IMPACT OF PRIVATIZATION IN AFRICA: COTE D'IVOIRE ELECTRICITY One of Eight Papers from a Project Entitled: Assessing the Impact of Privatization in Africa Funded by the Norwegian Trust Fund Managed by the Investment Climate Department and Africa Private Sector and Infrastructure Department of the World Bank Yahya Jammal Leroy Jones Boston Institute for Developing Economies (BIDE) October, 2006 These studies focus on identifying and explaining results of various forms of privatization, defined broadly to include any significant transfer of management or ownership from the public to the private sector (that is, management contracts, leases, affermage contracts, concessions and full and partial divestiture). The first goal is to measure performance quantitatively to the extent possible with available data. The second goal is to explain that performance in terms of how the privatization was conducted. A key feature of the study is that performance covers equity as well as efficiency. That is, we attempt to measure the impact on various stakeholders: primarily consumers, workers, the government, and the new owner or operator. In sum, a successful privatization is not just one where the deed gets done, but where performance improves substantially and the results of that change are distributed equitably with sizeable public benefits to help build and sustain political support. The cases include failures as well as successes. One can learn at least as much from the former as the latter. The goal is to help replace faith-based policies with ones that are fact-based. The opinions expressed here are the sole responsibility of the authors and do not reflect those of the World Bank.
Transcript
IMPACT OF PRIVATIZATION IN AFRICA:
COTE D'IVOIRE ELECTRICITY
One of Eight Papers from a Project Entitled: Assessing the Impact of Privatization in Africa
Funded by the Norwegian Trust Fund Managed by the Investment Climate Department and Africa Private Sector and
Infrastructure Department of the World Bank
Yahya Jammal
Leroy Jones
Boston Institute for Developing Economies (BIDE)
October, 2006 These studies focus on identifying and explaining results of various forms of privatization, defined broadly to include any significant transfer of management or ownership from the public to the private sector (that is, management contracts, leases, affermage contracts, concessions and full and partial divestiture). The first goal is to measure performance quantitatively to the extent possible with available data. The second goal is to explain that performance in terms of how the privatization was conducted. A key feature of the study is that performance covers equity as well as efficiency. That is, we attempt to measure the impact on various stakeholders: primarily consumers, workers, the government, and the new owner or operator. In sum, a successful privatization is not just one where the deed gets done, but where performance improves substantially and the results of that change are distributed equitably with sizeable public benefits to help build and sustain political support. The cases include failures as well as successes. One can learn at least as much from the former as the latter. The goal is to help replace faith-based policies with ones that are fact-based. The opinions expressed here are the sole responsibility of the authors and do not reflect those of the World Bank.
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TABLE OF CONTENTS
EXECUTIVE SUMMARY 1
1. WHAT WAS DONE? 3 1.1. COUNTRY CONTEXT & MAIN ISSUES 3 1.2. PRIVATIZATION OF ELECTRICITY 4 1.3. POST-PRIVATIZATION INSTITUTIONAL MODIFICATIONS 5 1.4. KEY FEATRURES 5
2. WHAT HAPPENED AND WHAT WOULD HAVE HAPPENED? 6 2.1. THE QUESTION 6 2.2. METHODOLOGY: THE COUNTERFACTUAL 6 2.3. TOTAL RETURN TO CAPITAL 6
2.3.1. Profit Trends 6 2.3.2. Distribution of Total Return 9 2.3.3. Collections 11 2.3.4. Price/Quantity Breakdown 14
2.4. Output Market 18 2.4.1. Blackouts/Brownouts 18 2.4.2. Loss in Transmission and Theft 20 2.4.3. Other Excess Demand 21 2.4.4. CIE/EECI Thermal and Hydro Capacity 24 2.4.5. IPP Capacity 24 2.4.6. System Optimization 25 2.4.7. Distortions 26 2.4.8. Services and Miscellaneous Output 26
2.5. LABOR MARKET 27 2.5.1. Issues 27 2.5.2. Data 27
4.4. HIGH REPUTATION 40 4.4.1. The Question 40 4.4.2. Blackout Reduction 40 4.4.3. Initial Price Reduction 41
4.5. ONGOING SUCCESS 41 4.5.1. The Question 41 4.5.2. Experienced Operator 41 4.5.3. Non-Transparent Sale 41 4.5.4. Incentives 41
5. CONCLUSION 48
APPENDIX A: REFERENCES 49
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TABLE OF TABLES Table 1: Performance of CIE/EECI Using Economically Relevant Accounts (billion FCFA) 8 Table 2: Reconciliation of Total Return to Capital and Accounting Profit for CIE/EECI 10 Table 3: Total Return to Capital vs Accounting Profit: Simplified Version (billion FCFA) 10 Table 4: CIE Billing and Collections 12 Table 5: CIE/EECI Balance Sheet 13 Table 6: Estimated Collection Rates From Receivables 14 Table 7: Performance of CIE/EECI Using Flows at Constant 1990 Prices 17 Table 8: Decomposition of CIE/EECI Profit Into Price & Quantity Effects 17 Table 9: Summary of Price and Quantity Effects: Pre vs Post Privatization 18 Table 10: Blackouts vs Transmission/Distribution Losses 21 Table 11: Derivation of Domestic Electricity Sales 23 Table 12: Labor Market Indicators 29 Table 13: Technical Coefficients and Prices of Major Intermediate Inputs 30 Table 14: Impact of Electricity Privatization 32 Table 15: Distribution of Consumer Benefits 33 Table 16: Sources of Government Gains 34 Table 17: Sensitivity of Total Net Benefits 37 Table 18: Sensitivity of Government Net Benefits 38 Table 19: R1- Remuneration for Generation and Distribution Services Provided by CIE 43 Table 20: R2- Remuneration for Fuel Used and Imported Energy 45 Table 21: Implicit Prices in US$ Paid/Received by EECI and CIE 47
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TABLE OF FIGURES Figure 1: CIE/EECI Profit/Quasi-Rent 8 Figure 2: Produced Electricity- Abidjan vs the Nation 19 Figure 3: Consumed Electricity- Abidjan vs the Nation 19 Figure 4: Net Benefits of Privatization 32 Figure 5: Distribution of Total Net Benefits 36 Figure 6: Distribution of Government Net Benefits 37
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EXECUTIVE SUMMARY Côte d'Ivoire’s privatization program was a pioneer in Africa, but the electricity sector was the pioneer of that program. By 1990, financial mismanagement at Energie Electrique de Côte d’Ivoire (EECI) had nearly bankrupted the company: it could not service its debts, and even had difficulty paying employees. Further, frequent blackouts were causing great public dissatisfaction. Dealing with this situation could not await the finalization of the country’s comprehensive privatization program, then in preparation. Neither was there time for the transparent competitive bidding of the sort embraced in that program. Instead, the head of France’s Societe Internationale des Services Publics (of which SAUR owned 65% and Electricitie de France the balance) was approached directly and 3 months later an agreement in principle was signed. Compagnie Ivoirienne d'Electricite (CIE) was formed with: SAUR holding 51% of the shares; the government, 20%; other Ivorians, 24%; and employees, 5%. On October 20, 1990, a concession agreement was signed and CIE began operation.
Far from paying a price for this rapid and non-standard process, the government reaped immediate benefits in the first year. From the standpoint of public opinion, by far the most important was the reduction in blackouts. Also contributing to a positive popular perception was a 10% residential price cut. These were real and substantial gains to privatization.
Financially, CIE recorded a net profit of over 800 million FCFA in its first year, compared to annual losses for EECI for the previous decade. This gave an underserved boost to CIE’s reputation because it was largely due to changes in accounting for depreciation. More generally, we can find only modest improvement in the amount of surplus generated by the sector in the first three private years over the last three public years. We attribute this first to the time it takes to change corporate culture and systems and to the relatively high inherited technical conditions: loss in transmission and distribution on the order of 14%; blackouts at 0.5% of production and private collection rate well over 90%. There was certainly room for improvement, but these are still numbers that many African utilities would envy. CIE had a harder job to do than those who took over less technically well-run firms.
The single biggest gain from privatization of CIE was that it relaxed the investment constraint by giving IPP investors confidence they would be repaid. And once the resulting capacity began in 1994, and combined with the ongoing improvements in operating efficiencies, the benefits of privatization took off. Our estimate of these benefits and their distribution are:
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Net Gains from Electricity Privatization: 1991-2005
Net Present Value (1995) Stakeholder FCFA million US$ million
These gains are substantial: the average annual gain after privatization was equivalent to 17.5% of total revenue in the year prior to privatization. They also appear to be reasonably equitably distributed. The four biggest gainers (Government, foreign consumers, domestic consumers, and domestic plus foreign owners) each had from 22-28% of the pie. The labor figure includes two quite different groups: workers employed by CIE gained more than 10% of the benefits through significantly higher pay and benefits. However, we argue that employment would have been much higher without privatization and that this cost about 4%. That CIE did not continue the public sector policy of overstaffing was a good thing for the economy, but it did have a cost. What was behind these results? The incentive system was critical because it both determined how hard the company was going to try to improve and how the benefits of that improvement would be distributed. CIE’s was uncommonly well designed even before considering its pioneering nature. That in turn was due to quality people doing the reform on the government’s side. We also argue that the contractor’s experience in Francophone Africa may have had much to do with the avoidance of unresolvable disputes that wounded—sometimes fatally—other African privatizations.
CIE is widely regarded as a success story of privatization. Our quantitative analysis suggests this reputation may have been somewhat overdone in the first three years after privatization. But, thereafter, and overall, it richly deserves its reputation.
October, 2006 IPA: Côte d'Ivoire Electricity Page 3 of 54 1. WHAT WAS DONE?
1.1. COUNTRY CONTEXT & MAIN ISSUES1
Before 2000, Côte d'Ivoire was politically stable and one of the most prosperous countries in Africa. The military coup in December, 1999, followed by the outbreak of regional hostilities in 2000 reversed this: political instability has dominated and the economy has contracted (by an estimated 7.4% by 20032). Accordingly, while the most relevant results of the study for most readers will be pre-2000, it will also be of interest to see how the electricity sector fared under adverse conditions.
