The Unassuming Economist

From VoxEU post by Reda Cherif and Fuad Hasanov:

“The ‘Asian miracles’ and their industrial policies are often considered as statistical accidents that cannot be replicated. The column argues that we can learn more about sustained growth from these miracles than from the large pool of failures, and that industrial policy is instrumental in achieving sustained growth. Successful policy uses state intervention for early entry into sophisticated sectors, strong export orientation, and fierce competition with strict accountability.

Achieving sustained growth over long periods of time has been an elusive ‘holy grail’ of macroeconomics. In the past 50 years developing economies have taken different paths. A few – such as the ‘Asian miracles’ of Hong Kong (China), South Korea, Singapore, and Taiwan Province of China – are catching up swiftly with the advanced economies, and some forging ahead. But many are falling behind, to use the terminology of Abramovitz (1986).

The empirical evidence shows that the odds for poor or middle-income countries to reach high-income status within two generations are very low (Cherif and Hasanov, forthcoming). Between 1960 and 2014, fewer than 10% of economies (16 out of 182 in the sample) reached high-income status. There were three categories of those that made it: Asian miracles, countries that discovered large quantities of oil, and those that benefited from joining the European Union (Figure 1)

 

Figure 1 Half a century of development

Source: Penn World Tables 9.0 (Feenstra et al. 2015).
Note: GDP per capita is in 2011 PPP dollars. The thresholds for upper-middle income and high income are 20 % and 50% of US GDP per capita, respectively (red lines). The diagonal line indicates no change in relative income levels (with respect to the US level).

We argue (Cherif and Hasanov 2019)  that one cannot ignore the pre-eminent role of industrial policy in the development of the Asian miracle countries as well as for Japan, Germany, and the US before them. The industrial policies pursued by the Asian miracles have a lot in common. This suggests that the standard ‘growth policy recipe’ of tackling only government failures (improving macro-stability, enforcing property rights, providing basic infrastructure and education, and so on) may not be enough to create advanced economies in a short period of time. Instead, recent research suggests that industrial policy may benefit economic development too (Rodrik 2019).”

From a Vox piece on NZ’s well-being budget:

“To Prime Minister Jacinda Ardern, the purpose of government spending is to ensure citizens’ health and life satisfaction, and that — not wealth or economic growth — is the metric by which a country’s progress should be measured. GDP alone, she said, “does not guarantee improvement to our living standards” and nor does it “take into account who benefits and who is left out.”The budget requires all new spending to go toward five specific well-being goals: bolstering mental health, reducing child poverty, supporting indigenous peoples, moving to a low-carbon-emission economy, and flourishing in a digital age. To measure progress toward these goals, New Zealand will use 61 indicators tracking everything from loneliness to trust in government institutions, alongside more traditional issues like water quality.”

Other material on similar subjects include an earlier IMF paper on Bhutan’s Gross National Happiness index (GNH) by Sriram Balasubramanian and Paul Cashin and a Vox piece on new growth models.

From an IMF working paper by Tamim Bayoumi and Jelle Barkema:

“Using bilateral data on migration across US metro areas, we find strong evidence that increasing house price and income inequality has reduced long distance migration, the type most linked to jobs. For those migrating uphill, from a less to a more prosperous location, lower mobility is driven by increasing house price inequlity, as the disincentives from higher house prices dominate the incentives from higher earnings. By contrast, increasing income inequality drives the fall in downhill migration as the disincentives from lower earnings dominate the incentives from lower house prices. The model underlines the plight of those trapped in decaying metro areas—those “left behind”.”

From Stumbling and Mumbling:

“I welcome the Deaton report into inequality. I especially like its emphasis (pdf)upon the causes of inequality:

To understand whether inequality is a problem, we need to understand the sources of inequality, views of what is fair and the implications of inequality as well as the levels of inequality. Are present levels of inequalities due to well-deserved rewards or to unfair bargaining power, regulatory failure or political capture?

I fear, however, that there might be something missing here – the impact that inequality has upon economic performance.

My chart shows the point. It shows the 20-year annualized rate of growth in GDP per worker-hour. It’s clear that this was much stronger during the relatively egalitarian period from 1945 to the mid-70s than it was before or since, when inequality was higher.

This might, of course, be coincidence: maybe WWII caused both a backlog of investment and innovation which allowed a subsequent growth spurt and a desire for greater equality.

Or it might not. This is not the only evidence for the possibility that inequality is bad for growth. Roland Benabou gave the example (pdf) of how egalitarian South Korea has done much better than the unequal Philippines. And IMF researchers have found (pdf) a “strong negative relation” between inequality and the rate and duration of subsequent growth spells across 153 countries between 1960 and 2010.”

 

From a new paper on robot adoption in China

“China is the world’s largest user of industrial robots. In 2016, sales of industrial robots in China reached 87,000 units, accounting for around 30 percent of the global market. To put this number in perspective, robot sales in all of Europe and the Americas in 2016 reached 97,300 units (according to data from the International Federation of Robotics). Between 2005 and 2016, the operational stock of industrial robots in China increased at an annual average rate of 38 percent. In this paper, we describe the adoption of robots by China’s manufacturers using both aggregate industry-level and firm-level data, and we provide possible explanations from both the supply and demand sides for why robot use has risen so quickly in China. A key contribution of this paper is that we have collected some of the world’s first data on firms’ robot adoption behaviors with our China Employer-Employee Survey (CEES), which contains the first firm-level data that is representative of the entire Chinese manufacturing sector.”