A Simple Measure of Economic Complexity

The conventional view on economic development simplifies a country’s production to one aggregate variable, GDP. Yet product diversification matters for economic development, as recent, data-driven, “economic complexity” research suggests. A country’s product diversity reflects the country’s diversity of productive knowhow, or “capabilities”. Researchers derive from algorithms (inspired by network theory) metrics that measure the number of capabilities in an economy, notably the Economic Complexity Index (ECI), argued to predict economic growth better than traditional variables such as human capital, and the country Fitness index. This paper offers an alternative economic complexity measure (founded on information theory) that derives from a simple model of production as a combinatorial process whereby a set of capabilities combine with some probability to transform raw materials into a product. A country’s number of capabilities is given by the logarithm of its product diversity, as predicts the model, which also predicts a linear dependence between log-diversity, ECI, and log-fitness. The model’s predictions fit the empirical data well; its informational interpretation, we argue, is a natural theoretical framework for the complexity view on economic development

News-driven Expectations and Volatility Clustering

Financial volatility obeys two well-established empirical properties: it is fat-tailed (power-law distributed) and it tends to be clustered in time. Many interesting models have been proposed to account for these regularities, notably agent-based computational models, which typically invoke complicated mechanisms, however. It can be shown that trend-following speculation generates the power law in an intrinsic way. But this model cannot exaplain clustered volatility. This paper extends the model and offers a simple explanation for clustered volatility: the impact of exogenous news on traders’ expectations. Owing to the famous no-trade results, rational expectations, the dominant model of news-driven expectations, is hard to reconcile with the incessant high-frequency trading behind the volatility clustering. The simplest alternative model of news-driven expectations is to assume that traders have prior views about the market (an asset’s future price change or its present value) and then modify their views with the advent of a news. This simple news-driven random walk of traders’ expectations explains volatility clustering in a generic way. Liquidity plays a crucial role in this dynamics of volatility, which is emphasized in a discussions section

Beware the Gini Index! A New Inequality Measure

The Gini index underestimates inequality for heavy-tailed distributions: for example, a Pareto distribution with exponent 1.5 (which has infinite variance) has the same Gini index as any exponential distribution (a mere 0.5). This is because the Gini index is relatively robust to extreme observations; while a statistic’s robustness to extremes is desirable for data potentially distorted by outliers, it is misleading for heavy-tailed distributions, which inherently exhibit extremes. We propose an alternative inequality index: the variance normalized by the second moment. This ratio is more stable (hence more reliable) for large samples from an infinite-variance distribution than the Gini index paradoxically. Moreover, the new index satisfies the normative axioms of inequality measurement; in particular, it is decomposable into inequality within and between subgroups, unlike the Gini index

News-Driven Expectations and Volatility Clustering

Financial volatility obeys two fascinating empirical regularities that apply to various assets, on various markets, and on various time scales: it is fat-tailed (more precisely power-law distributed) and it tends to be clustered in time. Many interesting models have been proposed to account for these regularities, notably agent-based models, which mimic the two empirical laws through a complex mix of nonlinear mechanisms such as traders switching between trading strategies in highly nonlinear way. This paper explains the two regularities simply in terms of traders’ attitudes towards news, an explanation that follows from the very traditional dichotomy of financial market participants, investors versus speculators, whose behaviors are reduced to their simplest forms. Long-run investors’ valuations of an asset are assumed to follow a news-driven random walk, thus capturing the investors’ persistent, long memory of fundamental news. Short-term speculators’ anticipated returns, on the other hand, are assumed to follow a news-driven autoregressive process, capturing their shorter memory of fundamental news, and, by the same token, the feedback intrinsic to the short-sighted, trend-following (or herding) mindset of speculators. These simple, linear models of traders’ expectations explain the two financial regularities in a generic and robust way. Rational expectations, the dominant model of traders’ expectations, is not assumed here, owing to the famous no-speculation, no-trade results

The Classical Theory of Supply and Demand

This paper introduces and formalizes the classical view on supply and demand, which, we argue, has an integrity independent and distinct from the neoclassical theory. Demand and supply, before the marginal rev-olution, are defined not by an unobservable criterion such as a utility func-tion, but by an observable monetary variable, the reservation price: the buyer’s (maximum) willingness to pay (WTP) value (a potential price) and the seller’s (minimum) willingness to accept (WTA) value (a potential price) at the marketplace. Market demand and supply are the cumulative distri-bution of the buyers’ and sellers’ reservation prices, respectively. This WTP-WTA classical view of supply and demand formed the means whereby mar-ket participants were motivated in experimental economics although ex-perimentalists (trained in neoclassical economics) were not cognizant of their link to the past. On this foundation was erected a vast literature on the rules of trading for a host of institutions, modern and ancient. This pa-per documents textually this reappraisal of classical economics and then formalizes it mathematically. A follow-up paper will articulate a theory of market price formation rooted in this classical view on supply and demand and in experimental findings on market behavior

