Search results

This chapter adopts value at risk (VaR) to analyze the hedge timing issue. Suppose that a producer, at a give time, recognizes the possible need of a futures contract for risk reduction purpose. Should the producer trade in the futures market immediately or should he wait? Conditions are characterized under which delaying the hedge decision is preferred as it produces a smaller VaR. For an efficient futures market, it appears that the producer is better off delaying the hedge decision as long as possible. However, strong backwardation promotes early hedging.

Using a sample of developed and developing nations (including China and Hong Kong), this study examines the financial market and housing wealth effects on consumption. Housing performs the dual functions as both a commodity providing a flow of housing services and an investment providing a flow of capital income. With an empirical framework based on the permanent income hypothesis, this study's findings suggest that a rise in housing price has both a positive wealth effect and a negative price effect on consumption. While the positive wealth effect is caused by an increase in capital income from housing investment, the negative price effect is caused by an increase in the cost of consuming housing services. Moreover, the sensitivity of consumption to unanticipated changes in housing price is related to the level of financial and institutional development.

This chapter studies the dynamic responses of the conditional quantiles and their applications in macroeconomics and finance. The authors build a multi-equation autoregressive conditional quantile model and propose a new construction of quantile impulse response functions (QIRFs). The tool set of QIRFs provides detailed distributional evolution of an outcome variable to economic shocks. The authors show the left tail of economic activity is the most responsive to monetary policy and financial shocks. The impacts of the shocks on Growth-at-Risk (the 5% quantile of economic activity) during the Global Financial Crisis are assessed. The authors also examine how the economy responds to a hypothetical financial distress scenario.

This paper proposes a new class of estimators for the autoregressive coefficient of a dynamic panel data model with random individual effects and nonstationary initial condition. The new estimators we introduce are weighted averages of the well-known first difference (FD) GMM/IV estimator and the pooled ordinary least squares (POLS) estimator. The proposed procedure seeks to exploit the differing strengths of the FD GMM/IV estimator relative to the pooled OLS estimator. In particular, the latter is inconsistent in the stationary case but is consistent and asymptotically normal with a faster rate of convergence than the former when the underlying panel autoregressive process has a unit root. By averaging the two estimators in an appropriate way, we are able to construct a class of estimators which are consistent and asymptotically standard normal, when suitably standardized, in both the stationary and the unit root case. The results of our simulation study also show that our proposed estimator has favorable finite sample properties when compared to a number of existing estimators.