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Semiparametric Estimation in Network Formation Models with Homophily and Degree Heterogeneity 具有同态和程度异质性的网络形成模型的半参数估计
ERN: Model Construction & Estimation (Topic) Pub Date : 2017-11-03 DOI: 10.2139/ssrn.2988698
Peter Tóth
{"title":"Semiparametric Estimation in Network Formation Models with Homophily and Degree Heterogeneity","authors":"Peter Tóth","doi":"10.2139/ssrn.2988698","DOIUrl":"https://doi.org/10.2139/ssrn.2988698","url":null,"abstract":"This paper considers a semiparametric version of the network formation model of Graham (2017). The two-way fixed-effects binary choice model allows for homophily and degree heterogeneity, but unlike Graham (2017) leaves the distribution of pair-specific unobservables unspecified. Identification of the slope parameters and fixed effects follows from a novel approach that does not rely on distributional assumptions. The identification strategy suggests an estimator for the slope parameters based upon tetrads of nodes within the network. A computationally simple version of this estimator is shown to be consistent with a non-parametric convergence rate. A consistent estimator of the fixed effects is also provided. Partial identification, for the case of discrete covariate support, and an extension to nonlinear fixed effects are also considered.","PeriodicalId":273058,"journal":{"name":"ERN: Model Construction & Estimation (Topic)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115676642","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
Estimating Discrete-Time Gaussian Term Structure Models in Canonical Companion Form 离散时间高斯期限结构模型的正则伴形估计
ERN: Model Construction & Estimation (Topic) Pub Date : 2017-10-08 DOI: 10.2139/ssrn.2867896
Juliusz F. Radwanski
{"title":"Estimating Discrete-Time Gaussian Term Structure Models in Canonical Companion Form","authors":"Juliusz F. Radwanski","doi":"10.2139/ssrn.2867896","DOIUrl":"https://doi.org/10.2139/ssrn.2867896","url":null,"abstract":"This article formally introduces a convenient parametrization for the popular class of discrete-time essentially-affine term structure models in the spirit of Duffee (2002), and Ang and Piazzesi (2003). First, I show that if the term structure is spanned by N_f latent state variables, all pricing information must also be contained in N_f shortest-maturity forward rates. Every no-arbitrage model of the type studied is therefore observationally equivalent to a unique canonical model in which these forward rates act as factors. Second, the risk-neutral transition matrix of the canonical model is conveniently parametrized by N_f unrestricted real numbers, and the risk neutral drift is a function of factor covariance matrix, plus one extra parameter. Third, although it may appear restrictive to specify the shortest-maturity forward rates as factors, the model can be estimated using all information in observed bond prices, either by Kalman filter, or assuming perfect observability of certain combinations of yields. Monte-Carlo evidence suggests that both approaches lead to similar out-of-sample forecasting performance in artificial data sets. Finally, by using unique insights offered by the canonical companion form, I discuss some difficulties in fitting term structure models of the essentially-affine class to the standard set of Fama-Bliss discount bonds. The problems stem from the existence of factors seemingly inconsistent with the assumption of no arbitrage. This discussion may have implications for interpreting the evidence of bond return predictability, and for the question of whether imposing no arbitrage can improve yield forecasts.","PeriodicalId":273058,"journal":{"name":"ERN: Model Construction & Estimation (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129768556","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
From Tick Data to Semimartingales 从Tick Data到半鞅
ERN: Model Construction & Estimation (Topic) Pub Date : 2017-10-06 DOI: 10.2139/ssrn.3049113
Yacine Ait-Sahalia, J. Jacod
{"title":"From Tick Data to Semimartingales","authors":"Yacine Ait-Sahalia, J. Jacod","doi":"10.2139/ssrn.3049113","DOIUrl":"https://doi.org/10.2139/ssrn.3049113","url":null,"abstract":"Tick-by-tick asset price data exhibit a number of empirical regularities, including discreteness, long periods where prices are flat, periods of price moves of alternating plus and minus one tick, periods of rapid successive price moves of the same sign, and others. This paper proposes a framework to examine whether and how these microscopic features of the tick data are compatible with the typical macroscopic continuous-time models, based on Ito semimartingales, that are employed to represent asset prices. We construct in particular tick-by-tick models that deliver by scaling macroscopic semimartingale models with stochastic volatility and jumps.","PeriodicalId":273058,"journal":{"name":"ERN: Model Construction & Estimation (Topic)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126921830","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: 3
