Income drops permanently after an involuntary job displacement, but it has never been clear what happens to long run wealth in the USA. Upon displacement, wealth falls 14% relative to workers of the same age and similar education from the Panel Study of Income Dynamics (PSID). Their wealth is still 18% lower 12 years after the event. A standard life cycle model calibrated to US data with permanent decreases in income after displacement behaves differently than these findings. The agents in the model also experience a large drop in wealth but they recover. The biggest culprit for these differences is small and statistically insignificant changes to consumption in the PSID whereas agents in the model decrease their consumption considerably. Extending the model to include habit formation reconciles some of these differences by generating similar long run effects on wealth. This allows for the examination of wealth at death through the lens of the model.

This paper presents a monetary stochastic general equilibrium model that allows the real cyclical movements of the economy to be explained as a consequence of exogenous monetary, public spending, and technology shocks. The model is calibrated and simulated, and its accuracy in replicating the cyclical movements in the real variables is compared with that of the standard real business cycle (RBC) model. We find that our model fits the observed data better than the existing RBC models, especially for the labor market.

This paper extracts housing boom-bust cycle signals from metropolitan statistical area (MSA)-level housing prices using a Markov-switching dynamic factor model. To mitigate the estimation bias, it utilizes high-frequency housing prices that follow the methodology of the monthly Case–Shiller house price indices. The housing bust phases specified from weekly and daily housing prices precede those based on monthly prices by approximately 2 years. MSAs with top signal-to-noise ratios offer greater marginal contributions to improvements in forecasting housing cycles than MSAs with bottom ratios for all frequencies. The results highlight the importance of indicator quality and provide evidence against “The more, the better” since incorporating more MSA-level housing prices into housing factors does not guarantee more satisfactory housing cycle forecasts.

This paper extends the ongoing literature on the macroeconomic effects of money supply volatility. We use monthly data for the USA and a bivariate, Markov switching, structural vector error correction model that is modified to accommodate generalized autoregressive conditional heteroscedasticity-in-mean errors to isolate the effects of money growth volatility on output growth. The model allows us to study how monetary uncertainty affects economic growth across different macroeconomic regimes.

In this paper I develop a dynamic stochastic general equilibrium model of credit frictions in which the production technology provides a U-shaped average cost curve, enabling endogenous solutions for firm size and quantity. Firms weigh the present value of future net revenues against the opportunity cost of staying in business in their entry or exit decisions. I find that credit frictions increase variable investment costs and result in a larger firm size and a smaller number of firms in the steady state. As the economy deviates from the steady state, however, the presence of credit frictions increases fluctuation in the number of firms, raising market entry during an economic upturn and market exit during a downturn. Also, I find that allowing free entry mitigates some of the effects of credit frictions due to macroeconomic fluctuations. In addition to the homogeneous-firm model, I examine the model when firms have heterogeneous access to credit and find that different credit access gives rise to different firm sizes in the steady state. Firms with easier access to credit become larger than those with less access to credit. Heterogeneous credit access also means that these two types of firms will respond differently to a common technology shock.

We present a new methodology that uses professional forecasts to estimate the effects of fiscal policy. We use short-term forecasts to better identify exogenous shocks to government spending by controlling for anticipatory information already in the public domain. We use longer-term forecasts to net out expectations from the future path of other variables, which improves accuracy and efficiency by focusing on more precise measures of the impact of shocks. We show that this improves the statistical fit relative to both local projection methods and vector autoregression-based analyses that do not control for the entire future path of expectations.

This paper proposes an unobserved-component approach to estimate expected returns on household assets and expected growth rates of excess consumption (consumption in excess of labor income) within a present-value model of consumption. The present-value model of consumption implies that the excess-consumption–assets ratio can be expressed as a function of the present discounted value of expected excess-consumption growth rate and expected asset returns. Because expected returns and expected excess-consumption growth rate are unobserved variables, we use an unobserved-component approach to extract them from the observed history of realized returns and excess-consumption growth rate. Our results suggest that both filtered returns and filtered excess-consumption growth rate are significant and better predictors of realized returns and realized excess-consumption growth rate than the one obtained by the lagged excess-consumption–assets ratio.

