Project acronym 3D-In-Macro
Project Inequality in 3D – measurement and implications for macroeconomic theory
Researcher (PI) Andreas Fagereng
Host Institution (HI) STIFTELSEN HANDELSHOYSKOLEN BI
Call Details Starting Grant (StG), SH1, ERC-2019-STG
Summary This project will contribute toward a better understanding of inequality and its macroeconomic implications. We will study inequality and its dynamics along three dimensions: Consumption, Income and Wealth, “3D Inequality.” With novel microdata we can measure the entirety of the economy down to the single household along the 3 dimensions.
In macroeconomics, much theoretical progress has been made in understanding when distributions matter for aggregates. Newer heterogeneous agent models deliver strikingly different implications for monetary and fiscal policies than what the traditional representative agent models do, and also allow us to study the distributional implications of different policies across households. In principle, this class of models can incorporate the potentially rich interactions between inequality and the macroeconomy: on the one hand, inequality shapes macroeconomic aggregates; on the other hand, macroeconomic shocks and policies affect inequality. However, absent precise micro-level facts it is difficult to establish which of the potential mechanisms highlighted by these models are the most important in reality.
Our empirical efforts will be disciplined by these recent developments in modelling macroeconomic phenomena with microeconomic heterogeneity. Our overarching motivation is to quantify the type of micro heterogeneity that matters for macroeconomic theory and thereby inform the development of current and future macroeconomic models. The novel insights we aim to provide could lead to substantial improvements in both fiscal and monetary policy tools. Furthermore, a better understanding of the forces behind growing inequality will inform the current debate on this issue and provide important lessons to policy makers who see economic inequality as a problem in itself.
Summary
This project will contribute toward a better understanding of inequality and its macroeconomic implications. We will study inequality and its dynamics along three dimensions: Consumption, Income and Wealth, “3D Inequality.” With novel microdata we can measure the entirety of the economy down to the single household along the 3 dimensions.
In macroeconomics, much theoretical progress has been made in understanding when distributions matter for aggregates. Newer heterogeneous agent models deliver strikingly different implications for monetary and fiscal policies than what the traditional representative agent models do, and also allow us to study the distributional implications of different policies across households. In principle, this class of models can incorporate the potentially rich interactions between inequality and the macroeconomy: on the one hand, inequality shapes macroeconomic aggregates; on the other hand, macroeconomic shocks and policies affect inequality. However, absent precise micro-level facts it is difficult to establish which of the potential mechanisms highlighted by these models are the most important in reality.
Our empirical efforts will be disciplined by these recent developments in modelling macroeconomic phenomena with microeconomic heterogeneity. Our overarching motivation is to quantify the type of micro heterogeneity that matters for macroeconomic theory and thereby inform the development of current and future macroeconomic models. The novel insights we aim to provide could lead to substantial improvements in both fiscal and monetary policy tools. Furthermore, a better understanding of the forces behind growing inequality will inform the current debate on this issue and provide important lessons to policy makers who see economic inequality as a problem in itself.
Max ERC Funding
1 376 875 €
Duration
Start date: 2020-05-01, End date: 2025-04-30
Project acronym ABEP
Project Asset Bubbles and Economic Policy
Researcher (PI) Jaume Ventura Fontanet
Host Institution (HI) Centre de Recerca en Economia Internacional (CREI)
Call Details Advanced Grant (AdG), SH1, ERC-2009-AdG
Summary Advanced capitalist economies experience large and persistent movements in asset prices that are difficult to justify with economic fundamentals. The internet bubble of the 1990s and the real state market bubble of the 2000s are two recent examples. The predominant view is that these bubbles are a market failure, and are caused by some form of individual irrationality on the part of market participants. This project is based instead on the view that market participants are individually rational, although this does not preclude sometimes collectively sub-optimal outcomes. Bubbles are thus not a source of market failure by themselves but instead arise as a result of a pre-existing market failure, namely, the existence of pockets of dynamically inefficient investments. Under some conditions, bubbles partly solve this problem, increasing market efficiency and welfare. It is also possible however that bubbles do not solve the underlying problem and, in addition, create negative side-effects. The main objective of this project is to develop this view of asset bubbles, and produce an empirically-relevant macroeconomic framework that allows us to address the following questions: (i) What is the relationship between bubbles and financial market frictions? Special emphasis is given to how the globalization of financial markets and the development of new financial products affect the size and effects of bubbles. (ii) What is the relationship between bubbles, economic growth and unemployment? The theory suggests the presence of virtuous and vicious cycles, as economic growth creates the conditions for bubbles to pop up, while bubbles create incentives for economic growth to happen. (iii) What is the optimal policy to manage bubbles? We need to develop the tools that allow policy makers to sustain those bubbles that have positive effects and burst those that have negative effects.
