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2024

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Articles 91 - 120 of 153

Full-Text Articles in Econometrics

Better The Devil You Know: Improved Forecasts From Imperfect Models, Dong Hwan Oh, Andrew John Patton May 2024

Better The Devil You Know: Improved Forecasts From Imperfect Models, Dong Hwan Oh, Andrew John Patton

Research Collection School Of Economics

Many important economic decisions are based on a parametric forecasting model that is known to be good but imperfect. We propose methods to improve out-of-sample forecasts from a misspecified model by estimating its parameters using a form of local M estimation (thereby nesting local OLS and local MLE), drawing on information from a state variable that is correlated with the misspecification of the model. We theoretically consider the forecast environments in which our approach is likely to offer improvements over standard methods, and we find significant forecast improvements from applying the proposed method across four distinct empirical analyses including volatility …

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Exploring Diversity, Discrimination, And Performance Dynamics, George Agyeah May 2024

Exploring Diversity, Discrimination, And Performance Dynamics, George Agyeah

Graduate Theses and Dissertations

This dissertation utilizes empirical and experimental approaches to investigate the multifaceted factors that affect decision-making in economic contexts. The three chapters place a particular focus on group affiliation, perceived discrimination, and the gender gap in entrepreneurship. The first chapter explores the impact of team diversity on economic decision-making within a dynamic context. Through a series of laboratory experiments involving participants randomly assigned to teams, the study examines how team diversity influences individual behavior and performance. Results indicate that team diversity significantly affects individual behavior, with newcomers being particularly influenced by the diversity of the team they join. The findings underscore …

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New York Camp Econometrics Xviii Program, Center For Policy Research Apr 2024

New York Camp Econometrics Xviii Program, Center For Policy Research

Camp Econometrics-Programs

No abstract provided.

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Jargon To Jackpot: The Financial Impact Of Infusing Pop Culture References In Social Media, Madelynn Solow Apr 2024

Jargon To Jackpot: The Financial Impact Of Infusing Pop Culture References In Social Media, Madelynn Solow

Business and Economics Honors Papers

This research explores the impact of incorporating pop culture references in a company's Twitter feed on the company's stock price. Pop culture is integral to people's everyday lives, providing a sense of familiarity and fun between individuals. Many companies have started leveraging pop culture references on social media platforms like Twitter to establish a relatable and engaging connection with diverse consumer demographics. The primary purpose of this research is to investigate whether this strategy is beneficial within the stock market. It is hypothesized that incorporating pop culture references on Twitter can lead to increased sales and higher stock prices, as …

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Cooperation In Temporary Partnerships, Gabriele Camera, Alessandro Gioffré Apr 2024

Cooperation In Temporary Partnerships, Gabriele Camera, Alessandro Gioffré

ESI Working Papers

The literature on cooperation in infinitely repeated Prisoner’s Dilemmas covers the extreme opposites of the matching spectrum: partners, a player’s opponent never changes, and strangers, a player’s opponent randomly changes in every period. Here, we extend the analysis to settings where the opponent changes, but not in every period. In these temporary partnerships, players can deter some deviations by directly sanctioning their partner. Hence, relaxing the extreme assumption of one-period matchings can support some cooperation also off equilibrium because a class of strategies emerges that are less extreme than the typical “grim” strategy. We establish conditions supporting full …

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Global Coffee Production, Payton Herres Apr 2024

Global Coffee Production, Payton Herres

Student Papers in Local and Global Regional Economies

This study aims to provide a comprehensive understanding of the many factors that influence global coffee production, with a particular focus on weather conditions, land area, labor force, and human capital. By exploring these multifaceted aspects, this research aims to provide valuable insights for stakeholders in the coffee industry, policymakers, and researchers. This research explores patterns, calculations, and causal relationships that shape the dynamics of coffee production worldwide through a rigorous analysis of weather variables, including temperature and rainfall, along with assessments of land area, labor dynamics, and human capital. Furthermore, the research aims to illuminate the complex interplay between …

