Econometrics Commons^™

Econometric Estimates Of Earth's Transient Climate Sensitivity, Peter C. B. Phillips, Thomas Leirvik, Trude Storelvmo

Research Collection School Of Economics

How sensitive is Earth's climate to a given increase in atmospheric greenhouse gas (GHG) concentrations? This long-standing question in climate science was recently analyzed by dynamic panel data methods using extensive spatio-temporal data of global surface temperatures, solar radiation, and GHG concentrations over the last half century to 2010 (Storelvmo et al, 2016). Those methods revealed that atmospheric aerosol effects masked approximately one-third of the continental warming due to increasing GHG concentrations over this period, thereby implying greater climate sensitivity to GHGs than previously thought. The present study provides regularity conditions and asymptotic theory justifying the use of time series …

Specification Tests For Temporal Heterogeneity In Spatial Panel Models With Fixed Effects, Yuhong Xu, Zhenlin Yang

Research Collection School Of Economics

We propose score type tests for testing the existence of temporal heterogeneity in slope and spatial parameters in spatial panel data (SPD) models, allowing for the presence of individual-specific and/or time-specific fixed effects (or in general intercept heterogeneity). The SPD model with spatial lag effect is treated in detail by first considering the model with individual-specific effects only, and then extending it to the model with both individual and time specific effects. Two types of tests (naive and robust) are proposed, and their asymptotic properties are presented. These tests are then fully extended to an SPD model with both spatial …

Nonstationary Panel Models With Latent Group Structures And Cross-Section Dependence, Wenxin Huang, Sainan Jin, Peter C. B. Phillips, Liangjun Su

Research Collection School Of Economics

This paper proposes a novel Lasso-based approach to handle unobserved parameter heterogeneity and cross-section dependence in nonstationary panel models. In particular, a penalized principal component (PPC) method is developed to estimate group-specific long-run relationships and unobserved common factors and jointly to identify the unknown group membership. The PPC estimators are shown to be consistent under weakly dependent innovation processes. But they suffer an asymptotically non-negligible bias from correlations between the nonstationary regressors and unobserved stationary common factors and/or the equation errors. To remedy these shortcomings we provide three bias-correction procedures under which the estimators are re-centered about zero as both …

A Comparative Analysis On Output Gap - Inflation Relation: The New Keynesian Approach, Oladimeji Tomiwa Shodipe

Masters Theses

The thrust of this research paper is to examine the inflation information that is contained in the output gap using the New Keynesian Phillips Curve framework. As informed by the model, the study also sets to investigate inflation persistence and the influence of forward inertia on the current inflation. This paper follows the Gali and Monacelli (2005) of the small open-economy type of model. However, the current study differs by introducing external factors (trade and real exchange rate) not only on the hybrid model, also on the backward, forward and the hybrid restricted models for time-series data (1971-2017) of all …

The Relationship Between Commuting Habits And Mortality Rates In The United States, Samuel Earl Supplee-Niederman

Graduate Student Theses, Dissertations, & Professional Papers

In recent years, policy makers have invested in public transportation and infrastructure to promote walking and cycling to work. There is also a large body of economic research that has found mortality rates increase during economic expansions. While there has been a number of epidemiological studies that investigate the impact of commuting mode choice on individual health outcomes, there is a lack of research on the aggregate health effects of alternative transportation methods, such as biking, walking, or using public transportation. This paper uses a fixed-effect model to investigate the impact of an increase in total employment on mortality rates, …

Do You Want To Run A Regression? Nah, I Think I’Ll Dance One Instead: Physicalizing Econometrics, Rachel Lau

Senior Independent Study Theses

This project asked how can one make use of an econometric tool, specifically the regression model, as a source for choreography. Through integrating my research on dance choreography and econometrics, I created a dance piece that demonstrates the numerical relationships of a realized regression equation. The dance was separated into three sections, with each examining an econometric concept. Taking the primary question at hand one step further, this project also explored how this approach to choreography can be generalized so that almost any regression model can be a choreographic tool. Subsequently, a guideline was devised to provide other choreographers various …

A Full Characterization Of Best-Response Functions In The Lottery Colonel Blotto Game, Dan Kovenock, David Rojo Arjona

ESI Working Papers

We fully characterize best-response functions in Colonel Blotto games with lottery contest success functions.