Summary
Advanced capitalist economies experience large and persistent movements in asset prices that are difficult to justify with economic fundamentals. The internet bubble of the 1990s and the real state market bubble of the 2000s are two recent examples. The predominant view is that these bubbles are a market failure, and are caused by some form of individual irrationality on the part of market participants. This project is based instead on the view that market participants are individually rational, although this does not preclude sometimes collectively sub-optimal outcomes. Bubbles are thus not a source of market failure by themselves but instead arise as a result of a pre-existing market failure, namely, the existence of pockets of dynamically inefficient investments. Under some conditions, bubbles partly solve this problem, increasing market efficiency and welfare. It is also possible however that bubbles do not solve the underlying problem and, in addition, create negative side-effects. The main objective of this project is to develop this view of asset bubbles, and produce an empirically-relevant macroeconomic framework that allows us to address the following questions: (i) What is the relationship between bubbles and financial market frictions? Special emphasis is given to how the globalization of financial markets and the development of new financial products affect the size and effects of bubbles. (ii) What is the relationship between bubbles, economic growth and unemployment? The theory suggests the presence of virtuous and vicious cycles, as economic growth creates the conditions for bubbles to pop up, while bubbles create incentives for economic growth to happen. (iii) What is the optimal policy to manage bubbles? We need to develop the tools that allow policy makers to sustain those bubbles that have positive effects and burst those that have negative effects.
Max ERC Funding
1 000 000 €
Duration
Start date: 2010-04-01, End date: 2015-03-31
Project acronym ABRSEIST
Project Antibiotic Resistance: Socio-Economic Determinants and the Role of Information and Salience in Treatment Choice
Researcher (PI) Hannes ULLRICH
Host Institution (HI) DEUTSCHES INSTITUT FUR WIRTSCHAFTSFORSCHUNG DIW (INSTITUT FUR KONJUNKTURFORSCHUNG) EV
Call Details Starting Grant (StG), SH1, ERC-2018-STG
Summary Antibiotics have contributed to a tremendous increase in human well-being, saving many millions of lives. However, antibiotics become obsolete the more they are used as selection pressure promotes the development of resistant bacteria. The World Health Organization has proclaimed antibiotic resistance as a major global threat to public health. Today, 700,000 deaths per year are due to untreatable infections. To win the battle against antibiotic resistance, new policies affecting the supply and demand of existing and new drugs must be designed. I propose new research to identify and evaluate feasible and effective demand-side policy interventions targeting the relevant decision makers: physicians and patients. ABRSEIST will make use of a broad econometric toolset to identify mechanisms linking antibiotic resistance and consumption exploiting a unique combination of physician-patient-level antibiotic resistance, treatment, and socio-economic data. Using machine learning methods adapted for causal inference, theory-driven structural econometric analysis, and randomization in the field it will provide rigorous evidence on effective intervention designs. This research will improve our understanding of how prescribing, resistance, and the effect of antibiotic use on resistance, are distributed in the general population which has important implications for the design of targeted interventions. It will then estimate a structural model of general practitioners’ acquisition and use of information under uncertainty about resistance in prescription choice, allowing counterfactual analysis of information-improving policies such as mandatory diagnostic testing. The large-scale and structural econometric analyses allow flexible identification of physician heterogeneity, which ABRSEIST will exploit to design and evaluate targeted, randomized information nudges in the field. The result will be improved rational use and a toolset applicable in contexts of antibiotic prescribing.
