The ECB's New Multi-Country Model for the euro area: NMCM - simulated with rational expectations

The model presented here is a New estimated medium-scale Multi-Country Model (NMCM) which covers the five largest euro area countries and is used for forecasting and scenarios analysis at the European Central Bank. The model has a tight theoretical structure which allows for non-unitary elasticity of substitution, non-constant augmenting technical progress and heterogeneous sectors with differentiated price and income elastiticites of demand across sectors. Furthermore, it has the explicit inclusion of expectations on the basis of three optimising private sector decision making units: i.e. firms, trade unions and households, where output is in the short run demand-determined and monopolistically competing firms set prices and factor demands. Labour is indivisible and monopoly-unions set wages and households make consumption/saving decisions. We assume agents optimise under limited information where each agent knows only the parameters related to his/her optimization problem. Therefore we estimate with GMM, which implicitly assumes limited information boundedly rational expectations. In this paper we provide some simulation results under the assumption of model-consistent rational expectations, we show that there is some heterogeneity across countries and that the reactions of the economies to shocks depends strongly on whether the shocks are pre-announced, announced and credible or unannounced and uncredible. JEL Classification: C51, C6, E5Macro model, open-economy macroeconomics, Rational Expectations

The ECB's New Multi-Country Model for the euro area: NMCM - with boundedly rational learning expectations

Rational expectations has been the dominant way to model expectations, but the literature has quickly moved to a more realistic assumption of boundedly rational learning where agents are assumed to use only a limited set of information to form their expectations. A standard assumption is that agents form expectations by using the correctly specified reduced form model of the economy, the minimal state variable solution (MSV), but they do not know the parameters. However, with medium-sized and large models the closed-form MSV solutions are difficult to attain given the large number of variables that could be included. Therefore, agents base expectations on a misspecified MSV solution. In contrast, we assume agents know the deep parameters of their own optimising frameworks. However, they are not assumed to know the structure nor the parameterisation of the rest of the economy, nor do they know the stochastic processes generating shocks hitting the economy. In addition, agents are assumed to know that the changes (or the growth rates) of fundament variables can be modelled as stationary ARMA (p,q) processes, the exact form of which is not, however, known by agents. This approach avoids the complexities of dealing with a potential vast multitude of alternative mis-specified MSVs. Using a new Multi-country Euro area Model with Boundedly Estimated Rationality we show this approach is compatible with the same limited information assumption that was used in deriving and estimating the behavioral equations of different optimizing agents. We find that there are strong differences in the adjustment path to the shocks to the economy when agent form expectations using our learning approach compared to expectations formed under the assumption of strong rationality. Furthermore, we find that some variation in expansionary fiscal policy in periods of downturns compared to boom periods. JEL Classification: C51, D83, D84, E17, E32bounded rationality, Expectation, heterogeneity, imperfect information, Learning, macro modelling, open-economy macroeconomics

The ECB's New Multi-Country Model for the Euro area: NMCM - with Boundedly Rational Learning Expectations*

Rational expectations has been the dominant way to model expectations, but the literature has quickly moved to a more realistic assumption of boundedly rational learning where agents are assumed to use only a limited set of information to form their expectations. A standard assumption is that agents form expectations by using the correctly specified reduced form model of the economy, the minimal state variable solution (MSV), but they do not know the parameters. However, with medium-sized and large models the closed-form MSV solutions are difficult to attain given the large number of variables that could be included. Therefore, agents base expectations on a misspecified MSV solution. In contrast, we assume agents know the deep parameters of their own optimizing frameworks. However, they are not assumed to know the structure nor the parameterization of the rest of the economy, nor do they know the stochastic processes generating shocks hitting the economy. In addition, agents are assumed to know that the changes (or the growth rates) of fundament variables can be modeled as stationary ARMA(p,q) processes, the exact form of which is not, however, known by agents. This approach avoids the complexities of dealing with a potential vast multitude of alternative mis-specified MSVs. Using a new Multi-country Euro area Model with Boundedly Estimated Rationality we show this approach is compatible with the same limited information assumption that was used in deriving and estimating the behavioral equations of different optimizing agents. We find that there are strong differences in the adjustment path to the shocks to the economy when agent form expectations using our learning approach compared to expectations formed under the assumption of strong rationality. Furthermore, we find that some variation in expansionary fiscal policy in periods of downturns compared to boom periods.

