Standard Dynamic Stochastic General Equilibrium Research Articles

ASSET‐MARKET SENTIMENTS AND BUSINESS CYCLE FLUCTUATIONS

AbstractWe present a tractable model that accommodates asset‐market sentiment in a standard Dynamic Stochastic General Equilibrium (DSGE) setting, allowing us to quantitatively evaluate sentiment‐driven macroeconomic fluctuations. In our model, changes in households' perceived uncertainty about housing prices lead to self‐fulfilling fluctuations in housing prices, which then impact investment and output through entrepreneurs' collateral constraints. Household sentiment shocks hence are transmitted and propagated to the macroeconomy, generating boom–bust cycles. Uncertainty, housing prices, and the real economy are linked. Quantitatively, the sentiment shock in the form of risk–panic is a crucial driver of business cycle fluctuations despite the presence of various competing shocks.

DSGE on the metaverse

This paper explores the economic dynamics of the metaverse by using on-chain data of token holdings from a blockchain game. We use the New Keynesian Dynamic Stochastic General Equilibrium (DSGE) model to examine the token inflation of the metaverse economy. We extend the standard DSGE models with in-game cryptocurrency to capture the demand and supply of NFTs assets. We compare the responses to tokenomic shocks that drive the metaverse economy. This paper is the first to use on-chain token holding data and DSGE models to study the metaverse economy.

The Forward Guidance Puzzle

This paper argues that standard dynamic stochastic general equilibrium models grossly overestimate the impact of forward guidance on the macroeconomy, a phenomenon we call the “forward guidance puzzle.” Using data from a panel of Blue Chip survey expectations, we show that accommodative forward guidance had effects on output and inflation expectations that were positive and nontrivial, but still 28 and 8 times smaller, respectively, than implied by standard models. We show that incorporating a perpetual youth structure into the benchmark provides one possible resolution to the puzzle.

Consumption tax and productive government expenditure in DSGE model

Our article presents a dynamic stochastic general equilibrium (DSGE) model to derive effects of a consumption tax rate increase. In the DSGE model, money and inflation are examined to elucidate the transitional path of policy. Results of a consumption tax rate increase are intuitive: GDP declines because of lower aggregate consumption. With a consumption tax rate increase, we consider the productive government expenditure model. In the standard DSGE model, the production function comprises inputs of capital stock and labor. Policy can change the capital stock and labor inputs to alter the production level. However, the production level can be changed by other policies. For instance, increased public investment in infrastructure by government can change the production level. After setting the DSGE model with productive government expenditure, we attempt derivation of a result. We consider the case in which additional productive government expenditure is financed by a consumption tax. In this case, compared with the case of a consumption tax increase without productive government expenditure, GDP increases even if the consumption tax rate is raised. An increase in productive government expenditure increases marginal labor productivity, thereby raising the wage rate. Consequently, by virtue of a raised wage rate, consumption can increase even if the consumption tax negatively affects aggregate consumption.

Heterogeneous stock traders, endogenous bubbles, and economic fluctuations

The impact of stock market bubbles on the real economy has always been an important topic. By introducing heterogeneous transactions of behavioral economics into a standard dynamic stochastic general equilibrium (DSGE) model, this paper finds, first, that heterogeneous trading behaviors cause an endogenous stock bubble. Second, the endogenous inverted U-shaped bubble affects the real economy through the borrowing constraint channel, which causes an inverted U-shaped output and promotes the output to rise against the decline of the total factor productivity (TFP) shock. Third, the positive bubble and increasing bubble dominate in promoting the output and investment of the real economy.

Equity home bias and consumption-real exchange rate puzzles: A joint solution

In a standard dynamic stochastic general equilibrium model with a complete asset market, home agents should hold a foreign equity biased portfolio to hedge the non-traded labor income risk, which contradicts home equity biased portfolios observed worldwide. As the labor income share increases, the degree of home bias should decrease because there is more incentive to hold foreign equity. In the data, there is not any evidence that the labor income share and the degree of home bias are negatively correlated. The standard model also predicts that the consumption differential-real exchange rate correlation is positive, while it is negative in the data. I show that a combination of market incompleteness, non-tradable goods, and labor supply can explain the three features above. My model can generate a large equity home bias, despite the strong positive correlation of non-traded human capital return with domestic equity return. The home bias is not sensitive to the labor income share. The consumption differential-real exchange rate unconditional correlation generated by my model simulation is zero.

Does social capital explain the Solow residual? A DSGE approach

Social capital plays a role in many desirable economic outcomes. We analyze how these beneficial effects translate into the performance of economies by developing a dynamic stochastic general equilibrium (DSGE) model featuring the role of social capital in explaining the Solow residual. We then simulate and estimate the model with Bayesian techniques using Italian data. Our framework fits actual data better than a standard DSGE model, suggesting that social capital may improve the economic performance via its impact on total factor productivity. Including human capital in the model further raises social capital’s ability to explain the Solow residual.

