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\title{The Usage of Lric Model Regulation for Access Relevant Markets in Economically Small Countries}
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\begin{document}

             \author[1]{Dr. Andrej  Mihevc}

             \affil[1]{  University of Primorska}

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\date{\small \em Received: 5 February 2015 Accepted: 28 February 2015 Published: 15 March 2015}

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\begin{abstract}
        


The aim of the article was answer the main research question if ex ante regulation using LRIC (?Long run incremental costs?) model is appropriate for Access relevant markets regulation on economic small markets, especially in time of NGN (next generation networks). LRIC model is the strongest regulation which can be imposed by regulators in some EU country. European Commission defined two relevant Access markets susceptible to ?ex ante? regulation. The new recommendation of the European Commission (EC 2007) on relevant markets defined Market 4 (previously Market 11) as the market for wholesale (physical) network infrastructure Access (also local loop unbundling) at fixed location and market 5 as Broadband Access (include only bit stream Access).

\end{abstract}


\keywords{lric model, regulation, market analyses, broadband, correlation, dsl technology.}

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\let\tabcellsep& 	 	 		 
\section[{I. Introduction}]{I. Introduction}\par
n this chapter we describe the process of ex ante regulation (also regulation) starting with general description of the process. This chapter also includes the description of Access relevant markets (also markets) recommended by the European Commission. The aim of this chapter is to generally describe the process of "ex ante" regulation and the markets which were evaluated through our research. a) Description of "ex ante" regulation Ex ante regulation (also "regulation") is a specific sector regulation, necessary to solve competition problems in EU. It is done through market analyses process, where national regulators in every EU country define relevant geographic and product markets and check if there exists an SMP ("significant market power") operator. They impose remedies to that operator. The aim is to ensure effective competition on each relevant market. Typically the SMP operator was the national incumbent. The EU framework of the European Parliament and of the Council recommended following remedies to be imposed on SMP players to  
\section[{b) Access markets recommended by European Commission}]{b) Access markets recommended by European Commission}\par
EC (2007) defined two wholesale markets susceptible to ex ante regulation (based on three criteria test). The wholesale broadband access market comprises non-physical or virtual network access (based on copper or optical fibre) including "bit stream" access at fixed location. With bit stream access, the wholesale product of the incumbent DSL (Digital subscriber line) technology consists of transmission capacity, which allows new entrants to offer their own services to their customers. Bit stream access may also include "backhaul" services to carry traffic to higher layers in the DSL network, where the entrant already has a point of presence (Bouckaert and van Dijk, 2010). Regulation of optical Access (also: next generation Access) was mostly not included in the analyses, because only a few regulators have started with "ex ante" regulation in the recent past and "there is perceived uncertainty about consumers' willingness to pay for next-generation Internet access services, which raises deep reservations about the viability of the business case for optical Access" \hyperref[b13]{(Siciliani, 2010)}. 
\section[{II. Literature Review}]{II. Literature Review}\par
In this chapter we evaluate the literature review regarding imposing the different types of remedies to operators with significant market power. We start with description of measuring the intensity of remedies and then we evaluate the difference between price control remedies as the most commonly used remedies. We end the chapter with the proposed ranking of remedies which was used later in our analyses. 
\section[{a) Description of the intensity of "ex ante" regulation}]{a) Description of the intensity of "ex ante" regulation}\par
In this chapter we describe the possible ways of measuring the intensity of regulation. The intensity of regulation was measured by the percentage of MDSs (main distribution frames) with competitors present regulated technology \hyperref[b5]{(Höffler 2005)} or the number of local loop unbundling lines compared to the number of all broadband lines on the market (Koutrumpis 2009). The methods have more disadvantages because they did not include all the effects of regulation on the market, like quantity or effects of bit stream regulation. The method which is measuring the market share of incumbent on the regulated technology shows us the level of competition and in some way the effectiveness of regulation. The disadvantage of such measures is also that we can't compare directly the work of regulators with the results on the market and especially we could not separately check only ex ante regulation or the remedies which are imposed by means of ex ante regulation. It is impossible to check the effects of different remedies on the customer welfare and investment initiatives. This is valid also for other above mentioned methods. The evaluation of effects by imposing different level of obligations, especially the most intensive way of regulation (LRIC model) was the goal of our later research. So the ranking of remedies should have followed the principle, which the regulators were using in imposing the remedies. The importance of market share of incumbent and consequently the intensity of regulation in correlation with the market size was emphasized by \hyperref[b12]{Symeou (2009)}, who confirmed the importance of specific regulation in small economies. 
