Standard Real Business Cycle Model Research Articles

The Interaction between Credit Constraints and Uncertainty Shocks

AbstractThis paper proposes a novel link between credit markets and uncertainty shocks. We introduce a role for credit uncertainty via collateral constraints in an otherwise standard real business cycle (RBC) model and show that an increase in credit uncertainty triggers a precautionary response that interacts with the collateral constraint to generate a simultaneous decline in output, consumption, investment, real wages, and hours; a feature that previous work on uncertainty shocks without credit constraints is unable to produce in a flexible‐price environment. We also empirically test the theoretical predictions and show that an unforeseen increase in credit uncertainty generates a simultaneous decline in a broad measure of real activity in recessions.

Endogenous Uncertainty and Credit Crunches

Abstract We develop a theory of endogenous uncertainty in which the ability of investors to learn about firm-level fundamentals is impaired during financial crises. At the same time, higher uncertainty reinforces financial distress. Through this two-way feedback loop, a temporary financial shock can cause a persistent reduction in risky lending, output, and employment that coincides with increased uncertainty, default rates, credit spreads, and disagreement among forecasters. We embed our mechanism into standard real business cycle and New-Keynesian models and show how it generates endogenous and internally persistent processes for the efficiency and labour wedges.

Sentiments and real business cycles

We introduce sentiments under incomplete information in an otherwise standard real business cycle model. Individual firms receive signals about their idiosyncratic demand shocks, which are confounded by sentiments. Sentiments coordinate the optimal decisions of individual firms through their extraction of aggregate economic conditions from the signals. We show that there exists a sentiment-driven rational expectations equilibrium, in addition to a fundamental equilibrium. Optimism stimulates the aggregate economy, leading to positive comovements between output, consumption, investment, and hours worked. We calibrate a full-fledged dynamic stochastic general equilibrium model based on U.S. aggregate data and find that sentiment shocks substantially amplify aggregate fluctuations and contribute to real business cycles.

Polynomial Chaos Expansion Efficient Evaluation and Estimation of Computational Models

Polynomial chaos expansion (PCE) provides a method that enables the user to represent a quantity of interest (QoI) of a model's solution as a series expansion of uncertain model inputs, usually its parameters. Among the QoIs are the policy function, the second moments of observables, or the posterior kernel. Hence, PCE sidesteps the repeated and time consuming evaluations of the model's outcomes. The paper discusses the suitability of PCE for computational economics. We, therefore, introduce to the theory behind PCE, analyze the convergence behavior for different elements of the solution of the standard real business cycle model as illustrative example, and check the accuracy, if standard empirical methods are applied. The results are promising, both in terms of accuracy and efficiency.

An RBC model with Epstein-Zin (non-expected-utility) recursive preferences: lessons from Bulgaria (1999-2018)


 
 
 We introduce Epstein-Zin (1989, 1991) preferences into a real-business-cycle (RBC) model with government. We calibrate the model economy to Bulgarian data for the period after the currency board regime (1999-2018). We evaluate the quantitative importance of the presence of ”early resolution of uncertainty” motive for the propagation of cyclical fluctuations in Bulgaria. Allowing for Epstein-Zin preferences improves the model performance against data, and in addition this extended setup dominates the standard RBC model framework, e.g., Vasilev (2009).
 
 

LABOR MARKET DYNAMICS UNDER TECHNOLOGY SHOCKS: THE ROLE OF SUBSISTENCE CONSUMPTION

This paper establishes new stylized facts about labor market dynamics in developing economies, which are distinct from those in advanced economies, and then proposes a simple model to explain them. We first show that the response of hours worked and employment to a technology shock—identified by a structural VAR model with either short-run or long-run restrictions—is substantially smaller in developing economies. We then present compelling empirical evidence that several structural factors related to the relevance of subsistence consumption across countries can jointly account for the relative volatility of employment to output and that of consumption to output. We argue that a standard real business cycle (RBC) model augmented with subsistence consumption can explain the several salient features of business cycle fluctuations in developing economies, especially their distinct labor market dynamics under technology shocks.

