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Economic Regulation and Regional Integration:

Evidence from the Mexican Power Industry

Alejandro Díaz-Bautista *

Departamento de Estudios Económicos, El Colegio de la Frontera Norte

Resumen

Este estudio se centra en la caracterización de la modelo mexicano de energía

eléctrica con una nueva regulación federal bajo leyes que promueven un mer-cado eléctrico regional más competitivo con la participación de productores in-dependientes. El ejercicio empírico de los precios de nodos de energía entre lasregiones en los mercados energéticos regionales en México, muestra una mayorintegración después de la reforma económica parcial en el sector eléctrico mexi-cano de 1992 a 1993. En 1998, cerca de 75% de los pares nodales de energía entrelas diferentes regiones están cointegrados, lo que muestra un mayor grado de in-tegración en el sistema nacional de transmisión.

Abstract

The present study focuses on the characterization of Mexico’s Power model witha more relaxed federal regulation under the new competitive laws, greater regionalpower trade and a more competitive open access power market. The empirical

exercise of nodal power prices among regions shows that regional power marketsin Mexico became more integrated after the partial economic reform in the Mexi-can power sector during 1992 and 1993. By 1998, around 75% of the nodal energy price market pairs among regions were cointegrated, showing a higher degree of integration in Mexico’s national power transmission network.

Clasificación JEL : L51, C2, F15.Palabras clave/keywords: regulación económica; integración regional; industria eléc-trica; economic regulation; regional integration; power industry; Mexico.

* Tel: +52 664 631 6300 ext. 3428.

Email: [email protected].



Quantitativa Revista de Economía Vol. 1. Núm. 1

Introducción

After decades of providing electricity through a state monopoly, the Me-xican government is taking incremental steps to permit private participa-tion in the sector. This reform is being driven by increases in demand forelectricity that have outpaced the government’s ability to finance necessary expansion and modernization. The role of the Mexican government in theelectricity sector is rooted in the Mexican Constitution, which providesthat the State has a monopoly over the public service of electricity, inclu-ding the generation, transmission, distribution and commercialization of energy. Under this monopoly structure, Mexico was able to supply electri-city to 94.7 per cent of its population by 2000. According to the 2001−2006Energy Program developed by the Mexican Government,demand for elec-

tricity was expected to grow at 6 per cent annually for the next ten years, which will require an additional 27,357 megawatts ( MW ) of generation capa-city. While 10,854 MW of that capacity will be covered by existing contractsor commitments, the 16,503 MW shortfall must be made up by additionalgeneration projects that have not yet been committed.

In 1992, the Mexican Congress amended the Electric Power PublicUtility Law to allow, for the first time, some private investment in powergeneration. The new law and economic regulation allowed private invest-ment in the following types of generation facilities:

1. Self-generation or self-consumption (generation dedicated to the ex-clusive use of the generator and its owners);

2. Co-generation (generation using steam or other thermal energy pro-duced by industrial processes);

3. Independent power production (generation by plants greater than 30MW for the sole purpose of selling the energy and capacity producedto the CFE, also known as IPPs );

4. Small production (generation by plants of less than 30 MW for thesole purpose of selling the energy and capacity produced to the CFE );and

5. Generation exclusively for import (to satisfy the permit holder’s own

needs) and for export purposes.

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Economic Regulation and Regional Integration

The Law also provided that permit holders (i.e., the private genera-

tors described above) could enter into contracts with the CFE for a) thesale of up to 20 MW of their excess capacity and associated energy; or b)the sale of excess energy (i.e., energy other than that required to meet thepermit holder’s needs). By January 2002, permits for nearly 18,000 MW of co-generation, independent production and import and export had beengranted in Mexico.

Another mayor change in the industrial organization of the power in-dustry in Mexico came in 2009. During 2009, President Felipe Calderónissued a decree ordering the liquidation of Luz y Fuerza, according to anotice published in Mexico’s official gazette. The financial situation of Luzy Fuerza was unsustainable. If Luz y Fuerza were left to continue opera-ting, the federal government would have to transfer about 300 billion pesosto the company by 2012. Between 2003 and 2008, Luz y Fuerza generatedsales of 235.7 billion pesos, while costs reached 443.2 billion pesos, genera-ting losses. By June of 2009 the company reported a loss of 30.6 percent of the power that it distributed. Almost no other power company in the worldshowed a percentage of power loss registered by Luz y Fuerza in Mexico.

The econometric technique used in this paper is cointegration analysis.If a linear combination of variables is stationary even though the variablesthemselves are not stationary, they are said to be cointegrated. Thus, coin-tegration refers to a linear combination of nonstationary variables. Beforeany meaningful test of cointegration among various variables can be per-formed, it is necessary to explore first whether the examined time series

contain one or more unit roots. The existence of a unit root in a singletime series is taken to mean that the underlying series is non-stationary. Two or more variables must be integrated of the same order if they are tobe cointegrated. In the present study, a time series cointegration analysis isapplied in the Mexican power regional nodes before and after the partialderegulation of the electricity industry in 1993.