\section[{b) Comparison of different price control remedies imposed by regulators}]{b) Comparison of different price control remedies imposed by regulators}\par
This chapter we evaluated the literature review regarding imposing the different types of remedies to potential SMP players. It includes the comparison of cost based and retail minus remedies as price control remedies. The other proposed remedies, like transparency, non-discrimination and Access obligation described in chapter 1.1 represent mostly only a threat to the regulated operator and they don't have really a strong influence on the behaviour of the regulated operator. If we really want to influence the market, one of the price control remedies must be imposed. Retail minus regulation remedy avoids foreclosure and leads to better results than cost-based regulation in terms of investment level and consumer surplus. Retail minus regulation allows a higher consumer surplus than deregulation and cost based regulation of access price as long as the regulator carefully defines the retail minus instruments  {\ref (Brandão and Sarmento, 2007)}. If the regulator carefully defines the margin between retail and access (wholesale) prices, with retail minus regulation it is possible to achieve better results than either with deregulation or cost-based regulation, in terms of protection of downstream competition and consumer surplus. The concept of cost-based regulation adopted by many telecommunication regulators is the Long Run Incremental Costs (LRIC). The implementation of LRIC involves the quantification of the incremental cost of providing access in a forward-looking perspective. With this perspective it is necessary to consider the substitution costs of the assets that will be supported in the future. This is in contrast to historic cost accounting. Several problems can be indicated, when using LRIC model. The precise quantification of LRIC model raises many questions, namely concerning the allocation of common costs and the process of gathering the necessary information to compute appropriate replacement costs  {\ref (Mason and Valletti, 2001)}. \hyperref[b0]{Evans and Guthrie (2003)} suggested to regulators to use the concept of optimized deprival value, which takes into account the existing value of equipment and also the demand risk. It is necessary to take into calculation also the spare capacities in which the regulated operator invested. The efficiency of regulation must be evaluated by means of investment initiatives and also the customer welfare. It is necessary to find the maximum relation between the level of investments and prices for end users \hyperref[b10]{(Mihevc 2009)}. The investments must be distributed among operators equally and the prices for end users low as possible. The concept of LRIC mostly does not take into the consideration neither the irreversible nature of many telecommunications investments, nor costs with the development of new services that did not succeed in the market. LRIC model adopted by some European countries discourages investment in fixed networks by the incumbent firms, because they anticipate that they will be required to offer access at cost-based prices (Cave and Prosperetti, 2001). LRIC model also has a poor performance in terms of dynamic efficiency of cost-based regulation because firms do not have the incentive to innovate if they know that they will be required to offer access to their rivals at cost-based prices. 
\section[{c) Ranking of remedies}]{c) Ranking of remedies}\par
After the description of different types of remedies and analyse it through literature review we need to commit the proper ranking of remedies, which was the basis for our research. The influence of imposed remedies by regulators could be measured by the ranking of imposed remedies by regulators and its influence on other parameters on the market \hyperref[b11]{(Mihevc 2011}). If some regulator did not complete the analyses or did not impose any obligation to the incumbent then its ranking is 1. If the regulator did not impose any of the price control remedies then its ranking is 2. The possible non price controls are transparency, non-discrimination and access obligation. Those remedies allow a lot of freedom to incumbent regarding setting its wholesale prices. Obligation of retail minus only imposes the difference between retail and wholesale price to the incumbent operator. So it allows still some freedom to the incumbent regarding setting its wholesale prices. 
\section[{The last and most intensive regulation is cost based}]{The last and most intensive regulation is cost based} 
\section[{Global Journal of Management and Business Research}]{Global Journal of Management and Business Research}\par
Volume XV Issue V Version I Year ( ) regulation. It is divided in two groups, one for cost based regulation which is based on the actual network of the SMP player and the most intensive regulation which is based on the optimal network, built now and with current prices. The most intensive regulation is definitely based on imposed LRIC model, which is quite a common practice in EU, despite the fact that the network was built in the past. Summarized ranking is presented in Table \hyperref[tab_0]{1}.  
