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1.
    
The present penalized quantile variable selection methods are only applicable to finite number of predictors or do not have oracle property associated with estimator. This technique is considered as an alternative to ordinary least squares regression in case of the outliers and the heavy‐tailed errors existing in linear models. The variable selection through quantile regression with diverging number of parameters is investigated in this paper. The convergence rate of estimator with smoothly clipped absolute deviation penalty function is also studied. Moreover, the oracle property with proper selection of tuning parameter for quantile regression under certain regularity conditions is also established. In addition, the rank correlation screening method is used to accommodate ultra‐high dimensional data settings. Monte Carlo simulations demonstrate finite performance of the proposed estimator. The results of real data reveal that this approach provides substantially more information as compared with ordinary least squares, conventional quantile regression, and quantile lasso.  相似文献   

2.
Under minimal assumptions, finite sample confidence bands for quantile regression models can be constructed. These confidence bands are based on the “conditional pivotal property” of estimating equations that quantile regression methods solve and provide valid finite sample inference for linear and nonlinear quantile models with endogenous or exogenous covariates. The confidence regions can be computed using Markov Chain Monte Carlo (MCMC) methods. We illustrate the finite sample procedure through two empirical examples: estimating a heterogeneous demand elasticity and estimating heterogeneous returns to schooling. We find pronounced differences between asymptotic and finite sample confidence regions in cases where the usual asymptotics are suspect.  相似文献   

3.
    
At the end of the nineteenth century, the content and practice of statistics underwent a series of transitions that led to its emergence as a highly specialised mathematical discipline. These intellectual and later institutional changes were, in part, brought about by a mathematical-statistical translation of Charles Darwin's redefinition of the biological species as something that could be viewed in terms of populations. Karl Pearson and W.F.R. Weldon's mathematical reconceptualisation of Darwinian biological variation and \"statistical\" population of species in the 1890s provided the framework within which a major paradigmatic shift occurred in statistical techniques and theory. Weldon's work on the shore crab in Naples and Plymouth from 1892 to 1895 not only brought them into the forefront of ideas of speciation and provided the impetus to Pearson's earliest statistical innovations, but it also led to Pearson shifting his professional interests from having had an established career as a mathematical physicist to developing one as a biometrician. The innovative statistical work Pearson undertook with Weldon in 1892 and later with Francis Galton in 1894 enabled him to lay the foundations of modern mathematical statistics. While Pearson's diverse publications, his establishment of four laboratories and the creation of new academic departments underscore the plurality of his work, the main focus of his life-long career was in the establishment and promulgation of his statistical methodology.  相似文献   

4.
    
In this paper, we develop a fully parametric quantile regression model based on the generalised three-parameter beta (GB3) distribution. Beta regression models are primarily used to model rates and proportions. However, these models are usually specified in terms of a conditional mean. Therefore, they may be inadequate if the observed response variable follows an asymmetrical distribution. In addition, beta regression models do not consider the effect of the covariates across the spectrum of the dependent variable, which is possible through the conditional quantile approach. In order to introduce the proposed GB3 regression model, we first reparameterise the GB3 distribution by inserting a quantile parameter, and then we develop the new proposed quantile model. We also propose a simple interpretation of the predictor–response relationship in terms of percentage increases/decreases of the quantile. A Monte Carlo study is carried out for evaluating the performance of the maximum likelihood estimates and the choice of the link functions. Finally, a real COVID-19 dataset from Chile is analysed and discussed to illustrate the proposed approach.  相似文献   

5.
由于即将退休与刚退休的这一代人拥有低赡养比与低抚养比,本文称其为“双低一代”。本文基于宏观统计数据与微观调查数据,利用分位回归等方法对“双低一代”的社会学特征与经济学特征进行研究,发现其具有人口总量较多、教育背景优良、社会阅历丰富、消费倾向明显等特征。此外,通过对“双低一代”的人力资本存量进行测算,提出充分发挥“双低一代”余热、缓解老龄化问题的政策建议。  相似文献   

