A.B.M. Rabiul Alam Beg

Tests Against Inequality Constraints When Some Nuisance Parameters Are Present Only under the Alternative: Test of ARCH in ARCH-M Models

In this article we develop improved statistical tests for situations satisfying the following two nonstandard conditions simultaneously: (a) Some nuisance parameters become unidentified under the null hypothesis, and (b) the alternative hypothesis is restricted in the sense that it has inequality constraints/multiparameter one-sided hypotheses. In the statistical and econometric literature, inference problems under these two nonstandard conditions have been studied separately but not simultaneously. For example, procedures to deal with the nonstandard condition (a) only have been studied by Bera and Ra and by Andrews and Ploberger; surveys of test procedures to deal with (b) only may be found in the work of Robertson, Wright, and Dykstra. A main contribution of this article is that, by pooling the ideas and insights from both these areas of literature, we develop new tests to deal with (a) and (b) simultaneously. Based on the approach that we take, we would conjecture that our tests should perform better than other tests that are available for tests under the nonstandard conditions (a) and (b). As an example, we consider the problem of testing whether or not the error variance is constant over time, in an ARCH-in-Mean (ARCH-M) model. We use this example to motivate and explain our ideas. A data example illustrates the application of the test in a simple situation. In a simulation study, we observed that the new test procedures proposed here performed better than the other available ones for this problem.

Detecting volatility persistence in GARCH models in the presence of the leverage effect

Most asset prices are subject to significant volatility. The arrival of new information is viewed as the main source of volatility. As new information is continually released, financial asset prices exhibit volatility persistence, which affects financial risk analysis and risk management strategies. This paper proposes a nonlinear regime-switching threshold generalized autoregressive conditional heteroskedasticity model which can be used to analyse financial data. The empirical results based on quasi-maximum likelihood estimation presented in this paper suggest that the proposed model is capable of extracting information about the sources of volatility persistence in the presence of the leverage effect.

What determines China's trade balance dynamics: a disaggregate analysis of panel data

Chinas huge trade surplus has attracted much interest around the globe from people of different walks of life. What has contributed to Chinas trade surplus has been a puzzle. Many researchers have attempted to discover the determinants that are responsible for Chinas trade imbalance but their findings are inconclusive or debatable. This paper offers new insights into the determinants of Chinas trade balance. In this study, the re-export role of Hong Kong in the trade of Chinas mainland is examined and the actual level of bilateral trade flows between China and each of its major trading partners is then re-estimated. Both these treatments are the first time employed in the literature, representing a major innovation in studying Chinas trade balance. The analysis with re-estimated trade data reveals that labour costs, income, foreign direct investment (FDI) and the exchange rate are all important determinants of Chinas trade surplus. However, the low labour cost has a much greater impact on Chinas trade surplus, followed by FDI. The exchange rate is also important but not as critical as many others have claimed.

The driving forces of the level and the growth rate of real per capita income in Indonesia

We investigate the driving forces behind the level and the growth rate in real per capita Gross Domestic Product (GDP) in Indonesia. The ultimate reasons and the proximate causes underlying Indonesias economic growth since the mid-1960s are still unclear. In the literature there have been at least three ways of investigating the driving forces of economic growth in Indonesia, namely: growth accounting system, regression and causality. The difference and improvement in this article is that we employed a two-step bounds testing approach to cointegration, which has not been done before; it uses the endogenous growth model to consider 12 policy variables and two external factors that potentially affect per capita income, this number is more than that has been done before. The empirical results that we obtained using this two-step bounds testing approach help us draw policy implications that if or when implemented would be expected to increase the growth of real per capita income, as well as the welfare of the people of Indonesia. Economic growth in Indonesia is largely driven by government policy, so the ability to increase Indonesias economic growth rate, in the long run, will largely depend on the implementation of appropriate government policies.

Robust Tests Against Smooth Transition Autoregressive Models

In this paper, we consider testing for linearity against a well-known class of regime switching models known as the smooth transition autoregressive (STAR) models. Apart from the model selection issues, one reason for interest in testing for linearity in time-series models is that non-linear models such as the STAR are considerably more difficult to use. This testing problem is non-standard because a nuisance parameter becomes unidentified under the null hypothesis. In this paper, we further explore the class of tests proposed by Luukkonen, Saikonnen and Terasvirta (1988). Luukkonen et al . (1988) proposed LM tests for linearity against STAR models. A potential difficulty here is that the linear approximation introduces high leverage points, and hence outliers are likely to be quite influential. To overcome this difficulty, we use the same approximating linear model of Luukkonen et al . (1988), but we apply Wald and F -tests based on l 1 - and bounded influence estimates. The efficiency gains of this procedure cannot be easily deduced from the existing theoretical results because the test is based on a misspecified model under H 1 . Therefore, we carried out a simulation study, in which we observed that the robust tests have desirable properties compared to the test of Luukkonen et al . (1988) for a range of error distributions in the STAR model, in particular the robust tests have power advantages over the LM test.