T: time for shift in tech representing change in tech. efficiency
Transcript
1.
Economies of Scale andUtilization in the Swiss Electric Power Distribution Industry Author: Massimo Filippini Presenters: Arvind K. Yadav Rashi Saxena
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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
Be the first to comment