Côte d'Ivoire was perhaps one of the first countries in Africa to experiment with privatization (does any reviewer know of an earlier case?). As early as 1971, the government granted a concession to a private company (SODECI, a French/Ivorian consortium) to provide water and sewerage in Abidjan under a leasing arrangement, and by 1987 the concession was extended to all urban centers. In 1987 when the government faced financial difficulties regarding sectoral investments and tariffs, SODECI was given responsibility for both operations and investments for the entire country under a new concession contract. By the late 1990s, SODECI provided services close to the standards of industrial countries. Its bonds were traded on the Abidjan Stock Exchange and it distributed dividends to shareholders. The company also paid taxes to the government.3
The poor performance of public enterprises, the increasingly competitive international environment and the successful experience with SODECI convinced the government of the potential economic gains from breaking up state-owned enterprises, eliminating monopolies and removing barriers to entry. Consequently, the government began formulating a privatization program in 1990, which resulted in a Decree no. 90-1610 (enacted on December 28, 1990)4, creating a special committee (“Comite de Privatisation et de Restructuration du Secteur Parapublic”) to oversee the privatization process, with a technical arm (“Cellule Technique”) in charge of implementation. The objectives of the privatization program were to increase the productivity and competitiveness of the enterprises, expand labor market opportunities, improve domestic savings, increase private sector participation in financing economic activities, and increase the government’s financial resources. The program attempted to focus on the biggest enterprises, namely those in infrastructure and agro-industry, divestiture of which would have the biggest impact on the economy.
1 A more detailed discussion of the whole privatization program, its context and its impact is provided in Impact of Privatization in
Côte d'Ivoire, Leroy Jones, Yahya Jammal and Nilgun Gokgur, Boston Institute for Developing Economies(BIDE), December, 1999.
2 IMF, Article IV Consultation, 2003. 3 World Development Report, 1994, the World Bank, p. 63 4 Comite de Privatisation, Journees Portes Ouvertes sur la Privatisation en Côte d’Ivoire, January 29-31, 1997, p. 12
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1.2. PRIVATIZATION OF ELECTRICITY
Even before enactment of the decree, however, the government dealt with a deteriorating situation in the electricity sector. By 1990, financial mismanagement in the only producer in the sector (Energie Electrique de Côte d’Ivoire, EECI) had nearly bankrupted the company: its annual losses were running at FCFA 1 billion per month in mid 1990; its accumulated losses were 110 billion; its accumulated debt totaled FCFA 90 billion (almost the same level as its operating revenues), it could not repay pay its debts, and even had difficulty paying its employees5. What was particularly striking was that this occurred despite having some of the highest electricity tariffs in the world. Facing what was perceived as a national emergency, the government decided that "it was time for action, any action”. Dealing with that situation could not await the finalization of a privatization strategy.
The problem was in fact dealt with remarkably rapidly. Various versions of the tale survive, but one of the more common variants has the President himself calling an old friend and established French businessman, Mr. Bouygues (who also was behind SODECI), and asking him to get involved. Whether or not the call is apocryphal, three months after Bouygues was first approached, an agreement in principle was signed with him. Since the process was completely non-transparent, it is not possible to ascertain how Bouygues won out over the other interested party (Canada’s Quebec Hydro). At one extreme, Bougyues’ personal obligation to the country and to the President led him to leap in as savior; at the other, payoffs could have greased the wheels. Whatever the truth of the process, a new privately-held company (CIE) was created to generate, transport, distribute, import and export electricity in the country. To add sector experience, the Electricite de France (EDF) was brought on board.6 Equity shares were divided as follows: Societe Internationale des Services Publics 51% (of which SAUR, Bouygues’s company, owned 65% and EDF owned 35%), the government 20% (these shares are reserved for the government but had not been issued as of 1999), other Ivorians 24% and employees 5%. EECI’s role was relegated to owning the underlying assets used by CIE and “management of the patrimony”. The process of breakup of EECI, creation of CIE and overseeing the sector was managed by an established and powerful agency (“Direction et Controle des Grands Travaux”, DCGTX) with direct access to the President. On October 20, 1990, a concession agreement was signed and CIE began operation.
Despite the political risks that the government took in creating CIE, an apparent turnaround happened almost immediately: in its first year of operation, CIE recorded a net profit of over 800 million FCFA, compared to annual losses for EECI during the
5 Jeune Afrique, April 23, 1992, p. 65. 6 Equity shares were divided as follows: Societe Internationale des Services Publics 51% (of which SAUR, Bouygues’s company,
owned 65% and EDF owned 35%), the government 20% (these shares are reserved for the government but have not been issued to date), other Ivorians 24% and employees 5%.
October, 2006 IPA: Côte d'Ivoire Electricity Page 5 of 54 whole decade; and repaid for the first time in more than a decade a portion of outstanding debt to the state.7
The apparent and highly visible success of the electricity privatization provided further impetus to the government, which was already setting the stage for deregulating the economy, devaluing the currency and (eventually) privatizing two large, and politically difficult, sectors: telecommunications and agro-industry. The first comprehensive privatization program was devised and a new and much improved privatization law was enacted in 1994 to support it (No. 94-338).
1.3. POST-PRIVATIZATION INSTITUTIONAL MODIFICATIONS In 1998/99 EECI (and its affiliated satellite companies) were abolished and replaced with 3 new entities, all reporting to the Minister of Energy:
• SOGEP: responsible for accounting, holding of assets of the sector, paying loans, and supervising IPPs;
• SOPIE: responsible for investments, rural electrification and technical analysis the
sector (this function was taken away from BNEDT);
• ANARE (Agence Nationale de Regulation): responsible for regulation. CIE's original contract expired in October 2004. Since then there have been on-going negotiations on drafting a new contract but nothing has been finalized.
1.4. KEY FEATRURES
In our quantitative impact analysis, we note four salient features of the electricity divestiture:
1. Market Structure: Electricity is a domestic monopoly. As a
result, the impact on consumers is potentially significant both through the possibility of exploitative pricing and increased output and quality of service.
2. Incentives: Because of the market structure, prices will normally
be regulated by the government to protect consumers. However, depending on how this is done, it may reduce or eliminate any incentive for cost reduction and thus blunt the impact of privatization. While improved management practices in certain (competitive) industries necessarily benefit the owner, in electricity, they need not.
7 World Bank, Privatization in Côte d’Ivoire, Progress Report, 1996.
October, 2006 IPA: Côte d'Ivoire Electricity Page 6 of 54 3. Modality of Divestiture: Only the management function was
divested. Consequently, investment is not directly affected by privatization, so potential gains from this source are likely to be small.
4. Visibility: Because electricity is large, affects most consumers
directly, and was done early, its perceived success or failure had a major external impact on public acceptance of other privatizations.
2. WHAT HAPPENED AND WHAT WOULD HAVE HAPPENED?
2.1. THE QUESTION The Ivory Coast electricity sector is widely regarded as a success story, with even persistent critics of privatization acknowledging this. But conventional wisdom is sometimes wrong. To what extent do the data support this conclusion? One of our principal assignments is to test this with some rigor. However, it is critical to understand that our primary concern is not the performance of the sector, but the contribution of privatization per se to that performance.
2.2. METHODOLOGY: THE COUNTERFACTUAL To answer this question we require two data pictures of the firm. One is the factual portrait of the sector as it actually evolved with privatization. The other is the counterfactual conjecture as to how it would have evolved under continued public operation. The net benefits of privatization are then the difference between the two runs. In this section we try to identify and specify the differences and in the next section we identify the impact on various stakeholders. We cover a fifteen-year period after privatization, with actual data for fourteen years and one year projected.
2.3. TOTAL RETURN TO CAPITAL8
2.3.1. Profit Trends The first place we look for change is profit, not because it is the most important but because we have to start somewhere. Profit can be measured in many ways but since we are interested in efficiency we start with operating profit. We convert the private Profit and Loss Statement to economically relevant categories in the following form: Output (=Sales + Output Inventory Change) - Intermediate Inputs = Value Added
- Returns to Labor = Total Return to Operating Capital or EBDIT or Quasi-rents
8 Our original study, cited above, was based upon detailed data through 1997 with direct access to CIE. For this study, data have
been updated through 2003. The data in the later period are somewhat more limited so some tables only run through 1997.
October, 2006 IPA: Côte d'Ivoire Electricity Page 7 of 54 We accomplish this by simply rearranging the P&L: everything on it is examined and explicitly put in one of the above categories. Economists like to think of this as Quasi-Rents while those who speak management call it EBDIT (earnings before depreciation, interest and taxes. Results are presented in Table 1 and Figure 1.
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Table 1: Performance of CIE/EECI Using Economically Relevant Accounts (billion FCFA)
October, 2006 IPA: Côte d'Ivoire Electricity Page 9 of 54 Looking only at the current price series for the moment, these numbers show three things. First, contrary to the conventional wisdom of a dramatic turn-around with privatization, this series shows, as a first approximation, little change over the four years prior to, and the five years following, privatization. Second, there was a substantial improvement in 1995 as the IPPs came on line, exports began, and domestic demand increased as the economy continued to emerge from recession. Third, thereafter the trend was largely declining.
We need to explain this trend, which runs contrary to conventional wisdom. One possibility is that efficiency improvements are masked by unfavorable price movements, shifts in the hydro/thermal mix, or other factors outside management’s control. We shall investigate this in depth in a moment. However, let us first investigate a paradox: if the sector was generating no more surplus than before, how was it immediately able to start paying down its debt? There are two simple and fundamental accounting explanations.
2.3.2. Distribution of Total Return
Table 2 reconciles the two versions of profit (total return to capital as previously presented, and accounting profit after tax). It simply shows the distribution out of the total return, with accounting profit after tax being the residual. To allow us to focus on the essentials, Table 3 simplifies Table 2 into four categories, averages the three years prior to privatization and the four years after, and converts to billions of FCFA.9
9 A knowledgeable World Bank official suggested a modification of our treatment of “Miscellaneous Losses & Charges” in Error!
Reference source not found.. This account included unexplained “extraordinary items” in the company’s accounts which we considered as real economic costs in the same year. The modification suggested that they be debited to the previous year, an assumption equally reasonable to the one we used in the report. If one were to adopt the latter assumption, which results in shifting these expenses back one year, the numbers for “return on capital” in Error! Reference source not found. would change substantially in 1988 and 1989 (with a lower value in 1989 but a higher one in 1988), but would not materially affect those in Error! Reference source not found. (using averages for pre- and post-privatization periods) and would not change our conclusions in any way. As the truth about what year to assign these costs lies probably between the two assumptions, and since both assumptions yielded the same conclusion, we chose not to change the numbers in the report.
