What's the Point of Reciprocal Trade Negotiations? Exports, Imports, and Gains from Trade

This paper explains why trade-policy makers may prefer reciprocal trade negotiations (RTN) to unilateral tariff reductions (UTR) for economic reasons. It answers puzzles like "Why WTO reciprocity?" and strengthens the unncecessarily weak case made for the WTO by those who downplay or dismiss benefits from foreign tariff reductions (FTR). RTN is superior to UTR because it provides economic benefits that UTR cannot -- namely, FTR benefits which are clearer than potentially important UTR benefits: Whereas each policy offers efficiency gains, any terms-of-trade effect of UTR generally detracts from these gains, while any terms-of-trade effect of FTR is typically beneficial (especially for a small price-taking country) with this benefit augmenting FTR's efficiency gains. Moreover, benefits from reductions in foreign barriers may come from several sources; they are not solely the result of terms-of-trade improvement -- or economies of scale (the two benefits already noted in the literature, though often dismissed). E.g. with foreign NTB elimination, possible home benefits are shown even with rising costs and terms-of-trade deterioration. RTN is also superior to UTR because, by eliminating protection in either NTB or tariff form, RTN provides an escape from not only a terms-of-trade prisoners' dilemma, but many other previously unrecognized prisoners' dilemmas, including one in international rent transfers, and several others with no economies-of-scale or terms-of-trade motivation. If reciprocity is an option, but only in a narrower CU or FTA form, such reciprocity may still be superior to UTR, or it may be inferior; theory cannot unambiguously rank these.

Eliminating unpredictable variation through iterated learning

Human languages may be shaped not only by the (individual psychological) processes of language acquisition, but also by population-level processes arising from repeated language learning and use. One prevalent feature of natural languages is that they avoid unpredictable variation. The current work explores whether linguistic predictability might result from a process of iterated learning in simple diffusion chains of adults. An iterated artificial language learning methodology was used, in which participants were organised into diffusion chains: the first individual in each chain was exposed to an artificial language which exhibited unpredictability in plural marking, and subsequent learners were exposed to the language produced by the previous learner in their chain. Diffusion chains, but not isolate learners, were found to cumulatively increase predictability of plural marking by lexicalising the choice of plural marker. This suggests that such gradual, cumulative population-level processes offer a possible explanation for regularity in language

Constraining generalisation in artificial language learning : children are rational too

Successful language acquisition involves generalization, but learners must balance this against the acquisition of lexical constraints. Examples occur throughout language. For example, English native speakers know that certain noun-adjective combinations are impermissible (e.g. strong winds, high winds, strong breezes, *high breezes). Another example is the restrictions imposed by verb subcategorization, (e.g. I gave/sent/threw the ball to him; I gave/sent/threw him the ball; donated/carried/pushed the ball to him; * I donated/carried/pushed him the ball). Such lexical exceptions have been considered problematic for acquisition: if learners generalize abstract patterns to new words, how do they learn that certain specific combinations are restricted? (Baker, 1979). Certain researchers have proposed domain-specific procedures (e.g. Pinker, 1989 resolves verb subcategorization in terms of subtle semantic distinctions). An alternative approach is that learners are sensitive to distributional statistics and use this information to make inferences about when generalization is appropriate (Braine, 1971). A series of Artificial Language Learning experiments have demonstrated that adult learners can utilize statistical information in a rational manner when determining constraints on verb argument-structure generalization (Wonnacott, Newport & Tanenhaus, 2008). The current work extends these findings to children in a different linguistic domain (learning relationships between nouns and particles). We also demonstrate computationally that these results are consistent with the predictions of domain-general hierarchical Bayesian model (cf. Kemp, Perfors & Tenebaum, 2007)

Variability, negative evidence, and the acquisition of verb argument constructions

We present a hierarchical Bayesian framework for modeling the acquisition of verb argument constructions. It embodies a domain-general approach to learning higher-level knowledge in the form of inductive constraints (or overhypotheses), and has been used to explain other aspects of language development such as the shape bias in learning object names. Here, we demonstrate that the same model captures several phenomena in the acquisition of verb constructions. Our model, like adults in a series of artificial language learning experiments, makes inferences about the distributional statistics of verbs on several levels of abstraction simultaneously. It also produces the qualitative learning patterns displayed by children over the time course of acquisition. These results suggest that the patterns of generalization observed in both children and adults could emerge from basic assumptions about the nature of learning. They also provide an example of a broad class of computational approaches that can resolve Baker's Paradox

Hubs and Spokes, and Free Trade in the Americas

This paper compares two possible formats for free trade in the Americas: a system of spokes surrounding a U.S. hub, and a free trade area. The paper identifies the sources of welfare change, and it argues that a country's attitude towards a system depends on whether the arrangement is a complement or a substitute trading club. The paper argues also that rent-seeking activities, and costs of administration and transportation, are likely to be higher in a hub-and-spoke system than in a free trade area.