Local Sunspot Equilibria Reconsidered

We generalize the usual notion of local sunspot equilibria. We say such equilibria exist around a steady state of an OLG economy whenever stationary sunspot equilibria of arbitrarily close economies exist within any neighborhood of the steady state. Unlike the usual notion, this generalization allows to address the following identification problem: Can an analyst distinguish empirically small fluctuations due to small shocks to the fundamentals from pure expectations-driven fluctuations? We study conditions under which these generalized local sunspot equilibria exist in OLG economies, and show that they may exist around not only indeterminate but also determinate steady states.     

The Zero Lower Bound and Parameter Bias in an Estimated DSGE Model

This paper examines how and to what extent parameter estimates can be biased in a dynamic stochastic general equilibrium (DSGE) model that omits the zero lower bound (ZLB) constraint on the nominal interest rate. Our Monte Carlo experiments using a standard sticky‐price DSGE model show that no significant bias is detected in parameter estimates and that the estimated impulse response functions are quite similar to the true ones. However, as the frequency of being at the ZLB or the duration of ZLB spells increases, the parameter bias becomes larger and therefore leads to substantial differences between the estimated and true impulse responses. It is also demonstrated that the model missing the ZLB causes biased estimates of structural shocks even with the virtually unbiased parameters. Copyright © 2015 John Wiley & Sons, Ltd.     

Automatic Selection of Classification Algorithms for Non-Experts Using Meta-Features

With the arrival of big-data society, methods for classifying real-world problems have attracted much attention for researchers and developers in various fields. In recent years, much effort has been devoted for improving performances of classification algorithms by adding functions or modifying their weaknesses. However, since a large variety of classification algorithms has been available, it is difficult for non-experts to find classification algorithms that achieve good results on a given data set. Therefore, if there is a system which automatically selects the best classification algorithm for a given data set, non-experts would receive various benefits such as saving time and effort. This paper presents a system of predicting the best possible classification algorithm for a given data set with respect to the accuracy. To the best of our knowledge, this is the first approach focused on predicting the best one. The main target users of the proposed system are non-experts who do not have knowledge and experience in data mining. The proposed system utilizes useful meta-features selected from existing recta-features to increase the performance of the prediction. The feature selection is conducted by a wrapper approach with the genetic search algorithm. In the proposed system, K-nearest neighbor algorithm is used to learn the selectedmeta-features and build a classification model for predicting future data. Experiments using 58 real-world data sets show that the proposed system predicted the best classification algorithm with 60.34% accuracy from the top five in 30 classification algorithms.     

Price Fluctuations and Growth Patterns in Singapore's Trade, 1831–1913

Using a newly created trade price index, this paper determines the real growth rate of Singapore's trade during 1831–1913. We find that Singapore's trade grew between 1831 and 1873 at a higher rate than during the later period. An analysis of the terms of trade and purchasing power parity reveals that the growth pattern of Singapore's entrepôt trade changed after 1850 from growth fuelled by transit trade of industrial products to balanced growth between regional imports and exports. This change resulted from the operation of the international monetary system, which enhanced market integration between Britain and Southeast Asia via Singapore.     

The measurement of waste with nonconvex technology

The measurement of waste problem is reconsidered with the generalization that nonconvex production technologies are allowed. A general equilibrium measure of waste allowing for nonconvexity in production is derived by extending the contributions by Debreu (1954) and Diewert (1981, 1985).     

The Structure of Sunspot Equilibria: The Role of Multiplicity

This paper examines the structure of sunspot equilibria in a standard two period exchange economy with real assets. We show that for a generic choice of utility functions and endowments, there exists an open set of real asset structures whose payoffs are independent of sunspots such that the economy with this asset structure has a regular sunspot equilibrium. An important implication of our result is that the multiplicity of non-sunspot equilibria is not necessary for the existence of sunspot equilibria. Our technique is general and can be applied to show the existence of sunspot equilibria in other frameworks.     

An experimental approach to the effectiveness of an incentive system against moral hazard in the insurance market

Although traditional Japanese insurance theory has tended to assume the basic altruism of policyholders, this assumption may not be warranted. Many people might be opportunists rather than altruists. So in the actual insurance market, moral hazard may occur not accidentally but naturally. Without effective incentive mechanisms, policyholders may deviate from their original purpose. It is important to design penalties as negative incentives for the control and prevention of moral hazard. We test these propositions here by means of a game theory and questionnaire. The reason why we use a game theory and carry out the questionnaire is that it is not suitable to apply the econometric model to collect reliable data about moral hazard.     

Interim efficient allocations under uncertainty

This paper considers an exchange economy under uncertainty with asymmetric information. Uncertainty is represented by multiple priors and posteriors of agents who have either Bewley's incomplete preferences or Gilboa-Schmeidler's maximin expected utility preferences. The main results characterize interim efficient allocations under uncertainty; that is, they provide conditions on the sets of posteriors, thus implicitly on the way how agents update the sets of priors, for non-existence of a trade which makes all agents better off at any realization of private information. For agents with the incomplete preferences, the condition is necessary and sufficient, but for agents with the maximin expected utility preferences, the condition is sufficient only. A couple of necessary conditions for the latter case are provided.     

Bootstrapping Smooth Functions of Slope Parameters and Innovation Variances in VAR(∞) Models*

It is common to conduct bootstrap inference in vector autoregressive (VAR) models based on the assumption that the underlying data‐generating process is of finite‐lag order. This assumption is implausible in practice. We establish the asymptotic validity of the residual‐based bootstrap method for smooth functions of VAR slope parameters and innovation variances under the alternative assumption that a sequence of finite‐lag order VAR models is fitted to data generated by a VAR process of possibly infinite order. This class of statistics includes measures of predictability and orthogonalized impulse responses and variance decompositions. Our approach provides an alternative to the use of the asymptotic normal approximation and can be used even in the absence of closed‐form solutions for the variance of the estimator. We illustrate the practical relevance of our findings for applied work, including the evaluation of macroeconomic models.