analysis about the efficiency changes and influencing factors of the fourth telecommunications refor

1、<p>　　Analysis about the Efficiency Changes and Influencing Factors of the Fourth Telecommunications Refor</p><p>　　Abstract. The telecommunications reform in 2008 has formed a new business operation wi

2、th market competition， having a far-reaching impact on the telecommunications industry. The efficiency of the telecommunications industry is a key factor in the quantitative evaluation of the reform. Based on the super-e

3、fficient DEA and Malmquist Index， this paper analysis the changes in efficiency of the telecommunications industry of Chinese provinces and regions from 2003 to 2010， and established the Tobit r</p><p>　　Key

4、 words： Data envelopment analysis； Super efficiency DEA； Malmquist Index； The efficiency of the telecommunications industry； Influencing factors </p><p>　　1 Introduction </p><p>　　In May 2008， t

5、he Ministry of Industry and Information Technology， National Development and Reform Commission， Ministry of Finance issued the Circular on deepening the reform of the telecommunications system to encourage China Telecom

6、acquired China Unicom's CDMA network， China Unicom merged with China Netcom， China Satcom basic telecom business into China Telecom， China Railcom into China Mobile， reform， restructuring and the issuance of third ge

7、neration mobile communication 3G licenses in the c</p><p>　　This paper attempts to expand from the following two aspects of existing literature： （1） Does it occur a marked change of the telecommunication eff

8、iciency after the fourth reform？ （2） How do the regulatory factors affect this change？ Based on this， this article adopts the 2003-2010 inter-provincial panel data empirical research on the efficiency of China's tele

9、com industry， to combine the exceed efficiency of DEA and Malmquist Index together to evaluate the efficiency of China's telecommunicatio</p><p>　　2.1 Model </p><p>　　2.1.1 The Super-Efficie

10、nt DEA Model </p><p>　　When the CCR model is in the calculation of the efficiency value， the calculated results are often many efficient DMU； it cannot be compared among the effective DMU efficiency values.

11、To compensate for this deficiency， Andersen and Peterson （1993） proposed a super-efficient （the Super-Efficiency） DEA model for efficient evaluation of DMU j0， excluded from the reference set of DMU. For the DEA efficien

12、t DMU j0 （efficiency rating is 1）， ultra-efficient model will be the production frontier to re-c</p><p>　　2.1.2 Malmquist Index Model </p><p>　　Usually it takes the total factor productivity gro

13、wth （TFPG） index to measure the dynamic efficiency of the industry changes. The Malmquist Index model in the analysis of the process of consumption by Malmquist （1953）， Fare et al （1992） on this basis， the use of DEA met

14、hod constructs a Malmquist productivity index. Malmquist index can analyze the different DMU to measure the change of where the production set， as well as understand the relative efficiency of a DMU in the production set

15、. </p><p>　　The Malmquist total factor productivity index calculates the two Malmquist index by taking the geometric means for different periods， and it can be decomposed for the technical efficiency change

16、（Efficient ， Effch） and technical progress changes （Technology Change， Tech）： </p><p>　　2.1.3 Two-stage Tobit Model </p><p>　　In order to assess and measure the environmental factors which affec

17、ted the DEA efficiency values， as well as the degree of impact， Coelli et al. （1998） proposed a two-stage method： The first stage DEA model's efficiency value of DMU measure； the second phase of the efficiency values

18、 （dependent variable） on various environmental factors （explanatory variables cannot be the first step in the input， output indicators） regression coefficient determine the environmental factors and the explanatory v<

19、/p><p>　　In essence， it is usually on the efficiency of the telecommunications industry that the input variables belong to a proxy variable for capital and labor inputs， the output variables are proxy variables

20、 of the volume of business and income-generating. </p><p>　　In this paper， to take the capital （investment in fixed assets） and labor （Employed Persons） as input variables to the telecom business volume and

21、the main telecom business revenue as the output variable， to measure the integrated production efficiency. According to data availability and integrity of principle， we have chosen 2003-2010 at the provincial level panel

