By James H. Nolt
Most critics of textbook economics today adhere to some rival economic school, including Marxian, post-Keynesian, neo-Ricardian, Austrian, information, and evolutionary economics. Each of these schools also has internal debates among rival adherents, but what they all have in common is that they reject much of neoclassical textbook economics. Which of them is right?
All of the schools offer some useful points, but none has a comprehensive conceptual system adequate to understanding political economy today. I draw on elements from each of them, but also try to unite critical economists around a new common core of corporatist political economy. I add a few simple but powerful concepts missing from all the existing schools of economics, or, as I prefer, political economy.
The most obvious failure of all versions of economics, including these critical ones, is accounting systematically for private power and strategy. Some of them mention private power in some aspect. For example, Marxism talks much about the class struggle between workers and capitalists. This is the area of private power Marxism takes seriously. Neo-Ricardians also consider this power as determinative of the distribution of social product between workers and capitalists.
Post-Keynesians, including Joan Robinson and Edward Chamberlain, founded another study of private power: monopoly and oligopoly theory. Their work in this area, in a truncated form, is even incorporated into the later chapters of modern textbooks, though it is treated as an exception rather than the rule and ignored in most economic analysis, where “perfect market” assumptions are preferred for their mathematical simplicity. This effort focused mainly on what I call pricing power. It does not have much to say about financial or credit power.
Information economics highlights the asymmetries of power that derive from control of or access to private information. Joseph Stiglitz is one of its pioneers. It opposes the perfect-market assumption of accurate and complete information available equally to all. Asymmetric control of information is indeed a fundamental element of private power, but many of the most cited examples of information power concern relatively trivial issues rather than detailing all of its uses in its most potent area of application: finance.
Financial power and strategy, like power and strategy in war, depend on manipulating information. Financial reform efforts, recognizing this, often focus on “transparency” as a goal for minimizing financial power and increasing fairness. Yet transparency in finance can only go so far. It runs up against the privacy rights of investors and financial institutions to conduct their transactions and trades without real-time public scrutiny. Complete transparency, or a real democracy of information, would doom the most profitable financial operations.
My brand of corporatist political economy criticizes all economic thinking that does not put private power and strategy front and center. Most of economic thinking, to me, is like telling the history war without mentioning generals or decisive battles. It is filled with routine and mechanical relationships as if strategic action does not occur. Contrast that with really incisive analysis by writers such as Yves Smith, whose book Econned was one of the best analyses of the rigged games that led to the 2008 world economic crises.
Whenever you criticize economists for their lack of strategic thinking, they are quick to mention game theory. Never mind that game theory is largely an afterthought, playing little role in any real economic analysis. Game theory is merely a heuristic device to suggest how players might behave if a situation were like one of a handful of stylized games. It is a purely deductive exercise, not an empirical one.
I find game theory among the most arid and sterile conceptual schemes of economics. Yet it shares with other forms of economic modeling a focus on routine scenarios easy to model in characteristic ways. Game theory suffers from the extraordinary limitations of the ways games can be specified. The rules are known in advance by all players. The payoffs are known as well. The only mystery is what the players—almost always only two—might do next among a limited and specified set of options, usually binary.
Real corporate strategy is not like that. Entrepreneurs are relentlessly innovative, always striving to find new ways to rig games in their favor. The most typical real power games involve asymmetric information: One or more players think they are playing by one set of rules, and one or more powerful players are rigging the rules covertly so that the rules and the payoffs are nothing like the expectations of most players who lack power and accurate strategic information.
Learning about strategic exercise of private power is not easy because it is not taught in any typical university curriculum. Economics does not teach it, political science does not teach it, and even finance courses do not teach it. None of these academic disciplines explain how real power games are played because all of them start with false conceptual schemes that minimize or ignore private power and strategy.
Economics ignores private power by teaching what I call the myth of the market, assuming that there exists some market realm wherein power does not intrude. This is nonsense. All prices are political, not the least because all prices are affected by the wage struggle (or class struggle, as Marxists would say), by pricing power, and by financial power (the power to advance or deny credit).
Relative rates of inflation—that is, which prices are rising—depend on where credit is being expanded and where it is being contracted. Since the power to allocate credit is primarily a private power, even in nominally socialist countries like China, price levels, exchange rates, terms of trade, asset prices, and the business cycle are all influenced if not determined by the exercise of private power. Models are doomed to fail when they deny private strategic action and treat the economy like a hydraulic machine.
Many trained in the methodology of economics will reject what I am saying as “unscientific” because they think models with unrealistic conceptual foundations are necessary to be simple enough to process masses of data efficiently. But no matter how much data you process, if you are blinded by wrong concepts, you can never make sense of it. This is the enormous mistake that will cause great errors and injustices again and again in this era of fascination with “big data.” Big data analyzed without correct concepts amount to just mountains of garbage.
Perhaps it is a mystery to many where correct concepts come from and how we can tell which ones are more correct. That is a philosophical question I will save for next time, using a practical example of a major conceptual failure to illustrate my point.
James H. Nolt is a senior fellow at World Policy Institute and an adjunct associate professor at New York University.
[Photo courtesy of waldryano]