Equilibrium asset prices and savings of heterogeneous agents in the presence of incomplete markets and portfolio constraints

We study the quantitative properties of a dynamic general equilibrium model in which agents face both idiosyncratic and aggregate income risk, state-dependent borrowing constraints that bind in some but not all periods and markets are incomplete. Optimal individual consumption-savings plans and equilibrium asset prices are computed under various assumptions about income uncertainty. Then we investigate whether our general equilibrium model with incomplete markets replicates two empirical observations: the high correlation between individual consumption and individual income, and the equity premium puzzle. We find that, when the driving processes are calibrated according to the data from wage income in different sectors of the US economy, the results move in the direction of explaining these observations, but the model falls short of explaining the observed correlations quantitatively. If the incomes of agents are assumed independent of each other, the observations can be explained quantitatively.

On the distribution of income and worker assignment under intra-firm spillovers, with an application to ideas and networks

We study the earnings structure and the equilibrium assignment of workers when workers exert intra-firm spillovers on each other.We allow for arbitrary spillovers provided output depends on some aggregate index of workers' skill. Despite the possibility of increasing returns to skills, equilibrium typically exists. We show that equilibrium will typically be segregated; that the skill space can be partitioned into a set of segments and any firm hires from only one segment. Next, we apply the model to analyze the effect of information technology on segmentation and the distribution of income. There are two types of human capital, productivity and creativity, i.e. the ability to produce ideas that may be duplicated over a network. Under plausible assumptions, inequality rises and then falls when network size increases, and the poorest workers cannot lose. We also analyze the impact of an improvement in worker quality and of an increased international mobility of ideas.

Multi-scale integration and predictability in resting state brain activity.

The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales.

Heterogeneous information and trade policy

Protectionism enjoys surprising popular support, in spite of deadweight losses. At thesame time, trade barriers appear to decline with public information about protection.This paper develops an electoral model with heterogeneously informed voters whichexplains both facts and predicts the pattern of trade policy across industries. In themodel, each agent endogenously acquires more information about his sector of employment. As a result, voters support protectionism, because they learn more about thetrade barriers that help them as producers than those that hurt them as consumers.In equilibrium, asymmetric information induces a universal protectionist bias. Thestructure of protection is Pareto inefficient, in contrast to existing models. The modelpredicts a Dracula effect: trade policy for a sector is less protectionist when there ismore public information about it. Using a measure of newspaper coverage across industries, I find that cross-sector evidence from the United States bears out my theoreticalpredictions.

Modeling the forensic two-trace problem with Bayesian networks

The forensic two-trace problem is a perplexing inference problem introduced by Evett (J Forensic Sci Soc 27:375-381, 1987). Different possible ways of wording the competing pair of propositions (i.e., one proposition advanced by the prosecution and one proposition advanced by the defence) led to different quantifications of the value of the evidence (Meester and Sjerps in Biometrics 59:727-732, 2003). Here, we re-examine this scenario with the aim of clarifying the interrelationships that exist between the different solutions, and in this way, produce a global vision of the problem. We propose to investigate the different expressions for evaluating the value of the evidence by using a graphical approach, i.e. Bayesian networks, to model the rationale behind each of the proposed solutions and the assumptions made on the unknown parameters in this problem.

Testing Spatial Autocorrelation in Weighted Networks : the Modes Permutation Test

In a weighted spatial network, as specified by an exchange matrix, the variances of the spatial values are inversely proportional to the size of the regions. Spatial values are no more exchangeable under independence, thus weakening the rationale for ordinary permutation and bootstrap tests of spatial autocorrelation. We propose an alternative permutation test for spatial autocorrelation, based upon exchangeable spatial modes, constructed as linear orthogonal combinations of spatial values. The coefficients obtain as eigenvectors of the standardised exchange matrix appearing in spectral clustering, and generalise to the weighted case the concept of spatial filtering for connectivity matrices. Also, two proposals aimed at transforming an acessibility matrix into a exchange matrix with with a priori fixed margins are presented. Two examples (inter-regional migratory flows and binary adjacency networks) illustrate the formalism, rooted in the theory of spectral decomposition for reversible Markov chains.

Estimating Bayesian decision problems with heterogeneous priors

In many areas of economics there is a growing interest in how expertise andpreferences drive individual and group decision making under uncertainty. Increasingly, we wish to estimate such models to quantify which of these drive decisionmaking. In this paper we propose a new channel through which we can empirically identify expertise and preference parameters by using variation in decisionsover heterogeneous priors. Relative to existing estimation approaches, our \Prior-Based Identification" extends the possible environments which can be estimated,and also substantially improves the accuracy and precision of estimates in thoseenvironments which can be estimated using existing methods.

The dynamics of research networks in Brite-Euram

Network formation within the BRITE--EURAM program is investigated.Wedescribe the role of the hub of the network, which is defined as the setofmain contractors that account for most of the participations. We studytheeffects that the conflict of objectives within European research fundingbetween pre-competitive research vs. European cohesion has on theformationof networks and on the relationship between different partnersof the network. \\A panel data set is constructed including the second and third frameworkof theBrite--Euram program. A model of joint production of research results isusedto test for changes in the behavior of partners within the twoframeworks. \\The main findings are that participations are very concentrated, that isasmall group of institutions account for most of the participations, butgoingfrom the second to the third framework the presence of subcontractorsand singleparticipants increases substantially. This result is reinforced by the factthat main contractors receive smaller spill-ins within networks, butspill-insincrease from the second to the third framework.

Competitive location and pricing on networks

In this paper we consider a location and pricing model for a retail firm that wants to enter a spatial market where a competitor firm is already operating as a monopoly with several outlets. The entering firms seeks to determine the optimal uniform mill price and its servers' locations that maximizes profits given the reaction in price of the competitor firm to its entrance. A tabu search procedure is presentedto solve the model together with computational experience.

Median problems in networks

The P-median problem is a classical location model par excellence . In this paper we, firstexamine the early origins of the problem, formulated independently by Louis Hakimi andCharles ReVelle, two of the fathers of the burgeoning multidisciplinary field of researchknown today as Facility Location Theory and Modelling. We then examine some of thetraditional heuristic and exact methods developed to solve the problem. In the third sectionwe analyze the impact of the model in the field. We end the paper by proposing new lines ofresearch related to such a classical problem.