Source: AIER, Aug 2019
My work has argued that nations that are open to risk-taking, trial-and-error experimentation, and technological dynamism (i.e., “permissionless innovation”) are more likely to enjoy sustained economic growth and prosperity than those rooted in precautionary principle thinking and policies (i.e., prior restraints on innovative activities).
Collison and Cowen suggest that “there can be ecosystems that are better at generating progress than others, perhaps by orders of magnitude. But what do they have in common? Just how productive can a cultural ecosystem be?” Beyond gaining a better understanding of how innovation ecosystems work, they also want to nurture them. “Can we deliberately engineer the conditions most hospitable to this kind of advancement or effectively tweak the systems that surround us today?” they ask.
Mokyr has argued that technological innovation and economic progress can be viewed as “a fragile and vulnerable plant, whose flourishing is not only dependent on the appropriate surroundings and climate, but whose life is almost always short. It is highly sensitive to the social and economic environment and can easily be arrested by relatively small external changes.” McCloskey’s work has shown that cultural attitudes, social norms, and political pronouncements have had a profound and underappreciated influence on opportunities for entrepreneurialism, innovation, and long-term economic growth
Many scholars have surveyed the elements that contribute to a successful innovation culture and their lists typically include:
- trust in the individual / openness to individual achievements;
- positive attitudes towards competition and wealth-creation (especially religious openness toward commercial activity and profit-making);
- support for hard work, timeliness, and efficiency;
- willingness to take risks and accept change (including failure);
- a long-term outlook;
- openness to new information / tolerance of alternative viewpoints;
- freedom of movement and travel for individuals and organizations (including flexible immigration and worker mobility policies);
- positive attitudes towards science and development;
- advanced education systems;
- support for property rights and contracts;
- reasonable regulations and taxes;
- impartial administration of justice and the respect for the rule of law; and,
- stable government institutions and transfers of power.
Source: SagePub, Jun 2019
In economics, the University of Chicago holds the top spot with 32 laureates, followed by Harvard (30), MIT (28), Stanford (25), Berkeley (23), Yale (21), and Princeton (19). In terms of the graduate department awarding the PhD degree to economics Nobel laureates, about half have come from only five universities: MIT (11), Harvard (10), Chicago (9), Carnegie Mellon (4) and the London School of Economics (4). Six other universities have produced two each.
Robert Solow (Nobel 1987) published (in 1956) a formal model of economic growth in which the output to capital ratio was not fixed, and the growth rate of population (and consequently the labor force) drove economic growth. Technological progress entered the process via a specified steady rate of productivity growth. His first order differential equation explaining the rate of economic growth appealed to the mathematical formalism of economists (and has lasted as a staple for more than 50 years) because it is founded on notions essential to popular classical economic theories.
Paul Romer, recipient of the 2018 Prize, extended the basic growth model by including technological progress as an endogenous factor, wherein economic policies, such as trademark and patent laws, could affect and accelerate the rate of technological progress (Henderson, 2018).
Source: Bloomberg, Aug 2018
The offshoot of the digital coin, known as Bitcoin Cash, is barely being used in commerce, according to blockchain analytics firm Chainalysis. A review of payments received by the world’s 17 largest crypto merchant processing services, such as BitPay, Coinify and GoCoin, found that Bitcoin Cash payments slumped to $3.7 million in May from a high of $10.5 million in March. Bitcoin payments totaled $60 million in May, down from a peak of $412 million in September.
Adoption in commerce has been low, partly the result of concentrated ownership, Grauer said. About 56 percent of Bitcoin Cash is controlled by 67 wallets not located on exchanges, according to Chainalysis. Of those, two wallets hold between 10,000 and 100,000 Bitcoin Cash. And chances are, the wealthiest holders are the ones sending a lot of the traffic to merchant services, Grauer said.
Source: MacroMarketMusings, May 2016
Selgin’s call for a Productivity Norm, a nominal income target for central banks that would result in inflation moving inversely with expected productivity growth. That is, he would have central banks stabilize aggregate demand growth but allow more price level flexibility based on technological advances. Along the way we cover the difference between benign and malign deflation and look, examine some of the historical cases of deflation, and discuss the recent productivity surge of the late 1990s and early 2000s.
