Numbers and Plans
Reading Two Books, on Economic Planning and on Statistics in 1950s Asia (Long Post | #FromMyLongReadings, Issue 1, 2023)
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#FromMyLongReadings is a new extension of my #FromMyReadings blog series. Here, I’ll write longer posts (3500 words or more) about books and research papers I’ve been reading. Sometimes, I may also write shorter, more opinionated pieces to accompany these long posts.
Books for this post:
(1) Planning Democracy by Nikhil Menon
(2) Making It Count by Arunabh Ghosh
NOTE: Some illustrations in this post are AI-generated. These have been marked as such.
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Introduction
The end of the Second World War triggered a new chapter in history. In the Global North, the War’s after-effects pushed centres of power out from Europe, to the Soviet Union and the United States. In Asia and Africa, crumbling colonial empires gave way to dozens of new nations — independent, but confronting shaky futures. As the world reshaped itself, countries had to ask themselves how to move forward in uncertain times.
Most of us today roughly know what choices the world made — consolidating the United Nations; Reconstructing Europe; Developing the ‘Third World’; engaging in the Cold War; setting up the Non-Aligned Movement. Yet, ‘roughly’ knowing about these may not be sufficient.
The 2020–21 Pandemic may mark a turning point in history similar to what the world witnessed after 1945 (and also after 1991, but that’s for another day). At such turning points, the question of “How do we move ahead?” becomes crucial. New ideas will be proposed, and old ideas recycled. The future will seem exciting, uncertain, and unknown. At such times, it’s useful to look back (deeply) at other turning points in history, and learn from them. In this long post, I’ll use two books to look back at the 1950s. I’ll follow this up with a second, shorter post later on, examining what lessons the 1950s hold for us.
For this post, I was lucky enough to come across two books at the same time, which dive deep into 1950s India and China. The first book is Planning Democracy by historian Nikhil Menon of Notre-Dame University, published in 2022. The other is Making It Count by historian Arunabh Ghosh of Harvard University, published in 2020. While Planning Democracy focuses on independent India’s first attempts at designing Five-Year Plans, Making It Count focuses on early attempts in the People’s Republic of China to build national statistical systems.
The two books aren’t perfectly comparable. One focuses on planning systems, the other examines statistical ones. Economic Planning and Statistics are linked to each other (they were particularly close in the 1950s), but they’re not identical. Still, both books are histories of national-scale attempts, by Asian countries of similar size and population, to build new technical systems and processes at a time of great change. There are enough overlaps between them for us to examine them together.
Both India and China underwent massive social and political transformations in the late 1940s (independence in India, revolution in China), which created new moments to change their future paths. In both countries, new laws had to be written, new programmes designed, new organisations built, and new systems put in place. If these changes were to be effective, decisions had to be consolidated, centralised, and tracked. Therefore, numbers and plans began to occupy the centre of the stage. Disciplines like Economic Planning and Statistics started attracting attention in political and bureaucratic circles.
It wasn’t long before technical experts in these subjects would become key figures of the 1950s.
The Rise of Mahalanobis
One person who dominates narratives in both books is Prasanta Chandra (P C) Mahalanobis. A physicist by training, Mahalanobis began forays into Statistics while studying at Cambridge University, something he continued at Presidency College in Calcutta. In a stroke of serendipity, Mahalanobis began his shift from Physics to Statistics precisely when the need for statisticians was rising among government planners. As Nikhil Menon explains in Planning Democracy:
In the mid-twentieth century, several nation states witnessed a spurt in the production of statistical data.
[…]
Planners saw the economy as being essentially calculable.
[…]
Centralised planning required data about the economy, and statistics came to be viewed as the discipline that could deliver it.
- Planning Democracy, Chapter 1, Page 6.
Riding the tide, Mahalanobis set up the Indian Statistical Institute (ISI) in 1931 and launched a Statistics journal, Sankhya, in 1933. Over the next twenty years, both he and the ISI would build a reputation for themselves as the ultimate Indian authorities on Statistics (and later, Economic Planning).
