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# Elasticity Coefficient – Definition

### Elasticity Coefficient Definition

Price elasticity or elasticity coefficient is an economic term which shows the percentage change in quantity demanded due to change in price of goods and services.

### A Little More on What is Elasticity Coefficient

Price elasticity is simply percentage change in quantity demanded divided by percentage change in price of goods and service.

The formula for calculating price elasticity is as following;

Ep= % change in quantity demanded(Q) / % change in price(P)

Example: Price Elasticity

Where Ep represents elasticity coefficient, %ΔQ shows change in quantity demanded, and %ΔP represents change in price of particular goods and services. Let’s assume the price of oil increases by 60%, and the quantity demanded decreases by 20%, the elasticity coefficient will be;

Ep = % Δ Quantity (20%) / % Δ Price (60%) = 0.33

### How to Interpret the Elasticity Coefficient

1) If Ep > 1, demand is elastic. This means that a slight variation in price can produce greater change in quantity demanded. Therefore, hike in prices will negatively affect revenue, as the sales will drop with increase in price and vice versa.

2) If Ep < 1, demand is inelastic for the particular good or service. It means quantity demanded is not affected significantly from variation in price of goods and services. In simple words, there is less change in quantity demanded due to price fluctuation.

3) If Ep = 1, demand for goods is unit elastic. It means quantity demanded is fluctuated in proportion to price of goods and services. Thus, price changes have no effects on revenue of the firm.

### Academic Research on Elasticity Coefficient

• ●      State tax stability criteria and the revenue-income elasticity coefficient reconsidered, Wilford, W. T. (1965). National Tax Journal18(3), 304-312. This paper explores the adequacy criterion, which emphasis on the ability of given state tax structures to meet the expanding needs of state social goods and services. This paper is primarily concerned with a re-evaluation of the adequacy criteria, and with the techniques implemented in the calculation of the adequacy of state revenue structures.
• ●      Factoring the elasticity of demand in electricity prices, Kirschen, D. S., Strbac, G., Cumperayot, P., & de Paiva Mendes, D. (2000). IEEE Transactions on Power Systems15(2), 612-617. This paper explores consumers’ behaviours towards the volatility of electricity prices. The main change in consumers’ behaviour is the modification of their usage to reduce electricity costs.The main objective is to show the effect that the market structure can have on the elasticity of the demand for electricity. A 26 system generator is taken into consideration for purpose of analysis.
• ●      The causal relationship between energy and GNP: an international comparison, Yu, E. S., & Choi, J. Y. (1985). The Journal of Energy and Development, 249-272. This study aims to find the relationship between GNP and energy, and the linkage between GNP and the aggregate, as well as the disaggregate from energy consumption using samples from five different nations. Results show that these findings are sensitive to samples. The study thus goes on to present the marginal and average ratios of the GNP to the aggregate and the disaggregate energy consumption of the five nations and evaluate their relevance and validity.
• ●      The Preliminary Analysis of Change of Elasticity Coefficient of Energy Consumption and the Relevant Causes of China [J], Faqi, S. (2005). Statistical Research5, 002. The author discusses in detail the change of elasticity coefficient of energy consumption of the relevant causes of China since 1978, especially the negative coefficient from 1997 to 1999 and the coefficient larger than one from 2002 to 2004.
• ●      A note on the Nerlove estimate of supply elasticity, Brandow, G. E. (1958). A note on the Nerlove estimate of supply elasticity. Journal of Farm Economics40(3), 719-722. This paper explores Nerlove estimate of supply elasticity. It aims to show that this approach (Nerlove) acreage in any year represents the influence of past market market prices, and other random factors.
• ●      Empirical properties of the elasticity coefficient in the constant elasticity of variance model, Ang, J. S., & Peterson, D. R. (1984). Financial Review19(4), 372-380. This paper explores the different evidence provided by various scholars on the properties of the constant elasticity of variance process. Results shows that these evidence are not sufficient to explain this concept properly. Thus, this article aims to provide further explanation to this concept.
• ●      Disentangling the coefficient of relative risk aversion from the elasticity of intertemporal substitution: An irrelevance result, Kocherlakota, N. R. (1990). The Journal of Finance45(1), 175-190. This paper analyses the relationship between the elasticity of intertemporal substitution (EIS) and the coefficient of relative risk aversion (CRRA) for homothetic time and state separable preferences. To achieve this purpose, the author employs the annual data of the United States as a case study.
• ●      STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts, York, R., Rosa, E. A., & Dietz, T. (2003). Ecological economics46(3), 351-365. This paper studies the specific forces driving human alterations of the environment. The paper defines the causes of the absence of past studies, and proposes a new model for working on this problem. The authors go on to define three analytic formulations, and show the relationship, similar underpinning and different uses of each tool.
• ●      On the elasticity of the real property tax, Kurnow, E. (1963). The Journal of Finance18(1), 56-58. This article examines the economic concept of elasticity in terms of property tax assessment.
• ●      The elasticity of the property tax base: Some cross-section estimates, Bridges, B. (1964). Land Economics40(4), 449-451. This article examines the elasticity of property tax assessment based upon various estimates taken from cross-sections of the population.
• ●      The contribution of publicly provided inputs to states’ economies, Garcia-Mila, T., & McGuire, T. J. (1992). Regional science and urban economics22(2), 229-241.  This paper aims to back the theory of publicly provided infrastructure as an important element of economic growth. To achieve this, the authors employs data from 1969 to 1983 of 46 contiguous states on publicly provided inputs on highway labor and education.