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Table 2: Reconciliation of Total Return to Capital and Accounting Profit for CIE/EECI
Table 3: Total Return to Capital vs Accounting Profit: Simplified Version (billion FCFA)
Average Variable 1988-1990 1991-1994
Change
Total Return to Capital 45 42 -3
- Depreciation & Interest Payments 60 4 -56
- Taxes (+ Subsidies) 7 42 +35
+ Misc Income (- Costs) 1 6 +5
= Accounting Profit after Tax -22 1 +23
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Imagine a large capital-intensive public enterprise which is losing money. A consultant is asked to make it profitable overnight. Simple, he says. Alter your accounting conventions to reduce depreciation (for example, by writing off some assets) and interest payments (for example, by capitalizing interest). Accounting profits will then soar. Now imagine that this strategy was pursued so successfully that virtually all depreciation and interest payments disappear. That is to a large extent what happened at CIE, due to the mode of privatization chosen. Because the government kept most of the assets, depreciation charges were removed from the company’s books. Because the government kept most of the liabilities, interest payments were largely removed from the company’s books. As shown in Table 3, these two effects raised accounting profits by an average of FCFA 56 billion.
The offset, of course, is that the firm paid the government additional money in the form of various taxes and fees. However, these only increased by an average of FCFA 35 billion. Netting these two effects, the enterprise accounting profits rose by FCFA 21 billion. A host of other effects accounted for the other FCFA 2 billion, some of which we shall refer to later, but most of which are small enough that we can neglect them.
To summarize, as a first approximation, immediately after privatization there was no material rise in surplus generated by the electricity sector. The increased profits came instead from the fact that removing the enterprise’s responsibility for depreciation and interest more than offset the increased payment of taxes and fees to the government. Profits were moved around, not increased.
2.3.3. Collections
If profits were only moved around, then why was the sector suddenly able to resume payment on debt? The reason might be that both of the foregoing measures of profit credit sales when billed, rather than collected. A firm with paper profits can nonetheless be illiquid if its receipts go uncollected. This is the second “simple yet fundamental” explanation for the paradox described earlier.
CIE is quite proud of the job it did in turning collection rates around, citing it prominently when asked what improvements they made. They often elaborate by describing how they retrained surplus female workers as bill collectors, on the principle that it is hard to say “no” to young women, and thus demonstrating the flexibility, insight and creativity unleashed by privatization.
Sources at EECI, on the other hand, assert that they had already achieved a collection rate from private parties of 96%. However, the biggest deadbeats were government enterprises and the government itself and collections here did indeed fall short of what was desirable. To the extent that this is correct, then any improvements in these collection rates might then not be attributable to privatization, but to a change in government policy which could as easily have been undertaken without privatization.
What do the numbers show? CIE was able to provide the needed data for the 1992-1997 period, as replicated in Table 4. This series says five interesting things. First, it confirms that the company indeed did well on private collections, averaging 98% over the period. Second, CIE did not do as well on public collections, averaging only 90% over the
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period. Third, there is no obvious trend in private collections (it was already doing 100% in 1992). Fourth, there is a clear improvement in total collections, which averaged 88% from 1992 through 1994 but 102% from 1995 through 1997. Fifth, getting the government to pay its bills is not easy, since even the presumably10 highly motivated private operator took 4 years (until 1995) to persuade the government to get serious about paying its bills. Unfortunately, this series tells us little about what we really want to know, since EECI encountered difficulties in providing comparable data for the earlier period.
In order to move ahead, we constructed a proxy data set. We first put together a consistent time series of balance sheets (Table 5) in order to be sure that we had a complete picture. We then grouped all receivables and then calculated implicit aggregate collection rates ( Table 6), on the assumption that all changes in receivables were due to changes in consumer receivables. We know that this is not correct, because in the years where complete data are available, consumer credit is only about half of total receivables. Nonetheless, it is the best we can do.
What does this imperfect series say? As can be seen, there is no obvious trend. In the 5 years prior to privatization, estimated collections averaged a little higher as a percent of billings then they did afterward. Given the fact that these proxies also do not match the good data from CIE in later years, we discount them.
All we can say with certainty is that the fact that CIE had the data and EECI didn’t, confirms--at least in some small way-- that information and financial management improved with privatization. Beyond that, we strongly suspect there is an impact but we have no sound basis for estimating its magnitude. Accordingly, we will build the impact into the model with an arbitrary guesstimate. That guess will be that under continued public management private, collections would have averaged 90% for 3 years before improving to the private sector levels. Similarly public collections would have been at 25% before improving to private sector levels with a 3 year lag. How do we build this effect into the model? There are several possibilities, but we shall adopt a simple one.11 We treat receivables as an interest-free loan from the company to the consumer, with a one-month grace period. If the stock of outstanding receivables is equal to 7 months of billings, then there is a 6-month loan and a half-year of interest is transferred from the firm to the consumer. How big is this effect? As a concrete example, in 1992, receivables were 38 billion and billings were 90 so the loan duration was 2.5 months. At the prevailing nominal interest rate of 9%, the transfer was 700 million, or equivalent to 1.4% of the price per kwh for low tension.
2.3.4. Price/Quantity Breakdown
In this section we are searching for evidence of change in performance resulting from privatization. Thus far, we have shown that in current prices, the total surplus generated by operations was initially unchanged, then grew for two years before beginning a five-year period of decline. We now look for second-order effects and for the possibility of first-order offsets where unfavorable price movements were countered by improved efficiency, or vice versa. Because electricity is a domestic monopoly, prices are regulated by the government to protect consumers or pursue other social goals. They are generally not likely to be affected by privatization. For example, price increases per kwh after 1999 were kept down because of the unrest in the country and we strongly doubt that this would have 11 An alternative would be to treat the subsidy, not as a transfer, but as a price discount. This would have the desirable property of
building in a quantity feedback; the subsidized consumer would increase consumption beyond the efficient level. Doing it this way, however, turns out to be mechanically inconvenient. We justify using an inferior method on two grounds. First, the principal deadbeat is the government, and their demand is likely to be highly price inelastic, so the quantity feedback will be small. Second, as shown at the end of the paragraph, the magnitude of the effect is likely to be small as a percentage of the price, so again the quantity feedback will be small.
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been any different under continued public ownership. We do find one important exception. At the time of divestiture, prices to consumers were reduced by 10%. It is curious how little credit the government gets for this. Not a single interviewee mentioned it. Even at CIE it was not volunteered as part of any of the lists of “what changed with divestiture”. Part of the explanation may be that the decrease did not apply to all classes of users, so the weighted average reduction was only about 3.5% to low-tension users as a whole and 2.4% for consumption as a whole. Still, it appears there is a psychological asymmetry at work here: people would have remembered a 10% price increase, but quickly forget a 10% price cut. However that may be, there is little question that this cut would not have taken place without privatization, and constitutes a transfer to consumers from the government. Note that it is the government who pays, because the firm gets a formulatic remuneration while the government is the residual claimant on surplus. How long would this price differential have been maintained? Consumer prices were readjusted following the 1994 devaluation. Again being conservative, we will assume that the price differential would have been wiped out at that time.
Major inputs are tradable and their price is unlikely to vary with enterprise performance. To ascertain the impact of privatization, we must therefore take away the impact of most price changes and focus on quantities. The next step in evaluating how performance is impacted by privatization is, therefore, to ascertain how much of the change in any value (for example, revenue) is due to a change in prices (dictated by the regulatory authority) and how much to changes in quantities (for example kwh) sold. In essence, we are doing at the enterprise level what is done at the national level when converting from a nominal to a real GDP series. The reasons for the conversion are also the same. Table 7 therefore gives real (price adjusted)12 accounts. The bottom line can be seen from the constant price line in Figure 1. The decline in nominal (not price adjusted) surplus after 1987 is entirely explained by prices moving against the firm (output prices rose more slowly than inputs prices). From 1983 through 2003 real surplus rose at the impressive average annual compound rate of 10.7%. Table 8 gives additional detail by decomposing annual changes in profit into price and quantity effects for its main components. This table is one of our favorite ways of comparing enterprise performance in different periods. To interpret it, compare the output triplets in the 1988 and 1990. In 1988 the value of sales went up by 3870 and the bulk of this was due to increased quantity with only 510 due to changes in price (or price composition). In contrast, in 1990, sales increased by 1731 but here unfavorable quantity change of -3082 was more than offset by favorable price increases worth 4813. Similarly for the other categories. There is a lot of detail for evaluating annual performance, but our concern is broader trends, so Table 9 provides a summary for various sub-periods. What it says is that while neither prices nor quantities changed materially during the first three years after privatization, thereafter, real surplus (on the analogy of real GNP) increased at an annual average rate of 5,030 million fcfa but unfavorable price movements cost the firm even more, so losses averaged 1,801 million fcfa. That is, the enterprise did extremely will with the technical variables it could control, but this was more than offset by things it couldn’t, namely prices.
12 We do this using a Discrete Divisia indexing procedure with constantly changing weights.
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Here are some other points that emerge from the three tables together: 1. As a first approximation, real output was largely unchanged from 1987 through 1993, starting to rise only with the post-devaluation rise in demand.
2. Real profit (on the analogy to real GNP) is also very stable from 1988 through 1993, again beginning to rise only after devaluation.
3. Real profit jumps from 1987 to 1988, thanks to a marked drop in intermediate input consumption. This in turn is not due to better management, but to the hydro/thermal ratio nearly doubling (from 0.7 to 1.2) as either new capacity came on line or reservoirs filled. This is an important reminder that a major exogenous determinant of efficiency in a mixed system such as Côte d'Ivoire is God’s decision to provide or withhold rain, since it is much cheaper to produce hydro than thermal. In what follows, we will therefore have to look separately at these two forms of production.
4. Overall, it is difficult to see any immediate changes in real variables associated with privatization. As with nominal variables, there is little apparent change from the three years before privatization as compared with the three years after (1988 through 1993). 5. Thereafter, positive quantity effects were substantial but price trends were strongly negative. Recall that a major concern in utility privatization is that the privatized producer will capture the regulator, so that prices move disproportionately in his favor. This emphatically did not happen in Côte d'Ivoire; just the reverse. This does not of course mean that the pricing rules were optimal, but it does mean that increased input prices were absorbed by the sector rather than passed on to the consumer.
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Table 7: Performance of CIE/EECI Using Flows at Constant 1990 Prices
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Table 9: Summary of Price and Quantity Effects: Pre vs Post Privatization (annual average in millions of fcfa)
Pre (88-90) Post (91-93) Post (94-03) Price Effect 588 67 -6,831 Quantity Effect 4,925 72 5,030 Total (Value) Change 5,512 139 -1,801
We now have two questions. First, to what extent was privatization responsible for the real gains after 1994? Second, to what extent was it responsible for the lack of gains in the first three years after privatization? We do this by looking in greater detail at each of the components of profit: output, intermediates and labor.