Exchange Rate Disconnect in General Equilibrium

We propose a dynamic general equilibrium model of exchange rate determination that accounts for all major exchange rate puzzles, including Meese-Rogoff, Backus-Smith, purchasing power parity, and uncovered interest rate parity puzzles. We build on a standard international real business cycle model with home bias in consumption, augmented with shocks in the financial market that result in a volatile near-martingale behavior of exchange rates and ensure their empirically relevant comovement with macroeconomic variables, both nominal and real. Combining financial shocks with conventional productivity and monetary shocks allows the model to reproduce the exchange rate disconnect properties without compromising the fit of the business cycle moments.

PROGRESSIVE TAXATION AND MACROECONOMICS (IN)STABILITY UNDER HOUSEHOLD HETEROGENEITY

It has been shown that progressive income taxation may stabilize an otherwise standard representative-agent real business cycle model with an indeterminate steady state against aggregate fluctuations caused by agents’ animal spirits. By contrast, within an identical model that allows for sustained economic growth, progressive taxation could lead to equilibrium indeterminacy and sunspot-driven fluctuations. In the context of household heterogeneity that gives rise to income and asset inequality, the fiscal authority has (at least) two options of setting the baseline level of taxable income: (i) the economy-wide average level of income and (ii) the economy’s steady-state level of per capita income. I show that the adoption of a fiscal rule (i) invalidates the effects that a progressive tax can exert on the model’s local stability properties. Progressive income taxation thus no longer operates as an automatic stabilizer that mitigates belief-driven cyclical fluctuations in a no-growth economy, nor as an automatic destabilizer that leads to local indeterminacy in a sustained-growth economy. If a tax policy rule (ii) is instead adopted, then the existing literature’s findings of the (de)stabilizing roles of progressive taxation are robust to the inclusion of household heterogeneity.

Property rights, expropriations, and business cycles in China

Real business cycles in China are different than in many other countries, including consumption being more volatile than output and uncorrelated with investment. To study whether Chinese institutions can account for these features, we augment the standard real business cycle model by private and state-owned enterprises facing time-to-build constraints, expropriations, and government expenditures. We introduce shocks to each of these activities and estimate our model with Bayesian techniques. The model matches the salient data moments quite closely, with expropriations playing a central role. In particular, shocks to expropriations account for over 70% of consumption and output volatility, and over 60% of private investment volatility. To assess whether our estimated expropriations are empirically plausible, we show that: (i) the model-generated expropriation series is positively correlated with a commonly used measure of property rights; (ii) the explanatory power of expropriations drops considerably after 2012, coinciding with the government’s anti-corruption campaign; and (iii) a placebo test estimating the model for the U.S. finds expropriations to be about one eighth of those in China, and to account for only a small share of the U.S. aggregate fluctuations.

Sentiments and Real Business Cycles

We introduce sentiments under incomplete information into an otherwise standard real business cycle model. Individual firms receive signals about their idiosyncratic demand shocks which are confounded by sentiments. Sentiments coordinate optimal decisions of individuals through their extraction of the aggregate economic conditions from the signals. We show that there exists a sentiment-driven rational expectations equilibrium in addition to a fundamental equilibrium. Optimistic sentiments boost the aggregate economy, leading to positive comovements among output, consumption, investment, and hours worked. We calibrate a full-blown dynamic stochastic general equilibrium model based on U.S. aggregate data and find that sentiment shocks substantially amplify the aggregate fluctuations.

Common Trade Exposure and Business Cycle Comovement

A large empirical literature has shown that countries that trade more with each other have more correlated business cycles. We show that previous estimates of this relationship are biased upward because they ignore common trade exposure to other countries. When we account for common trade exposure to foreign business cycles, we find that (1) the effect of bilateral trade on business cycle comovement falls by roughly 25 percent and (2) common exposure is a significant driver of business cycle comovement. A standard international real business cycle model is qualitatively consistent with these facts but fails to reproduce their magnitudes. Past studies have used models that allow for productivity shock transmission through trade to strengthen the relationship between trade and comovement. We find that productivity shock transmission increases business cycle comovement largely because of a country-pair's common trade exposure to other countries rather than because of bilateral trade. When we allow for stronger transmission between small open economies than other country-pairs, comovement increases both from bilateral trade and common exposure, similar to the data.

