Real Business Cycle Model Research Articles

Stock Market Valuation and Monopolistic Competition: A Dynamic Stochastic General Equilibrium Approach

This paper extends a Real Business Cycle model to an economy in which monopolistic competitive firms’ technology is subject to idiosyncratic and common shocks. The value of future technology rents drive stock market valuation. We study how the arrival of new information about future technological developments affect each firm’s stream of future profit, the rate on return on physical capital, and the value of equity. We show that good news about future technology of a specific firm or industry will lift the price of shares of the specific firms, but that good news about future aggregate productivity will raise the discount rate, leaving the price of shares unchanged. On the other hand, good news about future aggregate profit margins will lift the price of shares.

Fisherian Futures Market

The very fact that utility maximization in real business cycle and New Keynesian models is intertemporal suggests the possibility of a Fisherian intertemporal futures market, which is not state-contingent. Ex-ante speaking, the addition of a futures market does not result in any difference, but the addition does make difference ex-post. Furthermore, New Keynesian models rely on nominal effects, and what would introduction of a Fisherian futures market mean for these models? This paper answers this question by presenting a model that features Fisherian intertemporal futures markets.

The macroeconomic effects of goods and labor markets deregulation

We study the macroeconomic effects of deregulating the goods and labor markets. To this end, we introduce endogenous product creation and labor market frictions in an otherwise-standard real business cycle model. Regulation affects producer entry costs, firing restrictions, and unemployment benefits. We find that reforms can have short-run recessionary effects, despite being expansionary in the long run. Estimates from a panel VAR for OECD countries provide empirical support for this result. Moreover, market deregulation has sizable effects on the efficiency of business cycle fluctuations. Increased flexibility in both goods and labor markets lowers the level and volatility of the inefficiency wedges that distort agents' equilibrium decisions, leading to a substantial reduction in the welfare cost of business cycles. Nevertheless, individual reforms produce contrasting effects.

The role of oscillatory modes in US business cycles

We apply multivariate singular spectrum analysis to the study of US business cycle dynamics. This method provides a robust way to identify and reconstruct oscillations, whether intermittent or modulated. We show such oscillations to be associated with comovements across the entire economy. The problem of spurious cycles generated by the use of detrending filters is addressed and we present a Monte Carlo test to extract significant oscillations. The behavior of the US economy is shown to change significantly from one phase of the business cycle to another: the recession phase is dominated by a five-year mode, while the expansion phase exhibits more complex dynamics, with higher-frequency modes coming into play. We show that the variations so identified cannot be generated by random shocks alone, as assumed in real business-cycle models, and that endogenous, deterministically generated variability has to be involved.

Can firm entry explain news-driven fluctuations?

Most models subjected to news shocks fail to re-produce the basic aggregate comovement facts. This paper proposes that firm entry can be a channel for the real business cycle model to generate quantitatively realistic expectations-driven fluctuations. Endogenous variation in products supports aggregate comovement in response to contemporaneous shocks and news about future technology. This occurs easily even if, as argued by recent empirical studies, markups are procyclical. The model matches the key second moments of U.S. business cycles. The findings highlight the importance of future work on the implications of news-driven firm entry and its interaction with markups for optimal policy.

Modeling FDI Flows from the USA to Canada: Two Main International Financial Variables Affect the Long-Run Economic Growth

This paper develops a model to predict for the spillover effects of the foreign capital inflows on the long run growth under conditions of international economic exposure to foreign exchange rate fluctuations. The paper utilizes a simple open economy version of the Solow growth model with the main features of real business cycle models. In addition, the paper uses a time series model with substitution techniques to test the impact of the spillover effect of foreign capital inflows from the USA on long run growth in Canada, while controlling for exposure to foreign exchange rate fluctuations, as well as for both external and internal balances. The results support the existence of positive spillover effects from foreign direct investment on the economy. The results also show that foreign exchange rate fluctuations have weaken the impact of underlying changes in productivity on the attractiveness of the economy to overseas investors and hence moderate the overall impact of the technology spillover effect of Foreign Direct Investment (FDI) on long-run growth.

Structural VARs, deterministic and stochastic trends: how much detrending matters for shock identification

Abstract Detrending within structural vector autoregressions (SVAR) is directly linked to the shock identification. We investigate the consequences of trend misspecification in an SVAR using both standard real business cycle models and bi-variate SVARs as data generating processes. Our bias decomposition reveals biases arising directly from trend misspecification are not trivial when compared to other widely studied misspecifications. Misspecifying the trend also distorts impulse response functions of even the correctly detrended variable within the SVAR system. Pretesting for unit roots mitigates trend misspecification to some extent. We also find that while practitioners can specify high lag order VARs to mitigate trend misspecification, relying on common information criterion such as the Akaike information criterion (AIC) or Bayesian information criterion (BIC) may choose a lag order that is too low.