1. Empirical Methodology

The law of one price states that a good must sell for the same price in allregions. This law applies in the regional and international markets and is a

common sense notion. If the law were not true, unexploited profit oppor-

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tunities would exist, allowing someone to earn riskless profits by purcha-

sing low in one region and selling high in another. For example: Mexicanconsumers buying power in the United States. In the paper I make a com-parison of the equilibrium price tendencies in regional markets, assuming prices are equal to marginal cost. In an arbitrage-free economy with notransactions costs, at any given time, a claim will be obtained for the sameprice. This will also be true for any package of time-state claims in power. This property is known as the law of one price.

Power traders and institutions attempt to exploit discrepancies in pri-ces that arise from transactions costs, broadly construed. But they also tendto decrease the transactions costs that will be borne by others. Thus the ac-tions of arbitrageurs, regulators and traders tend to bring markets for Stateclaims and combinations of such claims closer and closer to the ideal of zero transactions costs and true conformity with the law of one price. Thelaw of one price implies that every commodity should have the same price worldwide when measured in the same currency. Rogoff ’s (1996) survey isthe best single review and summary of research on law of one price.

In a pathbreaking paper in the energy literature, De Vany and Walls(1993) argued that the recently developed cointegration techniques werethe natural way to evaluate competition among the natural gas spot marketsat dispersed points in the national transmission network. They found thatmore than 65% of the natural gas markets had become cointegrated in theUS. The increased cointegration of prices showed evidence that open accesshad made gas markets more competitive.

De Vany and Walls (1996) also developed a model of the law of oneprice in a network where many markets are linked with a structure of paths. They show that arbitrage-free prices depend on the structure of the network and so do price dynamics. The estimates indicated that local bypassand open access pipeline transportation were instrumental in opening ar-bitrage paths to natural gas city markets in the US and causing their pricesto converge. Spot markets in the city gates, pipeline hubs and productionfields that were scattered over distant points in the vast pipeline network in the United States, now form a single market. De Vany and Walls (1999)developed a cointegration analysis of spot electricity prices and gave so-me insights on transmission efficiency in the Western United States grid.

I follow the work by De Vany and Walls (1999) and apply the time series

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cointegration analysis in the Mexican power regional nodes before and af-

ter the partial deregulation of 1993. This paper employs a time series cointegration method to study the validity of the law of one price. Linear cointegration techniques, such asunit root tests, examine the properties of power data by assuming that va-riables behave the same regardless of their proximity to the hypothesizedequilibrium condition. I test the law of one price by examining the powerprices among different regions of Mexico, among sectors of the economy in Mexico and finally between the US and Mexico. I anticipate the diffe-rential to be small, after the passage of the deregulation law of 1993 andbehaving in a random, non-deterministic way.1 When the deviations arelarge, arbitrage and substitution could restore the approximate equilibriumprice. Regional and international power price arbitrage is an application of

the Law of one price to the power markets. It states that power sold indifferent markets ought to have the same price after adjusting for trans-mission costs. If a price differential exists, then arbitrage should bid theprices closer together.

First, I test the relationship between the spot rate, S (t), and relativeprices with the following cointegration technique:

S (t) = α + β ( p(1, t) − p(2, t)) + ϵ (1)

where p(1, t) is the price in node 1 at time t, p(2, t) is the price in thesecond node at time t and ϵ is the error term.2

1 A new set of regulations for the Mexican power sector were issued during 1992 and1993 in Mexico’s official gazette and were put into effect by 1994. Some of the new regulations mentioned that private investors could construct, own and operate ge-neration facilities for the purposes of self-supply, cogeneration, independent powergeneration and small production, up to 30 MW of capacity. The government’s objective

was to double the installed capacity of Mexico in ten years, from a level of roughly 28GW in 1992. The Energy Minister’s team visualized major investments by IPPs. Thegovernment anticipated that as much as 80% of future electric power capacity couldcome from privately built and financed electric power stations. For this reason thefederal law governing electricity was modified to allow for private investment. This

was the first step towards an open access market for power in Mexico and the creationof the Energy Regulatory Commission ( CRE ) in 1994.

2I assume symmetry between both regions, β = 1.

