The Dynamic Relationship between Permanent and Transitory Components of U.S. Business Cycles

This paper investigates the dynamic relationship between permanent and transitory components of post-war U.S. business cycles. We specify a time-series model for real GNP and consumption in which the two share a common stochastic trend and transitory component, and Markov-regime switching is used to model business cycle phases in these components. The timing of switches between business cycle phases is allowed to differ across the permanent and transitory components. We find strong evidence of a lead-lag relationship between the switches in the two components. Specifically, switches in the permanent component leads switches in the transitory component when entering recessions.     

Countercyclical Policy and the Speed of Recovery after Recessions

We consider policies intended to accelerate recoveries by analyzing the duration of recoveries of U.S. states. Studying multiple recessions for a state and multiple states for a recession controls for differences in the economic conditions and the causes of recessions. Expansionary monetary policy at the national level helps to stimulate the exit of individual states from recession. Exogenous measures of decreases in taxes or targeted increases in federal spending reduce state recovery times, while ambient economic conditions (other states in the same region suffering from recession, the length of the preceding recession, and increases in oil prices) extend recovery times.     

Predicting the bear stock market: Macroeconomic variables as leading indicators

This paper investigates whether macroeconomic variables can predict recessions in the stock market, i.e., bear markets. Series such as interest rate spreads, inflation rates, money stocks, aggregate output, unemployment rates, federal funds rates, federal government debt, and nominal exchange rates are evaluated. After using parametric and nonparametric approaches to identify recession periods in the stock market, we consider both in-sample and out-of-sample tests of the variables’ predictive ability. Empirical evidence from monthly data on the Standard & Poor’s S&P 500 price index suggests that among the macroeconomic variables we have evaluated, yield curve spreads and inflation rates are the most useful predictors of recessions in the US stock market, according to both in-sample and out-of-sample forecasting performance. Moreover, comparing the bear market prediction to the stock return predictability has shown that it is easier to predict bear markets using macroeconomic variables.     

Nonlinear Effects of Mortgage Spreads Over the Business Cycle

This paper provides robust evidence for the nonlinear effects of mortgage spread shocks during recessions and expansions in the United States. Estimating a smooth-transition vector autoregression (STVAR) model, we show that mortgage spread shocks hitting in a recessionary phase create significantly deeper and more protracted declines in consumption and housing market variables. In addition, we provide evidence that these mortgage spread shocks could be largely interpreted as credit supply shocks in the mortgage market. Our empirical results imply that unconventional monetary policy, such as the Federal Reserve's mortgage-backed security purchase program, would be a more effective tool for stabilizing the economy during recessions than in expansions.     

The scarring effect of recessions

According to the conventional view, recessions improve resource allocation by driving out less productive firms. This paper posits an additional scarring effect: recessions impede the developments of potentially superior firms by destroying them during their infancy. A model is developed to capture both the cleansing and the scarring effects. A key ingredient of the model is that idiosyncratic productivity is not directly observable, but can be learned over time. When calibrated with statistics on entry, exit and productivity differentials, the model suggests that the scarring effect dominates the cleansing effect, and gives rise to lower average productivity during recessions.     

Demand and productivity components of business cycles: Estimates and implications

Standard stochastic growth models provide theoretical restrictions on output decomposition which can be used to investigate whether productivity shocks played a major role in observed business cycles. Applying these restrictions to US data leads to the following findings: (i) Business cycles implied by productivity shocks are mildly correlated to overall fluctuations and help account for a few episodes of US postwar recessions. However, only 20% of US fluctuations can be explained by these shocks. (ii) Most fluctuations seem instead to be due to “nominal demand” shocks, i.e. shocks which move output and prices in the same direction, but whose effects on output are ultimately transitory. (iii) Canonical sticky price models in the new-neoclassical synthesis tradition can account for the cyclical comovements of output and prices, but canonical, frictionless, RBC models cannot.     

An exploration into Pigou's theory of cycles

This paper explores a theory of business cycles in which recessions and booms arise due to difficulties encountered by agents in properly forecasting the economy's future needs in terms of capital. The idea has a long history in the macroeconomic literature, as reflected by the work of Pigou (Industrial Fluctuation, MacMillan, London, 1926). The contribution of this paper is twofold. First, we illustrate the type of general equilibrium structure that can give rise to such phenomena. Second, we examine the extent to which such a model can explain the observed pattern of U.S. recessions (frequency, depth) without relying on technological regress. We argue that such a model offer a framework for understanding elements of both the recent U.S. recession and of the Asia downturns of the late 1990s.     

