In-principle Cabinet approval for merger, VRS proposal
In an effort to revive the beleaguered state-owned telecom firms BSNL and MTNL, the Union Cabinet on Wednesday approved a package worth nearly ₹70,000 crore. The Cabinet, chaired by Prime Minister Narendra Modi, also gave an in-principle nod for the merger of the two entities.
Under the package, 4G spectrum worth ₹20,000 crore will be administratively allotted to the two firms. Their debt will be restructured by raising bonds with sovereign guarantee worth ₹15,000 crore and a voluntary retirement scheme, on an outlay of ₹30,000 crore, will be offered to the employees. The government also plans to monetize the assets of the two firms worth ₹38,000 crore.
“The thinking of our government is very clear. These are strategic assets of India. They are most cooperative when there is a natural calamity, the entire Army network is managed by them and even for banks most of the network is managed by BSNL. They are neither being closed or disinvested or hived off to a third party. We want to make these competitive and bring in professionalism,” Communications Minister Ravi Shankar Prasad said.
With these steps, BSNL and MTNL are expected to turn EBITDA (Earnings before interest, tax, depreciation and amortization) positive in the next two years, he said. Stating that an immediate merger will not be feasible, given that MTNL is a listed entity, he said till the time the process is completed, MTNL will work as a subsidiary of BSNL.
Mr. Prasad said administrative allotment of spectrum for 4G services to BSNL and MTNL will enable the PSUs to provide broadband and other data services. This spectrum will be funded by the government via capital infusion of ₹20,140 crore.
Bombay Telephone was founded in 1882. The first telephone exchange in Mumbai began operations on 28 January 1882. Delhi's first telephone system was established in 1911. Mahanagar Telephone Nigam was created by the Government of India in 1986 to oversee the telephone services of Delhi and Mumbai
Mahanagar Telephone Nigam Limited (MTNL) is a stateowned telecommunications service provider in the metro cities of Mumbai and New Delhi in India and in the island nation of Mauritius in Africa. The company had a monopoly in Mumbai and New Delhi until 1992, when the telecom sector was opened to other service providers. "Transparency makes us different" is the motto of the company. The Government of India currently holds 57% stock in the company with the rest being held by public and institutional investors. The company's shares are listed on Bombay Stock Exchange, Global depository receipts on London Stock Exchange and American depository receipts on New York Stock Exchange. As of January 2019, it has 6.71 million subscribers
Millennium Telecom Limited (MTL)
MTNL has restructured Millennium Telecom Ltd. (MTL) as a joint venture company of MTNL and BSNL with 50% and 50% equity participation respectively. The company will now be entering into new business stream of international long distance operations and will be executing a project of a submarine cable system, both east and west from India
Mahanagar Telephone Mauritius Limited (MTML)
MTNL has set up a wholly owned subsidiary called Mahanagar Telephone Mauritius Limited (MTML) in Mauritius, providing mobile and international long distance services. MTML is the second operator in Mauritius. Necessary licenses were obtained in January 2004
Bharat Sanchar Nigam Limited (abbreviated BSNL) is an Indian state owned telecommunications company headquartered in New Delhi. It was incorporated on 1 October 2000 and assumed the business of providing telecom services and network management from the erstwhile Central Government Departments of Telecom Services (DTS) and Telecom Operations (DTO) as of 1 October 2000 on a going-concern basis. It is the largest provider of fixed telephony with more than 49% market share, and is the fourth largest mobile telephony provider in India. BSNL is India's oldest communication service provider and its history can be traced back to the British era. During the British era, the first telegraph line, was established between Calcutta and Diamond Harbour. The British East India Company started using the telegraph in 1851 and till 1854 telegraph lines were laid across the country. In 1854, the telegraph service was opened to the public and the first telegram was sent from Mumbai to Pune. In 1885, the Indian Telegraph Act was passed by the British Imperial Legislative Counsel. After the bifurcation of post and Telegraph department in 1980s, the creation of Department of Telecom by 1990s eventually led to the emergence of the State owned telegraph and telephone company BSNL. BSNL then continued the telegraph services in India until it shut down telegraph services completely on 15 July 2013
Last week, demographers from around the world gathered in Delhi to mark 25 years of National Family Health Surveys (NFHS). It was both a celebratory and sombre moment. Policymakers and researchers celebrated tremendous achievements of four rounds of the NFHS since 1992-93; these have provided data on Indian families and allowed for development and evaluation of public policies regarding population, health, education and the empowerment of women. It was also heartening to see the political commitment towards ensuring the continuation of this outstanding survey programme at regular and predictable intervals. Nonetheless, a single concern permeated the two-day conference. Can India’s existing data infrastructure support high quality data collection or are we staring at a precipice where deteriorating data quality will lead evidence-based policy development astray?