- Stable prices or stable spending?–George Selgin
- A Brief Look at the Productivity Norm–David Beckworth
- Less than Zero: the Case for a Falling Price Level in a Growing Economy–George Selgin
- The Productivity Norm versus Zero Inflation in the History of Economic Thought–George Selgin
- The Productivity Gap: Monetary Policy, the Subprime Boom, and the Post-2001 Productivity Surge–George Selgin, David Beckworth, Berrak Bahadir
Source: Mercatus (George Mason University), Oct 2016
The Taylor rule is a standard guideline that central banks, such as the Federal Reserve (Fed), use for setting monetary policy. In its most basic form, a Taylor rule stipulates that central banks should set their interest rates in response to changes in inflation and in the output gap, which is the difference between actual and potential real gross domestic product (GDP). However, central banks continually face the problem of accurately forecasting these variables in real time.
In a new study for the Mercatus Center at George Mason University, Mercatus Senior Research Fellow David Beckworth and Joshua R. Hendrickson, assistant professor of economics at the University of Mississippi, demonstrate how a nominal GDP targeting rule is superior to a Taylor rule. A nominal GDP targeting rule targets the sum of all spending in an economy and would require less real-time knowledge on the part of policymakers than a Taylor rule, meaning it would be less prone to forecasting errors and would produce less economic volatility.
- In the 1990s, the Taylor rule, named after Stanford economist John Taylor, emerged as a popular rule for central banks to follow. If a central bank followed a Taylor rule when setting monetary policy, it would raise its interest rate when inflation was above target or output was above its potential, and it would lower its interest rate when inflation was below target or output was below its potential.
- While the Taylor rule does reduce central bank discretion, the knowledge problem still obstructs choices about how to measure and weigh inflation and the output gap. The biggest challenge is how to measure the output gap in real time, because (1) output data is generally revised over time and (2) potential output estimates are based on trends that rely on ever-changing endpoints.
- The central bank has to have perfect information about the output gap in order for the Taylor rule to work optimally. However, empirical evidence from the Federal Reserve Bank of Philadelphia shows that the Fed’s forecast of the output gap has diverged significantly from the ex post estimate of the output gap for prolonged periods of time. Forecast errors by the Fed and other central banks can potentially induce unanticipated changes in the short-term nominal interest rate, distinct from a standard monetary policy shock. From 1987 to 2007, the Fed’s forecast errors may have accounted for up to 13 percent of the fluctuations in the output gap.
NOMINAL GDP TARGETING
A nominal income target or nominal GDP target is a rule that targets the level or growth of nominal spending in the economy. Unlike a Taylor rule, which requires knowledge of inflation, actual output, and potential output, a nominal GDP target requires knowledge only of overall spending. While targeting nominal GDP growth might be subject to measurement error, it likely minimizes the significance of this measurement error in real time.
A nominal GDP target is superior to a Taylor rule because
- it allows central banks to target a single variable,
- it reduces the knowledge central banks need in order to conduct policy,
- it eliminates central banks’ need to control a real variable (i.e., a variable that is largely determined by economic factors outside monetary policy), and
- it does not require central banks to conduct monetary policy in accordance with real-time estimates of the output gap.
A nominal GDP target overcomes the knowledge problem better than the Taylor rule does and is therefore more likely to smooth out business cycles and mitigate economic booms and busts.
Related Resource: Michael Hatcher google sites, Sep 2016
Source: ZeroHedge, Aug 2017
Source: UPenn library, Apr 1988
In the late 1950s Solow formulated a theory of economic growth that emphasized the importance of technology. He stated that technology-broadly defined as the application of new knowledge to the production process-is chiefly responsible for expanding an economy over the long term, even more so than increases in capital or labor. And since basic and applied research is often the prelude to the birth of new technologies, the work of researchers has increasingly been perceived to have economic-not merely intellectual and cultural-significance.
But most remarkable, and startling even to the discoverer, was the finding, reported in the 1957 article (’‘Technical change and the aggregate production function’ ‘), that seven-eighths of the doubling in gross output per hour of work in the US economy between 1909 and 1949 was due to’ ‘technical change in the broadest sense” (which includes improvements in education of the labor force). Only one-eighth was due to increased injections of capital.
Karl-Goran Maler, Stockholm School of Economics, Sweden, a member of the Nobel committee, noted, ‘‘Solow showed us that in the long run it is not increase in quantity that is important. It is the increase in quality through better technology and increased efficiency.