Estimating price elasticity of demand for electricity: the case of Japanese manufacturing industry

Abstract

Many papers have estimated the residential and/or industrial price elasticity of demand for electricity. Most papers that study industrial elasticities analyze the elasticity for the whole industrial sector. Only a few studies have estimated elasticities for individual sectors, but even then, sectors are classified by broad divisions (alphabetical-letter industrial classification) such as agriculture, manufacturing, and services. Studies that classify sectors by major groups (two-digit industrial classification) such as food, chemicals or iron are rare. Companies that require large amounts of electricity will likely be influenced by an increase in the electricity price. After the Great East Japan Earthquake in 2011, activities at all nuclear power plants were halted. Electric power companies switched to generating electric power using thermal power plants instead of nuclear plants. This increased the electricity price because thermal power plants use expensive fossil fuels such as coal, petroleum, and liquefied natural gas (LNG). The increase in the electricity price imposed a heavy burden on manufacturing companies that consume a large amount of electricity. Some papers have discussed the fact that certain domestic manufacturing companies faced disadvantages and accelerated off-shoring when electricity prices increased. Hosoe (Appl Econ 46(17):2010–2020, 2014) simulated the effects of the power crisis on Japanese industrial sectors using a CGE (Computable General Equilibrium) model. The simulation indicated that the power crisis would decrease domestic output of the wood, paper and printing, pottery, steel and nonferrous metal, and food sectors in Japan, and would accelerate their foreign direct investment. For this paper we estimated the price elasticity of the electricity demand for each industry (major groups) in manufacturing, using the partial adjustment model and the Kalman filter model. In the partial adjustment model, the elasticity of electricity demand of manufacturing in aggregate is − 0.400. Other studies showed that the elasticities of electricity demand including different industrial sectors range from − 0.034 to − 0.300. We found that demand in the manufacturing sector is more elastic than in the aggregate of industrial sectors. They also found that elasticities differ greatly between sectors (major groups) in manufacturing. Sectors with more elastic electricity demand than the aggregate of manufacturing include textile mill products (− 0.775) followed by plastic, rubber and leather products (− 0.701), ceramic, stone and clay products (− 0.701), pulp, paper and paper products (− 0.570), printing and allied industries (− 0.530), machinery (− 0.485), food, beverages, tobacco and feed (− 0.468), miscellaneous manufacturing industries (− 0.413), and lumber and wood products (− 0.403). On the other hand, the less elastic sector is iron, steel, non-ferrous metals and products (− 0.251). The chemical and allied products (− 0.147) sector is not statistically significant at 5% level. In general, less elastic industries need electricity more. In other words, electricity is a necessary good for inelastic industries. The low elasticity implies that these industries cannot reduce electricity consumption even when electricity prices increase. This implies that a high electricity price is a heavy burden on these companies. Inelastic industries can move their operations overseas to access cheaper electricity or they can stop their operations when the price of electricity increases. We believe that policy makers should consider the elasticity of electricity demand because an increase in electricity price has the real possibility of aggravating de-industrialization and/or raising the unemployment rate.