THE INTENSIVE MARGIN PUZZLE AND LABOR MARKET ADJUSTMENT COSTS

This paper documents a puzzling fact, namely that there is a significant negative relation between employment protection legislation and the usage of the intensive margin of labor market adjustments. I make use of a real business cycle model and introduce search and matching frictions as well as adjustment costs along the extensive and the intensive labor market margins. I show that the model is able to replicate the observed patterns of cyclicality, volatility, and especially the behavior of extensive and intensive margins if we assume low firing costs and relatively high hours adjustment costs.

Correlations Between Macroeconomic Cycles in the US and UK: What Can a Frequency Domain Analysis Tell Us?

In this paper, the relationship between the growth of GDP and real GDP components is explored in the frequency domain using both static and dynamic techniques derived from wavelet analysis. This analysis is carried out separately for the US and the UK using quarterly data, and the results are found to be quite different for both countries. One of the major findings of the paper is that there are significant relationships between cycles of the GDP components at frequencies other than the business cycle frequencies that confirm some of the predictions of economic theory; but importantly contradict others. Secondly, that the relative power of the different cycles varies over time leading to the idea of “volatility transfers” between cycles. Third that the correlations and lead-lag relationships between cycles shift over time, leading to several new insights into how the aggregate demand in these two economies has actually evolved in practice. These results are of particular significance for understanding the current weak economic recovery and for why real business cycle models do not find the right relationships between GDP components.

Rebuilding “Time to Build”: A History of the Real Business Cycle Models

In his article “Present at the creation: Reflections on the 2004 Nobel Prize to Finn Kydland and Edward Prescott”, Robert Lucas wonders: I look back on this paper [“Time to Build and Aggregate Fluctuations”] with amazement: “How did [Kydland and Prescott] even think to put all these pieces together in just this way?” (Lucas, 2005, 777) Warren Young’s book Real Business Cycle Models in Economics is an excellent attempt to answer this question from the perspective of the history of (macro)econo...

Search frictions and labor market dynamics in a real business cycle model with undeclared work

We study the effects of undeclared work (UDW) on labor market dynamics in a real business cycle (RBC) model with search and matching frictions in the labor market. Distinction is made between the wages paid and the hours worked in regular and in undeclared types of activity. Calibrating the model on the US economy, we show that a greater size of UDW implies lower average employment, higher volatility of employment and lower volatility of regular wages. These volatilities are affected by the steady-state ratio between the minimum value of the regular wage that can be accepted by a worker and the maximum value that can be paid by a firm in the Nash bargaining process, which occurs when a labor match is realized. The greater the ratio, the higher the volatility of employment and the lower the volatility of wages. We demonstrate that, due to a social stigma attached to UDW, an increase in undeclared hours raises this ratio by reducing the numerator less than the denominator. This suggests that the introduction of UDW may improve the ability of RBC models to match the empirical volatilities of labor market variables.

Firing costs in a business cycle model with endogenous separations

Purpose– The purpose of this paper is to introduce productivity-dependent firing costs into an otherwise standard endogenous separations matching model. The authors suggest an alternative to the standard fix cost approach and account for empirical evidence emphasizing that firing costs vary across workers. The authors show that the model with firing costs outperformes the model without firing costs and replicates the empirical facts fairly well. Furthermore, the authors present cross-country evidence that countries with stricter employment protection have a weaker Beveridge curve relation and surprisingly more volatile job flow rates.Design/methodology/approach– The authors begin the analysis at the intersection of labor and product markets. For this purpose, the authors derive a real business cycle model with search and matching frictions and endogenous separations. The authors enrich this set-up by introducing productivity-dependent firing costs.Findings– The authors show that the model with firing costs outperformes the model without firing costs and replicates the empirical facts fairly well. Furthermore, the authors present cross-country evidence that countries with stricter employment protection have a weaker Beveridge curve relation and surprisingly more volatile job flow rates.Originality/value– This paper introduces productivity-dependent firing costs into an otherwise standard endogenous separations matching model. The authors suggest an alternative to the standard fix cost approach and account for empirical evidence emphasizing that firing costs vary across workers. The authors show that the model with firing costs outperformes the model without firing costs and replicates the empirical facts fairly well. Furthermore, the authors present cross-country evidence that countries with stricter employment protection have a weaker Beveridge curve relation and surprisingly more volatile job flow rates.

Scalable high-dimensional dynamic stochastic economic modeling

We present a highly parallelizable and flexible computational method to solve high-dimensional stochastic dynamic economic models. Solving such models often requires the use of iterative methods, like time iteration or dynamic programming. By exploiting the generic iterative structure of this broad class of economic problems, we propose a parallelization scheme that favors hybrid massively parallel computer architectures. Within a parallel nonlinear time iteration framework, we interpolate policy functions partially on GPUs using an adaptive sparse grid algorithm with piecewise linear hierarchical basis functions. GPUs accelerate this part of the computation one order of magnitude thus reducing overall computation time by 50%. The developments in this paper include the use of a fully adaptive sparse grid algorithm and the use of a mixed MPI-Intel TBB-CUDA/Thrust implementation to improve the interprocess communication strategy on massively parallel architectures. Numerical experiments on “Piz Daint” (Cray XC30) at the Swiss National Supercomputing Centre show that high-dimensional international real business cycle models can be efficiently solved in parallel. To the best of our knowledge, this performance on a massively parallel petascale architecture for such nonlinear high-dimensional economic models has not been possible prior to present work.

