Macro Economic Quotes

Many social justice or social activist movements have been rooted in a position. A position is usually against something. Any position will call up its opposition. If I say up, it generates down. If I say right, it really creates left. If I say good, it creates bad. So a position creates its opposition. A stand is something quite distinct from that. There are synonyms for “stand” such as “declaration” or “commitment,” but let me talk for just a few moments about the power of a stand. A stand comes from the heart, from the soul. A stand is always life affirming. A stand is always trustworthy. A stand is natural to who you are. When we use the phrase “take a stand” I’m really inviting you to un-cover, or “unconceal,” or recognize, or affirm, or claim the stand that you already are. Stand-takers are the people who actually change the course of history and are the source of causing an idea’s time to come. Mahatma Gandhi was a stand-taker. He took a stand so powerful that it mobilized millions of people in a way that the completely unpredictable outcome of the British walking out of India did happen. And India became an independent nation. The stand that he took… or the stand that Martin Luther King, Jr. took or the stand that Elizabeth Cady Stanton and Susan B. Anthony took for women’s rights—those stands changed our lives today. The changes that have taken place in history as a result of the stand-takers are permanent changes, not temporary changes. The women in this room vote because those women took so powerful a stand that it moved the world. And so the opportunity here is for us to claim the stand that we already are, not take a position against the macro economic system, or a position against this administration, although some of you may have those feelings. What’s way more powerful than that is taking a stand, which includes all positions, which allows all positions to be heard and reconsidered, and to begin to dissolve. When you take a stand, it actually does shift the whole universe and unexpected, unpredictable things happen.

Business capabilities are relative to macro conditions. Based on differences in macro conditions, the economic worth of a capability could differ from one scenario to another.

In Keynes’s time, physicists were first grappling with the concept of quantum mechanics, which, among other things, imagined a cosmos governed by two entirely different sets of physical laws: one for very small particles, like protons and electrons, and another for everything else. Perhaps sensing that the boring study of economics needed a fresh shot in the arm, Keynes proposed a similar world view in which one set of economic laws came in to play at the micro level (concerning the realm of individuals and families) and another set at the macro level (concerning nations and governments).

Finally, when young people who “want to help mankind” come to me asking, “What should I do? I want to reduce poverty, save the world,” and similar noble aspirations at the macro-level, my suggestion is: 1) Never engage in virtue signaling; 2) Never engage in rent-seeking; 3) You must start a business. Put yourself on the line, start a business. Yes, take risk, and if you get rich (which is optional), spend your money generously on others. We need people to take (bounded) risks. The entire idea is to move the descendants of Homo sapiens away from the macro, away from abstract universal aims, away from the kind of social engineering that brings tail risks to society. Doing business will always help (because it brings about economic activity without large-scale risky changes in the economy); institutions (like the aid industry) may help, but they are equally likely to harm (I am being optimistic; I am certain that except for a few most do end up harming). Courage (risk taking) is the highest virtue. We need entrepreneurs.

High art is researched more than folk art, and museums more than front yards. Yet I would make the case that the minutiae of everyday life deserve our attention; the micro-concerns of the normal round do not make the front pages, but I would hazard a guess that the "trivia" of life, the small things, are probably of more interest to most people most of the time than the macro-concerns of international politics and economics.

The corporatization of U.S. agriculture and the growth of international free markets squeeze growers such that they cannot easily imagine increasing the pay of the pickers or improving the labor camps without bankrupting the farm. In other words, many of the most powerful inputs into the suffering of farmworkers are structural, not willed by individual agents. In this case, structural violence is enacted by market rule and later channeled by international and domestic racism, classism, sexism, and anti-immigrant prejudice. However, structural violence is not just a simple, unidirectional phenomenon; rather, macro social and economic structures produce vulnerability at every level of the farm hierarchy.

Yet, during the last forty years, its contributions have been obscured by the rise of ‘macro-economics’, which seeks causal connections between hypothetically measurable entities or statistical aggregates. These may sometimes, I concede, indicate some vague probabilities, but they certainly do not explain the processes involved in generating them. But because of the delusion that macro-economics is both viable and useful (a delusion encouraged by its extensive use of mathematics, which must always impress politicians lacking any mathematical education, and which is really the nearest thing to the practice of magic that occurs among professional economists) many opinions ruling contemporary government and politics are still based on naive explanations of such economic phenomena as value and prices, explanations that vainly endeavour to account for them as ‘objective’ occurrences independent of human knowledge and aims.

