doi: 10.3934/dcdss.2019053

Total factor productivity growth and technological change in the telecommunications industry

School of Economics and Management, Beijing University of Posts and Telecommunications, No.10 Xi Tu Cheng Road, Haidian District, Beijing 100876, China

* Corresponding author: Xuchen Lin

Received  July 2017 Revised  January 2018 Published  November 2018

The fast growing telecommunications industry in China has been experiencing dramatic technological change and substantial productivity growth. The actual productivity growth pattern in the sector, however, need to be empirically examined. In this paper, using input and output data at the provincial level, we employ DEA-based Malmquist productivity index to estimate productivity change, technological change and relative efficiency change in China's telecommunications industry for the period spanning the years from 2011 to 2015. The results show that based on our sample, the productivity improved by 22.9% per annum, which was exclusively due to an average of 25.5% technological progress in the industry production function, while the average efficiency change is slightly negative. Our results also indicate that regions with relatively low levels of telecommunications (and economic) development have a greater chance and ability of enhancing telecommunications productivity growth through technological catch-up. In addition, we find that the industry experienced significantly higher productivity growth and technological progress in the later sample period between 2013 and 2015 than in the early period between 2011 and 2013.

Citation: Xuchen Lin, Ting-Jie Lu, Xia Chen. Total factor productivity growth and technological change in the telecommunications industry. Discrete & Continuous Dynamical Systems - S, doi: 10.3934/dcdss.2019053
References:
[1]

M. Abramovitz, Resource and output trends in the united states since 1870, in Resource and Output Trends in the United States Since 1870, NBER, 1956, 1–23.

[2]

R. D. BankerZ. CaoN. Menon and R. Natarajan, Technological progress and productivity growth in the us mobile telecommunications industry, Annals of Operations Research, 173 (2010), 77-87.

[3]

M. CalvoJ. I. M. Torcal and L. R. García, A new stepsize change technique for adams methods, Applied Mathematics and Nonlinear Sciences, 1 (2016), 547-558.

[4]

D. W. Caves, L. R. Christensen and W. E. Diewert, The economic theory of index numbers and the measurement of input, output, and productivity, Econometrica: Journal of the Econometric Society, 1393–1414.

[5]

A. CharnesW. W. Cooper and E. Rhodes, Measuring the efficiency of decision making units, European Journal of Operational Research, 2 (1978), 429-444. doi: 10.1016/0377-2217(78)90138-8.

[6]

H. W. Chesbrough and D. J. Teece, When is virtual virtuous, Harvard Business Review, 74 (1996), 65-73.

[7]

T. Coelli, A guide to deap version 2.1: A data envelopment analysis (computer) program, Centre for Efficiency and Productivity Analysis, University of New England, Australia.

[8]

L. Correa, The economic impact of telecommunications diffusion on uk productivity growth, Information Economics and Policy, 18 (2006), 385-404.

[9]

A. Datta and S. Agarwal, Telecommunications and economic growth: A panel data approach, Applied Economics, 36 (2004), 1649-1654.

[10]

M. Denny, M. A. Fuss and L. Waverman, The Measurement and Interpretation of Total Factor Productivity in Regulated Industries, with an Application to Canadian Telecommunications, Institute for Policy Analysis, University of Toronto, 1979.

[11]

W. E. Diewert, Exact and superlative index numbers, Journal of Econometrics, 4 (1976), 115-145. doi: 10.1016/0304-4076(76)90009-9.

[12]

A. Dutta, Telecommunications and economic activity: An analysis of granger causality, Journal of Management Information Systems, 17 (2001), 71-95.

[13]

R. Färe and S. Grosskopf, Malmquist productivity indexes and fisher ideal indexes, The Economic Journal, 102 (1992), 158-160.

[14]

R. FäreS. GrosskopfM. Norris and Z. Zhang, Productivity growth, technical progress, and efficiency change in industrialized countries, The American economic review, (), 66-83.

[15]

R. FäreS. Grosskopf and P. Roos, Productivity and quality changes in swedish pharmacies, International Journal of Production Economics, 39 (1995), 137-144.

[16]

Y. GaoM. Farahani and W. Gao, Ontology optimization tactics via distance calculating, Applied Mathematics and Nonlinear Sciences, 1 (2016), 154-169.

