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Economic Costs of Unsupplied Electricity: Evidence from Backup Generation Among African Firms Musiliu O. Oseni & Michael Pollitt University of Cambridge Nigerian Association for Energy Economics Conference, 2013. Why is there so much noise about the unreliability of electricity supply …?.
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Economic Costs of Unsupplied Electricity: Evidence from Backup Generation Among African Firms Musiliu O. Oseni & Michael Pollitt University of Cambridge Nigerian Association for Energy Economics Conference, 2013
Why is there so much noise about the unreliability of electricity supply …? • Productivity • Products Marketing (e.g. Internets) • Cost of Production • Electronic Payments ( a great challenge!)
Is it so bad in Africa compared to other regions? • WDI (2003): Seven African countries (Kenya, Nigeria, Uganda, Tanzania, Senegal, Lesotho and Mali) were amongst the first ten countries with highest incidents of power outages.
Between 2006 & 2010, more than 50% of firms in Africa identify electricity as a major constraint compared to transport (27%)
Strategy to cope with this challenge • But this strategy is not without cost however. • Arguably the decision might not only be influenced by outage time alone, Firm’s Xterics might have roles to play • For instance, why would some firms invest in backups while others do not despite facing the same level of outages?
Our research Questions: • To what extent can the variations in (unmitigated) outage costs be explained by firms’ characteristics? • How do firms’ characteristics create incentive for investment in backup generation? • To what extent are firms able to mitigate the effects of outages through backup strategy relative to the unmitigated costs? • Can firms benefit significantly under a cost-reflective tariff regime that ensures reliability?
Theory • Simple investment decision: Firms consider their MC & MB. • A firm facing outages would consider the MC of generating a kWh & the MB of that kWh. • Arguably, the relative MC-MB of a kWh generated would be influenced by firms’ characteristics.
What is known…… • Bental & Ravid (1982): The higher the outages the lower the (marginal) outage cost – US and Israel. • Pasha, Ghaus & Malik (1989): Outage loss accounts for 8.8% of industrial output – planned outage: 65%, unplanned: 35%; multiplier: 1.34, GDP (-1.8%) – (Subjective Valuation) • Beenstock, Goldin & Haitovsky (1997): Reliability varies inversely with demand for backup and total outage cost, but varies directly with marginal cost per kWh unsupplied.
Africa: • Steinbuks & Foster (2010): Firm’s size, emergency backup and export regulations play a critical role in the decision to own generator. • Adenikinju (2003); Steinbuks & Foster (2010): Cost of own generation is higher than the price of electricity supplied from the public grid (Is this because of subsidy?)
Methodology • Marginal Cost (Bental & Ravid, 1982) • Incomplete Backup (Beenstock et al., 1997) • Subjective Valuation (Pasha et al, 1989)
Marginal Cost Method • Total annual exp. Cost (in KW)= yearly generator cost + variable cost G: generator capacity, v: fuel cost per kWh, : total outage time The expected MC (in KW) with respect to gen. capacity is and the expected MC of a kWh from own generation is
Incomplete Backup Method Captures other extra costs due to incomplete investment in backup • Based on Two-Limit Tobit • Dependent variable is a censored variable. Censored as follows: • y*= 0 if firm does not have backup • y*= y if firm invests in incomplete backup (i.e., has backup & still suffer outage loss) • y*= if firm invests in complete backup (i.e., has backup & does not suffer outage loss)
is a row vector of parameters, Z is a vector of observables hypothesised to determine mean inverse of an outage loss The estimated equation is Where Eq. (4) implies that
i.e., the demand for backup varies proportionally with electricity consumption, inversely with the user cost of backup (P), directly with the unreliability of electricity supply (), & with the other firm’s specific characteristics (variables) The unmitigated outage cost per kWh to firm i is estimated as where The total annual outage cost is
Data: World Bank Survey of Business Enterprises Figure 3: Percentage of Firms Identifying Electricity as a Major Constraint and Generator Ownership
Figure 5: Percentage Distribution of the Reported Average Outage Loss Figure 4: Percentage Distribution of the Reported Outage Time Outage time Outage Loss Nigeria (29%) (2%) Mozambique (2%) (56%)
Results Table 1: Estimated Results from Two Limit Tobit
Table 3: Estimates of Unmitigated Cost per kWh Across Sectors
Table4: Unmitigated Cost ($) of power Outage per kWh Based on Firms’ Characteristics *Note: Small: 1-19; Medium: 20-100; Large: 101+
Table 5: Cost ($) of Power Outage per kWh and Cost-Reflective Tariffs * Africa Infrastructure Country Diagnostic (AICD) http://www.infrastructureafrica.org/models/canned/
Conclusions • Despite high demand for backup & clear evidence on how characteristics might create incentives for backup generation, unmitigated cost still constitutes the larger proportion of outage costs. • Although characteristics increase the probability of investing in backup generation, evidence is mixed on how firms’ characteristics might affect unmitigated outage costs. • Using Nigeria as an example, our analysis reveals that the net outage cost per kW is equivalent to the cost of paying two additional workers per annum, and that the amount that can be saved by increasing reliability by just 776 KW per annum is equivalent to 1.6 million jobs. • This suggests that government should be determined to pursue her reforms and ensures cost-reflective tariffs. This will encourage private investors and leads to job creations.
