Economies of scale and utilization swiss electricity distribution industry


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  • T: index of technology
  • T: time for shift in tech representing change in tech. efficiency
  • Economies of scale and utilization swiss electricity distribution industry

    1. 1. Economies of Scale andUtilization in the Swiss Electric Power Distribution Industry Author: Massimo Filippini Presenters: Arvind K. Yadav Rashi Saxena
    2. 2. Electric Utility Industry• Local monopolies• Cyclical demand• Require spare capacity for peak periods – Too high? – Over-capitalization?• Swiss electricity distribution industry – Economies of scale empirically evident
    3. 3. Cost Structure• Convention: long-run cost functions• Implication: – static equilibrium – Optimal utilization of inputs• Contention: Absence of static equilibrium w.r.t. stock of capital (quasi-fixed)• Implication: Economies of scale based on LR cost function may be imprecise
    4. 4. Suboptimal capacity: Supporting arguments• Costly adjustment to time profile of electricity demand – Longevity of transformers and distribution lines – Long-term load forecasts and distribution planning (inaccurate)• Legal obligation to maintain excess capacity – Service guarantee – Exclusivity of territorial franchise
    5. 5. Variable Cost Function• To model production structure• Takes account of sub optimality• Physical capital can’t be adjusted to minimize TC during observation period Production function … y= F(x1,x2,…, xg; k1,k2,…ke; q1,q2,…qn; T) ❶ – Y: output; x: inputs; k: quasi fixed inputs; q: operating and o/p characteristics variable; T: vector of time shifts
    6. 6. Variable Cost FunctionProperties Inputs• Concave and linearly • Labor homogenous in i/p prices • Purchased power• Non-decreasing in input • Quasi fixed input capital prices• Decreasing in quasi fixed inputs VC function of a Swiss electricity distribution utility VC = VC (y, wp, wl, k, T, LF, FDj) ❷ -y: output (kWh); wp, wl : kWh i/p and labor prices -K: stock of capital; T: time; LF: load factor; FD: firm specific variables
    7. 7. Translog function Sl = βl + µu ln (wl/wp) + ωyl ln y + πlk ln k + ᵟ ln LF ❸ lLF• Tested for – Homotheticity – Cobb-Douglas technology
    8. 8. Data/Structure• Swiss electric power industry• 1200 firms (public/private) – 900: municipals – 300: urban/regional • Generation/Transmission/Distribution: small amount of power generated• 10 main utilities vertically integrated – Generation/Transmission/Distribution: backbone• 74%: distribution utilities
    9. 9. Caveats and Procedure• Publically owned• Data available: 60 utilities• Utilities with more than 20% of their capital invested in generating activities (21 nos.): excluded 39 distribution utilities serving cities were analyzed• Measures of capital stock: – Capacity measure – Cost measure (data N.A.)
    10. 10. Results• Four models: – Model 1: Estimates of VC function model specified in ❸ – Model 2: homotheicity assumed – Model 3: corresponding to Cobb-Douglas technology – Model 4: ignores firm-specific effects, biased• Statistically significant coefficients• Cost elasticity < 1
    11. 11. ResultsExpected Estimated• VC function should be • Labor cost share is increasing w.r.t. output positive; increasing in and input prices input prices• Concave w.r.t. input • Concavity is satisfied prices • Increase in capital cost with increase in capacity;• Non-increasing VC w.r.t. non-increasing VC w.r.t. capital stock capital stock not satisfied • Cobb-Douglas and identical fixed-effects hypothesis: rejected
    12. 12. LR Results• Marginally increasing in capital stock increases (not decreases, as expected in cost theory) VC• Interpretations – Positive sign of coeff. of capital stock indicates excessive amount of capital stock employed by firms – Incorrect sign of coeff. of capital stock comes from multicollinearity between output and capital stock • More precise as based on empirical analysis • Causes unexplained
    13. 13. LR Results• Cause of positive sign of coeff. of capital stock: empirical difficulty in defining/calculating capital stock variable• Lack of data  SR cost studies use physical measures  reflect max. available production capacity  highly correlated with increasing output  multicollinearity• Solution: calculate capital stock using capital inventory method Estimation results are inconclusive to LR cost minimization hypothesis
    14. 14. Economies of utilization and scale• According to results: – Utilization and scale economies exist – If S/M/L companies increase output with holding capacity fixed, VC increases less than proportionally – Increase in output without holding capacity fixed increases TC less than proportionally – Importance of utilization and scale economies increases with size Empirical results confirm economies of scale in Swiss electric distribution utilities
    15. 15. Conclusions• Economies of scale exist for S/M/L utilities• Inconclusive regarding over-capitalization• Policy implications: – Utilities should operate as local franchised monopolies – Redesign on economic incentives to promote optimal behavior – Encourage competition and merger policy
    16. 16. THANK YOU