Money Is More Than Memory, Maria Bigoni, Gabriele Camera, Marco Casari

ESI Working Papers

Impersonal exchange is the hallmark of an advanced society and money is one key institution that supports it. Economic theory regards money as a crude arrangement for monitoring counterparts’ past conduct. If so, then a public record of past actions—or memory—should supersede the function performed by money. This intriguing theoretical postulate remains untested. In an experiment, we show that the suggested functional equivalence between money and memory does not translate into an empirical equivalence: money removed the incentives to free ride, while memory did not. Monetary systems performed a richer set of functions than just revealing past behaviors.

Modeling Interactions Between Risk, Time, And Social Preferences, Mark Schneider

ESI Working Papers

Recent studies have observed systematic interactions between risk, time, and social preferences that constitute violations of `dimensional independence' and are not explained by the leading models of decision making. This note provides a simple approach to modeling such interaction effects while predicting new ones. In particular, we present a model of rational-behavioral preferences that takes the convex combination of `behavioral' System 1 preferences and `rational' System 2 preferences. The model provides a unifying approach to analyzing risk, time, and social preferences, and predicts how these preferences are correlated with reliance on System 1 or System 2 thinking.

A Dual System Model Of Risk And Time Preferences, Mark Schneider

ESI Working Papers

Discounted Expected Utility theory has been a workhorse in economic analysis for over half a century. However, it cannot explain empirical violations of 'dimensional independence' demonstrating that risk interacts with time preference and time interacts with risk preference, nor does it explain present bias or magnitude-dependence in risk and time preferences, or correlations between risk preference, time preference, and cognitive reflection. We demonstrate that these and other anomalies are explained by a dual system model of risk and time preferences that unless models of a rational economic agent, models based on prospect theory, and dual process models of decision making.

Essays On Energy Economics And Environmental Policies, Janak R. Joshi

Economics ETDs

This dissertation contains three distinct empirical chapters in applied energy and environmental economics. Each chapter focuses on a unique set of research questions, methods, and data. The unifying motivation therein concerns the development of renewable or alternative low-carbon energy sources as a policy response to the challenges of climate change mitigation, local and regional environmental quality issues, and energy security concerns. Economic and environmental evaluation of the energy policies coupled with understanding energy use patterns is of paramount importance. Together, the empirical chapters focus on demand, supply, and policy aspects of energy markets in the United States (US).

First, Chapter …

A Snowball's Chance: Debt Snowball Vs. Debt Avalanche, Evan Mcallister

Senior Honors Projects, 2010-2019

Traditional mathematical analysis states that the most efficient way to pay off interest-bearing consumer debt is to pay the individual debts in order from largest to smallest interest rate. In doing this, the debtor will eliminate the largest sources of interest first, thus shortening the overall time-to-pay. This method is known as the “Debt Avalanche.” The “Debt Snowball” method, popularized in large part by investor-author David Ramsey, recommends that consumers pay debts in order from smallest to largest, regardless of interest rate. In this paper, I conduct an empirical analysis of the Federal Reserve’s Survey of Consumer Finance (SCF), calculating …

The Principal Problem With Principal Components Regression, Heidi Margaret Artigue, Gary Smith

Pomona Faculty Publications and Research

Principal components regression (PCR) reduces a large number of explanatory variables down to a small number of principal components. PCR is thought to be more useful, the more numerous the potential explanatory variables. The reality is that a large number of candidate explanatory variables does not make PCR more valuable; instead, it magnifies the failings of PCR.

Using Response Times To Measure Ability On A Cognitive Task, Aleksandr Alekseev

ESI Working Papers

I show how using response times as a proxy for effort coupled with an explicit process-based model can address a long-standing issue of how to separate the effect of cognitive ability on performance from the effect of motivation. My method is based on a dynamic stochastic model of optimal effort choice in which ability and motivation are the structural parameters. I show how to estimate these parameters from the data on outcomes and response times in a cognitive task. In a laboratory experiment, I find that performance on a Digit-Symbol test is a noisy and biased measure of cognitive ability. …

Rhode Island Current Conditions Index -- December 2018, Leonard Lardaro

The Rhode Island Current Conditions Index

No abstract provided.