The cornerstone of Mahalanobis’ and ISI’s reputation was the Random Sample Survey, a relatively new type of statistical study at the time. As the name suggests, statisticians choose a random sample of the full population under study, measure the sample, and extrapolate findings from the sample to the full population. The ISI pioneered the use of random sample surveys in Indian statistical practice, pushing them to become a critical tool of studying society and economy in the mid-20th Century. Random sample surveys would eventually become the basis for independent India’s National Sample Survey rounds, which commenced in 1950.
Additionally, Mahalanobis spent an enormous amount of effort burnishing his own reputation in global circles, travelling from conference to conference, meeting expert after expert in both the west and the Soviet Union. Menon claims there was a larger logic to his travels. Mahalanobis was an established statistician, but not a recognised economist or planner. By building connections with recognised economists and planners abroad, he could skirt around any questions about his credibility at home.
It’s here that we start seeing intersections with Arunabh Ghosh’s book, Making It Count. As Mahalanobis became a well-known international figure, the ISI campus at Baranagore (near Calcutta) became a frequent stop for intellectual superstars and international dignitaries. The statistician Ronald Fisher; the economists Ragnar Frisch, Simon Kuznets, and Jan Tinbergen; the scientist J B S Haldane; American ambassador J K Galbraith; and Indonesian Vice President Mohammad Hatta had all visited the ISI in the 1950s.
In 1956, the Chinese Premier Zhou Enlai paid a visit. Zhou’s interest in the ISI’s work threw the “day’s itinerary out of sync”, as he spent his time getting involved in intensive discussions with the ISI staff and Mahalanobis. After extensive questioning on Indian statistical methods and practices, Zhou told Mahalanobis that a group of Chinese statisticians would visit ISI after his visit. Two days later, a team did visit the ISI and stayed for a month.
The Story from China
Chinese interest in the ISI’s work had quite a history behind it. Ghosh notes that although statistical work in China was already covering a wide range of activities by the 1930s, the work was fragmentary and limited. Though there were efforts to co-ordinate statistical work into a centralised system, these efforts were disrupted by the 1949 Revolution, and rise of the Communist Party of China (CPC or CCP).
According to Ghosh, the CPC began expanding its own systems of statistics and data collection via its Northeast Statistics Bureau (NSB) in 1950. Both inspired and advised by the Soviet Union, the statistical work pioneered by the NSB and its director, Wang Sihui, strove for three basic features:
(1) For statistical work to be extensive, by including data from every major component of China’s economy, culture, education, and health care.
(2) For statistical work to be complete, so that whatever data *could be* captured *was* captured, and standardised into a central system.
(3) For statistical work to be objective, so that “unlike in capitalist systems”, statistics was not distorted or censored by profit motives and would not hide weaknesses.
In order to fulfill these criteria, Chinese statistical systems adopted two means of collecting data. The first was Exhaustive Enumeration. Simply put, this meant collecting data about everything deemed important — as broadly, deeply, and as frequently resources would allow.
The second way of collecting data (especially in agriculture) was via Typical Sample Surveys. Unlike the sample surveys pioneered by the ISI in India, samples here were selected by specified criteria instead of random selection. In addition to these two methods, there were several other forms of statistical work, from calculating price indices to correcting old records.
These lofty goals came with a toll. The Everything-Everywhere-All-At-Once approach adopted by the Chinese statistical systems began to generate far more data than could be processed by the people at the top. Reports started coming in of regional offices flooded with excess printed data which had no place to go. Additionally, discrepancies between local, regional, and national data began to increase, as tight deadlines pushed statisticians at higher levels of government to rely more on estimates than enumeration. A unified national statistical network was set up in the 1950s, but problems persisted.
Furthermore, Chinese statisticians were beginning to experience an ideological crisis. Although the Soviet Union had advised and supported the development of statistical systems in the early days of the People’s Republic, the Soviets were being viewed as unworthy of emulation by the mid-1950s. In 1956, Zhou Enlai commented that Chinese study of the Soviet Union had been conducted with “undue haste, arbitrary learning, and mechanical application”. By this time, China was opening itself to new perspectives from other countries, including India.
A Brief Time Together
In some ways, the statisticians of India and China were worlds apart when they met in 1956.