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Community And Regional Economic Analysis: Unveiling Economic Dynamics With The Location Quotient Method And Beyond, Daniela M. Mattos Apr 2024

Community And Regional Economic Analysis: Unveiling Economic Dynamics With The Location Quotient Method And Beyond, Daniela M. Mattos

Cornhusker Economics

In addition to the Location Quotient analysis, several other economic development analytical tools can contribute valuable insights to investment decisions, such as population-employment ratios and shift-share analysis. The use concomitant of these tools boosts the information provided by the Location Quotient analysis, offering a more holistic perspective. Recognizing that each analytical tool provides only a partial view, it is essential not to rely solely on one method when making investment decisions. Comprehensive decision-making necessitates leveraging multiple tools to gain a more nuanced and accurate understanding of local economies.

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Optimizing Nba Roster Construction, Nick R. Riccardi Apr 2024

Optimizing Nba Roster Construction, Nick R. Riccardi

Sport Management - All Scholarship

This study aims to quantify the effect that complementary player types have on team success in the National Basketball Association. Using cluster analysis, player-seasons are redefined from their traditional basketball positions to better encompass the roles that players play. For the 10 seasons of data, the best player for each of the 30 teams in the league is determined and teams are grouped based on the cluster of their best player. Ordinary Least Squares regressions are performed to test what player types fit together best. The results of this study show the importance of complementary workers to a firm’s success.

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Salary Distribution And Winning Percentage: A Panel Data Analysis Of The National Football League, Matthew Susich Apr 2024

Salary Distribution And Winning Percentage: A Panel Data Analysis Of The National Football League, Matthew Susich

Honors Projects in Mathematics and Economics

This paper analyzes the effect of player salary distribution, as well as other external and internal factors, on regular season win percentage of teams in the National Football League (NFL) over the past four seasons. The conclusions from this study were drawn from regression analysis of NFL salary data over the past four seasons (2019-2023). Player salaries were collected and condensed into twenty independent variables. These independent variables along with 8 control variables were regressed against regular season win percentage. The results indicate the greater total expenditure, a greater salary spread (range and variance), and greater salaries for the highest …

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Uniform Nonparametric Inference For Spatially Dependent Panel Data, Jia Li, Zhipeng Liao, Wenyu Zhou Apr 2024

Uniform Nonparametric Inference For Spatially Dependent Panel Data, Jia Li, Zhipeng Liao, Wenyu Zhou

Research Collection School Of Economics

This article proposes a uniform functional inference method for nonparametric regressions in a panel-data setting that features general unknown forms of spatio-temporal dependence. The method requires a long time span, but does not impose any restriction on the size of the cross section or the strength of spatial correlation. The uniform inference is justified via a new growing-dimensional Gaussian coupling theory for spatio-temporally dependent panels. We apply the method in two empirical settings. One concerns the nonparametric relationship between asset price volatility and trading volume as depicted by the mixture of distribution hypothesis. The other pertains to testing the rationality …

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Housing Markets Since Shapley And Scarf, Mustafa Oguz Afacan, Gaoji Hu, Jiangtao Li Apr 2024

Housing Markets Since Shapley And Scarf, Mustafa Oguz Afacan, Gaoji Hu, Jiangtao Li

Research Collection School Of Economics

Shapley and Scarf (1974) appeared in the first issue of the Journal of Mathematical Economics, and is one of the journal’s most impactful publications. As we approach the remarkable milestone of the journal’s 50th anniversary (1974–2024), this article serves as a commemorative exploration of Shapley and Scarf (1974) and the extensive body of literature that follows it.

