Econometrics: Econometric & Statistical Methods - General eJournal最新文献_第2页

Monte Carlo methods for real options under parameter uncertainty in multidimensional models 多维模型参数不确定性下实物期权的蒙特卡罗方法

Econometrics: Econometric & Statistical Methods - General eJournal Pub Date : 2021-06-21 DOI: 10.2139/ssrn.3549891

Ankush Agarwal, C. Ewald, Yihan Zou

引用次数: 0

The Nonstationary Newsvendor: Data-Driven Nonparametric Learning 非平稳的报贩:数据驱动的非参数学习

Econometrics: Econometric & Statistical Methods - General eJournal Pub Date : 2021-06-13 DOI: 10.2139/ssrn.3866171

N. B. Keskin, Xu Min, Jing-Sheng Song

{"title":"The Nonstationary Newsvendor: Data-Driven Nonparametric Learning","authors":"N. B. Keskin, Xu Min, Jing-Sheng Song","doi":"10.2139/ssrn.3866171","DOIUrl":"https://doi.org/10.2139/ssrn.3866171","url":null,"abstract":"We study a newsvendor problem with unknown demand distribution in a nonstationary demand environment over a multi-period time horizon. The demand in each period consists of a time-varying demand level and an additive random shock. Neither the demand level nor the random shock is separately observable. The amount of change in the demand level over the time horizon is measured by a cumulative variation metric. The problem has widespread applications, such as perishable inventory planning, staffing, and medical resource capacity planning in the wake of COVID-19. We design a nonparametric dynamic ordering policy, termed the moving window ordering policy, that tracks the shifts in the unknown demand level while accounting for the unobservable random demand shocks. To compute the order quantity in each period, this policy only needs the past demand observations, without any access to the underlying demand distribution. For a finite variation \"budget,\" we prove that our ordering policy is first-order optimal in the sense that its regret grows at the smallest possible rate. We also extend our analysis to the case of asymptotically large variation budgets. Through case studies based on real-life data, we show that our policy can save 20-80% of overage and underage costs, relative to policies widely used for perishable inventory replenishment and nurse staffing.","PeriodicalId":11465,"journal":{"name":"Econometrics: Econometric & Statistical Methods - General eJournal","volume":"53 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83276609","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: 6

Comparison of Local Projection Estimators for Proxy Vector Autoregressions 代理向量自回归的局部投影估计比较

Econometrics: Econometric & Statistical Methods - General eJournal Pub Date : 2021-05-01 DOI: 10.2139/ssrn.3855339

Martin Bruns, H. Luetkepohl

引用次数: 7

Reading the Candlesticks: An OK Estimator for Volatility 阅读烛台:对波动的一个好的估计

Econometrics: Econometric & Statistical Methods - General eJournal Pub Date : 2021-04-21 DOI: 10.2139/ssrn.3838231

Jia Li

引用次数: 4

Nonparametric Identification and Inference of First-Price Auctions with Heterogeneous Bidders 异质竞买人首价拍卖的非参数辨识与推理

Econometrics: Econometric & Statistical Methods - General eJournal Pub Date : 2021-04-11 DOI: 10.2139/ssrn.3809922

Zheng Li

引用次数: 0

Testing a Class of Semi- or Nonparametric Conditional Moment Restriction Models using Series Methods 用级数法检验一类半参数或非参数条件矩约束模型

Econometrics: Econometric & Statistical Methods - General eJournal Pub Date : 2021-03-22 DOI: 10.2139/ssrn.3667599

Jesper Riis-Vestergaard Sørensen

{"title":"Testing a Class of Semi- or Nonparametric Conditional Moment Restriction Models using Series Methods","authors":"Jesper Riis-Vestergaard Sørensen","doi":"10.2139/ssrn.3667599","DOIUrl":"https://doi.org/10.2139/ssrn.3667599","url":null,"abstract":"This paper proposes a new test for a class of conditional moment restrictions (CMRs) whose parameterization involves unknown, unrestricted conditional expectation functions. Motivating examples of such CMRs arise from models of discrete choice under uncertainty including certain static games of incomplete information. The proposed test may be viewed as a semi-/nonparametric extension of the Bierens (1982, Journal of Econometrics 20, 105–134) goodness-of-fit test of a parametric model for the conditional mean. Estimating conditional expectations using series methods and employing a Gaussian multiplier bootstrap to obtain critical values, the test is shown to be asymptotically correctly sized and consistent. Simulation studies indicate good finite-sample properties. In an empirical application, the test is used to study the validity of a game-theoretical model for discount store market entry, treating equilibrium beliefs as nonparametric conditional expectations. The test indicates that Walmart and Kmart entry decisions do not result from a static discrete game of incomplete information with linearly specified profits.","PeriodicalId":11465,"journal":{"name":"Econometrics: Econometric & Statistical Methods - General eJournal","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77829760","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: 0

