The Peninsula Foundation

Author: Arun Kumar

  • Changing Socio-Economic Situation of UP over the past Decade

    Changing Socio-Economic Situation of UP over the past Decade

    Elections have been announced and UP will be crucial. Parties have been campaigning for them for at least the last 6. The media has been awash with advertisements portraying a rosy picture of UP. They needed this unprecedented blitzkrieg to overcome the negativity due to the poor of the COVID second wave. Anyway, the and the government try to present a positive image of their work. Other state governments followed the UP, to the delight of media which is garnering much revenue.

    What is the reality on the ground in UP? Farmers, workers and have been protesting. Why this protest if the situation is as rosy as is projecting? Where does lie? Citizens need to know, to make up their minds about who to vote for. Since there has been growth. Even when it is small but positive, will be visible in socio-economic parameters, like, education, longevity, etc. There will be more roads, bridges, agricultural production, and so on.

    So, it is no brainer that the last 5 years would show progress compared to the immediately preceding 5 years and the ones before that, etc.. The meaningful comparison has to be based on changes in the ratios and growth rates between the earlier period and the present one. That tells us whether matters will improve faster or stagnate. Also, comparisons with all India figures would yield a picture of where UP stands compared to other states.

    If the present regimes 5 years are compared to the 5 years earlier this would be unfair since the last two years have been unusual – hit by the pandemic and the lockdown. The economy as a whole experienced a downturn and so did UP. A meaningful comparison would be between the pre-pandemic three years and the 5 years before them.

    Growth has Decreased

    A difficulty arises regarding measuring the growth of the economy since the Indian economy’s data is suspect, especially after demonetization. A disjuncture has been created between the organized and unorganized sectors while the data is largely from the former. So, the latter goes largely unrepresented and this causes a large error in the growth rates.

    Ignoring this aspect for the moment, let us analyse the official data, assuming it to be correct. It shows that out of the 20 major states, UP’s position remains at 19 in the last 10 years. In effect, there is no relative improvement in UP’s situation at the all India level.

    This is because the official growth rate was 11.8% in 2016-17 and has fallen to 6.3% in 2018-19 before the pandemic. The decline is also visible in the real income per person. Between 2012-13 and 2016-17, it increased by 27.63%. If we take the average over three years it increased by 16.6%. Leaving out the pandemic year of 2020-21, it rose by 9.23% (including the pandemic year it was 0.43%, that is it hardly grew). Including inflation also the per-person income growth slowed down. It was 25% during 2017–21 as compared to an increase of 65% during 2012–17.

    Slower Structural Transformation

    UP’s income (GSDP) was Rs.19 lakh crore out of GDP of Rs.190 lakh crore in 2019-20 – 10% of the country’s income. But its population share is estimated at 17%. The situation has not changed in the last 5 years and that is why the per-person income capita income rank or UP remains at 19th out of the 20 major states.

    One of the factors underlying the slow growth of UP is that it has structurally not transformed as much as has happened for the country as a whole. In UP, the share of agriculture is 24% while that of services is 50%. The all-India figures are 19.7% and 54.3% respectively. So, UP’s structural transformation is lagging behind that of all of India. Since agriculture cannot grow as fast as the services sector, the state’s growth rate is bound to be less than that for the nation. This feature is also the reason for weak employment generation in UP because agriculture cannot absorb more workers, in fact, it is characterized by mechanization and disguised unemployment.

    UP employed 57.13 lakh under MGNREGS, in May 2020 which was the highest in India. This points to high rural unemployment in UP. The large scale migration of workers from other states to UP in 2020 is an indication of the weak employment generation in UP which forced many to look for work elsewhere. No wonder the state faced the biggest impact of Coronavirus in India both in terms of employment and health aspects.

    Unfortunately, data invisibilizes the unorganized sector and hence the poor. The country has suffered policy induced crisis due to demonetisation, implementation of GST, NBFC crisis and the pandemic induced lockdown. This has deeply impacted the unorganized sectors of the economy and they have suffered massive losses during 2016-17 to 2020-21. The total loss for the unorganized sector in UP is estimated at 10% of the national loss during this period and amounts to Rs. 7.1 lakh crore. That is an average loss per annum of Rs. 1.78 lakh crore. This loss is far more than what the social welfare schemes of the government give. In any case, the schemes are mired in corruption and inefficiency and do not reach everyone uniformly. So, the poor are the net losers in spite of the government schemes.

