Computation and Analysis of Multiple Structural-Change Models

In a recent paper, Bai and Perron (1998) considered theoretical issues related to the limiting distribution of estimators and test statistics in the linear model with multiple structural changes. In this companion paper, we consider practical issues for the empirical applications of the procedures. We first address the problem of estimation of the break dates and present an efficient algorithm to obtain global minimizers of the sum of squared residuals. This algorithm is based on the principle of dynamic programming and requires at most least-squares operations of order O(T 2) for any number of breaks. Our method can be applied to both pure and partial structural-change models. Secondly, we consider the problem of forming confidence intervals for the break dates under various hypotheses about the structure of the data and the errors across segments. Third, we address the issue of testing for structural changes under very general conditions on the data and the errors. Fourth, we address the issue of estimating the number of breaks. We present simulation results pertaining to the behavior of the estimators and tests in finite samples. Finally, a few empirical applications are presented to illustrate the usefulness of the procedures. All methods discussed are implemented in a GAUSS program available upon request for non-profit academic use.

A Theoretical Comparison Between Integrated and Realized Volatilies

In this paper, we provide both qualitative and quantitative measures of the cost of measuring the integrated volatility by the realized volatility when the frequency of observation is fixed. We start by characterizing for a general diffusion the difference between the realized and the integrated volatilities for a given frequency of observations. Then, we compute the mean and variance of this noise and the correlation between the noise and the integrated volatility in the Eigenfunction Stochastic Volatility model of Meddahi (2001a). This model has, as special examples, log-normal, affine, and GARCH diffusion models. Using some previous empirical works, we show that the standard deviation of the noise is not negligible with respect to the mean and the standard deviation of the integrated volatility, even if one considers returns at five minutes. We also propose a simple approach to capture the information about the integrated volatility contained in the returns through the leverage effect.

Risk Aversion, Intertemporal Substitution, and Option Pricing

This paper develops a general stochastic framework and an equilibrium asset pricing model that make clear how attitudes towards intertemporal substitution and risk matter for option pricing. In particular, we show under which statistical conditions option pricing formulas are not preference-free, in other words, when preferences are not hidden in the stock and bond prices as they are in the standard Black and Scholes (BS) or Hull and White (HW) pricing formulas. The dependence of option prices on preference parameters comes from several instantaneous causality effects such as the so-called leverage effect. We also emphasize that the most standard asset pricing models (CAPM for the stock and BS or HW preference-free option pricing) are valid under the same stochastic setting (typically the absence of leverage effect), regardless of preference parameter values. Even though we propose a general non-preference-free option pricing formula, we always keep in mind that the BS formula is dominant both as a theoretical reference model and as a tool for practitioners. Another contribution of the paper is to characterize why the BS formula is such a benchmark. We show that, as soon as we are ready to accept a basic property of option prices, namely their homogeneity of degree one with respect to the pair formed by the underlying stock price and the strike price, the necessary statistical hypotheses for homogeneity provide BS-shaped option prices in equilibrium. This BS-shaped option-pricing formula allows us to derive interesting characterizations of the volatility smile, that is, the pattern of BS implicit volatilities as a function of the option moneyness. First, the asymmetry of the smile is shown to be equivalent to a particular form of asymmetry of the equivalent martingale measure. Second, this asymmetry appears precisely when there is either a premium on an instantaneous interest rate risk or on a generalized leverage effect or both, in other words, whenever the option pricing formula is not preference-free. Therefore, the main conclusion of our analysis for practitioners should be that an asymmetric smile is indicative of the relevance of preference parameters to price options.

Paretian Quasi-Orders: Two Agents.

We characterize Paretian quasi-orders in the two-agent continuous case.

Cognition in Seemingly Riskless Choices and Judgments.

We instillate rational cognition and learning in seemingly riskless choices and judgments. Preferences and possibilities are given in a stochastic sense and based on revisable expectations. the theory predicts experimental preference reversals and passes a sharp econometric test of the status quo bias drawn from a field study.

Integrating socio-economics and ecology: a taxonomy of quantitative methods and a review of their use in agro-ecology

Answering many of the critical questions in conservation, development and environmental management requires integrating the social and natural sciences. However, understanding the array of available quantitative methods and their associated terminology presents a major barrier to successful collaboration. We provide an overview of quantitative socio-economic methods that distils their complexity into a simple taxonomy. We outline how each has been used in conjunction with ecological models to address questions relating to the management of socio-ecological systems. We review the application of social and ecological quantitative concepts to agro-ecology and classify the approaches used to integrate the two disciplines. Our review included all published integrated models from 2003 to 2008 in 27 journals that publish agricultural modelling research. Although our focus is on agro-ecology, many of the results are broadly applicable to other fields involving an interaction between human activities and ecology. We found 36 papers that integrated social and ecological concepts in a quantitative model. Four different approaches to integration were used, depending on the scale at which human welfare was quantified. Most models viewed humans as pure profit maximizers, both when calculating welfare and predicting behaviour. Synthesis and applications. We reached two main conclusions based on our taxonomy and review. The first is that quantitative methods that extend predictions of behaviour and measurements of welfare beyond a simple market value basis are underutilized by integrated models. The second is that the accuracy of prediction for integrated models remains largely unquantified. Addressing both problems requires researchers to reach a common understanding of modelling goals and data requirements during the early stages of a project.

