In this episode of the NIJ Podcast, Anany Avasthi talks to Shri Surjit Bhalla, a renowned economist who throws light on various economic themes and issues we face as a nation and elaborates how the PM’s dream to make India a developed nation by 2047 is achievable in all senses.

TLDR:

The key idea of the video is that data manipulation and interpretation play a crucial role in shaping narratives and beliefs about the Indian economy, and unbiased data collection and interpretation are essential for understanding and addressing economic challenges.

Key Insights

Economic Data and Analysis

🌍 Mr. Bhalla’s work extends to advising the government, international banks, and multilaterals, showcasing his expertise and influence in the field of economics.

📈 “Mr. Arvind Subramanian claimed that India’s GDP is overestimated and it might be a lot lower than the claimed seven percent, even suggesting that a four percent GDP growth might paint a rosier picture than reality.”

🤔 The growth rate of the economy during the pandemic cannot be solely blamed on the data, but rather on the impact of the lockdown and COVID-19.

💡 “Data is the new oil, but it is also a new ideology, used for political purposes and shaping narratives in the age of social media.”

🍒 Surjit Bhalla criticizes the practice of cherry picking data in economics, stating that researchers often run a million regressions to find one that suits their ideology.

📊 “I would use the plfs data for any inferences on jobs unemployment labor force participation and I would not choose the CMIE data.”

📉 Between 2015 and 2020, the multi-dimensional poverty index shows that 135 million individuals were brought out of poverty in India.

🤔 The multi-dimensional poverty index over five years also indicates a substantial reduction in poverty in India, despite the skepticism of ideologues.

💰 “India and China had the same per capita income from 1500 to 1980, but China grew much faster than India, resulting in a divergence in their per capita income levels.”

Gender Disparities and Labor Force Participation

📉 The unemployment rate in India has decreased from 6.2% to 4.2% according to the latest survey, indicating a positive trend.

👩‍💼 Shockingly, the female labor force participation rate in India, as per the latest survey, is only 8%.

🤔 Only eight percent of women in India are employed, which is the lowest labor force participation rate in the world, even lower than war-torn economies like Yemen.

🤔 The high percentage of women in STEM disciplines in India (42%) contradicts the low labor force participation rate for women (8%), raising questions about the barriers they face in transitioning from education to employment.

Long Summary

00:00 📈 Between 2015 and 2020, 135 million people were lifted out of poverty in India, but some economists question the data to fit their ideologies, while the speaker discusses GDP growth rate controversy and the manipulation of data in economics.

1.1 Between 2015 and 2020, 135 million individuals were lifted out of poverty in India, with the poverty rate significantly reduced, and the speaker criticizes the tendency of some economists to question the data and interpret it in a way that aligns with their ideological conclusions.

1.2 Mr. Surjit Bhalla, a renowned economist, discusses major economic issues and demystifies them for common readers and listeners, offering his expertise to the government, international banks, and multilaterals.

1.3 The speaker discusses the controversy surrounding India’s GDP growth rate and the claim that it may be overestimated, with a study suggesting it could be as low as four percent, leaving the common Indian confused about the reality.

1.4 The speaker discusses using a method to estimate GDP growth in multiple countries, finding that Germany had the greatest overestimation, and questions why there is constant questioning of GDP data and policy discussions among economists.

1.5 The speaker discusses the issue of interpreting data in economics, particularly in relation to growth and poverty reduction in India, and criticizes the tendency to dismiss data that does not align with one’s ideological beliefs.

1.6 The speaker discusses the analysis of economic data, the impact of COVID-19 on growth rates, the manipulation of data to fit a narrative, and the debate on India’s manufacturing model.

13:14 📈 Services, like Tesla cars and AI in healthcare, have changed the world; manufacturing is still important in India; lack of agricultural reforms and state intervention hindered economic progress for assembly line workers; data is crucial in understanding unemployment and public consumption/employment in India.

2.1 The world has changed with the rise of services, such as Tesla cars being computer coded, and non-tradable services like going to a doctor can now be replaced by artificial intelligence reading X-rays.