Endogenous business cycles with financial frictions

ABSTRACT This paper uncovers a series of belief shocks that drive the U.S. economy from both financial markets data and a financial accelerator model with self-fulfiling prophecies. Indeterminacy in the economy does not require externalities or increasing returns in production but it arises from an endogenous and countercyclical markup channel. The computed belief shocks are well identified and resemble the observable proxy in the real world. The model-driven solely by belief shocks performs well on replicating major U.S. business cycle facts. The belief-driven model contains a strong internal propagation mechanism and has more forecasting ability than a standard real business cycle model disturbed by technology shocks.

Property Rights, Expropriations, and Business Cycles in China

Real business cycles in China are different than in many other countries, including consumption being more volatile than output and uncorrelated with investment. To study whether Chinese institutions can account for these features, we expand the standard real business cycle model with private and state-owned enterprises facing time-to-build constraints, expropriations, and government expenditures. We introduce shocks to each of these activities and estimate our model with Bayesian techniques. The model matches the salient data moments quite closely, with expropriations playing a central role. In particular, shocks to expropriations account for over 70% of consumption and output volatility, and over 60% of private investment volatility. To assess whether our estimated expropriations are empirically plausible, we show that: (i) the model-generated expropriation series is highly correlated with a commonly used measure of property rights; (ii) the explanatory power of expropriations drops considerably after 2012, coinciding with the government's anti-corruption campaign; and (iii) a placebo test estimating the model for the U.S. finds expropriations to be about an eight of those in China, and to account for only a small share of the U.S. aggregate fluctuations.

IDENTIFYING TECHNOLOGY SHOCKS AT THE BUSINESS CYCLE VIA SPECTRAL VARIANCE DECOMPOSITIONS

In this paper, we identify the technology shock at business cycle frequencies to improve the performance of structural vector autoregression models in small samples. To this end, we propose a new identification method based on the spectral decomposition of the variance, which targets the contributions of the shock in theoretical models. Results from a Monte-Carlo assessment show that the proposed method can deliver a precise estimate of the response of hours in small samples. We illustrate the application of our methodology using US data and a standard Real Business Cycle model. We find a positive response of hours in the short run following a non-significant, near-zero impact. This result is robust to a large set of credible parameterizations of the theoretical model.

Speculation-Driven Business Cycles

Speculation, in the spirit of Harrison and Kreps [1978], is introduced into a standard real business cycle model. Investors (speculators) hold heterogeneous beliefs about firm growth. Firm ownership, and thus, the firm’s discount factor varies with waves of optimism and leverage. These waves ripple into firm investments in hours. The firm’s discount discount factor links the equity premium and labor volatility puzzles. We obtain an upper bound to the amplification that can be generated by speculation for any model of beliefs -- a factor of 1.5. A calibration based on diagnostic beliefs amplifies hours volatility by a factor of 1.15 and produces a bubble component of 20 percent.

Aggregate Hours and Local Projections with Long-Run Restrictions

I extend the local projections method to identify structural shocks using long-run restrictions. I show that the proposed estimator is substantially more robust than structural VARs (SVARs) to both the choice of lag length and the order of integration of the endogenous variables using data from a standard real business cycle (RBC) model. Benchmark simulations show that the proposed estimator can yield substantial reductions in both the bias and mean squared error of estimated impulse response functions relative to SVARs, particularly at short forecast horizons. In all cases, the proposed estimator correctly estimates the direction of the contemporaneous response and the shape of the full impulse response function, and can eliminate virtually all of the bias for some specification choices. Using my proposed estimator and data obtained from the Bureau of Labor Statistics, I then estimate the response of aggregate labor hours to productivity shocks. In contrast to much of the evidence based on SVARs, I find that labor hours rise in response to positive productivity shocks and subsequently follow a hump shaped profile. This result is robust to a number of specification choices and provides new evidence in support of the standard RBC model.

