Latent Variable Models for Stochastic Discount Factors.

Latent variable models in finance originate both from asset pricing theory and time series analysis. These two strands of literature appeal to two different concepts of latent structures, which are both useful to reduce the dimension of a statistical model specified for a multivariate time series of asset prices. In the CAPM or APT beta pricing models, the dimension reduction is cross-sectional in nature, while in time-series state-space models, dimension is reduced longitudinally by assuming conditional independence between consecutive returns, given a small number of state variables. In this paper, we use the concept of Stochastic Discount Factor (SDF) or pricing kernel as a unifying principle to integrate these two concepts of latent variables. Beta pricing relations amount to characterize the factors as a basis of a vectorial space for the SDF. The coefficients of the SDF with respect to the factors are specified as deterministic functions of some state variables which summarize their dynamics. In beta pricing models, it is often said that only the factorial risk is compensated since the remaining idiosyncratic risk is diversifiable. Implicitly, this argument can be interpreted as a conditional cross-sectional factor structure, that is, a conditional independence between contemporaneous returns of a large number of assets, given a small number of factors, like in standard Factor Analysis. We provide this unifying analysis in the context of conditional equilibrium beta pricing as well as asset pricing with stochastic volatility, stochastic interest rates and other state variables. We address the general issue of econometric specifications of dynamic asset pricing models, which cover the modern literature on conditionally heteroskedastic factor models as well as equilibrium-based asset pricing models with an intertemporal specification of preferences and market fundamentals. We interpret various instantaneous causality relationships between state variables and market fundamentals as leverage effects and discuss their central role relative to the validity of standard CAPM-like stock pricing and preference-free option pricing.

Tests of Joint Hypotheses for Time Series Regression with a Unit Root

This Paper Studies Tests of Joint Hypotheses in Time Series Regression with a Unit Root in Which Weakly Dependent and Heterogeneously Distributed Innovations Are Allowed. We Consider Two Types of Regression: One with a Constant and Lagged Dependent Variable, and the Other with a Trend Added. the Statistics Studied Are the Regression \"F-Test\" Originally Analysed by Dickey and Fuller (1981) in a Less General Framework. the Limiting Distributions Are Found Using Functinal Central Limit Theory. New Test Statistics Are Proposed Which Require Only Already Tabulated Critical Values But Which Are Valid in a Quite General Framework (Including Finite Order Arma Models Generated by Gaussian Errors). This Study Extends the Results on Single Coefficients Derived in Phillips (1986A) and Phillips and Perron (1986).

How do Young People Choose College Majors?

Previous studies on the determinants of the choice of college major have assumed a constant probability of success across majors or a constant earnings stream across majors. Our model disregards these two restrictive assumptions in computing an expected earnings variable to explain the probability that a student will choose a specific major among four choices of concentrations. The construction of an expected earnings variable requires information on the student s perceived probability of success, the predicted earnings of graduates in all majors and the student s expected earnings if he (she) fails to complete a college program. Using data from the National Longitudinal Survey of Youth, we evaluate the chances of success in all majors for all the individuals in the sample. Second, the individuals' predicted earnings of graduates in all majors are obtained using Rumberger and Thomas's (1993) regression estimates from a 1987 Survey of Recent College Graduates. Third, we obtain idiosyncratic estimates of earnings alternative of not attending college or by dropping out with a condition derived from our college major decision-making model applied to our sample of college students. Finally, with a mixed multinominal logit model, we explain the individuals' choice of a major. The results of the paper show that the expected earnings variable is essential in the choice of a college major. There are, however, significant differences in the impact of expected earnings by gender and race.

Harsanyi’s Social Aggregation Theorem : A Multi-Profile Approach with Variable-Population Extensions

This paper provides new versions of Harsanyi’s social aggregation theorem that are formulated in terms of prospects rather than lotteries. Strengthening an earlier result, fixed-population ex-ante utilitarianism is characterized in a multi-profile setting with fixed probabilities. In addition, we extend the social aggregation theorem to social-evaluation problems under uncertainty with a variable population and generalize our approach to uncertain alternatives, which consist of compound vectors of probability distributions and prospects.

