Estimating DSGE Models: Recent Advances and Future Challenges

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Jesús Fernández-Villaverde ◽  
Pablo A. Guerrón-Quintana
Keyword(s):  
Likelihood Function ◽  
Space Representation ◽  
Annual Review ◽  
Publication Date ◽  
Dsge Models ◽  
State Space Representation ◽  
Current State ◽  
Recent Advances ◽  
Future Challenges ◽  
Dynamic Stochastic

We review the current state of the estimation of dynamic stochastic general equilibrium (DSGE) models. After introducing a general framework for dealing with DSGE models, the state-space representation, we discuss how to evaluate moments or the likelihood function implied by such a structure. We discuss, in varying degrees of detail, recent advances in the field, such as the tempered particle filter, approximated Bayesian computation, Hamiltonian Monte Carlo, variational inference, and machine learning. These methods show much promise but have not been fully explored by the DSGE community yet. We conclude by outlining three future challenges for this line of research. Expected final online publication date for the Annual Review of Economics, Volume 13 is August 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Bayesian Estimation of DSGE Models

2015 ◽  
Author(s):  
Edward P. Herbst ◽  
Frank Schorfheide
Keyword(s):  
Monte Carlo ◽  
Sequential Monte Carlo ◽  
Likelihood Function ◽  
Academic Research ◽  
Dynamic Stochastic General Equilibrium ◽  
Computational Techniques ◽  
Dsge Models ◽  
Monte Carlo Techniques ◽  
Dynamic Stochastic ◽  
Theoretical Foundations

Dynamic stochastic general equilibrium (DSGE) models have become one of the workhorses of modern macroeconomics and are extensively used for academic research as well as forecasting and policy analysis at central banks. This book introduces readers to state-of-the-art computational techniques used in the Bayesian analysis of DSGE models. The book covers Markov chain Monte Carlo techniques for linearized DSGE models, novel sequential Monte Carlo methods that can be used for parameter inference, and the estimation of nonlinear DSGE models based on particle filter approximations of the likelihood function. The theoretical foundations of the algorithms are discussed in depth, and detailed empirical applications and numerical illustrations are provided. The book also gives invaluable advice on how to tailor these algorithms to specific applications and assess the accuracy and reliability of the computations. The book is essential reading for graduate students, academic researchers, and practitioners at policy institutions.

scholarly journals Extrachromosomal DNA: An Emerging Hallmark in Human Cancer

2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Sihan Wu ◽  
Vineet Bafna ◽  
Howard Y. Chang ◽  
Paul S. Mischel
Keyword(s):  
Human Cancer ◽  
Regulatory Elements ◽  
Annual Review ◽  
Publication Date ◽  
Cancer Evolution ◽  
Form And Function ◽  
Current State ◽  
Human Genes ◽  
Cancer Tumor ◽  
And Function

Human genes are arranged on 23 pairs of chromosomes, but in cancer, tumor-promoting genes and regulatory elements can free themselves from chromosomes and relocate to circular, extrachromosomal pieces of DNA (ecDNA). ecDNA, because of its nonchromosomal inheritance, drives high-copy-number oncogene amplification and enables tumors to evolve their genomes rapidly. Furthermore, the circular ecDNA architecture fundamentally alters gene regulation and transcription, and the higher-order organization of ecDNA contributes to tumor pathogenesis. Consequently, patients whose cancers harbor ecDNA have significantly shorter survival. Although ecDNA was first observed more than 50 years ago, its critical importance has only recently come to light. In this review, we discuss the current state of understanding of how ecDNAs form and function as well as how they contribute to drug resistance and accelerated cancer evolution. Expected final online publication date for the Annual Review of Pathology: Mechanisms of Disease, Volume 17 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

From Linear to Nonlinear DSGE Models

2015 ◽  
Author(s):  
Edward P. Herbst ◽  
Frank Schorfheide
Keyword(s):  
Projection Methods ◽  
Order Perturbation ◽  
New Keynesian ◽  
Space Representation ◽  
Small Scale ◽  
Computational Techniques ◽  
Dsge Models ◽  
Linearization Technique ◽  
State Space Representation ◽  
Nonlinear Form

This chapter presents computational techniques that can be used to estimate DSGE models that have been solved with nonlinear techniques, such as higher-order perturbation methods or projection methods. From the perspective of Bayesian estimation, the key difference between DSGE models that have been solved with a linearization technique and models that have been solved nonlinearly is that in the former case, the resulting state–space representation is linear, whereas in the latter case, it takes the general nonlinear form. The chapter also highlights some of the features that researchers have introduced into DSGE models to capture important nonlinearities in the data, wherein it uses the small-scale New Keynesian DSGE model as illustrative example.