Can Warren Buffett forecast equity market corrections?

Warren Buffett suggested that the ratio of the market value of all publicly traded stocks to the Gross National Product could identify potential overvaluations and undervaluations in the US equity market when this ratio deviates above 120% or below 80%. We investigate whether this ratio is a statistically significant predictor of equity market corrections and rallies. We find that Buffett's decision rule does not deliver satisfactory forecasts. However, when we adopt a time-varying decision rule, the ratio becomes a statistically significant predictor of equity market corrections. The two time-varying decision rules are: (i) predict an equity market correction when the ratio exceeds a 95% one-tail confidence interval based on a normal distribution, and (ii) predict an equity market correction when the ratio exceeds a threshold computed using Cantelli's inequality. These new decision rules are robust to changes in the two key parameters: the confidence level and the forecasting horizon. This paper also shows that the MV/GNP ratio performs relatively well against the four most popular equity market correction models, but the ratio is not a particularly useful predictor of equity market rallies.     

The Market's Differential Reactions to Forward-Looking and Backward-Looking Dividend Changes

Empirical evidence on the signaling hypothesis of dividends is weak and mixed. Recent studies find that dividend changes reflect mostly current and past earnings but not future earnings. We provide a model in which not all dividend changes contain new information about future earnings. Some dividend decisions are backward looking (noninformation or nonsignaling events). Other dividend decisions are forward looking (information or signaling events). The model helps identify the two types of dividend changes and predicts that the market will respond strongly only to forward‐looking dividend changes. We provide evidence consistent with the implications of the model.     

DYNAMIC ORDER SUBMISSION AND HERDING BEHAVIOR IN ELECTRONIC TRADING

I analyze the dynamic trading behavior of market participants by developing a bivariate modeling framework for describing the arrival process of buy and sell orders in a limit order book. The model contains an extended autoregressive conditional duration model with a flexible generalized Beta distribution to explain the duration process, combined with a dynamic logit model to capture the traders' order submission strategy. I find that the state of the order book as well as the speed of the order arrival have a significant influence on the order placement, inducing temporal asymmetric market movements.     

Measuring time-varying financial market integration: An unobserved components approach

We measure the time-varying degree of world stock market integration of five developed countries (Germany, France, UK, US, and Japan) over the period 1970:1–2011:10. Time-varying financial market integration of each country is measured through the conditional variances of the country-specific and common international risk premiums in equity excess returns. The country-specific and common risk premiums and their conditional variances are estimated from a latent factor decomposition through the use of state space methods that allow for GARCH errors. Our empirical results suggest that stock market integration has increased over the period 1970:1–2011:10 in all countries but Japan. And while there is a structural increase in stock market integration in four out of five countries, all countries also exhibit several shorter periods of disintegration (reversals), i.e. periods in which country-specific shocks play a more dominant role. Hence, stock market integration is measured as a dynamic process that is fluctuating in the short run while gradually increasing in the long run.     

Understanding Housing Market Volatility

The Campbell–Shiller present value formula implies a factor structure for the price–rent ratio of housing market. Using a dynamic factor model, we decompose the price–rent ratios of 23 major housing markets into a national factor and independent local factors, and we link these factors to the economic fundamentals of the housing markets. We find that a large fraction of housing market volatility is local and that the national factor has become more important than local factors in driving housing market volatility since 1999, consistent with the findings in Del Negro and Otrok (2007). The local volatilities mostly are due to time variations of idiosyncratic housing market risk premia, not local growth. At the aggregate level, the growth and interest rate factors jointly account for less than half of the total variation in the price–rent ratio. The rest is due to the aggregate housing market risk premium and a pricing error. We find evidence that the pricing error is related to money illusion, especially at the onset of the recent housing market bubble. The rapid rise in housing prices prior to the 2008 financial crisis was accompanied by both a large increase in the pricing error and a large decrease in the housing market risk premium.     