[17]

D. I. Giokas and G. C. Pentzaropoulos, Evaluating productive efficiency in telecommunications: Evidence from greece, Telecommunications Policy, 24 (2000), 781-794.

[18]

J. A. Hausman and W. E. Taylor, Partial deregulation in telecommunications: An update, Journal of Competition Law and Economics.

[19]

E. Hisali and B. Yawe, Total factor productivity growth in uganda's telecommunications industry, Telecommunications Policy, 35 (2011), 12-19.

[20]

H. Kang, Technology management in services: Knowledge-based vs. knowledge-embedded services, Strategic Change, 15 (2006), 67-74.

[21]

F. Kiss, Productivity gains in bell canada, Economic Analysis of Telecommunications: Theory and Applications, Amsterdam: North-Holland.

[22]

J.-J. Laffont and J. Tirole, Competition in Telecommunications, MIT press, 2001.

[23]

P. LallA. M. Featherstone and D. W. Norman, Productivity growth in the western hemisphere (1978-94): The caribbean in perspective, Journal of Productivity Analysis, 17 (2002), 213-231.

[24]

P.-L. Lam and T. Lam, Total factor productivity measures for hong kong telephone, Telecommunications Policy, 29 (2005), 53-68.

[25]

P.-L. Lam and A. Shiu, Productivity analysis of the telecommunications sector in China, Telecommunications Policy, 32 (2008), 559-571.

[26]

D. Lien and Y. Peng, Competition and production efficiency: Telecommunications in oecd countries, Information Economics and Policy, 13 (2001), 51-76.

[27]

G. Madden and S. J. Savage, Telecommunications productivity, catch-up and innovation, Telecommunications Policy, 23 (1999), 65-81.

[28]

S. K. Majumdar, Does new technology adoption pay? electronic switching patterns and firm-level performance in us telecommunications, Research Policy, 24 (1995), 803-822.

[29]

S. Malmquist, Index numbers and indifference surfaces, Trabajos de Estadística, 4 (1953), 209-242. doi: 10.1007/BF03006863.

[30]

MIIT, Statistical bulletin of china's telecommunications industry in 2016, http://www.miit.gov.cn/n1146290/n1146402/n1146455/c5471508/content.html.

[31]

M. I. Nadiri and M. Schankerman, The structure of production, technological change, and the rate of growth of total factor productivity in the bell system, 1979.

[32]

M. Nishimizu and J. M. Page, Total factor productivity growth, technological progress and technical efficiency change: dimensions of productivity change in yugoslavia, 1965-78, The Economic Journal, 92 (1982), 920–936.

[33]

H. OnikiT. H. OumR. Stevenson and Y. Zhang, The productivity effects of the liberalization of japanese telecommunication policy, Journal of Productivity Analysis, 5 (1994), 63-79.

[34]

J. B. Quinn and M. N. Baily, Information technology: Increasing productivity in services, The Academy of Management Executive, 8 (1994), 28-48.

[35]

R. W. Shepherd, Theory of Cost and Production Functions, Princeton University Press, 1970.

[36]

N. D. Uri, Measuring productivity change in telecommunications, Telecommunications Policy, 24 (2000), 439-452.

[37]

N. D. Uri, Productivity change, technical progress, and efficiency improvement in telecommunications, Review of Industrial Organization, 18 (2001), 283-300.

[38]

C.-H. Yoon, Liberalisation policy, industry structure and productivity changes in korea's telecommunications industry, Telecommunications Policy, 23 (1999), 289-306.

show all references

References:
[1]

M. Abramovitz, Resource and output trends in the united states since 1870, in Resource and Output Trends in the United States Since 1870, NBER, 1956, 1–23.

[2]

R. D. BankerZ. CaoN. Menon and R. Natarajan, Technological progress and productivity growth in the us mobile telecommunications industry, Annals of Operations Research, 173 (2010), 77-87.

[3]

M. CalvoJ. I. M. Torcal and L. R. García, A new stepsize change technique for adams methods, Applied Mathematics and Nonlinear Sciences, 1 (2016), 547-558.

[4]

D. W. Caves, L. R. Christensen and W. E. Diewert, The economic theory of index numbers and the measurement of input, output, and productivity, Econometrica: Journal of the Econometric Society, 1393–1414.

[5]

A. CharnesW. W. Cooper and E. Rhodes, Measuring the efficiency of decision making units, European Journal of Operational Research, 2 (1978), 429-444. doi: 10.1016/0377-2217(78)90138-8.

