Article
Economics
Helmut Luetkepohl, Mika Meitz, Aleksei Netsunajev, Pentti Saikkonen
Summary: Tests for identification through heteroskedasticity in structural vector autoregressive analysis are developed for models with two volatility states where the time point of volatility change is known. The tests are Wald-type tests for which only the unrestricted model, including the covariance matrices of the two volatility states, has to be estimated. The asymptotic null distributions of the test statistics are derived, and simulations are used to explore their small-sample properties.
ECONOMETRICS JOURNAL
(2021)
Article
Mathematics, Applied
Dariusz Chruscinski
Summary: This study introduces a class of quantum evolution beyond Markovian semigroup, where dissipation and decoherence are controlled by a memory kernel and a generator, respectively, both processes commuting with the unitary evolution. The role of the decoherence generator is to ensure complete positivity in the evolution.
Article
Mathematics
Rong Meng, La-Su Mai, Ming Mei
Summary: This paper studies the local well-posedness for the free boundary value problem of smooth solutions to the cylindrical symmetric Euler equations with damping and related models. By setting a suitable weighted Sobolev space and using Hardy's inequality, the singularity and vacuum problems are successfully overcome, and well-posedness of local smooth solutions is obtained.
JOURNAL OF DIFFERENTIAL EQUATIONS
(2022)
Article
Multidisciplinary Sciences
Andres Garcia-Medina, Norberto A. Hernandez-Leandro, Graciela Gonzalez Farias, Nelson Muriel
Summary: The problem of multistage allocation is solved using the Target Date Fund (TDF) strategy under the latest regulatory framework of the Mexican pension system. The study analyzes the investment trajectory for a representative set of 14 assets over a long horizon, estimates expected returns using various models, and evaluates forecasts through asymmetric dependencies. The methodology is computationally efficient and shows the desired properties of a TDF strategy in realistic settings, with the GARCH(1,1) under a fixed historical covariance matrix exhibiting the highest Sharpe ratio.
Article
Statistics & Probability
Rong Ma, T. Tony Cai, Hongzhe Li
Summary: This article examines the global testing and large-scale multiple testing for regression coefficients in high-dimensional logistic regression, proposing theoretical methods that are shown to be effective through simulation studies and analysis of real datasets.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2021)
Article
Economics
Christian Francq, Jean-Michel Zakoian
Summary: This paper investigates the testing of moment existence in GARCH processes and proposes a method based on the joint asymptotic distribution of the Quasi-Maximum Likelihood estimator and empirical moments. A bootstrap procedure is introduced to enhance the finite-sample performance of the test, and optimal issues of non-Gaussian QML estimators are discussed.
JOURNAL OF ECONOMETRICS
(2022)
Article
Biochemical Research Methods
Simone Sturniolo, William Waites, Tim Colbourn, David Manheim, Jasmina Panovska-Griffiths
Summary: The study introduces the SEIR-TTI model as an extension of the classic SEIR model to enhance decision making by including contact tracing. This new model is shown to accurately approximate the behavior of agent-based models at a lower computational cost, making it a valuable tool for exploring testing and tracing levels in disease outbreak management.
PLOS COMPUTATIONAL BIOLOGY
(2021)
Article
Economics
Marius C. O. Amba, Taoufiki Mbratana, Julie Le Gallo
Summary: This paper proposes limited and full information estimators for a simultaneous panel data model with spatial lags on the dependent variables and spatially autocorrelated error processes. The estimators use various generalized moment procedures to estimate the spatial error components. Monte Carlo experiments demonstrate that the proposed estimators outperform traditional estimators and provide insights into the impact of misspecifying the error process. The different estimators are illustrated using an empirical example of competition between French municipalities in the capital region of Ile-de-France.
EMPIRICAL ECONOMICS
(2023)
Article
Economics
Matei Demetrescu, Iliyan Georgiev, Paulo M. M. Rodrigues, A. M. Robert Taylor
Summary: Standard tests have found limited evidence of predictability in stock returns based on full sample data. However, recent approaches analyzing subsamples suggest that predictability may exist only within specific periods. The use of subsample dates has been criticized for leading to spurious findings of predictability. To address this issue, this study proposes new tests based on sequences of predictability statistics calculated over subsamples. The proposed tests are shown to be valid and are applied to US stock returns, demonstrating their usefulness.