Discretizing Unobserved Heterogeneity 离散化未观测异质性
ERN: Model Construction & Estimation (Topic) Pub Date : 2017-03-22 DOI: 10.2139/ssrn.3333452
S. Bonhomme, T. Lamadon, E. Manresa
{"title":"Discretizing Unobserved Heterogeneity","authors":"S. Bonhomme, T. Lamadon, E. Manresa","doi":"10.2139/ssrn.3333452","DOIUrl":"https://doi.org/10.2139/ssrn.3333452","url":null,"abstract":"We study discrete panel data methods where unobserved heterogeneity is revealed in a first step, in environments where population heterogeneity is not discrete. We focus on \u0000 two‐step grouped fixed‐effects (GFE) estimators, where individuals are first classified into groups using \u0000 kmeans clustering, and the model is then estimated allowing for group‐specific heterogeneity. Our framework relies on two key properties: heterogeneity is a function—possibly nonlinear and time‐varying—of a low‐dimensional continuous latent type, and informative moments are available for classification. We illustrate the method in a model of wages and labor market participation, and in a probit model with time‐varying heterogeneity. We derive asymptotic expansions of two‐step GFE estimators as the number of groups grows with the two dimensions of the panel. We propose a data‐driven rule for the number of groups, and discuss bias reduction and inference.\u0000","PeriodicalId":273058,"journal":{"name":"ERN: Model Construction & Estimation (Topic)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130006810","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: 72
Parameter Reduction in Actuarial Triangle Models 精算三角模型的参数约简
ERN: Model Construction & Estimation (Topic) Pub Date : 2017-01-19 DOI: 10.2139/ssrn.2992300
G. Venter, Roman Gutkovich, Qian Gao
{"title":"Parameter Reduction in Actuarial Triangle Models","authors":"G. Venter, Roman Gutkovich, Qian Gao","doi":"10.2139/ssrn.2992300","DOIUrl":"https://doi.org/10.2139/ssrn.2992300","url":null,"abstract":"Very similar modeling is done for actuarial models in loss reserving and mortality projection. Both start with incomplete data rectangles, traditionally called triangles, and model by year of origin, year of observation, and lag from origin to observation. Actuaries using these models almost always use some form of parameter reduction as there are too many parameters to fit reliably, but usually this is an ad hoc exercise. Here we try two formal statistical approaches to parameter reduction, random effects and Lasso, and discuss methods of comparing goodness of fit.","PeriodicalId":273058,"journal":{"name":"ERN: Model Construction & Estimation (Topic)","volume":"278 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121040559","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
Structural Estimation of Pairwise Stable Networks: An Application to Social Networks in Rural India 两两稳定网络的结构估计:在印度农村社会网络中的应用
ERN: Model Construction & Estimation (Topic) Pub Date : 2017-01-10 DOI: 10.2139/ssrn.2262092
Jun Sung Kim
{"title":"Structural Estimation of Pairwise Stable Networks: An Application to Social Networks in Rural India","authors":"Jun Sung Kim","doi":"10.2139/ssrn.2262092","DOIUrl":"https://doi.org/10.2139/ssrn.2262092","url":null,"abstract":"This paper studies what we can learn from pairwise stable networks. Recent literature on empirical models of strategic network formation confronts problems such as the curse of dimensionality and multiple equilibria. To solve these problems, I consider the probability that the observed network is pairwise stable, instead of the probability that a certain equilibrium outcome is observed. Pairwise stability provides conditions under which no pairs of individuals have an incentive to deviate from the current network configuration. Pairwise stability and the assumption of myopic agents contained in it give strong identification power when we consider the probability that the observed network is pairwise stable. I propose a semiparametric maximum score estimator which is simple and computationally feasible. I applied the empirical model to different types of social networks in rural India. Estimation results show that individuals have strong homophily on castes in all types of social networks.","PeriodicalId":273058,"journal":{"name":"ERN: Model Construction & Estimation (Topic)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126064442","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: 4
Heterogeneous Archimedean Copula 异质阿基米德Copula
ERN: Model Construction & Estimation (Topic) Pub Date : 2016-12-05 DOI: 10.2139/ssrn.2880622
L. Overbeck