[6]

H. W. Chesbrough and D. J. Teece, When is virtual virtuous, Harvard Business Review, 74 (1996), 65-73.

[7]

T. Coelli, A guide to deap version 2.1: A data envelopment analysis (computer) program, Centre for Efficiency and Productivity Analysis, University of New England, Australia.

[8]

L. Correa, The economic impact of telecommunications diffusion on uk productivity growth, Information Economics and Policy, 18 (2006), 385-404.

[9]

A. Datta and S. Agarwal, Telecommunications and economic growth: A panel data approach, Applied Economics, 36 (2004), 1649-1654.

[10]

M. Denny, M. A. Fuss and L. Waverman, The Measurement and Interpretation of Total Factor Productivity in Regulated Industries, with an Application to Canadian Telecommunications, Institute for Policy Analysis, University of Toronto, 1979.

[11]

W. E. Diewert, Exact and superlative index numbers, Journal of Econometrics, 4 (1976), 115-145. doi: 10.1016/0304-4076(76)90009-9.

[12]

A. Dutta, Telecommunications and economic activity: An analysis of granger causality, Journal of Management Information Systems, 17 (2001), 71-95.

[13]

R. Färe and S. Grosskopf, Malmquist productivity indexes and fisher ideal indexes, The Economic Journal, 102 (1992), 158-160.

[14]

R. FäreS. GrosskopfM. Norris and Z. Zhang, Productivity growth, technical progress, and efficiency change in industrialized countries, The American economic review, (), 66-83.

[15]

R. FäreS. Grosskopf and P. Roos, Productivity and quality changes in swedish pharmacies, International Journal of Production Economics, 39 (1995), 137-144.

[16]

Y. GaoM. Farahani and W. Gao, Ontology optimization tactics via distance calculating, Applied Mathematics and Nonlinear Sciences, 1 (2016), 154-169.

[17]

D. I. Giokas and G. C. Pentzaropoulos, Evaluating productive efficiency in telecommunications: Evidence from greece, Telecommunications Policy, 24 (2000), 781-794.

[18]

J. A. Hausman and W. E. Taylor, Partial deregulation in telecommunications: An update, Journal of Competition Law and Economics.

[19]

E. Hisali and B. Yawe, Total factor productivity growth in uganda's telecommunications industry, Telecommunications Policy, 35 (2011), 12-19.

[20]

H. Kang, Technology management in services: Knowledge-based vs. knowledge-embedded services, Strategic Change, 15 (2006), 67-74.

[21]

F. Kiss, Productivity gains in bell canada, Economic Analysis of Telecommunications: Theory and Applications, Amsterdam: North-Holland.

[22]

J.-J. Laffont and J. Tirole, Competition in Telecommunications, MIT press, 2001.

[23]

P. LallA. M. Featherstone and D. W. Norman, Productivity growth in the western hemisphere (1978-94): The caribbean in perspective, Journal of Productivity Analysis, 17 (2002), 213-231.

[24]

P.-L. Lam and T. Lam, Total factor productivity measures for hong kong telephone, Telecommunications Policy, 29 (2005), 53-68.

[25]

P.-L. Lam and A. Shiu, Productivity analysis of the telecommunications sector in China, Telecommunications Policy, 32 (2008), 559-571.

[26]

D. Lien and Y. Peng, Competition and production efficiency: Telecommunications in oecd countries, Information Economics and Policy, 13 (2001), 51-76.

[27]

G. Madden and S. J. Savage, Telecommunications productivity, catch-up and innovation, Telecommunications Policy, 23 (1999), 65-81.

[28]

S. K. Majumdar, Does new technology adoption pay? electronic switching patterns and firm-level performance in us telecommunications, Research Policy, 24 (1995), 803-822.

[29]

S. Malmquist, Index numbers and indifference surfaces, Trabajos de Estadística, 4 (1953), 209-242. doi: 10.1007/BF03006863.

[30]

MIIT, Statistical bulletin of china's telecommunications industry in 2016, http://www.miit.gov.cn/n1146290/n1146402/n1146455/c5471508/content.html.

[31]

M. I. Nadiri and M. Schankerman, The structure of production, technological change, and the rate of growth of total factor productivity in the bell system, 1979.