2.4. OUTPUT MARKET
We model the output market as follows:
Own Hydro Generation + Own Thermal Generation + Imports + IPP Purchases - (Exports + Export Transmission Losses) = Gross Domestic Availability - Transmission and Distribution Losses - Stolen Electricity = Domestic Sales (separated into Low and High/Medium Tension) + Blackouts/Brownouts/Load-Shedding + Other Excess/Unsatisfied/Unmet Demand = Domestic Demand
We attempt to achieve accuracy by projecting each item separately under both private and counter-factual (un-privatized) scenarios. We begin near the bottom of the list and more or less work our way up. Table 11 gives time series for all output market variables and thus provides a one page summary of the entire output quantity section
2.4.1. Blackouts/Brownouts
Let us begin with a puzzle. Everyone we talked to in Côte d'Ivoire had vivid memories of the changes they personally experienced (even if they were out of the country at the time) as a result of divestiture in electricity: “before we often had no electricity; afterwards we always had it.” A vivid vignette defines the period: during final exams at the University, and just prior to national elections, electricity was cut off and students poured into the streets in protest. We therefore expected to see a sharp increase in the quantity of electricity supplied after 1990. However, as we have already shown in both nominal and real terms, there was no such change in the aggregate figures until after the devaluation of 1994. A closer look at the data reveals that there was a downturn of 3.7 to 3.9% in 1990 output compared to 1989, but was this enough to generate such strong and uniform memories? In particular, was it enough when sales continued to fall by 1.3-1.5%
October, 2006 IPA: Côte d'Ivoire Electricity Page 19 of 54 per year in 1991, 1992 and 1993? We tried all sorts of rearrangements of the data and asked all sorts of questions of all sorts of people in an attempt to unravel this paradox. One hypothesis runs as follows. It was not the total that mattered, but its distribution. Political influence is concentrated in Abidjan and if blackouts were also concentrated there, a relatively small change in availability might translate into a relatively large change in effective public opinion. Figure 2 generates some support for this hypothesis, because it shows a dramatic drop from 1987 to 1990 in both the level and share of electricity produced by the two plants serving the Abidjan region. However, with an inter-connected grid, why should the location of production have any impact on consumption? Indeed, as can be seen from Figure 3, the consumption trend in Abidjan is indistinguishable from that in the rest of the country.
Figure 2: Produced Electricity- Abidjan vs the Nation
Figure 3: Consumed Electricity- Abidjan vs the Nation
October, 2006 IPA: Côte d'Ivoire Electricity Page 20 of 54 A second hypothesis is that people simply really, really care when there electricity supply is disrupted. This phenomenon is by no means confined to Côte d'Ivoire. An astute World Bank observer, commenting on an earlier draft, asked just how much load shedding was actually involved in the infamous 2001 California electricity crisis. The answer is that they totaled 10.2% of daily peak load13, or less than 2 hours of service over the entire year if spread system-wide. Yet this was enough to put the system in crisis and contribute heavily to the Governor losing his job. So, even when blackouts are a quantitative blip, they are qualitatively critical for consumers.
In sum, in the 3 years prior to divestiture, blackouts doubled from about 1 day per year to two days; divestiture brought that figure back down to 1 day in two years and to a half day in another four years. This is an impressive accomplishment in relative terms. However, in absolute terms its contribution is extremely modest--amounting to less than three-tenths of one percent of annual output--because from an engineering standpoint things were pretty well run to begin with. The privatized firm did an excellent job, but there does not appear to have been too much of a job to do. Nonetheless, having been accustomed to extremely low levels of outages, consumers were incensed at the relative decline and greatly relieved at the improvement, however modest in absolute terms. We will reflect this in our welfare section below by using a very high value for electricity lost to blackouts. For our projections, we doubt there is much room for further improvement, so under private operation we project a decline to 12 hours in 1998, with no further changes. Under the counter-factual, we assume that the 1990 level of 50 hours would be maintained for three years, then return to the historic low of 27 hours over the following 3 years.
2.4.2. Loss in Transmission and Theft
The next technical parameter is Loss in Transmission & Distribution. What happened to this statistic with privatization? One’s prior might well be that it should have been similar to the trend in blackouts because both are subject to the same sort of engineering/maintenance remedies. As shown in Table 10, this expectation is only two-thirds confirmed. By LDC standards the absolute level was indeed pretty good throughout the period (13-18 percent) and there was indeed deterioration in the years prior to privatization (from 13.1% in 1986 to 16.3% in 1990). However, there was no immediate turnaround at the time of privatization. Indeed, the trend of deterioration continued, peaking at 17.7 percent in 1994 before declining to 15.0 percent in 1997. Furthermore, the best achieved under private operation was worse than the best under public operation (15.0 versus 13.1 percent).
How is this trend to be explained, and what was the role of privatization? Neither interviews nor number-crunching were of any help in answering this question. In particular, we asked if there were any exogenous changes in the structure, composition or condition of the grid which might help explain the trend, but could discover none.
Based on experience in other countries, however, we generated a hypothesis which appealed to several experts we tried it out on, and which is at least consistent with the
13 James L. Sweeney, The California Electricity Crisis, Hoover Institution Press Publication No. 513, 2002
October, 2006 IPA: Côte d'Ivoire Electricity Page 21 of 54 facts. The starting point is the observation that “Loss in Transmission and Distribution” has two parts: first, true electro-mechanical loss and second, theft of electricity. While both share the property that because of them what is put into the grid is less than what comes out, their welfare consequences are quite different. This is important from the point of view of our distributional welfare analysis because while the former is a real resource cost, the latter is only a redistribution of the benefits. We are alert to this fact, because in privatization of electricity networks elsewhere (most notably in Chile), major gains have accrued to the privatized firm from walking the lines (often with armed guards) and removing unauthorized connections.
How might this help explain the trend in Côte d'Ivoire? It seems reasonable to assume that when economic conditions deteriorate as much as they did in the late 1980's and early 1990's, people are driven in desperation to do things they would not otherwise do. One of those things is theft of electricity. It might therefore have increased steadily until times got better in 1994. Thereafter, with economic recovery, the rate would have tailed off, in small part because of a possible small decrease in the absolute level of theft and in large part because of expansion in the denominator (billed electricity sales).
If this seems reasonable, then we will take the further step of making it concrete as follows. There was no theft at the trough in 1996, thus giving us true loss in transmission. This increased and then decreased at the same rate as blackouts and for the same reasons. Remaining recorded losses are treated as increased theft. What about projections? It is perhaps surprising that CIE has not mounted a campaign against theft. Part of this may be political sensitivity. Part of it may be due to the fact that the scale adjustment factor mitigates against increased billings. Whatever the reason, we doubt that it will last forever, so we arbitrarily assume that in three years CIE mounts a campaign to eradicate stolen electricity and accomplishes this over the ensuing 3 years. Under the counter-factual of public operation, no such campaign will be mounted; the absolute level of theft will be maintained, but the rate will decline with increased sales.
Table 10: Blackouts vs Transmission/Distribution Losses
We are used to working in LDCs characterized by substantial excess demand for electricity, making extra electricity output extremely valuable because of the high associated consumer surplus. This is less true in Côte d'Ivoire, for four reasons. First, while EECI’s historic investment program by all accounts had many shortcomings, it did create considerable capacity. Second, the recession put a curb on the growth of demand. Third, imports from Ghana’s Volta River Authority were available to fill gaps between domestic supply and demand through 1992. Fourth, from 1995, exports could be reduced
October, 2006 IPA: Côte d'Ivoire Electricity Page 22 of 54 to meet domestic demand. We therefore conclude that there has been no excess capacity in the system for connected customers, other than the relatively small amount due to blackouts and brownouts described previously. However, there is still excess demand by unconnected consumers. One implication of this is that welfare gains to consumers will be smaller than for studies of electricity divestitures elsewhere which were characterized by the presence of excess demand. We approximate this conservatively by assuming that there was still excess demand even at the end of the period of 10% and that total demand had grown to that point at the GDP growth rate (an income elasticity of 1).
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Table 11: Derivation of Domestic Electricity Sales
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2.4.4. CIE/EECI Thermal and Hydro Capacity
Capacity expands in two ways: new investment and, to a much lesser extent, improved efficiency. Since investment responsibility remained with EECI, and since in any event a decision was made to expand using IPPs, it is simple to conclude that privatization had no impact on investment in the firm’s capacity. Again, this is in stark contrast with some other electricity divestitures where expanded investment created major gains for consumers.
What about the possibility of improved maintenance expanding available capacity by reducing downtime? An argument has been made that considerable improvement was possible here. According to one set of observers: there is “a thermal plant at Vridi, a suburb of Abidjan, with a capacity of 314 MW, but because of lack of adequate maintenance for several years it functions way below capacity.” This is one of the two plants behind the diagram in Figure 2, showing steadily declining output in the late 1980's. Sources at EECI, however, say that the decline was due simply to rational plant sequencing. Over that period, hydro capacity expanded, so they used the highest cost thermal plant less and, with lower expected capacity utilization, it made sense to defer maintenance. Sources at CIE actually seem to take a position that is closer to EECI, saying that EECI engineers were pretty good and mostly the same people were doing the same jobs under CIE, so there was not a lot of room for improvement. We are not engineers and this happened some time ago, so it is hard to judge. What do the data say? The fact that expanding hydro was offset by declining thermal without excess demand is confirmed by the factual series in Table 11. On the other hand, the same table shows that thermal production peaked at 1198 gwh under public operation (in 1987), but reached 1308 gwh under private operation (in 1994). We take this as an upper bound measure of the effective changes in this sphere. As a lower bound we can tell a story similar to the empirically demonstrated blackout reductions. That is, under continued public operation, capacity would be available for one day less per year through 1995, thereafter ramping up to the private level. For our base estimate we take a figure half-way between these boundaries.
2.4.5. IPP Capacity
This is one of the most important parts of the story in this report. We have already noted Côte d'Ivoire’s leading role in LDC infrastructure privatization, as manifested by the privatization of water and electricity operations. To this we can now add the fact that they had one of Africa’s earliest IPPs.
In the early 1990's, the government decided that future capacity expansion would be left to IPPs. They began discussions with a few interested parties, but there was no urgency as capacity seemed adequate for several years to come. However, by 1994 urgency was introduced by the combined impact of low water levels and increased demand after the devaluation. The government then quickly signed an agreement in July 1994 calling for the first three turbines to begin operation in March 1995. This was accomplished and by 1997 CIPREL was producing 1065 gwh/year, or 38% of domestic capacity.
