New York Camp Econometrics Xviii Program,
2024
Syracuse University
New York Camp Econometrics Xviii Program, Center For Policy Research
Camp Econometrics-Programs
No abstract provided.
Jargon To Jackpot: The Financial Impact Of Infusing Pop Culture References In Social Media,
2024
Ursinus College
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 …
Cooperation In Temporary Partnerships,
2024
Chapman University
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 …
Global Coffee Production,
2024
Wright State University
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 …
Community And Regional Economic Analysis: Unveiling Economic Dynamics With The Location Quotient Method And Beyond,
2024
University of Nebraska-Lincoln
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.
Optimizing Nba Roster Construction,
2024
Syracuse University
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.
Salary Distribution And Winning Percentage: A Panel Data Analysis Of The National Football League,
2024
Bryant University
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 …
Uniform Nonparametric Inference For Spatially Dependent Panel Data,
2024
Singapore Management University
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 …
Housing Markets Since Shapley And Scarf,
2024
Singapore Management University
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.
Wild Bootstrap Inference For Instrumental Variables Regressions With Weak And Few Clusters,
2024
Singapore Management University
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 …
Hiv Estimation Using Population Based Surveys With Non-Response: A Partial Identification Approach,
2024
Singapore Management University
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 …
Truth By Consensus: A Theoretical And Empirical Investigation,
2024
Chapman University
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.
Estimating The Stability Of Okun's Law,
2024
Fort Hays State University
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.
Does Dollarization Have An Impact On Economic Growth?,
2024
Georgia College
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 …
Ambiguity, Cognitive Reflection, And Strategic Complexity Across Auctions,
2024
Chapman University
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 …
Panel Data Models With Time-Varying Latent Group Structures,
2024
Singapore Management University
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 …
Optimal Inference For Spot Regressions,
2024
Duke University
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.
Testing The Dimensionality Of Policy Shocks,
2024
Singapore Management University
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.
Robust Inference On Correlation Under General Heterogeneity,
2024
Singapore Management University
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. …
High Frequency Principal Component Analysis Based On Correlation Matrix That Is Robust To Jumps, Microstructure Noise And Asynchronous Observation Times,
2024
Singapore Management University
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 …
