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Effects of smoking on productivity: estimating aggregate production technology using cross-sectional time series data

Author

Listed:
  • Euston Quah
  • Sutaip L.C. Saw
  • Khye-Chong Tan
  • Jongsay Yong

    (Nanyang Technological University
    Nanyang Technological University
    Nanyang Technological University
    University of Melbourne)

Abstract

The negative health effects of smoking are substantial and well documented. There are, however, few studies that focus on another aspect of the costs of smoking, namely its impact on productive activities, specifically in terms of productivity loss as a result of smoking. Previous economic studies of smoking tend to focus on the effectiveness of various smoking control measures, and the externalities of smoking in the form of higher health care costs that smokers impose on the wider community. The present study make use of aggregate time-series and cross-sectional data to carefully examine the relationship between smoking and productivity as measured by a properly specified and estimated aggregate production function. The questions we examine are whether smoking affects productivity, and if so, by how much. The empirical analysis makes use of data of 14 OECD countries over a period of 23 years, from 1970 to 1992. The results indicate that smoking appears to be a statistically significant factor in explaining productivity, in both level and growth. There is, however, no firm evidence that smoking has an adverse effect on productivity, although results from the output growth model appear to indicate that the effects are mostly negative, especially for countries with high per capita tobacco use.

Suggested Citation

  • Euston Quah & Sutaip L.C. Saw & Khye-Chong Tan & Jongsay Yong, 2005. "Effects of smoking on productivity: estimating aggregate production technology using cross-sectional time series data," Journal of Developing Areas, Tennessee State University, College of Business, vol. 39(1), pages 41-53, September.
  • Handle: RePEc:jda:journl:vol.39:year:2005:issue1:pp:41-53
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    More about this item

    Keywords

    Smoking; Productivity; Technology;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment
    • I1 - Health, Education, and Welfare - - Health

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