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See graph. The drought in the plain states has made grain, and therefore feed, quite expensive. Many ranchers cannot afford to feed their cattle, and have sold much of their herd for slaughter. What will be the immediate effect of this event on the equilibrium price and quantity of beef? Illustrate using a supply and demand diagram. Slaughtering the cows will result in an increase in the supply of beef to the market, which will in turn lead to a decrease in the equilibrium price of beef and an increase in the equilibrium quantity of beef.

Market for beef. Chicken and beef are substitute goods. Illustrate the effect that the slaughter of the cattle herds will have on the equilibrium price and quantity of chicken. As the price of beef decreases, consumers will buy more beef and less chicken. The demand for chicken will decrease, causing a decrease in the equilibrium price and quantity of chicken.

Market for chicken c. As it happens, the slaughter of beef cattle has coincided with a decrease in consumers' income.

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Demand and income

Assuming that steak is a normal good while hamburgers are an inferior good, use a supply-and-demand diagram for either market to illustrate the combined effect of the two aforementioned events on the equilibrium price and quantity of hamburgers and steak. As consumers' income decreases, the demand for normal goods such as steak decreases while the demand for inferior goods such as hamburgers increases. Keep in mind that our conclusion from part a is still valid. A lower price of beef will increase the supply of all goods in which beef is an input.

Therefore in each of the two markets in question we deal with simultaneous shifts in supply and demand. Assume that the markets for sugar cane, rum, and whiskey are initially in equilibrium. Assume further that Hurricane Marilyn destroys much of the Jamaican sugar cane crop. Sugar cane is a principal ingredient in rum, but it is not an ingredient in whiskey.

Analyze the effect of the hurricane on the markets for each of the three goods. Explain using graphs. Step One - The market for sugar cane The Hurricane results in a decrease in supply at any given price, sellers are no longer able to provide as much cane as they used to. Ashenfelter and D. Card eds. Elsevier: Netherlands.


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Kowalewski, K. Krueger D. Evidence and Theory. Laibson, D. Repetto, and J. Levy, S. Maki, D. Morgan, D.

Prelec, D. Rae, J. The Sociological Theory of Capital. London: McMillan. Ryscavage, P. Income Inequality in America. Armonk, NY: M. Soloman, M. Soman, D. Stires, D. Sullivan, T.

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Warren, and J. New Haven: Yale University Press. Thaler, R. Veblen, T. Comparisons with prior studies are based on the supplemental tables from [ 2 , 3 ] and published references in [ 1 ]. The present analysis is based on estimates obtained from primary studies for beer elasticities, studies for wine, studies for distilled spirits, and 66 studies for total alcohol demand. Compared to Wagenaar et al. Household survey studies are included if they provide population-level elasticities and standard errors.

Aggregate studies and household surveys are excluded if prices are not included.

Income Effect vs. Price Effect: What’s the Difference?

Studies are excluded if based predominantly on older data pre Duplicates are excluded. These elasticities are not comparable to aggregate quantity elasticities. Data from each study were collected and recorded by the author, including page or table numbers for primary estimates. No elasticity values were estimated, which is a reason for excluding most linear model estimates. Empirical studies in economics frequently report multiple estimates based on the same data or major portions of the same data set.

Using all estimates creates intra-study dependence or correlation, which will bias summary statistics. More weight is assigned to primary studies with multiple estimates than to studies with one or two estimates.

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

Equally important, using multiple estimates will bias standard errors of summary statistics, with understatement of errors being the generally expected outcome [[ 7 ], p. Inter-study dependence also occurs when primary investigators use the same data to estimate different models in separate publications or different investigators use the same data or very similar data.

Following Fogarty [[ 1 ], p. While this restriction reduces intra-study dependence, it does not address inter-study dependence. In particular, several authors have published multiple studies using similar data sets, such as country-level models using annual time series. The extracted data are in Additional file 2. Summaries of averages in three prior analyses are reported for comparison. Unweighted medians are reported for full samples used in this study. Trimming the sample has no effect on unweighted medians and only a small effect on unweighted means.

Weighted means for trimmed samples are reported using fixed-effect FE and random-effects RE models. In meta-analysis, fixed-effect models use inverse variances for weights, with dispersion in estimates due solely to stochastic sampling error in each primary study [ 13 , 14 ]. That is, all studies are viewed as estimating a common , or fixed, population effect size.

Estimates with smaller standard errors provide more precise information about the population value and are given greater weight. The plural or random-effects model also accounts for variation in population values by estimating a common inter-study variance based on observed dispersion of estimates, which is added to the study-level variance.

Inverses of combined variances provide weights for each effect size. Thus, in the random-effects model, true effect sizes are similar or comparable, but not identical across studies. This is the simplest procedure for addressing heterogeneity among estimates. Compared to fixed-effects, random-effect models assign greater weight to less precise studies and, as pointed out by Fogarty [ 1 ], p. Unweighted averages are similar for the several analyses, suggesting that prior analyses are not biased on sampling grounds. Average beer price elasticities range from For income, the ranges are beer, 0.

Unweighted averages for income elasticities are approximately: beer, 0. Results for weighted means indicate less elastic demands, especially FE means for prices.