Chew Lian Chua

Are Empirical Measures of Macroeconomic Uncertainty Alike

There is a plethora of time series measures of uncertainty for inflation and real output growth in empirical studies but little is known whether they are comparable to the uncertainty measure reported by individual forecasters in the survey of professional forecasters. Are these two measures of uncertainty inherently distinct? This paper shows that, compared with many uncertainty proxies produced by time series models, the use of real‐time data with fixed‐sample recursive estimation of an asymmetric bivariate generalized autoregressive conditional heteroskedasticity model yields inflation uncertainty estimates which resemble the survey measure. There is, however, overwhelming evidence that many of the time series measures of growth uncertainty exceed the level of uncertainty obtained from survey measure. Our results highlight the relative merits of using different methods in modelling macroeconomic uncertainty which are useful for empirical researchers.

A Two-Stage Estimation of Hospital Quality Using Mortality Outcome Measures: An Application Using Hospital Administrative Data

This paper proposes a method of deriving a quality indicator for hospitals using mortality outcome measures. The method aggregates any number of mortality outcomes into a single indicator via a two-stage procedure. In the first stage, mortality outcomes are risk-adjusted using a system of seemingly unrelated regression equations. These risk-adjusted mortality rates are then aggregated into a single quality indicator in the second stage via weighted least squares. This method addresses the dimensionality problem in measuring hospital quality, which is multifaceted in nature. In addition, our method also facilitates further analyses of determinants of hospital quality by allowing the resulting quality estimates be associated with hospital characteristics. The method is applied to a sample of heart-disease episodes extracted from hospital administrative data from the state of Victoria, Australia. Using the quality estimates, we show that teaching hospitals and large regional hospitals provide higher quality of care than other hospitals and this superior performance is related to hospital case-load volume.

Hospital Competition, Technical Efficiency and Quality

This paper studies the link between competition and technical efficiency of public hospitals in the state of Victoria, Australia. It finds a positive relationship between efficiency and competition as measured by the Hirschman–Herfindahl Index (HHI) and a negative relationship when the number of competing private hospitals is used instead of HHI. It also finds that whether or not quality is treated as an endogenous output variable influences the statistical estimates of the link between efficiency and competition. The findings point to possibly undesirable resource allocation effects when public hospitals are made to compete with a large number of private hospitals.

Bank and Official Interest Rates: How Do They Interact Over Time?

This paper implements a procedure to evaluate time-varying bank interest rate adjustments over a sample period which includes changes in industry structure, market and credit conditions and varying episodes of monetary policy. The model draws attention to the pivotal role of official rates and provides estimates of the equilibrium policy rate. The misalignment of actual official rates and their changing sensitivity to banking conditions is identified. Results are also provided for the variation in intermediation margins and pass-throughs as well as the interactions between lending and borrowing behaviour over the years, including behaviour before, during and after the global financial crisis. The case studies are the US and Australian banking systems.

Forecasting Australian Macroeconomic Variables Using a Large Dataset

This paper investigates the forecasting performance of the diffusion index approach for the Australian economy, and considers the forecasting performance of the diffusion index approach relative to composite forecasts. Weighted and unweighted factor forecasts are benchmarked against composite forecasts, and forecasts derived from individual forecasting models. The results suggest that diffusion index forecasts tend to improve on the benchmark AR forecasts. We also observe that weighted factors tend to produce better forecasts than their unweighted counterparts. We find, however, that the size of the forecasting improvement is less marked than previous research, with the diffusion index forecasts typically producing mean square errors of a similar magnitude to the VAR and BVAR approaches.

Markov-Switching Mean Reversion in Short-Term Interest Rates: Evidence from East Asian Economies

This paper employs a Markov-switching approach to model the dynamics of East Asian short rates. Regime changes are incorporated in standard unit root test to reveal periodic changes in the stationarity property of interest rates. There is evidence that three of the five short rates follow a random walk process in tranquil and low rates episodes but mean-revert in periods when rates are high and volatile. Singapore short rates are characterised by a random walk process, whereas the Philippines rates behave as a mean-reverting process in both regimes. Factors such as exchange rates, monetary policy and interest rate differentials vis-a-vis US interest rates influence the likelihood of short rates being in a volatile state. The regime switching dynamics of interest rates carry important implications for policy-makers. Copyright

THE BEHAVIOR OF U.S. PUBLIC DEBT AND DEFICITS DURING THE GLOBAL FINANCIAL CRISIS

In this paper we test the sustainability of U.S. public debt for the period 1916–2012 by analyzing how the primary surplus to gross domestic product (GDP) responds to changes in the debt to GDP ratio in a time‐varying parameter model. Further, we determine the stationarity property of the debt/GDP ratio while accommodating possible breaks in the data caused by wars and economic crisis under both the null and alternative hypotheses of an endogenous unit root test. The results show that the U.S. public debt was sustainable until 2005 when the primary surplus to GDP reacted negatively to the debt/income ratio. This is further exacerbated during the global financial crisis when primary surpluses continued to fall with increased debt, thus jeopardizing the sustainability of fiscal policy. While the stationarity test shows that the U.S. fiscal debt/GDP ratio is sustainable, it fails to highlight the risk that its debt policy has been becoming unsustainable in recent years.

Regional Indexes of Activity: Combining the Old with the New

This paper proposes a framework to construct indexes of activity which links two strands of the index literature – the traditional business cycle analysis and the latent variable approach. To illustrate the method, we apply the framework to Australian regional data, namely to two resource-rich and two service-based states. The results reveal differences in the evolution and drivers of economic activity across the four states. We also demonstrate the value of the Index in a broader context by using a structural vector autoregression (SVAR) approach to analyse the effects of shocks from the US and from China. This Index-SVAR approach facilitates a richer analysis because the unique feature of the index method proposed here allows impulse responses to be traced back to the components.

A Multivariate GARCH Model Incorporating the Direct and Indirect Transmission of Shocks

Theoretical models of contagion and spillovers allow for asset-specific shocks that can be directly transmitted from one asset to another, as well as indirectly transmitted across uncorrelated assets through some intermediary mechanism. Standard multivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models, however, provide estimates of volatilities and correlations based only on the direct transmission of shocks across assets. As such, spillover effects via an intermediary asset or market are not considered. In this article, a multivariate GARCH model is constructed that provides estimates of volatilities and correlations based on both directly and indirectly transmitted shocks. The model is applied to exchange rate and equity returns data. The results suggest that if a spillover component is observed in the data, the spillover augmented models provide significantly different volatility estimates compared to standard multivariate GARCH models.

Predicting Short-Term Interest Rates: Does Bayesian Model Averaging Provide Forecast Improvement?

This paper examines the forecasting qualities of Bayesian Model Averaging (BMA) over a set of single factor models of short-term interest rates. Using weekly and high frequency data for the one-month Eurodollar rate, BMA produces predictive likelihoods that are considerably better than the majority of the short-rate models, but marginally worse off than the best model in each dataset. We observe preference for models incorporating volatility clustering for weekly data and simpler short rate models for high frequency data. This is contrary to the popular belief that a diffusion process with volatility clustering best characterizes the short rate.