An Econometric Study: The Cost of Mobile Broadband

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An Econometric Study: The Cost of Mobile Broadband Zhiwei Peng, Yongdon Shin, Adrian Raducanu IATOM13 ENAC January 16, 2014 Zhiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband January 16, 2014 1 / 18

Overview 1 Introduction Our Topic Data 2 Econometric analysis First Model Second Model 3 Conclusion Zhiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband January 16, 2014 2 / 18

Our Topic Mobile Broadband Mobile broadband services can be accessed through a computer-based connection, using a USB-modem/dongle to connect to the mobile network, or through a handset-based connection. By 2016, more than 80 percent of broadband connections will be mobile.(source: Wireless Intelligence Database) Our Topic The impact of different factors on mobile broadband price. Zhiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband January 16, 2014 3 / 18

Parameters Dependent Variable The mobile broadband price on a country level Explanatory Variables GDP per capita Competition between service providers (ISP) Level of urbanization (Urban population ratio) Education level (Years of schooling) Population Number of mobile broadband subscribers Area of each country Zhiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband January 16, 2014 4 / 18

Data Zhiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband January 16, 2014 5 / 18

Rules for collecting price data We choose 500MB postpaid handset-based plans (most affordable) Rules Mobile data price from the operator with largest market share in the country Prices include TAX On a monthly basis Price in original currency, then converted into USD Sources International Telecommunication Union UNESCO World Bank Wikipedia Zhiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband January 16, 2014 6 / 18

Postpaid handset-based prices (500 MB), 2012 20 16 12 8 4 Series: PRICE Sample 1 112 Observations 112 Mean 20.00982 Median 14.25000 Maximum 96.00000 Minimum 1.800000 Std. Dev. 17.65126 Skewness 2.023797 Kurtosis 7.318659 Jarque-Bera 163.4913 Probability 0.000000 0 0 10 20 30 40 50 60 70 80 90 Zhiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband January 16, 2014 7 / 18

First Model Price i =β 0 + β 1 GDP i + β 2 ISP i + β 3 urbr i + β 4 edu i + β 5 pop i + β 6 msub i + β 7 area i i = 1, 2,..., 118 Descriptions Normalization: x new = x x min x max x min GDP: GDP per capita, ISP: service providers, Urbr: urban population ratio, edu: years of schooling, pop: population, msub: mobile broadband subscribers, area: area of each country Zhiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband January 16, 2014 8 / 18

First Model Regression results Variable Coefficient Std. Error t-stastistics Prob. C 0.126771 0.046686 2.715400 0.0078 GDP 0.356848 0.100310 3.557461 0.0006 ISP 0.580770 0.184103 3.154598 0.0021 URBR -0.029712 0.166233-0.178738 0.8585 EDU 0.012092 0.088155 0.137165 0.8912 POP 0.000436 0.137260 0.003178 0.9975 MSUB -0.044396 0.095052-0.467069 0.6414 AREA 0.019737 0.133237 0.148133 0.8825 R-squared 0.274433 Mean dependent var 0.193310 Adjusted R-squared 0.225597 S.D. dependent var 0.187381 S.E. of regression 0.164895 Akaike info criterion -0.698263 Sum squared resid 2.827808 Schwarz criterion -0.504084 Log likelihood 47.10272 Hannan-Quinn criter. -0.619478 F-statistic 5.619462 Durbin-Watson stat 1.785316 Prob(F-statistic) 0.000016 Zhiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband January 16, 2014 9 / 18

Hypothesis Test F-test Null: H 0 : c(1) = c(2) =... = c(k) = 0 Prob. = 0.000016 < 0.05 Reject the null hypothesis t-test, null hypothesis: C(6) = 0 Test Statistic Value df Probability t-statistic 0.003178 104 0.9975 0.9975 > 0.05, we accept the null hypothesis Same test is done for other coefficients Zhiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband January 16, 2014 10 / 18

Second Model Price i = β 0 + β 1 GDP i + β 2 ISP i Variable Coefficient Std. Error t-stastistics Prob. C 0.126843 0.019646 6.456549 0.0000 GDP 0.328647 0.071771 4.579083 0.0000 ISP 0.586936 0.163408 3.591852 0.0005 R-squared 0.272265 Mean dependent var 0.193310 Adjusted R-squared 0.258912 S.D. dependent var 0.187381 S.E. of regression 0.161309 Akaike info criterion -0.784565 Sum squared resid 2.836257 Schwarz criterion -0.711748 Log likelihood 46.93564 Hannan-Quinn criter. -0.755021 F-statistic 20.38994 Durbin-Watson stat 1.763455 Prob(F-statistic) 0.000000 Zhiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband January 16, 2014 11 / 18

Second Model Interpretations The two probabilities are almost zero Prob(F-statistic) < 0.05 R 2 = 0.272265, too small. Regression equation Price i = 0.12684 + 0.32865GDP i + 0.58694ISP i i = 1, 2, 3,..., 118 Zhiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband January 16, 2014 12 / 18

Heteroscedasticity Test: White F-statistic 0.654048 Prob. F(5,106) 0.6590 Obs*R-squared 3.351936 Prob. Chi-Square(5) 0.6459 Scaled explained SS 14.43108 Prob. Chi-Square(5) 0.0131 Interpretation Prob. = 0.6590 > 0.05, we accept the homoscedasticity hypothesis The residuals have the same finite variance Zhiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband January 16, 2014 13 / 18

Normality test of residuals 28 24 20 16 12 8 4 0-0.2 0.0 0.2 0.4 0.6 0.8 Series: RESID Sample 1 112 Observations 112 Mean -2.48e-18 Median -0.033340 Maximum 0.856568 Minimum -0.327627 Std. Dev. 0.159850 Skewness 2.031776 Kurtosis 10.09109 Jarque-Bera 311.7147 Probability 0.000000 Mean, E(ɛ) = 0 Prob. = 0, reject normality Zhiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband January 16, 2014 14 / 18

Actual, Fitted, Residual Graph 1.0 0.8 0.6 1.2 0.8 0.4 0.2 0.0 0.4 0.0-0.4 10 20 30 40 50 60 70 80 90 100 110 Residual Actual Fitted Zhiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband January 16, 2014 15 / 18

Elasticity Price i = 0.12684 + 0.32865GDP i + 0.58694ISP i Estimated price elasticity of GDP per capita Price GDP = 0.32865 A 10 percent increase in GDP p.c. results in a 3 percent increase in price Estimated price elasticity of ISP Price ISP = 0.58694 A 10 percent increase in number of service providers results in a 6 percent increase in price hiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband January 16, 2014 16 / 18

Conclusion Our model GDP p.c. and ISP are good indicators of mobile broadband price Not good fitness of data, R 2 too small Only two explanatory variables Residuals are not normally distributed A lot of factors are statically insignificant Further work Mobile broadband price seems not to be influenced by the area of each country, but we believe that for developing countries, it would have significant influence Conduct econometric study inside developing countries and developed countries to make a comparison Zhiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband January 16, 2014 17 / 18

The End Zhiwei Peng, Yongdon Shin, Adrian Raducanu (UCLA) The Cost of Mobile Broadband January 16, 2014 18 / 18