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Wild Bootstrap Inference For Instrumental Variables Regressions With Weak And Few Clusters, Wenjie Wang, Yichong Zhang Apr 2024

Wild Bootstrap Inference For Instrumental Variables Regressions With Weak And Few Clusters, Wenjie Wang, Yichong Zhang

Research Collection School Of Economics

We study the wild bootstrap inference for instrumental variable regressions under an alternative asymptotic framework that the number of independent clusters is fixed, the size of each cluster diverges to infinity, and the within cluster dependence is sufficiently weak. We first show that the wild bootstrap Wald test controls size asymptotically up to a small error as long as the parameters of endogenous variables are strongly identified in at least one of the clusters. Second, we establish the conditions for the bootstrap tests to have power against local alternatives. We further develop a wild bootstrap Anderson–Rubin test for the full-vector …

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Hiv Estimation Using Population Based Surveys With Non-Response: A Partial Identification Approach, Oyelola A Adegboye, Tomoki Fujii, Denis H. Y. Leung, Siyu Li Apr 2024

Hiv Estimation Using Population Based Surveys With Non-Response: A Partial Identification Approach, Oyelola A Adegboye, Tomoki Fujii, Denis H. Y. Leung, Siyu Li

Research Collection School Of Economics

HIV estimation using data from the Demographic and Health Surveys (DHS) is lim-ited by the presence of non-response and test refusals. Conventional adjustments such as imputation require the data to be missing at random. Methods that use instrumental variables allow the possibility that prevalence is different between the respondents and non-respondents, but their performance depends critically on the validity of the instru-ment. Using Manski’s partial identification approach, we form instrumental variable bounds for HIV prevalence from a pool of candidate instruments. Our method does not require all candidate instruments to be valid. We use a simulation study to evaluate and …

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Truth By Consensus: A Theoretical And Empirical Investigation, Gabriele Camera, Rod Garratt, Cyril Monnet Mar 2024

Truth By Consensus: A Theoretical And Empirical Investigation, Gabriele Camera, Rod Garratt, Cyril Monnet

ESI Working Papers

Truthful reporting about publicly observed events cannot be guaranteed by a consensus process. This fact, which we establish theoretically and verify empirically, holds true even if some individuals are compelled to tell the truth, regardless of economic incentives. In an experiment, subjects routinely misreported a commonly known event when they could monetarily gain from it. Relying on majority consensus did not help uncover the truth, especially if complying with the majority granted small personal monetary gains. This highlights the difficulties in relying on shared consensus protocols to agree on specific events, and the importance of institutions with trusted, impartial observers.

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Estimating The Stability Of Okun's Law, Xinrui (Crystal) Wang, Samuel Schreyer Mar 2024

Estimating The Stability Of Okun's Law, Xinrui (Crystal) Wang, Samuel Schreyer

SACAD: Scholarly Activities

This study focuses on employing the gap version of Okun's Law, conducting regression analysis between the output gap and the unemployment gap to assess their effectiveness and long-term stability, and also estimates the significant relationship between the output gap and the unemployment gap. This study also compares the output gap dynamics during economic contractions and expansions.

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Does Dollarization Have An Impact On Economic Growth?, Jorge Robinson Mar 2024

Does Dollarization Have An Impact On Economic Growth?, Jorge Robinson

Research Day

Many developing and undeveloped countries, grappling with issues such as hyperinflation, corruption, high unemployment rates, poverty, and financial instability, often view dollarization as a potential solution. Dollarization involves adopting the US currency as the official or parallel currency, a strategy observed in countries like El Salvador, Ecuador, and Zimbabwe. The purpose of this research is to compare the impact of dollarization on real gross domestic product (RGDP) to that of countries that did not adopt dollarization. My results indicate that dollarization does indeed affect economic growth. These findings demonstrate that dollarized countries experience a higher percentage change in RGDP compared …

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Ambiguity, Cognitive Reflection, And Strategic Complexity Across Auctions, Cary Deck, Paan Jindapon, Tigran Melkonyan, Mark Schneider Mar 2024

Ambiguity, Cognitive Reflection, And Strategic Complexity Across Auctions, Cary Deck, Paan Jindapon, Tigran Melkonyan, Mark Schneider