Many models are constructed to account for regularly observed phenomena. By design, their direct implications are consistent with reality. But others are built up from first principles, using the profession’s preferred building blocks. They may be mathematically elegant and match up well with the prevailing modeling conventions of the day. However, this does not make them necessarily more useful, especially when their conclusions have a tenuous relationship with reality. Macroeconomists have been particularly prone to this problem. In recent decades they have put considerable effort into developing macro models that require sophisticated mathematical tools, populated by fully rational, infinitely lived individuals solving complicated dynamic optimization problems under uncertainty. These are models that are “microfounded,” in the profession’s parlance: The macro-level implications are derived from the behavior of individuals, rather than simply postulated. This is a good thing, in principle. For example, aggregate saving behavior derives from the optimization problem in which a representative consumer maximizes his consumption while adhering to a lifetime (intertemporal) budget constraint.† Keynesian models, by contrast, take a shortcut, assuming a fixed relationship between saving and national income. However, these models shed limited light on the classical questions of macroeconomics: Why are there economic booms and recessions? What generates unemployment? What roles can fiscal and monetary policy play in stabilizing the economy? In trying to render their models tractable, economists neglected many important aspects of the real world. In particular, they assumed away imperfections and frictions in markets for labor, capital, and goods. The ups and downs of the economy were ascribed to exogenous and vague “shocks” to technology and consumer preferences. The unemployed weren’t looking for jobs they couldn’t find; they represented a worker’s optimal trade-off between leisure and labor. Perhaps unsurprisingly, these models were poor forecasters of major macroeconomic variables such as inflation and growth.8 As long as the economy hummed along at a steady clip and unemployment was low, these shortcomings were not particularly evident. But their failures become more apparent and costly in the aftermath of the financial crisis of 2008–9. These newfangled models simply could not explain the magnitude and duration of the recession that followed. They needed, at the very least, to incorporate more realism about financial-market imperfections. Traditional Keynesian models, despite their lack of microfoundations, could explain how economies can get stuck with high unemployment and seemed more relevant than ever. Yet the advocates of the new models were reluctant to give up on them—not because these models did a better job of tracking reality, but because they were what models were supposed to look like. Their modeling strategy trumped the realism of conclusions. Economists’ attachment to particular modeling conventions—rational, forward-looking individuals, well-functioning markets, and so on—often leads them to overlook obvious conflicts with the world around them.

learning—we have learned how to increase productivity, the outputs that can be produced with any inputs. There are two aspects of learning that we can distinguish: an improvement in best practices, reflected in increases in productivity of firms that marshal all available knowledge and technology, and improvements in the productivity of firms as they catch up to best practices. In fact, the distinction may be somewhat artificial; there may be no firm that has employed best practices in every aspect of its activities. One firm may be catching up with another in some dimension, but the second firm may be catching up with the first in others. In developing countries, almost all firms may be catching up with global best practices; but the real difference between developing and developed countries is the larger fraction of firms that are significantly below global best practices and the larger gap between their productivity and that of the best-performing firms. While we are concerned in this book with both aspects of learning, it is especially the learning associated with catching up that we believe has been given short shrift in the economics literature, and which is central to improvements in standards of living, especially in developing countries. But as we noted in chapter 1, the two are closely related; because of the improvements in best practices by the most innovative firms, most other firms are always engaged in a process of catching up. While the evidence of Solow and the work that followed demonstrated (what to many seems obvious) the importance of learning for increases in standards of living, to further explicate the role of learning, the first three sections of this chapter marshal other macro- and microeconomic evidence. In particular, we stress the pervasive gap between best practices and the productivity of most firms. We argue that this gap is far more important than the traditional allocative inefficiencies upon which most of economics has focused and is related to learning—or more accurately, the lack of learning. The final section provides a theoretical context within which to think about the sources of sustained increases in standards of living, employing the familiar distinction of movements of the production possibilities curve and movements toward the production possibilities curve. Using this framework, we explain why it is that we ascribe such importance to learning. Macroeconomic Perspectives There are several empirical arguments that can be brought to bear to support our conclusion concerning the importance of learning. The first is a simple argument: In theory, leading-edge technology is globally available. Thus, with sufficient capital and trained labor (or sufficient mobility for capital and trained labor), all countries should enjoy comparable standards of living. The only difference would be the rents associated with ownership of intellectual property rights and factor supplies. Yet there is an enormous divergence in economic performance and standards of living across national economies, far greater than can be explained by differences in factor supplies.1 And this includes many low-performing economies with high levels of capital intensity (especially among formerly socialist economies) and highly trained labor forces. Table 2.1 presents a comparison of formerly socialist countries with similar nonsocialist economies in the immediate aftermath of the collapse of the state-controlled model of economic activity. TABLE 2.1 Quality of Life Comparisons, 1992–1994 (U.S. $) Source: Greenwald and Khan (2009), p. 30. In most of these cases, at the time communism was imposed after World War II, the subsequently socialist economies enjoyed higher levels of economic development than

Technical analysis is quicker and simpler than fundamental analysis. You may master the core principles of technical analysis just by reading some books, while you must study macro- and micro-economics to perform reliable fundamental analyses.

