Financial factors in macroeconometric models

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The crucial role of credit has long been recognized as essential for economic development, with historical insights from notable economists. Before the financial crisis, there was consensus among researchers and policymakers about the significance of financial frictions in business cycles and the potential for financial turmoil to trigger severe economic downturns. However, practical applications often relied on simplified models that overlooked the impact of financial frictions, focusing instead on non-financial market issues. This approach persisted partly because many economic downturns did not appear directly linked to financial market failures. The subprime crisis, which triggered panic and led to Lehman Brothers' collapse in 2008, prompted a reevaluation of existing macroeconomic frameworks. To contribute to the economic discourse from a fresh perspective, it is essential to integrate relevant frictions that elucidate recent experiences. This thesis explores various methods for incorporating significant frictions and financial variables into macroeconometric models, examining their implications for standard statistical inference and macroeconomic policy. The work is organized into three distinct aspects, each presenting a self-contained idea, with further details provided in the subsequent sections.