The germane question is whether or not this IPP capacity can be credited to privatization of CIE, or would have happened anyway. Our answer is that it would have happened
October, 2006 IPA: Côte d'Ivoire Electricity Page 25 of 54 anyway, given the country’s commitment to private power, but it would not have happened nearly so quickly had CIE not previously been privatized. There are four reasons for this view. First, if you are familiar with the tortuous negotiations behind a typical LDC IPP you will appreciate how quickly this one was signed and implemented. Second, the fact that the government had privatized CIE helped make its commitment credible and speeded up negotiations. Third, since CIPREL was dealing with a private CIE, it was more confident that offtake arrangements, billing, etc. would be handled professionally and expeditiously. Fourth, all of these factors were made far more powerful by the fact that CIPREL is owned by the same parties that own CIE (Bouygues and Electricite de France). In sum, it seems obvious that the confidence generated by the earlier transaction allowed this one to proceed under conditions of mutual confidence, and this allowed it to happen much more quickly. How much more quickly? Had privatization not taken place, we think it would have been far more difficult to get an IPP into operation and we arbitrarily set this period at three years.
2.4.6. System Optimization
How do we calculate the costs of deferred IPP startup? This depends on the adjustment mechanism. What would have changed to compensate for the lower domestic capacity? We consider four possibilities:
1. Consumers: some consumer demand would go unsatisfied and the cost would be foregone consumer surplus.
2. Exports: at the margin, exports would be lower and the cost
would be foregone foreign exchange earnings. 3. High-Cost Thermal Output: under this scenario, low-cost IPP
production substitutes for the highest of the high cost existing thermal output so the cost of IPP deferral would be the extra costs of generation. Consumers and exporters would still get the same output, but at a higher cost to the economy.
4. Imports: lower domestic capacity would be compensated for by
higher imports, and the cost would be in foreign exchange lost.
These possibilities are of course not mutually exclusive. A combination of mechanisms is perfectly possible.
Which is most likely in the environment of the 1995 through 1998 Côte d'Ivoire? As was clear from Table 11, with the introduction of the IPPs, older thermal production fell substantially (by 522 gwh in 1995), exports rose (by 397 gwh in 1995), while consumption rose at a modest rate of 7% per year (by 65 gwh in 1995). Part of this was also a response to increased hydro availability. We can therefore rule out consumers as suffering from the delayed IPPs. We can also rule out additional imports as Ghana’s excess capacity was declining (as was shown in Table 11, imports peaked at 489 gwh in 1992 but dropped to 103 and 54 in 1993 and 1994, and to essentially zero thereafter).
October, 2006 IPA: Côte d'Ivoire Electricity Page 26 of 54 Instead, the adjustment mechanism was some combination of exports and high cost thermal plants.
To get a precise estimate, we use theory and the above facts to model electricity production under the conditions (especially relative prices) prevailing in Côte d'Ivoire from 1995 to 1998. 1. Produce all the hydro you can. 2. Buy all the IPP output that is available. 3. Produce as much thermal as is possible in plants where
the marginal cost of production is less than the export price. 4. Satisfy all domestic demand. 5. Export whatever is left. This is the short-run scheme. In the longer run, IPPs expand to meet domestic demand expanding at 8 percent per year, with no increase in exports. This same optimization model allows us to move from the earlier capacity estimates to the generation estimates given earlier. It also automatically quantifies the benefits and costs of the other changes postulated above.
2.4.7. Distortions
There are two distortions in this market: the value added tax at 20% and the stolen electricity referred to above. The latter is a distortion, since price does not clear the market where marginal costs equal marginal benefits. The question is who gets the rents which accrue to the consumer who gets for nothing what he is willing to pay something for. In the first round this accrues to the thief, but, some of the rents may be paid as bribes to meter readers or line-walkers to look the other way. This is more likely for industrial theft via meter jamming than it is for the poor person jimmying up a line. There are also costs of rent-seeking in the form of possible lawyer fees and the psychic disutility of being a thief and possibly being caught, the labor cost of jimmying/ tampering, etc. We allocate the rents one-third each to consumers, middle-men, and resource costs.
2.4.8. Services and Miscellaneous Output
Services increased rapidly after privatization, from a peak of 1.6 million FCFA before privatization (1989) to a high of 16.2 million FCFA in 1987, when it amounted to about 10% of electricity sales. There are two possible explanations. One is that it represents the entrepreneurial spirit at work as new services are added and old ones provided with enhanced quality. The other possibility is that it simply represents new ways of charging for services previously provided free or at below cost (such as new connections), or new ways of accounting for old services at old prices. Interviews at CIE generated the explicit response that the bulk of it was in the latter category. However, the former category includes improvements in the quality of service (timeliness and friendliness) and while there is apparently no consumer survey data on this, interviews suggest strongly that there was a major improvement here. We therefore allow ten percent of increment as new
October, 2006 IPA: Côte d'Ivoire Electricity Page 27 of 54 output. As an approximation to a logistics curve model, we project the real growth to continue for 3 years at half the earlier pre-divestiture rate and then to remain constant.
Miscellaneous output is a black box amounting to well under 1% of revenues in all years, and with no clear post/pre privatization trend. We leave it black and project no difference in behavior. Prices for both services and miscellaneous output are assumed to grow at the CPI rate.
2.5. LABOR MARKET
2.5.1. Issues The impact of privatization on labor is an important and intriguing issue everywhere, but particularly so in Côte d'Ivoire. If the privatized enterprises improve efficiency by reducing intermediates relative to output, virtually everyone applauds. If, however, they improve efficiency by reducing labor relative to output, many observers will boo. Regardless of one’s value judgments, it is an open question whether, on balance, workers as a group are harmed or helped by privatization. On the one hand, the public sector is usually thought to be overstaffed and overpaid (for their level of productivity), so there is room to reduce both employment and real benefits. On the other hand, an entrepreneurial privatized firm may expand, and actually add jobs, and if it is more profitable it may be easier for unions to extract higher wages.
2.5.2. Data Given the importance of such issues, we have paid particular attention to the labor market and have put together a reasonably consistent story (see Table 12 for the more salient pieces of the resulting data set).
A standard problem with labor data at the company level is that total labor compensation from the P&L is a flow for an entire year while the number of workers is typically reported as a stock at a particular point in time. If, for example, workers have been laid off near the end of the year, their benefits are included on the P& L for most of the year, but they are not counted as employees, resulting in an excessively high implicit wage and labor productivity. A similar problem occurs because no distinction is usually made between part-time and full-time work. When a company furloughs or puts on part time many workers; it would still list them as employees, though they are not paid, thus again distorting calculations of average compensation and productivity. The right way to deal with this problem is to collect data on a full-time-equivalent (FTE) basis. That is, two workers employed half-time count as one FTE. This, however, proved impossible with available data so we resorted to a proxy. We know from interviews that nominal wage rates were never lowered. If, therefore, implicit nominal wages fell, it was most likely14 due to labor shedding and fewer FTEs per listed employee. In such cases we adjust
14 A second possible reason is that the composition of the workforce may change, with firing of higher wage employees lowering the
average nominal wage. This important phenomenon will be dealt with below. Here we only note that the adjustment made here is in the direction of calculating a quality-adjusted FTE labor force figure.
October, 2006 IPA: Côte d'Ivoire Electricity Page 28 of 54 employment downward by enough to maintain average nominal wages. This process is usually referred to as “smoothing” and while it has that effect for wages and productivity, it has the opposite effect on employment, increasing the estimate of layoffs prior to privatization. The first feature of the labor force in this sector is the composition and level of the Non-Ivorian segment: it is small (well under 1% in all periods). Although 24 Europeans were brought in to manage the transition from 1991 through 1994 the number dropped steadily to 3 today. The balance is non-Ivorian African. The disproportionately high wages of the Europeans create two sharp discontinuities in the wage and benefit rates for the group. Turning to Ivorians, we first note that there was a declining nominal wage in the first several years of privatization. This was apparently due to a significant change in skill composition: higher-priced, more skilled, older workers were let go and replaced by lower-priced, younger, less-skilled workers. Note that much of this was accomplished by CIE’s selection of workers to take with them: in 1992, the average wage and benefit package at EECI was 14.3 million FCFA compared to 4.2 at CIE. However, this does not explain the trend in our data since we are using the combined companies. We wanted to address this problem by further decomposing the data, but unfortunately we could find no consistent breakdown by skill category. Instead we made a partial adjustment, postulating a non-declining nominal wage and getting quality adjusted full-time employment as a residual (QAFTE). This only applies in 1991-1993. As can be seen from Table 12, QAFTE Ivorian employment declined from a high of 4050 workers in 1987 to a low of 2793 in 1993 before rising slowly to 3323 in 1997. With no comparable consistent series available to us after 1997, that level was assumed to have remained the same. What would have happened without privatization? Two interpretations are possible. The first is that since the declining trend was similar before and after privatization and there was no discontinuity, the trend was not due to privatization. However, the cause of the decline was quite different in the two periods, with workers being laid off before privatization, and the replacement of high-priced workers by low-priced workers after. We therefore think the post-privatization decline should be charged to privatization. In the counter-factual, we thus hold employment constant at the 1990 level until improved economic conditions allow it to return to the “comfortable” average of 1988/89 over three years.
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October, 2006 IPA: Côte d'Ivoire Electricity Page 30 of 54 Now consider wages and benefits. Under continued public operation, we held nominal wages and benefits constant until economic conditions improved in 1994. Thereafter, we allowed them to increase at the rate of real labor productivity times and the rate of inflation. The same rule was applied for private operation in making projections after 1997.
2.6. INTERMEDIATE INPUTS MARKETS
Intermediate inputs are grouped into three classes: purchases (imports, IPPs), fuel/energy, and miscellaneous. Technical coefficients and prices are shown in Table 13. The first category was discussed earlier and nothing more need be said. The second category has highly unstable trends, due not only to changes in the hydro versus high-cost thermal versus low-cost thermal mix, but also to a technology switch to gas at some units. There is, at minimum, no apparent discontinuity in any of the technical coefficients around the time of privatization. Perhaps, more importantly, we know from the discussion of the remuneration covenants that CIE has no particular incentive to conserve on fuel. For both sets of reasons, we postulate no change in the amount of energy required per kwh of thermal production between public and private operation. Miscellaneous intermediate inputs relative to total sales also exhibit no apparent discontinuity. However, since CIE does have the incentive to keep this low, we allow the ratio to decline by the same small factor as for the blackout rate. There is no difference between factual and counter-factual prices during the data period. Thereafter both grow at the rate of inflation.