Summary
Antibiotics have contributed to a tremendous increase in human well-being, saving many millions of lives. However, antibiotics become obsolete the more they are used as selection pressure promotes the development of resistant bacteria. The World Health Organization has proclaimed antibiotic resistance as a major global threat to public health. Today, 700,000 deaths per year are due to untreatable infections. To win the battle against antibiotic resistance, new policies affecting the supply and demand of existing and new drugs must be designed. I propose new research to identify and evaluate feasible and effective demand-side policy interventions targeting the relevant decision makers: physicians and patients. ABRSEIST will make use of a broad econometric toolset to identify mechanisms linking antibiotic resistance and consumption exploiting a unique combination of physician-patient-level antibiotic resistance, treatment, and socio-economic data. Using machine learning methods adapted for causal inference, theory-driven structural econometric analysis, and randomization in the field it will provide rigorous evidence on effective intervention designs. This research will improve our understanding of how prescribing, resistance, and the effect of antibiotic use on resistance, are distributed in the general population which has important implications for the design of targeted interventions. It will then estimate a structural model of general practitioners’ acquisition and use of information under uncertainty about resistance in prescription choice, allowing counterfactual analysis of information-improving policies such as mandatory diagnostic testing. The large-scale and structural econometric analyses allow flexible identification of physician heterogeneity, which ABRSEIST will exploit to design and evaluate targeted, randomized information nudges in the field. The result will be improved rational use and a toolset applicable in contexts of antibiotic prescribing.
Max ERC Funding
1 498 920 €
Duration
Start date: 2019-01-01, End date: 2023-12-31
Project acronym ACAP
Project Acency Costs and Asset Pricing
Researcher (PI) Thomas Mariotti
Host Institution (HI) FONDATION JEAN-JACQUES LAFFONT,TOULOUSE SCIENCES ECONOMIQUES
Call Details Starting Grant (StG), SH1, ERC-2007-StG
Summary The main objective of this research project is to contribute at bridging the gap between the two main branches of financial theory, namely corporate finance and asset pricing. It is motivated by the conviction that these two aspects of financial activity should and can be analyzed within a unified framework. This research will borrow from these two approaches in order to construct theoretical models that allow one to analyze the design and issuance of financial securities, as well as the dynamics of their valuations. Unlike asset pricing, which takes as given the price of the fundamentals, the goal is to derive security price processes from a precise description of firm’s operations and internal frictions. Regarding the latter, and in line with traditional corporate finance theory, the analysis will emphasize the role of agency costs within the firm for the design of its securities. But the analysis will be pushed one step further by studying the impact of these agency costs on key financial variables such as stock and bond prices, leverage, book-to-market ratios, default risk, or the holding of liquidities by firms. One of the contributions of this research project is to show how these variables are interrelated when firms and investors agree upon optimal financial arrangements. The final objective is to derive a rich set of testable asset pricing implications that would eventually be brought to the data.
Summary
The main objective of this research project is to contribute at bridging the gap between the two main branches of financial theory, namely corporate finance and asset pricing. It is motivated by the conviction that these two aspects of financial activity should and can be analyzed within a unified framework. This research will borrow from these two approaches in order to construct theoretical models that allow one to analyze the design and issuance of financial securities, as well as the dynamics of their valuations. Unlike asset pricing, which takes as given the price of the fundamentals, the goal is to derive security price processes from a precise description of firm’s operations and internal frictions. Regarding the latter, and in line with traditional corporate finance theory, the analysis will emphasize the role of agency costs within the firm for the design of its securities. But the analysis will be pushed one step further by studying the impact of these agency costs on key financial variables such as stock and bond prices, leverage, book-to-market ratios, default risk, or the holding of liquidities by firms. One of the contributions of this research project is to show how these variables are interrelated when firms and investors agree upon optimal financial arrangements. The final objective is to derive a rich set of testable asset pricing implications that would eventually be brought to the data.