[32]

M. Nishimizu and J. M. Page, Total factor productivity growth, technological progress and technical efficiency change: dimensions of productivity change in yugoslavia, 1965-78, The Economic Journal, 92 (1982), 920–936.

[33]

H. OnikiT. H. OumR. Stevenson and Y. Zhang, The productivity effects of the liberalization of japanese telecommunication policy, Journal of Productivity Analysis, 5 (1994), 63-79.

[34]

J. B. Quinn and M. N. Baily, Information technology: Increasing productivity in services, The Academy of Management Executive, 8 (1994), 28-48.

[35]

R. W. Shepherd, Theory of Cost and Production Functions, Princeton University Press, 1970.

[36]

N. D. Uri, Measuring productivity change in telecommunications, Telecommunications Policy, 24 (2000), 439-452.

[37]

N. D. Uri, Productivity change, technical progress, and efficiency improvement in telecommunications, Review of Industrial Organization, 18 (2001), 283-300.

[38]

C.-H. Yoon, Liberalisation policy, industry structure and productivity changes in korea's telecommunications industry, Telecommunications Policy, 23 (1999), 289-306.

Figure 1.  Malmquist TFP index trend versus technological change and efficiency change during 2011 to 2015
Table 1.  Operating environments of 31 DMUs in 2015
DMUGRP
(billion yuan)
Population
(million)
Per capita GRP(yuan)Pr1Pr2Pr3
Eastern region
Beijing230121.710600936.2181.776.5
Tianjin165415.57617822.288.563
Liaoning286743.813205423.797.962.2
Shanghai251224.211572333129.773.1
Jiangsu701279.832296824.7100.255.5
Zhejiang428955.419754326.6131.565.3
Fujian259838.411966823.2108.269.6
Shandong630098.529020011.492.348.9
Guangdong7281108.533538725.9133.572.4
Hainan3709.11705618.898.251.6
Whole region371854957515724.5116.263.8
Central region
Hebei298174.313729213.282.650.5
Shanxi127736.65880512.188.554.2
Jilin140627.56477720.891.247.7
Heilongjiang150838.16947815.687.444.5
Anhui220161.41013621268.239.4
Jiangxi167245.77703312.566.438.7
Henan370094.817043810.779.539.2
Hubei295558.513611314.977.446.8
Hunan289067.813312911.669.239.9
Whole region2059050540790147945
Western region
Inner Mongolia178325.18213512.994.750.3
Guangxi168048773989.27542.8
Chongqing157230.27239618.690.848.3
Sichuan30058213843016.582.940
Guizhou105035.3483778.983.338.4
Yunnan136247.462732878.937.4
Tibet1033.2472810.882.944.6
Shanxi127736.65880512.188.554.2
Gansu679263127712.58138.8
Qinghai2425.91113317.787.954.5
Ningxia2916.71341212.695.349.3
Xinjiang93223.64295221.28654.9
Whole region139763703777013.485.646.1
Whole country7175113705238917.193.551.4
Note: DMU = Decision-making unit, GRP = Gross regional product, Pr1 = Fixed-line penetration rate(per 100 persons), Pr2 = Mobile penetration rate(per 100 persons), Pr3 = Internet penetration rate(%).
Source: China Statistical Yearbook 2016.
DMUGRP
(billion yuan)
Population
(million)
Per capita GRP(yuan)Pr1Pr2Pr3
Eastern region
Beijing230121.710600936.2181.776.5
Tianjin165415.57617822.288.563
Liaoning286743.813205423.797.962.2
Shanghai251224.211572333129.773.1
Jiangsu701279.832296824.7100.255.5
Zhejiang428955.419754326.6131.565.3
Fujian259838.411966823.2108.269.6
Shandong630098.529020011.492.348.9
Guangdong7281108.533538725.9133.572.4
Hainan3709.11705618.898.251.6
Whole region371854957515724.5116.263.8
Central region
Hebei298174.313729213.282.650.5
Shanxi127736.65880512.188.554.2
Jilin140627.56477720.891.247.7
Heilongjiang150838.16947815.687.444.5
Anhui220161.41013621268.239.4
Jiangxi167245.77703312.566.438.7