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De Vany and Walls (1993) mention that if the cointegrating parameter

in the cointegrating regression is equal to one, the result would be per-fect market integration.3 By relaxing the symmetry condition and testing whether the prices in both regions are cointegrated, I use the following:

p(1, t) = α + βp(2, t) + ϵ (2)

For the power prices between Mexico and the US, I include the exchan-ge rate S in the following equation:

p(1, t) = α + β (S (t) + p(2, t)) + ϵ (3)

The constant α reflects the cost of power of transmission between tworegions or nodes. To test for convergence of power prices and regional

arbitrage among regions in Mexico, I use the following equation:

p(1, t) = α + β ( p(2, t)) + ϵ (4)

Again the constant α reflects the cost of power transmission betweentwo regions or nodes. I consider two regional power price time series, p(1, t) and p(2, t). Suppose each series has a unit root and must be dif-ferentiated to achieve stationarity. Then we expect to have a linear trans-formation of the regional series that may be cointegrated:4

p(1, t) − α− β (2, t) = ϵ (5)

I expect the seriesϵ

to be integrated. If the linear transformation among regional prices exists, then they are said to be cointegrated.

3 When the price series are integrated of order one I (1), and they are cointegrated, thenthe linear combination of the series will be stationary. Non-stationarity would indicatethat the spot rate and relative prices are not cointegrated, which would be a failure of the law of one price. Prices would be drifting apart indefinitely.

4 A time series process (xt) and (yt) are cointegrated if there exists a linear combinationof them which is covariance stationary. A p-order autoregressive process may be writtenas zt = yt − βxt and zt = ρ(zt − 1) + φδzt − 1 + . . . + φ( p − 1)δzt − 1 + µt,

where µt is white noise and [1,−β ] is the cointegrating vector. If |ρ| <= 1 , then zt isstationary and (xt, yt) are considered cointegrated or the values cannot drift apart inthe long run, although they may vary randomly in the short run. If zt is at or near an

equilibrium value, |ρ| = 1 and (xt, yt) are cointegrated.

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In this study I also consider a two-country case with Mexico and the US.

Two power prices exist simultaneously for a product in an open industry,the domestic and foreign price. The nature of electricity as a tradable andhomogeneous product permits it to be transported with relatively easy ar-bitrage.

Adjusting the Mexican power price for the peso-dollar exchange rateand taking logarithms gives us:

p(1, t) = s(t) + p(1, t∗) (6)

where p(1, t) is the price index in country 1 for the power industry, s(t) isthe exchange rate between both countries and p(1, t∗) is the power indexin the other country. The price differential between the two markets is:

z(t) = p(1, t) − (s(t) + p(1, t∗)) (7)

then

z(t) = p(1, t) − p(2, t) (8)

where p(2, t) = s(t) + p(1, t∗), which is a rate-adjusted power price forregion 2.

First, I test hourly and daily nodal marginal costs by months for 25regions in Mexico between 1992 and 1993 and between 1997 and 1998. Thefirst sample is taken from the statistics of Mexico’s Comisión Federal deElectricidad ( CFE ) and Secretaría de Energía. The sample includes Mexico’snational interconnected power grid with the 25 regional nodal zones andfour regional divisions: Northern, North Baja, South Baja and Southern.

I also test average price data for the US and Mexico from 1973 to 1999. The sample is residential, commercial, industrial and agricultural power pri-ces from 1973 to 1999 in Mexico and the United States. The US data comesfrom the Energy Information Administration Statistics and the MexicanData from Secretaría de Energía. The econometric methodology to testfor cointegration across nodal power regions is the likelihood ratio cointe-gration test used by Johansen (1991).

2. Empirical Results in the Regional Power Model

Given a group of non-stationary power price series, I am interested in de-

termining whether the series are cointegrated, and if they are, in identifying

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the cointegrating (long-run equilibrium) relationships. Tests were perfor-

med for a unit root in the level, first difference or second difference of theseries. If the test failed to reject the test in levels but rejected the test in firstdifferences, then the series contains one unit root integrated of order oneI (1). To test the results of pairwise series cointegration, I used the Johan-sen Test. The accurate question is not the effect of deregulation, but wasthe partial deregulation of the Mexican power sector real?

Tables 1 and 2 show the results of the likelihood ratio cointegration testacross nodal power regions in Mexico for 1993 and 1998. The results con-firm Mexico’s regional competitive markets after the passage of the 1993regulatory framework. In 1993, 73% of the nodal power regions were notcointegrated. Before deregulation and the removal of legal restrictions andintegration of markets by law, and not by interconnection, we have a largepercentage of nodal regions showing lack of cointegration. After the pas-sage of several laws permitting more competitive markets, Mexico has amore integrated power network. In 1998, 75% of the regional nodal powermarkets had cointegrated prices. The result suggests that almost all powerregions were interconnected via transmission lines. This means that theMexican power network among regions is competitive and has the capabi-lity for complete open access.

