Total factor productivity growth and technological change in the telecommunications industry

Xuchen Lin; Ting-Jie Lu; Xia Chen

doi:10.3934/dcdss.2019053

Article Contents

2019, Volume 12, Issue 4&5: 795-809. Doi: 10.3934/dcdss.2019053 open access

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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
* Corresponding author: Xuchen Lin

Received: July 2017

Revised: January 2018

Published: March 2019

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Abstract

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.

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Mathematics Subject Classification: Primary: 90B30, 62P20; Secondary: 91B38.

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Figure 1. Malmquist TFP index trend versus technological change and efficiency change during 2011 to 2015

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Table 1. Operating environments of 31 DMUs in 2015

DMU	GRP (billion yuan)	Population (million)	Per capita GRP(yuan)	Pr1	Pr2	Pr3
DMU	Eastern region
Beijing	2301	21.7	106009	36.2	181.7	76.5
Tianjin	1654	15.5	76178	22.2	88.5	63
Liaoning	2867	43.8	132054	23.7	97.9	62.2
Shanghai	2512	24.2	115723	33	129.7	73.1
Jiangsu	7012	79.8	322968	24.7	100.2	55.5
Zhejiang	4289	55.4	197543	26.6	131.5	65.3
Fujian	2598	38.4	119668	23.2	108.2	69.6
Shandong	6300	98.5	290200	11.4	92.3	48.9
Guangdong	7281	108.5	335387	25.9	133.5	72.4
Hainan	370	9.1	17056	18.8	98.2	51.6
Whole region	37185	495	75157	24.5	116.2	63.8
Central region
Hebei	2981	74.3	137292	13.2	82.6	50.5
Shanxi	1277	36.6	58805	12.1	88.5	54.2
Jilin	1406	27.5	64777	20.8	91.2	47.7
Heilongjiang	1508	38.1	69478	15.6	87.4	44.5
Anhui	2201	61.4	101362	12	68.2	39.4
Jiangxi	1672	45.7	77033	12.5	66.4	38.7
Henan	3700	94.8	170438	10.7	79.5	39.2
Hubei	2955	58.5	136113	14.9	77.4	46.8
Hunan	2890	67.8	133129	11.6	69.2	39.9
Whole region	20590	505	40790	14	79	45
Western region
Inner Mongolia	1783	25.1	82135	12.9	94.7	50.3
Guangxi	1680	48	77398	9.2	75	42.8
Chongqing	1572	30.2	72396	18.6	90.8	48.3
Sichuan	3005	82	138430	16.5	82.9	40
Guizhou	1050	35.3	48377	8.9	83.3	38.4
Yunnan	1362	47.4	62732	8	78.9	37.4
Tibet	103	3.2	4728	10.8	82.9	44.6
Shanxi	1277	36.6	58805	12.1	88.5	54.2
Gansu	679	26	31277	12.5	81	38.8
Qinghai	242	5.9	11133	17.7	87.9	54.5
Ningxia	291	6.7	13412	12.6	95.3	49.3
Xinjiang	932	23.6	42952	21.2	86	54.9
Whole region	13976	370	37770	13.4	85.6	46.1
Whole country	71751	1370	52389	17.1	93.5	51.4
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.

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Table 2. Descriptive statistics of the input and output variables, 2011-2015 (n = 31)

	Telecom revenue(million)	Labour (person)	Cap 1	Cap 2	Cap 3	Cap 4
2011
Mean	37825	48776	390945	515413	14009	55366
Median	30775	43488	378032	433175	12154	44740
S.D.	30489	32707	254058	503184	10424	39246
Minimum	2386	1090	50642	34540	1270	2300
Maximum	161716	152384	1162101	2644348	47815	190767
2012
Mean	41879	49125	477203	508122	14112	59363
Median	34519	43579	441060	411477	11902	49244
S.D.	33254	32550	325007	497595	9840	42026
Minimum	3301	1090	63145	34540	1336	3420
Maximum	176638	152293	1567817	2587636	43606	203926
2013
Mean	50668	49600	563023	411595	13254	63406
Median	42938	44245	505633	342237	10255	52558
S.D.	40798	32412	372801	301962	9135	43518
Minimum	3965	1308	74047	16620	1337	3930
Maximum	217609	151377	1735687	1446394	40865	211481
2014
Mean	58511	50493	664920	315595	13069	66137
Median	52066	44681	584039	224364	8907	58580
S.D.	47187	33387	463481	281664	13534	44984
Minimum	4543	1635	88892	14310	536	3930
Maximum	249354	155175	2081008	1337449	74018	214181
2015
Mean	75311	50079	802043	268276	8530	70371
Median	69949	44354	656959	207480	7204	58941
S.D.	60863	32599	570614	209756	6017	47591
Minimum	5379	1617	115695	12870	115	4480
Maximum	315003	150432	2511543	851520	28447	220258
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).

