Forecasting Corporate Investment
Nicolas Ferrari
Abstract
Nicolas Ferrari
Abstract
Insee's quarterly survey of investment in industry is a prime source of information concerning short-term evolutions in productive investment, making it possible to estimate these evolutions at an early stage and with considerable precision. However, the annual nature of the questions posed makes it is difficult to use the results for forecasting on a quarterly basis. This article proposes a quarterly indicator based on revisions in industrial firms? expectations regarding their investment. This indicator measures the adjustments to investment figures made during the year in response to changes of a short-term nature. It turns out to be closely correlated with quarterly evolutions in firms? investment as measured in the national accounts. Moreover, it is available roughly three months before the publication of the initial quarterly national accounts figures. As the distributions examined fail to verify the classic normality hypothesis (thick tails and heavy concentrations at zero) it is necessary toapply an estimation method that is robust to extreme revisions. Taking into account also the presence of heteroscedasticity, the method adopted was that known as "Quasi-Generalised M-Estimators".
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Insee's quarterly survey of investment in industry is a prime source of information concerning short-term evolutions in productive investment, making it possible to estimate these evolutions at an early stage and with considerable precision. However, the annual nature of the questions posed makes it is difficult to use the results for forecasting on a quarterly basis. This article proposes a quarterly indicator based on revisions in industrial firms? expectations regarding their investment. This indicator measures the adjustments to investment figures made during the year in response to changes of a short-term nature. It turns out to be closely correlated with quarterly evolutions in firms? investment as measured in the national accounts. Moreover, it is available roughly three months before the publication of the initial quarterly national accounts figures. As the distributions examined fail to verify the classic normality hypothesis (thick tails and heavy concentrations at zero) it is necessary toapply an estimation method that is robust to extreme revisions. Taking into account also the presence of heteroscedasticity, the method adopted was that known as "Quasi-Generalised M-Estimators".
Key concepts: Investment (military), Heteroscedasticity, Econometrics, Term (time), Normality, Estimator, Economics, Prime (order theory)