Periodic Reporting for period 4 - LiquidHouseCycle (A Unified Framework of Business Cycles and Household Portfolios: Income Risks, Asset Liquidity, and Inequality)
Reporting period: 2021-12-01 to 2023-05-31
Households face large idiosyncratic income risks and use their wealth to self-insure. In doing so, they make portfolio choices that can be summarised grosso modo as choices between liquid (safe and nominal) and illiquid (risky and real) assets. These choices have the potential to generate strong aggregate effects, since investment in real assets generates an immediate demand for goods, while liquid nominal savings are only generated when someone else uses the funds for investment or consumption. As a result, portfolio choices are key to economic dynamics and important for the transmission of monetary and fiscal policy. Moreover, the portfolio positions of households and the liquidity of assets themselves become important determinants of aggregate saving and investment. Yet they are largely ignored in today's standard business cycle models.
The project develops a novel framework that allows us to understand this nexus - a framework that examines business cycles, household portfolios, income risks, and asset liquidity together. This allows us to address a wide range of important macroeconomic questions of our time: how wealth inequality and stabilization policies interact; how monetary policy redistributes; how a housing bust can cause a recession as big as the last one; and why crises are particularly severe in times of high household debt.
To develop this framework, empirical and theoretical work goes hand in hand: First, we document the historical movements in the distribution of household (and corporate) portfolios to understand how and whose portfolio positions change over the cycle and in response to shocks. Second, we document the cyclical movements in asset liquidity. Third, we develop a theoretical framework that allows us to understand the implications of changes in asset liquidity in a setting of incomplete markets and nominal rigidities.
The project develops a novel framework that allows us to understand this nexus - a framework that examines business cycles, household portfolios, income risks, and asset liquidity together. This allows us to address a wide range of important macroeconomic questions of our time: how wealth inequality and stabilization policies interact; how monetary policy redistributes; how a housing bust can cause a recession as big as the last one; and why crises are particularly severe in times of high household debt.
To develop this framework, empirical and theoretical work goes hand in hand: First, we document the historical movements in the distribution of household (and corporate) portfolios to understand how and whose portfolio positions change over the cycle and in response to shocks. Second, we document the cyclical movements in asset liquidity. Third, we develop a theoretical framework that allows us to understand the implications of changes in asset liquidity in a setting of incomplete markets and nominal rigidities.
Initially, the work has focused on the project's methodological underpinnings. The primary challenge is modeling business cycles with heterogeneous households that differ along many dimensions. To address this issue, we devised a solution method [1] that enables a relatively quick solution of this class of models and their representation by a linear state-space model.
This methodological advancement, coupled with its continuous development, permitted us to estimate the model of a heterogeneous household economy with assets of different liquidity using Bayesian inference. The outcome of this endeavor has been two papers [2,3]. In the first one [2], we investigate the impact of business cycle shocks on income and wealth inequality. Our findings demonstrate that business cycle shocks account for a considerable proportion of the growth in wealth inequality, which is a variable that changes gradually over time. In the second one [3], we examine the impact of government bond issuance on return premiums of different assets and their feedback on aggregate fluctuations. We demonstrate that an increase in government debt raises returns of government debt in comparison to illiquid assets, in particular relative to housing returns. Part of the project resulted in the development of an open-source software package (written in Julia) to rapidly develop, solve, and estimate heterogeneous agent business cycle models. This tool has been widely adopted by other researchers and policy institutions. We used it also to analyze the effects of the US CARES act on stabilizing the US economy [4]. Expanding the framework to include endogenous bankruptcy decisions, Lisa Dähne and Lucas ter Steege have investigated the impact of fluctuations in uncertainty and policy shocks on consumer credit and their repercussions on the overall economy. The findings have been condensed in reference [5].
Regarding the element of the project that estimates high-frequency fluctuations in the distribution of household income and wealth, our team employed an approach similar to the one developed for model estimation. This involves a combination of Kalman filtering/smoothing and dimensionality reduction. The method starts by identifying the factors that describe the fluctuations of the distributions. The results obtained at the end of the funding period are promising and a working paper will be published soon. Both external and internal validity checks demonstrate that the estimated series is of excellent quality.
Just as households do, firms too encounter a portfolio choice problem. This problem involves making a decision on the liability side of the firm's balance sheet, which is the portfolio choice among various financing sources. The problem and its interaction with aggregate fluctuations have been examined by research studies [6] and [7]. The key theoretical advancement of this project is the creation of a dynamic model that encompasses production, financing, and costly default, whereby firms are given the option to choose between debts of differing maturities. This has aggregate repercussions that interact with monetary policy.
[1] Bayer, C. and R. Luetticke (2020): “Solving heterogeneous agent models in discrete time with many idiosyncratic states by perturbation methods”, Quantitative Economics, 2020, vol. 11, 1253-1288.
[2] Bayer, C., B. Born, and R. Luetticke (2023) “Schocks, Frictions, and Inequality in US Business Cycles”, conditionally accepted at American Economic Review.
[3] Bayer, C., B. Born, and R.Luetticke (2023) “The Liquidity Channel of Fiscal Policy”, Journal of Monetary Economics, 2023, vol.134 86-117.
[4] Bayer, C., B. Born, R.Luetticke and Gernot Müller (2023) “The Coronavirus Stimulus Package: How large is the transfer multiplier?”, Economic Journal, 2023, vol. 133, 1318–1347.