ESI Working Papers

This paper bridges large but separate literatures on decision-making under ambiguity, the dual system framework of behavioral economics, and market design. We characterize behavior under ambiguity arising from dual system preferences. Rational System 2 satisfies the subjective expected utility axioms while behavioral System 1 satisfies the obvious dominance axiom from mechanism design. Our axioms provide a novel foundation for the popular NEO-EU ambiguity model and allow for source dependent ambiguity perceptions. Our approach also provides an explanation as to how behavioral differences arise between obviously strategy-proof mechanisms (e.g. English auctions) and other mechanisms. Empirically, we find ambiguity perceptions are lower …

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Panel Data Models With Time-Varying Latent Group Structures, Yiren Wang, Peter C. B. Phillips, Liangjun Su Mar 2024

Panel Data Models With Time-Varying Latent Group Structures, Yiren Wang, Peter C. B. Phillips, Liangjun Su

Research Collection School Of Economics

This paper considers a linear panel model with interactive fixed effects and unobserved individual and time heterogeneities that are captured by some latent group structures and an unknown structural break, respectively. To enhance realism, the model may have different numbers of groups and/or different group memberships before and after the break. With preliminary nuclear norm regularized estimation followed by row- and column-wise linear regressions, we estimate the break point based on the idea of binary segmentation and the latent group structures together with the number of groups before and after the break by sequential testing K-means algorithm simultaneously. It is …

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Optimal Inference For Spot Regressions, Tim Bollerslev, Jia Li, Yuexuan Ren Mar 2024

Optimal Inference For Spot Regressions, Tim Bollerslev, Jia Li, Yuexuan Ren

Research Collection School Of Economics

Betas from return regressions are commonly used to measure systematic financial market risks. "Good" beta measurements are essential for a range of empirical inquiries in finance and macroeconomics. We introduce a novel econometric framework for the nonparametric estimation of time-varying betas with high-frequency data. The "local Gaussian" property of the generic continuous-time benchmark model enables optimal "finite-sample" inference in a well-defined sense. It also affords more reliable inference in empirically realistic settings compared to conventional large-sample approaches. Two applications pertaining to the tracking performance of leveraged ETFs and an intraday event study illustrate the practical usefulness of the new procedures.

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Testing The Dimensionality Of Policy Shocks, Jia Li, Viktor Todorov, Qiushi Zhang Mar 2024

Testing The Dimensionality Of Policy Shocks, Jia Li, Viktor Todorov, Qiushi Zhang

Research Collection School Of Economics

This paper provides a nonparametric test for deciding the dimensionality of a policy shock as manifest in the abnormal change in asset returns' stochastic covariance matrix, following the release of a macroeconomic announcement. We use high-frequency data in local windows before and after the event to estimate the covariance jump matrix, and then test its rank. We find a one-factor structure in the covariance jump matrix of the yield curve resulting from the Federal Reserve's monetary policy shocks prior to the 2007-2009 financial crisis. The dimensionality of policy shocks increased afterwards due to the use of unconventional monetary policy tools.

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Robust Inference On Correlation Under General Heterogeneity, Liudas Giraitis, Yuefei Li, Peter C. B. Phillips Mar 2024

Robust Inference On Correlation Under General Heterogeneity, Liudas Giraitis, Yuefei Li, Peter C. B. Phillips

Research Collection School Of Economics

Considerable evidence in past research shows size distortion in standard tests for zero autocorrelation or zero cross-correlation when time series are not independent identically distributed random variables, pointing to the need for more robust procedures. Recent tests for serial correlation and cross-correlation in Dalla, Giraitis, and Phillips (2022) provide a more robust approach, allowing for heteroskedasticity and dependence in uncorrelated data under restrictions that require a smooth, slowly-evolving deterministic heteroskedasticity process. The present work removes those restrictions and validates the robust testing methodology for a wider class of innovations and regression residuals allowing for heteroscedastic uncorrelated and non-stationary data settings. …

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High Frequency Principal Component Analysis Based On Correlation Matrix That Is Robust To Jumps, Microstructure Noise And Asynchronous Observation Times, Dachuan Chen Mar 2024