Identifying High-Frequency Shocks with Bayesian Mixed-Frequency VARs 用贝叶斯混频var识别高频冲击

Econometrics: Econometric & Statistical Methods - General eJournal Pub Date : 2021-02-26 DOI: 10.2139/ssrn.3855847

Alessia Paccagnini, F. Parla

引用次数: 6

Estimating and Testing for Smooth Structural Changes in Moment Condition Models 矩态模型结构平滑变化的估计与检验

Econometrics: Econometric & Statistical Methods - General eJournal Pub Date : 2021-02-25 DOI: 10.2139/ssrn.3792747

Haiqi Li, Jin Zhou, Yongmiao Hong

{"title":"Estimating and Testing for Smooth Structural Changes in Moment Condition Models","authors":"Haiqi Li, Jin Zhou, Yongmiao Hong","doi":"10.2139/ssrn.3792747","DOIUrl":"https://doi.org/10.2139/ssrn.3792747","url":null,"abstract":"Numerous studies have been devoted to estimating and testing for moment condition models. Most of the existing studies assume that structural parameters are either fixed or changed abruptly over time. This study considers estimation of and testing for smooth structural changes in moment condition models where the data generating process is assumed to be locally stationary. A novel local generalized method of moment estimator and its boundary-corrected counterpart are proposed to estimate the smoothly changing structural parameters. Consistency and asymptotic normality are established, and an optimal weighting matrix and its consistent estimator are obtained. In particular, a consistent nonparametric test is proposed to check both smooth changes and abrupt breaks in structural parameters. The test is asymptotically pivotal and does not require prior information about the alternative. A Monte Carlo study is performed to illustrate the merits of the proposed test. In an empirical application, we document the time-varying features of the risk aversion parameter in an asset pricing model, which are consistent with business cycles and financial crisis.","PeriodicalId":11465,"journal":{"name":"Econometrics: Econometric & Statistical Methods - General eJournal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76668137","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: 1

Properties of Subjective Beliefs Estimators 主观信念估计量的性质

Econometrics: Econometric & Statistical Methods - General eJournal Pub Date : 2021-02-12 DOI: 10.2139/ssrn.3784757

Anish Ghosh, Taisuke Otsu, Guillaume Roussellet

引用次数: 0

The Estimation Risk and the IRB Supervisory Formula 风险评估与IRB监管公式

Econometrics: Econometric & Statistical Methods - General eJournal Pub Date : 2021-01-14 DOI: 10.2139/ssrn.3773406

S. Casellina, S. Landini, M. Uberti

{"title":"The Estimation Risk and the IRB Supervisory Formula","authors":"S. Casellina, S. Landini, M. Uberti","doi":"10.2139/ssrn.3773406","DOIUrl":"https://doi.org/10.2139/ssrn.3773406","url":null,"abstract":"In many standard derivation and presentations of risk measures like the Value-at-Risk or the Expected Shortfall, it is assumed that all the model’s parameters are known. In practice, however, the parameters must be estimated and this introduces an additional source of uncertainty that is usually not accounted for. The Prudential Regulators have formally raised the issue of errors stemming from the internal model estimation process in the context of credit risk, calling for margins of conservatism to cover possible underestimation in capital. Notwithstanding this requirement, to date, a solution shared by banks and regulators/supervisors has not yet been found. In our paper, we investigate the effect of the estimation error in the framework of the Asymptotic Single Risk Factor model that represents the baseline for the derivation of the credit risk measures under the IRB approach. We exploit Monte Carlo simulations to quantify the bias induced by the estimation error and we explore an approach to correct for this bias. Our approach involves only the estimation of the long run average probability of default and not the estimation of the asset correlation given that, in practice, banks are not allowed to modify this parameter. We study the stochastic characteristics of the probability of default estimator that can be derived from the Asymptotic Single Risk Factor framework and we show how to introduce a correction to control for the estimation error. Our approach does not require introducing in the Asymptotic Single Risk Factor model additional elements like the prior distributions or other parameters which, having to be estimated, would introduce another source of estimation error. This simple and easily implemented correction ensures that the probability of observing an exception (i.e. a default rate higher than the estimated quantile of the default rate distribution) is equal to the desired confidence level. We show a practical application of our approach relying on real data.","PeriodicalId":11465,"journal":{"name":"Econometrics: Econometric & Statistical Methods - General eJournal","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85454150","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: 1