ERN: Semiparametric & Nonparametric Methods (Topic)最新文献_第3页

Counterfactual Evaluation in Semiparametric Multinomial Choice Models 半参数多项式选择模型的反事实评价

ERN: Semiparametric & Nonparametric Methods (Topic) Pub Date : 2017-05-30 DOI: 10.2139/ssrn.3006737

K. Chiong, Yu-Wei Hsieh, M. Shum

引用次数: 2

Pension Eligibility Rules and the Local Causal Effect of Retirement on Cognitive Functioning 养老金资格规则及退休对认知功能的局部因果效应

ERN: Semiparametric & Nonparametric Methods (Topic) Pub Date : 2017-05-19 DOI: 10.2139/ssrn.2993152

Eduardo Fé

引用次数: 2

Efficient Estimation of Integrated Volatility Functionals via Multiscale Jackknife 基于多尺度折刀的综合波动函数的高效估计

ERN: Semiparametric & Nonparametric Methods (Topic) Pub Date : 2017-03-27 DOI: 10.2139/ssrn.2942235

Jia Li, Yunxiao Liu, D. Xiu

引用次数: 25

Penalized Quantile Regression with Semiparametric Correlated Effects: Applications with Heterogeneous Preferences 半参数相关效应的惩罚分位数回归:异质偏好的应用

ERN: Semiparametric & Nonparametric Methods (Topic) Pub Date : 2017-03-01 DOI: 10.1002/JAE.2520

M. Harding, Carlos Lamarche

{"title":"Penalized Quantile Regression with Semiparametric Correlated Effects: Applications with Heterogeneous Preferences","authors":"M. Harding, Carlos Lamarche","doi":"10.1002/JAE.2520","DOIUrl":"https://doi.org/10.1002/JAE.2520","url":null,"abstract":"This paper proposes new ?1-penalized quantile regression estimators for panel data, which explicitly allows for individual heterogeneity associated with covariates. We conduct Monte Carlo simulations to assess the small sample performance of the new estimators and provide comparisons of new and existing penalized estimators in terms of quadratic loss. We apply the techniques to two empirical studies. First, the new method is applied to the estimation of labor supply elasticities and we find evidence that positive substitution effects dominate negative wealth effects at the middle of the conditional distribution of hours. The overall effect tends to be larger at the lower tail, which suggests that changes in taxes have different effects across the response distribution. Second, we estimate consumer preferences for nutrients from a demand model using a large scanner dataset of household food purchases. We show that preferences for nutrients vary across the conditional distribution of expenditure and across genders, and emphasize the importance of fully capturing consumer heterogeneity in demand modeling. Both applications highlight the importance of estimating individual heterogeneity when designing economic policy.","PeriodicalId":264857,"journal":{"name":"ERN: Semiparametric & Nonparametric Methods (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132483435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 28

Comparison of Parametric and Semiparametric Representations of Unobserved Preference Heterogeneity in Logit Models Logit模型中未观察到的偏好异质性的参数和半参数表示比较

ERN: Semiparametric & Nonparametric Methods (Topic) Pub Date : 2016-12-28 DOI: 10.2139/ssrn.2902402

P. Bansal, Ricardo A. Daziano, Martin Achtnicht

{"title":"Comparison of Parametric and Semiparametric Representations of Unobserved Preference Heterogeneity in Logit Models","authors":"P. Bansal, Ricardo A. Daziano, Martin Achtnicht","doi":"10.2139/ssrn.2902402","DOIUrl":"https://doi.org/10.2139/ssrn.2902402","url":null,"abstract":"The logit-mixed logit (LML) model is a very recent advancement in semiparametric discrete choice models. LML represents the mixing distribution of a logit kernel as a sieve function (polynomials, step functions, and splines, among many other variants). In the first part of this paper, we conduct Monte-Carlo studies to analyze the number of required parameters (e.g., polynomial order) in three LML variants to recover the true population distributions, and also compare the performance (in terms of accuracy, precision, estimation time, and model fit) of LML and a mixed multinomial logit with normal heterogeneity (MMNL-N). Our results indicate that adding too many parameters in LML may not be the best strategy to retrieve underlying taste heterogeneity; in fact, overspecified models generally perform worst in terms of BIC. We recommend to use neither minimum-BIC nor the most flexible specification, but we rather suggest to start with the same number of parameters as a parametric model (such as MMNL-N) while checking changes in the derived histogram of the mixing distribution. As expected, LML was able to recover bimodal-normal, lognormal, and uniform distributions much better than the misspecified MMNL-N. Computational efficiency makes LML advantageous in the process of searching for the final specification. In the second part of the paper, we estimate the willingness-to-pay (WTP) estimates of German consumers for different vehicle attributes when making alternative-fuel-car purchase choices. LML was able to capture the bimodal nature of WTP for vehicle attributes, which was not possible to retrieve using standard parametric specifications.","PeriodicalId":264857,"journal":{"name":"ERN: Semiparametric & Nonparametric Methods (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115108441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

