Econometrics Commons^™

Essays On High-Frequency Dynamics Of Asset Prices, Yuhong Zhu

Dissertations and Theses Collection (Open Access)

This dissertation studies econometric inference for high-frequency financial data, with a focus on detecting nonstandard drift and volatility dynamics in continuous-time models.

The first chapter proposes a new framework for uniform inference on explosive drift in high-frequency data, where conventional Gaussian approximations can fail due to the non-Gaussian behavior of short-window spot statistics. Under fixed-window asymptotics, these statistics are coupled with dependent t variables, and their maximum converges to a Fréchet distribution. We establish an anti-clustering condition for dependent t-statistics under overlapping windows and develop a feasible coupling-based test. Simulation results demonstrate better size control, and the empirical findings suggest …

Essays On Financial Econometrics, Yuexuan Ren

Dissertations and Theses Collection (Open Access)

This dissertation consists of two papers that contribute to the theory of estimation, inference, and prediction using high-frequency financial data. In the first chapter, time-varying betas from return regressions, commonly used to measure systematic financial market risk, are studied using high-frequency data. A novel econometric framework is introduced for the nonparametric estimation of these betas. The optimal finite-sample inference, in a well-defined sense, is enabled by the local Gaussian property of a generic continuous-time benchmark model under the fixed-k framework. Furthermore, a uniform functional inference theory for spot regressions is developed. The proposed methodology is broadly applicable in empirical settings, …

Essays On Estimating Firm-Level Production Function With Spatial Dependence, Bo Lin Ng

Dissertations and Theses Collection (Open Access)

This dissertation consists of two chapters on the estimation of firm-level production functions when spatial effects are present. In joint work with Pao-Li Chang, chapter 1 focuses on the impacts of global value chains (GVC) on the firm-level outcomes of Singapore. First, we quantify Singapore’s participation in global value chains (GVC) using the export decomposition framework of Borin and Mancini (2019), before using these indicators to analyse how GVC participation affects sectoral-level valueadded and employment. We find that gross exports and foreign final demand have become more important for Singapore’s value-added, largely driven by the Services sectors. We then use …

Essays On High-Frequency Financial Econometric, Qiyuan Li

Dissertations and Theses Collection (Open Access)

This dissertation consists of three papers contributing to the theory of estimation and inference of high-frequency financial data. In the second chapter, a general framework is introduced for optimal nonparametric spot volatility estimation based on intraday range data, comprised of the first, highest, lowest, and last prices over a given time interval. Employing a decisiontheoretic approach together with a coupling-type argument, the form of the nonparametric estimator is directly tailored to the specific volatility measure of interest and the relevant loss function. The resulting new optimal estimators offer substantial efficiency gains compared to existing commonly used range-based procedures. The third …

Essays On Weak Identification, Dennis Guo Wei Lim

Dissertations and Theses Collection (Open Access)

This dissertation presents a comprehensive examination of inference techniques for weak instrumental variable (IV) models, crucial in addressing endogeneity and bias in econometric analyses. Comprising two interconnected chapters, the research explores innovative methodologies to enhance the reliability and robustness of IV regression estimations. Chapter 1 is concerned with maximizing the power of tests in the many weak IVs setting. This is done by introducing a novel approach that considers a linear combination of jackknife Anderson-Rubin (AR), jackknife Lagrangian multiplier (LM), and orthogonalized jackknife
LM tests for inference in IV regressions with many weak instruments and heteroskedasticity. Following I. Andrews (2016), …

Essays On Culture, Institutions, And Development, Meng Liu

Dissertations and Theses Collection (Open Access)

This dissertation consists of three chapters that study culture, institutions, and economic development. In the first chapter, we study the impact of Confucianism on long-run development in northern Vietnam. Using the variation in Confucian literati across 217 historical districts between the Primitive Le and Nguyen dynasties (1426 CE - 1919 CE), we find that districts with greater exposure to Confucianism have experienced better economic outcomes over the past century. The result is robust to using the distance to exogenously located hermit Confucian as an instrument and accounting for a battery of confounders. We show that the positive effects of Confucianism …

Efficient Estimation Of Generalized Nonparametric Model Under Additive Structure, Ying Xia

Dissertations and Theses Collection (Open Access)

In this thesis, we develop novel nonparametric estimation techniques for two distinct classes of models: (1) Generalized Additive Models with Unknown Link Functions (GAMULF) and (2) Generalized Panel Data Transformation Models with Fixed Effects. Both models avoid parametric assumptions on their respective link or transformation functions, as well as the distribution of the idiosyncratic error terms.