    Government’s Efforts Slowing

    Are the government schemes expanding? How much are they able to help UP develop and catch up with the other states of India?

    No doubt, the absolute budgetary expenditures rise with inflation and growth. So, on most items more is spent than in earlier years. But to know whether these expenditures will help improve the situation or not, one has to compare the expenditures as a ratio of the state’s income (GSDP). On this score, the Budget data shows:

    a) Development expenditure peaked in 2015-16 at 16.66% and declined to 13.28% in 2019-20. This signifies that development is decelerating.

    b) Non-Development expenditure rose from 6.81% in 2015-16 to 8.49% in 2018-19 and was at 7.12% in 2019-20. This reflects the expenditure on grandiose show schemes of the state government which resulted in a decline in developmental expenditures mentioned above.

    c) No wonder expenditure on Education, etc. peaked in 2016-17 at 4.21% and fell to 3.07% in 2018-19 and was at 3.3% in 2019-20. The target should have been 6% of GSDP on public education. Instead of moving towards that goal, there is retrogression.

    d) Similarly, health expenditure peaked in 2016-17 at 0.84% and fell to 0.79% in 2019-20. It should have been raised to at least 3% of GSDP and instead, it fell. The impact of this was visible during the pandemic with poor health facilities in large parts of the hinterland and unnecessary deaths.

    e) Budgetary Capital outlay peaked in 2015-16 at 5.66% and fell to 3.55% in 2019-20. This slows down infrastructure development and adversely impacts private investment.

    In brief, as the economy expands, there will be development in a state – more hospitals, schools, colleges and so on. Further, development may be skewed and leave the poor behind as is the case in recent times. The real picture becomes clear when one looks at the ratios and compares them with other states. In these respects, UP has lagged behind both its past performance and other states. The virtual campaigning required due to the spread of Omicron would marginalize the less tech-savvy parties and give BJP an advantage in painting a glorious image of itself, in spite of its recent indifferent performance.

    This article was published earlier in hwnews.in

    Feature Image Credit: www.dnaindia.com

  • 2021-22 Q1 GDP Data Overestimates: Economic Shocks Question Methodology

    2021-22 Q1 GDP Data Overestimates: Economic Shocks Question Methodology

    2021-22 Q1 GDP Data Overestimates: Economic Shocks Question Methodology: The demonetisation shock impacted the unorganised sector far more adversely than it did the organised sector

    There are methodological errors in estimating annual and quarterly GDP data, especially when there is a shock to the economy, by using projections from the previous year, dividing the annual estimates into the four quarters and using production targets as if they have been achieved, explains Professor Arun Kumar

     

    The Reserve Bank of India (RBI) has maintained its growth projection for 2021-22 at 9.5% while the World Bank has retained it at 8.3%. These are based on the union government’s growth estimate of 20.1% for first quarter of 2021-22—an unprecedented growth rate based on the low base in the same quarter of 2020-21, which witnessed a massive decline of 24.1%.

    A sharp rise in growth after a steep fall in the preceding year is not a new phenomenon for the economy. Prior to 1999, only annual, not quarterly, data was available. Official data shows that the economy has risen sharply several times since independence: 1953-54 (6.2%), 1958-59 (7.3%), 1967-68 (7.7%), 1975-76 (9.2%) 1980-81 (6.8%), 1988-89 (9.4%) and 2010-11 (9.8%). The data after 2011-12 base revision was controversial. For instance, the new series shows a high growth rate of 8.3% for 2016-17 though it is well known that demonetisation devastated the economy

    Methodological Issues

    If the new series, using 2011-12 as the base year, shows a high growth rate for 2016-17, the methodology is not right. This has been extensively discussed since 2015, when the series was announced. A major change has been the use of the data provided by the union ministry of corporate affairs, called the MCA-21 database, since 2015. But it has been pointed out that many of the companies in this database are shell firms and the government shut down several of them in 2018. Further, many companies were found to be missing.

