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- W2143807762 abstract "Instrumental variables estimation is classically employed to avoid simultaneous equations bias in a stable environment. Here we use it to improve upon ordinary least‐squares estimation of cointegrating regressions between non‐stationary and/or long memory stationary variables where the integration orders of regressor and disturbance sum to less than 1, as happens always for stationary regressors, and sometimes for mean‐reverting non‐stationary ones. Unlike in the classical situation, instruments can be correlated with disturbances and/or uncorrelated with regressors. The approach can also be used in traditional non‐fractional cointegrating relations. Various choices of instrument are proposed. Finite sample performance is examined." @default.
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- W2143807762 date "2006-06-09" @default.
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- W2143807762 title "Instrumental variables estimation of stationary and non‐stationary cointegrating regressions" @default.
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- W2143807762 doi "https://doi.org/10.1111/j.1368-423x.2006.00186.x" @default.
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