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multivariate modelling of non stationary economic time series pdf
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Multivariate modelling of non-stationary economic time series refers to the analysis and forecasting of multiple economic variables that exhibit non-stationary behavior over time. Non-stationarity implies that the statistical properties of the time series, such as mean and variance, change over time, making traditional time series analysis techniques inappropriate. In this context, multivariate modelling involves considering the interdependencies and interactions among different economic variables, rather than analyzing them in isolation. This approach allows for a more comprehensive understanding of the dynamics and relationships within the economic system, leading to more accurate forecasting and policy recommendations. To account for non-stationarity, various techniques can be used, such as differencing, detrending, or incorporating trend and seasonality components in the model. Additionally, cointegration analysis can be applied to identify long-run relationships among the variables, which helps in building more reliable models. Overall, multivariate modelling of non-stationary economic time series is a sophisticated analytical framework that enables economists and policymakers to better understand and predict the complex dynamics of the economy, and make informed decisions based on the relationships among multiple economic variables.