3. Regional Robustness Cases

Consider the Baja California region, since it remains isolated from the rest

of the Mexican National Interconnected system in terms of interconnec-tion via transmission lines. In 1998, the Baja California region showed lack of cointegration with other regions. We can rule out this region since it hasno possibility of integration.

In the Mexican power sector, most regions had an increase in physicalcapacities of generation and transmission lines. New technologies, like theNatural Gas Combined Cycle technology, affected regional marginal costsand prices. To net out the effect of legal liberalization, I consider a region where the physical capacity remained the same. In the Western region of Mexico, the regional capacity remained near 8,000 MW from 1994 to 1999,from a national total of 38,500 MW in 1999. The occidental area shows

the case controlling for new technology and increasing interconnection.

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TABLE 1 Empirical tests of the nodal power regions in Mexico using the

likelihood ratio cointegration test for 1993Baj Bjs Bal Bra Cam Cen Che Chi

Aca 3.5* 6.50* 3.63* 3.78* 6.86* 4.59* 1.32* 3.66*Baj -* 3.39* 1.94* 3.33* 3.40* 3.37* 3.36* 3.37*Bjs -* -** 3.24* 3.70* 3.20* 4.52* 5.43* 3.70*Bal -* -** -** 4.91* 1.16* 4.54* 1.21* 4.10*Bra -* -** -** -** 3.69* 3.88* 3.68* 2.77*Cam -* -** -** -** -** 5.10* 0.75* 4.73*Cen -* -** -** -** -** -** 3.16* 4.91*Che -* -** -** -** -** -** -** 3.84*

Coa Col Hua Jua Lag Ma1 Ma2 Mon Aca 4.77* 4.60* 1.00* 3.64* 4.72* 3.26* 5.21* 4.77*

Baj 1.33* 3.37* 1.90* 4.37* 3.33* 3.88* 2.87* 4.33*Bjs 3.70* 3.93* 4.13* 1.67* 3.65* 0.07* 5.97* 3.70*Bal 4.90* 3.28* 3.43* 3.08* 4.87* 1.55* 5.69* 3.90*Bra 3.70* 4.97* 1.94* 4.76* 4.50* 0.25* 4.96* 3.36*Cam 4.68* 4.96* 4.32* 3.70* 4.64* 1.09* 5.91* 4.68*Cen 4.87* 3.99* 3.65* 4.89* 4.84* 4.64* 6.31* 4.87*Che 4.64* 1.73* 1.73* 4.26* 4.62* 0.99* 1.96* 4.67*Chi 4.77* 3.16* 4.60* 4.25* 1.71* 3.45* 4.10* 1.77*Coa -** 4.97* 4.93* 1.77* 4.73* 3.27* 4.96* 3.21*Col -** -** 3.30* 3.14* 4.93* 3.42* 1.44* 4.96*Hua -** -** -** 4.59* 4.90* 4.06* 1.23* 4.93* Jua -** -** -** -** 4.70* 3.45* 4.09* 4.77*Lag -** -** -** -** -** 3.34* 4.94* 4.70*Ma1 -** -** -** -** -** -** 3.98* 3.27*Ma2 -** -** -** -** -** -** -** 4.96*

The Central region also maintained the installed capacity of around 5,500MW between 1994 and 1999. The regions were similar before and after thepartial open access and deregulation. In 1993, cointegration was rejectedbetween the Central and Western regions. By 1998, we had cointegrationacross both nodal regions. This shows that increasing cointegration of pri-ces is driven by the removal of legal barriers, and not by the case of purely external factors like new technologies and increasing generating capacity.

