Solving Dynamic Discrete Choice Models Using Smoothing and Sieve Methods

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 a smoothed version of the random Bellman operator and solve for the corresponding smoothed value function using sieve methods. We show that one can avoid using sieves by generalizing and adapting the `self-approximating' method of Rust (1997) to our setting. We provide an asymptotic theory for the approximate solutions and show that they converge with root-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

Clinical Features of Probable Cluster Headache: A Prospective, Cross-Sectional Multicenter Study

Background: Epidemiological data of probable cluster headaches (CH) are scarce in the relevant literature. Here, we sought to assess the prevalence and clinical characteristics of probable CH in comparison with definite CH.Methods: Data used in this study were obtained from the Korean Cluster Headache Registry (KCHR), a prospective, cross-sectional, multicenter headache registry that collected data from consecutive patients diagnosed with CH.Results: In total, 159 patients were enrolled in this study; 20 (12.6%) were diagnosed with probable CH. The most common unfulfilled criterion in patients with probable CH was the duration of attack, which was found in 40% of patients with probable CH. Among clinical characteristics, the number of autonomic symptoms tended to be lower in probable CH than in definite CH (1.7 ± 1.2 vs. 2.4 ± 1.5, p = 0.051) and conjunctival injection and lacrimation showed an increased odds ratio (OR) [OR = 3.03; 95% confidence interval (CI): 1.03–8.33] in definite CH. The groups did not differ with regard to baseline demographic characteristics, disability, impact on life, or treatment response.Conclusions: Probable CH is relatively common among CH disorders, with a clinical impact similar to that of definite CH

Essays in Econometrics /

Chapter 1 studies transformation models T₀(Y)=Xʹ[beta]₀ + [epsilon] with an unknown monotone transformation T₀. Our focus is on the identification and estimation of [beta]₀, leaving the specification of T₀ and the distribution of [epsilon] nonparametric. We identify [beta]₀ under a new set of conditions; specifically, we demonstrate that identification may be achieved even when the regressor X has bounded support and contains discrete random variables. Our identification is constructive and leads to sieve extremum estimator. The empirical criterion of our estimator has a U-process structure, and therefore does not conform to existing results in the sieve estimation literature. We derive the convergence rate of the estimator and demonstrate its asymptotic normality. For inference, the weighted bootstrap is proved to be consistent. The estimator is simple to implement with standard optimization algorithms. A simulation study provides insight on its finite-sample performance. Chapter 2 is concerned with the problem of maximum likelihood estimation and inference in parametric models that are finitely identified. That identification is finite means that there is a finite set of parameter values that are observationally equivalent, i.e. they generate the same distribution of the observed variables. This implies in particular that no amount of sample information (data) can allow the econometrician to distinguish between those parameter values. Under finite identification, the asymptotic distribution of the maximum likelihood estimator is nonstandard and we study its properties. In particular, we show that bootstrap can be used to uncover the identified set. Inference on a simple null hypothesis is conducted using likelihood ratio, Lagrange multiplier Wald test statistics, which in this situation are no longer asymptotically equivalent. In Chapter 3, we study a family of nonparametric tests of density ratio ordering between two continuous probability distributions on the real line. Density ratio ordering is satisfied when the two distributions admit a nonincreasing density ratio. Equivalently, density ratio ordering is satisfied when the ordinal dominance curve associated with the two distributions is concave. To test this property, we consider statistics based on the Lp-distance between an empirical ordinal dominance curve and its least concave majorant. We derive the limit distribution of these statistics when density ratio ordering is satisfied. Further, we establish that, when 1<̲ p <̲ 2, the limit distribution is stochastically largest when the two distributions are equal. When 2< p<̲ [infinity], this is not the case, and in fact the limit distribution diverges to infinity along a suitably chosen sequence of concave ordinal dominance curves. Our results serve to clarify, extend and amend assertions appearing previously in the literature for the cases p = 1 and p = [infinity]. We provide numerical evidence confirming their relevance in finite sample

Testing the concavity of an ordinaldominance curve

We study the asymptotic properties of a class of statistics used for testing the null hypothesis that an ordinal dominance curve is concave. The statistics are based on theLp-distance between the empirical ordinal dominance curve and its least concave majo- rant, with 1 ≤ p ≤ ∞. We formally establish the limit distribution of the statistics when the true ordinal dominance curve is concave. Further, we establish that, when 1 ≤ p ≤ 2, the limit distribution is stochastically largest when the true ordinal dominance curve is the 45-degree line. When p > 2, this is not the case, and in fact the limit distribution diverges to infinity along a suitably chosen sequence of concave ordinal dominance curves. Our results serve to clarify, extend and amend assertions appearing previously in the literature for the cases p = 1 and p = ∞

Testing the concavity of an ordinaldominance curve

We study the asymptotic properties of a class of statistics used for testing the null hypothesis that an ordinal dominance curve is concave. The statistics are based on theLp-distance between the empirical ordinal dominance curve and its least concave majo- rant, with 1 ≤ p ≤ ∞. We formally establish the limit distribution of the statistics when the true ordinal dominance curve is concave. Further, we establish that, when 1 ≤ p ≤ 2, the limit distribution is stochastically largest when the true ordinal dominance curve is the 45-degree line. When p > 2, this is not the case, and in fact the limit distribution diverges to infinity along a suitably chosen sequence of concave ordinal dominance curves. Our results serve to clarify, extend and amend assertions appearing previously in the literature for the cases p = 1 and p = ∞

Expression of protein S100A4 is a predictor of recurrence in colorectal cancer

AIM: To investigate the prognostic significance of S100A4 expression in colorectal cancer and its correlation with expression of E-cadherin and p53