Max ERC Funding
1 000 000 €
Duration
Start date: 2008-11-01, End date: 2014-10-31
Project acronym aCROBAT
Project Circadian Regulation Of Brown Adipose Thermogenesis
Researcher (PI) Zachary Philip Gerhart-Hines
Host Institution (HI) KOBENHAVNS UNIVERSITET
Call Details Starting Grant (StG), LS4, ERC-2014-STG
Summary Obesity and diabetes have reached pandemic proportions and new therapeutic strategies are critically needed. Brown adipose tissue (BAT), a major source of heat production, possesses significant energy-dissipating capacity and therefore represents a promising target to use in combating these diseases. Recently, I discovered a novel link between circadian rhythm and thermogenic stress in the control of the conserved, calorie-burning functions of BAT. Circadian and thermogenic signaling to BAT incorporates blood-borne hormonal and nutrient cues with direct neuronal input. Yet how these responses coordinately shape BAT energy-expending potential through the regulation of cell surface receptors, metabolic enzymes, and transcriptional effectors is still not understood. My primary goal is to investigate this previously unappreciated network of crosstalk that allows mammals to effectively orchestrate daily rhythms in BAT metabolism, while maintaining their ability to adapt to abrupt changes in energy demand. My group will address this question using gain and loss-of-function in vitro and in vivo studies, newly-generated mouse models, customized physiological phenotyping, and cutting-edge advances in next generation RNA sequencing and mass spectrometry. Preliminary, small-scale validations of our methodologies have already yielded a number of novel candidates that may drive key facets of BAT metabolism. Additionally, we will extend our circadian and thermogenic studies into humans to evaluate the translational potential. Our results will advance the fundamental understanding of how daily oscillations in bioenergetic networks establish a framework for the anticipation of and adaptation to environmental challenges. Importantly, we expect that these mechanistic insights will reveal pharmacological targets through which we can unlock evolutionary constraints and harness the energy-expending potential of BAT for the prevention and treatment of obesity and diabetes.
Summary
Obesity and diabetes have reached pandemic proportions and new therapeutic strategies are critically needed. Brown adipose tissue (BAT), a major source of heat production, possesses significant energy-dissipating capacity and therefore represents a promising target to use in combating these diseases. Recently, I discovered a novel link between circadian rhythm and thermogenic stress in the control of the conserved, calorie-burning functions of BAT. Circadian and thermogenic signaling to BAT incorporates blood-borne hormonal and nutrient cues with direct neuronal input. Yet how these responses coordinately shape BAT energy-expending potential through the regulation of cell surface receptors, metabolic enzymes, and transcriptional effectors is still not understood. My primary goal is to investigate this previously unappreciated network of crosstalk that allows mammals to effectively orchestrate daily rhythms in BAT metabolism, while maintaining their ability to adapt to abrupt changes in energy demand. My group will address this question using gain and loss-of-function in vitro and in vivo studies, newly-generated mouse models, customized physiological phenotyping, and cutting-edge advances in next generation RNA sequencing and mass spectrometry. Preliminary, small-scale validations of our methodologies have already yielded a number of novel candidates that may drive key facets of BAT metabolism. Additionally, we will extend our circadian and thermogenic studies into humans to evaluate the translational potential. Our results will advance the fundamental understanding of how daily oscillations in bioenergetic networks establish a framework for the anticipation of and adaptation to environmental challenges. Importantly, we expect that these mechanistic insights will reveal pharmacological targets through which we can unlock evolutionary constraints and harness the energy-expending potential of BAT for the prevention and treatment of obesity and diabetes.
Max ERC Funding
1 497 008 €
Duration
Start date: 2015-05-01, End date: 2020-04-30
Project acronym AfricanWomen
Project Women in Africa
Researcher (PI) catherine GUIRKINGER
Host Institution (HI) UNIVERSITE DE NAMUR ASBL
Call Details Starting Grant (StG), SH1, ERC-2017-STG
Summary Rates of domestic violence and the relative risk of premature death for women are higher in sub-Saharan Africa than in any other region. Yet we know remarkably little about the economic forces, incentives and constraints that drive discrimination against women in this region, making it hard to identify policy levers to address the problem. This project will help fill this gap.