When testing is done for cointegration between the residential and

heavy industry sector in Mexico, it shows support for cointegration. We

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TABLE 1 Continued…

Occ Ori Pet Sin Son Sur Tep Ver Yuc Aca 4.74* 4.34* 4.66* 3.60* 3.23* 5.29* 4.65* 4.98* 1.34*Baj 1.68* 1.85* 1.97* 3.86* 3.88* 4.58* 1.68* 1.62* 1.67*Bjs 4.95* 1.68* 4.21* 0.10* 0.02* 1.25* 1.97* 1.44* 1.45*Bal 4.36* 4.53* 3.45* 4.92* 3.61* 3.74* 4.01* 4.25* 1.21*Bra 4.98* 4.76* 4.91* 3.58* 3.36* 4.75* 4.98* 4.78* 4.68*Cam 1.16* 1.27* 1.07* 1.24* 0.73* 0.86* 3.12* 6.35* 3.69*Cen 4.98* 1.43* 3.25* 3.97* 3.68* 1.76* 3.92* 4.79* 5.16*Che 4.85* 1.33* 1.13* 1.14* 0.64* 0.77* 1.83* 1.41* 4.23*Chi 3.23* 4.87* 3.11* 4.96* 3.50* 3.31* 4.20* 3.10* 3.84*Coa 4.97* 5.84* 4.90* 3.59* 3.37* 4.74* 4.97* 4.78* 4.67*Col 4.64* 3.68* 3.73* 3.78* 3.47* 1.59* 3.02* 4.91* 1.73*Hua 3.07* 1.37* 3.42* 4.45* 4.14* 1.68* 3.10* 4.78* 4.26* Jua 3.20* 4.85* 3.09* 3.96* 3.50* 4.29* 3.18* 3.08* 3.82*Lag 4.94* 4.80* 4.87* 3.68* 3.46* 3.70* 3.94* 4.74* 3.62*Ma1 3.38* 3.59* 3.55* 4.23* 3.98* 3.36* 3.39* 3.37* 0.99*Ma2 1.43* 1.25* 1.61* 5.42* 4.19* 1.64* 1.44* 1.86* 1.96*Mon 3.97* 4.84* 3.90* 3.59* 3.37* 4.74* 4.97* 4.77* 4.67*Occ -** 4.84* 4.15* 3.73* 3.43* 1.82* 3.14* 1.25* 1.86*Ori -** -** 3.66* 3.93* 3.62* 1.01* 3.77* 1.74* 1.33*Pet -** -** -** 3.92* 3.61* 3.79* 3.56* 3.34* 4.13*Sin -** -** -** -** 3.07* 3.71* 3.74* 3.70* 1.14*Son -** -** -** -** -** 3.38* 3.41* 3.38* 0.64*Sur -** -** -** -** -** -** 1.48* 3.53* 4.48* Tep -** -** -** -** -** -** -** 1.12* 1.84*

Ver -** -** -** -** -** -** -** -** 4.57** Denotes rejection of the hypothesis of one cointegrating equation at 5% (1%) significance level. If not rejected the likelihood ratio test indicates one cointegrating equation at 5% (1%) significance level.

The finding of at least one cointegrating relation is in accordance with the theory. Note: Aca = Acapulco, Baj = Baja, Bjs = Baja Sur, Bal = Balsas, Bra = Bravo, Cam = Campeche, Cen= Central, Che = Chetumal, Chi = Chihuahua,Coa = Coahuila, Col = Colima, Hua = Huasteca, Jua =

Juarez, Lag = Laguna, Ma1 = Mazatlan 101,Ma2 = Mazatlan 102,Mon = Monterrey,Occ = Occidente,Ori = Oriente, Pet = Petacalco, Sin = Sinaloa, Son = Sonrante, Sur = Sureste, Tep = Tepic and Ver =

Veracruz.

have rejection of the hypothesis of no cointegration at the 5% significancelevel. And no rejection for one cointegrating equation using a linear deter-ministic trend in the data.

I also test the law of one price between the United States and Mexico.

Tariffs, product differentiation and institutional entry barriers are a few of

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TABLE 2 Empirical tests of the nodal power regions in Mexico using the

likelihood ratio cointegration test for 1998Baj Bjs Bal Bra Cam Cen Che Chi

Aca 3.54* 3.71* 1.94* 0.06* 1.48* 1.37* 1.53* 1.22*Baj -** 3.25 * 2.53* 4.76* 4.93* 4.54* 4.90* 4.10*Bjs -*** -** 4.64* 3.78* 3.72* 4.67* 4.76* 1.77*Bal -** -** -** 1.03* 1.44* 1.78* 1.49* 4.20*Bra -** -** -** -** 1.74* 1.09* 1.79* 5.23*Cam -** -** -** -** -** 1.43* 1.00* 3.69*Cen -** -** -** -** -** -** 1.16* 1.82*Che -** -** -** -** -** -** -** 1.34*

Coa Col Hua Jua Lag Ma1 Ma2 Mon Aca 3.04* 4.86* 6.72* 1.23* 1.43* 1.55* 1.43* 3.04*

Ba 4.77* 4.53* 4.53* 4.06* 4.21* 5.38* 4.47* 4.78*Bjs 4.53* 4.61* 4.65* 1.77* 3.86* 1.68* 4.00* 4.54*Bal 3.01* 4.48* 3.10* 4.20* 1.43* 1.48* 1.43* 1.01*Bra 1.49* 1.96* 1.98* 3.21* 1.15* 1.49* 2.00* 2.08*Cam 4.74* 1.46* 1.48* 1.68* 1.59* 1.29* 1.60* 1.74*Cen 1.81* 1.49* 1.23* 1.87* 2.82* 1.60* 1.31* 2.83*Che 1.61* 1.71* 1.70* 1.24* 2.61* 0.91* 1.90* 2.61*Chi 4.71* 3.15* 1.61* 2.28* 2.73* 1.43* 1.11* 2.71*Coa -** 1.91* 1.95* 2.76* 2.79* 0.21* 2.95* 1.25*Col -** -** 3.32* 2.18* 1.43* 1.44* 1.43* 1.95*Hua -** -** -** 3.21* 1.42* 1.53* 1.43* 1.96* Jua -** -** -** -** 4.49* 1.68* 3.51* 3.24*Lag -** -** -** -** -** 1.21* 1.43* 1.20*Ma1 -** -** -** -** -** -** 1.18* 1.54*Ma2 -** -** -** -** -** -** -** 1.05*

