Anomalies in Economics and Finance

The term “anomaly” played a crucial role in Thomas Kuhn’s characterization of scientific progress. For Kuhn, an anomaly is a puzzle which challenges an accepted paradigm. Puzzles only achieve anomalous status once an alternative paradigm becomes available which allows explanation of the puzzle. Anomalies were introduced into the finance literature by Michael Jensen but more as resolvable puzzles than Kuhnian anomalies. They entered economics via Richard Thaler who saw behavioural economics as the alternative to the neoclassical paradigm. Both authors use the term anomaly in a deliberately Kuhnian manner. Kuhn formulated his ideas by looking back across the history of physics. By contrast, behavioural economists use Kuhn’s concepts in a forward-looking manner as a marketing tool for their ideas.anomaly, behavioural, effects.

Commodity Speculation and Commodity Investment

I distinguish between speculation and index-based investment in commodity futures stressing the differing motivations of the two groups and the differing instruments that they use. I discuss the amounts of money deployed in these activities. I document evidence of extrapolative behaviour in metals prices, consistent with speculation affecting prices, and show that in at least one market (soybeans) index-based investment has a significant and persistent price impact.Commodities, Speculation, Asset Allocation

How to Understand High Food Prices

Commodity price booms are best explained by macroeconomic rather than market-specific factors. I argue that the rise in food prices over 2007 and the first half of 2008 should be seen as part of the wider commodity boom which is largely the result of rapid economic growth in China and throughout Asia in a context of loose money and in which, because of previous low investment, supply was inelastic. The demand for grains and oilseeds as biofuel feedstocks was the main cause of the price rise but macroeconomic and financial factors explain its extent. The futures market may be an important monetary transmission mechanism, but it is commodity investors, not speculators, who, by investing in commodities as an asset class, may have generalized prices rises across markets.Food prices, commodity prices, money, futures markets

Commonality in the LME aluminium and copper volatility processes through a Figarch lens

We consider dynamic representation of spot and three month aluminium and copper volatilities. These are the two most important metals traded in the London Metal Exchange (LME). They share common business cycle factors and are traded under identical contract specifications. We apply the bivariate FIGARCH model which allows parsimonious representation of long memory volatility processes. Our results show that spot and three month aluminium and copper volatilities follow long memory processes, that they exhibit a common degree of fractional integration and that the processes are symmetric. However, there is no evidence that the processes are fractionally cointegrated. This high degree of commonality may result from the common LME trading process

Globalization and International Commodity Trade with Specific Reference to the West African Cocoa Producers

Liberalization of tropical agricultural markets has brought globalization, in the sense that all producers now face world rather than domestic prices. Producer prices have tended to rise as a share of fob prices as intermediation costs and tax has declined. However, in conjunction with inelastic demand, the downward shift of the aggregate supply curve results in lower world prices. Farmers therefore get a higher share of a lower price. Cocoa is the market where these changes have been most pronounced. The incidence of the liberalization benefits in cocoa is largely on developed country consumers at the expense of the governments of the exporting countries and farmers in non-liberalizing (non-African) countries. Farmers in liberalized African markets are broadly neither better nor worse off.

Models for Non-Exclusive Multinomial Choice, with Application to Indonesian Rural Households

Textbook discussions of discrete choice modelling focus on binomial and multinomial choice models in which agents select a single response. We consider the situation of non-exclusive multinomial choice. The widely used Marginal Logit Model imposes independence and has other disadvantages. We propose two models which account for non-exclusive and dependent multiple responses and require at least one response. In the first and simpler specification, the Poisson-multinomial, households first choose the number of responses to a specific shock, and then the specific choices are identified to maximize household utility conditional on the former choice. The second specification, the threshold-multinomial, generalizes the standard multinomial logit model by supposing that agents will choose more than one response if the utility they derive from other choices is “close” to that of the utility-maximizing choice. We apply these two approaches to reported responses of rural Indonesian rural households to demographic and economic shocks.Discrete choice models, Marginal logit, Shocks, Risk coping strategies

Representation in Econometrics: A Historical Perspective

Measurement forms the substance of econometrics. This chapter outlines the history of econometrics from a measurement perspective - how have measurement errors been dealt with and how, from a methodological standpoint, did econometrics evolve so as to represent theory more adequately in relation to data? The evolution is organized in terms of four phases: 'theory and measurement', 'measurement and theory', 'measurement with theory' and 'measurement without theory'. The question of how measurement research has helped in the advancement of knowledge advance is discussed in the light of this history.Econometrics, History, Measurement error

Bivariate FIGARCH and Fractional Cointegration

We consider the modelling of volatility on closely related markets. Univariate fractional volatility (FIGARCH) models are now standard, as are multivariate GARCH models. In this paper we adopt a combination of the two methodologies. There is as yet little consensus on the methodology for testing for fractional cointegration. The contribution of this paper is to demonstrate the feasibility of estimating and testing cointegrated bivariate FIGARCH models. We apply these methods to volatility on the NYMEX and IPE crude oil markets. We find a common order of fractional integration for the two volatility processes and confirm that they are fractionally cointegrated. An estimated error correction FIGARCH model indicates that the preponderant adjustment is of the IPE towards NYMEX.FIGARCH, Fractional Cointegration, ECM

Managing Agricultural Price Risk in Developing Countries

We survey the experience of risk management in developing country agricultural supply chains. We focus on exposure, instruments, impediments to access and developing country futures markets. We draw on lessons from experience over the past two decades.Commodities, Risk Management, Developing Countries