Zijun Wang

A MONTE CARLO STUDY ON THE SELECTION OF COINTEGRATING RANK USING INFORMATION CRITERIA

We conduct Monte Carlo simulations to evaluate the use of information criteria (Akaike information criterion [AIC] and Schwarz information criterion [SC]) as an alternative to various probability-based tests for determining cointegrating rank in multivariate analysis. First, information criteria are used to determine cointegrating rank given the lag order in a levels vector autoregression. Second, information criteria are used to determine the lag order and cointegrating rank simultaneously. Results show that AIC has an advantage over trace tests for cointegrated or stationary processes in small samples. AIC does not perform well in large samples. The performance of SC is close to that of the trace test. SC shows better large sample results than AIC and the trace test, even if the series are close to nonstationary series or they contain large negative moving average components. We also find evidence that supports the joint estimation of lag order and cointegrating rank by the SC criterion. We conclude that information criteria can complement traditional parametric tests.We are grateful to Peter C.B. Phillips and an anonymous referee for their comments, which significantly improved the paper.

Stock market reaction to food recalls: a GARCH application

How food recalls due to bacterial contamination affect the stock prices of two companies are examined using a version of the financial market model that accounts for Generalized Autoregressive Conditional Heteroscedasticity (GARCH) effects. GARCH methodology was necessary to uncover the time-varying volatility in the series and it contributed to more efficient econometric results. The initial food recall undertaken by the company is associated with reduced mean returns and higher volatility of the companies studied. Repeated recalls by the same company are not associated with strong reactions. Volatility spillovers across firms suggest potential industry-wide repercussions from bacterial contamination incidents.

Financial crisis and African stock market integration

This article examines long-run relationships and short-run dynamic causal linkages among the five largest emerging African stock markets and the US market, with particular attention to the 1997–1998 global emerging market crisis. In general, interdependence between the African markets and the influence of the US on these markets was limited during 1996–2002. There is evidence that both long-run relationships and short-run causal linkages between these markets were substantially weakened after the crisis.

Regional inequality in China's health care expenditures.

This paper has two parts. The first part examines the regional health expenditure inequality in China by testing two hypotheses on health expenditure convergence. Cross-section regressions and cluster analysis are used to study the health expenditure convergence and to identify convergence clusters. We find no single nationwide convergence, only convergence by cluster. In the second part of the paper, we investigate the long-run relationship between health expenditure inequality, income inequality, and provincial government budget deficits (BD) by using new panel co-integration tests with health expenditure data in Chinas urban and rural areas. We find that the income inequality and real provincial government BD are useful in explaining the disparity in health expenditure prevailing between urban and rural areas. In order to reduce health-spending inequality, one long-run policy suggestion from our findings is for the government to implement more rapid economic development and stronger financing schemes in poorer rural areas.

Is the Value Premium a Proxy for Time-Varying Investment Opportunities? Some Time-Series Evidence

We uncover a positive stock market risk-return tradeoff after controlling for the covariance of market returns with the value premium. Fama and French (1996) conjecture that the value premium proxies for investment opportunities; therefore, by ignoring it, early specifications suffer from an omitted variable problem that causes a downward bias in the risk-return tradeoff estimation. We also document a positive relation between the value premium and its conditional variance, and the estimated conditional value premium is strongly countercyclical. The latter evidence supports the view that value is riskier than growth in bad times, when the price of risk is high.

The convergence of health care expenditure in the US states

In response to rising health care costs, many have called for more effective regional health policy coordination. In this paper, we address the issue by examining the degree of convergence in per capita health care expenditure and its nine components across the US states from 1980 to 2004. The major finding is the moderate evidence of convergence in total health care expenditure and the diverse performance of the expenditure components regarding convergence. We also find hospital care to be responsible for the bulk of cross-state convergence in total expenditure. The expenditure on prescription drugs is the most important diverging factor. Policy implications of these empirical results are discussed.

Conditional Coskewness in Stock and Bond Markets: Time-Series Evidence

In the context of a three-moment intertemporal capital asset pricing model specification, we characterize conditional coskewness between stock and bond excess returns using a bivariate regime-switching model. We find that both conditional U.S. stock coskewness (the relation between stock return and bond volatility) and bond coskewness (the relation between bond return and stock volatility) command statistically and economically significant negative ex ante risk premiums. The impacts of stock and bond coskewness on the conditional stock and bond premiums are quite robust to various model specifications and various sample periods, and also hold in another major developed country (the United Kingdom). The findings also carry important implications for portfolio management.

Regional variations in medical spending and utilization: a longitudinal analysis of US Medicare population

One of the perceived symptoms of US Medicare inefficiency is the existence of the dramatic variation in spending and utilization in different areas of the country. This study uses the Continuous Medicare History Sample, a large longitudinal 5% sample of all Medicare beneficiaries from 1974 to 2003, to study the issue. We show that the spending and utilization disparities are significant at the aggregate state level. More importantly, the variation shows signs of narrowing over time, particularly in the earlier years of the sample period and in some cases following major reforms. However, it remains significant even after an array of demographic, demand and supply side factors are controlled for.

What determines health: a causal analysis using county level data.

This article revisits the long-standing issue of the determinants of health outcomes. We make two contributions to the literature. First, we use a large and comprehensive US county level health data set that has only recently become available. This data set includes five measures of health outcomes and 24 health risk factors in the categories of health behaviors, clinical care, social and economic factors, and physical environment. Second, to distinguish causality from correlation, we implement an emerging data-driven method to study the causal factors of health outcomes. Among all included potential health risk factors, we identify adult smoking, obesity, motor vehicle crash death rate, the percent of children in poverty, and violent crime rate to be major causal factors of premature mortality. Adult smoking, preventable hospital stays, college or higher education, employment, children in poverty, and adequacy of social support determine health-related quality of life. Finally, the Chlamydia rate, community safety, and liquor store density are three important factors causally related to low birth weight. Policy implications of these findings are discussed.

Evaluating the ‘Fed Model’ of Stock Price Valuation: An out-of-sample forecasting perspective

The “Fed Model” postulates a cointegrating relationship between the equity yield on the S&P 500 and the bond yield. We evaluate the Fed Model as a vector error correction forecasting model for stock prices and for bond yields. We compare out-of-sample forecasts of each of these two variables from a univariate model and various versions of the Fed Model including both linear and nonlinear vector error correction models. We find that for stock prices the Fed Model improves on the univariate model for longer-horizon forecasts, and the nonlinear vector error correction model performs even better than its linear version.