I will investigate gender discrimination from two complementary perspectives. First, through the lens of economic history, I will investigate the forces driving trends in women’s relative well-being since slavery. To quantify the evolution of well-being of sub-Saharan women relative to men, I will use three types of historical data: anthropometric indicators (relative height), vital statistics (to compute numbers of missing women), and outcomes of formal and informal family law disputes. I will then investigate how major economic developments and changes in family laws differentially affected women’s welfare across ethnic groups with different norms on women’s roles and rights.
Second, using intra-household economic models, I will provide new insights into domestic violence and gender bias in access to crucial resources in present-day Africa. I will develop a new household model that incorporates gender identity and endogenous outside options to explore the relationship between women’s empowerment and the use of violence. Using the notion of strategic delegation, I will propose a new rationale for the separation of budgets often observed in African households and generate predictions of how improvements in women’s outside options affect welfare. Finally, with first hand data, I will investigate intra-household differences in nutrition and work effort in times of food shortage from the points of view of efficiency and equity. I will use activity trackers as an innovative means of collecting high quality data on work effort and thus overcome data limitations restricting the existing literature
Summary
Rates of domestic violence and the relative risk of premature death for women are higher in sub-Saharan Africa than in any other region. Yet we know remarkably little about the economic forces, incentives and constraints that drive discrimination against women in this region, making it hard to identify policy levers to address the problem. This project will help fill this gap.
I will investigate gender discrimination from two complementary perspectives. First, through the lens of economic history, I will investigate the forces driving trends in women’s relative well-being since slavery. To quantify the evolution of well-being of sub-Saharan women relative to men, I will use three types of historical data: anthropometric indicators (relative height), vital statistics (to compute numbers of missing women), and outcomes of formal and informal family law disputes. I will then investigate how major economic developments and changes in family laws differentially affected women’s welfare across ethnic groups with different norms on women’s roles and rights.
Second, using intra-household economic models, I will provide new insights into domestic violence and gender bias in access to crucial resources in present-day Africa. I will develop a new household model that incorporates gender identity and endogenous outside options to explore the relationship between women’s empowerment and the use of violence. Using the notion of strategic delegation, I will propose a new rationale for the separation of budgets often observed in African households and generate predictions of how improvements in women’s outside options affect welfare. Finally, with first hand data, I will investigate intra-household differences in nutrition and work effort in times of food shortage from the points of view of efficiency and equity. I will use activity trackers as an innovative means of collecting high quality data on work effort and thus overcome data limitations restricting the existing literature
Max ERC Funding
1 499 313 €
Duration
Start date: 2018-08-01, End date: 2023-07-31
Project acronym AgeingStemCellFate
Project The Role of Ectopic Adipocyte Progenitors in Age-related Stem Cell Dysfunction, Systemic Inflammation, and Metabolic Disease
Researcher (PI) Tim Julius Schulz
Host Institution (HI) DEUTSCHES INSTITUT FUER ERNAEHRUNGSFORSCHUNG POTSDAM REHBRUECKE
Call Details Starting Grant (StG), LS4, ERC-2012-StG_20111109
Summary Ageing is accompanied by ectopic white adipose tissue depositions in skeletal muscle and other anatomical locations, such as brown adipose tissue and the bone marrow. Ectopic fat accrual contributes to organ dysfunction, systemic insulin resistance, and other perturbations that have been implicated in metabolic diseases.
This research proposal aims to identify the regulatory cues that control the development of ectopic progenitor cells that give rise to this type of fat. It is hypothesized that an age-related dysfunction of the stem cell niche leads to an imbalance between (1) tissue-specific stem cells and (2) fibroblast-like, primarily adipogenic progenitors that reside within many tissues. Novel methodologies that assess stem/progenitor cell characteristics on the single cell level will be combined with animal models of lineage tracing to determine the developmental origin of these adipogenic progenitors and processes that regulate their function.
Notch signalling is a key signalling pathway that relies on direct physical interaction to control stem cell fate. It is proposed that impaired Notch activity contributes to the phenotypical shift of precursor cell distribution in aged tissues.
Lastly, the role of the stem cell niche in ectopic adipocyte progenitor formation will be analyzed. External signals originating from the surrounding niche cells regulate the developmental fate of stem cells. Secreted factors and their role in the formation of ectopic adipocyte precursors during senescence will be identified using a combination of biochemical and systems biology approaches.