the impediments in the history of the Mexican power markets. Other im-pediments include restrictive agreements between manufacturers and re-tailers, exchange rate volatility, tariffs, transmission costs and the numberof interconnections between both countries. The Northern part of Mexico was connected to the US grid in nine places and two US electricity grids. Twoof the connections are to the California border, and seven connections areto Texas. For this part of the study I use the average price data for the US

and Mexico. The sample is residential, commercial, industrial and agricul-

tural power prices from 1973 to 1999 in Mexico and the United States with

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TABLE 2 Continued…

Occ Ori Pet Sin Son Sur Tep Ver Yuc Aca 1.93* 1.62* 1.83* 1.55* 1.56* 1.75* 5.23* 1.16* 1.51*Baj 3.53* 3.54* 4.53* 2.38* 2.39* 4.55* 4.53* 4.55* 5.91*Bjs 4.61* 4.67* 4.64* 1.68* 1.67* 4.68* 4.59* 4.68* 5.74*Bal 1.72* 1.69* 1.90* 1.48* 1.49* 4.84* 4.93* 1.21* 1.46*Bra 2.96* 1.09* 1.02* 1.49* 1.50* 1.11* 1.98* 1.11* 1.77*Cam 1.46* 1.41* 1.45* 1.29* 1.29* 1.46* 1.40* 1.42* 4.28*Cen 1.91* 1.34* 1.13* 1.98* 1.73* 1.34* 3.90* 4.54* 5.34*Che 1.34* 1.12* 1.34* 1.34* 0.23* 1.45* 1.67* 1.35* 1.67*Chi 1.56* 1.58* 3.63* 1.34* 1.59* 1.34* 1.25* 1.45* 1.45*Coa 1.91* 1.78* 4.45* 1.78* 0.39* 1.75* 1.67* 1.87* 1.34*Col 4.18* 4.67* 1.44* 1.44* 1.45* 1.79* 4.24* 1.89* 1.48*Hua 3.35* 2.48* 3.03* 1.53* 1.53* 1.97* 4.01* 1.40* 1.51* Jua 4.18* 3.22* 3.20* 1.68* 1.68* 1.68* 3.16* 5.22* 4.68*Lag 1.43* 1.43* 1.43* 1.21* 1.22* 1.43* 1.42* 1.43* 1.55*Ma1 1.44* 1.48* 1.48* 1.70* 1.83* 1.53* 1.42* 1.53* 1.22*Ma2 1.43* 1.43* 1.43* 1.18* 1.18* 1.43* 1.42* 1.43* 1.61*Mon 1.94* 1.07* 1.00* 1.54* 1.54* 1.08* 1.96* 1.09* 1.77*Occ -** 1.71* 1.70* 1.44 1.45* 1.88* 4.22* 1.01* 1.48*Ori -** -** 1.72* 1.53* 1.53* 2.41* 1.29* 4.72* 1.44*Pet -** -** -** 1.48* 1.48* 1.48* 4.84* 1.19* 1.47*Sin -** -** -** -** 1.42* 1.53* 1.42* 1.53* 1.22*Son -** -** -** -** -** 1.53* 1.43* 1.53* 1.22*Sur -** -** -** -** -** -** 1.53* 1.43* 1.22* Tep -** -** -** -** -** -** -** 1.54* 1.42*

Ver -** -** -** -** -** -** -** -** 1.44** Denotes rejection of the hypothesis of one cointegrating equation at 5% (1%) significance level. If not rejected the likelihood ratio test indicates one cointegrating equation at 5% (1%) significance level.

The finding of at least one cointegrating relation is in accordance with the theory. Note: Aca = Acapulco, Baj = Baja, Bjs = Baja Sur, Bal = Balsas, Bra = Bravo, Cam = Campeche, Cen= Central, Che = Chetumal, Chi = Chihuahua,Coa = Coahuila, Col = Colima, Hua = Huasteca, Jua =

Juarez, Lag = Laguna, Ma1 = Mazatlan 101,Ma2 = Mazatlan 102,Mon = Monterrey,Occ = Occidente,Ori = Oriente, Pet = Petacalco, Sin = Sinaloa, Son = Sonrante, Sur = Sureste, Tep = Tepic and Ver =

Veracruz.

data from the Energy Information Administration Statistics and Mexico’sSecretaría de Energía.