Following the Soviets’ example, the People’s Republic of China had wrung statistics through an ideological mangle. A culture of criticising the ‘bourgeois statistics’ of the West had entrenched a belief that statistics was a social science with no universal rules. Ghosh dwells quite a bit on China’s suspicion of statistics which was rooted in formal mathematics, since it was seen as conflating social and natural worlds together. Concepts like Measures of Central Tendency (Mean, Median, Mode) or Fisher’s Price Index were criticised as distorting social reality. Overall, the People’s Republic of China had spent years distancing itself from the statistical practices of capitalist countries.
By contrast, Mahalanobis and the ISI had spent decades engaging with the west (and elsewhere) to legitimise their work on random sample surveys. When appointed as a chair for a new UN Sub-Commission on Statistical Sampling, Mahalanobis advocated for spreading sampling methods worldwide. Menon mentions that India’s National Sample Surveys became the norm for UN Household Surveys. Furthermore, Indian statisticians were less suspicious of what the Chinese called ‘bourgeois statistics’. For instance, India used random sample surveys to pioneer the concept of the Poverty Line in 1962, an idea that might have been criticised in China.
However, the changed attitude to the Soviet Union by 1956, and a new openness in China’s foreign policy after the 1955 Bandung Conference meant that the Chinese showed tremendous interest in Indian statistical methods. In both Ghosh’s and Menon’s books, the initial meetings between the Indians and the Chinese were quite positive. Prior to Zhou Enlai’s visit to ISI, an Indian team led by Pitambar Pant has visited China in July 1956. Ghosh describes a meeting with Zhou Enlai during this visit, where Zhou praised Indian statistical measurements of agriculture.
After the Chinese team visited ISI, Mahalanobis and his colleagues were also invited to lecture in China in 1957. Given China’s earlier suspicions of mathematical connections to statistics, it’s interesting to note that during this visit, Mahalanobis gave a lecture on The Theory of Mathematical Probability in Sample Surveys, while his colleague D B Lahiri delivered four lectures on Applications of Mathematical Probability in Sample Surveys. Even if Chinese suspicion of mathematical statistics hadn’t vanished, they were now willing to listen to alternative opinions.
This optimistic state of events wasn’t to last. Initially, there were some good signs. After Mahalanobis and his team returned to India, Ghosh reports how Wang Sihua of the NSB publicly advocated for adopting Indian random sampling techniques in Chinese statistical work. However, his advocacy was guarded, suggesting that random samples be used only when original records were missing or where numbers to be enumerated were too high. In other cases, Wang suggested that “a socialist country” like the People’s Republic of China could not abandon complete enumeration or Soviet methods entirely.
The larger political climate in China was much more disruptive. In June 1957, Mao Zedong and Deng Xiaoping commenced the Anti-Rightist campaign, where a purge of CPC members perceived as not being left-wing enough was conducted. This was followed by Mao’s Great Leap Forward in 1958, where academics and intellectuals were evicted from cities and sent to work in agricultural communes. In such an environment, Ghosh notes that intellectual attempts to be open-minded to foreign ideas was to invite disaster.
Both the existing Chinese statistical methods, (Ghosh notes) as well as the random sampling techniques from India, were sidelined during the Great Leap Forward. Statistical methods of the NSB had always sat uneasily with Mao’s own preferences of relying upon in-person experience, and on using singular examples as representative of larger trends. During the Great Leap Forward, larger surveys, sampling, and comprehensive data systems were ignored in favour of more personalised methods.
In addition to this, diplomatic relations between India and China had begun to fail. Negotiations on fixing the disputed Sino-Indian border broke down, and the 1959 exodus of the Dalai Lama to India effectively ended most academic and cultural exchanges between India and China. A few years later, in 1962, the two countries would go to war over the unresolved border. The statistical exchange between the countries had had a promising start, but it was cut short too soon to be of lasting value.
Statistics in Five Year Plans
India-China comparisons have been going on for years. They are the only countries in the world with billion-plus populations, they are both Asian, both are among the world’s largest countries by landmass, both have high economic growth rates, and both are expected to become geopolitical superpowers this century. There are significant differences of course, but there is still enough to warrant comparisons with each other. Studying them can often reveal interesting parallels.
I noted two such parallels when reading Planning Democracy and Making It Count together. The first was in the use of Statistics to build Five Year Plans. Both India and China carried out Five Year Planning exercises in the 1950s, both for the first time. In both cases Statistics was considered subservient to the larger goal of the Five Year Planning process.