While the macro- and the micro-evidence hold the promise of a business case, gender equality is not a magic bullet automatically leading to economic progress. This is why, at the end of the day, the case of gender equality must rest on a moral argument. It just is the right thing to do. Full stop.

We're so shit at seeing the Macro, and ultimately it's those macro uncoupling dynamics that matter more than anything else.

1. The chief root of monetary troubles is the scientific authority the Keynesians gave the superstition that increasing the quantity of money can ensure prosperity and full employment. 2. The superstition was fought successfully by economists for two centuries of stable prices during the age of modern industrialism and the gold standard. 3. Before then inflation largely dominated history. 4. Keynes’s (macro-economic) error was to suppose that labour demand and supply can be equated (and unemployment avoided) by managing total demand. Employment depends on demand in each sector of the economy. Managing total demand by expanding money supply created only temporary and therefore unstable employment. 5. A “lost generation” of economists who have learned nothing else continues to offer the quack “full employment” remedy and to win short-term popularity for it. 6. No government, national or international, that wants to remain in office can be expected to limit the quantity of money better than a gold standard or any other (semi-) automatic system because in practice it succumbs to sectional pressures for additional cheap money and expenditure. 7. The gold standard, balanced budgets, fixed exchanges, enabled governments to resist sectional importunities. The removal of these “shackles” has enabled governments to act more irresponsibly. 8. The only hope for stable money and resistance to inflation is to protect money from politics by removing the power of government to require its citizens to use its money as the only legal tender. 9. Government would then not inflate its supply, because it would be forsaken for other currencies. 10. Inflation can therefore be stopped by introducing competition in currency. The notion that it is a proper function of government to issue the national currency is false. Citizens should be free to use and refuse any currencies they wish: politicians would then have to limit their quantities. Then inflation would be avoided.

Like Putin, from his early days in power Erdoğan created a loyal web of vassals, and gradually transformed the decision-making process for matters concerning the nation’s finances until every economic transaction, from the most micro to the most macro, was in some way connected to him.

The technosphere is described here as if neither history nor social or political dynamics mattered. It does not take into account collective agency or political, economic, and social structures, let alone the evolution of knowledge with its powerful impact on shaping technological systems. Has human technology now reached a stage (or will it any time soon) at which it attains the autonomy of an organism with its own agency - an autopoietic structure reproducing its own organization? Such generalizations tend to overlook some essential features of human interaction with the global environment. For instance, while the biosphere has proven its resilience over the course of at least 3.5 billion years of evolution, the technosphere may turn out to be a rather fragile scaffolding for human existence. While it is quite conceivable that the sum total of the unintended consequences of our actions has developed its own dynamics, even in the age of the Anthropocene escape routes may still be left to us - an observation, however, that does not imply, vice versa, that there will be a guarantee for the existence of an escape route. It rather appears that the dynamics underlying the Anthropocene might well enhance both the challenges with which we are confronted and our opportunities to react to them, leaving the question open as to whether the latter will always be sufficient to match the former. Is it possible, for instance, that geoengineering can intervene in the planetary system to the point that a new state of the planetary system would be reached in which high carbon dioxide concentration, radioactive pollution, and other unintended consequences of industrialization are no longer challenging problems but can be safely kept under control by novel technologies? Given the fact that macro-scale interventions in the Earth system are beyond anything that human engineering has achieved so far, and given the fact that there are still important gaps in our knowledge about our planetary system, we are certainly on the safer side to prioritize, at least for the time being and to the extent that it is possible at all, the preservation of our existing Earth system and damage control.

In virtue ethical terms, if the micro-level of property is about justice for the individual and the meso-level about temperance from the community regarding justice for the individual, the macro-level is about prudence, the society-wide promotion of economic betterment. The competing institutions that emerge to unite the day-to-day interactions of strangers from different communities are the ones that are comparatively less costly. (18)

Property rights are the expectations defined by property, not the content of property. In other words, property effects property rights. The micro- and meso-foundations of property make the macro-level of property rights possible. Such a view challenges the felicitousness of the bundle-of-sticks metaphor, which inverts how humans cognize property. It also means legal realists are wrong on the facts to claim that there is no prior normative conception of property. (21)

The Jacor story was all about seeing micro opportunities in macro events. In this case, the macro event was legislation similar to the impact of the Economic Recovery Tax Act of 1981 on NOLs. But I find implications for opportunity everywhere—in world events, economic news, and conversations. I’ve always been on the lookout for big-picture influencers and anomalies that will direct the course of industries and companies.

for an MMT advocate, an employment guarantee should be a permanent feature of the economy, providing the opportunity for everybody ready and willing to work, but unable to find suitable employment, with the opportunity to contribute meaningfully to the quality of life for the community.

