Length Of Business Cycle Research Articles

Effect of the policy and consumption delay on the amplitude and length of business cycle.

In this paper, the amplitude and the length of the business cycle are investigated. It is the first time the length of the business cycle based on the Goodwin model (one classical business cycle model) is discussed. The effect of the time delay of the economic policy and consumption on the amplitude and the length of the business cycle is studied. Meanwhile, the memory property of making economic policy is also considered. The theoretical amplitude of the business cycle is obtained by multiple-scale methods. The transitions of the amplitude induced by memory property and time delay are analyzed. How the economic parameter and random excitation affect the length of the business cycle is proposed. Based on the results, we can find that the time delay of both economic policy and consumption can induce the transitions. Moreover, the memory property of economic policy will change the critical value of the parameters when the transitions occur. In one typical induced investment function, the length of the business cycle is determined only by the autonomous investment and consumption. However, the length of the business cycle is not mainly affected by the autonomous investment and consumption in some other typical induced investment function. This states that the type of induced investment function has a very important role in determining the length of the business cycle.

A study of financial cycles and the macroeconomy in Taiwan

This paper studies the characteristics of financial cycles (credit and house prices) and their interactions with business cycles in Taiwan. We employ multivariate structural time series model to estimate trend and cyclical components in real bank credit, real house prices, and real GDP. We find that financial cycles are roughly twice the length of the business cycles, and house price cycles lead both credit and business cycles. Nevertheless, the estimated length of business and financial cycles in Taiwan is much shorter than those in industrialized economies. We then use machine learning to evaluate the importance of a macroeconomic variable that predicts downturns of financial cycles, by conducting both in-sample fitting and out-of-sample forecasting. Those macrovariables selected by machine learning reflects Taiwan’s close linkage in trades and financial interdependence with other countries such as China and spillover effects from the Fed’s monetary policy.

Asset Pricing with Persistence Risk

Persistence risk is an endogenous source of risk that arises when a rational agent learns about the length of business cycles. Persistence risk is positive during recessions and negative during expansions. This asymmetry, which solely results from learning about persistence, causes expected returns, return volatility, and the price of risk to rise during recessions. Persistence risk predicts future excess returns, particularly at 3- to 7-year horizons. Its predictability is strongest around business-cycle peaks and troughs. We confirm the model’s predictions in the data and provide evidence that persistence risk is priced in financial markets.Received October 13, 2017; editorial decision September 19, 2018 by Editor Stijn Van Nieuwerburgh. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Asset Pricing with Disagreement and Uncertainty About the Length of Business Cycles

We study an economy with incomplete information in which two agents are uncertain and disagree about the length of business cycles. That is, the agents do not question whether the economy is growing or not, but instead continuously estimate how long economic cycles will last—i.e., they learn about the persistence of fundamentals. Learning about persistence generates high and persistent stock return volatility mostly during recessions, but also (to a smaller extent) during economic booms. Disagreement among agents fluctuates and earns a risk premium. A clear risk–return trade-off appears only when conditioning on the sign and magnitude of disagreement. We confirm these predictions empirically.This paper was accepted by Neng Wang, finance.

Asset Pricing with Persistence Risk

Persistence risk is an endogenous source of risk that arises when a rational agent learns about the length of business cycles. Persistence risk is positive during recessions and negative during expansions. This asymmetry, which solely results from learning about persistence, causes expected returns, return volatility, and the price of risk to rise during recessions. Persistence risk predicts future excess returns, particularly at 3- to 7-year horizons. Its predictability is strongest around business-cycle peaks and troughs. We confirm the model's predictions in the data and provide evidence that persistence risk is priced in financial markets.

Asset Pricing with Disagreement and Uncertainty about the Length of Business Cycles

We study an economy with incomplete information in which two agents are uncertain and disagree about the length of business cycles. That is, the agents do not question whether the economy is growing or not, but instead continuously estimate how long economic cycles will last — i.e., they learn about the persistence of fundamentals. Learning about persistence generates high and persistent stock return volatility mostly during recessions, but also (to a smaller extent) during economic booms. Disagreement among agents fluctuates and earns a risk premium. A clear risk-return tradeoff appears only when conditioning on the sign and magnitude of disagreement. We confirm these predictions empirically.

Measuring length of business cycles across countries using a new non-stationary unit-root cyclical approach

This article examines the length of the cycles in the gross domestic product (GDP) real per capita series of 15 countries by means of new statistical techniques based on unit root cycles. We propose tests for unit root cycles at each of the frequencies of the process. Using this approach, we are able to approximate the number of periods per cycle. The results show that the cycles have a periodicity of approximately six years when the disturbances are white noise. However, if we permit autocorrelation, they may also occur at smaller intervals of time. Copyright © 2006 John Wiley & Sons, Ltd.

British Company Taxation and Automatic Stabilisation

Using a model where the company income tax base is a function of levels of economic activity, it is shown that there is no basis for the widely held view that the built-in effect of the British company tax system has been destabilising. The model, synthesised from separate models of gross profit and depreciation, was estimated for eight industry groups using annual data for the period 1950–66. A comparison of the lags in the model with the length of business cycles between 1950–66 showed that the automatic effect of the tax is likely to have been stabilising.