[5] Dähne, L. and L. terSteege (2021): "Destabilizing Effects of Consumer Bankruptcy”, p. 101-145, in Lucas terSteege (2021) "Essays on Inflation Expectations, Leaning Against the Wind Policy, and Consumer Bankruptcy", PhD thesis, University of Bonn.
[6] Jungherr, J. and I. Schott (2020): "Slow debt, deep recessions", American Economic Journal: Macroeconomics, Vol. 14(1), pp. 224-59
[7] Jungherr, J., M. Meier, T. Reinelt, and I. Schott (2022): "Corporate debt maturity matters for monetary policy", Revise & Resubmit: Review of Economic Studies
This methodological advancement, coupled with its continuous development, permitted us to estimate the model of a heterogeneous household economy with assets of different liquidity using Bayesian inference. The outcome of this endeavor has been two papers [2,3]. In the first one [2], we investigate the impact of business cycle shocks on income and wealth inequality. Our findings demonstrate that business cycle shocks account for a considerable proportion of the growth in wealth inequality, which is a variable that changes gradually over time. In the second one [3], we examine the impact of government bond issuance on return premiums of different assets and their feedback on aggregate fluctuations. We demonstrate that an increase in government debt raises returns of government debt in comparison to illiquid assets, in particular relative to housing returns. Part of the project resulted in the development of an open-source software package (written in Julia) to rapidly develop, solve, and estimate heterogeneous agent business cycle models. This tool has been widely adopted by other researchers and policy institutions. We used it also to analyze the effects of the US CARES act on stabilizing the US economy [4]. Expanding the framework to include endogenous bankruptcy decisions, Lisa Dähne and Lucas ter Steege have investigated the impact of fluctuations in uncertainty and policy shocks on consumer credit and their repercussions on the overall economy. The findings have been condensed in reference [5].
Regarding the element of the project that estimates high-frequency fluctuations in the distribution of household income and wealth, our team employed an approach similar to the one developed for model estimation. This involves a combination of Kalman filtering/smoothing and dimensionality reduction. The method starts by identifying the factors that describe the fluctuations of the distributions. The results obtained at the end of the funding period are promising and a working paper will be published soon. Both external and internal validity checks demonstrate that the estimated series is of excellent quality.
Just as households do, firms too encounter a portfolio choice problem. This problem involves making a decision on the liability side of the firm's balance sheet, which is the portfolio choice among various financing sources. The problem and its interaction with aggregate fluctuations have been examined by research studies [6] and [7]. The key theoretical advancement of this project is the creation of a dynamic model that encompasses production, financing, and costly default, whereby firms are given the option to choose between debts of differing maturities. This has aggregate repercussions that interact with monetary policy.
[1] Bayer, C. and R. Luetticke (2020): “Solving heterogeneous agent models in discrete time with many idiosyncratic states by perturbation methods”, Quantitative Economics, 2020, vol. 11, 1253-1288.
[2] Bayer, C., B. Born, and R. Luetticke (2023) “Schocks, Frictions, and Inequality in US Business Cycles”, conditionally accepted at American Economic Review.
[3] Bayer, C., B. Born, and R.Luetticke (2023) “The Liquidity Channel of Fiscal Policy”, Journal of Monetary Economics, 2023, vol.134 86-117.
[4] Bayer, C., B. Born, R.Luetticke and Gernot Müller (2023) “The Coronavirus Stimulus Package: How large is the transfer multiplier?”, Economic Journal, 2023, vol. 133, 1318–1347.
[5] Dähne, L. and L. terSteege (2021): "Destabilizing Effects of Consumer Bankruptcy”, p. 101-145, in Lucas terSteege (2021) "Essays on Inflation Expectations, Leaning Against the Wind Policy, and Consumer Bankruptcy", PhD thesis, University of Bonn.
[6] Jungherr, J. and I. Schott (2020): "Slow debt, deep recessions", American Economic Journal: Macroeconomics, Vol. 14(1), pp. 224-59
[7] Jungherr, J., M. Meier, T. Reinelt, and I. Schott (2022): "Corporate debt maturity matters for monetary policy", Revise & Resubmit: Review of Economic Studies
The methodology piece [1] and the two estimation papers [2,3] go substantially beyond what is state of the art. They have been published in or accepted for publication in leading journals and have already developed an impact on the field.
With respect to the project group’s work on firm-level debt portfolios, the main theoretical innovation of [4, 6,7] is to develop a dynamic model of production, financing, and costly default, in which firms are allowed to choose between the debt of different maturities. As explained above, this slow adjustment of firm debt amplifies and prolongs aggregate fluctuations. This opens up room for welfare-improving stabilization policies.
Finally, the part of the project, where we develop tools to study portfolio distributions of households and firms at business cycle frequency from mixed frequency data can be expected to enhance our understanding of the empirical distribution of household savings rates and firm investment sensitivities based on their portfolio of assets and liabilities. The final results of this development, however, will be made available only in the upcoming months.
With respect to the project group’s work on firm-level debt portfolios, the main theoretical innovation of [4, 6,7] is to develop a dynamic model of production, financing, and costly default, in which firms are allowed to choose between the debt of different maturities. As explained above, this slow adjustment of firm debt amplifies and prolongs aggregate fluctuations. This opens up room for welfare-improving stabilization policies.
Finally, the part of the project, where we develop tools to study portfolio distributions of households and firms at business cycle frequency from mixed frequency data can be expected to enhance our understanding of the empirical distribution of household savings rates and firm investment sensitivities based on their portfolio of assets and liabilities. The final results of this development, however, will be made available only in the upcoming months.