Classical Theory of Competitive Market Price Formation

We offer an information theory of market price formation, formalizing and elaborating on an old, implicit, classical tradition of supply and demand based on buyers’ and sellers’ mone-tary valuations of commodities (formally their reservation prices) and competition as a multilat-eral higgling and bargaining process. The early laboratory market experiments, as it turns out with hindsight, established the remarkable stability, efficiency, and robustness of the old view of competitive price discovery, and not the neoclassical price theory (based on individual utility and profit maximization for given prices). Herein, we present a partial-equilibrium version of the the-ory in which wealth is implicitly constant, and reservation values are fixed, as in the early exper-iments, formulating an information interpretation à la Shannon that corresponds with modern notions of the pricing system as an information signaling system. Competitive equilibrium price, we show, conveys maximum information about the distribution of traders’ valuations. We illus-trate the theory as it applies to a few market conditions (notably a non-clearing market case) and institutions (posted-price market, English auction, double auction, sealed-bid call market)

Perishable Goods versus Re-tradable Assets: A Theoretical Reappraisal of a Fundamental Dichotomy

Although various typologies of goods are commonly adopted in economics, one stood out in market experiment results contrasting market stability and efficiency with market instability: non-durable, or perishable, goods (Smith, 1962) versus durable re-tradable assets (Smith et al., 1988; Dickhaut et al., 2012; S. D. Gjerstad et al., 2015). This dichotomy of goods also proved central for understanding macroeconomic instability more broadly: about 75% of consumer spending is bought for final consumption, and is a rock of stability; instability arises from the other 25% re-tradable goods, most prominently, houses (S. D. Gjerstad & Smith, 2014). In this chapter, we revisit this well-known but underappreciated dichotomy of goods in the light of our theory of classical competitive price formation. We also emphasize the fundamental and unifying nature of the concept of asset re-tradability as a general concept in finance: the concept of asset re-tradability allows for a simple, transparent, and unified treatment of the no-arbitrage and no-trade theorems of neoclassical finance

Adam Smith’s Theory of Value: A Reappraisal of Classical Price Discovery

The relevance of Adam Smith for understanding human morality and sociality is recognized in the growing interest in his work on moral sentiments among scholars of various academic backgrounds. But, paradoxically, Adam Smith’s theory of economic value enjoys a less prominent stature today among economists, who, while they view him as the “father of modern economics”, considered him more as having had the right intuitions about a market economy than as having developed the right concepts and the technical tools for studying it. Yet the neoclassical tradition, which replaced the classical school around 1870, failed to provide a satisfactory theory of market price formation. Adam Smith’s sketch of market price formation (Ch. VII, Book I, Wealth of Nations), and more generally the classical view of competition as a collective higgling and bargaining process, as this paper argues, offers a helpful foundation on which to build a modern theory of market price formation, despite any shortcomings of the original classical formulation (notably its insistence on long-run, natural value). Also, with hindsight, the experimental market findings established the remarkable stability, efficiency, and robustness of the old view of competition, suggesting a rehabilitation of classical price discovery. This paper reappraises classical price theory as Adam Smith articulated it; we explicate key propositions from his price theory and derive them from a simple model, which is an elementary sketch of the authors’ more general theory of competitive market price formation

Classical Economics: Lost and Found

We argue that neoclassical value theory suffers from a more basic and serious logical indeterminacy, which is inherent in the axiom of price-taking behavior, and which renders price dynamics indeterminate before inquiring as to its stability. If everyone in the economy takes price as given, whence come these prices? Who is giving these prices? Jevons avoided the indeterminacy by assuming that people must have complete information on supply and demand, and the consequent equilibrium prices—‘perfect competition.’ Walras in effect imported an external agent who found the prices by trial-and-error-correction (the Walrasian Auctioneer). Paradoxically, both approaches had the potential better to serve central planning, than a market economy. A theory based on price taking agents required some agency for giving prices. Indeed, the fit with socialism was rigorously established by influential neoclassical authors starting from Wieser (1893, ch. VI) and Pareto (1897, 364-371; 1909, 362-364), and, more formally during the Socialist Calculation Debate, by Barone ([1908] 1935), Lerner (1934), and Lange (1936, 1937). The paradox is hidden in the idea of ‘perfect competition’ a passive treatment of individuals who are not even interacting, let alone interacting in a rivalrous manner. ‘Perfect competition’ is the negation of any real competition, as Hayek (1948) emphasized

A Classical Model of Speculative Asset Price Dynamics

In retrospect, the experimental findings on competitive market behavior called for a revival of the old, classical, view of competition as a collective higgling and bargaining pro-cess (as opposed to price-taking behaviors) founded on reservation prices (in place of the utility function). In this paper, we specialize the classical methodology to deal with specula-tion, an important impediment to price stability. The model involves typical features of a field or lab asset market setup and lends itself to an experimental test of its specific predic-tions; here we use the model to explain three general stylized facts, well established both empirically and experimentally: the excess, fat-tailed, and clustered volatility of speculative asset prices. The fat tails emerge in the model from the amplifying nature of speculation, leading to a random-coefficient autoregressive return process (and power-law tails); the volatility clustering is due to the traders’ long memory of news; bubbles are a persistent phenomenon in the model, and, assuming the standard lab present value pattern, the bub-ble size increases with the proportion of speculators and decreases with the trading horizon