The first chapter aims to provide an in-depth and systematic introduction to cross- sectional and panel-data nonparametric transformation models, encompassing practical applications, a diverse range of estimation techniques, and the study of asymptotic properties. We discuss the advantages and limitations of these models and …

Essays On Large Panel Data Models With Two-Way Heterogeneity, Yiren Wang

Dissertations and Theses Collection (Open Access)

This dissertation consists of two papers that contribute to the estimation and inference theory of the panel data models with two-way slope heterogeneity. The first paper considers the panel quantile regression model with slope heterogeneity along both individuals and time. By modelling this two-way heterogeneity with the low-rank slope matrix, the slope coefficient can be estimated via the nuclear norm regularization followed by sample-splitting, row- and column-wise quantile regression, and debiasing. The inferential theory for the final slope estimator along with its factor and factor loading is derived. Two specification tests are proposed: one tests whether the slope coefficient is …

Externalities In The Housing Market And Agglomeration Economies, Yifan Wu

Dissertations and Theses Collection (Open Access)

This thesis studies the externalities in the housing market and agglomeration economies. While knowledge-based externalities, or knowledge spillovers are one of the most important micro-foundations of agglomeration economies, the first chapter studies how knowledge spillovers from universities affect local innovation activities. In the second chapter, we propose a high-order spatiotemporal autoregression approach to study the externalities in the housing market. The third chapter studies another important but under explored aspect of the agglomeration economies – the role that marriage market plays in providing incentives to promote urbanization, along with the unique feminization phenomenon during this process.

The first chapter studies …

Spatial Panel Data Models: Unbalanced Panel, Threshold Effect And Network Structure, Xiaoyu Meng

Dissertations and Theses Collection (Open Access)

This thesis studies the estimation and inference problems for spatial panel data models when the panels are unbalanced, when the panels contain threshold effects, or when the panels contain time-varying network structures. These three scenarios divide the thesis naturally into three chapters.

The first chapter considers estimation and inferences for fixed effects spatial panel data models based on unbalanced panels that result from randomly missing spatial units. The unbalanced nature of the panel data renders the standard method of estimation inapplicable. In this chapter, we proposed an M-estimation method where the estimating functions are obtained by adjusting the concentrated quasi …

Bayesian And Machine Learning Methods With Applications In Asset Pricing, Yaohan Chen

Dissertations and Theses Collection (Open Access)

The dissertation consists of three essays on asset pricing by constructing new data set and developing new methodologies. In the first chapter, we conduct empirical studies on the volatility-managed portfolios in the Chinese stock market. Using data from the Chinese stock market, we have found that the main empirical findings in Moreira and Muir (2017) break down. Based on the empirical findings, we exploit a comprehensive set of $99$ equity strategies in the Chinese stock market to analyze the value of managed portfolios. Based on these $99$ equity trading strategies, we find that there exists no systematic gain from scaling …

Essays On Long Memory Time Series And Panel Models, Shuyao Ke

Dissertations and Theses Collection (Open Access)

This dissertation studies different long memory models. The first chapter considers a time series regression model where both the regressors and error term are locally stationary long memory processes with time-varying memory parameters, and the regression coefficients are also allowed to be time-varying. We consider a frequency-domain least squares estimator with kernelized discrete Fourier transform and derive its pointwise asymptotic normality and uniform consistency. A specification test on the constancy of coefficients is provided. The second chapter studies a linear regression panel data model with interactive fixed effects where the regressors, factors and idiosyncratic error terms are all stationary but …

Three Essays On Nonstationary Financial Econometrics, Yajie Zhang

Dissertations and Theses Collection (Open Access)

This dissertation consists of three essays that contribute to the theory of nonstationary time-series analysis.