Accomplishment of these studies will help to understand the basic processes of stem cell ageing and identify mechanisms of age-related functional decline in tissue regeneration. By targeting the population of tissue-resident adipogenic progenitor cells, therapeutic strategies could be developed to counteract metabolic complications associated with the ageing process.
Summary
Ageing is accompanied by ectopic white adipose tissue depositions in skeletal muscle and other anatomical locations, such as brown adipose tissue and the bone marrow. Ectopic fat accrual contributes to organ dysfunction, systemic insulin resistance, and other perturbations that have been implicated in metabolic diseases.
This research proposal aims to identify the regulatory cues that control the development of ectopic progenitor cells that give rise to this type of fat. It is hypothesized that an age-related dysfunction of the stem cell niche leads to an imbalance between (1) tissue-specific stem cells and (2) fibroblast-like, primarily adipogenic progenitors that reside within many tissues. Novel methodologies that assess stem/progenitor cell characteristics on the single cell level will be combined with animal models of lineage tracing to determine the developmental origin of these adipogenic progenitors and processes that regulate their function.
Notch signalling is a key signalling pathway that relies on direct physical interaction to control stem cell fate. It is proposed that impaired Notch activity contributes to the phenotypical shift of precursor cell distribution in aged tissues.
Lastly, the role of the stem cell niche in ectopic adipocyte progenitor formation will be analyzed. External signals originating from the surrounding niche cells regulate the developmental fate of stem cells. Secreted factors and their role in the formation of ectopic adipocyte precursors during senescence will be identified using a combination of biochemical and systems biology approaches.
Accomplishment of these studies will help to understand the basic processes of stem cell ageing and identify mechanisms of age-related functional decline in tissue regeneration. By targeting the population of tissue-resident adipogenic progenitor cells, therapeutic strategies could be developed to counteract metabolic complications associated with the ageing process.
Max ERC Funding
1 496 444 €
Duration
Start date: 2013-03-01, End date: 2018-02-28
Project acronym ALK7
Project Metabolic control by the TGF-² superfamily receptor ALK7: A novel regulator of insulin secretion, fat accumulation and energy balance
Researcher (PI) Carlos Ibanez
Host Institution (HI) KAROLINSKA INSTITUTET
Call Details Advanced Grant (AdG), LS4, ERC-2008-AdG
Summary The aim of this proposal is to understand a novel regulatory signaling network controlling insulin secretion, fat accumulation and energy balance centered around selected components of the TGF-² signaling system, including Activins A and B, GDF-3 and their receptors ALK7 and ALK4. Recent results from my laboratory indicate that these molecules are part of paracrine signaling networks that control important functions in pancreatic islets and adipose tissue through feedback inhibition and feed-forward regulation. These discoveries have open up a new research area with important implications for the understanding of metabolic networks and the treatment of human metabolic syndromes, such as diabetes and obesity.
To drive progress in this new research area beyond the state-of-the-art it is proposed to: i) Elucidate the molecular mechanisms by which Activins regulate Ca2+ influx and insulin secretion in pancreatic ²-cells; ii) Elucidate the molecular mechanisms underlying the effects of GDF-3 on adipocyte metabolism, turnover and fat accumulation; iii) Investigate the interplay between insulin levels and fat deposition in the development of insulin resistance using mutant mice lacking Activin B and GDF-3; iv) Investigate tissue-specific contributions of ALK7 and ALK4 signaling to metabolic control by generating and characterizing conditional mutant mice; v) Investigate the effects of specific and reversible inactivation of ALK7 and ALK4 on metabolic regulation using a novel chemical-genetic approach based on analog-sensitive alleles.
This is research of a high-gain/high-risk nature. It is posed to open unique opportunities for further exploration of complex metabolic networks. The development of drugs capable of enhancing insulin secretion, limiting fat accumulation and ameliorating diet-induced obesity by targeting components of the ALK7 signaling network will find a strong rationale in the results of the proposed work.
