Publications - Dennis Kristensen https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/dennis-kristensen?tx_pure_pure5%5Bcontroller%5D=Publications&cHash=21dfeb46158b53a0f2030f857def9ef4 en-us PURE Extension typo3support@science.au.dk (Web Department) 30 <![CDATA[Solving dynamic discrete choice models using smoothing and sieve methods]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/dennis-kristensen?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=17629e2f-599d-48da-96e5-8e8068f6276a&tx_pure_pure5%5BshowType%5D=pub&cHash=ee95d4ae423b3d04fd9137040b5a3eae Kristensen, D., Mogensen, P. K., Moon, J. M., Schjerning, B. We propose to combine smoothing, simulations and sieve approximations to solve for either the integrated or expected value function in a general class of dynamic discrete choice (DDC) models. We use importance sampling to approximate the Bellman operators defining the two functions. The random Bellman operators, and therefore also the corresponding solutions, are generally non-smooth which is undesirable. To circumvent this issue, we introduce smoothed versions of the random Bellman operators and solve for the corresponding smoothed value functions using sieve methods. We also show that one can avoid using sieves by generalizing and adapting the “self-approximating” method of Rust (1997b) to our setting. We provide an asymptotic theory for both approximate solution methods and show that they converge with N-rate, where N is number of Monte Carlo draws, towards Gaussian processes. We examine their performance in practice through a set of numerical experiments and find that both methods perform well with the sieve method being particularly attractive in terms of computational speed and accuracy.

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Forskning Sun, 01 Aug 2021 14:10:27 +0200 17629e2f-599d-48da-96e5-8e8068f6276a
<![CDATA[Identification of a class of index models]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/dennis-kristensen?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=262215eb-24fe-4ea2-bef9-30c5961bc733&tx_pure_pure5%5BshowType%5D=pub&cHash=f16c78db6efafd33d65fd6669716e73e Fosgerau, M., Kristensen, D. Forskning Fri, 01 Jan 2021 14:10:27 +0100 262215eb-24fe-4ea2-bef9-30c5961bc733 <![CDATA[Diffusion copulas]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/dennis-kristensen?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=de16d502-0690-4fea-badf-7553aff2ccac&tx_pure_pure5%5BshowType%5D=pub&cHash=95110ee4231695aaf7fcf8ffd5bf3977 Bu, R., Hadri, K., Kristensen, D. We propose a new semiparametric approach for modelling nonlinear univariate diffusions, where the observed process is a nonparametric transformation of an underlying parametric diffusion (UPD). This modelling strategy yields a general class of semiparametric Markov diffusion models with parametric dynamic copulas and nonparametric marginal distributions. We provide primitive conditions for the identification of the UPD parameters together with the unknown transformations from discrete samples. Likelihood-based estimators of both parametric and nonparametric components are developed and we analyse their asymptotic properties. Kernel-based drift and diffusion estimators are also proposed and shown to be normally distributed in large samples. A simulation study investigates the finite sample performance of our estimators in the context of modelling US short-term interest rates. We also present a simple application of the proposed method for modelling the CBOE volatility index data.

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Forskning Thu, 01 Apr 2021 14:10:27 +0200 de16d502-0690-4fea-badf-7553aff2ccac
<![CDATA[Higher-order properties of approximate estimators]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/dennis-kristensen?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=0a5d25ed-4191-45df-8b19-90f619a45a8b&tx_pure_pure5%5BshowType%5D=pub&cHash=003bd53388b1c59f7f9fa8f73ee794b3 Kristensen, D., Salanié, B. Many modern estimation methods in econometrics approximate an objective function, for instance, through simulation or discretization. These approximations typically affect both bias and variance of the resulting estimator. We first provide a higher-order expansion of such “approximate” estimators that takes into account the errors due to the use of approximations. We show how a Newton–Raphson adjustment can reduce the impact of approximations. Then we use our expansions to develop inferential tools that take into account approximation errors: we propose adjustments of the approximate estimator that remove its first-order bias and adjust its standard errors. These corrections apply to a class of approximate estimators that includes all known simulation-based procedures. A Monte Carlo simulation on the mixed logit model shows that our proposed adjustments can yield significant improvements at a low computational cost.