6.
This paper estimates a class of models which satisfy a monotonicity condition on the conditional quantile function of the response variable. This class includes as a special case the monotonic transformation model with the error term satisfying a conditional quantile restriction, thus allowing for very general forms of conditional heteroscedasticity. A two-stage approach is adopted to estimate the relevant parameters. In the first stage the conditional quantile function is estimated nonparametrically by the local polynomial estimator discussed in Chaudhuri (Journal of Multivariate Analysis 39 (1991a) 246–269; Annals of Statistics 19 (1991b) 760–777) and Cavanagh (1996, Preprint). In the second stage, the monotonicity of the quantile function is exploited to estimate the parameters of interest by maximizing a rank-based objective function. The proposed estimator is shown to have desirable asymptotic properties and can then also be used for dimensionality reduction or to estimate the unknown structural function in the context of a transformation model.  相似文献   

7.
    
The paper discusses the asymptotic validity of posterior inference of pseudo‐Bayesian quantile regression methods with complete or censored data when an asymmetric Laplace likelihood is used. The asymmetric Laplace likelihood has a special place in the Bayesian quantile regression framework because the usual quantile regression estimator can be derived as the maximum likelihood estimator under such a model, and this working likelihood enables highly efficient Markov chain Monte Carlo algorithms for posterior sampling. However, it seems to be under‐recognised that the stationary distribution for the resulting posterior does not provide valid posterior inference directly. We demonstrate that a simple adjustment to the covariance matrix of the posterior chain leads to asymptotically valid posterior inference. Our simulation results confirm that the posterior inference, when appropriately adjusted, is an attractive alternative to other asymptotic approximations in quantile regression, especially in the presence of censored data.  相似文献   

8.
    
Adrian, Boyarchenko and Giannone ((2019), ABG) adapt quantile regression (QR) methods to examine the relationship between US economic growth and financial conditions. We confirm their empirical findings, using their methodology and their pre-2016 sample. Mindful of the importance of the Covid-19 pandemic, we extend the sample to 2021Q3 and find attenuation of the key estimated coefficients using ABG's empirical methods. Given the pandemic observations, we provide robust QR analysis of dependence based on ranked data and explain the relationship with extant copula modelling methods.  相似文献   

9.
    
Roger William Koenker was born February 21, 1947. He graduated from Grinnell College in 1969 and obtained his PhD in Economics from University of Michigan in 1974 under the direction of Saul Hymans. He was Assistant Professor of Economics at the University of Illinois at Urbana‐Champaign (UIUC) from 1974 to 1976, and a member of Technical Staff at Bell Telephone Laboratories from 1976 to 1983 and returned to UIUC as Professor in 1983. He is currently a William B. McKinley Professor of Economics and Professor of Statistics at UIUC. He is best known for his seminal work on quantile regression, which has emerged as a powerful regression analysis tool across many disciplines. He is a Fellow of the American Statistical Association, Fellow of the Institute of Mathematical Statistics, Fellow of Econometric Society, and recipient of the 2010 Emanuel and Carol Parzen Prize for Statistical Innovation. The conversation covers part of Roger Koenker's career as an econometrician and statistician, starting from his college years.  相似文献   

10.
We use the US data gathered by Reinhart and Rogoff (2010) to assess whether debt affects economic growth differently at different phases of the business cycle. In order to do that, we extend the threshold regression model of Chudik et al. (2017) and propose a new threshold quantile ARDL regression model. Our results show that to stimulate growth policy makers can manage the debt/GDP percentage according to how well the economy is doing. The estimated quantile thresholds (range 31–53 per cent) are larger than the one found by Lee et al. (2017) using median regressions, but still (much) smaller than the 90 per cent of Reinhart and Rogoff. In particular, when the US economy observes growth rates above their median value, that is when a smaller debt-to-GDP threshold affects the performance of the economy. In a steady-state situation, in general, regardless of the position of the business cycle and whether the debt-to-GDP ratio is below or above its threshold effect, less debt as a percentage of GDP boosts the US growth. Remarkably, this effect was always greater before than after World War II. Moreover, the most recent decades have witnessed the negative (positive) effect of more (less) debt when the economy had growth rates at their first quartile (median and third quartile). That is, the US policy makers are advised to reduce the debt-to-GDP ratio during expansions to promote growth.  相似文献   