2.2 The definition and content of services has expanded, and a study by Mr. Goldar from The Institute of Economic Growth shows that the share of labor in manufacturing in India is larger than commonly believed.

2.3 The speaker argues that while some economists believe that manufacturing is no longer important, he disagrees and believes that services, particularly in India, have been a greater contributor to GDP growth.

2.4 Assembly line workers in developing countries, including India, missed out on economic progress due to a lack of agricultural reforms and increased state intervention, despite attempts by Prime Minister Modi to implement changes.

2.5 The speaker discusses the ideology and importance of data in economics, specifically focusing on the debate around unemployment in India and the availability of public data on consumption and employment.

20:56 📊 The unemployment rate in India was initially reported as 2.5% but subsequent surveys revealed it to be 6.2%, with recent data showing a decrease to 4.2%; only 8% of women in India are employed, the lowest labor force participation rate in the world, with discrepancies in data sources.

3.1 The national unemployment rate in India was initially reported as 2.5%, but subsequent surveys and data showed it to be 6.2%, indicating a discrepancy in reporting.

3.2 The unemployment rate in India has decreased from 6.2% in 2017–18 to 4.2% in 22–23, according to recent surveys.

3.3 The private agency CMIE has been publishing data on Indian Capital markets since 1980, including unemployment rates and female labor force participation, with the latest survey showing an 8% female labor force participation rate in India.

3.4 Only 8% of women in India are employed, which is the lowest labor force participation rate in the world, and there is a discrepancy between different data sources regarding women’s labor force participation and unemployment rates.

28:15 📊 Data is crucial for shaping narratives and beliefs, with India using a pioneering approach to measure employment, but response error in surveys affects data on women’s labor force participation, which has increased to 25% in 2021 while men’s labor force participation dropped during COVID-19 shutdowns.

4.1 Data is not only the new oil but also a new ideology, as it is crucial for pushing narratives and supporting beliefs, even if the data is manufactured or cherry-picked.

4.2 India has multiple measures of employment, with the standard method being asking if someone worked any day last week, but in India, they ask if someone worked any hour last week, which is a pioneering approach.

4.3 The speaker discusses different measures of employment status and highlights the importance of applying appropriate definitions for employment, particularly in developing countries like India.

4.4 We are measuring things properly, but there is a problem with response error in surveys and the number of responses, which affects data on employment and labor force participation of women.

4.5 Women’s labor force participation rate decreased from 30% in the 1990s to 17.5% in 2018, but has increased to 25% in 2021, while men’s labor force participation rate dropped to 10% during the COVID-19 shutdowns.

4.6 The speaker recommends using the PLFS data for inferences on jobs, unemployment, and labor force participation, rather than the less accurate CMIE data.

38:36 📊 Despite a high percentage of women in STEM disciplines in India, their labor force participation rate is low due to unpaid care work; however, the female labor force participation rate has remained constant over time and there has been a significant reduction in poverty in India.

5.1 In India, there is a high percentage of women in STEM disciplines in college compared to the US, despite having a low labor force participation rate.

5.2 Women, especially in India, spend significantly more time on unpaid care work compared to men, which is a global phenomenon and a topic of extensive research.

5.3 The female labor force participation rate in India decreased by 10 percentage points between 2004–5 and 2011–12 due to a definitional change in measuring women’s work in rural areas.

5.4 The labor force participation rate of women in India has remained constant over time, despite the fact that girls were attending school less than boys in the past.

5.5 There is a measurement problem in economics where one cannot be in two places at the same time, as discussed in a paper from 2011–12.

5.6 Between 2015 and 2020, the multi-dimensional poverty index shows that 135 million individuals were lifted out of poverty in India, with the previous measure of poverty in 2011–12 being 23 percent.

48:07 📊 India’s goal of becoming a developed country by 2047 depends on defining per capita income, and it is projected to reach the same level as China by 2042–43 based on relative growth rates.