    Another problem pointed out, starting the year of demonetisation, is that the measurement of the contribution of the unorganised sector—which constitutes 45% of the GDP—is not based on independent data.

    The data for the non-agriculture sector is collected during surveys every five years. In between these years, the organised sector is largely used as a proxy and projections are made from the past. Both these features of estimation pose a problem when there is a shock to the economy.

    The demonetisation shock impacted the unorganised sector far more adversely than it did the organised sector. Hence, after demonetisation, the organised sector data should not have been used as a proxy to measure the contribution of the unorganised sector. Further, due to the shock, projections from the past will not be a valid procedure. This problem was accentuated by the implementation of the Goods and Services Tax (GST), which again impacted the unorganised sector more adversely

    Demand started to shift from the unorganised sector to the organized, making the situation even more adverse. For instance, e-commerce has severely impacted the neighbourhood stores and taxi aggregators have displaced the local taxi stands.

    Due to the shocks, the earlier procedure of calculating GDP becomes invalid and should have been changed. Since this has not been done, in effect, the GDP data is measuring the organised sector and agriculture.

    Thus, 31% of the economy is not being measured, and by all accounts, this part is declining, not growing. Therefore, GDP growth is far lower than what has been officially projected since 2016-17.

    The pandemic and the lockdown have administered the biggest shock to the economy. But the organised sector was hit far less than the unorganised sector. The split between the two sectors has been far greater than due to demonetisation or GST. Therefore, there is an urgent need to revise the method of calculating GDP—also, projections from the past do not make sense.

    Quarterly Data Issues

     The problem is even greater when projecting quarterly GDP growth. The data used is sketchier than the annual data. Not only most of the data for the unorganised sector is unavailable (except for agriculture), even the organised sector data is partial. For instance, the data for businesses is based on companies that declare their results in that quarter. Only a few hundred companies out of the thousands might be declaring such data.

    Worse, the estimation is based on a) projections for the same quarter in the preceding year same quarter, b) in many cases, the projection is not just for the quarter but for the year as a whole and then it is divided into four to get the data for one quarter and c) cases where targets, not actual production data. are used to estimate the contribution to GDP.

    Worse, the estimation is based on a) projections for the same quarter in the preceding year same quarter, b) in many cases, the projection is not just for the quarter but for the year as a whole and then it is divided into four to get the data for one quarter and c) cases where targets, not actual production data. are used to estimate the contribution to GDP.

    Fishing and aquaculture, mining and quarrying, and quasi-corporate and the unorganised sector are a few sectors which belong to the first group. Some sectors belonging to the second category are other crops, major livestock products, other livestock products and forestry and logging. Livestock belongs to the third category, where annual targets/projections are used.

    This procedure is clearly inadequate but maybe acceptable in a normal year. But when there is a shock to the economy, does it make sense? If there is a projection from the previous year, it is likely to give an upward bias since the economy was performing better in the preceding year. Further, projections have to be based on some indicators and the data on these indicators were only partially available due to the lockdown.

    Finally, how can the annual projection be made and then divided into four to obtain the quarterly estimate when the economy is highly variable from quarter to quarter. In 2020, each quarter was very different from the previous one.

    Next, if the data for 2020-21 is erroneous, when there was a massive slump in the economy, the shock continues into 2021-22. How can projections be made from the 2020-21 to 2021-22? Thus, there would be large errors in the quarterly data for the current year. This will then be fed into the data for 2022-23. Therefore, the shock to the economy will play itself out for several years.

    Impact on other Macro Variables

    Quarterly data are also published for other macro variables like consumption, and investment by public and private sectors. The government-related data is available in the Budget documents, but the private sector data poses a huge challenge. These estimates are, again, based on projections from the previous year, and in some cases, annual estimates are divided between quarters. Production data is also used to project consumption and investment by the private sector. So, if the former is incorrect, as pointed out above, then the estimates for the latter will also be erroneous.

    The RBI’s survey of the organised sector showed that capacity utilisation was down to 63% in January 2021, but the official quarterly data was showing a growth of 1.3% rather than a decline of 10%. Thus, the quarterly data was not representative of even the organised sector.