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Table 3. Malmquist productivity change index

DMU	Annual averages (2011-2015)
DMU	EffCh	TechCh	PEffCh	SEffCh	TFPCh
Eastern region
Beijing	1.000	1.110	1.000	1.000	1.110
Tianjin	0.919	1.158	0.986	0.932	1.064
Liaoning	0.872	1.175	0.871	1.001	1.025
Shanghai	0.998	1.137	0.999	0.999	1.134
Jiangsu	1.003	1.246	1.000	1.003	1.250
Zhejian	1.000	1.218	1.000	1.000	1.218
Fujian	1.019	1.289	1.017	1.002	1.314
Shandong	0.935	1.235	0.936	0.999	1.155
Guangdong	1.000	1.209	1.000	1.000	1.209
Hainan	1.016	1.309	1.000	1.016	1.330
Central region
Hebei	0.921	1.221	0.924	0.996	1.124
Shanxi	0.929	1.272	0.931	0.998	1.182
Jilin	0.946	1.260	0.952	0.994	1.191
Heilongjiang	0.888	1.177	0.899	0.988	1.045
Anhui	1.040	1.360	1.068	0.974	1.415
Jiangxi	0.993	1.234	0.992	1.001	1.225
Henan	0.987	1.289	1.014	0.973	1.272
Hubei	0.996	1.296	1.003	0.993	1.291
Hunan	0.958	1.266	0.957	1.001	1.213
Western region
Inner Mongolia	0.914	1.349	0.930	0.983	1.232
Guangxi	0.972	1.137	0.969	1.003	1.105
Chongqing	1.017	1.337	1.015	1.002	1.361
Sichuan	0.963	1.371	1.000	0.963	1.320
Guizhou	1.061	1.166	1.060	1.001	1.237
Yunnan	1.009	1.274	1.009	1.001	1.285
Tibet	1.000	1.351	1.000	1.000	1.351
Shanxi	1.016	1.268	1.022	0.994	1.288
Gansu	1.043	1.291	1.060	0.984	1.347
Qinghai	1.043	1.439	1.000	1.043	1.501
Ningxia	1.006	1.259	1.000	1.006	1.266
Xinjiang	0.932	1.275	0.947	0.983	1.188
Eastern region	0.975	1.207	0.980	0.995	1.177
Central region	0.961	1.263	0.970	0.991	1.214
Western region	0.997	1.291	1.000	0.997	1.287
All regions	0.979	1.255	0.985	0.994	1.229

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Table 4. Malmquist TFP index summary of annual averages during 2011 to 2015

Year	EffCh	TechCh	PEffCh	SEffCh	TFPCh
2012	1.006	1.068	1.006	1.000	1.074
2013	0.916	1.293	0.934	0.981	1.185
2014	1.017	1.293	1.007	1.010	1.315
2015	0.982	1.390	0.993	0.988	1.364

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Table 5. Comparison of the indexes between the period of 2011– 2013 and the period of 2013–2015

	EffCh	TechCh	PEffCh	SEffCh	TFPCh
2011-2013	0.960	1.175	0.970	0.990	1.128
2013-2015	0.999	1.340	1.000	0.999	1.339