Circulating DNA and survival in solid tumors

[Background]: The ability to undertake molecular analysis to inform on prognosis and predictors of response to therapy is limited by accessibility of tissue. Measurement of total circulating free DNA (cfDNA) or circulating tumor DNA (ctDNA) in peripheral blood may allow easier access to tumor material and help to predict clinical outcomes. [Methods]: A systematic review of electronic databases identified publications exploring the association between cfDNA or ctDNA and overall survival (OS) in solid tumors. HRs for OS were extracted from multivariable analyses and included in a meta-analysis. Pooled HRs were computed and weighted using generic inverse variance and random-effect modeling. For studies not reporting multivariable analyses, univariable ORs were estimated from Kaplan-Meier curves for OS at 1 and 3 years. [Results]: Thirty-nine studies comprising 4,052 patients were included in the analysis. Detection of ctDNA was associated with a significantly worse OS in multivariable analyses [HR, 2.70; 95% confidence interval (CI), 2.02-3.61; P < 0.001). Similar results were observed in the univariable analyses at 3 and 1 year (OR, 4.83; 95% CI, 3.20-7.28; P < 0.001).There was also a statistically significant association between high total cfDNA and worse OS for studies reporting multivariable and univariate data at 3 years (HR, 1.91; 95% CI, 1.59-2.29; P < 0.001 and OR, 2.82; 95% CI, 1.93-4.13; P < 0.001, respectively). [Conclusions]: High levels of total cfDNA and presence of ctDNA are associated with worse survival in solid tumors. [Impact]: Circulating DNA is associated with worse outcome in solid tumors.This work was supported by grants from CRIS cancer foundation (to A. Ocaña and A. Pandiella).Peer Reviewe

Integrin ανβ6 Protein Expression and Prognosis in Solid Tumors: A Meta-Analysis

[Background and objective]: Integrins are a family of adhesion receptor proteins that provide signaling from the extracellular matrix to the cytoplasm. They have been associated with cancer by promoting migration, invasion, metastasis, and survival. ¿¿ß6 integrin is upregulated in several tumors. Here, we evaluate the prognostic impact of ¿¿ß6 integrin protein expression in solid tumors. [Methods]: A systematic search of electronic databases identified publications exploring the effect of ¿¿ß6 integrin on overall survival (OS). Hazard ratios (HRs) were pooled in a meta-analysis using generic inverse variance and random effects modeling. Subgroup analyses were conducted based on tumor site, tumor stage, antibody used for immunohistochemistry (IHC) and method for extraction of the HR. A meta-regression explored the influence of clinical variables on the magnitude of effect of ¿¿ß6 integrins on OS. [Results]: Seventeen studies comprising 5795 patients met the inclusion criteria. High ¿¿ß6 integrin expression in tumors was associated with worse OS (HR 1.65, 95% confidence interval [CI] 1.32-2.06; Cochran's Q p < 0.001, I2 = 81%). Adverse outcomes were similar in all tumor sites (subgroup difference p = 0.10), with the strongest association between ¿¿ß6 integrins and OS in gastric cancer (HR 2.20, 95% CI 1.71-2.83) and the lowest in head and neck cancer (HR 1.21, 95% CI 0.79-1.83). There was no significant difference between early-stage and metastatic cancer, type of IHC antibodies, and analysis methods. [Conclusions]: High expression of ¿¿ß6 integrins is associated with adverse survival outcome in several tumors. Prospective studies evaluating the prognostic impact of ¿¿ß6 integrin and its role as a therapeutic target are warranted

The ECB.s New Multi-Country Model for the Euro area: NMCM - with Boundedly Rational Learning Expectations

Rational expectations has been the dominant way to model expectations, but the literature has quickly moved to a more realistic assumption of boundedly rational learning where agents are assumed to use only a limited set of information to form their expectations. A standard assumption is that agents form expectations by using the correctly speci ed reduced form model of the economy, the minimal state variable solution (MSV), but they do not know the parameters. However, with medium-sized and large models the closed-form MSV solutions are di¢ cult to attain given the large number of variables that could be included. Therefore, agents base expectations on a misspeci ed MSV solution. In contrast, we assume agents know the deep parameters of their own optimising frameworks. However, they are not assumed to know the structure nor the parameterisation of the rest of the economy, nor do they know the stochastic processes generating shocks hitting the economy. In addition, agents are assumed to know that the changes (or the growth rates) of fundament variables can be modelled as stationary ARMA(p,q) processes, the exact form of which is not, however, known by agents. This approach avoids the complexities of dealing with a potential vast multitude of alternative mis-speci ed MSVs. Using a new Multi-country Euro area Model with Boundedly Estimated Rationality we show this approach is compatible with the same limited information assumption that was used in deriving and estimating the behavioral equations of di¤erent optimizing agents. We nd that there are strong di¤erences in the adjustment path to the shocks to the economy when agent form expectations using our learning approach compared to expectations formed under the assumption of strong rationality. Furthermore, we nd that some variation in expansionary scal policy in periods of downturns compared to boom periods