Noisy information, risk sharing, and international business cycles

AbstractWe introduce a noisy information structure into an otherwise standard international real business cycle model with two countries. When domestic firms observe current foreign technology with some noise, predictions of the model on international correlation can be very different from those of a standard perfect information model. We show that the model can explain: (a) positive output correlation both in complete and incomplete market models, (b) consumption correlation smaller than output correlation with an introduction of information‐constrained consumers, and (c) observation of both positive and negative productivity–hours correlation in two countries.

REGIME-SWITCHING PRODUCTIVITY GROWTH AND BAYESIAN LEARNING IN REAL BUSINESS CYCLES

Growth in total factor productivity (TFP) in the USA has slowed down significantly since the mid-2000s, reminiscent of the productivity slowdown of the 1970s. This paper investigates the implications of a productivity slowdown on macroeconomic variables using a standard real business cycle (RBC) model, extended with regime-switching in trend productivity growth and Bayesian learning regarding the growth regime. I estimate the Markov-switching parameters using US data and maximum-likelihood methods, and compute the model solution using global projection methods. Simulations reveal that, while adding a regime-switching component to the standard RBC setup increases the volatility in the system, further incorporating incomplete information and learning significantly dampens this effect. The dampening is mainly due to the responses of investment and labor in response to a switch in the trend component of TFP growth, which are weaker in the incomplete information case as agents mistakenly place some probability that the observed decline in TFP growth is due to the transient component and not due to a regime switch. The model offers an objective way to infer slowdowns in trend productivity, and suggests that macroeconomic aggregates in the USA are currently close to their potential levels given observed productivity, while counterfactual simulations indicate that the cost of the productivity slowdown to US welfare has been significant.

Uncertainty Quantification and Global Sensitivity Analysis for Economic Models

Sensitivity analysis assesses the influence of input parameters on the conclusion of a model. Traditional analysis methods — based on evaluating the model at a reference parameter vector and changing one parameter at a time — are local, linear, and usually don’t capture interactions among the parameters. By contrast, the global sensitivity analysis that we present summarizes the parameters’ importance over a range of values, fully capturing nonlinearities and identifying interactions. Specifically, we propose Sobol’ indices, which are based on variance decomposition, and exemplify their use with a standard real business cycle model. Standard approaches to variance decomposition require a large number of model evaluations. To overcome this, we present the state-of-the-art approach for calculating Sobol’ indices, which is based on building a polynomial representation of the model from a limited number of evaluations. In addition, we use this polynomial representation to evaluate the univariate effects, which are conditional expectation functions that can be interpreted as a robust impact of a parameter on the model conclusions.

Exchange Rate Disconnect in General Equilibrium

We propose a dynamic general equilibrium model of exchange rate determination, which simultaneously accounts for all major exchange rate puzzles. This includes the Meese-Rogoff disconnect puzzle, the PPP puzzle, the terms-of-trade puzzle, the Backus-Smith puzzle, and the UIP puzzle. We build on a standard international real business cycle model augmented with a financial sector with noise traders and risk-averse intermediaries, which results in equilibrium UIP deviations due to limits to arbitrage. We show that financial UIP shocks result in persistent near-martingale processes for exchange rates and ensure empirically relevant comovement properties between exchange rates and macro variables, including excess exchange-rate volatility relative to aggregate consumption and output. In contrast, conventional productivity and monetary shocks, while successful in explaining the international business cycle comovement, result in counterfactual exchange rate dynamics with insufficient volatility. As a result, when combined together, the two sets of shocks reproduce both the exchange rate disconnect behavior and the empirical business cycle properties. The transmission mechanism relies on a conventional Taylor rule, home bias in consumption, and muted pass-through of exchange rates into prices and quantities due to pricing to market and weak substitutability between home and foreign goods. Nominal rigidities improve somewhat the quantitative performance of the model, yet are not necessary for the exchange rate disconnect, as monetary shocks are not the key drivers of the exchange rate.