Henan370094.817043810.779.539.2
Hubei295558.513611314.977.446.8
Hunan289067.813312911.669.239.9
Whole region2059050540790147945
Western region
Inner Mongolia178325.18213512.994.750.3
Guangxi168048773989.27542.8
Chongqing157230.27239618.690.848.3
Sichuan30058213843016.582.940
Guizhou105035.3483778.983.338.4
Yunnan136247.462732878.937.4
Tibet1033.2472810.882.944.6
Shanxi127736.65880512.188.554.2
Gansu679263127712.58138.8
Qinghai2425.91113317.787.954.5
Ningxia2916.71341212.695.349.3
Xinjiang93223.64295221.28654.9
Whole region139763703777013.485.646.1
Whole country7175113705238917.193.551.4
Note: DMU = Decision-making unit, GRP = Gross regional product, Pr1 = Fixed-line penetration rate(per 100 persons), Pr2 = Mobile penetration rate(per 100 persons), Pr3 = Internet penetration rate(%).
Source: China Statistical Yearbook 2016.
Table 2.  Descriptive statistics of the input and output variables, 2011-2015 (n = 31)
Telecom revenue(million)Labour (person) Cap 1Cap 2Cap 3Cap 4
2011
Mean37825487763909455154131400955366
Median30775434883780324331751215444740
S.D.30489327072540585031841042439246
Minimum23861090506423454012702300
Maximum1617161523841162101264434847815190767
2012
Mean41879491254772035081221411259363
Median34519435794410604114771190249244
S.D.3325432550325007497595984042026
Minimum33011090631453454013363420
Maximum1766381522931567817258763643606203926
2013
Mean50668496005630234115951325463406
Median42938442455056333422371025552558
S.D.4079832412372801301962913543518
Minimum39651308740471662013373930
Maximum2176091513771735687144639440865211481
2014
Mean58511504936649203155951306966137
Median5206644681584039224364890758580
S.D.47187333874634812816641353444984
Minimum4543163588892143105363930
Maximum2493541551752081008133744974018214181
2015
Mean7531150079802043268276853070371
Median6994944354656959207480720458941
S.D.6086332599570614209756601747591
Minimum53791617115695128701154480
Maximum315003150432251154385152028447220258
Note: Cap 1 = the length of optical cable lines (in kilometres); Cap 2 = the capacity of long-distance telephone exchanges(in circuits); Cap 3 = the capacity of local office telephone exchanges(in thousand exchange lines); Cap 4 = the capacity of mobile telephone exchanges(in thousand subscribers).
Telecom revenue(million)Labour (person) Cap 1Cap 2Cap 3Cap 4
2011
Mean37825487763909455154131400955366
Median30775434883780324331751215444740
S.D.30489327072540585031841042439246
Minimum23861090506423454012702300
Maximum1617161523841162101264434847815190767
2012
Mean41879491254772035081221411259363
Median34519435794410604114771190249244
S.D.3325432550325007497595984042026
Minimum33011090631453454013363420
Maximum1766381522931567817258763643606203926
2013
Mean50668496005630234115951325463406
Median42938442455056333422371025552558
S.D.4079832412372801301962913543518
Minimum39651308740471662013373930
Maximum2176091513771735687144639440865211481
2014
Mean58511504936649203155951306966137
Median5206644681584039224364890758580
S.D.47187333874634812816641353444984
Minimum4543163588892143105363930
Maximum2493541551752081008133744974018214181
2015
Mean7531150079802043268276853070371
Median6994944354656959207480720458941
S.D.6086332599570614209756601747591
Minimum53791617115695128701154480
Maximum315003150432251154385152028447220258
Note: Cap 1 = the length of optical cable lines (in kilometres); Cap 2 = the capacity of long-distance telephone exchanges(in circuits); Cap 3 = the capacity of local office telephone exchanges(in thousand exchange lines); Cap 4 = the capacity of mobile telephone exchanges(in thousand subscribers).
