Project acronym DETECT
Project Describing Evolution with Theoretical, Empirical, and Computational Tools
Researcher (PI) Jeffrey Jensen
Host Institution (HI) ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE
Country Switzerland
Call Details Starting Grant (StG), LS8, ERC-2012-StG_20111109
Summary As evolutionary biologists we are of course motivated by the desire to gain further insight in to the evolution of natural populations. The main goals of this proposal are to (i) develop theory and methodology that will enable the identification of adaptively evolving genomic regions using polymorphism data, (ii) develop theory and methodology for the estimation of whole-genome rates of adaptive evolution, and (iii) apply the developed theory in two strategic collaborative applications. Capitalizing on recently available and soon-to-be available whole genome polymorphism data across multiple taxa, these approaches are expected to significantly improve the identification and localization of recent selective events, as well as provide long sought after information regarding the genomic distributions of selective effects. Additionally, through these on-going collaborations with empirical and experimental labs, this methodology will allow for specific hypothesis testing that will further illuminate classical examples of adaptation. Together, this proposal seeks to Describe Evolution with Theoretical, Empirical and Computational Tools (DETECT), seeking to accurately describe the very mode and tempo of Darwinian adaptation.
Summary
As evolutionary biologists we are of course motivated by the desire to gain further insight in to the evolution of natural populations. The main goals of this proposal are to (i) develop theory and methodology that will enable the identification of adaptively evolving genomic regions using polymorphism data, (ii) develop theory and methodology for the estimation of whole-genome rates of adaptive evolution, and (iii) apply the developed theory in two strategic collaborative applications. Capitalizing on recently available and soon-to-be available whole genome polymorphism data across multiple taxa, these approaches are expected to significantly improve the identification and localization of recent selective events, as well as provide long sought after information regarding the genomic distributions of selective effects. Additionally, through these on-going collaborations with empirical and experimental labs, this methodology will allow for specific hypothesis testing that will further illuminate classical examples of adaptation. Together, this proposal seeks to Describe Evolution with Theoretical, Empirical and Computational Tools (DETECT), seeking to accurately describe the very mode and tempo of Darwinian adaptation.
Max ERC Funding
1 071 729 €
Duration
Start date: 2013-01-01, End date: 2017-08-31
Project acronym HETMAT
Project Heterogeneity That Matters for Trade and Welfare
Researcher (PI) Thierry Mayer
Host Institution (HI) FONDATION NATIONALE DES SCIENCES POLITIQUES
Country France
Call Details Starting Grant (StG), SH1, ERC-2012-StG_20111124
Summary Accounting for firms' heterogeneity in trade patterns is probably one of the key innovations of international trade that occurred during the last decade. The impact of initial papers such as Melitz (2003) and Bernard and Jensen (1999) is so large in the field that it is considered to have introduced a new paradigm. Apart from providing a convincing framework for a set of empirical facts, the main motivation of this literature was that there are new gains to be expected from trade liberalization. Those come from a selection process, raising aggregate productivity through the reallocation of output among heterogeneous firms. It initially seemed that the information requirements for trade policy evaluations had become much more demanding, in particular requiring detailed micro data. However, the recent work of Arkolakis et al. (2011) suggests that two aggregate ``sufficient statistics'' may be all that is needed to compute the welfare changes associated with trade liberalization. More, they show that those statistics are the same when evaluating welfare changes in representative firm models. The project has three parts. The first one starts by showing that the sufficient statistics approach relies crucially on a specific distributional assumption on heterogeneity, the Pareto distribution. When distributed non-Pareto, heterogeneity does matter, i.e. aggregate statistics are not sufficient to evaluate welfare changes and predict trade patterns. The second part of the project specifies which type of firm-level heterogeneity matters. It shows how to identify which sectors are characterized by ``productivity sorting'' and in which ones ``quality sorting'' is more relevant. Extending the analysis to multiple product firms, the third part shows that heterogeneity inside the firm also matters for welfare changes following trade shocks. It considers how the change in the product mix of the firm following trade liberalization alters the measured productivity of the firm.
Summary
Accounting for firms' heterogeneity in trade patterns is probably one of the key innovations of international trade that occurred during the last decade. The impact of initial papers such as Melitz (2003) and Bernard and Jensen (1999) is so large in the field that it is considered to have introduced a new paradigm. Apart from providing a convincing framework for a set of empirical facts, the main motivation of this literature was that there are new gains to be expected from trade liberalization. Those come from a selection process, raising aggregate productivity through the reallocation of output among heterogeneous firms. It initially seemed that the information requirements for trade policy evaluations had become much more demanding, in particular requiring detailed micro data. However, the recent work of Arkolakis et al. (2011) suggests that two aggregate ``sufficient statistics'' may be all that is needed to compute the welfare changes associated with trade liberalization. More, they show that those statistics are the same when evaluating welfare changes in representative firm models. The project has three parts. The first one starts by showing that the sufficient statistics approach relies crucially on a specific distributional assumption on heterogeneity, the Pareto distribution. When distributed non-Pareto, heterogeneity does matter, i.e. aggregate statistics are not sufficient to evaluate welfare changes and predict trade patterns. The second part of the project specifies which type of firm-level heterogeneity matters. It shows how to identify which sectors are characterized by ``productivity sorting'' and in which ones ``quality sorting'' is more relevant. Extending the analysis to multiple product firms, the third part shows that heterogeneity inside the firm also matters for welfare changes following trade shocks. It considers how the change in the product mix of the firm following trade liberalization alters the measured productivity of the firm.
Max ERC Funding
1 119 040 €
Duration
Start date: 2012-11-01, End date: 2018-07-31