Mild-Explosive And Local-To-Mild-Explosive Autoregressions With Serially Correlated Errors, Yiu Lim Lui, Weilin Xiao, Jun Yu

Research Collection School Of Economics

This paper firstly extends the results of Phillips and Magdalinos (2007a) by allowing for anti-persistent errors in mildly explosive autoregressive models. It is shown that the Cauchy asymptotic theory remains valid for the least squares (LS) estimator. The paper then extends the results of Phillips, Magdalinos and Giraitis (2010) by allowing for serially correlated errors of various forms in local-to-mild-explosive autoregressive models. It is shown that the result of smooth transition in the limit theory between local-to-unity and mild-explosiveness remains valid for the LS estimator. Finally, the limit theory for autoregression with intercept is developed.

Root-N Consistency Of Intercept Estimators In A Binary Response Model Under Tail Restrictions, Lili Tan, Yichong Zhang

Research Collection School Of Economics

The intercept of the binary response model is irregularly identified when the supports of both the special regressor V and the error term ε are the whole real line. This leads to the estimator of the intercept having potentially a slower than √n convergence rate, which can result in a large estimation error in practice. This paper imposes addition tail restrictions which guarantee the regular identification of the intercept and thus the √n-consistency of its estimator. We then propose an estimator that achieves the √n rate. Finally, we extend our tail restrictions to a full-blown model with endogenous regressors.

Semiparametric Maximum Likelihood Inference For Nonignorable Nonresponse With Callbacks, Zhong Guan, Denis H. Y. Leung, Jing Qin

Research Collection School Of Economics

We model the nonresponse probabilities as logistic functions ofthe outcome variable and other covariates in the survey sampling study withcallback. The identification aspect of this callback model is investigated. Semiparametricmaximum likelihood estimators of the parameters in the responseprobabilities are proposed and studied. As a result, an efficient estimator ofthe mean of the outcome variable is constructed using the estimated responseprobabilities. Moreover, if a regression model for conditional mean of the outcomevariable given some covariate is available, then we can obtain an evenmore efficient estimate of the mean of the outcome variable by fitting the regressionmodel using an adjusted least squares …

Quantile Treatment Effects And Bootstrap Inference Under Covariate-Adaptive Randomization, Xin Zheng, Yichong Zhang

Research Collection School Of Economics

This paper studies the estimation and inference of the quantile treatment effect under covariate-adaptive randomization. We propose three estimation methods: (1) the simple quantile regression (QR), (2) the QR with strata fixed effects, and (3) the inverse propensity score weighted QR. For the three estimators, we derive their asymptotic distributions uniformly over a set of quantile indexes and show that the estimator obtained from inverse propensity score weighted QR weakly dominates the other two in terms of efficiency, for a wide range of randomization schemes. For inference, we show that the weighted bootstrap tends to be conservative for methods (1) …

Forecasting Large Covariance Matrix With High-Frequency Data: A Factor Correlation Matrix Approach, Yingjie Dong, Yiu Kuen Tse

Research Collection School Of Economics

We propose a factor correlation matrix approach to forecast large covariance matrix of asset returns using high-frequency data. We apply shrinkage method to estimate large correlation matrix and adopt principal component method to model the underlying latent factors. A vector autoregressive model is used to forecast the latent factors and hence the large correlation matrix. The realized variances are separately forecasted using the Heterogeneous Autoregressive model. The forecasted variances and correlations are then combined to forecast large covariance matrix. We conduct Monte Carlo studies to compare the finite sample performance of several methods of forecasting large covariance matrix. Our proposed …

On Booms That Never Bust: Ambiguity In Experimental Asset Markets With Bubbles, Brice Corgnet, Roberto Hernán-González, Praveen Kujal

ESI Working Papers

We study the effect of ambiguity on the formation of bubbles and on the occurrence of crashes in experimental asset markets à la Smith, Suchanek, and Williams (1988). We extend their framework to an environment where the fundamental value of the asset is ambiguous. We show that, when the fundamental value is ambiguous, asset prices tend to be lower than when it is risky although bubbles form in both the ambiguous and the risky environments. Additionally, bubbles do not crash in the ambiguous case whereas they do so in the risky one. These findings regarding depressed prices and the absence …