Risk factors affecting seroconversion after influenza A/H1N1 vaccination in hemodialysis patients

<p>Abstracts</p> <p>Background</p> <p>Hemodialysis (HD) patients have multiple causes of immune dysfunction and poor immune response to influenza vaccination. We investigated the antibody response rate to a pandemic H1N1/2009 influenza vaccination and clinical parameters influencing the induction of antibody responses in HD patients.</p> <p>Methods</p> <p>A total of 114 HD patients were vaccinated with a monovalent adjuvanted H1N1 inactivated influenza vaccine. Titers of neutralizing antibodies were evaluated by hemagglutination inhibition (HI) assay at pre- and 4 weeks after vaccination. Seroconversion was defined as either a pre-vaccination HI titer < 1:10 and a post vaccination HI titer > 1:40 or a pre-vaccination HI titer ≥ 1:10 and a minimum four-fold rise in post-vaccination HI antibody titer. Seventeen out of 114 HD patients (14.9%) tested positive for antibodies against influenza A/H1N1/2009 before vaccination. The remaining 97 baseline sero-negative patients were included in the analysis.</p> <p>Results</p> <p>Only 30 (30.9%) HD patients had seroconversion 4 weeks after vaccination. The elderly patients, those over 65 years of age, showed significantly lower seroconversion rate compared to younger HD patients (20.5% vs. 39.6%, p = 0.042). Furthermore, patients with hemoglobin values less than 10 g/dL had a significantly lower seroconversion rate compared to those with higher hemoglobin values (20.0 vs. 38.6%, p = 0.049). By multivariate logistic regression analysis, only age ≥65 years (OR = 0.336, 95% confidence interval (CI) 0.116-0.971, p = 0.044) and hemoglobin levels <10 g/dL (OR = 0.315, 95% CI 0.106-0.932, p = 0.037) were independently associated with seroconversion after vaccination.</p> <p>Conclusions</p> <p>Our data show that HD patients, especially who are elderly with low hemoglobin levels, are at increased risk for lower seroconversion rate after influenza A/H1N1 vaccination. Further studies are needed to improve the efficacy of vaccination in these high risk patients.</p

Clinical features of chronic cluster headache based on the third edition of the International Classification of Headache Disorders: A prospective multicentre study.

The criterion for the remission period of chronic cluster headache (CCH) was recently revised from < 1 month to < 3 months in the third edition of the International Classification of Headache Disorders (ICHD-3). However, information on the clinical features of CCH based on the ICHD-3 criteria is currently limited. The present study aimed to investigate the clinical features of CCH based on ICHD-3 using data from the Korean Cluster Headache Registry (KCHR). The KCHR is a multicentre prospective registry of patients with cluster headache (CH) from 15 hospitals. Among the 250 participants with CH, 12 and 176 participants were classified as having CCH and episodic cluster headache (ECH), respectively. Among 12 participants with CCH, 6 (50%) had remission periods of < 1 month, and the remaining 6 (50%) had a remission period of 1-3 months. Six participants had CCH from the time of onset of CH, and in the other 6 participants, CCH evolved from ECH. CCH subjects had later age of onset of CH, developed the condition after a longer interval after CH onset, and had more migraine and less nasal congestion and/or rhinorrhoea than ECH subjects. Clinical features of CCH with remission periods < 1 month were not significantly different from those of CCH with remission periods of 1-3 months, except for the total number of bouts. More current smoking and less diurnal rhythmicity were observed in participants with CCH evolved from ECH compared to those with ECH. In conclusion, the number of subjects with CCH doubled when the revised ICHD-3 criteria were used. Most of clinical characteristics of CCH did not differ when the previous and current version of ICHD was applied and compared. Some clinical features of CCH were different from those of ECH, and smoking may have a role in CH chronification

Impact of cluster headache on employment status and job burden: a prospective cross-sectional multicenter study

Abstract Background Cluster headaches (CH) are recurrent severe headaches, which impose a major burden on the life of patients. We investigated the impact of CH on employment status and job burden. Methods The study was a sub-study of the Korean Cluster Headache Registry. Patients with CH were enrolled from September 2016 to February 2018 from 15 headache clinics in Korea. We also enrolled a headache control group with age-sex matched patients with migraine or tension-type headache. Moreover, a control group including individuals without headache complaints was recruited. All participants responded to a questionnaire that included questions on employment status, type of occupation, working time, sick leave, reductions in productivity, and satisfaction with current occupation. The questionnaire was administered to participants who were currently employed or had previous occupational experience. Results We recruited 143 patients with CH, 38 patients with other types of headache (migraine or tension-type headache), and 52 headache-free controls. The proportion of employees was lower in the CH group compared with the headache and headache-free control groups (CH: 67.6% vs. headache controls: 84.2% vs. headache-free controls: 96.2%; p = 0.001). The CH group more frequently experienced difficulties at work and required sick leave than the other groups (CH: 84.8% vs. headache controls: 63.9% vs. headache-free controls: 36.5%; p <  0.001; CH: 39.4% vs. headache controls: 13.9% vs. headache-free controls: 3.4%; p <  0.001). Among the patients with CH, sick leave was associated with younger age at CH onset (25.8 years vs. 30.6 years, p = 0.014), severity of pain rated on a visual analogue scale (9.3 vs. 8.8, p = 0.008), and diurnal periodicity during the daytime (p = 0.003). There were no significant differences with respect to the sick leave based on sex, age, CH subtypes, and CH recurrence. Conclusions CH might be associated with employment status. Most patients with CH experienced substantial burdens at work