Abstract
Among the many reforms that landed India’s mobile industry such tremendous success, was the shift in the interconnection pricing regime, from Receiving Party Pays to Calling Party Pays in 2003. Mobile tele-density leapfrogged and retail tariffs declined steadily. Interconnection eliminates the need for a customer to subscribe to multiple networks in order to be able to communicate with all other customers and is, therefore, indispensable for the functioning of a competitive telecommunications market. It falls under the category of conduct regulations which regulates firm behavior using price controls. This paper empirically tests the market outcomes driven by regulatory evolution in the India’s interconnection regime. More specifically, it establishes a relation between interconnection usage (termination) charges on retail prices of mobile services in India. This is academically referred to as the waterbed effect. Using a system of simultaneous equations with sub-national data for mobile operators in India for a period of 29 quarters from 2009 to 2016, the paper does not find that the market for mobile services in India is statistically interlinked with the market for wholesale termination, with the exception of postpaid connections which demonstrate a significant tide effect.
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Notes
The Long Run Incremental Cost (LRIC) Model is the classical form of the forward-looking bottom-up approach. A well-designed LRIC approach provides an estimate of the cost of an operator to provide interconnection in a fully competitive market.
Under a Bill and Keep (BAK) regime, termination rates are set to zero. BAK reduces the need for regulation within the mobile industry, as operators now recover costs only from their retail customers. It incentivises operators to expand their customer base and encourage growth in traffic.
Ibid.
Growitsch et al. (2010).
Ibid.
Off-net calls are calls that terminate on a rival network.
This data was shared by the regulator, TRAI under a confidentiality agreement and strictly for the purpose of research.
Since the number of operators for prepaid connections is different than that for postpaid connections, the alphabets may not denote the same operator across the tables for postpaid and prepaid. For example, Operator ‘A’ in postpaid may not be same operator as cited in the table for prepaid as Operator ‘A’.
Matthew Shum, Empirical methods for industrial organisation, http://people.hss.caltech.edu/~mshum/gradio/china1.pdf.
Data for the quarter ending December 2011 is missing from the data set.
The Fisher type test performs either Augmented Dicky Fuller Test or Phillips–Perron unit-root test. I use the Phillips–Perron unit-root test for this research.
Observations with negative ARPM values were dropped from the data set.
These operators are Vodafone, Reliance, HFCL (Quadrant) and Loop (BPL).
Op Cit.
Op Cit.
Op Cit.
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Appendices
Appendix 1
See Table 7.
Appendix 2 Results from the identification test
Endogenous coefficients matrix.
realarpm1 | tmouog1 | |
realarpm1 | − 1 | |
tmouog1 | 0.5 | − 1 |
Exogenous coefficients matrix.
realinv1diff | type2 | mtr | public | year | realarpmoth1 | realgdp1diff | service | provider |
realarpm1 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0 | 0 | 0 |
tmouog1 | 0 | 0 | 0 | 0 | 0 | 0.5 | 0.5 | 0.5 |
Equation 1 is identified.
Equation 2 is identified.
System is identified.
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Kedia, M. Testing the waterbed effect for India’s telecom industry. Ind. Econ. Rev. 54, 121–148 (2019). https://doi.org/10.1007/s41775-019-00044-7
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DOI: https://doi.org/10.1007/s41775-019-00044-7