Frictions and empirical fit in a DSGE model for Indonesia

I build a small-scale dynamic stochastic general equilibrium (DSGE) model for Indonesia and assess which structural features of the model are consistent with actual data. I show that the best-fitting model does not include habit formation or backward-looking price indexation, which are widely assumed features in standard DSGE models. Money-holding friction, however, is found to be an important feature. When these features are assumed to be present, I find that the degrees of habit formation and price indexation decline after full-fledged adoption of the inflation targeting framework in Indonesia. This implies that agents of the economy believe that Bank Indonesia’s monetary policy is credible in achieving its inflation target. When using a large-scale DSGE model for policy analysis, central banks must evaluate which frictions should be included.

Understanding the effects of government spending in a time-inconsistent model

This paper examines the effects of government spending shock in a model that features time inconsistency. We build a time-inconsistency edifice on a standard dynamic stochastic general equilibrium (DSGE) model to explore dynamic behavior of macroeconomic aggregates and present-value multipliers. Comparison of the results from a time-inconsistent model (TIM) and a time-consistent model (TCM) reveals that two models deliver markedly different dynamic responses and multiplier effects. A positive government spending shock in TIM delivers a larger decrease in consumption, a smaller decrease in investment and a larger increase in labor and output than TCM. Impact and long-run fiscal multipliers for output in TIM are around 0.28 and 0.01, respectively, which are larger than those in TCM (0.13 and −0.23). The larger multipliers result from the sophistication effect formed by an individual’s perception of their future selves’ behavior. Various sensitivity analyses on important parameters do not reverse the baseline result.

Multiperiod Loans, Occasionally Binding Constraints, and Monetary Policy: A Quantitative Evaluation

AbstractWe introduce multiperiod mortgage loans, fixed interest rate, a lower bound constraint on newly granted loans, and a possibly slack collateral constraint, in an otherwise standard Dynamic Stochastic General Equilibrium (DSGE) model with housing. Our nonlinear estimation shows that all those features are important to understand the evolution of mortgage debt during the recent U.S. housing market boom and bust. The transmission of monetary policy becomes dependent on the housing cycle, with weaker effects when house prices are high or start falling sharply. Higher average loan duration makes monetary policy less effective, eventually leading to asymmetric responses to positive and negative monetary shocks.

Technology Shocks and Non-stationary Hours in Emerging Countries and DSVAR

We test a standard DSGE (Dynamic Stochastic General Equilibrium) model on impulse responses of hours worked and real GDP after technology and non-technology shocks in emerging market economies (EMEs). Most dynamic macroeconomic models assume that hours worked are stationary. However, in the data, we observe apparent changes in hours worked from 1970 to 2013 in these economies. Motivated by this fact, we first estimate a structural vector autoregression (SVAR) model with a specification of hours in difference (DSVAR) and then set up a DSGE model by incorporating permanent labour supply (LS) shocks that can generate a unit root in hours worked, while preserving the property of a balanced growth path. These LS shocks could be associated with very dramatic changes in LS which look permanent in these economies. Hence, the identification restriction in our models comes from the fact that both technology and LS shocks have a permanent effect on GDP yet only the latter shocks have a long-run impact on hours worked. For inference purposes, we compare empirical impulse responses based on the EMEs data to impulse responses from DSVARs run on the simulated data from the model. The results show that a DSGE model with permanent LS shocks that can generate a unit root in hours worked is required to properly evaluate the DSVAR in EMEs as this model is able to replicate indirectly impulse responses obtained from a DSVAR on the actual data. JEL Classification: C32, E32

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THE CONDITIONAL INS AND OUTS OF FRENCH UNEMPLOYMENT

In this paper, I investigate the conditional contributions of the ins and outs of unemployment from both empirical and theoretical perspectives. Based on a New Keynesian Dynamic Stochastic General Equilibrium (DSGE) theoretical framework, I estimate a sign restriction Vector Auto Regressive (VAR) model using French data. To identify the origins of unemployment dynamics in terms of worker transition rates, I simulate two shocks: one on the supply side (technology) and the other on the demand side (monetary). The VAR model reveals that the contributions of transition rates in explaining unemployment differ across shocks. After a technology shock, unemployment fluctuations are mainly explained by the job finding process, while the contributions of the two margins are more balanced for the monetary shock. The theoretical model is not able to reproduce the underlying mechanisms inducing unemployment. In particular, the conditional contributions of the job separation margin are overestimated each time. For instance, after a technology shock, 60% of unemployment changes are generated by this margin, while the data suggest a contribution of 28%. This paper strongly indicates that, in its standard formulation, a search and matching DSGE model featuring endogenous job separations is not able to replicate the dominating influence of the outflow process.