JOURNAL OF ECONOMETRICS
(2022)
Article
Mathematics, Applied
Dinh Nho Hao, Nguyen Trung Thanh, Nguyen Van Duc, Nguyen Van Thang
Summary: This paper considers the coefficient identification problem for a system of one-dimensional advection-reaction equations using boundary data. The stability of the problem is proved using global Carleman estimates. The CIP is solved using the least-squares approach accompanied with the adjoint equation technique, and Lipschitz-type error estimates of the reconstructed coefficients are proved. Numerical tests are conducted to evaluate the performance of the proposed algorithm.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2023)
Article
Mathematics
Belen Perez-Sanchez, Martin Gonzalez, Carmen Perea, Jose J. Lopez-Espin
Summary: Simultaneous Equations Models (SEM) is a statistical technique widely used in various fields such as economics, psychology, and medicine to model the simultaneity relationship between variables. This paper compares different methods for estimating SEM through experimental and computational studies, and proposes a new estimation method that offers better approximations and efficiency compared to existing methods.
Article
Statistics & Probability
Yuchen Xu, Marie-Christine Duker, David S. S. Matteson
Summary: This paper proposes novel methods for testing simultaneous diagonalization of possibly asymmetric matrices, including a two-sample test and a generalization for multiple matrices. A partial version of the test is also studied to check for the sharing of partial eigenvectors across samples. Additionally, a new algorithm for the testing methods is introduced. Simulation studies show favorable performance for all designs. Finally, the theoretical results are applied to decouple vector autoregression models into multiple univariate time series and to test for the same stationary distribution in recurrent Markov chains. These applications are demonstrated using macroeconomic indices of 8 countries and streamflow data, respectively.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2023)
Article
Economics
Andrzej Kociecki, Marcin Kolasa
Summary: We propose an analytical framework to study global identification in structural models with forward-looking expectations. Our approach combines similarity transformation and constraints imposed by model parameters to solve the identification problem. By utilizing the concept of a Grobner basis and analytical algorithms, we can determine whether a model is identified or not at a specific parameter point and provide the complete set of observationally equivalent parameter vectors. We apply our framework to solve the global identification problem in various DSGE models.
JOURNAL OF ECONOMETRICS
(2023)
Article
Computer Science, Artificial Intelligence
Jemy A. Mandujano Valle, Alexandre L. Madureira
Summary: The Hodgkin-Huxley model is a landmark in neuroscience, describing the initiation and propagation of action potentials in neurons through a system of nonlinear differential equations. This study introduces a minimal error iteration method to estimate some of the model's parameters using measured membrane potential data, even in the presence of noise.
NEURAL COMPUTATION
(2022)
Article
Computer Science, Interdisciplinary Applications
Ran Liu, Lixing Zhu
Summary: Checking the models of the ongoing COVID-19 pandemic is important. The study proposes a new test to examine partially observed ODE models and presents the asymptotic properties of the test. Simulation studies show that the SEIR model may not be appropriate for certain periods in Japan and Algeria.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2023)
Article
Economics
George Milunovich, Minxian Yang
JOURNAL OF BUSINESS & ECONOMIC STATISTICS
(2018)
Article
Business, Finance
George Milunovich, Shuping Shi, David Tan
QUANTITATIVE FINANCE
(2019)
Article
Economics
George Milunovich
Summary: Major cryptocurrencies such as bitcoin and etherium rely on PoW consensus mechanism, while some digital coins implementing more energy efficient algorithms like PoS are gaining popularity. Research shows that PoW cryptocurrencies are more strongly connected within the network and export more uncertainty to other digital assets.
Article
Economics
George Milunovich, Seung Ah Lee
Summary: This study uses machine learning algorithms to predict the survival and closure of cryptocurrency exchanges, finding that exchange lifetime, transacted volume, and cyber-security measures are important factors for accurate predictions.
JOURNAL OF FORECASTING
(2022)
Article
Environmental Studies
Laurence Carleton, Roselyne Joyeux, George Milunovich
Summary: This study examines the relationship between rail accessibility and the demographic characteristics in well-established rail transit-served communities. The results show that property premiums associated with rail transit access are significant in metropolitan Sydney, but there is little evidence of sorting based on economic advantage or disadvantage. Furthermore, the commonly identified demographic groups linked with gentrification, such as high-income and professional individuals, do not dominate areas with high rail accessibility. Only individuals with higher educational qualifications are found to concentrate in areas with closer access to rail transit.
