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A comparison of regression and ARIMA models for assessing program effects: An application to the mandated highway speed limit reduction of 1974

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Abstract

Time series analysis is a technique which has been utilized by econometricians and others for examining the relationship between events and time, particularly for forecasting purposes. More recent work has focused on time series analysis as a method to evaluate the effects of an exogenous event on a series. The major advantage of the interrupted time series design over a simple pre-post comparison is that the form of the change is taken into account. This paper will examine two alternative models for analyzing such data: regression and ARIMA. An example of the application of the two models will be demonstrated using data on highway deaths in North Carolina occurring before and after the national reduction in speed limits instituted in 1974. Conclusions are drawn about the comparative usefulness of these two techniques for program evaluation.

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Bibliography

  1. Barr, A. J., Goodnight, J. H., Sall, J. P., Blair, W. H. and Chilko, D. M.: 1979, SAS User's Guide (SAS Institute, Inc., Raleigh, NC).

  2. Box, G. E. P. and Jenkins, G. M.: 1976, Time Series Analysis: forecasting and control, Revised Edition (Holden-Day, Inc., San Francisco).

  3. Campbell, D. T. and Stanley, J. C.: 1963, Experimental and quasi-experimental Designs for Research (Rand McNally, Chicago).

  4. Committee on Traffic and Highway Safety of the Highway Division: 1980, ‘The 55 MPH speed limit: a review’, Transportation Engineering Journal 106, pp. 299–307.

  5. Gillings, D., Makuc, D., and Siegel, E.: 1981, ‘Analysis of interrupted time series mortality trends: an example to evaluate regionalized perinatal care’, American Journal of Public Health 71, pp. 38–46.

  6. Institute of Transportation Engineers: ‘Ramifications of the 55 MPH speed limit’, Final Report of Committee 4M-2.

  7. McCain, L. J. and McClearly, R.: 1979, ‘The statistical analysis of the simple interrupted time series quasi-experiment’, in: T. D. Cook and D. T. Campbell (eds.): Quasi-Experimentation: Design and Analysis Issues for Field Settings (Rand-McNally, Chicago).

  8. McCleary, R. and Hay, R. A.: Applied Time Series Analysis for the Social Sciences (Sage Publications, Inc., Beverly Hills, CA).

  9. Theil, H.: 1971, Principles of Econometrics (John Wiley and Sons, Inc., New York).

  10. U.S. Department of Transportation: 1980, ‘Effect of the 55 MPH speed limit on traffic accidents in Illinois’, NHTSA Technical Report, DOT HS-805 400, National Highway Traffic Administration, Office of Program and Demonstration Evaluation.

  11. What's wrong with 55 MPH?’, Consumer's Research Magazine 63 (1980), pp. 18–20.

  12. Wonnacott, R. H. and Wonnacott, T. H. 1979, Econometrics, Second Edition (John Wiley and Sons, Inc., New York).

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Veney, J.E., Luckey, J.W. A comparison of regression and ARIMA models for assessing program effects: An application to the mandated highway speed limit reduction of 1974. Soc Indic Res 12, 83–105 (1983). https://doi.org/10.1007/BF00428862

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Keywords

  • Time Series
  • Recent Work
  • Alternative Model
  • Time Series Analysis
  • Program Evaluation