\section[{III. Research Methodology}]{III. Research Methodology}\par
The research methodology consists of three parts: case study of small national markets, quantitative analyse trough correlation matrix and critical analyse and synthesis of the facts. 
\section[{a) Case study of small national markets and conclusions based on case studies}]{a) Case study of small national markets and conclusions based on case studies}\par
In the first part, we evaluated the existing situation in some national small markets compare the situations on those markets as case study and came to some conclusion for specific markets or general. The countries under the observations are small EU countries, which adopted EU recommendation. We assumed that regulation in small countries should be different than in bigger countries. The economy of size definitely plays an important role in regulation process, especially in small economies where the growth and investment initiatives are limited. The observation period was from January 2008 till January 2010. The importance of incumbent is very high in small economies, where are specific limitations regarding infrastructure competition and competition development. From this purpose it was necessary to evaluate the process of market development in small economies and the existing process of regulation separately from bigger economies. It was not possible to do the quantitative analyse just for small economies, because of limited number of small countries in EU. The results of case studies showed us some specifics in small countries and it helped in critical analyse and synthesis of the facts to develop the final conclusions. 
\section[{b) Quantitative analyse trough correlations matrix}]{b) Quantitative analyse trough correlations matrix}\par
Qualitative analyse in second part was done based on the data of 27 European countries and Switzerland and Norway (total 29 countries), which implemented the Electronic Communications Law based on EU Directives irrespectively of their sizes for the period 2003-2010. We could define five level of regulation intensity as it is shown in table 1. The relevant data we got from EC Reports (2010) and ERG 2009 or CIA world factbook (regarding specific characteristics of the national markets). To get the answer on question how the increasing intensity of regulation from 1 to 5 influenced the other factors on the market, we needed to calculate the Pearson's coefficient. The result we got from SPSS 15 program. All the variables followed the normal distribution. We checked the correlations between the intensity of regulation and level of sector investments for electronic communications in GDP for 2008, level of penetration (measured by number of inhabitants using broadband Access compared to all inhabitants in a country), the level of penetration increase in the observation period (January 2008-January 2010), market share of incumbent in retail market and on regulated DSL technology, share of regulated technology among all existing Broadband technologies and the size of the national market (measured by mill. of inhabitants living in a national market). The data are valid for the beginning of the year 2010, except for investment level as mentioned. We took into the analyse only fixed Broadband, while mobile Broadband was not spread enough and it couldn't be compared to fixed one by means of coverage and speeds offering. 
\section[{c) Critical analyse and synthesis of the facts}]{c) Critical analyse and synthesis of the facts}\par
The critical analyse and synthesis of facts regarding correlation, case studies and the influence of intensity of regulation (especially the imposition of LRIC model as the highest level of intensity) on investments initiatives and customer welfare was done at the end. For the purpose of analyse, we evaluated the influence of intensity of regulation on the penetration growth taking into the consideration the size of the economy. We also checked the influence of the intensity of regulation on the other parameters. We summarized the above mentioned facts from quantitative analyse and the results of case studies, where we suggested the appropriate regulation strategies in small countries. The critical synthesis of the facts came from quantitative analyse and case studies, which influence on the intensity of regulation and especially on the regulation via LRIC model was done. It gave us the answer regarding the justification of using LRIC model and imposing it on the SMP player. 
\section[{IV. Results and Discussion}]{IV. Results and Discussion} 
\section[{a) Case studies}]{a) Case studies}\par
As mentioned in the literature review, Symeou (2009) emphasized that small economies maintain higher concentration levels after competition in all technologies. The countries included in table 2 are small sized countries in EU and they were used based on its size of population (under 4 million). The regulation on such market should not be too strong to discourage the incumbent to invest into new services. 
\section[{Source: EC, 2010}]{Source: EC, 2010}\par
Based on the case studies we could conclude that the best strategy of "ex ante" regulation could be the imposition of regulation, which does not limit the investments of incumbent and allow the development of competition on retail market on other side. Small operators must be allowed to compete especially on offering small speeds, while the higher speeds should be under the control of the incumbent which is investing into the access markets. Following that strategy we could ensure the development and increasing investments from the incumbent to build or upgrade the Access networks. Ex ante regulation should not be too strong to limit the incumbent in its investment activities.\par
On the other side it should allow and not limit service competition too much, because infrastructure competition based on high parallel investments is not convenient for small countries. The results of case studies shows us that using the strongest level of regulation is not convenient for small countries and that using the strongest level of regulation could harm the market more than in bigger economies. The results of correlations in the next section will additionally justify or not justify the using of the strongest level of regulation (LRIC model) in the regulation process. It is not possible because of small data and limited number of countries in EU. 