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Forskning Thu, 01 Jun 2017 14:10:27 +0200 0a5d25ed-4191-45df-8b19-90f619a45a8b
<![CDATA[On selection of statistics for approximate Bayesian computing (or the method of simulated moments)]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/dennis-kristensen?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=ad34cc22-c789-4f14-bf19-49be85eb07df&tx_pure_pure5%5BshowType%5D=pub&cHash=ccaf596adbbab938f3b3979c9281d3a0 Kristensen, D., Creel, M. . Forskning Fri, 01 Jan 2016 14:10:27 +0100 ad34cc22-c789-4f14-bf19-49be85eb07df <![CDATA[Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/dennis-kristensen?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=d9e4d6f8-dcb3-4486-bbf8-3cb6779c8f5c&tx_pure_pure5%5BshowType%5D=pub&cHash=b36de45bd5a5fe8ee988061c1f4858cd Agosto, A., Cavaliere, G., Kristensen, D., Rahbæk, A. Forskning Fri, 01 Jan 2016 14:10:27 +0100 d9e4d6f8-dcb3-4486-bbf8-3cb6779c8f5c <![CDATA[Asymptotic Theory for the QMLE in GARCH-X Models With Stationary and Nonstationary Covariates]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/dennis-kristensen?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=a3beb028-775a-4a7b-90e5-02ae515d4718&tx_pure_pure5%5BshowType%5D=pub&cHash=5ff5a89783d18f4c8469511a35766fe1 Han, H., Kristensen, D. Forskning Wed, 01 Jan 2014 14:10:27 +0100 a3beb028-775a-4a7b-90e5-02ae515d4718 <![CDATA[Bounding quantile demand functions using revealed preference inequalities]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/dennis-kristensen?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=0439b486-eb25-4e97-89d8-103994973f08&tx_pure_pure5%5BshowType%5D=pub&cHash=2ce8c3dfc948e21d0a8dd2c5a1cd1c87 Blundell, R., Kristensen, D., Matzkin, R. This paper develops a new approach to the estimation of consumer demand models with unobserved heterogeneity subject to revealed preference inequality restrictions. Particular attention is given to nonseparable heterogeneity. The inequality restrictions are used to identify bounds on counterfactual demand. A nonparametric estimator for these bounds is developed and asymptotic properties are derived. An empirical application using data from the UK Family Expenditure Survey illustrates the usefulness of the methods.

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Forskning Tue, 01 Apr 2014 14:10:27 +0200 0439b486-eb25-4e97-89d8-103994973f08
<![CDATA[Estimation of Stochastic Volatility Models by Nonparametric Filtering]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/dennis-kristensen?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=207a4e28-49a0-4b1c-9392-8747c1e627b7&tx_pure_pure5%5BshowType%5D=pub&cHash=be20a25a3725a2b1d502d07ace0f55c5 Kanaya, S., Kristensen, D. Forskning Fri, 01 Jan 2016 14:10:27 +0100 207a4e28-49a0-4b1c-9392-8747c1e627b7 <![CDATA[Testing and inference in nonlinear cointegrating vector error correction models]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/dennis-kristensen?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=45ee80ae-27bd-4295-92ec-5e0df075f487&tx_pure_pure5%5BshowType%5D=pub&cHash=3d44d69e380aeb7fc5d94a0f3d8e14e6 Kristensen, D., Rahbek, A. Forskning Sun, 01 Dec 2013 14:10:27 +0100 45ee80ae-27bd-4295-92ec-5e0df075f487 <![CDATA[Control functions and simultaneous equations methods]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/dennis-kristensen?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=3c09b8db-7cde-471b-a0eb-59935697aadd&tx_pure_pure5%5BshowType%5D=pub&cHash=a9116bbd844d324cab7be3ba27a7965b Blundell, R., Kristensen, D., Matzkin, R.L. Forskning Wed, 01 May 2013 14:10:27 +0200 3c09b8db-7cde-471b-a0eb-59935697aadd <![CDATA[Testing conditional factor models]]> https://econ.au.dk/da/research/researchcentres/creates/people/international-fellows/dennis-kristensen?tx_pure_pure5%5Baction%5D=single&tx_pure_pure5%5Bcontroller%5D=Publications&tx_pure_pure5%5Bid%5D=834c6a26-c193-4716-964e-5d166d568b62&tx_pure_pure5%5BshowType%5D=pub&cHash=370b6778dbd8cad85726ec2cc91acbcb Ang, A., Kristensen, D. Forskning Mon, 01 Oct 2012 14:10:27 +0200 834c6a26-c193-4716-964e-5d166d568b62