Summary
The aim of this proposal is to understand a novel regulatory signaling network controlling insulin secretion, fat accumulation and energy balance centered around selected components of the TGF-² signaling system, including Activins A and B, GDF-3 and their receptors ALK7 and ALK4. Recent results from my laboratory indicate that these molecules are part of paracrine signaling networks that control important functions in pancreatic islets and adipose tissue through feedback inhibition and feed-forward regulation. These discoveries have open up a new research area with important implications for the understanding of metabolic networks and the treatment of human metabolic syndromes, such as diabetes and obesity.
To drive progress in this new research area beyond the state-of-the-art it is proposed to: i) Elucidate the molecular mechanisms by which Activins regulate Ca2+ influx and insulin secretion in pancreatic ²-cells; ii) Elucidate the molecular mechanisms underlying the effects of GDF-3 on adipocyte metabolism, turnover and fat accumulation; iii) Investigate the interplay between insulin levels and fat deposition in the development of insulin resistance using mutant mice lacking Activin B and GDF-3; iv) Investigate tissue-specific contributions of ALK7 and ALK4 signaling to metabolic control by generating and characterizing conditional mutant mice; v) Investigate the effects of specific and reversible inactivation of ALK7 and ALK4 on metabolic regulation using a novel chemical-genetic approach based on analog-sensitive alleles.
This is research of a high-gain/high-risk nature. It is posed to open unique opportunities for further exploration of complex metabolic networks. The development of drugs capable of enhancing insulin secretion, limiting fat accumulation and ameliorating diet-induced obesity by targeting components of the ALK7 signaling network will find a strong rationale in the results of the proposed work.
Max ERC Funding
2 462 154 €
Duration
Start date: 2009-04-01, End date: 2014-03-31
Project acronym ALMP_ECON
Project Effective evaluation of active labour market policies in social insurance programs - improving the interaction between econometric evaluation estimators and economic theory
Researcher (PI) Bas Van Der Klaauw
Host Institution (HI) STICHTING VU
Call Details Starting Grant (StG), SH1, ERC-2007-StG
Summary In most European countries social insurance programs, like welfare, unemployment insurance and disability insurance are characterized by low reemployment rates. Therefore, governments spend huge amounts of money on active labour market programs, which should help individuals in finding work. Recent surveys indicate that programs which aim at intensifying job search behaviour are much more effective than schooling programs for improving human capital. A second conclusion from these surveys is that despite the size of the spendings on these programs, evidence on its effectiveness is limited. This research proposal aims at developing an economic framework that will be used to evaluate the effectiveness of popular programs like offering reemployment bonuses, fraud detection, workfare and job search monitoring. The main innovation is that I will combine economic theory with recently developed econometric techniques and detailed administrative data sets, which have not been explored before. While most of the literature only focuses on short-term outcomes, the available data allow me to also consider the long-term effectiveness of programs. The key advantage of an economic model is that I can compare the effectiveness of the different programs, consider modifications of programs and combinations of programs. Furthermore, using an economic model I can construct profiling measures to improve the targeting of programs to subsamples of the population. This is particularly relevant if the effectiveness of programs differs between individuals or depends on the moment in time the program is offered. Therefore, the results from this research will not only be of scientific interest, but will also be of great value to policymakers.
Summary
In most European countries social insurance programs, like welfare, unemployment insurance and disability insurance are characterized by low reemployment rates. Therefore, governments spend huge amounts of money on active labour market programs, which should help individuals in finding work. Recent surveys indicate that programs which aim at intensifying job search behaviour are much more effective than schooling programs for improving human capital. A second conclusion from these surveys is that despite the size of the spendings on these programs, evidence on its effectiveness is limited. This research proposal aims at developing an economic framework that will be used to evaluate the effectiveness of popular programs like offering reemployment bonuses, fraud detection, workfare and job search monitoring. The main innovation is that I will combine economic theory with recently developed econometric techniques and detailed administrative data sets, which have not been explored before. While most of the literature only focuses on short-term outcomes, the available data allow me to also consider the long-term effectiveness of programs. The key advantage of an economic model is that I can compare the effectiveness of the different programs, consider modifications of programs and combinations of programs. Furthermore, using an economic model I can construct profiling measures to improve the targeting of programs to subsamples of the population. This is particularly relevant if the effectiveness of programs differs between individuals or depends on the moment in time the program is offered. Therefore, the results from this research will not only be of scientific interest, but will also be of great value to policymakers.