\section[{b) Quantitative analyse}]{b) Quantitative analyse}\par
It is crucial for our research to find the statistical correlations between the intensity of regulation and other characteristics of the market, as mentioned in the methodology. The results of case studies showed us that also smallness affects the imposed regulation. From this purpose it also necessary to check the correlations between the size of the national economy (measured in the number of population) and the market share of the regulated operator or regulated technology. Those elements are also very important in judging the appropriate intensity of regulation. We could summarize facts, which we got from correlation matrix based on sample of 29 countries regarding choosing the LRIC model as a regulation toll:\par
? We found significant statistical correlation between the size of the national market and market share of the leading operator on the regulated technology (r=-0,666**, , while the correlation between the intensity of local loop unbundling and level of penetration was also positive but not significant, ? Based on negative correlation between the intensity of regulation (including the length) and relative change of penetration, we could predict a negative curve between the Intensity of regulation and relative change of penetration. The curve could be inverse or linear with negative coefficient. Smaller economies had higher share of incumbent on the regulated technology and lower share of DSL technology among the all Access technologies. On the other side the intensity of regulation had a positive impact on the development of the regulated technology or market share of DSL technology among all the other technologies and had positive impact on the competition on the regulated technology. The market share of incumbent was decreasing with the intensity of regulation. We could assume that market share of incumbent on the regulated technology represented the intensity of regulation if we did not include the influence of infrastructure competition on the behaviour of incumbent regarding offering the Access to other operators.\par
The significant positive correlation between the GDP per capita and intensity of bit-stream regulation showed, that the rich countries had stronger regulation. This fact confirmed that deregulation had not started yet and the countries which joined EU earlier had been increasing the intensity of regulation trough time. This was additionally confirmed by the fact, that intensity of regulation had a positive impact on the level of penetration. There was a significant correlation between the intensity of bit-stream regulation and GDP per capita (r=0,436*, The relative change of penetration was statistically negatively correlated with the intensity of regulation. This fact proves that more the regulation was intensive less was the relative increase of penetration. Based on that fact and the fact that intensity of regulation was positively correlated with the level of penetration we could conclude that high intensity of regulation in EU leaded to high level of penetration, but also to a lower increase of penetration. EU market is at the stage where additional imposing of intensive regulation (especially LRIC model) would lead to a slower penetration increase or even no increase. Through two regression models between significantly correlated parameters intensity of regulation (including the length) and the relative change of penetration in the observation period from 2008 to 2010, we could get the point when positive increase turns into the negative one. We looked separately for the intensity of bit-stream regulation and local loop unbundling regulation, while both were significantly correlated. The regression models were constructed in such a manner, that we could explain 12, 9 \% and 19, 9 \% of relative change of penetration by the intensity of local loop unbundling and bit-stream intensity of regulation. We could assume linear regression model between the independent variable intensity of regulation and dependent variable relative change of penetration. Regression models showed following linear approximation (table 2 and 3 contain the regression coefficients): From this equation we calculated the point when positive increase turns into negative. For bit-stream regulation, it appeared at value of 
\section[{= I}]{= I}\par
. This figure means that on average if the market was regulated 5, 2 years by LRIC model, the relative increase of penetration would be 0. We could assume that intensity of bit stream regulation has strong influence on relative change of penetration. It was important to take into the consideration also the fact that richest countries were using stronger regulation. We calculated the break-even point at the value of 7 , 38 = I for local loop unbundling regulation. This meant that the influence of local loop unbundling had been much weaker. Size of the economy was not statistically significant correlated with the intensity of regulation, but for linear approximation we used the significant statistical correlation between the size of the national market and market share of incumbent on the regulated technology:847 , 0 * 005 , 0 + ? = v DSL\par
Where DSL meant the share of regulated incumbent on the regulated technology and v was measured in millions of inhabitants in a country. Smaller markets had higher share of incumbent. 
