실질환율의 비선형동학과 예측 분석
Nonlinear Dynamics and Out-of-sample Forecasts of Real Exchange Rates
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본 논문에서는 실질환율의 비선형성을 검정하고 이를 이용해서 표본외 예측 분석을 하였다. 1975년 이후 선진 7개국의 데이터를 사용하여 실질환율데이터에 비선형성을 확인할 수 있었는데, 이러한 비선형성은 ESTAR 모형으로 잘 포착되었다. 즉 실질환율은 재정거래가 불가능한 일정한 범위에서는 단위근을 갖지만, 그 범위에서 이탈되면 다시 그 범위로 회귀하는 비선형적 평균회귀의 특성을 보이는 것으로 판단된다. 이러한 결과는 구매력평가설의 성립을 함축한다는 점에서 매우 주요한 결과로 평가된다. ESTAR 모형을 사용해서 표본외 예측 분석을 하였는데, 예측치의 RMSE나 Diebold-Mariano 통계량으로 볼 때, 전반적으로 ESTAR 모형으로 임의행보모형보다 정확한 예측치를 얻지 못했다. 하지만 일부 실질환율의 경우, 특히 독일, 이탈리아 및 프랑스의 경우 예측범위(forecast horizon)가 긴 경우 ESTAR 모형으로 얻은 예측치가 임의행보모형보다 우수한 것으로 나타났다.
Abstract
The purpose of the paper is to contribute to the debate on the relevance of nonlinear modeling and forecasts in real exchange rates. Using monthly data from the post‐Bretton Woods periods for the developed seven countries, we found strong evidence of the presence of nonlinearities in the behavior of real exchange rate, which appeared to be modeled well by an exponential smooth transition autoregressive model. The presence of nonlinear mean‐reverting adjustment for real exchange rates can be explained by the theoretical models that emphasize the role of transaction and monopolistic pricing. We then used this model to make out‐of‐sample forecasting analysis. Overall, we find fairly limited evidence that favors the ESTAR model over a simple random walk benchmark. The nonlinear ESTAR forecasts tend to outperform a simple random walk at longer forecast horizons for UK and Switzerland, but at shorter forecast horizons for Japan and Canada, although the magnitude of the gain from using the ESTAR relative to a random walk is rather small in magnitude at entire forecast horizon.
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