Globalization and business cycle transmission

The paper uses long-run GDP data for developed countries drawn from Maddison [Maddison, A. (2003). The world economy—Historical statistics. Paris: OECD Development Centre] to generate deviation cycles for the period from 1870 to 2001. The cyclical deviates are examined for their bilateral cross-correlation values in three separate periods, those of the first globalization wave (1870–1914), the period of the “bloc economy” (1915–1959) and for the period of the second globalization (1960–2001). Cluster analysis is applied and the McNemar test is used to test for the relative coherence of alternative groupings of countries in the three periods. The bloc economy period emerges as one that features some well-defined sub-global clusters, where the second globalization period does not, the first globalization period lying between the two in this respect. The second globalization period shows a generally higher level of cross-correlations and a lower variance than the other two periods. The features uncovered suggest that the second globalization period is indeed one that comprises a more inclusive world economy than ever before.     

Stock market volatility and the business cycle

This paper investigates the joint time series behavior of monthly stock returns and growth in industrial production. We find that stock returns are well characterized by year-long episodes of high volatility, separated by longer quiet periods. Real output growth, on the other hand, is subject to abrupt changes in the mean associated with economic recessions. We study a bivariate model in which these two changes are driven by related unobserved variables, and conclude that economic recessions are the primary factor that drives fluctuations in the volatility of stock returns. This framework proves useful both for forecasting stock volatility and for identifying and forecasting economic turning points.     

Detrending,stylized facts and the business cycle

The stylized facts of macroeconomic time series can be presented by fitting structural time series models. Within this framework, we analyse the consequences of the widely used detrending technique popularised by Hodrick and Prescott (1980). It is shown that mechanical detrending based on the Hodrick–Prescott filter can lead investigators to report spurious cyclical behaviour, and this point is illustrated with empirical examples. Structural time-series models also allow investigators to deal explicitly with seasonal and irregular movements that may distort estimated cyclical components. Finally, the structural framework provides a basis for exposing the limitations of ARIMA methodology and models based on a deterministic trend with a single break.     

Capital maintenance and depreciation over the business cycle

This paper develops and estimates a stochastic general equilibrium model with capital maintenance, which affects endogenously the depreciation rate of capital. The estimate of maintenance series is found to track survey-based measures for Canada quite closely and to generate the procyclical pattern of maintenance observed in the data. We use our model estimates to infer the time profile of equipment capital depreciation in Canadian and US manufacturing. The depreciation rate is estimated to be volatile and highly procyclical in both countries.     

CES technology and business cycle fluctuations

We contribute to an emerging literature that brings the constant elasticity of substitution (CES) specification of the production function into the analysis of business cycle fluctuations. Using US data, we estimate by Bayesian-Maximum-Likelihood methods a standard medium-sized DSGE model with a CES rather than Cobb–Douglas (CD) technology. We estimate a elasticity of substitution between capital and labour well below unity at 0.15–0.18. In a marginal likelihood race CES decisively beats the CD production and this is matched by its ability to fit the data better in terms of second moments. We show that this result is mainly driven by the implied fluctuations of factor shares under the CES specification. The CES model performance is further improved when the estimation is carried out under an imperfect information assumption. Hence the main message for DSGE models is that we should dismiss once and for all the use of CD for business cycle analysis.     

Forecasting the business cycle using survey data

Regular business survey data are published as percentages of firms predicting higher, equal or lower values of some reference variable. Time series of such percentages do not fit production data too well. Univariate models often produce forecasts which are just as accurarate. Still, surveys contain anticipative judgement which, when combined with univariate modeling and proper filtering, may produce a good indicator for business cycle turning points. The way survey data are transformed so as to fit statistics on production seems not to be of much importance. A case study of the Finnish forest industry is offered as an example.     

Privatization and economic performance throughout the UK business cycle

Since 1979, many state-owned industries in the UK have been sold to private shareholders. Initial studies of the impact of privatization on performance were unable to distinguish once-and-for-all shake-out effects and those that were part of a continuing process. Moreover, the immediate post-privatization period often coincided with the boom conditions of the late 1980s. Using two standard performance ratios, this paper examines these issues by tracking the record of eleven firms that were privatized in the 1980s. The results make it difficult to sustain the hypothesis that private ownership is unequivocally more efficient than nationalization.     

Sentiment and the U.S. business cycle

Psychological factors are commonly believed to play a role on cyclical economic fluctuations, but they are typically omitted from state-of-the-art macroeconomic models.This paper introduces “sentiment” in a medium-scale DSGE model of the U.S. economy and tests the empirical contribution of sentiment shocks to business cycle fluctuations.The assumption of rational expectations is relaxed. The paper exploits, instead, observed data on expectations in the estimation. The observed expectations are assumed to be formed from a near-rational learning model. Agents are endowed with a perceived law of motion that resembles the model solution under rational expectations, but they lack knowledge about the solution’s reduced-form coefficients. They attempt to learn those coefficients over time using available time series at each point in the sample and updating their beliefs through constant-gain learning. In each period, however, they may form expectations that fall above or below those implied by the learning model. These deviations capture excesses of optimism and pessimism, which can be quite persistent and which are defined as sentiment in the model. Different sentiment shocks are identified in the empirical analysis: waves of undue optimism and pessimism may refer to expected future consumption, future investment, or future inflationary pressures.The results show that exogenous variations in sentiment are responsible for a sizable (above forty percent) portion of historical U.S. business cycle fluctuations. Sentiment shocks related to investment decisions, which evoke Keynes’ animal spirits, play the largest role. When the model is estimated imposing the rational expectations hypothesis, instead, the role of structural investment-specific and neutral technology shocks significantly expands to capture the omitted contribution of sentiment.     

The international business cycle and gold-price fluctuations

Drawing on recent empirical research, we study whether the international business cycle, as measured in terms of the output gaps of the G7 countries, has out-of-sample predictive power for gold-price fluctuations. To this end, we use a real-time forecasting approach that accounts for model uncertainty and model instability. We find some evidence that the international business cycle has predictive power for gold-price fluctuations. After accounting for transaction costs, a simple trading rule that builds on real-time out-of-sample forecasts does not lead to a superior performance relative to a buy-and-hold strategy. We also suggest a behavioral-finance approach to study the quality of out-of-sample forecasts from the perspective of forecasters with potentially asymmetric loss functions.     

Search in the product market and the real business cycle

Empirical evidence suggests that most firms operate in imperfectly competitive markets. We develop a search-matching model between wholesalers and retailers. Firms face search costs and form long-term relationships. Price bargain results in both wholesaler and retailer mark ups, which depend on firms' relative bargaining power. We simulate the general equilibrium model and explore the role of product market search frictions for business cycles. We conclude from the simulation exercise that incorporating product market search structure and shocks improve the standard real business cycle model to reproduce US business cycle fluctuations.     

The business cycle in the G-7 economies

In this paper the Hodrick–Prescott filter is used to decompose real GDP for the G7 countries into cyclical and trend components. The resulting series of cyclical components are then examined for static relationships, using correlations and graphs; long-run relationships using autoregressive-distributed lag models; and short-run relationships, using error–correction models. The main result is that the patterns of cyclical behaviour changed following the oil price shocks in the 1970s. Since 1980, cyclical fluctuations have been smaller as a result of a decline in synchronisation of the cycles in the G7. Two separate cycles seem to be developing since 1990. One is for Germany, Italy and France, whilst the other is for the US, UK and Canada. Within each of these groups there are both long-run and short-run relationships between the cyclical components of GDP.     

Consumer misperceptions,uncertain fundamentals,and the business cycle

This paper estimates the importance of shocks to consumer misperceptions “noise shocks” for U.S. business cycle fluctuations. I embed imperfect information as in Lorenzoni (2009) into a Smets and Wouters (2007)-type DSGE model. Agents only observe aggregate productivity and a signal about the permanent component contaminated with noise. Based on this information agents form beliefs about the temporary and the permanent component of productivity. Shocks to the signal (noise shocks) trigger aggregate fluctuations unrelated to changes in productivity. Bayesian estimation shows that noise shocks explain up to 14 percent of output and up to 25 percent of consumption fluctuations. Nominal rigidities and the specification of the monetary policy rule are crucial for the importance of noise shocks. These features help to resolve conflicting results in the previous literature.     