Credit Misallocation, Endogenous TFP Changes, and Economic Fluctuation in China

ABSTRACTIn 2009, to cope with the economic slowdown China initiated a large-scale stimulus mainly in the form of bank credit that favored the state-owned sector. Data shows that during the policy easing episodes the credits allocated to the private enterprises (PE) are crowded out by the state-owned enterprises (SOE). I then incorporate SOE and PE into a standard dynamic stochastic general equilibrium (DSGE) model without imposing any ex ante asymmetry to the two sectors. The calibration exercise reveals two findings from a static view: (i) while on average the leverage of SOE is close to that of PE, the credit constraint is much smaller for SOE than PE, consistent with the well accepted views; (ii) the credit misallocation exists in the sense that by deleveraging the SOE can lead to aggregate efficiency gains. On the dynamic side, however, numerical simulations indicate that endogenous TFP changes brought about by the asymmetric credit shocks that are consistent with the data are in fact quantitatively unimportant to economic fluctuations.

How Many Agents are Rational in China’s Economy? Evidence from a Heterogeneous Agent-Based New Keynesian Model

A new Keynesian model built on an agent-based approach is considered and employed to investigate China’s monetary policy and macroeconomic fluctuations. The assumption of perfect rationality used in standard dynamic stochastic general equilibrium (DSGE) models is abandoned. The expectation’s heterogeneity, caused by agents behaving according to individual rules through adaptive learning, is one of the agent-based model (ABM) characteristics inserted into the DSGE model. Differential evolution (DE) algorithm is employed to estimate the parameters of an agent-based new Keynesian (ABNK) model, which combined the ABM and the new Keynesian DSGE models. The primary contribution of this study is that the degree of rationality in the economy has been estimated using a model with heterogeneous bounded rationality and adaptive learning. In addition, the determinacy properties of ABNK models with different degrees of heterogeneity are analyzed, which shows that the models that are determinate under the assumptions of rationality may become indeterminate in the presence of heterogeneous expectations.

Quasi‐Bayesian Estimation of Time‐Varying Volatility in DSGE Models

We propose a novel quasi‐Bayesian Metropolis‐within‐Gibbs algorithm that can be used to estimate drifts in the shock volatilities of a linearized dynamic stochastic general equilibrium (DSGE) model. The resulting volatility estimates differ from the existing approaches in two ways. First, the time variation enters non‐parametrically, so that our approach ensures consistent estimation in a wide class of processes, thereby eliminating the need to specify the volatility law of motion and alleviating the risk of invalid inference due to mis‐specification. Second, the conditional quasi‐posterior of the drifting volatilities is available in closed form, which makes inference straightforward and simplifies existing algorithms. We apply our estimation procedure to a standard DSGE model and find that the estimated volatility paths are smoother compared to alternative stochastic volatility estimates. Moreover, we demonstrate that our procedure can deliver statistically significant improvements to the density forecasts of the DSGE model compared to alternative methods.

Real-time forecast evaluation of DSGE models with stochastic volatility

Recent work has analyzed the forecasting performance of standard dynamic stochastic general equilibrium (DSGE) models, but little attention has been given to DSGE models that incorporate nonlinearities in exogenous driving processes. Against that background,we explore whether incorporating stochastic volatility improves DSGE forecasts (point, interval, and density). We examine real-time forecast accuracy for key macroeconomic variables including output growth, inflation, and the policy rate. We find that incorporating stochastic volatility in DSGE models of macroeconomic fundamentals markedly improves their density forecasts, just as incorporating stochastic volatility in models of financial asset returns improves their density forecasts.

The effects of the near-zero interest rate policy in a regime-switching dynamic stochastic general equilibrium model

Standard Dynamic Stochastic General Equilibrium (DSGE) models cannot explain the near-zero interest rate policy (near-ZIRP) by the Federal Reserve. I study two methods of modeling the near-ZIRP in DSGE models: the perfect foresight model and the Markov regime-switching model developed in this paper. The near-ZIRP has a significant expansionary effect, and the regime-switching model generates a more realistic predicted path of macro variables than the perfect foresight model. Furthermore, the government purchases multiplier in the near-ZIRP regime is smaller than what the literature finds at the zero lower bound (ZLB), and the contractionary effects of higher productivity found by the recent literature at the ZLB are not present in the regime-switching model.

Should the Federal Reserve Pay Competitive Interest on Reserves?

In 2008, the Federal Reserve began paying interest on reserves. How should the Fed use this new policy instrument? As the Fed reduces its balance sheet, should it continue to satiate reserve demand and pay competitive interest on reserves? Here, we argue that this may be an inefficient use of the new policy instrument. Using a standard Dynamic Stochastic General Equilibrium model (DSGE), augmented to include a banking sector and an interbank market, our benchmark calibration implies an optimal tax on reserves of about 20 to 40 basis points in the steady state, and a fluctuating tax rate in response to shocks.

What Drives the Owner‐Occupied and Rental Housing Markets? Evidence from an Estimated DSGE Model

Most dynamic stochastic general equilibrium (DSGE) models with a housing market do not explicitly include a rental market and assume a tight mapping between house prices and rents over the business cycle. However, rents are much smoother than house prices in the data. We match this feature of the data by adding both an owner‐occupied housing market and a rental market in a standard DSGE model. The intertemporal preference shock accounts for more than half of the variation in house prices and contributes to residential investment fluctuations through the liquidity constraint, and nominal rigidity in rental contracts captures the variation in the price‐rent ratio.