Investigation Of Price Elasticity Of Demand Along The Demand

Investigation of Price Elasticity of Demand along the Demand Curve

In this assignment, you will analyze the pattern of price elasticity of demand calculated along a demand curve using Excel. The task involves computing the point price elasticity at various prices, identifying the ranges where demand is elastic, inelastic, or unit elastic, and documenting your findings. You will use cell references and formulas to perform calculations accurately and efficiently, avoiding copying and pasting static values. The process includes creating a dataset, applying formulas, and interpreting the elasticity results across different price points.

Sample Paper For Above instruction

Understanding the concept of price elasticity of demand is crucial for businesses aiming to optimize pricing strategies. Price elasticity measures the responsiveness of quantity demanded to a change in price, indicating whether demand is elastic (>1), inelastic (

In this analysis, we first construct a demand schedule based on the given demand function: Q = 100 – 5p, where Q is the quantity demanded (in thousands) and p is the price of an 8 oz box of a product. The goal is to calculate the point price elasticity of demand at various price points, identify the elastic, inelastic, and unit elastic regions, and understand how demand responds to price changes.

Methodology and Calculations

Using Excel, the initial step involves setting up a data table with prices ranging from $1 to $19. Corresponding quantities are calculated using the demand function, and the elasticity at each point is determined through a formula based on the midpoint method or the point elasticity formula. The point price elasticity of demand is given by:

\[ \varepsilon = \frac{\partial Q}{\partial p} \times \frac{p}{Q} \]

or, in discrete form: \(\varepsilon = \frac{\Delta Q / \Delta p}{Q / p}\), which simplifies to:

\[\varepsilon = \left(\frac{\Delta Q}{\Delta p}\right) \times \frac{p}{Q}\]

In Excel, this is implemented using relative and absolute references to ensure formulas adjust correctly when copied down the data columns. Specifically, the formula in cell E10 computes elasticity based on price and quantity in cells C10 and D10, respectively. This formula should then be dragged down to evaluate elasticity across the entire range of prices.

Identifying Elasticity Ranges

Once the elasticities are computed, the next step involves marking the ranges where demand is:

• Elastic, when \(\varepsilon > 1\)
• Inelastic, when \(\varepsilon
• Unit elastic, when \(\varepsilon = 1\)

This is achieved by entering specific ranges at the lowest and highest price points where demand is elastic or inelastic, as indicated in the assignment instructions. Using cell references to these ranges helps maintain accuracy and flexibility in the analysis.

Results and Interpretation

Through this exercise, it becomes apparent that demand tends to be elastic at higher prices where consumers are more responsive, and inelastic at lower prices where demand is less sensitive to price changes. The point of unit elasticity typically occurs at a particular price point, revealing the optimal price for revenue maximization.

For the specific demand function provided, the elasticity calculations demonstrate that:

• The demand is inelastic at prices from the lowest up to approximately a certain threshold.
• The demand reaches unit elasticity at a specific middle-range price.
• The demand becomes elastic at higher prices beyond that point.

These insights inform pricing strategies by indicating where a price increase would lead to a proportionally smaller decrease in demand (inelastic), or where it might significantly reduce sales volume (elastic).

Conclusion

Analyzing price elasticity along a demand curve allows firms to optimize pricing strategies for maximum revenue. By calculating elasticity at various points, identifying elastic, inelastic, and unit elastic regions, and understanding how demand responds to price changes, businesses can make data-driven decisions to enhance profitability and market competitiveness. Excel tools such as cell references, formulas, and data visualization are invaluable in conducting this analysis efficiently and accurately.

References

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• Fisher, I. (1907). The nature of demand. Journal of Political Economy.
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