Predicting how People Play Games: a Simple Dynamic Model of Choice.

We use the model developed in Sarin and Vahid (1999, GEB) to explain the experiments reported in Erev and Roth (1998, AER). The model supposes that players maximize subject to their "beliefs" which are non-probabilistic and scalar-valued. They are intended to describe the payoffs the players subjectively assess they will obtain from a strategy. In an earlier paper (Sarin and Vahid (1997) we showed that the model predicted behaviour in repeated coordination games remarkably well, and better than equilibrium theory of reinforcement learning models. In this paper we show that the same one-parameter model can also explain behaviour in games with a unique mixed strategy Nash equilibrium better than alternative models. Hence, we obtain further support for the simple dynamic model.Game Theory, Probability

The Importance Of Common Cyclical Features in VAR Analysis: A Monte-Carlo Study.

Despite the commonly held belief that aggregate data display short-run comovement, there has been little discussion about the econometric consequences of this feature of the data. We use exhaustive Monte-Carlo simulations to investigate the importance of restrictions implied by common-cyclical features for estimates and forecasts based on vector autoregressive models.Reduced rank models; model selection criteria; forecasting; variance decomposition

Strategy Similarity and Coordination.

This paper introduces similarity among strategies in the payoff assessment model of choice (Sarin and Vahid (1999, GEB)). The assessments of strategies that are more similar to the chosen strategy are updated more similarly to the chosen strategy. We use this model to explain a recent experiment.Econometric analysis of experimental data; Adaptive learning; Similarity; Coordination games; Payoff assessments without probabilities

Market Architecture and Nonlinear Dynamics of Australian Stock and Future Indices.

This paper studies the All Ordinaries Index in Australia, and its futures contract known as the Share Price Index. We use a new form of smooth transition model to account for a variety of nonlinearities caused by transaction costs and other market/data imperfections, and given the recent interest in the effects of market automation on price discovery, we focus on how the nonlinear properties of the basis and returns have changed, now that floor trading in futures contract has been replaced by electronic trading.Arbitrage; Electronic trading; Mean reversion; Nonlinear error correction; Smooth transition models; Thresholds; Transaction Costs

The Missing Link: Using the NBER Recession Indicator to Construct Coincident and Leading Indices of Economic Activity.

We use the information content in the decisions of the NBER Business cycle Dating Committee to construct coincident and leading indices of economic activity for United States. Specifically, we use canonical correlation analysis to filter out the noisy information contained in the coincident series. Finally, to construct our preferred coincident index of the U.S. business cycle, we take account of measurement error in the commonly used coincident series by using instrumental-variable methods. The resulting index is a simple linear combination of four coincident series that encompassed currently popular coincident indices.Coincident and Leading Indicators; Business Cycle; Canonical Correlation; Instrumental Variable Probit; Encompassing

Upper Bounds to the Performance of Cooperative Traffic Relaying in Wireless Linear Networks

Wireless networks with linear topology, where nodes generate their own traffic and relay other nodes' traffic, have attracted increasing attention. Indeed, they well represent sensor networks monitoring paths or streets, as well as multihop networks for videosurveillance of roads or vehicular traffic. We study the performance limits of such network systems when (i) the nodes' transmissions can reach receivers farther than one-hop distance from the sender, (ii) the transmitters cooperate in the data delivery, and (iii) interference due to concurrent transmissions is taken into account. By adopting an information-theoretic approach, we derive analytical bounds to the achievable data rate in both the cases where the nodes have full-duplex and half-duplex radios. The expressions we provide are mathematically tractable and allow the analysis of multihop networks with a large number of nodes. Our analysis highlights that increasing the number of coop- erating transmitters beyond two leads to a very limited gain in the achievable data rate. Also, for half-duplex radios, it indicates the existence of dominant network states, which have a major influence on the bound. It follows that efficient, yet simple, communication strategies can be designed by considering at most two cooperating transmitters and by letting half-duplex nodes operate according to the aforementioned dominant state

Capturing the Shape of Business Cycles with Nonlinear Autoregressive Leading Indicator Models.

This paper studies linear and linear autoregressive leading indicator models of business cycles in OECD countries. The models use the spread between short-term and long-term interest rates as leading indicators for GDP, and their success in capturing business cycles gauged by the non-parametric procedures developed by Harding and Pagan (2001). Our preliminary findings indicate that bivariate nonlinear models of output and the interest rate spread can successfully capture the shape of the business cycle. In particular, they can capture the features of recession and the deviation of the actual path of the cycles from a triangular approximation to this path, both characteristics that other models of GDP fail to reproduce.Business Cycles; Leading Indicators; Nonlinear Models; Yield Spread

Does International Trade Synchronize Business Cycles?

This paper studies the relationship between international trade and output fluctuations. The authors find evidence that the business cycles of countries that are more open to international trade are more likely to by synchronized with the business cycles of their major trading partners. A detailed study of the South Korean case shows that while business cycles are related to openness, the diversification of export destinations seems to weaken these links. The authors find no relationship between openness and output volatility.Coherence; Volatility; Business Cycles; Time Series

VAR(MA), What is it Good For? More Bad News for Reduced-form Estimation and Inference

It is common practice to use reduced-form vector autoregression (VAR) models, or more generally vector autoregressive moving average (VARMA) models, to characterize the dynamics in observed data and to identify innovations to the macroeconomy in some economically meaningful way. We demonstrate that neither approach|VAR or VARMA|are suitable reduced form guides to \reality", if reality were induced by some underlying structural DSGE model. We conduct such a thought experiment across a wide class of DSGE structures that imply particular VARMA data generating processes (DGPs). We find that with the typical small samples for macroeconomic data, the MA component of the fitted VARMA models is close to being non-identified. This in turn leads to an order reduction when identifying the lag structures of the VARMA models. As a result, VARMA models barely show any advantage over VARs using realistic sample sizes. However, the VAR remains a truly misspecified approximation. The VAR's performance deteriorates, in contrast to the VARMA's, as we enlarge the sample size generated from the true DGPs