Article
Economics
Zhongjian Lin, Yingyao Hu
Summary: This paper proposes a binary choice model with misclassification and social interactions to address the misclassification problems in social interactions studies. The identification of the conditional choice probability of the latent dependent variable is achieved using repeated measurements and a monotonicity condition. The complete likelihood function is constructed from the two repeated measurements, and a nested pseudo likelihood algorithm is proposed for estimation. Consistency and asymptotic normality results are shown for the proposed estimation method.
JOURNAL OF ECONOMETRICS
(2024)
Article
Economics
Zhao Chen, Vivian Xinyi Cheng, Xu Liu
Summary: This paper focuses on the testing problems of high-dimensional quantile regression and proposes a new test statistic based on the quantile regression score function. The paper investigates the limiting distributions of the proposed test statistic and shows through Monte Carlo simulations and empirical analysis that the proposed method outperforms existing methods in terms of controlling error rate and power.
JOURNAL OF ECONOMETRICS
(2024)
Article
Economics
Julian Martinez-Iriarte, Gabriel Montes-Rojas, Yixiao Sun
Summary: This paper analyzes the unconditional effects of a general policy intervention, including location-scale shifts and simultaneous shifts. The study finds that failing to account for these shifts may lead to incorrect assessment of the potential policy effects on the outcome variable of interest.
JOURNAL OF ECONOMETRICS
(2024)
Article
Economics
Vassilis Hajivassiliou, Frederique Savignac
Summary: The paper develops new methods for establishing coherency and completeness conditions in Static and Dynamic Limited Dependent Variables (LDV) Models. It characterizes the two distinct problems as empty-region incoherency and overlap-region incoherency or incompleteness and shows that the two properties can co-exist. The paper focuses on the class of models that can be Simultaneously Incomplete and Incoherent (SII) and proposes estimation strategies based on Conditional Maximum Likelihood Estimation (CMLE) for simultaneous dynamic LDV models.
JOURNAL OF ECONOMETRICS
(2024)
Article
Economics
Dennis Lim, Wenjie Wang, Yichong Zhang
Summary: We propose a linear combination of jackknife tests for IV regressions with weak instruments and heteroskedasticity, and select the weights based on a decision-theoretic rule. Our test performs well in empirical applications and exhibits good power properties.
JOURNAL OF ECONOMETRICS
(2024)
Article
Economics
Sung Jae Jun, Joris Pinkse
Summary: This paper discusses how to determine the optimal reserve price in auctions using maximum entropy estimation and proposes a maxmin decision rule that includes both the maximum entropy solution and other methods.
JOURNAL OF ECONOMETRICS
(2024)
Article
Economics
Hassan Nosratabadi
Summary: This study introduces a shortlisting model to explain choice anomalies in multi-attribute choice space, by analyzing the decision-making process of individuals and their use of sequential filtering.
MATHEMATICAL SOCIAL SCIENCES
(2024)
Article
Economics
Di Wang, Yao Zheng, Guodong Li
Summary: This paper proposes a new modeling framework for modeling and forecasting high-dimensional tensor-valued time series using the autoregression method. By considering a low-rank Tucker decomposition, this method can flexibly capture the underlying low-dimensional tensor dynamics, achieving dimension reduction and multidimensional dynamic factor interpretations. The paper also studies different estimation methods and their non-asymptotic properties under different low-rank settings.
JOURNAL OF ECONOMETRICS
(2024)
Article
Economics
Li Hou, Baisuo Jin, Yuehua Wu
Summary: The spatiotemporal modeling of networks is highly significant in epidemiology and social network analysis. This research proposes a method for estimating the parameters of spatial dynamic panel models effectively and efficiently. The study also introduces a complex orthogonal greedy algorithm for variable selection and incorporates fixed effects into the model. Extensive simulation studies and data examples demonstrate the effectiveness of the proposed method.
JOURNAL OF ECONOMETRICS
(2024)
Article
Economics
Anna Rita Bacinello, Rosario Maggistro, Ivan Zoccolan
Summary: In this paper, a model is proposed for pricing GLWB variable annuities under a stochastic mortality framework. The contract value is defined through an optimization problem solved by using dynamic programming. The authors prove the validity of the bang-bang condition for the withdrawal strategies of the model using backward induction. Extensive numerical examples are presented, comparing the results for different parameters and policyholder behaviours.