Effects of Oil Price Shocks on German Business Cycles

In this paper we analyse to what extent movements in oil prices can help to explain business cycle fluctuations in Germany.We proceed in several steps:As a starting point we use a standard real business cycle model for the German economy and introduce energy as an additional factor in the production function. As in Kim/Loungani (1992) our finding is that oil price shocks increase the volatility of output but only to a limited extent.We therefore continue by using a real business cycle model for a small open economy and again include energy use in the production function (de Miguel et al. 2003).But compared to our previous model we could only find an additional increase in volatility of output under certain conditions. Subsequently,we use these models to analyse whether the impact of oil price movements has changed over time by splitting our data set into two subsamples: the first from 1970 to 1986 and the second from 1987 to 2002.The main results suggest that the reduced importance of energy for industrial production substantially decreases the vulnerability of the German economy with regard to oil price shocks.

The consequences of an unknown debt target

Several proposals to reduce U.S. debt reveal large differences in their targets. We examine how an unknown debt target affects economic activity using a real business cycle model in which Bayesian households learn about a state-dependent debt target in an endogenous tax rule. Recent papers use stochastic volatility shocks to study fiscal uncertainty. In our setup, the fiscal rule is time-varying due to unknown changes in the debt target. Households infer the current debt target from a noisy tax rule and jointly estimate the transition probabilities. Three key findings emerge from our analysis: (1) limited information about the debt target amplifies the effect of tax shocks through changes in expected tax rates; (2) the welfare losses are an order of magnitude larger when both the debt target state and transition matrix are unknown than when only the debt target state is unknown to households; (3) an unknown debt target likely reduced the stimulative effect of the ARRA and uncertainty about the sunset provision in the Bush tax cuts may have slowed the recovery and led to welfare losses.

International Correlations and the Composition of Trade

Taking the composition of trade into account, this paper shows that an otherwise parsimonious international real business cycle model can account for the international comovement of macro quantities. In disaggregated US trade data the share of non-durable consumer goods in imports and exports is low and remarkably stable from 1989 to 2012. In the model as in the data, trade is mostly in consumer durables and capital goods, and cross-country correlations are consistent with the evidence. Output comoves positively across countries with a higher cross-country correlation than consumption, and the cross-country correlation of investment and employment are both positive. Standard models of international business cycles that ignore the composition of trade flows typically fail to produce these patterns in international correlations.

Ambiguity and Financial Uncertainty in a Real Business Cycle Model

We examine a representative-agent production economy with stochastic mean and volatility of productivity growth, in which the agent has ambiguity aversion and learns about the mean growth state. In recessions, the agent's heightened concern about state uncertainty increases financial uncertainty, measured by the risk-neutral variance of market returns. Consistent with empirical observations, financial uncertainty relates negatively to quantities but positively to volatilities of quantities. Financial uncertainty also leads to lower equity value and carries a positive risk premium. Our calibrated model can closely match moments of quantities and asset returns and also generate a sizable variance risk premium.

Indeterminacy with Progressive Taxation and Sector‐Specific Externalities

AbstractThis paper quantitatively examines the empirical plausibility of equilibrium indeterminacy and sunspot‐driven cyclical fluctuations in a real business cycle model with two distinct production sectors that yield consumption and investment goods, together with separable or non‐separable preferences. When calibrated to match the observed progressivity of the US federal individual income tax schedule, each version of our model economy exhibits an indeterminate steady state under empirically realistic combinations of the household's labour supply elasticity and the degree of productive externalities in the investment goods sector. Therefore, macroeconomic instability due to agents' self‐fulfilling expectations may, in fact, be a prevalent feature of the US economy.

Demand Shocks and Open Economy Puzzles

We pose good markets frictions on top of an otherwise standard two-country international real business cycle (IRBC) model. Shopping for goods takes effort, which prevents perfect matching between customers and producers. An increase in search effort implies increased measured productivity. Demand shocks increase expenditures and search effort simultaneously increasing output, consumption, productivity, and the trade deficit and appreciating the real exchange rate. Thus we solve the Backus-Smith puzzle and we show that the cross country correlation of consumption is higher than that of output. Standard IRBC models cannot account for these puzzles along with movements in TFP.

Testing for linear and nonlinear Granger causality in the real exchange rate–consumption relation

International real business cycle models predict a relationship between real exchange rates and consumption. This prediction is not supported by the empirical literature. In a new approach, we apply nonlinear Granger-causality tests to data for 14 OECD countries.