    Similarly, consumer sentiment was down to 55.5 compared to 105 a year back, implying that even the organised sector consumption had not recovered to the pre-pandemic levels. Both these variables were further dented in the second wave of COVID-19 in Q1 of 2021-22. The implication is that the data on these variables is also not reliable.

    If the production data is an overestimate due to the use of projections from the last year, the consumption and investment data would also be over projections. The further implication is that if the data for 2020-21 is not right, the quarterly data for 2021-22, projected from the previous year, will also be erroneous and overestimate.

    Analysis of Macro Variables for Q1 of 2021-22

    For the moment, let us analyse the Q1 data leaving aside the errors pointed out above. When the economy was in decline in the preceding year, comparing rates of growth makes less sense than comparing the level of GDP.

    On a low base of 2020-21 (-24.4%), the rate of growth for 2021-22 looks impressive (+20.1%). But it is 9.2% less than the pre-pandemic Q1 of 2019-20—i.e., the economy has not recovered to the pre-pandemic level.

    Further, if the economy was growing at the pre-pandemic rate, the economy would have expanded another 7.5% in two years. Thus, compared to the possible level of GDP in 2021-22, it is down by about 16%.

    Except for agriculture and the utilities sectors, data shows that none of the other sectors have recovered to the levels in 2019-20. Private final consumption expenditure is down by 11.9% and gross fixed capital formation by 17.1%. Government consumption expenditure and exports have increased compared to their levels in 2019-20. The former does give a boost to the economy by increasing demand but the latter does not since imports remain much higher than exports.

    Therefore, out of the four sources of demand, only government expenditure has increased—but this is not enough to compensate for the decline in the other three and that is why the economy is still down compared to 2019-20.

    It may be argued that over time, data undergoes revision as more data becomes available. But the situation now is unusual due to the pandemic. This necessitated a major revision in the methodology itself due to lack of data and consequent non-comparability across quarters and years.

     The views expressed are those of the author.

    This article was published earlier in NEWSCLICK.

    Image Credit: The Federal

     

  • To Become Atmanirbhar, Bharat Needs Strong R&D

    To Become Atmanirbhar, Bharat Needs Strong R&D

    India has gone full circle from Gandhi’s days of Swadeshi to Nehru’s vision of self-reliant India to New Economic Policies of indiscriminate opening of the economy to Atmanirbhar Bharat. In between lip service was paid to Swadeshi in 1998 but the government continue with the indiscriminate opening up of the economy. Even agriculture was not left untouched with the opening up of 1400 commodities after the Seattle round of negotiations in 1999.

    What is Atmanirbharta?

    What do we understand by atmanirbhar – is it at the narrow level of producing most things that we need ourselves or at the wider philosophical level? If the latter, it implies independence of thought and development of socially relevant knowledge. It could lead to an alternate vision of development and prosperity for the nation.

    In an open economy people will then buy the foreign produced cheaper goods. So, the more important aspect of atmanirbharta is the philosophical aspect.

    The idea of producing most things ourselves runs into a contradiction in a globalizing world which is premised on marketization. Most things are being produced cheaper and better somewhere else, including our cultural symbols such as gulal, diyas and ganesh statue. In an open economy people will then buy the foreign produced cheaper goods. So, the more important aspect of atmanirbharta is the philosophical aspect.

    Opening up the Economy

    In 1991, with the New Economic Policies we gave up the idea of ourselves producing most things that we need. Our global trade increased dramatically with the percentage of export plus import of goods and services in GDP rising from around 17% in 1991 to about 55.8% by 2013. In 2019 it is down to about 40%.

    With the evolution of Washington Consensus in the 1980s, based on the idea of marketization, the world started to integrate in the 1990s with all countries showing a sharp rise in trade to GDP ratio. China captured a large share of the world markets and built a huge trade surplus. Its foreign exchange reserves rose to over $3.5 trillion. This gave it enormous clout globally not only with developing countries but also with the developed countries.

    The idea of atmanirbharta or self-reliance underwent a change. It became a matter of global competition to gain market share globally. One imported more to export more. Growth was supposed to depend on this. South East Asia and China were given as examples of success of such openness and rapid improvement in the living standard of the population. China post-Mao successfully adopted such a strategy. It was a large economy so it could not even be said that India cannot do what Singapore can do.