Determinants Of Parking Fees On College Campuses, Hannah Huckeby

Posters-at-the-Capitol

The price of parking has recently been a hot topic around the Murray area, especially among the college students. Due to the drastic increase in parking pass prices there has been an abundant amount of discussion surrounding this idea of parking being a public good. Many individuals have been outraged which has brought up the questions of why there is a price tag on something that many people consider a public good. With that being said, this paper is going to take a deeper look into parking specifically pertaining to college campuses but also in the cities surrounding these institutions. …

Conditional Independence In A Binary Choice Experiment, Nathaniel Wilcox

ESI Working Papers

Experimental and behavioral economists, as well as psychologists, commonly assume conditional independence of choices when constructing likelihood functions for structural estimation. I test this assumption using data from a new experiment designed for this purpose. Within the limits of the experiment’s identifying restriction and designed power to detect deviations from conditional independence, conditional independence is not rejected. In naturally occurring data, concerns about violations of conditional independence are certainly proper and well-taken (for well-known reasons). However, when an experimenter employs contemporary state-of-the-art experimental mechanisms and designs, the current evidence suggests that conditional independence is an acceptable assumption for analyzing data …

Selection In The Lab: A Network Approach, Aleksandr Alekseev, Mikhail Freer

ESI Working Papers

We study the selection problem in economic experiments by focusing on its dynamic and network aspects. We develop a dynamic network model of student participation in a subject pool, which assumes that students' participation is driven by the two channels: the direct channel of recruitment and the indirect channel of student interaction. Using rich recruitment data from a large public university, we find that the patterns of participation and biases are consistent with the model. We also find evidence of both short- and long-run selection biases between males and females, as well as between cohorts of students. Males tend to …

The Econometric Analysis Of The Factors Affecting The Revenue Of Bangkok Port, Viyada Suriyakul Na Ayudhaya, Praew Ritthirungrat

World Maritime University Dissertations

No abstract provided.

Rhode Island Current Conditions Index -- November 2018, Leonard Lardaro

The Rhode Island Current Conditions Index

No abstract provided.

Threshold Regression Asymptotics: From The Compound Poisson Process To Two-Sided Brownian Motion, Ping Yu, Peter C. B. Phillips

Research Collection School Of Economics

The asymptotic distribution of the least squares estimator in threshold regression is expressed in terms of a compound Poisson process when the threshold effect is fixed and as a functional of two-sided Brownian motion when the threshold effect shrinks to zero. This paper explains the relationship between this dual limit theory by showing how the asymptotic forms are linked in terms of joint and sequential limits. In one case, joint asymptotics apply when both the sample size diverges and the threshold effect shrinks to zero, whereas sequential asymptotics operate in the other case in which the sample size diverges first …

Identifying Latent Grouped Patterns In Cointegrated Panels, Wenxin Huang, Sainan Jin, Liangjun Su

Research Collection School Of Economics

We consider a panel cointegration model with latent group structures that allows for heterogeneous long-run relationships across groups. We extend Su, Shi, and Phillips’ (2016) 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 stationary regressors to diverge with the sample size. We show that we can identify the individuals’ group membership and estimate the group-specific long-run cointegrated relationships simultaneously. We demonstrate the desirable property of uniform classification consistency and the oracle properties of both the C-Lasso …

The Grid Bootstrap For Continuous Time Models, Yiu Lim Lui, Weilin Xiao, Jun Yu

Research Collection School Of Economics

This paper considers the grid bootstrap for constructing confidence intervals for the persistence parameter in a class of continuous time models driven by a Levy process. Its asymptotic validity is established by assuming the sampling interval (h) shrinks to zero. Its improvement over the in-fill asymptotic theory is achieved by expanding the coefficient-based statistic around its in fill asymptotic distribution which is non-pivotal and depends on the initial condition. Monte Carlo studies show that the gird bootstrap method performs better than the in-fill asymptotic theory and much better than the long-span theory. Empirical applications to U.S. interest rate data highlight …

Specification Tests Based On Mcmc Output, Yong Li, Jun Yu, Tao Zeng

Research Collection School Of Economics

Two test statistics are proposed to determine model specification after a model is estimated by an MCMC method. The first test is the MCMC version of IOSA test and its asymptotic null distribution is normal. The second test is motivated from the power enhancement technique of Fan et al. (2015). It combines a component (J1) that tests a null point hypothesis in an expanded model and a power enhancement component (J0) obtained from the first test. It is shown that J0 converges to zero when the null model is correctly specified and diverges when the null model is misspecified. Also …