6.1 The speaker questions the relevance of asking about the prices of various items in 1951 and suggests focusing on the prices of durable goods such as TVs, videos, radios, and bicycles.

6.2 In 2011–12, using the correct measurement method, it was found that 100 million people in India were moved out of poverty, indicating a significant reduction in poverty, despite the skepticism of ideologues.

6.3 India’s goal of becoming a developed country by 2047 depends on how the per capita income level of a developed country is defined.

6.4 The common shorthand measure of being developed is per capita income, but this definition is complicated as it does not account for factors like freedom and improvement in countries like China and Islamic countries.

6.5 Korea was recognized as a developed economy by the OECD in 1996, and by comparing India’s per capita income to Korea’s at that time, it is projected that India could achieve developed country status by 2047.

6.6 India and China had the same per capita income until 1980, but China’s rapid growth has caused a divergence, and it is estimated that India will reach the same per capita income level as China by 2042–43 based on relative growth rates.

58:55 📊 Improving data collection is crucial to avoid data becoming an ideology, as subjective factors like press freedom should be considered when measuring indices such as democracy and nutrition, highlighting the difficulty in determining which country has more press freedom.

7.1 We use the same U.N system of accounts as other countries, including the US, which has transitioned to using computer tablets for surveys.

7.2 Improving data collection is important for avoiding data becoming an ideology, and while there may be measurement problems with indices of democracy and nutrition, subjective factors such as press freedom, political liberties, and civil liberties should also be considered.

7.3 The speaker discusses the issue of freedom of the press in different countries, highlighting the subjective nature of indices and the difficulty in determining which country has more press freedom.

7.4 The change in the Indian elite has made certain interpretations of data more democratic and uncomfortable for some people.

01:04:21 📊 The speaker emphasizes the importance of unbiased data interpretation and being a contrarian in examining controversies surrounding the Indian economy.

8.1 The speaker, who has a background in engineering, discusses the importance of data and its interpretation in his work.

8.2 The speaker discusses the importance of being a contrarian in examining data and calling out the bluff in controversies surrounding the Indian economy, emphasizing the need for data to remain unbiased and not be used as a weapon of political ideology.

Q&A

Q1: Has poverty reduced in India between 2015 and 2020?

A1: Yes, according to the multi-dimensional poverty index, there has been a significant reduction in poverty in India during this period. Approximately 135 million individuals were brought out of poverty. This positive change can be attributed to various factors, including the efforts made by the Indian government and the leadership of Prime Minister Modi.

Q2: Is there a discrepancy in India’s GDP growth rate?

A2: There is a debate regarding India’s GDP growth rate. Mr. Arvind Subramanian has suggested that India’s GDP might be overestimated and could be as low as 4%, which is significantly lower than the claimed 7%. Subramanian’s analysis using multi-country regression indicates that India’s GDP growth rate may not be as high as reported. A lower GDP growth rate could provide a more accurate reflection of the actual state of the Indian economy.

Q3: How does the labor force participation rate of women in India compare to other countries?

A3: India has a relatively high percentage of women in STEM disciplines among large countries. In college, 42% of women in India are enrolled in STEM disciplines, compared to 31% in the United States. This high representation in STEM disciplines potentially contributes to the overall labor force participation rate of women in India. However, it is important to consider multiple factors when assessing women’s labor force participation, as the overall rate has remained relatively constant over time.

Q4: What factors determine a country’s development status?

A4: Development status is typically determined by indicators such as per capita income, but other factors like freedom and government regimes play a crucial role as well. Per capita income is often used as a shorthand measure of development, similar to GDP. However, it is important to consider other aspects such as freedom for women and the overall freedom of a nation. Recognition as a developed economy can change over time, and achieving a high per capita income does not guarantee developed status if other factors are lacking. For example, China has seen rapid economic growth but still lacks certain freedoms, while India aims to achieve developed country status by considering both income levels and other developmental factors.

Note - This content is generated by AI, we believe it is accurate, but we don’t claim any liability of inaccuracies in the AI generated content.

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