\section[{c) Critical analyse and synthesis of the facts}]{c) Critical analyse and synthesis of the facts}\par
Based on the fact that intensity of regulation had positive effect on the competition level on the regulated technology, we concluded that intensity of regulation could be also presented by the share of incumbent on the regulated technology. We had to 
\section[{Global Journal of Management and Business Research}]{Global Journal of Management and Business Research}\par
Volume XV Issue V Version I Year ( ) a. Dependent variable: relative change of penetration exclude the fact that open Access could be also influenced by infrastructure competition. This meant, that in case of high infrastructure competition, incumbent could be interested in opening its Access.\par
Less intensive regulation should have been imposed on smaller markets (negative correlation). This conclusion we could derive from the fact in previous chapter, that bigger economies had smaller market share of the incumbent on DSL technology That meant that small economies were more sensitive to regulation and less intensive regulation should have been imposed to achieve the same results regarding customer welfare and investment initiatives. From the perspective of relative change of penetration, we had to include in our calculations also the factor, which represented the size of the market. It is important to emphasize as mentioned in previous chapter, that it was no significant statistical correlation between the relative increase of penetration and share of incumbent on the regulated technology and the size of the economy, measured by the number of inhabitants on other side. More intensive regulation in small economies could reach the break-even point between positive and negative increase of penetration faster than in bigger economies.\par
To evaluate the influence of LRIC method, it was also important to check the correlations between the intensity of regulation and the initiative for investments, measured as the percentage of investments in Electronic Communications sector in GDP. Based on strong negative correlations, as mentioned in previous chapter between the size of the economy and the market share of the incumbent on the regulated technology and strong negative correlations between the intensity of regulation and the share of investments in GDP we could come to conclusion, that the strongest level of intensity of regulation had extremely negative influence on the level of investments, while incumbent was the most important actor on the market. Strong regulation had extremely negative impact on its investments. It is extremely important for small countries, where the market share of incumbent is very high.\par
For the purpose of evaluating LRIC model in small economies, it was necessary to take into the consideration also the correlation between the size of the economy and market share of the regulated technology. The correlation as mentioned in previous chapter showed that small economies in EU had smaller percentage of DSL technology among all the Access technologies. Intensive regulation (LRIC model) on that technology would have additional negative impact on investments initiatives of regulated operators, while DSL technology was the only regulated one.\par
Increasing intensity of regulation caused decreasing share of regulated operator on regulated technology. This was especially important in the period of NGN networks via optical Access. The implementation of optical Access was/is very expensive and the imposing of strong regulation on optical Access would additionally harm the initiatives for investments.\par
To summarize at the end, following facts were important to answer the main question in our research:\par
? The penetration growth was negatively correlated with the intensity of regulation (LRIC model is the most intensive way of regulation), ? Market share of incumbent on the regulated DSL technology as a key indicator of the regulation level was negatively correlated with the size of the market. This meant that regulation was very sensitive in small economies, where the market share of the incumbent od regulated technology was very high and regulated operator was the investment leader, ? The intensity of regulation was negatively correlated with the percentage of sector investments in GDP, ? The situation was additionally confirmed by the existing fact, that small economies had lower share of regulated technology, ? The only positive effect of intensity of regulation was that the intensity of regulation was positively correlated with the level of penetration reached in 2010, but this is/was out-weighted by the negative effects mentioned above.\par
LRIC Model is definitely in-appropriate model for the regulation of Access networks in small economies. It is in-appropriate from perspective of customer welfare and also the investment initiatives. It is also necessary to precisely evaluate the imposition of LRIC model in bigger economies. The above mentioned facts show also negative elements for all sized economies. 