Article
Economics
George Milunovich, Seung Ah Lee
Summary: This study investigates the impact of cyberattacks on digital exchanges on Bitcoin returns from 2012 to 2021. The results show that there is a negative and statistically significant impact on Bitcoin price on the days of cyberattacks. However, the effect has diminished and become statistically insignificant in the more recent subsample from 2019 to 2021.
Article
Economics
George Milunovich
Article
Economics
Helmut Luetkepohl, George Milunovich
JOURNAL OF ECONOMIC DYNAMICS & CONTROL
(2016)
Article
Business, Finance
Mardi Dungey, George Milunovich, Susan Thorp, Minxian Yang
JOURNAL OF BANKING & FINANCE
(2015)
Article
Economics
Roselyne Joyeux, George Milunovich
Proceedings Paper
Economics
Roselyne Joyeux, George Milunovich
INTERNATIONAL WORK-CONFERENCE ON TIME SERIES (ITISE 2014)
(2014)
Article
Economics
George Milunovich, Jelena Minovic
Article
Economics
George Milunovich
JOURNAL OF FORECASTING
(2020)
Article
Economics
George Milunovich
AUSTRALIAN ECONOMIC REVIEW
(2018)
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
Ji Hyung Lee, Yuya Sasaki, Alexis Akira Toda, Yulong Wang
Summary: Administrative data, often presented as tabulated summaries for confidentiality reasons, can be more easily accessed in this form. In this study, the authors propose a novel nonparametric density estimation method based on maximum entropy and demonstrate its consistent results. The method does not require tuning parameters and provides a closed-form density for further analysis. The authors apply this method to estimate the income distribution using tabulated summary data from U.S. tax returns.
JOURNAL OF ECONOMETRICS
(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
Hongfei Wang, Binghui Liu, Long Feng, Yanyuan Ma
Summary: This study addresses the problem of testing mutual independence of high-dimensional random vectors and proposes a series of high-dimensional rank-based max-sum tests. Through extensive simulations and real data analysis, the superiority of these tests is demonstrated.
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
Karim Chalak
Summary: This paper generalizes the Gini-Frisch bounds to accommodate nonparametric heterogeneous effects and provides suitable conditions for their application in nonparametric nonseparable equations.
JOURNAL OF ECONOMETRICS
(2024)
Article
Economics
Koki Fusejima
Summary: In this paper, sufficient conditions for identifying treatment effects on continuous outcomes are established in endogenous and multi-valued discrete treatment settings with unobserved heterogeneity. The monotonicity assumption for multi-valued discrete treatments and instruments is employed, and the identification condition has a clear economic interpretation. Additionally, the local treatment effects in multi-valued treatment settings are identified, and closed-form expressions of the identified treatment effects are derived.
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
Weilun Zhou, Jiti Gao, David Harris, Hsein Kew
Summary: This paper discusses the estimation of a semi-parametric single-index regression model that allows for nonlinear predictive relationships. The presence of cointegrated predictors balances the nonstationarity properties of the predictors with the stationarity properties of asset returns and avoids the curse of dimensionality. In an empirical application, it is found that using cointegrated predictors produces better out-of-sample forecasts.
JOURNAL OF ECONOMETRICS
(2024)
Article
Economics
Eric Beutner, Alexander Heinemann, Stephan Smeekes
Summary: This paper proposes a fixed-design residual bootstrap method for the two-step estimator associated with the conditional Value-at-Risk. The consistency of the bootstrap is proven for a general class of volatility models, and intervals are constructed for the conditional Value-at-Risk. Simulation results show that the reversed-tails bootstrap interval provides accurate coverage compared to the equal-tailed percentile bootstrap interval.
JOURNAL OF ECONOMETRICS
(2024)
Article
Economics
Federico M. Bandi, Davide Pirino, Roberto Reno
Summary: The article examines the staleness of asset prices, including systematic (market-wide) staleness and idiosyncratic (asset specific) staleness. The authors provide a limit theory based on joint asymptotics, utilizing increasingly-frequent observations and an increasing number of assets. They introduce novel structural estimates of systematic and idiosyncratic measures of liquidity obtained solely from transaction prices, and assess the economic signal contained in these estimates using suitable metrics.
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
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
Economics
Jean-Jacques Forneron
Summary: This paper develops an approach to detect identification failure in moment condition models by introducing a quasi-Jacobian matrix. The quasi-Jacobian matrix is singular when local and/or global identification fails, and equivalent to the usual Jacobian matrix when the model is globally and locally identified. A simple test is introduced to conduct subvector inferences allowing for various levels of identification without prior knowledge about the underlying identification structure.
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)