{"title":"Heterogeneous Archimedean Copula","authors":"L. Overbeck","doi":"10.2139/ssrn.2880622","DOIUrl":"https://doi.org/10.2139/ssrn.2880622","url":null,"abstract":"Archimedean copulae build a large family of copulae exhibiting tail-dependency in many cases. We extend the classical homogeneous (exchangeable) Archimedean copula to the heterogeneous case. This will extend the use of this copula family to multivariate random variable with pairwise different dependencies.","PeriodicalId":273058,"journal":{"name":"ERN: Model Construction & Estimation (Topic)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131529372","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
Another Look at Single-Index Models Based on Series Estimation 再看一下基于序列估计的单指数模型
ERN: Model Construction & Estimation (Topic) Pub Date : 2016-10-22 DOI: 10.2139/ssrn.2858624
Chaohua Dong, Jiti Gao, B. Peng
{"title":"Another Look at Single-Index Models Based on Series Estimation","authors":"Chaohua Dong, Jiti Gao, B. Peng","doi":"10.2139/ssrn.2858624","DOIUrl":"https://doi.org/10.2139/ssrn.2858624","url":null,"abstract":"In this paper, a semiparametric single-index model is investigated. The link function is allowed to be unbounded and has unbounded support that answers a pen ding issue in the literature. Meanwhile, the link function is treated as a point in an infinitely many dimensional function space which enables us to derive the estimates for the index parameter and the link function simultaneously. This approach is different from the profile method commonly used in the literature. The estimator is derive d from an optimization with the constraint of identification condition for index parameter, which is a natural way but ignored in the literature. In addition, making use of a property of Hermite orthogonal polynomials, an explicit estimator for the index parameter is obtained. Asymptotic properties for the two estimators of the index parameter are established. Their efficiency is discussed in some special cases as well. The finite sample properties of the two estimates are demonstrated through an extensive Monte Carlo study and an empirical example.","PeriodicalId":273058,"journal":{"name":"ERN: Model Construction & Estimation (Topic)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133078583","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: 2
Sparse Multivariate GARCH 稀疏多元GARCH
ERN: Model Construction & Estimation (Topic) Pub Date : 2016-06-15 DOI: 10.2139/ssrn.2799549
Wu Jianbin, G. Dhaene
{"title":"Sparse Multivariate GARCH","authors":"Wu Jianbin, G. Dhaene","doi":"10.2139/ssrn.2799549","DOIUrl":"https://doi.org/10.2139/ssrn.2799549","url":null,"abstract":"We propose sparse versions of multivariate GARCH models that allow for volatility and correlation spillover effects across assets. The proposed models are generalizations of existing diagonal DCC and BEKK models, yet they remain estimable for high-dimensional systems of asset returns. To cope with the high dimensionality of the model parameter spaces, we employ the L1 regularization technique to penalize the off-diagonal elements of the coefficient matrices. A simulation experiment for the sparse DCC model shows that the true underlying sparse parameter structure can be uncovered reasonably well. In an application to weekly and daily market returns for 24 countries using data from 1994 to 2014, we find that the sparse DCC model outperforms the standard DCC and the diagonal DCC models in and out of sample. Likewise, the sparse BEKK model outperforms the diagonal BEKK model.","PeriodicalId":273058,"journal":{"name":"ERN: Model Construction & Estimation (Topic)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116519488","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: 3
An Overview of Spatial Econometrics 空间计量经济学概论
ERN: Model Construction & Estimation (Topic) Pub Date : 2016-05-11 DOI: 10.2139/ssrn.2778679
Alexander J. Tybl
{"title":"An Overview of Spatial Econometrics","authors":"Alexander J. Tybl","doi":"10.2139/ssrn.2778679","DOIUrl":"https://doi.org/10.2139/ssrn.2778679","url":null,"abstract":"This paper offers an expository overview of the field of spatial econometrics. It first justifies the necessity of special statistical procedures for the analysis of spatial data and then proceeds to describe the fundamentals of these procedures. In particular, this paper covers three crucial techniques for building models with spatial data. First, we discuss how to create a spatial weights matrix based on the distances between each data point in a dataset. Next, we describe the conventional methods to formally detect spatial autocorrelation – both global and local. Finally, we outline the chief components of a spatial autoregressive model, noting the circumstances under which it would be appropriate to incorporate each component into a model. This paper seeks to offer a concise introduction to spatial econometrics that will be accessible to interested individuals with a background in statistics or econometrics.","PeriodicalId":273058,"journal":{"name":"ERN: Model Construction & Estimation (Topic)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124859732","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
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