For the commercial sector, the Johansen Test rejects the hypothesis of no cointegration. And it does not reject the hypothesis of one cointegrating

relation, and two cointegrating relations, against the hypothesis of full rank

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TABLE 3 Cointegration between the residential and the heavy industry

sector in MexicoLags interval: 1 to 1. Series: residential − heavy industry

Likelihood 5 Percent 1 Percent HypothesizedEigenvalue Ratio Critical Value Critical Value No. of CEs−0.554401 −39.343320 42.440, 48.4500000 None−0.420344 *−9.134940 25.320, 30.4500000 At most 1−0.197544 *−5.501949 12.250, 16.2600000 At most 2

Unnormalized Cointegrating Coefficients

−0.340777 *−0.601533 −12.06120 0.271097−0.201437 *−0.082893 −6.487738 0.019478−0.376810 *−0.434175 −3.792995 0.124032

The table shows the trace test for the number of cointegrating relations in the residential and the

industrial sectors in Mexico. The eigenvalues are presented in the first column,while the second column(likelihood ratio) gives the LR test statistic. The first row in the upper table tests the hypothesis of nocointegration, the second row tests the hypothesis of one cointegrating relation, the third row tests thehypothesis of two cointegrating relations, and so on, all against the alternative hypothesis of full rank.

or all the series are stationary. For the commercial sector, the law one priceholds for power prices between Mexico and the US. For the industrial andagricultural sectors we cannot reject the hypothesis of no cointegration.

The problem for the agricultural sector may be the high cost of arbi-trage of power by low voltage distribution lines in the commercial sector.If the law of one price (price equalization principle) did not hold, arbitrage would be possible and restore parity. Many factors may prevent completeadjustment in relative price levels. These include trade barriers, such as ta-riffs and quotas; non-tariff barriers, including the bureaucratic difficultiesof establishing foreign distribution systems for power; the failure of nomi-nal exchange rate adjustment between the peso and the dollar; or the CFE

exercising local monopoly power and pricing to segmented markets. Somecombination of all of these factors is likely to prevent a rapid adjustmenttoward a single price, as it seems improbable that any one in isolation isimportant to explain the slow convergence in its entirety.

If firms could price discriminate between domestic and foreign mar-kets, the law of one price will not hold for homogenous goods. Finally, if goods are not homogenous (the Mexican power is not as reliable as the US

power), the US price in dollars of the Mexican power does not have to be

equal to the price in dollars of the US power.

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TABLE 4 Mexico and the United States Commercial, Agricultural and

Industry Price CointegrationComercial Sector

Series: Peso-dollar exchange rate, Price commercial sector USA

and Price commercial sector Mexico.Lags interval: 1 to 1 **denotes rejection of hypothesis at 5% significance level.

Eigenvalue LR 5% Critical 1% Critical Hypothesized Value Value No. of CEs

0.908108 71.77333 42.44 48.45 None **0.256767 12.09493 25.32 30.45 At most 10.170599 124.676298 12.25 16.26 At most 2

Agricultural Sector

Series: Peso-dollar exchange rate, Price agricultural sector USA

and Price agricultural sector Mexico.Lags interval: 1 to 1 **denotes rejection of hypothesis at 5% significance level.Eigenvalue LR 5% Critical 1% Critical Hypothesized

Value Value No. of CEs

0.406070 17.98729 25.32 30.45 None0.180020 14.96204 12.25 16.26 At most 1

Industrial Sector

Series: Peso-dollar exchange rate, Price industrial sector USA

and Price industrial sector Mexico.Lags interval: 1 to 1 **denotes rejection of hypothesis at 5% significance level.

Eigenvalue LR 5% Critical 1% Critical Hypothesized Value Value No. of CEs

0.446900 20.41396 25.32 30.45 None

0.200958 124.608532 12.25 16.26 At most 1 The table shows the trace test for the number of cointegrating relations in the residential and theindustrial sectors in Mexico. The eigenvalues are presented in the first column,while the second column(likelihood ratio) gives the LR test statistic. The first row in the upper table tests the hypothesis of nocointegration, the second row tests the hypothesis of one cointegrating relation, the third row tests thehypothesis of two cointegrating relations, and so on, all against the alternative hypothesis of full rank.

To understand the importance of the exchange rate in the price of power in North America, we observe that the dollar had a dramatic apprecia-tion compared with the peso in the 1980s and 1990s. Consider the com-petition in the power industry in the late 1980s. As the dollar appreciatedin the 1980s and 1990s, the Mexican power industry had now two options.Since the dollar has appreciated, they could maintain their peso prices and

sell energy at a much lower price in the US.