Projection-Based Statistical Inference in Linear Structural Models with Possibly Weak Instruments

It is well known that standard asymptotic theory is not valid or is extremely unreliable in models with identification problems or weak instruments [Dufour (1997, Econometrica), Staiger and Stock (1997, Econometrica), Wang and Zivot (1998, Econometrica), Stock and Wright (2000, Econometrica), Dufour and Jasiak (2001, International Economic Review)]. One possible way out consists here in using a variant of the Anderson-Rubin (1949, Ann. Math. Stat.) procedure. The latter, however, allows one to build exact tests and confidence sets only for the full vector of the coefficients of the endogenous explanatory variables in a structural equation, which in general does not allow for individual coefficients. This problem may in principle be overcome by using projection techniques [Dufour (1997, Econometrica), Dufour and Jasiak (2001, International Economic Review)]. AR-types are emphasized because they are robust to both weak instruments and instrument exclusion. However, these techniques can be implemented only by using costly numerical techniques. In this paper, we provide a complete analytic solution to the problem of building projection-based confidence sets from Anderson-Rubin-type confidence sets. The latter involves the geometric properties of “quadrics” and can be viewed as an extension of usual confidence intervals and ellipsoids. Only least squares techniques are required for building the confidence intervals. We also study by simulation how “conservative” projection-based confidence sets are. Finally, we illustrate the methods proposed by applying them to three different examples: the relationship between trade and growth in a cross-section of countries, returns to education, and a study of production functions in the U.S. economy.

Distribution-Free Bounds for Serial Correlation Coefficients in Heteroskedastic Symmetric Time Series

We consider the problem of testing whether the observations X1, ..., Xn of a time series are independent with unspecified (possibly nonidentical) distributions symmetric about a common known median. Various bounds on the distributions of serial correlation coefficients are proposed: exponential bounds, Eaton-type bounds, Chebyshev bounds and Berry-Esséen-Zolotarev bounds. The bounds are exact in finite samples, distribution-free and easy to compute. The performance of the bounds is evaluated and compared with traditional serial dependence tests in a simulation experiment. The procedures proposed are applied to U.S. data on interest rates (commercial paper rate).

The shunt from the cyclooxygenase to lipoxygenase pathway in human osteoarthritic subchondral osteoblasts is linked with a variable expression of the 5-lipoxygenase-activating protein

Affiliation: Unité de recherche en Arthrose, Centre de recherche du Centre Hospitalier de l'Université de Montréal, Hôpital Notre-Dame

From Smeed's Single-Damage Fixed-Form Three-Variable Model to Multinational and Multiprovincial Drag-Type Formulations: Does the Mystery of 1972-1973 Disapear ?

Rapport de recherche

Les erreurs de mesure sur la variable indépendante, dans le cadre de séries chronologiques.

Rapport de recherche

L'obligation d'information à échelle d'intensité variable: vers une théorisation de l'obligation de conseil

En 1992, la Cour suprême du Canada souligne l'importance de faire la distinction entre l'obligation principale de conseil qui est l'objet principal du contrat et l'obligation d'information qui est accessoire. L'obligation principale de conseil est reconnue à l'égard des professionnels des professions dites libérales à l'époque, comme les avocats et notaires dans un contrat de mandat. Par contre, l'évolution jurisprudentielle récente démontre que l'obligation de conseil ne se limite plus à l'objet principal du contrat, et que la notion de «professionnel» n'a plus le sens restrictif d'autrefois. Au Québec, l'obligation principale de conseil est reconnue dans un premier temps à l'égard des professionnels soumis au Code des professions, notamment avocats et notaires. On reconnaît aussi une telle obligation accessoire de conseil à l'égard d'autres personnes qui, bien qu'elles ne soient pas des «professionnels» au sens du Code des professions, exercent tout de même des activités de nature professionnelle. C'est le cas, par exemple, des courtiers en valeurs mobilières, des courtiers en assurances ou des institutions financières. D'ailleurs, une controverse semble régner dans le domaine bancaire sur l'étendue de l'obligation de conseil et d'information des institutions financières envers un client dans le cadre d'un contrat de prestation de services. Plus particulièrement, les tribunaux semblent partagés sur la reconnaissance ou non d'une obligation de conseil de la banque dans le cadre d'un emprunt. Certaines décisions sont à l'effet que seule une obligation d'information s'impose alors que d'autres préconisent le conseil. Afin d'élucider la confusion qui règne présentement en jurisprudence dans le domaine bancaire ainsi que dans le contrat de services et d'entreprise en général, il faut faire une étude jumelée de l'évolution de l'obligation de conseil accessoire et de l'obligation de conseil principale. Notre étude porte sur l'évolution jurisprudentielle qui tend vers une théorisation dans le contrat de services ou d'entreprise, de l'obligation de conseil qui devient alors une variante ou une intensité de l'obligation accessoire d'information. Par le fait même, on constate qu'une obligation de conseil principale semble également s'étendre à une catégorie plus large de professionnels. Dans ce cas, l'obligation de conseil est similaire, dans son fondement, au devoir de conseil du «professionnel» traditionnel, au sens du Code des professions. On constate alors que l'obligation principale de conseil n'est plus restreinte aux professionnels au sens classique du terme.