The first chapter explores the inference procedures for predictive regressions with time-varying characteristics. We extend the self-generated instrumentation, called IVX, to incorporate persistent regressors of functional local-to-unity, functional mildly explosive, and functional mildly stationary roots. The asymptotic distributions of IVX estimators under time-varying parameters are novel and nonpivotal but lead to pivotal distributions of the corresponding Wald statistics that are robust across various roots. The numerical experiments justify the robustness of IVX testing procedures in finite samples. We also verify the existence of time-varying coefficients …

Spatial Panel Data Models With Temporal Heterogeneity, Yuhong Xu

Dissertations and Theses Collection (Open Access)

This dissertation studies the fixed effects (FE) spatial panel data (SPD) models with temporal heterogeneity (TH), where the regression coefficients and spatial coefficients are allowed to change with time. The FE-SPD model with time-varying coefficients renders the usual transformation method in dealing with the fixed effects inapplicable, and an adjusted quasi score (AQS) method is proposed, which adjusts the concentrated quasi score function with the fixed effects being concentrated out. AQS tests for the lack of temporal heterogeneity (TH) in slope and spatial parameters are first proposed. Then, a set of AQS estimation and inference methods for the FE-SPD model …

Essays On Multivariate Stochastic Volatility Models, Han Chen

Dissertations and Theses Collection (Open Access)

In this dissertation, I have made several contributions to the literature on the multivariate stochastic volatility model. First, I have considered a new multivariate stochastic volatility (MSV) model based on a recently proposed novel parameterization of the correlation matrix. This modeling design is a generalization of Fisher's z-transformation to the high-dimensional case. It is fully flexible as the validity of the resulting correlation matrix is guaranteed automatically. It allows me to completely separate the driving factors of volatilities and correlations. To conduct an econometric analysis of the proposed model, I develop a new Bayesian method that relies on the Markov …

Three Essays On Econometrics, Xin Zheng

Dissertations and Theses Collection (Open Access)

The dissertation includes three chapters on econometrics. The first chapter is about treatment effects and its application in randomized control trial. The second chapter is about specification test. The third chapter is about panel data model with fixed effects.

In the first chapter, we study the estimation and inference of the quantile treatment effect under covariate-adaptive randomization. We propose two estimation methods: (1) the simple quantile regression and (2) the inverse propensity score weighted quantile regression. For the two estimators, we derive their asymptotic distributions uniformly over a compact set of quantile indexes, and show that, when the treatment assignment …

Essays On Time Series And Financial Econometrics, Yijie Fei

Dissertations and Theses Collection (Open Access)

This dissertation contains four essays in financial econometrics. In the first essay, some asymptotic results are derived for first-order autoregression with a root moderately deviating from unity and a nonzero drift. It is shown that the drift changes drastically the large sample properties of the least-squares (LS) estimator. The second essay is concerned with the joint test of predictability and stability in the context of predictive regression. The null hypothesis under investigation is that the potential predictors exhibit no predictability and incur no structural break during the sample period. We first show that the IVX estimator provides better finite sample …

Essays On Nonstationary Econometrics, Yanbo Liu

Dissertations and Theses Collection (Open Access)

My dissertation consists of three essays that contribute new theoretical results to robust inference procedures and machine learning algorithms in nonstationary models.

Chapter 2 compares OLS and GLS in autoregressions with integrated noise terms. Grenander and Rosenblatt (2008) gave sufficient conditions for the asymptotic equivalence of GLS and OLS in deterministic trend extraction. However when extending to univariate autoregression model yt = ρnyt−1 + ut , ρn = 1 + c nα , ut = ut−1 + t , and t is one iid disturbance term with zero expectation and σ 2 variance, the asymptotic equivalence no longer holds. Under …

Essays On A Mechanism Design Approach To The Problem Of Bilateral Trade And Public Good Provision, Cuiling Zhang

Dissertations and Theses Collection (Open Access)

The dissertation consists of three chapters which studies a mechanism design approach to the problem of bilateral trade and public good provision.