Sepsis-Induced Immunosuppression

2021 ◽  
Vol 84 (1) ◽  
Author(s):  
Lisa K. Torres ◽  
Peter Pickkers ◽  
Tom van der Poll
Keyword(s):  
Organ Transplant ◽  
Annual Review ◽  
Publication Date ◽  
Predisposing Factor ◽  
Substantial Impact ◽  
Immunomodulatory Agents ◽  
Secondary Infections ◽  
Future Challenges ◽  
Treatment Paradigm ◽  
New Treatment

Sepsis is expected to have a substantial impact on public health and cost as its prevalence increases. Factors contributing to increased prevalence include a progressively aging population, advances in the use of immunomodulatory agents to treat a rising number of diseases, and immune-suppressing therapies in organ transplant recipients and cancer patients. It is now recognized that sepsis is associated with profound and sustained immunosuppression, which has been implicated as a predisposing factor in the increased susceptibility of patients to secondary infections and mortality. In this review, we discuss mechanisms of sepsis-induced immunosuppression and biomarkers that identify a state of impaired immunity. We also highlight immune-enhancing strategies that have been evaluated in patients with sepsis, as well as therapeutics under current investigation. Finally, we describe future challenges and the need for a new treatment paradigm, integrating predictive enrichment with patient factors that may guide the future selection of tailored immunotherapy. Expected final online publication date for the Annual Review of Physiology, Volume 84 is February 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

The Psychology of Pandemics

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Steven Taylor
Keyword(s):  
Psychological Factors ◽  
Disease Outbreaks ◽  
Annual Review ◽  
Publication Date ◽  
Prolonged Grief ◽  
Psychological Phenomena ◽  
Current State ◽  
Health Authorities ◽  
Important Field ◽  
Mitigation Methods

This article reviews the current state of knowledge and promising new directions concerning the psychology of pandemics. Pandemics are disease outbreaks that spread globally. Historically, psychological factors have been neglected by researchers and health authorities despite evidence that pandemics are, to a large extent, psychological phenomena whereby beliefs and behaviors influence the spreading versus containment of infection. Psychological factors are important in determining ( a) adherence to pandemic mitigation methods (e.g., adherence to social distancing), ( b) pandemic-related social disruption (e.g., panic buying, racism, antilockdown protests), and ( c) pandemic-related distress and related problems (e.g., anxiety, depression, posttraumatic stress disorder, prolonged grief disorder). The psychology of pandemics has emerged as an important field of research and practice during the coronavirus 2019 (COVID-19) pandemic. As a scholarly discipline, the psychology of pandemics is fragmented and diverse, encompassing various psychological subspecialties and allied disciplines, but is vital for shaping clinical practice and public health guidelines for COVID-19 and future pandemics. Expected final online publication date for the Annual Review of Clinical Psychology, Volume 18 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Missing Data Assumptions

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Roderick J. Little
Keyword(s):  
Missing Data ◽  
Statistical Inference ◽  
Missing Values ◽  
Likelihood Function ◽  
Sufficient Conditions ◽  
Annual Review ◽  
Publication Date ◽  
Missing Completely At Random ◽  
Missingness Mechanism ◽  
Original Definition

I review assumptions about the missing-data mechanism that underlie methods for the statistical analysis of data with missing values. I describe Rubin's original definition of missing at random, (MAR), its motivation and criticisms, and his sufficient conditions for ignoring the missingness mechanism for likelihood-based, Bayesian, and frequentist inference. Related definitions, including missing completely at random, always MAR, always missing completely at random, and partially MAR are also covered. I present a formal argument for weakening Rubin's sufficient conditions for frequentist maximum likelihood inference with precision based on the observed information. Some simple examples of MAR are described, together with an example where the missingness mechanism can be ignored even though MAR does not hold. Alternative approaches to statistical inference based on the likelihood function are reviewed, along with non-likelihood frequentist approaches, including weighted generalized estimating equations. Connections with the causal inference literature are also discussed. Finally, alternatives to Rubin's MAR definition are discussed, including informative missingness, informative censoring, and coarsening at random. The intent is to provide a relatively nontechnical discussion, although some of the underlying issues are challenging and touch on fundamental questions of statistical inference. Expected final online publication date for the Annual Review of Statistics, Volume 8 is March 7, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Physiologically Based Modeling of Food Digestion and Intestinal Microbiota: State of the Art and Future Challenges. An INFOGEST Review

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Steven Le Feunteun ◽  
Ahmed Al-Razaz ◽  
Matthijs Dekker ◽  
Erwin George ◽  
Beatrice Laroche ◽  
...  
Keyword(s):  
Gastrointestinal Tract ◽  
Historical Background ◽  
Annual Review ◽  
Publication Date ◽  
Physiologically Based ◽  
The Future ◽  
Future Challenges ◽  
Full Picture ◽  
Food Digestion

This review focuses on modeling methodologies of the gastrointestinal tract during digestion that have adopted a systems-view approach and, more particularly, on physiologically based compartmental models of food digestion and host–diet–microbiota interactions. This type of modeling appears very promising for integrating the complex stream of mechanisms that must be considered and retrieving a full picture of the digestion process from mouth to colon. We may expect these approaches to become more and more accurate in the future and to serve as a useful means of understanding the physicochemical processes occurring in the gastrointestinal tract, interpreting postprandial in vivo data, making relevant predictions, and designing healthier foods. This review intends to provide a scientific and historical background of this field of research, before discussing the future challenges and potential benefits of the establishment of such a model to study and predict food digestion and absorption in humans. Expected final online publication date for the Annual Review of Food Science and Technology, Volume 12 is March 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

