Limits...
Meta-analysis of alcohol price and income elasticities - with corrections for publication bias.

Nelson JP - Health Econ Rev (2013)

Bottom Line: Adjusting for outliers is important to avoid assigning too much weight to studies with very small standard errors or large effect sizes.For individual beverages, corrected price elasticities are smaller (less elastic) by 28-29 percent compared with consensus averages frequently used for alcohol beverages.These new results imply that attempts to reduce alcohol consumption through price or tax increases will be less effective or more costly than previously claimed.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Economics, Pennsylvania State University, University Park, PA 16802, USA. jpn@psu.edu.

ABSTRACT

Background: This paper contributes to the evidence-base on prices and alcohol use by presenting meta-analytic summaries of price and income elasticities for alcohol beverages. The analysis improves on previous meta-analyses by correcting for outliers and publication bias.

Methods: Adjusting for outliers is important to avoid assigning too much weight to studies with very small standard errors or large effect sizes. Trimmed samples are used for this purpose. Correcting for publication bias is important to avoid giving too much weight to studies that reflect selection by investigators or others involved with publication processes. Cumulative meta-analysis is proposed as a method to avoid or reduce publication bias, resulting in more robust estimates. The literature search obtained 182 primary studies for aggregate alcohol consumption, which exceeds the database used in previous reviews and meta-analyses.

Results: For individual beverages, corrected price elasticities are smaller (less elastic) by 28-29 percent compared with consensus averages frequently used for alcohol beverages. The average price and income elasticities are: beer, -0.30 and 0.50; wine, -0.45 and 1.00; and spirits, -0.55 and 1.00. For total alcohol, the price elasticity is -0.50 and the income elasticity is 0.60.

Conclusions: These new results imply that attempts to reduce alcohol consumption through price or tax increases will be less effective or more costly than previously claimed.

No MeSH data available.


a Beer price elasticities (n = 172, FE mean = -0.26). b Wine price elasticities (n = 178, FE mean = -0.34). c Spirits price elasticities (n = 182, FE mean = -0.49).
© Copyright Policy - open-access
Related In: Results  -  Collection


getmorefigures.php?uid=PMC3722038&req=5

Figure 1: a Beer price elasticities (n = 172, FE mean = -0.26). b Wine price elasticities (n = 178, FE mean = -0.34). c Spirits price elasticities (n = 182, FE mean = -0.49).

Mentions: A standard method for detecting publication bias is a funnel graph. Briefly, the horizontal scale measures the effect size and the vertical scale measures the standard error (or precision). In the absence of publication bias, a plot of effects against their errors should be symmetric about a weighted mean. However, a “funnel-shaped” plot is expected due to heteroskedasticity as larger effects tend on average to have larger errors regardless of publication bias. In the presence of bias, a plot can be either less dense or asymmetric. First, suppose the true effect in the population is zero. If studies with significant results are more likely to be published, bias is revealed in the plot as an empty area around zero that results from non-publication of insignificant or results regardless of direction or sign. Second, suppose instead that the true effect is not zero, but rather some small or moderate value. Bias will appear as an asymmetric plot as studies with small effects and large errors are less likely to be published or reported. Asymmetry also reveals the direction of bias as successful publication tends to be associated with both sign and significance of results. Funnel plots are an informal method, so it is important to recognize that a skewed plot also can result from underlying heterogeneity in the sample. Figures 1a – 1c show funnel graphs for price elasticities for beer, wine, and spirits. The vertical line in each graph is the fixed-effect mean, reflecting a concern that random-effects are partly due to publication bias [[16], p. 82]. Diagonal lines indicate 95% confidence intervals. The graphs indicate asymmetry with a negative bias in primary estimates, which implies that reported estimates tend toward more elastic values.


Meta-analysis of alcohol price and income elasticities - with corrections for publication bias.

Nelson JP - Health Econ Rev (2013)

a Beer price elasticities (n = 172, FE mean = -0.26). b Wine price elasticities (n = 178, FE mean = -0.34). c Spirits price elasticities (n = 182, FE mean = -0.49).
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3722038&req=5

Figure 1: a Beer price elasticities (n = 172, FE mean = -0.26). b Wine price elasticities (n = 178, FE mean = -0.34). c Spirits price elasticities (n = 182, FE mean = -0.49).
Mentions: A standard method for detecting publication bias is a funnel graph. Briefly, the horizontal scale measures the effect size and the vertical scale measures the standard error (or precision). In the absence of publication bias, a plot of effects against their errors should be symmetric about a weighted mean. However, a “funnel-shaped” plot is expected due to heteroskedasticity as larger effects tend on average to have larger errors regardless of publication bias. In the presence of bias, a plot can be either less dense or asymmetric. First, suppose the true effect in the population is zero. If studies with significant results are more likely to be published, bias is revealed in the plot as an empty area around zero that results from non-publication of insignificant or results regardless of direction or sign. Second, suppose instead that the true effect is not zero, but rather some small or moderate value. Bias will appear as an asymmetric plot as studies with small effects and large errors are less likely to be published or reported. Asymmetry also reveals the direction of bias as successful publication tends to be associated with both sign and significance of results. Funnel plots are an informal method, so it is important to recognize that a skewed plot also can result from underlying heterogeneity in the sample. Figures 1a – 1c show funnel graphs for price elasticities for beer, wine, and spirits. The vertical line in each graph is the fixed-effect mean, reflecting a concern that random-effects are partly due to publication bias [[16], p. 82]. Diagonal lines indicate 95% confidence intervals. The graphs indicate asymmetry with a negative bias in primary estimates, which implies that reported estimates tend toward more elastic values.

Bottom Line: Adjusting for outliers is important to avoid assigning too much weight to studies with very small standard errors or large effect sizes.For individual beverages, corrected price elasticities are smaller (less elastic) by 28-29 percent compared with consensus averages frequently used for alcohol beverages.These new results imply that attempts to reduce alcohol consumption through price or tax increases will be less effective or more costly than previously claimed.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Economics, Pennsylvania State University, University Park, PA 16802, USA. jpn@psu.edu.

ABSTRACT

Background: This paper contributes to the evidence-base on prices and alcohol use by presenting meta-analytic summaries of price and income elasticities for alcohol beverages. The analysis improves on previous meta-analyses by correcting for outliers and publication bias.

Methods: Adjusting for outliers is important to avoid assigning too much weight to studies with very small standard errors or large effect sizes. Trimmed samples are used for this purpose. Correcting for publication bias is important to avoid giving too much weight to studies that reflect selection by investigators or others involved with publication processes. Cumulative meta-analysis is proposed as a method to avoid or reduce publication bias, resulting in more robust estimates. The literature search obtained 182 primary studies for aggregate alcohol consumption, which exceeds the database used in previous reviews and meta-analyses.

Results: For individual beverages, corrected price elasticities are smaller (less elastic) by 28-29 percent compared with consensus averages frequently used for alcohol beverages. The average price and income elasticities are: beer, -0.30 and 0.50; wine, -0.45 and 1.00; and spirits, -0.55 and 1.00. For total alcohol, the price elasticity is -0.50 and the income elasticity is 0.60.

Conclusions: These new results imply that attempts to reduce alcohol consumption through price or tax increases will be less effective or more costly than previously claimed.

No MeSH data available.