Chapter 1 characterizes mechanisms satisfying Bayesian incentive compatibility (BIC) and interim individual rationality (IIR) in the classical public good provision problem. We propose a stress test for the results in the standard continuum type space by subject- ing them to a finite type space. The main contribution of this paper is to propose a set of techniques that allow us to characterize the efficient and optimal mechanisms in a discrete setup. Using these techniques, we conclude that many …

Three Essays On Nonstationary Time Series Econometrics, Yiu Lim Lui

Dissertations and Theses Collection (Open Access)

This dissertation comprises three papers that separately study different nonstationary time series models.

The first paper, titled as "The Grid Bootstrap for Continuous Time Models", is a joint work with Professor Jun Yu and Professor Weilin Xiao. It considers the grid bootstrap for constructing confidence intervals for the persistence parameter in a class of continuous-time models driven by a Lévy process. Its asymptotic validity is discussed under the assumption that the sampling interval (h) shrinks to zero, the time span (N) goes to infinity or both. Its improvement over the in-fill asymptotic theory is achieved by expanding the coefficient-based statistic …

Essays On Empirical Asset Pricing, Liyao Wang

Dissertations and Theses Collection (Open Access)

The dissertation consists of four chapters on empirical asset pricing. The first chapter reexamines the existence of time-series momentum. Time-series momentum (TSM) refers to the predictability of the past 12-month return on the next one month return. Using the same data set as Moskowitz, Ooi, and Pedersen (2012) (MOP, henceforth), we show that asset-by-asset time-series regressions reveal little evidence of TSM, both in- and out-of-sample. While the t -statistic in a pooled regression appears large, it is not statistically reliable as it is less than the critical values of parametric and nonparametric bootstraps. From an investment perspective, the performance of …

Nonstationary Panels With Unobserved Heterogeneity, Wenxin Huang

Dissertations and Theses Collection (Open Access)

This dissertation develops several econometric techniques to address the unobserved heterogeneity in nonstationary panels, namely identifying latent group structures in cointegrated panels, studying nonstationary panels with both cross-sectional dependence and latent group structures, and estimating panel error-correction model with unobserved dynamic common factors.

Chapter 1 considers a panel cointegration model with latent group structures that allows for heterogeneous long-run relations across groups. We extend Su et al. (2013) classifier-Lasso (C-Lasso) method to the nonstationary panels and allow for the presence of endogeneity in both the stationary and nonstationary regressors in the model. In addition, we allow the dimension of the …

Dispersion And Uncertainty In Density Forecasts: Evidence From Surveys Of Professional Forecasters, You Li

Dissertations and Theses Collection (Open Access)

This dissertation studies patterns of dispersion in density forecasts as reported in surveys of professional forecasters. We pay special attention to the role of uncertainty in explaining dispersion in professional forecasters’ density forecasts of real output growth and inflation. We also consider the relationship between survey design and forecaster behavior. The last chapter describes future research exploring the characteristics of forecaster expectations using probability integral transforms.

As a starting point, chapter one gives a summary of the literature that tries to answer, using data from survey of forecasters, the following three key questions: Why do forecasters disagree? What do density …

Three Essays On Panel Structure Models, Wuyi Wang

Dissertations and Theses Collection (Open Access)

In panel structure models, individuals can be classified into different groups with the slope parameters being homogeneous within the same group but heterogeneous across groups, both the number of groups and each individual’s group membership are unknown. This dissertation proposes some methods to identify the panel structure models under different specifications, namely, developing a Lasso-type Panel-CARDS method in the linear panel, constructing two sequential binary segmentation algorithms in the nonlinear panel, and using K-means algorithm in the spatial panel.