    Globalization is all about development of technology and India has lagged behind in that.

    Lessons from China

    What are the lessons India can learn from China’s achievements in the last thirty years? Apart from the fact that it is an authoritarian state with a strong sense of nationalism, its advances in research are stupendous.

    China has invested huge sums in building a strong infrastructure and research base in Universities, Institutions and Industry. It has one of the highest investment and savings rate in the world at 44 per cent in 2019. India’s comparative figure for 2019 is around 30%. It has developed the 5G technology faster than others and is willing to provide it cheaper than its competitors. This is also the case with many other lines of production such as, electronics, pharmaceuticals, automobiles and toys. It has moved rapidly in various fields such as development of artificial intelligence and applications of internet for commerce and financial sectors.

    Globalization is all about development of technology and India has lagged behind in that.

    China has had the long term vision to develop this rapidly by investing heavily in Research and Development. After getting technology from foreign companies, it has advanced the same by mastering it. Unfortunately, India has not done so and has repeatedly imported the next level of technology.

    Need for strong R&D

    India’s investment in R&D has been minimal. The private sector has been investing little in technology development. And, the public sector has been hamstrung in technology development by lack of autonomy, bureaucratization and corruption.

    Global competitiveness requires rapid development of technology. It requires massive investment in both absorption and development of technology. Instead, India’s investment in R&D has been minimal. The private sector has been investing little in technology development. And, the public sector has been hamstrung in technology development by lack of autonomy, bureaucratization and corruption.

    Research and Development require autonomy for researchers and a long term vision. Of course resources are also required but autonomy and vision are crucial and these have been weak in India. The same Indian researchers are able to do well in foreign lands but when in India they are not able to deliver. Our research establishment are rather feudal in approach and work within rigid hierarchies so that often talent gets suppressed.

    a culture of promoting independent and critical thinking is largely missing and that reacts back on research and generation of new ideas.

    Universities are the places where autonomy is greater and a long term vision can flourish away from the immediate profit motive. But unfortunately most of our universities are also bureaucratized and do not give autonomy to the academics. The authorities largely with bureaucratized and feudal mindset see independent thinking as a threat to themselves and, therefore, put up road blocks in the path of the independent thinkers thereby frustrating them and making their functioning difficult. Often the independent minded are seen as trouble makers and a challenge to the domination of the authorities. This is true not only in social sciences but also in the case of sciences in most universities. Thus, a culture of promoting independent and critical thinking is largely missing and that reacts back on research and generation of new ideas.

    Imperatives of Strengthening R&D

    Atmanirbharta in the present day world does not imply closing the economy but having the strength to face the challenge from other nations. This has to be based on a long term vision and cannot be achieved in the short run or by ad hoc measures.

    It requires high quality education right from the school stage. Thus, the education budget has to be expanded and teaching paid much higher attention than given at present. The status of teachers has to be enhanced so that talented people come in to academia.

    The world has been globalizing for thousands of years with trade and exchange of knowledge across nations and across continents. But earlier it was a slow two way process. Colonization turned into a one way process with western knowledge and thought establishing its hegemony globally and more so in India. That killed the internal dynamism of Indian society. It reinforced feudalism in India and decimated the quest for socially relevant knowledge generation.

    There has to be a continuum in knowledge generation but with an Indian perspective. India has to have the self-confidence that it can move ahead without denying the last few hundred years. Denial is only a sign of weakness.

    As Gandhi suggested, there is need for Indian modernity. Achieving that is crucial. Can it be based on denying what has happened over the last 250 years and going to what existed prior to that? Such a gap would undermine our understanding of social developments in India. That would be a recipe for repeating our mistakes. There has to be a continuum in knowledge generation but with an Indian perspective. India has to have the self-confidence that it can move ahead without denying the last few hundred years. Denial is only a sign of weakness.

    Denial would prevent us from understanding the nature of globalization we are undergoing and therefore we would not be able to work out any correctives that are needed. It would lead to much confusion in society. For instance, we would not be able to understand why consumerism is sweeping the world, including the poor in India or why our research lacks dynamism. In brief, Atmanirbharta requires India to move with self-confidence and not be in denial.