Dataset Information

The extensive margin and US aggregate fluctuations: A quantitative assessment.

ABSTRACT: We report empirical evidence indicating that US net business formation has recently turned more volatile, procyclical and persistent. To study these stylized facts, we estimate a DSGE model with endogenous entry and exit. Business units feature heterogeneous productivity and they shut down if the present value of expected future dividends falls below the current liquidation value. The model provides a better fit than a constant exit rate model with the fluctuations of US business formation. The introduction of the extensive margin amplifies the effects of technology and risk-premium shocks, and reduces the procyclicality of firm-level production. The main sources of variability of the US aggregate fluctuations during the Great Recession are countercyclical technology shocks, persistent adverse risk-premium shocks, and expansionary monetary policy shocks.

SUBMITTER: Casares M

PROVIDER: S-EPMC7539540 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The extensive margin and US aggregate fluctuations: A quantitative assessment.

Casares Miguel M Khan Hashmat H Poutineau Jean-Christophe JC

Journal of economic dynamics & control 20200926

We report empirical evidence indicating that US net business formation has recently turned more volatile, procyclical and persistent. To study these stylized facts, we estimate a DSGE model with endogenous entry and exit. Business units feature heterogeneous productivity and they shut down if the present value of expected future dividends falls below the current liquidation value. The model provides a better fit than a constant exit rate model with the fluctuations of US business formation. The ...[more]

PMID: 33041404

Similar Datasets

Project description:Background and objectiveA positive surgical margin (PSM) occurs in up to 32% of patients undergoing robot-assisted radical prostatectomy (RARP). Diffuse reflectance spectroscopy (DRS), which measures tissue composition according to its optical properties, can potentially be used for real-time PSM detection during RARP. Our objective was to assess the feasibility of DRS in distinguishing prostate cancer from benign tissue in RARP specimens.MethodsIn a single-center prospective study, DRS measurements were taken ex vivo for RARP specimens from 59 patients with biopsy-proven prostate carcinoma. Discriminating features from the DRS spectra were used to create a machine learning-based classification algorithm. The data were split patient-wise into training (70%) and testing (30%) sets, with ten iterations to ensure algorithm robustness. The average sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) from ten classification iterations were calculated.Key findings and limitationsWe collected 542 DRS measurements, of which 53% were tumor and 47% were healthy-tissue measurements. Twenty discriminating features from the DRS spectra were used as the input for a support vector machine model. This model achieved average sensitivity of 89%, specificity of 82%, accuracy of 85%, and AUC of 0.91 for the test set. Limitations include the binary label input for classification.Conclusions and clinical implicationsDRS can potentially discriminate prostate cancer from benign tissue. Before implementing the technique in clinical practice, further research is needed to assess its performance on heterogeneous tissue volumes and measurements from the prostate surface.Patient summaryWe looked at the ability of a technique called diffuse reflectance spectroscopy to guide surgeons in discriminating prostate cancer tissue from benign prostate tissue in real time during prostate cancer surgery. Our study showed promising results in an experimental setting. Future research will focus on bringing this technique to clinical practice.

Dataset Information

The extensive margin and US aggregate fluctuations: A quantitative assessment.

Publications

The extensive margin and US aggregate fluctuations: A quantitative assessment.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets