Discrete-time ARMA processes can be placed in a one-to-one correspondence\ud with a set of continuous-time processes that are bounded in frequency by the\ud Nyquist value of π radians per sample period. It is well known that, if data are\ud sampled from a continuous process of which the maximum frequency exceeds\ud the Nyquist value, then there will be a problem of aliasing. However, if the\ud sampling is too rapid, then other problems will arise that will cause the ARMA\ud estimates to be severely biased. The paper reveals the nature of these problems\ud and it shows how they may be overcome. It is argued that the estimation of\ud macroeconomic processes may be compromised by a failure to take account of\ud their limits in frequency
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