Table 13: Technical Coefficients and Prices of Major Intermediate Inputs
Throughout this set of cases we attempt to identify the impact on various stakeholders. But in this paper, we go further and do a systematic welfare analysis which attempts to quantify systematically and consistently the net benefits accruing to each. We first do a benefit-cost analysis and then distribute all benefits and all costs to the stakeholders to which they accrue. The methodology is described in detail in an appendix to our main report, but here we provide a summary. The basic benefit-cost framework is Harbergarian, so we capture second-order effects as prices adjust in each market from which the enterprise demands and to which it supplies. We have adapted the model so that distributional effects are also derived. The core of the work is in a one-hundred line market module which incorporates such standards as price, quantity, taxes, subsidies and consumer surplus, but also less common features such as rent-seeking, non-price rationing and externalities. There are 17 of these market modules (six for outputs, five for inputs, one for labor plus others for the impact on things like foreign exchange and domestic capital markets. Consistency is maintained across markets through profit and loss, cash flow statements and balance sheets. We cover a fifteen-year period after privatization, including thirteen years of actual data and two years of projections. We do all this twice, once for the privatized enterprise and once for the counterfactual enterprise as we conjecture it would have performed without privatization. The net benefits of privatization are then the difference between the two runs. The impact on each stakeholder follows.
3.2. SUMMARY RESULTS Crunching the numbers yields the summary results in Table 14. What does it say? First the total gains were large, at 269 billion FCFA (US$ 586 million).15 This is over twice the size of sales in the last pre-privatization year of 1989. However, this is comparing a stock (Net Present Value: NPV) with a flow (sales in 1989), so we calculate the Annual Component of the Perpetuity Equivalent of the NPV (the annual perpetuity which would yield the same NPV: ACPE). The ACPE as a percentage of sales is 17.5%. That is, the average annual gain after privatization was equivalent to about one-sixth of total revenue in the year prior to privatization. One important feature of the net benefits series is its time pattern, given in Figure 4. There are two points of interest. First, gains during the first four years were negligible. Second, gains dropped substantially in the last four years. We will need to explain both these features in our explanatory section. 15 These gains are considerably larger than reported in our draft report. This is because at that point we had only seven years of
actual data. As a glance at Figure 4 will readily confirm, the first three of these years showed (and still show) little improvement, so projections were based on three good and four weak years. Actual performance turned out to be considerably better than projected.
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Figure 4: Net Benefits of Privatization (1995 NPV millions)
-5000
05000
1000015000
2000025000
1990 1992 1994 1996 1998 2000 2002 2004
Table 14: Impact of Electricity Privatization
Net Present Value (1995) Stakeholder FCFA million US$ million
We now look at what happened to individual stakeholders.
3.3. CONSUMERS Consumers benefited from additional electricity made available by the technical efficiencies and accelerated IPP provision which followed from privatization and received almost half of the net benefits to all stakeholders. Table 15 shows how these net benefits were distributed.
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Table 15: Distribution of Consumer Benefits
Net Present Value (1995) Consumers FCFA million US$ million
As can be seen, about half the benefits went to foreign consumers via exports. Domestic purchasers also did very nicely, with a small offset in terms of reduced consumption by thieves. The figure for blackout reduction results from our placing a very high value on a very small quantity, to reflect the revealed preferences of consumers described earlier.16 The benefits to domestic consumers were spread widely, thanks to a very important access expansion. From 1990 to 2006, connections more than doubled from 413,000 to 860,000.
3.4. EMPLOYEES Table 15 showed that workers as a group got a modest 6% of the gains. However, this is the net of two quite different effects. CIE employees gained 27,403 million FCFA while the loss in jobs cost an estimated 11,638 million FCFA. Let us consider the two groups in turn. Employees' estimated benefits include significantly higher wages, their dividends from their 5% ownership and much expanded benefits. These benefits included:
• Participation in a much expanded pension plan. This had been rising only modestly prior to 1997, but more than doubled in value over the next seven years.
• Workers loan program which more than quadrupled after privatization and included and education plan on financial management.
• A free HIV-AIDS prevention and treatment program, the first by a private enterprise in Africa. Medicine is provided free to affected workers at a cost thus far to CIE of US$ 0.5 million.
• Medical coverage by an in-house team of eight doctors and 36 nurses and other professionals. CIE covers 80% of the costs of medicine and 90% of the cost of hospitalization. This coverage has cost CIE US$ 31 million.
• Training programs for: professional responsibilities, future retirees and family budget management.
16 For all markets we measured consumer surplus using a model with excess demand and random rationing. This is explained in
detail in our Senegal Water paper. For the other markets we used a price elasticity of demand of -0.8, but for blackout reduction we used -0.10 reflected in an average price about four times as high.
October, 2006 IPA: Côte d'Ivoire Electricity Page 34 of 54 In addition to such quantifiable benefits, it is said that workers have also gained from much better morale. So, in all, there is no doubt that workers employed by CIE have gained very handsomely from privatization. CIE has maintained its initial commitment to not lay off any workers except for cause, even during the recent years of social unrest. Nonetheless, employment was reduced as employees who were fired for cause, retired, or resigned voluntarily went un-replaced. And our counterfactual story is that under continued public ownership, not only would departing workers be replaced, but the traditional pattern of job growth would have continued, culminating in approximately 400 additional jobs by 2005. As economists we certainly believe that reducing excess employment and operating more efficiently is a positive step for the economy. But there is a cost borne by some stakeholders and it is our job to take this into account in evaluating the net benefits from privatization.
3.5. GOVERNMENT The government had a healthy 28% share of the total gains. As shown in Table 16, the bulk of this (66%) came from corporate taxes on the privatized firm.. A further 23% came from their net ownership return (that is, dividends, retained earnings and capital gains), 13% from VAT on the increased electricity sales (especially exports) and -2% from changes in input markets (largely labor).
Table 16: Sources of Government Gains
Net Present Value (1995) Consumers FCFA million US$ million
The foreign owners garnered 13% of the net benefits and domestic private partners got 8%. How good is this? It is actually pretty hard to tell, because we don’t know what to compare their returns to. Ordinarily, we look at returns relative to investment (e.g. in the form of an internal rate of return). However, here, the buyers put up none of their money, instead taking over the firm in return for the annual fees enumerated above. In effect, it was a 100 percent leveraged buyout, so the return on zero investment was infinite (even if they had only gotten 1 franc back). All we can say is that their 21% share may well have been a modest price to pay for the gains to other members of society.
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3.7. ECONOMY When additional and/or more reliable electricity is supplied, considerable benefits accrue to commercial users in the form of increased profitability and to workers in the form of additional employment. The inflow of foreign investment is also enhanced. Quantifying this effect would require an economy-wide computable general equilibrium or other macro model, and this beyond the scope of this paper. But these gains are undoubtedly substantial. A second important effect was the impact on the privatization program. The electricity privatization had a considerable impact on shaping favorable public opinion and kick-starting the ambitious and highly successful privatization program of 1994.
3.8. SENSITIVITY ANALYSIS
3.8.1. Monte Carlo Analysis
Obviously, there is uncertainty in our counter-factual story. The most common way of dealing with this is to wave some verbal homage at the problem and then forget it. Those that do attempt quantification most commonly do a sensitivity analysis in which key variables are perturbed by a small symmetrical amount (say, +/- 10%) and the relative importance of each reported as a “sensitivity” indicator (percentage change in NPV or IRR over percentage change in the variable; an elasticity). This is certainly a step in the right direction, but it has two drawbacks which we try to correct. First, not all uncertainty is created equal. Ask yourself what the most important variable is in our counterfactual. Our answer going in (and going out) was the lag in the introduction of IPPs. Our base assumption was three years. But the distribution is asymmetric and the variance is quite likely to be large; it is much more likely to be longer rather than shorter, and it is impossible to be more than three years less but entirely possible that it be four or even six or nine years longer. Similarly, our base elasticity of –0.8 cannot go above zero, but could well be -1 or less (with the lower values resulting in increased consumer surplus). Contrast this with, say, the rate of transmission losses which is just as likely to be over the truth as under it. To adjust for such differences in our sensitivity analysis we adopt Monte Carlo analysis, the first characteristic of which is that it allows specification of a different distribution (normal, Poisson, etc.) and variance (standard deviation) for each variable. We use this provision judiciously: our default specification is normal, and we use something else only where there is a strong basis for believing to the contrary. A second problem with the most common approach is that it doesn’t give you a bottom line. Take two projects with comparable NPVs but quite different tables of sensitivity. Which is better? Monte Carlo analysis fixes this by doing successive runs with random draws from all sensitivity values, calculating the resulting NPVs and repeating the process thousands of times if necessary until the resulting composite NPV converges.
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3.8.2. Total Net Benefits The distribution of the Monte Carlo analysis is given in Figure 5. Note first that the mean of the runs is 517,962, about 92% higher than our base run. The reason for this is our relatively conservative assumptions and the fact that there is more upside potential than downside. Similarly, the distribution is asymmetric, positively skewed and has a high variance with a maximum of 1,114,312 and a minimum of 164,393 (61% of our base run).
Figure 5: Distribution of Total Net Benefits
Which parameters are most responsible for this variance? This is measured in Table 17 by a stepwise linear regression with net benefits on the right and the parameters on the left.17 Parameters with zero coefficients are omitted. Since consumers have close to two-thirds of the net benefits, what matters for them is what matters for the total. What the table then says is this. They are sensitive to two sets of factors: first, those that determine the amount of electricity (lag in IPPs, transmission losses, number of workers, counterfactual hydro production); second, those that determine the valuation of that electricity (demand elasticity, growth in domestic demand). 17 Regression coefficients in the table are normalized. A coefficient of 0.65 means that a 1 standard deviation change in the
independent variable produces a 0.65 standard deviation change in the dependent variable.
Values in Millions
0.000
0.200
0.400
0.600
0.800
1.000
Mean=517962.3
0.1 0.375 0.65 0.925 1.20.1 0.375 0.65 0.925 1.2
5% 90% 5% .26 .7687
Mean=517962.3
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Table 17: Sensitivity of Total Net Benefits
Variable Regression Coefficient
Counterfactual lag in purchases from IPPs (in years) 0.411 Demand elasticity 0.353 Counterfactual/factual ratio of growth in the number of Ivorian workers 0.351 Counterfactual/factual ratio of hydro production -0.351 Annual growth in domestic demand for electricity 0.242 Annual transmission losses 0.092 Counterfactual growth in the number of Ivorian workers through 1994 0.063
3.8.3. Government
The second largest net beneficiary was the government but its distribution is quite different. As shown in Figure 6, the Monte Carlo distribution of its benefits is normal and symmetric. The mean is 148,401, with a minimum of 47,509 and a maximum of 283,465. This just says that our base run is likely an under-estimate, and that the government certainly did well; it is just a question of how well.