22、 data. Data in addition to the number of workers in the telecommunications industry from 11 20 04 - 20 "China Statistical Yearbook"， </p><p>　　3 The Empirical Results and Analysis </p><p

23、>　　3.1 Analysis of technical efficiency </p><p>　　As the DEA analysis of the obtained efficiency value of the relative efficiency indicators， directly each DMU annual input of the input-output data for an

24、alysis， only get the DMU efficiency compared with the effective frontier derived value， but because each year the effective frontier different， it will result in the efficiency values of different years are not comparabl

25、e. </p><p>　　In this paper， EMS1.3 software is used to solve the model. Table 1 shows the technical efficiency of the provinces and autonomous regions in the year 2003 to 2010. </p><p>　　Table 1

26、. Technical efficiency （TE） value in different provinces and regions of 2003-2010 </p><p>　　Table 2. 2003-2010 National and district average technical efficiency </p><p>　　Table 3 has decomposed

27、 the TE further into pure technical efficiency （Pure Technical Efficiency， PE） and scale efficiency of the Scale Efficiency （SE）. </p><p>　　Table 3. 2003-2010 Average value and decomposition of technical eff

28、iciency </p><p>　　3.2 Dynamic efficiency analysis </p><p>　　In 2004-2007， before the fourth telecommunications reform， the changes of Effch are basically a positive contribution to the TFP growt

29、h. But in 2008-2010， after the reform， the Effch continued to improve. Further decomposed into the Pech and the Sech， 2009 Pech have significantly improved， an increase of 5.6% and 5.7% in 2009 and 2010， respectively； Se

30、ch in 2009 after a slight decrease， the former shows that the restructuring is conducive to operations providers engaged in the improvement of the</p><p>　　3.3 Regulatory impact factor of the Tobit model <

31、;/p><p>　　In order to investigate the impact of regulation on the efficiency of China's telecommunications industry， this paper learns from the literature， and combines with the preceding research results a

32、nd China's telecommunications industry development status and study from several angles： </p><p>　　3.3.1 Market Concentration </p><p>　　Lien and Peng （2001） and Tsai， et al. （2006） found tha

33、t telecom operators will become more efficient in the face of competition， so the intensity of competition is related to the efficiency of the operators. </p><p>　　Hypothesis H1： Market concentration is nega

34、tively correlated with the efficiency of the telecommunications industry. </p><p>　　3.3.2 Move the Effect of Fixed Alternative （Fixed-Mobile Substitution， FMS） </p><p>　　FMS refers to the develo

35、pment and popularization of mobile communication， consumer was an increasing trend of using mobile communication to abandon the fixed communication trends. Higher the FMS effect generally means the mobile and fixed telep

36、hony penetration rate of the region are higher. </p><p>　　Assumption H2： FMS effect is related to the efficiency of the telecommunications industry. </p><p>　　3.3.3 Launch of 3G </p><

37、p>　　In 2008-2009， the Chinese telecom operators for 3G "arms race." After the telecom restructuring in 2008， several major operators invested heavily in 3G network construction. Over the years has been relat

38、ively stable in the telecommunications industry employment and investment in fixed assets increased significantly. </p><p>　　Assumption H3： The 3G start-up will reduce the efficiency of the telecommunication

39、s industry in 2008-2009. </p><p>　　3.3.4 Regional Differences </p><p>　　Regional economic and population density will have a direct impact on the local telecommunications industry efficiency， th

40、e efficiency of the eastern， central and western telecommunications declines in turn. </p><p>　　Hypothesis H4： Eastern part of the telecommunications industry is more efficient than central and western regio

41、ns. </p><p>　　Based on the above assumptions， the Tobit regression model： </p><p>　　4 Conclusions and Policy Recommendations </p><p>　　Based on the 2003-2010 inter-provincial panel

42、data， this paper use the DEA method to take a comprehensive evaluation and empirical analysis of the efficiency of China's telecommunications industry， focusing on the efficiency of China's telecommunications ind

43、ustry before and after telecommunications reform trend， the Tobit model on which regulatory factors affecting the measurement test， conclusions and policy recommendations are as follows： 　　Firstly， it can be seen that t

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