Presentations by Dr. Amy Tsui, Professor at Johns Hopkins University, and Dr. Santanu Pramanik, Deputy Director, National Council of Applied Economic Research (NCAER)-National Data Innovation Centre, on contraceptive use highlighted the difficulties in obtaining reliable, high quality data. Between 2005-06 and 2015-16, the total fertility rate (TFR) declined from 2.68 to 2.18 births. However, instead of being accompanied by increased contraceptive use, as would happen during normal circumstances, contraceptive use also declined from 56.3% to 53.5%. Using different approaches, both Prof. Tsui and Dr. Pramanik came to the same conclusion — that this aberration must be attributed at least partially to declining quality of contraceptive use data in NFHS-4.
Much of the data quality discussions in the past have erupted when politically sensitive results around topics such as GDP growth rate or poverty rates have been released and partisan bickering allows for little room to think about data collection systems. A retrospective look at the way in which an outstanding programme of research such as the NFHS has changed over time along with the nation it chronicles, and emerging challenges facing the NFHS and other data collection efforts provide an opportunity to look at overall challenges facing our data infrastructure in a constructive manner.
As Pravin Srivastava, Chief Statistician of India, noted at the NFHS conference, there is an amazing greed for data in modern India. This greed ranges from wanting to evaluate success of Poshan Abhiyaan (nutrition programme) to measure changes in the aspirational districts. However, he also noted that the once vaunted Indian statistical infrastructure is crumbling and is not able to fulfil even its traditional tasks, let alone meet these new demands.
I would like to submit that every government over the past two decades has been complicit in this neglect. If we are to move towards developing a more robust data infrastructure, subscribing to the following core principles may be a good start.
First, set realistic goals and use creative strategies. In order to obtain data at the district level, the sample size grew from about one lakh households in NFHS-3 to over six lakhs in NFHS4. At that time the National Statistical Commission had expressed a concern that such an expansion may reduce data quality.
There was a fair amount of agreement among the participants at the NFHS conference that this concern may have been prescient. The government’s need for district-level estimates of various health and population parameters is legitimate, but do we need to rely on household surveys to obtain them?
With a variety of small area estimation techniques available for pooling data from diverse sources to obtain robust estimates at district level, it may make sense for us to think of alternatives and to make sure that we obtain required local government directory identifiers in each aspect of government data, including Census, sample registration system, and Ayushman Bharat payment systems to ensure that these data can be pooled and leveraged.
Second, adapt to changing institutional and technological environment for data collection. Veterans of the Indian statistical system blame deteriorating data quality on the move from regular employees to contract investigators at the National Sample Survey and use of for-profit data collection agencies in the NFHS. For better or worse, that train has left the station. Rising government salaries combined with increased technological needs of modern data collection systems make it difficult to rely on veteran investigators in the civil services to meet all of government data needs. However, if we are going to rely on outside data collectors, what do we need to do to ensure quality? Some of the initiatives undertaken by the Ministry of Statistics and Programme Implementation for developing training programmes for investigators offer a welcome improvement but stop far short of the radical restructuring of data collection oversight.
I have enormous empathy for field investigators. They work under difficult conditions and are sometimes employed by for-profit agencies that require unrealistically high levels of output. Nonetheless, this is the data that guides the policies affecting millions of Indians and must be faithfully collected. Where interviewers make a mistake, they must be retrained. Where agencies impose an unrealistic workload, they must be checked.
However, discovering mistakes after data collection has been completed is far too late to take any corrective steps. Concurrent monitoring using technologically-enabled procedures such as random voice recording of interviews, judicious back checks, and evaluation of agency and interviewer performance on parameters such as skipping sections, inconsistent data and consistent misreporting may be needed to ensure quality. Academician Dr. Leela Visaria noted the declining role of State population research centres in NFHS data collection. It may be worth investigating if they can be involved in quality monitoring.
Need for exclusive units
Third, establish research units exclusively focused on data collection and research design.
At one point in time, innovative research on the NSS was undertaken by an associated unit at the Indian Statistical Institute in Kolkata. Since the dissolution of this association, very little research on data collection techniques takes place in India. We know little about whether men or women are better responders for data on household consumption expenditure. Nor do we know the extent of discrepancy in reporting on employment data between a direct response from women in the household vis-à-vis a proxy response via the household head. Do Likert scales that ask individuals to respond on their health status in five categories work well in India or do Indian respondents avoid choosing extreme categories? How does the presence of other people bias responses on contraceptive use? And does it have an equal impact on reported pill use as it does on sterilisation?
While research on data collection methods has stagnated, research methodologies have changed phenomenally. Telephone surveys via random digit dialling or selection of respondents using voter lists are increasingly emerging as low-cost ways of collecting data. However, we know little about representativeness of such samples. Are men or women more likely to respond to telephone surveys? Are migrants from other States well represented on the voter list?
Unless we pay systematic attention to the data infrastructure, we are likely to have the national discourse hijacked by poor quality data as has happened in the past with a measurement of poverty or inconsistent data on GDP.