\section[{V. Conclusion}]{V. Conclusion}\par
The final Conclusion was that ex ante regulation in EU should have been planned precisely not to decrease initiative for investments and customer welfare. Regulators all around EU should have taken the facts in this article into their decisions and not use LRIC model too often, especially in Access regulation. The results in this article showed the negative impact of LRIC regulation on initiative for investments and relative increase of penetration. This was especially obvious in case of small economies, where the incumbent market share was very high on the regulated technology and the development of infrastructure competition was/is mostly economically not justified. The correlation in EU also showed that the share of regulated DSL technology was lower in smaller countries. This correlation showed that other Access technologies were also developed and regulation via LRIC model would additionally hamper the incumbent, who built the DSL technology to access the end users. On the other hand intensity of regulation also had negative impact on penetration growth. All those facts confirmed that regulation of Access via LRIC model was/is not appropriate in small\begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-2.png}
\caption{\label{fig_0}}\end{figure}
   \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.8033536585365854\textwidth}P{0.046646341463414634\textwidth}}
Remedy\tabcellsep Rank\\
No regulation\tabcellsep 1\\
Remedies except cost price control\tabcellsep 2\\
Price control with the retail minus remedy\tabcellsep 3\\
Cost based prices (FDC ?) except LRIC model\tabcellsep 4\\
LRIC, LRAIC model\tabcellsep 5\end{longtable} \par
 
\caption{\label{tab_0}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.02992299229922992\textwidth}P{0.4137788778877888\textwidth}P{0.40629812981298125\textwidth}}
Country\tabcellsep Specifics\tabcellsep General conclusions\\
Cyprus\tabcellsep Low infrastructure competition\tabcellsep Regulations should not be too\\
\tabcellsep High market share of incumbent\tabcellsep strong and should allow incumbent\\
\tabcellsep Low Broadband speeds\tabcellsep as the market driver to invest.\\
Luxemburg\tabcellsep High penetration rate\tabcellsep Appropriate regulation for small\\
\tabcellsep High market share of incumbent\tabcellsep markets. It is necessary only to\\
\tabcellsep Soft regulation\tabcellsep improve the share of high\\
\tabcellsep \tabcellsep bandwidths (retail minus approach\\
\tabcellsep \tabcellsep is recommended)\\
Ireland\tabcellsep Strong regulation (local loop\tabcellsep Regulation should be a little bit\\
\tabcellsep unbundling)\tabcellsep weaker (LLU) to encourage the\\
\tabcellsep Quite low penetration (high GDP per\tabcellsep incumbent to invest in this relatively\\
\tabcellsep capita),\tabcellsep small market.\\
\tabcellsep Low share of high bandwidths\tabcellsep \\
\tabcellsep High market share of mobile internet\tabcellsep \\
Latvia\tabcellsep Low penetration level\tabcellsep Necessary to impose the\\
\tabcellsep Quite high share of high bandwidths\tabcellsep appropriate model of regulation\\
\tabcellsep High infrastructure competition\tabcellsep (High infrastructure competition\\
\tabcellsep Lack of regulation\tabcellsep might not be the right solution for\\
\tabcellsep \tabcellsep small countries)\\
Malta\tabcellsep High penetration level\tabcellsep Soft ex ante regulation on both\\
\tabcellsep Two infrastructures (cable and DSL)/\tabcellsep infrastructures should also be in\\
\tabcellsep market share divided by those two.\tabcellsep place, while duopoly might have\\
\tabcellsep High share of high bandwidths\tabcellsep negative effect in the future.\\
\tabcellsep Soft regulation\tabcellsep \\
Estonia\tabcellsep High penetration level\tabcellsep Regulation is still necessary, but it\\
\tabcellsep High infrastructure competition\tabcellsep must be carefully planned, because\\
\tabcellsep Low service competition\tabcellsep of high infrastructure competition\\
Lithuania\tabcellsep Low penetration rate\tabcellsep Ex ante regulation is still necessary\\
\tabcellsep High share of high bandwidths\tabcellsep especially in bit stream regulation,\\
\tabcellsep High infrastructure competition and\tabcellsep where regulator was not active till\\
\tabcellsep low service competition\tabcellsep now to increase the penetration.\\
Slovenia\tabcellsep High infrastructure competition\tabcellsep \\
\tabcellsep Quite low market share of incumbent\tabcellsep \\
\tabcellsep Penetration rate is not high\tabcellsep \\
\tabcellsep High bandwidths below the EU\tabcellsep \\
\tabcellsep average\tabcellsep \\
\tabcellsep Strong regulation (also fibre)\tabcellsep \end{longtable} \par
 
