Journal of Economic Dynamics & Control最新文献

We evaluate the empirical performance of financial frictions à la Bernanke et al. (1999) during and after the Global Financial Crisis. We document that in an ex-post analysis based on nonlinear Bayesian methods, these frictions do not improve the standard medium-scale DSGE model's ability to explain the macroeconomic dynamics during the Great Recession. The reason is that in the estimated model with financial frictions, the drastic post-2008 collapse of investment causes firms' leverage to decline. Taking the model at face value, this would trigger a narrowing of the credit spread, contradicting the observed persistently large credit spread throughout the post-2008 period. Additionally, the estimated model attributes only a minor role to risk shocks à la Christiano et al. (2014). These findings are confirmed independently for US and euro area data.

Utilizing insights from financial literature and empirical financial data, we introduce a comprehensive system of factor models designed to capture both return and risk dynamics. Our focus extends to addressing the multi-period mean-variance portfolio selection challenge within the framework of these proposed factor models. Through rigorous analysis, we formulate a semi-analytical optimal portfolio policy, characterized by a linear relationship with the current wealth level. The coefficients of this optimal policy are intricately linked to a specific stochastic process known as the future investment opportunity (FIO), reflecting the investor's anticipation of future investment prospects. Furthermore, empirical examination within the U.S. market context underscores the efficacy of our approach. By incorporating the factor models for return and risk, our optimal portfolio policy exhibits superior out-of-sample Sharpe ratio compared to benchmark policies.

An agent often considers retirement adequacy when making a retirement decision. This paper introduces a target wealth constraint, where financial wealth must exceed an agent-based threshold for retirement, and studies several early retirement models under such a constraint. We present explicit characterizations of the optimal retirement time and demonstrate the influence of the target wealth on the early retirement decision and the consumption-investment strategy. As the target wealth for retirement increases, the agent will increase consumption, decrease investment in the risky asset, and delay the retirement time. Due to the early retirement effect, the proportion of financial wealth invested in risky assets could increase when the financial wealth approaches the target wealth. Our models demonstrate that retirement adequacy is a crucial factor in early retirement decisions.

I solve for the sequences of shocks (or wedges) that allow a standard real business cycle model to exactly replicate the quarterly time paths of U.S. macroeconomic variables and asset returns since 1960. The resulting shock sequences can be grouped into three main categories: (1) shocks that affect household sentiment and preferences, (2) shocks that appear in the law of motion for capital, and (3) shocks that appear in the production function for output. For most variables including output, no single shock category is clearly dominant in explaining the observed movements in U.S. data. While some variables are driven by a single dominant shock category, the dominant category is different for each of those variables. The results imply that there is no “most important shock.” Rather, U.S. economic outcomes have been shaped by a complex and time-varying mixture of fundamental and non-fundamental disturbances.

We develop and estimate a consumption-based asset pricing model that uses historical US financial data and assumes recursive utility, allowing for priced regime-switching risk and intrinsic bubbles. We also estimate several restricted versions, including only a subset of these features. Priced regime-switching risk is essential to the equity risk premium, explaining more than fifty per cent of it. Furthermore, a model that does not consider regime switching would overestimate the public's risk aversion, mistakenly assigning the observed risk premium to high-risk aversion instead of priced regime-switching. We also find that intrinsic bubbles are statistically significant, and even though they are not crucial in explaining the risk premium, they substantially improve the model's fit at the end of the sample.

Nonparametric additive models are garnering increasing attention in applied research across fields like statistics and economics, attributed to their distinct interpretability, versatility, and their adeptness at addressing the curse of dimensionality. This paper introduces a novel and efficient fully Bayesian method for estimating nonparametric additive models, employing a band matrix smoothness prior. Our methodology leverages unobserved binary indicator parameters, promoting linearity in each additive component while allowing for deviations from it. We validate the efficacy of our approach through experiments on synthetic data derived from ten-component additive models, encompassing diverse configurations of linear, nonlinear, and zero function components. Additionally, the robustness of our algorithm is tested on high-dimensional models featuring up to one hundred components, and models correlated components. The practical utility and computational efficiency of our technique are further underscored by its application to two real-world datasets, showcasing its broad applicability and effectiveness in various scenarios.

Firms borrow against earnings more than they do against their assets. How does this affect the aggregate response to financial crises? I take a dynamic stochastic general equilibrium model of heterogeneous firms that choose their capital and debt subject to a borrowing constraint and examine the recovery from a financial crisis when firms can use different types of collateral. I compare between two collateral types: assets, and earnings. I find that when firms borrow against earnings recessions are deeper, but recoveries are quicker compared to when firms borrow against assets. I also find that neither type of collateral can, by itself, completely explain the recovery from the Great Recession. Instead, the path of investment after the 2007-2008 Financial crisis is better captured by firms borrowing against earnings than by firms borrowing against assets, but this is reversed when looking at the path of output. This suggests that a combination of collateral types is required to fully capture the recovery from the Great Recession.

I develop a general equilibrium model of trade and horizontal multinational firms with firm heterogeneity and parent-to-affiliate technology transfer to evaluate how multinationals affect international business cycles. When calibrated to match micro and macro features of the United States, the impact of multinational firms crucially depends on the labor supply elasticity and the technology transfer parameter. Surprisingly, with standard (elastic) labor supply, multinationals lead to lower international correlations and higher macroeconomic volatility. A novel mechanism – procyclical exit of multinational firms – drives these results. The results are overturned only when inelastic labor supply and a high level of technology transfer are implemented together. Using novel bilateral data on the number and sales of multinational affiliates, I find evidence that the key model mechanism, i.e., entry and exit by multinationals, increases international output correlation.

Balance sheet policy is now a prominent facet of monetary policy. Based on the U.S. experience between 2017 and 2019, Smith and Valcarcel (2023) show the first period of quantitative tightening (QT1) was markedly different from earlier balance sheet expansions. This paper provides evidence the Federal Reserve's second balance sheet unwind effort that began in January 2022 (QT2) is strikingly different from QT1. We find substantial announcement effects during QT2 for various treasury yields and interest rate spreads, which are largely absent from QT1. At the time of this writing—by February 2023—both episodes have experienced a similar percent reduction in reserve balances. Yet, QT2 shows a stronger market response upon implementation. Not only are the underlying financial conditions different across the two periods, but the conduct of monetary policy in 2022 seems to be different as well. A clearer signaling mechanism for the expectations channel of monetary transmission takes place during QT2 than was apparent during QT1. The liquidity effects that seemed to be so important during QT1 have been largely attenuated during the second episode of balance sheet tightening.

This paper studies how the China shock affects unemployment rates and wage inequality across high-skilled and low-skilled workers in the United States, with particular emphasis on the dynamic and general equilibrium channels of firms' production locations and entry decisions. To shed light on the subject, I build a two-country trade-in-task model with firm heterogeneity, search-and-matching labor market frictions, and firms' endogenous selections into entry and offshoring. The model, consistent with evidence from vector autoregression analyses, uncovers important dynamics with implications for the impact of the China shock on U.S. worker inequality. Namely, it shows association between a decrease in offshoring costs and a short-lived increase in low-skilled unemployment in the source country, a longer-term decline in high-skilled unemployment, a transient expansion of the wage gap between high- and low-skilled workers, and an increase in firm entry.