, Han & L’Ecuyer, Pierre & Shen, Haipeng, 2016. "Modeling and forecasting call center arrivals: A literature survey and a case study," International Journal of Forecasting, Elsevier, vol. 32(3), pages 865-874.
- Zeng Tian & Swanson Norman R., 1998.
"Predictive Evaluation of Econometric Forecasting Models in Commodity Futures Markets,"
Studies in Nonlinear Dynamics & Econometrics,
De Gruyter, vol. 2(4), pages 1-21, January.
- Zeng, T. & Swanson, N.R., 1997. "Predictive Evaluation of Econometric Forecasting Models in Commodity Futures Markets," Papers 9-97-4, Pennsylvania State - Department of Economics.
- Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
- Peter R. Hansen & Asger Lunde & James M. Nason, 2010.
"The Model Confidence Set,"
CREATES Research Papers
2010-76, Department of Economics and Business Economics, Aarhus University.
- Edward E. Gbur & Robert A. Collins, 1989. "A Small-Sample Comparison of Estimators in the EU-MGF Approach to Decision Making," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(1), pages 202-210.
- Robert Jung & A. Tremayne, 2011. "Useful models for time series of counts or simply wrong ones?," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 59-91, March.
- G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
- James W. Taylor, 2008. "A Comparison of Univariate Time Series Methods for Forecasting Intraday Arrivals at a Call Center," Management Science, INFORMS, vol. 54(2), pages 253-265, February.
- Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
- Garratt A. & Lee K. & Pesaran M.H. & Shin Y., 2003. "Forecast Uncertainties in Macroeconomic Modeling: An Application to the U.K. Economy," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 829-838, January.
- James W. Taylor, 2012. "Density Forecasting of Intraday Call Center Arrivals Using Models Based on Exponential Smoothing," Management Science, INFORMS, vol. 58(3), pages 534-549, March.
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