High Frequency Principal Component Analysis Based On Correlation Matrix That Is Robust To Jumps, Microstructure Noise And Asynchronous Observation Times, Dachuan Chen

Research Collection School Of Economics

This paper developed the high frequency estimation for the principal component analysis (PCA) based on correlation matrix. This estimation methodology is robust to jumps, microstructure noise and asynchronous observation times simultaneously, which is enabled by the newly proposed Truncated and Smoothed Two-Scales Realized Volatility (Truncated S-TSRV) estimator. The general framework of our methodology is constructed based on the estimation of realized spectral functions with respect to the spot correlation matrix. A new asymptotic representation for the element-wise estimation error of the spot correlation matrix estimate has been derived, resulting in a new bias correction term which is much more complex …

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Bootstrap Inference For Quantile Treatment Effects In Randomized Experiments With Matched Pairs, Liang Jiang, Xiaobin Liu, Peter C B Phillips, Yichong Zhang Mar 2024

Bootstrap Inference For Quantile Treatment Effects In Randomized Experiments With Matched Pairs, Liang Jiang, Xiaobin Liu, Peter C B Phillips, Yichong Zhang

Research Collection School Of Economics

This paper examines methods of inference concerning quantile treatment effects (QTEs) in randomized experiments with matched-pairs designs (MPDs). Standard multiplier bootstrap inference fails to capture the negative dependence of observations within each pair and is therefore conservative. Analytical inference involves estimating multiple functional quantities that require several tuning parameters. Instead, this paper proposes two bootstrap methods that can consistently approximate the limit distribution of the original QTE estimator and lessen the burden of tuning parameter choice. Most especially, the inverse propensity score weighted multiplier bootstrap can be implemented without knowledge of pair identities.

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Reinvigorating Gva Nowcasting In The Post-Pandemic Period: A Case Study For India, Kaustubh Na, Soumya Suvra Bhadury, Saurabh Ghosh Feb 2024

Reinvigorating Gva Nowcasting In The Post-Pandemic Period: A Case Study For India, Kaustubh Na, Soumya Suvra Bhadury, Saurabh Ghosh

Bulletin of Monetary Economics and Banking

We reinvigorate nowcasting models considering structural changes caused by the COVID-19 pandemic. It emphasizes the need to understand the heterogeneous impact of shocks on agriculture, industry, and services sectors in an emerging market economy (e.g., India). Our findings advocate a bottom-up approach that tracks sectors separately rather than a headline number. Our results suggest including digital-activity index and supply-side disruption index in the post-pandemic period could improve nowcast performance. Expectation-Maximization (E-M) algorithm is used to combine data series based on their availability. Among bridging methods, the averaging method is preferred due to its simplicity and flexibility.

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Cognitive Abilities And Individual Earnings In Hybrid Continuous Double Auctions, Yan Peng, Jason Shachat, Lijia Wei, S. Sarah Zhang Feb 2024

Cognitive Abilities And Individual Earnings In Hybrid Continuous Double Auctions, Yan Peng, Jason Shachat, Lijia Wei, S. Sarah Zhang

ESI Working Papers

There is growing evidence that human cognitive abilities strongly influence individual trader financial performance. Much of this evidence has been established in experimental asset markets whose participants are exclusively human traders. However, algorithmic trading has reshaped financial markets, raising the issue of whether these assessments on the impact of cognititive abilities still hold in these settings, particularly in markets with low latency algorithmic traders. Extending previous findings in experimental asset markets, we examine how individual cognitive abilities—reaction time, trader intuition (Theory of Mind), and cognitive reflection—affect human earnings in induced demand and supply markets with and without algorithmic traders of …

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Possible Role Of The One-Half Heuristic In Overconfidence Research, Vojtěch Zíka Feb 2024