Chapter 2 studies the estimation of a linear panel data model with latent structures. To identify the unknown group structure of …

On Refined And Robust Inferences For Spatial Econometric Models, Shew Fan Liu

Dissertations and Theses Collection (Open Access)

Asymptotically refined and heteroskedasticity robust inferences are considered for spatial linear and panel regression models, based on the quasi maximum likelihood (QML) or the adjusted concentrated quasi score (ACQS) approaches. Refined inferences are achieved through bias correcting the QML estimators, bias correcting the t-ratios for covariate effects, and improving tests for spatial effects; heteroskedasticity-robust inferences are achieved through adjusting the quasi score functions. Several popular spatial linear and panel regression models are considered including the linear regression models with either spatial error dependence (SED), or spatial lag dependence (SLD), or both SED and SLD (SARAR), the linear regression models with …

Three Essays On Financial Econometrics, Jiang Liang

Dissertations and Theses Collection (Open Access)

This dissertation develops several econometric techniques to address three issues in financial economics, namely, constructing a real estate price index, estimating structural break points, and estimating integrated variance in the presence of market microstructure noise and the corresponding microstructure noise function. Chapter 2 develops a new methodology for constructing a real estate price index that utilizes all transaction price information, encompassing both single-sales and repeat-sales. The method is less susceptible to specification error than standard hedonic methods and is not subject to the sample selection bias involved in indexes that rely only on repeat sales. The methodology employs a model …

Three Essays On Nonstationary Time Series Analysis, Ye Chen

Dissertations and Theses Collection (Open Access)

Financial and macroeconomic time series data are often nonstationary. My dissertation consists of three essays concerning time series models with nonstationarity. Chapter 1 develops a new jackknife estimator for nonstationary autoregressive model. The remaining two chapters explore the restricted maximum likelihood (REML hereafter) estimation and the restricted maximum likelihood based likelihood ratio test (RLRT hereafter) in predictive regression. Chapter 1 proposes an improved jackknife estimator of the persistence parameter that works for both the discrete time unit root model and the continuous time unit root model. Maximum likelihood estimation of the persistence parameter in the discrete time unit root model …

Three Essays On Large Panel Data Models With Cross-Sectional Dependence, Yonghui Zhang

Dissertations and Theses Collection (Open Access)

My dissertation consists of three essays which contribute new theoretical results to large panel data models with cross-sectional dependence. These essays try to answer or partially answer some prominent questions such as how to detect the presence of cross-sectional dependence and how to capture the latent structure of cross-sectional dependence and estimate parameters efficiently by removing its effects. Chapter 2 introduces a nonparametric test for cross-sectional contemporaneous dependence in large dimensional panel data models based on the squared distance between the pair-wise joint density and the product of the marginals. The test can be applied to either raw observable data …

Three Econometric Essays On Continuous Time Models, Xiaohu Wang

Dissertations and Theses Collection (Open Access)

Multivariate continuous time models are now widely used in economics and finance. Empirical applications typically rely on some process of discretization so that the system may be estimated with discrete data. The Chapter 2 introduces a framework for discretizing linear multivariate continuous time systems that includes the commonly used Euler and trapezoidal approximations as special cases and leads to a general class of estimators for the mean reversion matrix. Asymptotic distributions and bias formulae are obtained for estimates of the mean reversion parameter. Explicit expressions are given for the discretization bias and its relationship to estimation bias in both multivariate …

Testing Heterogeneity In Panel Data Models With Interactive Fixed Effects, Qihui Chen

Dissertations and Theses Collection (Open Access)

This paper proposes a test for the slope homogeneity in large dimensional panel data models with interactive fixed effects based on a measure of goodness-of-fit (R²). We first obtain, for each cross-sectional unit, the R² from the time series regression of residuals on the constant and observable regressors and then construct the test statistic R² as an equally weighted average of the cross-sectional R²'s. R̄² is close to 0 under the null hypothesis of homogenous slopes and deviates away from 0 otherwise. We show that after being appropriately centered and scaled, R^{2 …}