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TABLE 5 North American electricity imports and exports, 1990-1996

Country 1990 1991 1992 1993 1994 1995 1996Imports

Canada 19.4 2 7.9 2 7.9 2 9.8 2 6.5 2 8.0 2 7.7Mexico 20.6 20.6 21.0 20.8 21.1 21.2 21.3United States 22.6 30.8 37.2 39.1 52.2 46.8 46.5North America 42.5 39.4 46.1 49.7 59.8 55.9 55.6

Exports

Canada 20.1 28.7 35.2 37.1 50.2 44.5 45.3Mexico 22.0 22.1 22.0 22.0 22.0 22.3 21.3United States 20.5 28.5 28.9 10.7 27.6 29.1 29.0North America 42.5 39.4 46.1 49.7 59.8 55.9 55.6

Note: includes imports and exports by NAFTA countries between 1989 and 1996 (billion kilowatthours).

The appreciation of the dollar reduces the competitiveness of US powersince now you can import Mexican power at a much lower price. This lossof competitiveness is the typical effect of a domestic currency appreciation.Imported goods become cheaper than domestic goods and the energy tra-de balance will worsen as we buy more foreign goods, and there is a fullpass-through of the exchange rate to the domestic ( US ) price of importedgoods.

The data shows an increased imports and exports of Mexican electricity in the NAFTA region in the 1990s. Mexico was exporting power to the US

until 1996, when the Mexican power sector had limited reserve capacity.

While the profit margin of the Mexican power industry was not increasing,Mexican power became cheaper, the demand was higher and the marketshare of Mexico’s power in the US market became larger. In this case profitmargins were constant but market shares are larger for the Mexican powerindustry. This is a case where the law of one price does not hold since theprice of US power is different from the price of Mexican power.

Conclusions

The study has shown that the apparent failure of the law of one price in73% of the Mexican Regional Power Markets in 1993 was due to the pre-

sence of substantial barriers to producer arbitrage. The results also suggests

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that the law of one price does not hold in the residential sector between

the US and Mexico during 1973−

1998, since the price differentials behaverandomly and linear tests are unable to find evidence of the convergencecondition.

The empirical examination of nodal power prices among regions inMexico in 1998 leads to conclude that regional power markets became mo-re integrated after the economic regulation reform in the power sector. By 1998, 75% of the nodal price market pairs among regions were cointegra-ted, showing a higher degree of integration in the Mexican National Power Transmission Network. Partial open access in the Mexican transmissionsystem has provided the basis for integrating separate and distant mar-kets into one market. Cointegration in the heavy industry power series between Mexico and the US, and increasing power exchanges between Mexicoand the US also shows a more integrated North American power marketthan the one previously thought by energy analysts. The law of one pri-ce partly holds in the Mexican regional power sector, due to the changein power laws, power institutions and regulators. Another result from theanalysis is the expected gains in efficiency, which would be derived fromimprovements in both generation and transmission interconnection. Ho- wever, this result depends greatly on the implementation of proper incen-tives for the construction of new infrastructure, a competitive market forelectricity and a proper regulation of the other areas of the industry. If theintegrating conditions can be implemented, then a decline in medium andlong-run prices will likely occur in Mexico.

The Mexican transmission grid is fully capable of making a slow, market-based transition to consumer choice and further deregulation. It is alsocapable of installing the upgrades and the capabilities that will allow allthe players to continue to make a profit on generating, transmitting anddistributing electricity to the end consumer. Moving to a competitive envi-ronment is likely to cause a short-term increase in the conventional steamand natural gas of combined cycle-generating capacity in Mexico. Tech-nological advances will come into play in the power sector since we areallowing entry into a marketplace by generators and distribution providers who currently are forbidden to compete. Electricity demand was satisfiedin Mexico according to the 2001−2006 Energy Program developed by the

Mexican government, which required the installation of more than 27,000

40




MW of generation capacity. By the year 2010, electricity generation and

supply were well above demand, and the national power sector in Mexicohad a large reserve margin close to 42.4%. Energy outlook analysis showsthat by 2012 Mexico will have a reserve margin of 33% in the electricity sector and will buy almost 50% of its power from independent power pro-ducers.

The analysis across nodal power regions in Mexico for 1993 and 1998confirms Mexico’s regional power transmission integration and competitive markets after the passage of the 1992 and 1993 regulatory framework. The findings support the consensus between the political establishmentand industry plans in Mexico to keep transmission under State control withopen access to independent power producers. Finally, the Mexican regio-nal power network is considered more integrated, competitive and has thecapability for complete open access.

Fecha de recepción: 30-IV -2011.Fecha de aceptación: 20- V -2011.

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