Possible Role Of The One-Half Heuristic In Overconfidence Research, Vojtěch Zíka

ESI Working Papers

Overconfidence research often involves estimating performance within a fixed range. Recent studies suggest that overprecision is affected by central tendency bias, the tendency to estimate near the center of a perceived distribution. This paper examines whether a similar pattern influences the other two overconfidence types, overestimation and overplacement. In a laboratory experiment (N = 120), participants estimated their own and the average performance over five rounds of ten Rock–Paper–Scissors games. Each round earned for up to 40 points, but average performance varied across three treatments, with means of 16.6, 20, and 23.3 points. The main question was whether this manipulation …

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Horizontal Economic Inequality And Mass Atrocity Risk: A Large-Sample Empirical Inquiry, Charles H. Anderton, Roxane A. Anderton Feb 2024

Horizontal Economic Inequality And Mass Atrocity Risk: A Large-Sample Empirical Inquiry, Charles H. Anderton, Roxane A. Anderton

Genocide Studies and Prevention: An International Journal

Our research question is: Does inter-group horizontal economic inequality elevate state-perpetrated mass atrocity risk? Theoretical perspectives in genocide studies show how economic and other forms of discrimination against ethnic or religious groups can elevate the risk of government violence against them. Among the approximately five dozen large-sample empirical studies of mass atrocity risk, only a few consider the effects of economic discrimination. Moreover, no large-sample empirical studies, to the best of our knowledge, test hypotheses related to how inter-group horizontal economic inequalities (as distinct from vertical economic inequalities based on GINI coefficients or quantile income or wealth measures) affect mass …

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How Does Passive Investing Effect The Informational Efficiency Of Prices?, Brice Corgnet, Mark Desantis, Yan Peng, David Porter, Jason Shachat Feb 2024

How Does Passive Investing Effect The Informational Efficiency Of Prices?, Brice Corgnet, Mark Desantis, Yan Peng, David Porter, Jason Shachat

ESI Working Papers

We investigate the causal effects of passive investing on informational efficiency and market quality metrics by developing a novel laboratory experiment that introduces Index trackers with exogenous passive investment flows. We find that, while improving liquidity, Index tracking hurts informational efficiency, confirming our main hypothesis. Furthermore, we observe violations of the law of one price, leading to widespread and persistent arbitrage opportunities. Additionally, our research uncovers that Active traders, particularly those with private information about asset values and high cognitive ability, reap benefits from the introduction of Index tracking.

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Assessing The Recreational Charter Fishing Market In Florida: A Hedonic Price Analysis, Mehrnoosh Asadi, Pallab Mozumder, Mahadev G. Bhat Feb 2024

Assessing The Recreational Charter Fishing Market In Florida: A Hedonic Price Analysis, Mehrnoosh Asadi, Pallab Mozumder, Mahadev G. Bhat

Economics Faculty Publications

In this study we analyze the effect of a wide range of factors on the variation of recreational fishing trip prices in Florida. We collected extensive data from recreational fishing websites maintained by guides and outfitters and used different empirical methods for quantifying the relationship between trip price and various trip characteristics. The Hedonic Price model was used to estimate the implicit prices of freshwater and saltwater fishing trip characteristics. The results suggest that freshwater and saltwater anglers significantly value the lodging feature included in the fishing trip package. Moreover, saltwater anglers had a higher willingness to pay to catch …

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Essays In Macroeconomics And Finance, Archil Dvalishvili Feb 2024

Essays In Macroeconomics And Finance, Archil Dvalishvili

Dissertations, Theses, and Capstone Projects

Chapter 1: (A Quantitative Analysis of Interest on Reserves and Reserve Requirements) - I construct a medium scale DSGE model with financial frictions both on the demand (entrepreneurs) and supply (banks) sides of credit to study the costs and benefits of fixed/time-varying minimum reserve requirements and interest paid by the Fed on reserves.The results can be summarized as follows: (1) An optimal time-varying minimum reserve requirement generates substantial welfare gain when compared with a fixed minimum reserve requirement when no interest is paid on reserves. (2) Paying interest on reserves is substantially welfare inferior to a policy with no interest …

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