Using GARCH Model in the Analysis of Trade Liberalization and Poverty in Developing Countries

Abstract

The current paper reviews impacts of trade liberalization on developing countries and levels of poverty. The expected impacts of multilateral trade liberalization on wage levels and subsequent poverty are implored. Empirical Auto-regression models are visualized to develop a different set of strategies and programs to provide real benefits to the poor with real benefits. It is concluded that GARCH updating formula takes the weighted average of the unconditional variance, the squared residual for the first observation and the starting variance and estimates the variance of the second observation. This input into the forecast of the third variance and so forth. Eventually, an entire time series of variance forecasts is constructed. Ideally, this series is large when the residuals are large and small when they are small. The likelihood function provides a systematic way to adjust the parameters to give the best fit. It is possible that the true variance process can differ from the one specified by econometricians. In order to detect this, a variety of diagnostic tests are available. Various tests such as tests for autocorrelation in the squares are able to detect model failures.

Keywords: Trade Liberalization, Poverty, GARCH Model