\caption{\label{tab_1}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.4231111111111111\textwidth}P{0.12088888888888888\textwidth}P{0.068\textwidth}P{0.01888888888888889\textwidth}P{0.056666666666666664\textwidth}P{0.0037777777777777775\textwidth}P{0.034\textwidth}P{0.02266666666666667\textwidth}P{0.011333333333333334\textwidth}P{0.03022222222222222\textwidth}P{0.041555555555555554\textwidth}P{0.01888888888888889\textwidth}}
Model/ bit-stream\tabcellsep Unstandardized\tabcellsep \multicolumn{2}{l}{Std.}\tabcellsep \multicolumn{6}{l}{Standardized}\tabcellsep t\tabcellsep ?\\
\tabcellsep Beta\tabcellsep \multicolumn{2}{l}{Error}\tabcellsep \tabcellsep \tabcellsep \multicolumn{4}{l}{Beta (r)}\\
Constant\tabcellsep ,494\tabcellsep \multicolumn{2}{l}{,079}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 6,291\tabcellsep ,000\\
Intensity of regulation\tabcellsep -,019\tabcellsep \multicolumn{2}{l}{,007}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{3}{l}{-,479}\tabcellsep -2,730\tabcellsep ,011\\
(bitstream)\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{a. Dependent variable: relative change of penetration}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep ? p p\tabcellsep =\tabcellsep , 0 ?\tabcellsep 019\tabcellsep *\tabcellsep I\tabcellsep +\tabcellsep , 0\tabcellsep 494\end{longtable} \par
 
\caption{\label{tab_2}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.4910472972972973\textwidth}P{0.07753378378378378\textwidth}P{0.0028716216216216218\textwidth}P{0.01722972972972973\textwidth}P{0.028716216216216218\textwidth}P{0.05168918918918919\textwidth}P{0.014358108108108109\textwidth}P{0.04307432432432433\textwidth}P{0.0028716216216216218\textwidth}P{0.05456081081081081\textwidth}P{0.03445945945945946\textwidth}P{0.022972972972972974\textwidth}P{0.008614864864864865\textwidth}}
Model/ local loop\tabcellsep \multicolumn{2}{l}{Unstandardized}\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Std.}\tabcellsep \multicolumn{3}{l}{Standardized}\tabcellsep t\tabcellsep ?\\
unbundling\tabcellsep Beta\tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Error}\tabcellsep \tabcellsep \tabcellsep Beta (r)\\
Constant\tabcellsep ,464\tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{,081}\tabcellsep \tabcellsep \tabcellsep 5,691\tabcellsep ,000\\
Intensity of regulation\tabcellsep -,012\tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{,005}\tabcellsep \tabcellsep \tabcellsep -,403\tabcellsep -2,204\tabcellsep ,037\\
(local loop\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
unbundling)\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{? p p}\tabcellsep =\tabcellsep , 0 ?\tabcellsep 012\tabcellsep *\tabcellsep I\tabcellsep +\tabcellsep , 0\tabcellsep 464\\
\multicolumn{7}{l}{The risk to accept this relation was very low,}\tabcellsep \tabcellsep \\
\multicolumn{2}{l}{especially in case of Bit stream regulation (}\tabcellsep ?\tabcellsep =\tabcellsep \multicolumn{3}{l}{). 011 , 0}\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_3}Table 4 :}\end{figure}
 			\footnote{© 2015 Global Journals Inc. (US) 1} 			\footnote{© 2015 Global Journals Inc. (US)} 			\footnote{© 2015 Global Journals Inc. (US)to do the separate analyse for big and small economies,} 		 		\backmatter  			 \par
sized economies, but also showed negative impacts, which regulators should have taken into the account, when imposing remedies in economically bigger countries.. As mentioned retail minus regulation allows a higher consumer surplus than deregulation and cost based regulation of access price as long as the regulator carefully defines the retail minus instruments (Brandão and Sarmento, 2007). Cost based regulation was defined in article mostly as LRIC model, based on incremental costs.  {\ref Mason and Valletti (2001)} emphasized, that the precise quantification of LRIC model raised many questions, namely concerning the allocation of common costs and the process of gathering the necessary information to compute appropriate replacement costs necessary to build the model. Cave and Prosperetti (2001) also found out that LRIC model adopted by some European countries discourages investment in fixed networks by the incumbent firms, because they anticipate that they will be required to offer access at cost-based prices. All those authors in the past pointed out the negative effects of LRIC model-, but no analyse was done based on facts through the regulation process on Access markets and comparison the intensity of regulation with other parameters on the market to prove or not to prove the economically justified usage of LRIC model or any other model of regulation used by regulators. So the analyse in this article proved, that conclusions of the authors in the past were valid also for Access markets and especially for economically small national markets. Additionally, this article proved, based on quantitative analyse and case studies the conclusions of previous authors and pointed out all the negative effects of using LRIC model in EU market.  
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