CAPITAL STRUCTURE,SHAREHOLDER RIGHTS,AND CORPORATE GOVERNANCE

We show how capital structure is influenced by the strength of shareholder rights. Our empirical evidence shows an inverse relation between leverage and shareholder rights, suggesting that firms adopt higher debt ratios where shareholder rights are more restricted. This is consistent with agency theory, which predicts that leverage helps alleviate agency problems. This negative relation, however, is not found in regulated firms (i.e., utilities). We contend that this is because regulation already helps alleviate agency conflicts and, hence, mitigates the role of leverage in controlling agency costs.     

Oil Price Uncertainty

The theories of investment under uncertainty and real options predict that uncertainty about, for example, oil prices will tend to depress current investment. We reinvestigate the relationship between the price of oil and investment, focusing on the role of uncertainty about oil prices. We find that volatility in oil prices has had a negative and statistically significant effect on several measures of investment, durables consumption, and aggregate output. We also find that accounting for the effects of oil price volatility tends to exacerbate the negative dynamic response of economic activity to a negative oil price shock, while dampening the response to a positive oil price shock.     

On the nonlinear relation between product market competition and earnings quality

The literature documents conflicting results regarding the influence of product market competition on earnings quality. We extend this stream of literature by incorporating competition’s effect on both the opportunities and the incentives to manage earnings. The combination of both effects results in a nonlinear relation between product market competition and earnings quality. At low competition levels, additional information associated with one more rival helps reveal earnings irregularity and deter earnings management to a larger extent than its effect on the incentives to manage earnings, suggesting a positive relation between competition and earnings quality. At high competition levels, the latter effect dominates the former. We thus predict a positive (negative) relation between competition and earnings quality at low (high) competition levels. Consistent with our hypothesis, we document an inverted U-shaped relation between earnings quality and product market competition.     

Labor Market and Financial Shocks: A Time-Varying Analysis

We estimate a time-varying VAR model to analyze the effects of a financial shock on the U.S. labor market. We find that a tightening of financial conditions is highly detrimental to the labor market. We show that while negative financial shocks have been responsible for increases in unemployment, our model does not find significant contributions of financial shocks during periods of expansion. The source of this asymmetry is the time-varying standard deviation of the identified shock, which is higher in times of financial distress; on the other hand, we find that the transmission mechanism does not significantly change over time.     

Regime switching and monetary policy measurement

This paper applies regime-switching methods to the problem of measuring monetary policy. Policy preferences and structural factors are specified parametrically as independent Markov processes. Interaction between the structural and preference parameters in the policy rule serves to identify the two processes. The estimates uncover policy episodes that are initiated by switches to “dove regimes,” shown to Granger-cause both NBER recessions and the Romer dates. These episodes imply real effects of monetary policy that are smaller than those found in previous studies.     

Dynamic linkages between the center and periphery in international stock markets

This paper examines the dynamic linkages between the equity market of US representing the center and emerging markets using the Granger-causality test. The findings show that causality runs from the S&P500 to the stock prices of the 15 emerging markets but not vice versa.     

Explaining international stock correlations with CPI fluctuations and market volatility

This paper investigates the dynamic correlations among six international stock market indices and their relationship to inflation fluctuation and market volatility. The current research uses a newly developed time series model, the Double Smooth Transition Conditional Correlation with Conditional Auto Regressive Range (DSTCC-CARR) model. Findings reveal that international stock correlations are significantly time-varying and the evolution among them is related to cyclical fluctuations of inflation rates and stock volatility. The higher/lower correlations emerge between countries when both countries experience a contractionary/expansionary phase or higher/lower volatilities.     

Market Feedback,Investment Constraints,and Managerial Behavior

This paper examines the joint role of market feedback and investment constraints on managerial behavior. Using a sample of UK fixed price initial public offerings, we show that underperformance of share returns at the IPO significantly affects managerial investment decisions in the period after the offering. Firms with better investment opportunities and proportionately lower fixed (higher intangible) assets are more sensitive to negative market feedback. Over the longer term, the more responsive firms perform significantly better than their non‐responsive counterparts. The findings contribute to the debate on the informational advantage of managers over investors and present strong evidence that the market, on aggregate, can provide a superior assessment of a firm's opportunities. Managers who are able to respond to negative market feedback can significantly improve their firm's future prospects.