Combining qualitative and quantitative methods to analyze serious games outcomes: A pilot study for a new cognitive screening tool

Computer games for a serious purpose - so called serious games can provide additional information for the screening and diagnosis of cognitive impairment. Moreover, they have the advantage of being an ecological tool by involving daily living tasks. However, there is a need for better comprehensive designs regarding the acceptance of this technology, as the target population is older adults that are not used to interact with novel technologies. Moreover given the complexity of the diagnosis and the need for precise assessment, an evaluation of the best approach to analyze the performance data is required. The present study examines the usability of a new screening tool and proposes several new outlines for data analysis.

Using Quantitative Methods to Explore Political Leverage, Trade Policy, and Food Security: A Case Study of the Middle East

This dissertation explores why some states consistently secure food imports at prices higher than the world market price, thereby exacerbating food insecurity domestically. I challenge the idea that free market economics alone can explain these trade behaviors, and instead argue that states take into account political considerations when engaging in food trade that results in inefficient trade. In particular, states that are dependent on imports of staple food products, like cereals, are wary of the potential strategic value of these goods to exporters. I argue that this consideration, combined with the importing state’s ability to mitigate that risk through its own forms of political or economic leverage, will shape the behavior of the importing state and contribute to its potential for food security. In addition to cross-national analyses, I use case studies of the Gulf Cooperation Council states and Jordan to demonstrate how the political tools available to these importers affect their food security. The results of my analyses suggest that when import dependent states have access to forms of political leverage, they are more likely to trade efficiently, thereby increasing their potential for food security.

Anemia screening in potential female blood donors: comparison of two different quantitative methods

Anemia screening before blood donation requires an accurate, quick, practical, and easy method with minimal discomfort for the donors. The aim of this study was to compare the accuracy of two quantitative methods of anemia screening: the HemoCue 201(+) (Aktiebolaget Leo Diagnostics) hemoglobin (Hb) and microhematocrit (micro-Hct) tests. Two blood samples of a single fingerstick were obtained from 969 unselected potential female donors to determine the Hb by HemoCue 201(+) and micro-Hct using HemataSTAT II (Separation Technology, Inc.), in alternating order. From each participant, a venous blood sample was drawn and run in an automatic hematology analyzer (ABX Pentra 60, ABX Diagnostics). Considering results of ABX Pentra 60 as true values, the sensitivity and specificity of HemoCue 201(+) and micro-Hct as screening methods were compared, using a venous Hb level of 12.0 g per dL as cutoff for anemia. The sensitivities of the HemoCue 201(+) and HemataSTAT II in detecting anemia were 56 percent (95% confidence interval [CI], 46.1%-65.5%) and 39.5 percent (95% CI, 30.2%-49.3%), respectively (p < 0.001). Analyzing only candidates with a venous Hb level lower than 11.0 g per dL, the deferral rate was 100 percent by HemoCue 201(+) and 77 percent by HemataSTAT II. The specificities of the methods were 93.5 and 93.2 percent, respectively. The HemoCue 201(+) showed greater discriminating power for detecting anemia in prospective blood donors than the micro-Hct method. Both presented equivalent deferral error rates of nonanemic potential donors. Compared to the micro-Hct, HemoCue 201(+) reduces the risk of anemic female donors giving blood, specially for those with lower Hb levels, without increasing the deferral of nonanemic potential donors.

Exact Nonparametric Two-Sample Homogeneity Tests for Possibly Discrete Distributions.

In this paper, we study several tests for the equality of two unknown distributions. Two are based on empirical distribution functions, three others on nonparametric probability density estimates, and the last ones on differences between sample moments. We suggest controlling the size of such tests (under nonparametric assumptions) by using permutational versions of the tests jointly with the method of Monte Carlo tests properly adjusted to deal with discrete distributions. We also propose a combined test procedure, whose level is again perfectly controlled through the Monte Carlo test technique and has better power properties than the individual tests that are combined. Finally, in a simulation experiment, we show that the technique suggested provides perfect control of test size and that the new tests proposed can yield sizeable power improvements.

An Eigenfunction Approach for Volatility Modeling.

In this paper, we introduce a new approach for volatility modeling in discrete and continuous time. We follow the stochastic volatility literature by assuming that the variance is a function of a state variable. However, instead of assuming that the loading function is ad hoc (e.g., exponential or affine), we assume that it is a linear combination of the eigenfunctions of the conditional expectation (resp. infinitesimal generator) operator associated to the state variable in discrete (resp. continuous) time. Special examples are the popular log-normal and square-root models where the eigenfunctions are the Hermite and Laguerre polynomials respectively. The eigenfunction approach has at least six advantages: i) it is general since any square integrable function may be written as a linear combination of the eigenfunctions; ii) the orthogonality of the eigenfunctions leads to the traditional interpretations of the linear principal components analysis; iii) the implied dynamics of the variance and squared return processes are ARMA and, hence, simple for forecasting and inference purposes; (iv) more importantly, this generates fat tails for the variance and returns processes; v) in contrast to popular models, the variance of the variance is a flexible function of the variance; vi) these models are closed under temporal aggregation.