The Making of Plant Armor: The Periderm

2022 ◽  
Vol 73 (1) ◽  
Author(s):  
Olga Serra ◽  
Ari Pekka Mähönen ◽  
Alexander J. Hetherington ◽  
Laura Ragni
Keyword(s):  
Regulatory Networks ◽  
Plant Biology ◽  
Raw Material ◽  
Industrial Processes ◽  
Annual Review ◽  
Publication Date ◽  
Biotic And Abiotic Stress ◽  
Meristematic Tissue ◽  
Future Challenges ◽  
Periderm Formation

The periderm acts as armor protecting the plant's inner tissues from biotic and abiotic stress. It forms during the radial thickening of plant organs such as stems and roots and replaces the function of primary protective tissues such as the epidermis and the endodermis. A wound periderm also forms to heal and protect injured tissues. The periderm comprises a meristematic tissue called the phellogen, or cork cambium, and its derivatives: the lignosuberized phellem and the phelloderm. Research on the periderm has mainly focused on the chemical composition of the phellem due to its relevance as a raw material for industrial processes. Today, there is increasing interest in the regulatory network underlying periderm development as a novel breeding trait to improve plant resilience and to sequester CO2. Here, we discuss our current understanding of periderm formation, focusing on aspects of periderm evolution, mechanisms of periderm ontogenesis, regulatory networks underlying phellogen initiation and cork differentiation, and future challenges of periderm research. Expected final online publication date for the Annual Review of Plant Biology, Volume 73 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Recent Advances in Geochemical Paleo-Oxybarometers

2021 ◽  
Vol 49 (1) ◽  
Author(s):  
Brian Kendall
Keyword(s):  
Biological Evolution ◽  
Oxygenic Photosynthesis ◽  
Annual Review ◽  
Publication Date ◽  
Grand Challenge ◽  
Spatiotemporal Variations ◽  
Recent Advances ◽  
History Of ◽  
Integrated Approaches ◽  
Over Time

Knowledge of how and why oxygenic photosynthesis, eukaryotes, metazoans, and humans evolved on Earth is important to the search for complex life outside our Solar System. Hence, one grand challenge for modern geoscience research is to reconstruct the story of how Earth's environment and life coevolved through time. A critical part of the effort to understand Earth's story is the use of geochemical signatures from the rock record—paleo-oxybarometers—to constrain atmosphere and ocean O2 levels and their spatiotemporal variations. Recent advances in analytical methods and improved knowledge of elemental and isotopic (bio)geochemical cycles have fostered development and refinement of many paleo-oxybarometers. Each offers its unique perspective and challenges toward obtaining robust (semi)quantitative O2 estimates. Overall, these paleo-oxybarometers have provided critical new insights but have also spurred new debates about Earth's oxygenation and its impact on biological evolution (and vice versa). Integrated approaches with multiple paleo-oxybarometers are now more critical than ever. ▪ Paleo-oxybarometers estimate atmosphere or ocean O2 levels, providing insight on how Earth's environment and life coevolved over time. ▪ Recent conceptual, analytical, and modeling advances, aided by studies on modern environments, have improved quantitative O2 estimates. ▪ Atmosphere and ocean paleo-oxybarometers reveal a complex history of dynamic O2 fluctuations since oxygenic photosynthesis evolved. ▪ Further improvements in the accuracy and robustness of atmosphere-ocean O2 estimates will require more integrated approaches. Expected final online publication date for the Annual Review of Earth and Planetary Sciences, Volume 49 is May 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Replicability in Empirical Legal Research

2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Jason M. Chin ◽  
Kathryn Zeiler
Keyword(s):  
Social Sciences ◽  
Social Science ◽  
Science Volume ◽  
Reform Movement ◽  
Annual Review ◽  
Publication Date ◽  
Legal Research ◽  
Current State ◽  
The Social ◽  
Statistical Issues

As part of a broader methodological reform movement, scientists are increasingly interested in improving the replicability of their research. Replicability allows others to perform replications to explore potential errors and statistical issues that might call the original results into question. Little attention, however, has been paid to the state of replicability in the field of empirical legal research (ELR). Quality is especially important in this field because empirical legal researchers produce work that is regularly relied upon by courts and other legal bodies. In this review, we summarize the current state of ELR relative to the broader movement toward replicability in the social sciences. As part of that aim, we summarize recent collective replication efforts in ELR and transparency and replicability guidelines adopted by journals that publish ELR. Based on this review, ELR seems to be lagging other fields in implementing reforms. We conclude with suggestions for reforms that might encourage improved replicability. Expected final online publication date for the Annual Review of Law and Social Science, Volume 17 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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