Max ERC Funding
550 000 €
Duration
Start date: 2008-07-01, End date: 2013-06-30
Project acronym AltCheM
Project In vivo functional screens to decipher mechanisms of stochastically- and mutationally-induced chemoresistance in Acute Myeloid Leukemia
Researcher (PI) Alexandre PUISSANT
Host Institution (HI) INSTITUT NATIONAL DE LA SANTE ET DE LA RECHERCHE MEDICALE
Call Details Starting Grant (StG), LS4, ERC-2017-STG
Summary Acute Myeloid Leukemia (AML), the most common leukemia diagnosed in adults, represents the paradigm of resistance to front-line therapies in hematology. Indeed, AML is so genetically complex that only few targeted therapies are currently tested in this disease and chemotherapy remains the only standard treatment for AML since the past four decades. Despite an initial sustained remission achieved by chemotherapeutic agents, almost all patients relapse with a chemoresistant minimal residual disease (MRD). The goal of my proposal is to characterize the still poorly understood biological mechanisms underlying persistence and emergence of MRD.
MRD is the consequence of the re-expansion of leukemia-initiating cells that are intrinsically more resistant to chemotherapy. This cell fraction may be stochastically more prone to survive front-line therapy regardless of their mutational status (the stochastic model), or genetically predetermined to resist by virtue of a collection of chemoprotective mutations (the mutational model).
I have already generated in mice, by consecutive rounds of chemotherapy, a stochastic MLL-AF9-driven chemoresistance model that I examined by RNA-sequencing. I will pursue the comprehensive cell autonomous and cell non-autonomous characterization of this chemoresistant AML disease using whole-exome and ChIP-sequencing.
To establish a mutationally-induced chemoresistant mouse model, I will conduct an innovative in vivo screen using pooled mutant open reading frame and shRNA libraries in order to predict which combinations of mutations, among those already known in AML, actively promote chemoresistance.
Finally, by combining genomic profiling and in vivo shRNA screening experiments, I will decipher the molecular mechanisms and identify the functional effectors of these two modes of resistance. Ultimately, I will then be able to firmly establish the fundamental relevance of the stochastic and/or the mutational model of chemoresistance for MRD genesis.
Summary
Acute Myeloid Leukemia (AML), the most common leukemia diagnosed in adults, represents the paradigm of resistance to front-line therapies in hematology. Indeed, AML is so genetically complex that only few targeted therapies are currently tested in this disease and chemotherapy remains the only standard treatment for AML since the past four decades. Despite an initial sustained remission achieved by chemotherapeutic agents, almost all patients relapse with a chemoresistant minimal residual disease (MRD). The goal of my proposal is to characterize the still poorly understood biological mechanisms underlying persistence and emergence of MRD.
MRD is the consequence of the re-expansion of leukemia-initiating cells that are intrinsically more resistant to chemotherapy. This cell fraction may be stochastically more prone to survive front-line therapy regardless of their mutational status (the stochastic model), or genetically predetermined to resist by virtue of a collection of chemoprotective mutations (the mutational model).
I have already generated in mice, by consecutive rounds of chemotherapy, a stochastic MLL-AF9-driven chemoresistance model that I examined by RNA-sequencing. I will pursue the comprehensive cell autonomous and cell non-autonomous characterization of this chemoresistant AML disease using whole-exome and ChIP-sequencing.
To establish a mutationally-induced chemoresistant mouse model, I will conduct an innovative in vivo screen using pooled mutant open reading frame and shRNA libraries in order to predict which combinations of mutations, among those already known in AML, actively promote chemoresistance.
Finally, by combining genomic profiling and in vivo shRNA screening experiments, I will decipher the molecular mechanisms and identify the functional effectors of these two modes of resistance. Ultimately, I will then be able to firmly establish the fundamental relevance of the stochastic and/or the mutational model of chemoresistance for MRD genesis.
Max ERC Funding
1 500 000 €
Duration
Start date: 2018-03-01, End date: 2023-02-28