Neuregulin expression in solid tumors: Prognostic value and predictive role to anti-HER3 therapies

[Background]: Neuregulins (NRG) are a family of epidermal growth factor ligands which act through binding to HER3 and HER4 receptors. NRGs are widely expressed in solid tumors. Their prognostic significance or their role as predictors of benefit from anti-HER3 therapy is not known. [Results]: Of 29 included studies, 7 studies reported the association between NRG and outcome. NRG was most commonly expressed in breast, prostate, colon and bladder cancers. NRG expression was not associated with either OS or PFS (HR: 3.47, 95% CI 0.78-15.47, p = 0.10 and HR: 1.64, 95% CI 0.94-2.86, p = 0.08, respectively). In 4 placebo controlled trials of anti-HER3 therapy, the addition of anti-HER3 antibodies to control therapy in unselected patients was not associated with improved PFS (HR: 0.88, 95% CI 0.75-1.04. p = 0.14). However, in patients with high NRG expression, there was significantly delayed progression (HR: 0.35, 95% CI 0.23-0.52, p < 0.001). Anti-HER3 antibodies were associated with increased risk of diarrhea, nausea and rash. [Methods]: A search of electronically available databases identified studies exploring clinical outcomes based on NRG expression, as well as placebo-controlled trials of HER3- directed therapy reporting results based on NRG expression status. Data were combined in a meta-analysis using generic inverse variance and random effects modeling for studies reporting the hazard ratio (HR) for overall (OS) or progression-free survival (PFS). Mantel-Haenszel random-effect modeling was used for odds ratio (OR) for 3-year and 5-year OS and PFS. [Conclusions]: NRG expression is not associated with either OS or PFS, but is a predictor of benefit from anti-HER3 antibodies.Instituto de Salud Carlos III (PI13/01444), ACEPAIN; Diputación de Albacete and CRIS Foundation (to AO). Ministry of Economy and Competitiveness of Spain (BFU2012–39151), the Instituto de Salud Carlos III through the Spanish Cancer Centers Network Program (RD12/0036/0003), the scientific foundation of the AECC and the CRIS Foundation (to AP). Instituto de Salud Carlos III (PI15/01180) (to AE-O). JCM is a recipient of a Miguel Servet fellowship program (CP12/03073). The work carried out in the EU laboratories receive support from the European Community through the regional development funding program (FEDER).Peer Reviewe

Transcriptomic analyses identify association between mitotic kinases, PDZ-binding kinase and BUB1, and clinical outcome in breast cancer

Protein kinases are important components in oncogenic transformation of breast cancer. Evaluation of upregulated genes that codify for protein kinases could be used as biomarkers to predict clinical outcome. Gene expression and functional analyses using public datasets were performed to identify differential gene expression and functions in basal-like tumors compared with normal breast tissue. Overall survival (OS) associated with upregulated genes was explored using the KM Plotter online tool. The prognostic influence of these genes in luminal tumors and systemically untreated patients was also assessed. Of the 426 transcripts identified in basal-like tumors, 11 genes that coded for components of protein kinases were upregulated with more than a fourfold change. Regulation of cell cycle was an enriched function containing 10 of these 11 identified genes. Among them, expression of four genes, BUB1β, CDC28, NIMA, and PDZ binding kinase, were all associated with improved OS when using at least one probe in the basal-like subtype. Two genes, BUB1β and PDZ binding kinase, showed consistent association with improved OS irrespective of the gene probe used for the analysis. No association was observed for these genes with relapse-free survival. In contrast, both BUB1β and PDZ binding kinase showed worse OS in luminal tumors and in a cohort of systemically untreated patients. BUB1β and PDZ binding kinase are associated with improved OS in basal-like tumors and worse OS in luminal and untreated patients. The association with a better outcome in basal-like tumors could be due to a more favorable response to chemotherapy.Instituto de Salud Carlos III (PI13/01444), ACEPAIN; Diputación de Albacete and CRIS Cancer Foundation (to AO). Ministry of Economy and Competitiveness of Spain (BFU2012-39151), the Instituto de Salud Carlos III through the Spanish Cancer Centers Network Program (RD12/0036/0003) and the Scientific Foundation of the Spanish Association Against Cancer (AECC) and the CRIS Foundation to AP. Our work is partially supported by the European Union through the FEDER program.Peer Reviewe