Benn is a smart guy. He graduated from an elite college (the University of Virginia) with a degree in economics, and like many in his situation he had ambitions for his career. It didn’t take him long to realize that these ambitions would be thwarted so long as his main professional skills could be captured in an Excel macro. He decided, therefore, he needed to increase his value to the world. After a period of research, Benn reached a conclusion: He would, he declared to his family, quit his job as a human spreadsheet and become a computer programmer. As is often the case with such grand plans, however, there was a hitch: Jason Benn had no idea how to write code. As a computer scientist I can confirm an obvious point: Programming computers is hard. Most new developers dedicate a four-year college education to learning the ropes before their first job—and even then, competition for the best spots is fierce. Jason Benn didn’t have this time. After his Excel epiphany, he quit his job at the financial firm and moved home to prepare for his next step. His parents were happy he had a plan, but they weren’t happy about the idea that this return home might be long-term. Benn needed to learn a hard skill, and needed to do so fast.

Thomas Malthus (1766–1834) had a growth schema with only two factors of production—natural resources and labour—with no allowance for technical progress, capital formation, or gains from international specialization. In 1798, he portrayed the general situation of humanity as one where population pressure put such strains on the ability of natural resources to produce subsistence that equilibrium would be attained only by various catastrophes. His influence has been strong and persistent, largely because of his forceful rhetoric and primitive scaremongering…He would have been very surprised to discover that Britain in 2003 would have only 1.2 per cent of its working population in agriculture and a life expectation of 78 years.

Over the past millennium, world population rose nearly 24-fold, per capita income 14-fold, GDP 338-fold. This contrasts sharply with the preceding millennium, when world population grew by only a sixth, and per capita income fell. From the year 1000 to 1820, growth was predominantly extensive. Most of the GDP increase went to accommodate a four-fold increase in population. The advance in per capita income was a slow crawl—the world average increased only by half over a period of eight centuries. In the year 1000, the average infant could expect to live about 24 years. A third died in the first year of life. Hunger and epidemic disease ravaged the survivors. By 1820, life expectation had risen to 36 years in the west, with only marginal improvement elsewhere. After 1820, world development became much more dynamic. By 2003, income per head had risen nearly ten-fold, population six-fold. Per capita income rose by 1.2 per cent a year: 24 times as fast as in 1000–1820. Population grew about 1 per cent a year: six times as fast as in 1000–1820. Life expectation increased to 76 years in the west and 63 in the rest of the world.

It is important to distinguish between lead and follower countries to understand the dynamics of technological diffusion, and analyse processes of catch-up and falling behind. ‘Lead’ countries are those whose economies operate nearest to the technical frontier; ‘follower’ countries have a lower level of labour productivity (or GDP per capita). Since 1500 there have been four lead countries, northern Italy in the sixteenth century, the Netherlands from the sixteenth century until the Napoleonic wars, when the UK took over. The British lead lasted until around 1890, and the US has been the leader since then.

The order of discovery concerning the materials in the human environment and of the technology that resulted from such discoveries was not haphazard or accidental. The order of discovery followed a logical order and an order that it had to follow. The easier discoveries were made before the harder discoveries; discoveries that were dependent upon prior discoveries being made, were only made after those discoveries; and inventions that were not economic or did not meet human needs were not made until they made economic sense or until a need arose. The course of human social and cultural history is written into the structure of the universe.

The first and the most exciting thing for me as someone who has studied growth across countries from a macro perspective was that there is something truly unique about the Indian development model. I call this the ‘precocious development model’, since a precocious child does things far ahead of its time—in both the good and bad sense. Political scientists have often observed that India is a complete outlier in having sustained democracy at very low levels of income, low levels of literacy, with deep social fissures, and with a highly agrarian economy. Almost no country in the world has managed that under these conditions. I think the only continuous democracies have all been small countries (Costa Rica, Barbados, Jamaica, Mauritius and Botswana) with higher levels of literacy and fewer social divisions. The second part of the precocious model is that it entails not just precocious politics but also precocious economics. There are many ways of explaining this precocious economics model, but I focus on two. Most countries grow by either specializing in or exploiting their minerals—as in the old model—and in some cases, exploiting their geography. But most of the post-war growth experiences have come about by becoming manufacturing powerhouses, especially starting with low-skill labour and going up the value-added spectrum. Korea, Taiwan and China are classic examples, specializing in textiles and clothing initially and now becoming major exporters of electronics, cars, IT products, etc.

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