Table 3.  Malmquist productivity change index
DMUAnnual averages (2011-2015)
EffChTechChPEffChSEffChTFPCh
Eastern region
Beijing1.0001.1101.0001.0001.110
Tianjin0.9191.1580.9860.9321.064
Liaoning0.8721.1750.8711.0011.025
Shanghai0.9981.1370.9990.9991.134
Jiangsu1.0031.2461.0001.0031.250
Zhejian1.0001.2181.0001.0001.218
Fujian1.0191.2891.0171.0021.314
Shandong0.9351.2350.9360.9991.155
Guangdong1.0001.2091.0001.0001.209
Hainan1.0161.3091.0001.0161.330
Central region
Hebei0.9211.2210.9240.9961.124
Shanxi0.9291.2720.9310.9981.182
Jilin0.9461.2600.9520.9941.191
Heilongjiang0.8881.1770.8990.9881.045
Anhui1.0401.3601.0680.9741.415
Jiangxi0.9931.2340.9921.0011.225
Henan0.9871.2891.0140.9731.272
Hubei0.9961.2961.0030.9931.291
Hunan0.9581.2660.9571.0011.213
Western region
Inner Mongolia0.9141.3490.9300.9831.232
Guangxi0.9721.1370.9691.0031.105
Chongqing1.0171.3371.0151.0021.361
Sichuan0.9631.3711.0000.9631.320
Guizhou1.0611.1661.0601.0011.237
Yunnan1.0091.2741.0091.0011.285
Tibet1.0001.3511.0001.0001.351
Shanxi1.0161.2681.0220.9941.288
Gansu1.0431.2911.0600.9841.347
Qinghai1.0431.4391.0001.0431.501
Ningxia1.0061.2591.0001.0061.266
Xinjiang0.9321.2750.9470.9831.188
Eastern region0.9751.2070.9800.9951.177
Central region0.9611.2630.9700.9911.214
Western region0.9971.2911.0000.9971.287
All regions0.9791.2550.9850.9941.229
DMUAnnual averages (2011-2015)
EffChTechChPEffChSEffChTFPCh
Eastern region
Beijing1.0001.1101.0001.0001.110
Tianjin0.9191.1580.9860.9321.064
Liaoning0.8721.1750.8711.0011.025
Shanghai0.9981.1370.9990.9991.134
Jiangsu1.0031.2461.0001.0031.250
Zhejian1.0001.2181.0001.0001.218
Fujian1.0191.2891.0171.0021.314
Shandong0.9351.2350.9360.9991.155
Guangdong1.0001.2091.0001.0001.209
Hainan1.0161.3091.0001.0161.330
Central region
Hebei0.9211.2210.9240.9961.124
Shanxi0.9291.2720.9310.9981.182
Jilin0.9461.2600.9520.9941.191
Heilongjiang0.8881.1770.8990.9881.045
Anhui1.0401.3601.0680.9741.415
Jiangxi0.9931.2340.9921.0011.225
Henan0.9871.2891.0140.9731.272
Hubei0.9961.2961.0030.9931.291
Hunan0.9581.2660.9571.0011.213
Western region
Inner Mongolia0.9141.3490.9300.9831.232
Guangxi0.9721.1370.9691.0031.105
Chongqing1.0171.3371.0151.0021.361
Sichuan0.9631.3711.0000.9631.320
Guizhou1.0611.1661.0601.0011.237
Yunnan1.0091.2741.0091.0011.285
Tibet1.0001.3511.0001.0001.351
Shanxi1.0161.2681.0220.9941.288
Gansu1.0431.2911.0600.9841.347
Qinghai1.0431.4391.0001.0431.501
Ningxia1.0061.2591.0001.0061.266
Xinjiang0.9321.2750.9470.9831.188
Eastern region0.9751.2070.9800.9951.177
Central region0.9611.2630.9700.9911.214
Western region0.9971.2911.0000.9971.287
All regions0.9791.2550.9850.9941.229
Table 4.  Malmquist TFP index summary of annual averages during 2011 to 2015
YearEffChTechChPEffChSEffChTFPCh
20121.0061.0681.0061.0001.074
20130.9161.2930.9340.9811.185
20141.0171.2931.0071.0101.315
20150.9821.3900.9930.9881.364
YearEffChTechChPEffChSEffChTFPCh
20121.0061.0681.0061.0001.074
20130.9161.2930.9340.9811.185
20141.0171.2931.0071.0101.315
20150.9821.3900.9930.9881.364
Table 5.  Comparison of the indexes between the period of 2011– 2013 and the period of 2013–2015
EffChTechChPEffChSEffChTFPCh
2011-20130.9601.1750.9700.9901.128
2013-20150.9991.3401.0000.9991.339
EffChTechChPEffChSEffChTFPCh
2011-20130.9601.1750.9700.9901.128
2013-20150.9991.3401.0000.9991.339
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