Modern state is a welfare state, but if borrowing for spending could make countries rich, then no country would be poor. State governments must sustainably create high-paying jobs by raising the productivity of five places — three are of them are not geographic.
There are no poor people, only people in poor places.
An electrician moving from Kanpur to Bangalore gets three times more salary; on moving from Bangalore to Switzerland, she earns 20 times more.
The higher salaries reflect the higher productivity of the electrician’s customers in Bangalore (if every Indian lived in Bangalore, India’s GDP would be more than China’s) and Switzerland (their nine million people produce more GDP than India’s 220 million farmers).
Switzerland – their nine million people produce more GDP than India’s 220 million farmers
Harvard economist Lant Pritchett suggested global wage differences for identical workers are a policy-induced price distortion. Extending his thinking to India, the country’s wage differentials reflect massive productivity differences between five areas — states, cities, sectors, firms, and skills. Let’s dive deeper.
In the next decade, more people will die than be born in Karnataka.
In the next 20 years, six states in South and West India will account for almost 35 per cent of GDP growth but only 5 per cent of population growth because economic complexity breeds higher wages.
Economic complexity is like a game of scrabble — to win, you must make more, and longer words — and the government provides vowels while the private sector offers letters. States that provide more vowels — it’s unviable for employers to provide public goods — will attract more high-paying jobs.
Hyderabad has a higher GDP than Odisha and four times that of J&K.
Pillars of governance – out of tune ?
The 299 remarkable people who wrote our Constitution got many things right, but their mental model of the three pillars of governance — PM, CM, and DM — is no longer fit for purpose.
District magistrates — or their synonym collector — are unelected, inexperienced, and unempowered for the complex trade-offs needed to breed well-paying jobs. Cities that blunt the bad urbanisation that creates a divergence between nominal wages (what employers care about) and real wages (what employees care about) will attract high-paying jobs.
Software – employs only 0.8 per cent of our labour force but generates 8 per cent of GDP
Agriculture has 42 per cent of our labour force but only generates 16 per cent of GDP.
Software — an oasis of high firm productivity — employs only 0.8 per cent of our labour force but generates 8 per cent of GDP, while agriculture has 42 per cent of our labour force but only generates 16 per cent of GDP.
Our large population, colossal farm employment, and self-exploitation pair our fifth total GDP with the 138th per-capita GDP country ranking.
China raised its per capita income 80 times in 40 years by moving 700 million people from farm to non-farm employment.
States that increase manufacturing and service jobs will have more high-paying jobs; the only way to help farmers is to have fewer of them.
We fought with our parents, who said, “he has found a good job; he now works for a multinational company,” believing it was racism. But we now recognise that “MNC” was their proxy for the higher wages paid by higher productivity firms with more capital, technology, and meritocracy.
The pre-1991 unfair labour market advantage of multinationals no longer exists as Indian firms have raised their game. But the problem persists — our 6.3 crore enterprises only translate to 23,500 companies with a paid-up capital of more than Rs 10 crore, and our largest and smallest manufacturing companies have a 24 times difference in productivity. States that replace deals with rules by reducing regulatory cholesterol will attract high-paying jobs.
Indian cricket players have 100 times higher lifetime earnings than hockey players
There are many reasons — fair and unfair — that Indian cricket players have 100 times higher lifetime earnings than hockey players.
The wage difference between a good and lousy electrician is five times, but it’s fifty times between a good and bad programmer, CEO, or investor.
It is impossible to predict wage premiums, but Grade 12 is the new Grade 8. English fluency is like Windows, an operating system that is a vocational skill.
Wages are higher for using minds than muscles. States with high populations of residents with skills in demand will attract more high-paying jobs.
Fixing these five places requires a chief ministerial agenda. Police reforms, or how the rule of law is experienced.
Empowered mayors — this pertains to devolution of funds, functions, and functionaries.
Fixing government schools — raise their 45 per cent share of enrollment.
Creating the supply that will attract demand (providing skills to workers in advance for the manufacturing boom just like South India did for software with its 1980s engineering college deregulation).
Agriculture reform — prices and distribution. Uninterrupted power (generators are unaffordable by small employers. Reliable public transport — this helps the environment, women, and youth).
Formalisation — state governments generate more than 75 per cent of India’s 67,000 plus compliances, 6,700 plus filings, and 26,410 employer criminal provisions.
A rational HR in the Civil Services — don’t punish good performers by promoting bad performers.
Digitise: Set a 12-month target for paperless and cashless for all citizen interfaces by leveraging India’s unique stack of digital public goods.
India’s problem is not jobs but wages. Wages will not rise without the balanced targeting of the five poor places. State governments must restore policy balance by combining targeting poor people with transforming poor places.
AI, or artificial intelligence, refers to the development of computer systems that can perform tasks that would normally require human intelligence, such as recognizing speech, making decisions, and understanding natural language.
Virtual assistants: Siri, Alexa, and Google Assistant are examples of virtual assistants that use natural language processing to understand and respond to users’ queries.
Recommendation systems: Companies like Netflix and Amazon use AI to recommend movies and products to their users based on their browsing and purchase history.
Efficiency: AI systems can work continuously without getting tired or making errors, which can save time and resources.
Personalization: AI can help provide personalized recommendations and experiences for users.
Automation: AI can automate repetitive and tedious tasks, freeing up time for humans to focus on more complex tasks.
Job loss: AI has the potential to automate jobs previously performed by humans, leading to job loss and economic disruption.
Bias: AI systems can be biased due to the data they are trained on, leading to unfair or discriminatory outcomes.
Safety and privacy concerns: AI systems can pose safety risks if they malfunction or are used maliciously, and can also raise privacy concerns if they collect and use personal data without consent.