Figure 6: Distribution of Government Net Benefits
Table 18 identifies the parameters to which government benefits are sensitive. With the exception of demand elasticity, the other six major factors influencing the total net benefits are at play here.
Values in Thousands
0.000
0.200
0.400
0.600
0.800
1.000
Mean=148401
0 100 200 3000 100 200 300
5% 90% 5% 76.2528 223.4057
Mean=148401
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Table 18: Sensitivity of Government Net Benefits
Variable Regression Coefficient
Counterfactual lag in purchases from IPPs (in years) 0.449 Counterfactual/factual ratio of hydro production -0.415 Counterfactual/factual ratio of growth in the number of Ivorian workers 0.360 Annual growth in domestic demand for electricity 0.257 Annual transmission losses 0.113 Counterfactual growth in the number of Ivorian workers through 1994 0.081
3.8.4. Sensitivity Conclusion
We could have gone into much greater detail in each of the above sections, and could have added others for each of the stakeholders. However, this should be enough to make our basic point. Any Benefit-Cost analysis involves the risk of error due to projecting an unknown future. Our variant adds the further risk of trying to tell a counterfactual story. We suggest that this Monte Carlo analysis supports our repeated contention that our base run is conservative and that it would be much more reasonable to tell a more positive story about the consequences of privatization than to tell a less positive one. 4. WHAT EXPLAINS THESE RESULTS?
4.1. PURPOSE
We now attempt to explain the foregoing results. In doing so, we try to distinguish between external factors over which sector decision-makers had little or no control, and internal factors over which they had discretion. But we organize the section according to the more important questions to be answered.
4.2. TRANSACTIONAL SUCCESS
4.2.1. The Question
Why did the deed get done? The Ivory Coast was an African pioneer in privatization and CIE was the first transaction in its justifiably renowned program. What made this possible at a time when privatization was rare in the less-developed world and even rarer in Africa?
4.2.2. Crisis
It is a truism of economic reform in rich and poor countries alike that tough economic decisions are most often made in times of crisis. CIE’s privatization indeed took place in such an environment, both for the economy as a whole and in the electricity sector. During the 1980's, per capita income had dropped by half (and a recession continued until 1994), making people relatively ready to accept tough measures and the fact that more
October, 2006 IPA: Côte d'Ivoire Electricity Page 39 of 54 government subsidies were not part of the solution. But this is hardly a sufficient condition as there are a lot more crises in the world than there are serious and successful economic reforms.
4.2.3. Receptivity to Privatization The following factors --largely favorable to privatization—may help to explain the early and successful privatization of CIE:
• By African standards, the country’s experiment with Statism was relatively brief and a stronger underlying belief in capitalism made people less opposed to privatization. This was reinforced by the fact that water had been privatized for about 20 years with no ill effects.
• By any standards, the country was quite open to foreign investment, with
about one-third of the modern sector in the hands of outsiders. This made sale to foreigners much more readily acceptable and greatly expanded the effective demand for firms.
• With about one-third of the labor force made up of Non-Ivorian Africans,
necessary labor-shedding could be accomplished with comparatively little effective union opposition. Another way of saying the same thing is that with apparent full employment of Ivorians, labor opposition was muted compared to other countries.
• Many of the enterprises already had minority private shareholders, thus
facilitating the finding of buyers and making it easier for outside buyers to know what they were really buying.
It should be emphasized that these factors did not make privatization easy, only easier than in countries where they are not present.
4.2.4. Qualified Reformers In addition to the foregoing external factors, there was a key internal factor: the people doing the reform were uncommonly qualified and despite the speed of the reform, got it pretty much right. If what we have said thus far is not enough to convince you of this, then our detailed description of the incentive system below should.
4.3. SLOW START
4.3.1. The Question We have shown that quantifiable progress in the first three years after privatization, with the notable exception of blackouts, was minimal. Why was this?
October, 2006 IPA: Côte d'Ivoire Electricity Page 40 of 54
4.3.2. Inertia
It can be argued that management turnarounds of any large organization, public or private, take time. Changing workplace culture is not easy and new systems need to be put in place before change is manifest. This is undoubtedly true, and may have been part of the explanation at CIE, but we know plenty of cases of privatization performance kinks appearing in a year or two.
4.3.3. Investment Constraint Some of the biggest gains to privatization often come from relaxing an investment constraint as a financially strapped public operator is replaced by a bankable private one. This was indeed the case with CIE, with big gains only coming when the IPPs came on line. But because only the income statement was privatized and the balance sheet remained nationalized this could not happen immediately as the government was still responsible for investment. We have argued that privatization was the key to establishing the climate for IPP entry so it was indeed instrumental in relaxing the investment constraint. But because it was a concession, it seems to have taken longer to realize investment gains. This by no means implies that the concession was a wrong choice, only that there may have been at least one cost which to some extent offset the many advantages of this privatization vehicle.
4.3.4. Technical Inheritance Another element contributing to the slow turnaround was the technical quality of what was taken over. Given the predecessor's poor reputation, this may seem a strange statement. Recall some of the numbers however: loss in transmission and distribution on the order of 14%; blackouts at 0.5% of production and private collection rate well over 90%. There was certainly room for improvement, but these are still numbers that many, if not most, utilities in Africa would look at with envy. The germane point is that as you approach a technical limit, further progress becomes harder and harder. So, it is much easier to show dramatic change if you take over a company whose technical coefficients are, say, half of those in pre-privatization. CIE had a harder job to do than those who took over less technically well-run companies.
4.4. HIGH REPUTATION
4.4.1. The Question While our slow turnaround story is based on the numbers, public opinion was that the turnaround was sudden and dramatic. Why the difference (other than that public opinion is quite often not fact based, at least in the United States)?
4.4.2. Blackout Reduction If you want to get public opinion on your side, do something which dramatically affects people’s daily life. This may seem obvious, but is easier said than done. But this is what
October, 2006 IPA: Côte d'Ivoire Electricity Page 41 of 54 CIE did by halving blackouts. Since one of the authors was without electricity for four days while working on this report, we are acutely conscious of the resulting impact on people’s lives. A quantitative blip in production figures looms large in people’s minds, and for good reason.
4.4.3. Initial Price Reduction At the time of privatization, prices were lowered by 10% to residential customers. Again, quantitatively, this was not a big factor, as it only amounted to an average reduction of 2.4 percent of total sales and persisted for only 3 years. Might this have been a modest price to pay for public good will?
4.5. ONGOING SUCCESS
4.5.1. The Question In the longer-term, the privatization has been a clear success both in terms of efficiency and in terms of equity. With the biggest winners being consumers, the second biggest being government, the private operator a distant third, and only unemployed workers losing a bit, we think most observers would agree that it has also been reasonably equitable. What caused this?
4.5.2. Experienced Operator The private operator was very experienced, not only in electricity, but also in Francophone Africa. Elsewhere we have seen privatizations fail in part because of the inability to reach agreement on serious problems not foreseen in the contract. In the case of CIE, such natural problems have been worked out collegially in a harmonious working relationship. We suggest the experience of the operator may have contributed to this.
4.5.3. Non-Transparent Sale The deal was negotiated on a person-to-person basis rather than being bid competitively and transparently as virtually all privatization experts advise. Yet it worked out well. Does this mean the advice is wrong? We don’t think so, but this case clearly shows that it can work in at least some cases. Doing it this way entailed considerable risk and they might well have gotten a better deal if they delayed and negotiated harder with more partners. This, however, would have meant considerable delay. Such delay would probably not have been particularly costly but would have been very expensive in terms of public support for privatization and the government if the blackouts had persisted.
4.5.4. Incentives As economists, we are biased towards believing that operators will do what they are paid to do, so incentives are critical in explaining the results. They both motivated the operator to do better and determined the equitable distribution of those gains. We therefore believe they deserve to be spelled out in detail.
October, 2006 IPA: Côte d'Ivoire Electricity Page 42 of 54 An all too common feature of regulatory pricing rules--especially those based on the traditional US cost-plus model--is that they provide little or no incentive for improved cost efficiency. That is, if the firm is reimbursed for its costs plus a return on investment, it has no incentive to cut either the current or the capital costs. This raises the possibility that the absence of significant change between the pre- and post-privatization periods may be due to a contract fee structure which provided inadequate incentives. It is appropriate to investigate this possibility now, because if there is no incentive to cut costs, then there is little point in our breaking our necks disaggregating things in a search for such efficiencies.
We will focus on the situation prior to 1994 when there were no exports and no IPP purchases18. The process is as follows: 1. CIE collects from consumers. 2. It keeps an amount R2/kwh to reimburse it for is fuel costs. 3. It keeps an amount R1/kwh to reimburse it for all other costs/fees. 4. It pays the balance to the government (“Redevance”) The formula for R1 is given as Table 19 and the formula for R2 is in Table 20. To aid interpretation for those familiar with international prices, Table 21 gives a time series of the various resulting prices in US cents per kwh. The formula for R1 looks complicated, but it is conceptually a simple four-part formula plus a bunch of technocratic implementation language. Focusing on the concept, CIE gets: 1. 17 cfa/kwh (Pi, an estimate of the relevant costs in 1990/91); 2. but applied to electricity charges collected, rather than billed (Et); 3. times a cost escalation factor (Ft) 4. times a scale reduction factor (0.5+0.5Ei/Et) What are the implications of these formulae for our work? First, and perhaps most importantly, the system creates high powered incentives for cost efficiency. The cost adjustment factor is a weighted average of various input prices (labor, taxes, tariffs, etc.) all of which are exogenous (e.g. as published by the Bureau of Price). This means that if the enterprise’s own costs go down, its fees do not fall, as in the traditional US system. The sole exception is provided by particular fuels whose costs are pass-throughs as shown by the formulae in Table 19. With this exception, the enterprise has every incentive to reduce costs. The second point is that the enterprise has every incentive to maximize collections, since its reimbursements are based on what is paid for rather than what is billed. In light of this, the three-year delay in getting the government to pay its bills is particularly noteworthy.