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References

	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.
	R. D. Banker , Z. Cao , N. Menon and R. Natarajan , Technological progress and productivity growth in the us mobile telecommunications industry, Annals of Operations Research, 173 (2010) , 77-87.
	M. Calvo , J. I. M. Torcal and L. R. García , A new stepsize change technique for adams methods, Applied Mathematics and Nonlinear Sciences, 1 (2016) , 547-558.
	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.
	A. Charnes , W. 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.
	H. W. Chesbrough and D. J. Teece , When is virtual virtuous, Harvard Business Review, 74 (1996) , 65-73.
	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.
	L. Correa , The economic impact of telecommunications diffusion on uk productivity growth, Information Economics and Policy, 18 (2006) , 385-404.
	A. Datta and S. Agarwal , Telecommunications and economic growth: A panel data approach, Applied Economics, 36 (2004) , 1649-1654.
	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.
	W. E. Diewert , Exact and superlative index numbers, Journal of Econometrics, 4 (1976) , 115-145. doi: 10.1016/0304-4076(76)90009-9.
	A. Dutta , Telecommunications and economic activity: An analysis of granger causality, Journal of Management Information Systems, 17 (2001) , 71-95.
	R. Färe and S. Grosskopf , Malmquist productivity indexes and fisher ideal indexes, The Economic Journal, 102 (1992) , 158-160.
	R. Färe , S. Grosskopf , M. Norris and Z. Zhang , Productivity growth, technical progress, and efficiency change in industrialized countries, The American economic review, () , 66-83.
	R. Färe , S. Grosskopf and P. Roos , Productivity and quality changes in swedish pharmacies, International Journal of Production Economics, 39 (1995) , 137-144.
	Y. Gao , M. Farahani and W. Gao , Ontology optimization tactics via distance calculating, Applied Mathematics and Nonlinear Sciences, 1 (2016) , 154-169.
	D. I. Giokas and G. C. Pentzaropoulos , Evaluating productive efficiency in telecommunications: Evidence from greece, Telecommunications Policy, 24 (2000) , 781-794.
	J. A. Hausman and W. E. Taylor, Partial deregulation in telecommunications: An update, Journal of Competition Law and Economics.
	E. Hisali and B. Yawe , Total factor productivity growth in uganda's telecommunications industry, Telecommunications Policy, 35 (2011) , 12-19.
	H. Kang , Technology management in services: Knowledge-based vs. knowledge-embedded services, Strategic Change, 15 (2006) , 67-74.
	F. Kiss, Productivity gains in bell canada, Economic Analysis of Telecommunications: Theory and Applications, Amsterdam: North-Holland.
	J.-J. Laffont and J. Tirole, Competition in Telecommunications, MIT press, 2001.
	P. Lall , A. 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.
	P.-L. Lam and T. Lam , Total factor productivity measures for hong kong telephone, Telecommunications Policy, 29 (2005) , 53-68.
	P.-L. Lam and A. Shiu , Productivity analysis of the telecommunications sector in China, Telecommunications Policy, 32 (2008) , 559-571.
	D. Lien and Y. Peng , Competition and production efficiency: Telecommunications in oecd countries, Information Economics and Policy, 13 (2001) , 51-76.
	G. Madden and S. J. Savage , Telecommunications productivity, catch-up and innovation, Telecommunications Policy, 23 (1999) , 65-81.
	S. K. Majumdar , Does new technology adoption pay? electronic switching patterns and firm-level performance in us telecommunications, Research Policy, 24 (1995) , 803-822.
	S. Malmquist , Index numbers and indifference surfaces, Trabajos de Estadística, 4 (1953) , 209-242. doi: 10.1007/BF03006863.
	MIIT, Statistical bulletin of china's telecommunications industry in 2016, http://www.miit.gov.cn/n1146290/n1146402/n1146455/c5471508/content.html.
	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.
	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.
	H. Oniki , T. H. Oum , R. Stevenson and Y. Zhang , The productivity effects of the liberalization of japanese telecommunication policy, Journal of Productivity Analysis, 5 (1994) , 63-79.
	J. B. Quinn and M. N. Baily , Information technology: Increasing productivity in services, The Academy of Management Executive, 8 (1994) , 28-48.
	R. W. Shepherd, Theory of Cost and Production Functions, Princeton University Press, 1970.
	N. D. Uri , Measuring productivity change in telecommunications, Telecommunications Policy, 24 (2000) , 439-452.
	N. D. Uri , Productivity change, technical progress, and efficiency improvement in telecommunications, Review of Industrial Organization, 18 (2001) , 283-300.
	C.-H. Yoon , Liberalisation policy, industry structure and productivity changes in korea's telecommunications industry, Telecommunications Policy, 23 (1999) , 289-306.