An Infinite Hidden Markov Model for Short-term Interest Rates 短期利率的无限隐马尔可夫模型

ERN: Semiparametric & Nonparametric Methods (Topic) Pub Date : 2016-05-03 DOI: 10.2139/ssrn.3521099

J. Maheu, Qiao Yang

引用次数: 26

Measuring Productivity When Technologies are Heterogeneous: A Semi-Parametric Approach for Electricity Generation 测量技术异质时的生产力:发电的半参数方法

ERN: Semiparametric & Nonparametric Methods (Topic) Pub Date : 2015-11-01 DOI: 10.2139/ssrn.2698067

S. Seifert

引用次数: 1

Regression Discontinuity Designs with Nonclassical Measurement Errors 具有非经典测量误差的回归不连续设计

ERN: Semiparametric & Nonparametric Methods (Topic) Pub Date : 2015-10-27 DOI: 10.2139/ssrn.3080198

Takahide Yanagi

引用次数: 2

Semiparametric Dynamic Portfolio Choice with Multiple Conditioning Variables 具有多条件变量的半参数动态投资组合选择

ERN: Semiparametric & Nonparametric Methods (Topic) Pub Date : 2015-02-08 DOI: 10.2139/ssrn.2563317

Jia Chen, Degui Li, O. Linton, Zudi Lu

{"title":"Semiparametric Dynamic Portfolio Choice with Multiple Conditioning Variables","authors":"Jia Chen, Degui Li, O. Linton, Zudi Lu","doi":"10.2139/ssrn.2563317","DOIUrl":"https://doi.org/10.2139/ssrn.2563317","url":null,"abstract":"Dynamic portfolio choice has been a central and essential objective for investors in active asset management. In this paper, we study the dynamic portfolio choice with multiple conditioning variables, where the dimension of the conditioning variables can be either fixed or diverging to infinity at certain polynomial rate of the sample size. We propose a novel data-driven method to estimate the optimal portfolio choice, motivated by the model averaging marginal regression approach suggested by Li et al. (2015). More specifically, in order to avoid the curse of dimensionality associated with the multivariate nonparametric regression problem and to make it practically implementable, we first estimate the marginal optimal portfolio choice by maximizing the conditional utility function for each univariate conditioning variable, and then construct the joint dynamic optimal portfolio through the weighted average of the marginal optimal portfolio across all the conditioning variables. Under some regularity conditions, we establish the large sample properties for the developed portfolio choice procedure. Both the simulation study and empirical application well demonstrate the finite-sample performance of the proposed methodology.","PeriodicalId":264857,"journal":{"name":"ERN: Semiparametric & Nonparametric Methods (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133195183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Obesity and Health-Related Decisions: An Empirical Model of The Determinants of Weight Status 肥胖与健康相关决策:体重状况决定因素的实证模型

ERN: Semiparametric & Nonparametric Methods (Topic) Pub Date : 2014-12-01 DOI: 10.2139/ssrn.2532479

Leonardo Fabio Morales, P. Gordon-Larsen, David K. Guilkey

{"title":"Obesity and Health-Related Decisions: An Empirical Model of The Determinants of Weight Status","authors":"Leonardo Fabio Morales, P. Gordon-Larsen, David K. Guilkey","doi":"10.2139/ssrn.2532479","DOIUrl":"https://doi.org/10.2139/ssrn.2532479","url":null,"abstract":"Using Add Health, a very comprehensive longitudinal data set of teenagers and young adults in the United States, we estimate a structural dynamic model of the determinants of obesity. In addition to including many of the well-recognized endogenous factors mentioned in the literature as obesity determinants, i.e., physical activity, smoking, a proxy for food consumption, and childbearing, we also model the residential location as a choice variable, relevant to the young-to middle-aged adult, as a major component. This allows us to control for an individual’s self-selection into communities which possess the types of amenities in the built environment which in turn affect their behaviors such as physical activity and fast food consumption. We specify reduced form equations for all these endogenous demand decisions, together with an obesity structural equation. The whole system of equations is jointly estimated by a semi-parametric full information log-likelihood method that allows for a general pattern of correlation in the errors across equations. Simulations are then used to allow us to quantify the effects of these endogenous factors on the probability of obesity. A key finding is that controlling for residential self-selection has important substantive implications. To our knowledge, this has not been yet documented within a full information maximum likelihood framework.","PeriodicalId":264857,"journal":{"name":"ERN: Semiparametric & Nonparametric Methods (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132327389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11