18 Additional formulae (R3 & R4) adjust for exports and IPP purchases, but we do not investigate these.
October, 2006 IPA: Côte d'Ivoire Electricity Page 43 of 54 Table 19: R1- Remuneration for Generation and Distribution Services Provided by CIE
R E P F E Et et i i pt1 05 05= +( . . / )
where: Pi represents the base price in FCFA per kwh collected prevailing in 1990/91 (17
FCFA) Ee is energy collected (in kwh) Ei is energy billed in 1990/91 Ep is provisional current energy billed F is a yearly revision factor which is the following function:
FMM
KK
OO
KK
II
TT
DD
GG
= +++
+++
+++
++
+0 275 0 725 05133
11
01833
11
0 2611
11
0 050 0 0 0 0 0 0 0
. . ( . . . . )
where: M3 is the index of minimum wage for skilled workers as published in the Official
Bulletin of Prices (“Bulletin d’Officialisation des Prix”, BOP) in public works and construction
K is a coefficient representing the social charges published in the BOP O3 is the index of the average hourly salary of unskilled workers of the third category
published in the BOP G is the index of the price of the hectoliter of “gas-oil”, including taxes, published
by the BOP I is the index, before tax, of industrial products, base 100 in 1980, intermediate
products Level 15, published by the BOP T is the rate of value added tax on industrial products for the following items:
84.01.90 (separate parts and pieces of steam furnaces) 84.08.62 (separate parts and pieces of gas turbines) 85.19.90 (separate parts and pieces of electric equipment)
which equals: 0.15 Tv + 0.15 Tg + 0.70 Te where Tv is the value added tax on spare parts for steam furnaces (84.10.90)
Tg is the value added tax on spare parts for gas turbines (84.08.62) Te is the value added tax on spare parts for electric equipment
(85.19.90) D is the rate of import rights on industrial products for the following items:
84.01.90 (separate parts and pieces of steam furnaces) 84.08.62 (separate parts and pieces of gas turbines) 85.19.90 (separate parts and pieces of electric equipment)
where DFv is the fiscal right on spare parts for steam furnaces (84.10.90)
DDv is the customs right on spare parts for steam furnaces (84.10.90) DFg is the fiscal right on spare parts for gas turbines (84.08.62) DDg is the customs right on spare parts for gas turbines (84.08.62)
October, 2006 IPA: Côte d'Ivoire Electricity Page 44 of 54
DFe is the fiscal right tax on spare parts for electric equipment (85.19.90) DDe is the customs right tax on spare parts for electric equipment (85.19.90) OIC is the relative “incidence” of the Office Ivoirien des Chargeurs
The subscript 0 refers to values at the end of June 1990. Following the end of each fiscal year, an adjustment to the above formula will be made as follows:
A = Pat - 2,520,000,000 + (Pr - Pp) Eet where: A is the amount of the adjustment, in FCFA, to be paid to CIE by the state if A > 0
and vice versa if A < 0 Pat is the actual payment made during the year Eet is total collected energy during the year Pr = Pi F (0.5 + 0.5 Ei/Er) Er actual billed energy during the year.
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Table 20: R2- Remuneration for Fuel Used and Imported Energy
R2 = Minimum (ER/r - PH - PI - PA; PT1). Cs1. p1 + PT3 . Cs3 . p’3 . T + Maximum (ER/r - PH - PI PA - PT1 - PT3; 0) . Cs2 . p2 + PI . pi . tc . + PA . pa + EI/ri . Csi . p3
where ER is total billed energy from the interconnected grid for the month in question r the yield of the interconnected transportation and distribution grid fixed for the
month by the periodic convention ER/r represents the net energy to produce contractually for the interconnected grid for
the month in question PH is net hydroelectric production for the month PI is net imported energy from Ghana for the month PA is net energy purchased from authorized producers for the month EI is total billed energy in isolated areas for the month PT = ER/r - PH - PI - PA , which represents total net thermal energy to produce for
the interconnected grid PT1 is monthly thermal production in steam tranches 1 to 4 PT2 is monthly thermal production in gas tranches 5 to 8 with HVO fuel
HVO = ER/r - PH - PI - PA - PT1 - PT3 PT3 is monthly thermal production in gas tranches 5 to 8 with DDO fuel Cs1 is actual monthly consumption for steam tranches 1 to 4 and for a Fuel Oil 380 of
41.02 MJ/kg. The specific consumption is to be readjusted proportionately to the real “PCI” of the consumed fuel.
Cs2 is actual monthly consumption for gas tranches 5 to84 and for a HVO fuel of 41.86 MJ/kg. The specific consumption is to be readjusted proportionately to the real “PCI” of the consumed fuel.
p1,p2 are the average purchase prices for the month, in FCFA per kg, of fuel used in tranches 1 to 4 (“Fuel-Oil” 380) and 5 to 8 (HVO), the price being that actually paid by CIE.
pi is the contractual dollar price per kwh of net energy imported from Ghana pa is the contractual FCFA price per kwh of net energy purchased from authorized
producers. tc is the average exchange rate for the month (FCFA/US $) published by the
BCEAO ri is the average yield of isolated grids, fixed for the year by the periodic convention EI/ri represents net contractual energy to produce for the isolated grids during the
month in question Csi is the average specific consumption in liters of DDO per kwh for thermal groups
of production in isolated grids p3 is the FCFA purchase price of a liter of DDO used for thermal production in
isolated grids p’3 is the monthly purchase price for a liter of DDO used in the Vridi plant
October, 2006 IPA: Côte d'Ivoire Electricity Page 46 of 54 T = 0 when at least one “TAV” or a system of preheating of HVO supplied by the
state is functioning = 1 when the 4 “TAV” do not function
where p1 is the price of “Fuel-Oil” 380 applicable to month n, in FCFA per kg p1n-1 is the price of “Fuel-Oil” 380 applicable to month n-1, in FCFA per kg p1n is the price of “Fuel-Oil” 380 calculated for month n, in FCFA per kg expr is the absolute value of the following expression
p1n = [(PFn-1 + Tauxn-1 + Tarifn-1) . Cn-1 + Taxen-1 ] / 100 PFn-1 is the median of average maximum and minimum prices of “Fuel-oil” 3.5% for
the month n-1 as it appears in the telex of PLATT’S MARKETSCAN under the title CARGOES FOB NWE in US dollars per metric ton
Tauxn-1 is the rate of AFRA GENERAL PURPOSE for month n-1 Tarifn-1 is the base tariff WORLDSCALE of Rotterdam-Abidjan in US dollars per metric tons in
month n-1 Cn-1 is the average monthly quotations for the month n-1 published by the Paris Bourse
(FCFA/$) Taxen-1 is the port tax at the Abidjan Port in FCFA per metric ton for month n-1 How p2 is set:
p2 = 234 . (0.10 + 0.45 . PGOn-1/249 + 0.45 . PFOn-1/170 ) . Cn-1 / 100 where: p2 is the price of HVO applicable for the month n, in FCFA per kg PGOn-1 is the median of average maximum and minimum prices of “Fuel-oil” for the
month n-1 as it appears in the telex of PLATT’S MARKETSCAN under the title CARGOES CIF NWE in BASIS ARA in US dollars per metric ton
PFOn-1 is the median of average maximum and minimum prices of “Fuel-oil” 3.5% for the month n-1 as it appears in the telex of PLATT’S MARKETSCAN under the title CARGOES CIF NWE in BASIS ARA in US dollars per metric ton
Cn-1 is the average monthly quotations for the month n-1 published by the Paris Bourse (FCFA/$)
October, 2006 IPA: Côte d'Ivoire Electricity Page 47 of 54
Table 21: Implicit Prices in US$ Paid/Received by EECI and CIE
(in US$/kwh; recall the 100% devaluation in January 1994) 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
R1: for generation and distribution (domestic sales)
0.059 0.036 0.044 0.041 0.038
R2: for fuel costs 0.025 0.024 0.028 0.024 0.029 R3: for exports 1) 0.006 0.006 0.005
CIE Payment to Government
0.064 0.077 0.069 0.026 0.037 0.037 0.032
The third point concerns the scale reduction factor. First let us make sure we understand how the formula works. By way of example, it says that if you double your production and billing, your price is adjusted by the factor (.5+.5(1/2))=.75. This factor is presumably what accounts for the fall in R1, at least from 1993 to 1997 (see Table 21; data are missing for earlier years). It therefore has profound implications for the distribution of the benefits from privatization. If this factor had not been included, considerably more revenues would have stayed with the firm and less would have gone to the government. Why was such a provision agreed to? We are not privy to the drafters’ thinking, but an economist’s first thought is that it reflects decreasing costs, for example due to fixed costs. As you increase output, average costs decline and you should be compensated less. This is what the formula accomplishes. However, for a multi-plant mixed hydro/thermal system, marginal costs are determined by the sequence in which you produce: for low loads you use hydro, for medium loads you add the newest and lowest cost thermal, and for peak loads you turn on the oldest and most inefficient and costly thermal plants. In this sense, marginal costs increase and you should get paid more at the margin. However, over a year, demand increases all across the load curve and not just at peak, so depending on the distribution across the load curve, average costs could increase, decrease or stay the same. Further, the trend in average costs will also depend on the extent to which the rains have filled the reservoirs. Presumably the drafters of the contract took all this into
October, 2006 IPA: Côte d'Ivoire Electricity Page 48 of 54 account with full knowledge of the relevant technical parameters. We do not mean to criticize this innovate factor, but merely to point out that in practice its presence has significantly shifted benefits towards the government and away from CIE. There is, however, a fourth point, which cuts the other way. As technocrats, we can only admire the sophistication of the formulae, and bask in the complexities. In practice, however, the complexity means that the task of calculating the values is left to CIE and there is some danger that they might inadvertently err on their own behalf. This is understandable, but if so, we could find no one on the government side who had the time/data/background combination to seriously check CIE’s calculations. As a fifth point, some might worry that in context of the much emulated UK RPI-X formula, there is no X in Côte d'Ivoire. That is, there is no allowance for technological progress or increased efficiency. However, the scale adjustment factor has precisely the same effect. Plugging an annual growth rate of domestic supply of 8% into the scale adjustment formula above yields an annual price decrement of 3.7%, a very reasonable number. That is, if you don’t quite see the logic of the scale adjustment factor, recast it as forcing an annual productivity gain of 3.7% and you may like it after all. We are so inclined, for what that is worth. In sum, the remuneration formulae have four very desirable properties/consequences. First, there is every incentive for minimizing costs other than fuel. Second, there is every incentive for maximizing collections. Third, to maintain profit per unit, CIE must increase efficiency by almost 4% per year. Fourth, the remuneration formulae in concert with the decisions of those who set consumer prices have combined to keep relative prices moving against CIE (output prices on average go up by less than input prices). On the down side, the formulae do not give full incentive to expand output, because of the scale adjustment factor. 5. CONCLUSION CIE is widely regarded as a success story of privatization. Our quantitative analysis suggests this reputation may have been somewhat overdone in the first three years after privatization. But, thereafter, and overall it richly deserves its reputation.
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