It’s important for us to remember how ubiquitous the ideas of Economic Planning and National Development were in the 1950s. At several points in his book, Menon mentions how the notion of Planning had permeated the national consciousness in India. “The Five Year Plans…” he observes. “…represented an alternate national calendar.”
“A satirical piece in Shankar’s Weekly noted that visitors to the country may notice that ‘India is very plan-minded’.”
[…]
“‘You cannot get away from this planning business…whatever you talk about somehow they [Indians] lead you to the question of planning as though everything depended on planning, everywhere.’”
- Planning Democracy, Chapter 4, Page 114.
In an atmosphere enveloped in Planning fervour, technical disciplines and scientific work had to be adopted to serve the larger national good. Vikram Sarabhai once defended India’s space programme by commenting that “…we [India] must be second to none in the application of advanced technologies to the real problems of man and society”. Even to Mahalanobis, the relationship between Statistics and Economic Planning was clear. Menon notes how Mahalanobis once commented “Poverty is the most basic problem of the country, and that Statistics must help solving this problem.”
This relationship between Statistics and Economic Planning in India had also been formalised. In 1950, the Government of India set up the Central Statistical Organisation (CSO) in tandem with the establishment of the country’s Planning Commission. While the Planning Commission was in charge of the Five Year Planning Process, the CSO would organise the statistical apparatus of the Government to serve the Planning process. Mahalanobis was regularly invited to Planning Commission meetings and the CSO shared physical space with the Commission at Yojana Bhavan in Delhi. The ISI’s workhorse, the Random Sample Survey served as the statistical backbone of the Planning process, with the first National Sample Survey in 1950–51 covering 1833 villages in 15 languages (translated back to English).
A similar attitude to statistics and planning prevailed in China. The Five Year Planning process in China (at the time) was co-ordinated by its State Planning Commission or SPC. After preparing and circulating a draft plan, the SPC would receive smaller draft plans from lower-level organisations in the government hierarchy which would then be used to revise the national plan.
At the lowest levels, Ghosh notes that Planning and Statistics were combined into a single office. However, at the national level, the State Planning Commission would partner with the State Statistical Board or SSB, in a manner not too different from how India’s CSO worked with its Planning Commission. The SSB and SPC occupied the same building, just like the CSO and the Planning Commission in India.
In an echo of Mahalanobis, statistical work in China was seen as serving the national planning process (Ghosh observes this could have stemmed from Mao Zedong’s emphasis to “serve the people”). Statistical numbers were the basis for preparing plans, inspecting them, deciding on policies and checking on implementation. In 1954, the SPC released a six-page document which exhorted for greater co-operation and understanding between the Planning and Statistics offices in order to solve pending issues of co-ordination.
The Role of ‘Ideal People’
The second parallel which I noted in both books was how both India and China relied upon idealistic depictions of ordinary people to make their respective systems work. It’s important to note that the two countries had (and continue to have) very different political systems. Yet, both regimes had to ensure that their plans and systems were considered legitimate by the people at the grassroots. Both regimes did this by creating imagery of ordinary people as integral parts of the larger planning or statistical processes. By creating such imagery, both nations sought popular support for their national initiatives.
Menon observes that in independent India, citizen rights were often seen as coming attached with duties, to be performed by the citizens for the nation. Very often, this would require ordinary citizens to become part of the planning process in some way or another. Menon argues that state campaigns in India to remind Indian citizens of their duties were crucial to to Plan success, since “unlike in the Soviet Union or China”, the Indian government could not force its citizens to comply.
While it is true that the People’s Republic had far more stringent means of ensuring public participation, it does not mean that the Chinese government didn’t face its own challenges. Ghosh observes that sometimes the hardest people to convince were ground-level workers within the Chinese bureaucracy itself. In Chapter 6 of his book (wryly titled To Ardently Love Our Statistical Work), Ghosh talks about how (unlike engineering or farming) statistics was not seen as “productive work” by ground-level statistical workers, since it did not produce tangible goods and dealt with abstract notions and concepts. There was a need to communicate the importance of statistical work and its role in nation-building.
Authorities in China undertook a slew of initiatives to train ground-level workers in both methods and the importance of statistical work. Apart from the many training institutes and courses however, a significant number of debates and discourse also took part among the pages of statistical journals, with (likely fictional) ground-level workers lamenting on the uselessness of statistics and experts providing responses.
