This volume uses state of the art models from the frontier of macroeconomics to answer key questions about how the economy functions and how policy should be conducted. The contributions cover a wide range of issues in macroeconomics and macroeconomic policy. They combine high level mathematics with economic analysis, and highlight the need to update our mathematical toolbox in order to understand the increased complexity of the macroeconomic environment. The volumerepresents hard evidence of high research intensity in many fields of macroeconomics, and warns against interpreting the scope of macroeconomics too narrowly. The mainstream business cycle analysis, based on dynamic stochastic general equilibrium (DSGE) modelling of a particular type, has beencriticised for its inability to predict or resolve the recent financial crisis. However, macroeconomic research on financial, information, and learning imperfections had not yet made their way into many of the pre-crisis DSGE models because practical econometric versions of those models were mainly designed to fit data periods that did not include financial crises. A major response to the limitations of those older DSGE models is an active research program to bring big financial shocks andvarious kinds of financial, learning, and labour market frictions into a new generation of DSGE models for guiding policy. The contributors to this book utilise models and modelling assumptions that go beyond particular modelling conventions. By using alternative yet plausible assumptions, they seek toenrich our knowledge and ability to explain macroeconomic phenomena. They contribute to expanding the frontier of macroeconomic knowledge in ways that will prove useful for macroeconomic policy.

This volume uses state of the art models from the frontier of macroeconomics to answer key questions about how the economy functions and how policy should be conducted. The contributions cover a wide range of issues in macroeconomics and macroeconomic policy. They combine high level mathematics with economic analysis, and highlight the need to update our mathematical toolbox in order to understand the increased complexity of the macroeconomic environment. The volumerepresents hard evidence of high research intensity in many fields of macroeconomics, and warns against interpreting the scope of macroeconomics too narrowly. The mainstream business cycle analysis, based on dynamic stochastic general equilibrium (DSGE) modelling of a particular type, has beencriticised for its inability to predict or resolve the recent financial crisis. However, macroeconomic research on financial, information, and learning imperfections had not yet made their way into many of the pre-crisis DSGE models because practical econometric versions of those models were mainly designed to fit data periods that did not include financial crises. A major response to the limitations of those older DSGE models is an active research program to bring big financial shocks andvarious kinds of financial, learning, and labour market frictions into a new generation of DSGE models for guiding policy. The contributors to this book utilise models and modelling assumptions that go beyond particular modelling conventions. By using alternative yet plausible assumptions, they seek toenrich our knowledge and ability to explain macroeconomic phenomena. They contribute to expanding the frontier of macroeconomic knowledge in ways that will prove useful for macroeconomic policy.