11.
In human resource management (HRM) and allied fields (e.g., organizational behavior, management, and industrial and organizational psychology), tests of mediation are frequently conducted using the hierarchical multiple regression (HMR) strategy of Baron and Kenny [Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173–1182]. Although previous research has identified a number of serious problems with this approach, the present study adds to the literature by identifying yet additional problems with its use in inferring the existence of mediation. Using a statistical simulation, we found that certain patterns of correlation coefficients guarantee inferences about mediation, whereas other patterns preclude such inferences. On the basis of various analyses including logistic regression and inspection of three-dimensional plots, we identified patterns of correlation coefficients needed to satisfy Baron and Kenny's [Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173–1182] conditions for inferring mediation. The same patterns have no necessary relation to actual causal connections among variables in mediation models. Moreover, as a consequence of the failure of the HMR strategy to detect mediating effects, many instances of actual mediation in HRM and allied fields may have gone undetected. In view of the foregoing, we conclude that the HMR strategy should no longer be used in testing for mediation.  相似文献   

12.
本文使用1991年1月到2012年3月的样本数据对货币波动率和实际产出波动率之间的关系进行了检验。首先,应用GARCH模型度量货币波动率和产出波动率,进而对二者进行了Granger因果关系检验,发现我国货币供给增长率及其波动率对实际产出增长率及其波动率具有解释和预测能力。其次,使用分位数回归模型研究产出波动率在较小(低分位数)和较大(高分位数)时对货币供给量M0和M1波动率的不同反应程度。最后,提出了稳定产出增长,防止产出剧烈波动的货币政策建议。  相似文献   

13.
This study employs a new GARCH copula quantile regression model to estimate the conditional value at risk for systemic risk spillover analysis. To be specific, thirteen copula quantile regression models are derived to capture the asymmetry and nonlinearity of the tail dependence between financial returns. Using Chinese stock market data over the period from January 2007 to October 2020, this paper investigates the risk spillovers from the banking, securities, and insurance sectors to the entire financial system. The empirical results indicate that (i) three financial sectors contribute significantly to the financial system, and the insurance sector displays the largest risk spillover effects on the financial system, followed by the banking sector and subsequently the securities sector; (ii) the time-varying risk spillovers are much larger during the global financial crisis than during the periods of the banking liquidity crisis, the stock market crash and the COVID-19 pandemic. Our results provide important implications for supervisory authorities and portfolio managers who want to maintain the stability of China’s financial system and optimize investment portfolios.  相似文献   

14.
    
Small area estimation typically requires model‐based methods that depend on isolating the contribution to overall population heterogeneity associated with group (i.e. small area) membership. One way of doing this is via random effects models with latent group effects. Alternatively, one can use an M‐quantile ensemble model that assigns indices to sampled individuals characterising their contribution to overall sample heterogeneity. These indices are then aggregated to form group effects. The aim of this article is to contrast these two approaches to characterising group effects and to illustrate them in the context of small area estimation. In doing so, we consider a range of different data types, including continuous data, count data and binary response data.  相似文献   

15.
物流系统的数学模型   总被引:2,自引:0,他引:2  
万梅芳  陈以 《物流科技》2009,32(1):24-26
作为企业“第三利润源泉”的物流,对其成本的控制目前已经成为物流合理化进程中的热点问题。文章把物流系统看成是一个特殊的生产系统,用柯布一道格拉斯生产函数方程对其进行建模。把物流系统的产出——满足服务需求看成是此方程的产出,把运输费用、储存费用和管理费用看戍是投入.对物流系统的数学建模提供了一个新的方法。最后用这个物流系统模型对社会物流系统进行了实例验证。  相似文献   