INSURANCE MATHEMATICS & ECONOMICS
(2024)
Article
Economics
Thomas Macurdy, David Glick, Sonam Sherpa, Sriniketh Nagavarapu
Summary: In a successful transition from youth to adulthood, individuals go through a series of roles in school, work, and family formation, culminating in becoming self-sufficient adults. However, some disconnected youth spend significant time outside of any role that leads to adult independence. Understanding the meaning of disconnection, the number of disconnected youth, their characteristics, and how the problem has evolved is essential in assisting these youth. Using comprehensive data, a study examined disconnection spells and found that in the early 2000s, approximately 19% of young men and 25% of young women experienced disconnection before the age of 23. These rates were even higher for certain sub-groups, reaching over 30% for some. The study also revealed that the majority of disconnected youth remained disconnected for more than a year, but once reconnected, they typically stayed connected for at least three years. The findings highlight the need for targeted interventions to prevent lengthy disconnection spells.
JOURNAL OF ECONOMETRICS
(2024)
Article
Social Sciences, Mathematical Methods
Max Rubinstein, Amelia Haviland, Joshua Breslau
Summary: Using the COVID-19 Trends and Impact Survey, researchers found that COVID-19 vaccinations led to reductions in feelings of depression, anxiety, isolation, and worries about health among vaccine-accepting respondents. Social isolation was found to have a stronger impact on depression than worries about health. However, the causal interpretations of these findings rely on strong assumptions.
STATISTICS AND PUBLIC POLICY
(2023)
Letter
Social Sciences, Mathematical Methods
Max D. Morris
STATISTICS AND PUBLIC POLICY
(2023)
Article
Social Sciences, Mathematical Methods
Chris R. Surfus
Summary: For the first time, the US Census Bureau collected data on the LGBT community through Phase 3.2 of the Household Pulse Survey, which assesses the impact of COVID-19 on US residents. This study combines six weeks of data and provides the first nationally representative sample of transgender residents in the US. It specifically focuses on LGBT people with disabilities and highlights disparities faced by transgender disabled adults in terms of economic considerations and mental health.
STATISTICS AND PUBLIC POLICY
(2023)
Article
Business, Finance
Tao Chen, Mike Ludkovski, Moritz Voss
Summary: This article investigates optimal order execution problems in discrete time with instantaneous price impact and stochastic resilience. It derives a closed-form recursion for the optimal strategy in the setting of linear transient price impact and develops a numerical algorithm based on dynamic programming and deep learning for the case of nonlinear transient price impact. The study shows that neural network functional approximators can accurately approximate optimal strategies.
QUANTITATIVE FINANCE
(2023)
Article
Mathematics, Interdisciplinary Applications
Ying Liu, Steven Andrew Culpepper
Summary: This study proposes new identifiability conditions for the parameters of Restricted Latent Class Models (RLCMs) for multiclass data and discusses their implications for substantive applications. A Bayesian framework is proposed to infer model parameters, and parameter recovery is assessed through a Monte Carlo simulation study. The model is also applied to a real dataset.
Article
Economics
Tony Chernis
Summary: This paper examines the choice of synthesis function in Bayesian Predictive Synthesis when combining a large number of predictions, which is a common occurrence in macroeconomics. To address the difficulty of estimating combination weights with many predictions, shrinkage priors and factor modelling techniques are considered. The results show that the sparse weights of shrinkage priors perform well across exercises.
STUDIES IN NONLINEAR DYNAMICS AND ECONOMETRICS
(2023)
Article
Public, Environmental & Occupational Health
Teun Schrieks, W. J. Wouter Botzen, Toon Haer, Oliver V. Wasonga, Jeroen C. J. H. Aerts
Summary: This study investigates adaptation behavior in rural communities of the Horn of Africa Drylands by assessing economic and social psychological theories on decision making under risk. The results show that economic theories have the best fit for adaptation decisions, with risk and time preferences playing an important role. Elements of social psychological theories also have significant effects on adaptation decisions, such as perceived self-efficacy and adaptation by family and friends. Additionally, factors like gender, education level, access to financial resources, and access to government support or aid influence the type of adaptation measures implemented.
Article
Mathematics, Interdisciplinary Applications
Clio Andris, Caglar Koylu, Mason A. Porter
Summary: This study examines the effectiveness of different geographic regions in limiting the spread of COVID-19. It finds that regions constructed from GPS-trace networks and commute networks have the lowest case rates, indicating that they may reflect natural partitions in COVID-19 transmission. On the other hand, regions constructed from geolocated Facebook friendships and Twitter connections are less effective. This has implications for policy decisions and public messaging in emergency situations.
Article
Business, Finance
Xin Guo, Othmane Mounjid
Summary: This paper analyzes the difficulties in training generative adversarial networks (GANs) for financial time series and proposes a stochastic control framework for hyper-parameters tuning. It establishes the dynamic programming principle and solves the minimax game by deriving explicit forms for the optimal adaptive learning rate and batch size. Empirical studies demonstrate the superiority of this approach over the standard ADAM method in terms of convergence and robustness.
MATHEMATICAL FINANCE
(2023)