Taking Dutta and Kapur's study (Review of Economic Studies 65, 551–572, 1998) as a case of the Tobin effect, this note investigates the extent to which the Tobin effect persists with the addition of sophisticated financial instruments in incomplete markets. On one hand, after dynamic contracts are introduced to the fullest extent, money demand as a precautionary device is crowded out completely, and there is thus no room for the Tobin effect to persist. On the other hand, the Tobin effect may be strengthened under conditions of coexistence of fiat money and dynamic insurance contracts with limited transfers thanks to relaxed incentive compatibility conditions in a moderately inflationary environment.

This paper provides estimates of the probability of an economy hitting its effective lower bound (ELB) on the nominal interest rate and of the expected duration of such an event for eight advanced economies. To that end, a mean-adjusted panel vector autoregression with static interdependencies and the possibility of regime change is estimated. The simulation procedure produces ELB risk estimates for both the short term, where the current phase of the business cycle plays an important role, and the medium term, where the occurrence of an ELB situation is determined mainly by the equilibrium values of macroeconomic variables. The paper also discusses the ELB event probability estimates with respect to previous approaches used in the literature.

This paper studies the role of stochastic volatility in a setting where housing serves as an important propagation mechanism. After showing time-varying volatility in US house prices, we estimate a dynamic stochastic general equilibrium model with housing, financial frictions, and stochastic volatility using a nonlinear approximation and Bayesian econometric techniques. Incorporating stochastic volatility into the model greatly improves model fit and accounts for approximately half of the increased volatility in house prices observed during the Great Recession. Increased stochastic volatility escalates uncertainty which has significant effects on macroeconomic variables. While uncertainty in most sectors has negative effects on the economy, uncertainty on collateral constraints has the largest role. Unlike other uncertainty shocks, the housing demand uncertainty creates positive spillovers in the economy. Credit conditions, adjustment costs of capital and housing, and monetary policy are important transmission mechanisms for the stochastic volatility shocks.

This paper examines the consequences of international financial integration in a two-sector standard incomplete markets model with occupational choice under risk and financial constraints affecting entrepreneurial activity. We endogenize international productivity differences and discuss the implications of international integration for the macroeconomy, inequality, and welfare. Lending countries are characterized by tighter domestic constraints and experience an increase in gross national product, whereas the gross domestic product effect is ambiguous. We conclude that international integration is beneficial only for economies where there are substantial financial constraints on entrepreneurial activity. Otherwise, a majority of households suffer, due to the unequal distribution of welfare gains and losses across the heterogeneous population.

This paper studies the dynamic interactions between the money supply and the shape of the yield curve in the context of a regime-switching latent factor model. Estimates show that the money supply has important implications for the level, slope, and curvature of the yield curve. Moreover, the Divisia aggregates can provide more information than simple-sum aggregates based on parameter estimates and impulse response functions in understanding the dynamics of the yield curve. The favored broad Divisia aggregate could especially be associated with changes in the yield curve’s level, slope, and curvature over the business cycle. Therefore, this paper highlights the important role of Divisia aggregates in the linkage between financial markets and monetary policy.

Economists have long been interested in the effect of business sentiment on economic activity. Using text analysis, I construct a new company-level indicator of sentiment based on the net balance of positive and negative words in Australian company disclosures. Company-level investment is very sensitive to changes in this corporate sentiment indicator, even controlling for fundamentals, such as Tobin’s Q, as well as controlling for measures of company-level uncertainty.

The high sensitivity of investment to sentiment could be due to several mechanisms. It could be because of animal spirits among managers or because of sentiment proxies for private information held by managers about company prospects. Overall, I find mixed evidence of the underlying causal mechanism. The effect of sentiment on investment is relatively persistent, which is consistent with managers having private information about company fundamentals. But the sensitivity of investment to sentiment is not any stronger at opaque companies in which managers are likely to be better informed than investors. Further, investment is sensitive to sentiment even when investors have an information advantage over managers by lagging the sentiment indicator by a year. Overall, the sensitivity of investment to sentiment appears to reflect both animal spirits and fundamentals.

Corporate investment has been weak since the global financial crisis (GFC) and demand-side factors, such as lower sales growth, explain more than half of this weakness. Low sentiment and heightened uncertainty weighed on investment during the GFC but have been less important factors since then.