16.
The solvency issue of life insurance companies has become more important in recent years as business risks turn increasingly greater. This study examines the relationship among investing risk, underwriting risk, and the capital ratio during the post risk-based capital regulation period of 2004–2009 in Taiwan. In addition to the two-stage least square regression (2SLS), we also adopt the two-stage quantile regression (2SQR) to capture the effects of low capital (or risk) levels and high capital (or risk) levels. 2SLS do not fully explain the capital-risk relation. Contrary to previous evidence reported in the U.S., our findings in 2SQR model indicate that the relationship between capital and underwriting risk is positive, while the relationship between investing risk and capital shows a reverse pattern. Overall, the 2SQR provides stronger evidence than the 2SLS.  相似文献   

17.
    
“Constant proportion portfolio insurance” is a popular technique among portfolio insurance strategies: the risky part of a portfolio is reallocated with respect to market conditions, via a fixed parameter (the multiple), guaranteeing a predetermined floor. We propose here to use a conditional time-varying multiple as an alternative. We provide the main properties of the conditional multiples for some mainstream cases, including discrete-time rebalancing and an underlying risk asset driven by the Lévy process, while evaluating conditional and unconditional gap risks. Finally, we evaluate the use of a dynamic autoregressive expectile model for estimating the conditional multiple in such a context.  相似文献   

18.
李晶 《价值工程》2013,(12):160-161
以我国2012年64家高科技上市公司为研究对象,利用分位数回归模型,检验了不同绩效水平的企业中高管人力资本对企业绩效的影响关系。实证结果表明不同企业绩效水平下各高管人力资本指标对企业绩效有不同的影响,并提出了一些相应的建议和对策。  相似文献   

19.
《Economic Systems》2022,46(2):100982
Economic growth is driven by numerous factors. However, traditional economic theory focuses on certain key reasons, while ignoring the impact of other factors. Since 1978, China has achieved unprecedented economic growth, but also faces low per capita GDP. To clarify the driving forces behind this situation, we used per capita GDP to represent China’s economic growth and performed total factor analysis based on 13 variables in 7 socioeconomic dimensions using panel data from 30 Chinese provinces over the 40 years since China opened to the west in 1978. We found similar determinants in different regressions. Internal trade, privatization and investment were the primary factors driving Chinese economic development. Surprisingly, we found that the contribution of foreign trade to economic growth (per capita GDP) was weak. Education had a much smaller contribution than science and technology. Using per capita income as the dependent variable to provide a robustness test, we found that China’s income distribution has not paralleled its economic development and the distribution of the benefits of GDP growth to citizens must be improved. China’s experience demonstrates that promoting economic growth requires coordinated development of many factors, and that different policy preferences should be adopted to meet different economic development conditions.  相似文献   

20.
    
The scope of this study is to investigate the main determinants of renewable energy investments in Greece. For this reason, we build an appropriate framework to infer the decision‐making process in the renewable energy sources (RES). The main drivers are then categorized under two groups as economic, and behavioral ones. In the next stage, we rely on binomial (logit and probit) and quantile regression analysis to estimate the impact of these factors on investment decisions towards RES. Our findings indicate that investors who gain better access to knowledge and exhibit a more positive attitude towards the contribution of artificial intelligence (AI) on the RES industry have a higher share of renewables in their portfolio. We argue that these investors are willing to invest a higher amount in the RES industry today. At the same time, quantile regression models illustrate that this relationship is nonmonotonic (i.e., inverted U shaped curve), arguing that positive attitudes towards the contribution of behavioral factors on RES are not adequate to encourage investments after crossing a certain point (threshold). Based on the empirical findings, we argue that the message to policymakers and government officials is to promote a faster penetration of low carbon technologies to achieve sustainable economic and social growth.  相似文献   

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