The business cycle model with a unique stable limit cycle

This paper provides the mathematical foundation to the long-standing academic belief that Goodwin's 1951 nonlinear business cycle model has a unique stable limit cycle. In spite of the asymmetric nonlinearity of investment function, the model has certainly a unique stable limit cycle in an economically meaningful region. Once solution paths start from any initial point in the region, they all tend to the limit cycle without escaping from the region or hitting the ceiling or floor of investment during a transition period. The structural stability of the model prevents the limit cycle from vanishing in the face of small perturbations.     

State productivity growth in agriculture: catching-up and the business cycle

This paper examines the relation between the business cycle and convergence in levels of agricultural productivity across the 48 contiguous states. First, we find evidence of convergence in total factor productivity levels across the different phases of the business cycle, but the speed of convergence was greater during periods of contraction in economic activity than during periods of expansion. Second, we find that technology embodied in capital was an important source of productivity growth in agriculture. As with the rate of catch-up, the embodiment effect was much stronger during low economic activity phases of the business cycle.     

Income inequality and the business cycle: A threshold cointegration approach

This paper investigates the impact of various socio-economic variables on various cohorts of the income distribution. We use asymmetric cointegration tests to show that unemployment and immigration shocks have real impacts on income inequality. In addition, using threshold test results we are able to show that positive and negative shocks to the economy do not have symmetric effects nor do the impacts of these shocks impact income quintiles uniformly.     

Bank fee-based shocks and the U.S. business cycle

Efficient liquidity matching requires from banks to track external shocks (e.g., GDP growth shocks, stock market shocks and monetary policy shocks) in order to optimally allocate their assets between loans and other business lines. Profit maximizing banks have to rebalance their product-mix to take advantage of these changes. However, even though banking is cyclical, and contemporaneously reacts to shocks outside the banking sphere, there may also be some feedback effects at play, whereby bank changes, in turn, could affect economic and financial conditions. Generalizing the results of Marcucci and Quagliariello (2006, 2009), who indeed find an asymmetric impact of credit shocks on economic and financial time series in recession, we use a similar VAR framework to show that an even stronger feedback effect is prevalent for fee-based shocks. If the feedback effects of credit and fee-based shocks might have been both at play before the subprime crisis, the feedback effect of credit shocks seems to have faded away during the subprime crisis, whereas the feedback effect stemming from fee-based shocks has gained further strength.     

A monetary business cycle model with unemployment

To reproduce key features of the post-war U.S. data, most monetary business cycle models must assume there are high price markups and that agents have high labour supply elasticities despite the existence of contradictory microeconomic evidence. This paper eliminates the need for these assumptions by introducing imperfectly observed effort into a limited participation model. The estimated model is better able to capture the sluggish price response to a monetary policy shock than the standard model, and is consistent with evidence regarding the qualitative responses of the U.S. economy to technology shocks, fiscal policy shocks and monetary policy shocks.     

The asymmetric behavior of household consumption under the business cycle

In this study, we examine whether and to what extent the pattern of household consumption is asymmetrically sensitive to economic changes. We use a threshold model with error correction to characterize household consumption under the business cycle. Using data from the 1979–2014 Survey of Family Income and Expenditure in Taiwan, we find that household consumption has pro-cyclical characteristics during the business cycle. More importantly, household consumption responds asymmetrically to economic fluctuations such that changes in consumption tend to be larger during expansions than during downturns. Furthermore, the nature of this asymmetry differs across household income quantiles.     

A useful tool for forecasting the Euro-area business cycle phases

Based on a novel extension of existing multivariate Markov-switching models, we provide the reader with a useful tool for analyzing current business conditions and making predictions about the future state of the Euro-area economy in real time. Apart from the Industrial Production Index, we find that the European Commission Industrial Confidence Indicator, which is issued with no delay, is very useful for constructing the real-time predictions.     

Asset prices in affine real business cycle models

I describe a tractable way to study macroeconomic quantities and asset prices in a large class of dynamic stochastic general equilibrium models. The proposed approximate solution is analytical, log-linear, and adjusted for risk. Therefore, it is well suited to investigate economic mechanisms, describe the time series properties or estimate the model, and deal with stochastic volatility. I explain the pitfalls encountered by previous attempts to use simple approximation techniques, in particular with models featuring recursive preferences. Finally, I show the theoretical relationship between my solution and higher-order perturbation methods.