From these discourses arose the romantic idea of the Ideal Statistical Worker. Ghosh writes that lamentations about the uselessness of statistical work got responses about “needs of the nation and the people”. Statistical workers were criticised for thinking only about their personal prospects and profits and told to focus on the bigger picture. On the other hand, ‘good’ statistical workers began to receive ‘model worker’ awards. In May 1956, nearly 300 people were honoured as model workers in a national conference. Furthermore, propaganda painted statistical reports as tangible, desirable outputs, thereby addressing the claim that Statistics was abstract, useless work.
At the same time, in India, massive public outreach campaigns were being designed to raise awareness of and participation in the Five Year Plans. Much of the second half of Menon’s book focuses on Indian government attempts to increase public participation in the Five Year Plans. He reports on how Nehru commented that the Planning Commission’s task also involved “…how to get the villager…to realise that something is not only being done for him, but he’s doing it and is part of the machinery doing it…” The Indian government created mass campaigns at the 1954 Kumbh Mela, set up a Five Year Plan Publicity Organisation, distributed pamphlets and posters about “Help the Plan, Help Yourself”, held exhibitions for urban citizens, and released a documentary.
The parallels between Indian citizens participating in the Five Year Plans and in Chinese statistical workers participating in the national statistical work are therefore quite striking. In both circumstances, an ideal worker or a citizen was someone typically from the grassroots or lower levels who may not have truly understood the scope or the scale of the project they were ostensibly part of, but who performed their duties for the national good nonetheless. In both circumstances, it became the duty of senior bureaucrats to engage with the grassroots, promote images of the grassroots worker as part of a larger national agenda, and recruit them to larger causes.
Conclusion
Reading Menon and Ghosh together brings out how crucial the 1950s were as a decade of change for Asia as a whole. There were other critical moments as well — the 1955 Afro-Asian Conference at Bandung for instance — but the fact that two of Asia’s largest countries embarked upon drastic political, bureaucratic, and economic restructuring at the same time effectively make the 1950s a turning point for Asian history. Much of what we see in India and China today took root during that decade.
Furthermore, despite the deep differences in ideology and political structure, despite the trigger points for change being so vastly different in the two countries (independence from a colonial power versus ascendancy via armed revolution), it’s remarkable to see broad similarities in the challenges the two countries faced, and in the ways they chose to respond. They even interacted with each other briefly about these, before deeper issues destroyed relations between the two.
I’ll need a separate post to ruminate on the implications of the 1950s for our present times, but some brief points may be useful here. Firstly, it’s useful to remind ourselves that neither India nor China are what they used to be in the 1950s. In India, the Planning Commission and the Five Year Planning process were abandoned in 2015 for being too archaic, while the country’s national statistical architecture is currently under reform. In China, sweeping changes under Deng Xiaoping and more recently, under the Xi Jinping regime, has made it a very different nation from Mao’s and Zhou’s time. For both countries, private sector growth, corporate-led capitalism, and the emergence of a consumption class has come to signify popular markers of growth.
That being said, there are some echoes between what Menon and Ghosh write about the 1950s and what we see today. We may no longer harp about enumerations or random sample surveys to the same extent as back then, but the need for large-scale statistics continues to remain high. Debates now focus on Big Data, Data Science, and Artificial Intelligence to answer deep questions about our society in similar ways. We may no longer resort to Five Year Plans, but grand visions built on rising economic prosperity continue to dominate discourse, with governments in both India and China finding new ways to tap into global economic trends.
In some ways, it does seem like these two countries have come far from the days covered by Menon and Ghosh. In other ways, we seem to still be right where we began. More on this in a later post.
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*A note on the AI-generated images: The copyright status on AI-generated images in India is still unclear. In the absence of a clear legal judgement, I’ll be treating AI software like DALL-E and MidJourney as tools, and claiming any art work generated through my prompts to them as my own. (I’ll update this note if the legal status becomes clearer).
However, there should be no contest that the prompts I give AI software are my own. I request that if you make AI art of your own by using the same prompts I’ve used in this post — can you please acknowledge me as the original author of those prompts? Just a note in your final publication will do. I’m not going to charge you or anything, I‘d just appreciate the acknowledgement! Thanks.
