Towards unveiling individual differences in different stages of information processing: a clustering-based approach

Information Integration Theory (IIT) is a theory of judgment in daily life. Its principal aim is to study the cognitive rules that people use to integrate information when they make a judgment. Traditionally, the identification of individual differences in these qualitatively different integration rules requires individual designs. It also requires the grouping of individuals according to their integration rule, which can be a challenging task, particularly when the data are noisy or when the pattern involves many factors. This paper builds on the cluster analysis tradition for developing a series of clustering procedures that can be implemented for studying, not only individual differences in integration rules, but also individual differences in other stages of information processing. These procedures are intended to simplify the identification of differences in (a) the subjective valuation of information, (b) the integration of the subjective values, and (c) general attitudes before judging.     

Commodity price bubbles and macroeconomics: evidence from the Chinese agricultural markets

This article investigates the links between commodity price bubbles and macroeconomic factors, with an application to the agricultural commodity markets in China from 2006 to 2014. Price bubbles are identified using a newly developed, recursive right‐tailed unit root test. A Zero‐inflated Poisson model is used to analyze the factors contributing to bubbles. Results show that (a) there were speculative bubbles in most Chinese agricultural commodity futures markets during the sample period, though their presence was infrequent; (b) economic growth, money supply, and inflation have positive effects on bubble occurrences, while interest rates have a negative effect; and (c) among all macroeconomic factors considered, economic growth and money supply have the greatest impact in triggering bubbles. Our findings shed new light on the nature and formation of bubbles in the Chinese agricultural commodity markets.     

Housing and the labor market: Time to move and aggregate unemployment

Conventional macro-search models (Mortensen and Pissarides) with unemployment benefits and taxes have been able to account for the variation in unemployment rates across countries but do not account for the role geographic mobility or commuting time might play. We build a model in which both unemployment and mobility rates are endogenous. Our findings indicate that an increase in unemployment benefits and in taxes does not generate a strong decline in mobility but does increase unemployment as in the standard model. We find that with higher commuting costs the effect of housing frictions plays a large role and can generate a substantial decline in mobility.     

How efficient is maize production among smallholder farmers in Zimbabwe? A comparison of semiparametric and parametric frontier efficiency analyses

The controversial Fast Track Land Reform Programme in Zimbabwe that redistributes commercially-owned farmland to smallholder households has caused concerns about the efficiency of agricultural production in the country. In this paper, we estimate the efficiency of resource use among smallholder farmers in Zimbabwe when producing maize, the staple crop in the country. Using both a semiparametric model and a fully parametric stochastic frontier model, we find significant production shortfalls for smallholder maize production. While labor, capital, and land all significantly affect the total output, the estimated mean efficiency score for farms with less than 10 hectares of land (A1) appears to be under 0.75, and for the entire sample (A1 and A2) it ranges between 0.595 and 0.772. There clearly exists a great potential for maize farmers to improve the technical efficiency and increase the total output. Gender and age of the household head, access to extension services, and activities of other crops significantly affect the technical efficiency of smallholder maize production in Zimbabwe. We also find that all farms operate under increasing returns to scale and that the technical efficiency score tends to increase with the level of output.     

From private to public common agency

This note establishes that two propositions in the theory of private common agency by Laussel and Le Breton (J. Econ. Theory 100 (2001) 93) extend to a larger class of games, in which each principal's gross monetary payoff does not depend exclusively on the quantities she receives. A new result is offered to demonstrate that Proposition 4.3 is robust to the introduction of negative externalities. An existing result is reinterpreted to show that Proposition 4.2 is robust to the introduction of positive externalities.     

Macroeconomic forecasting using penalized regression methods

We study the suitability of applying lasso-type penalized regression techniques to macroe-conomic forecasting with high-dimensional datasets. We consider the performances of lasso-type methods when the true DGP is a factor model, contradicting the sparsity assumptionthat underlies penalized regression methods. We also investigate how the methods handle unit roots and cointegration in the data. In an extensive simulation study we find that penalized regression methods are more robust to mis-specification than factor models, even if the underlying DGP possesses a factor structure. Furthermore, the penalized regression methods can be demonstrated to deliver forecast improvements over traditional approaches when applied to non-stationary data that contain cointegrated variables, despite a deterioration in their selective capabilities. Finally, we also consider an empirical applicationto a large macroeconomic U.S. dataset and demonstrate the competitive performance of penalized regression methods.     

Beyond the labour income tax wedge: the unemployment-reducing effect of tax progressivity

In this paper, we argue that, for a given overall level of labour income taxation, a more progressive tax schedule increases employment. From a theoretical point of view, higher progressivity increases overall employment through a wage moderating effect and also because employment of low-paid workers is more elastic to wages. We test these theoretical predictions on a panel of 21 OECD countries over 1998–2008. Controlling for the burden of taxation at the average wage, our estimates suggest that a more progressive tax schedule reduces the unemployment rate and increases the employment rate. These findings are confirmed when we account for the potential endogeneity of both average taxation and progressivity. Overall, our results suggest that policy-makers should not only focus on the detrimental effects of tax progressivity on in-work effort, but also consider the employment-enhancing effects.     

A Comparison of Group Model Building and Strategic Options Development and Analysis

A distinctive tradition within group decision support uses models to structure managerial problems. In this tradition, stakeholders jointly construct a model on their issue of concern in facilitated workshops. In the past decades a wide variety of theoretical insights into and techniques for model-based decision support have been proposed and tested in practical applications. Methods are designed and used by experts; guidelines on their use are not completely spelled out in the literature. This lack of transparency may lead to difficulties in showing the value of methods to researchers in other fields, limit transferability of methods and complicate recombining elements of methods into a multimethodology. In this paper we aim to contribute to transparency by contrasting two model-driven methods: group model building (GMB) and Strategic Options Development and Analysis (SODA). We first develop a framework for comparing methods on a theoretical and practical level. Second, we describe the separate use of each approach, on one and the same issue, with a similar group of participants. By contrasting the choices made in a practical application we clarify process and results in different phases of problem analysis. Our conclusion is that theoretical assumptions of both approaches are more similar than expected. Each method captures different aspects of the problem and in this sense methods may supplement one another: where SODA focuses on the future and identification of actions, GMB aims to create insight into the relation between (past) behavior and structure of the problem. In choosing which element of the methods to use, it is important to realize that each element strikes a particular balance between costs (e.g. time taken from participants or modelers) and benefits (e.g. level of involvement or model verification). For instance, some elements speed up the process but do so at the cost of lowering participants’ involvement. A practical combination of elements of GMB and SODA thus requires the user to assess the relative importance of insight and action as project deliverables, weigh costs and benefits of elements of either method and string these together in a logical sequence that creates the outcomes required.