Nonparametric identification using instrumental variables: sufficient conditions for completeness

This paper provides sufficient conditions for the nonparametric identification of the regression function m(.) in a regression model with an endogenous regressor x and an instrumental variable z. It has been shown that the identification of the regression function from the conditional expectation of the dependent variable on the instrument relies on the completeness of the distribution of the endogenous regressor conditional on the instrument, i.e., f(x/z). We provide sufficient conditions for the completeness of f(x/z) without imposing a specific functional form, such as the exponential family. We show that if the conditional density f(x/z) coincides with an existing complete density at a limit point in the support of z, then f(x/z) itself is complete, and therefore, the regression function m(.) is nonparametrically identified. We use this general result provide specific sufficient conditions for completeness in three different specifications of the relationship between the endogenous regressor x and the instrumental variable z.

Nonparametric Identification Using Instrumental Variables: Sufficient Conditions For Completeness

This paper provides sufficient conditions for the nonparametric identification of the regression function m(.) in a regression model with an endogenous regressor x and an instrumental variable z. It has been shown that the identification of the regression function from the conditional expectation of the dependent variable on the instrument relies on the completeness of the distribution of the endogenous regressor conditional on the instrument, i.e., f(x|z). We provide sufficient conditions for the completeness of f(x|z) without imposing a specific functional form, such as the exponential family. We show that if the conditional density f(x|z) coincides with an existing complete density at a limit point in the support of z, then f(x|z) itself is complete, and therefore, the regression function m(.) is nonparametrically identified. We use this general result provide specific sufficient conditions for completeness in three different specifications of the relationship between the endogenous regressor x and the instrumental variable z.

Parameterized conditional specifications : sufficient completeness and implicit induction

Theorem proving in parameterized specifications allows for shorter and more structured proofs. Moreover, a generic proof can be given just once and reused for each instantiation of the parameters. We present procedures to test sufficient completeness and to prove and disprove inductive properties automatically in parameterized conditional specifications. Our method relies on the notion of test set, which can be seen as a well-suited induction scheme. Previously, we could only compute a test set for conditional specifications if the constructors were free. Here, we give a new definition of test sets and an algorithm to compute them even if the constructors are not free. The method uses a new notion of provable inconsistency which allows us to refute more false conjrectures than with previous approaches. This new method when limited to non parameterized conditional specifications, can refute general clauses, refutational completeness is also preserved for boolean ground convergent rewrite systems with completely defined functions even if the constructors are not free. The method has been implemented in the prover SPIKE. Based on computer experiments, the method appears to be more practical and efficient than inductive theorem proving in non-parameterized specifications

Not throwing out the baby with the bathwater: Bell's condition of local causality mathematically 'sharp and clean'

The starting point of the present paper is Bell's notion of local causality and his own sharpening of it so as to provide for mathematical formalisation. Starting with Norsen's (2007, 2009) analysis of this formalisation, it is subjected to a critique that reveals two crucial aspects that have so far not been properly taken into account. These are (i) the correct understanding of the notions of sufficiency, completeness and redundancy involved; and (ii) the fact that the apparatus settings and measurement outcomes have very different theoretical roles in the candidate theories under study. Both aspects are not adequately incorporated in the standard formalisation, and we will therefore do so. The upshot of our analysis is a more detailed, sharp and clean mathematical expression of the condition of local causality. A preliminary analysis of the repercussions of our proposal shows that it is able to locate exactly where and how the notions of locality and causality are involved in formalising Bell's condition of local causality.Comment: 14 pages. To be published in PSE volume "Explanation, Prediction, and Confirmation", edited by Dieks, et a

Identification and Estimation of Partial Effects with Proxy Variables

I develop a new identification approach for partial effects in nonseparable models with endogeneity. I use a proxy variable for the unobserved heterogeneity correlated with the endogenous variable to construct a valid control function, where the definition of a proxy variable is the same as in the measurement error literature. The identifying assumptions are distinct from existing methods, in particular instrumental variables and selection on observables approaches, and I provide an alternative identification strategy in settings where existing approaches are not applicable. Building on the identification result, I consider three estimation approaches, ranging from nonparametric to flexible parametric methods, and characterize asymptotic properties of the proposed estimators.Comment: 48 pages with the appendi

Completeness, robustness, and safety in real-time software requirements specification

This paper presents an approach to providing a rigorous basis for ascertaining whether or not a given set of software requirements is internally complete, i.e., closed with respect to questions and inferences that can be made on the basis of information included in the specification. Emphasis is placed on aspects of software requirements specifications that previously have not been adequately handled, including timing abstractions, safety, and robustness

Sciduction: Combining Induction, Deduction, and Structure for Verification and Synthesis

Even with impressive advances in automated formal methods, certain problems in system verification and synthesis remain challenging. Examples include the verification of quantitative properties of software involving constraints on timing and energy consumption, and the automatic synthesis of systems from specifications. The major challenges include environment modeling, incompleteness in specifications, and the complexity of underlying decision problems. This position paper proposes sciduction, an approach to tackle these challenges by integrating inductive inference, deductive reasoning, and structure hypotheses. Deductive reasoning, which leads from general rules or concepts to conclusions about specific problem instances, includes techniques such as logical inference and constraint solving. Inductive inference, which generalizes from specific instances to yield a concept, includes algorithmic learning from examples. Structure hypotheses are used to define the class of artifacts, such as invariants or program fragments, generated during verification or synthesis. Sciduction constrains inductive and deductive reasoning using structure hypotheses, and actively combines inductive and deductive reasoning: for instance, deductive techniques generate examples for learning, and inductive reasoning is used to guide the deductive engines. We illustrate this approach with three applications: (i) timing analysis of software; (ii) synthesis of loop-free programs, and (iii) controller synthesis for hybrid systems. Some future applications are also discussed

Towards an Effective Decision Procedure for LTL formulas with Constraints

This paper presents an ongoing work that is part of a more wide-ranging project whose final scope is to define a method to validate LTL formulas w.r.t. a program written in the timed concurrent constraint language tccp, which is a logic concurrent constraint language based on the concurrent constraint paradigm of Saraswat. Some inherent notions to tccp processes are non-determinism, dealing with partial information in states and the monotonic evolution of the information. In order to check an LTL property for a process, our approach is based on the abstract diagnosis technique. The concluding step of this technique needs to check the validity of an LTL formula (with constraints) in an effective way. In this paper, we present a decision method for the validity of temporal logic formulas (with constraints) built by our abstract diagnosis technique.Comment: Part of WLPE 2013 proceedings (arXiv:1308.2055