What are the differences in processes in Eviews Chow - Lin Data temporal Disaggregation and other data disaggregation methods in eviews ?

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Fozil Xolmurotov

In EViews, there are various methods available for data disaggregation, including the Chow-Lin data temporal disaggregation method. Here are some key differences between the Chow-Lin method and other data disaggregation methods in EViews:

Chow-Lin Data Temporal Disaggregation: The Chow-Lin method is based on a regression-based approach and is suitable for disaggregating annual or higher-frequency data into lower-frequency data. It assumes that the relationships between the aggregate and disaggregate series are stable over time, allowing for the estimation of disaggregated values. The method minimizes the mean square error between the aggregated and disaggregated series by estimating the regression coefficients. It requires the availability of historical data for both the aggregate and disaggregate series.

Proportional Disaggregation: Proportional disaggregation is a simple method where the disaggregated series is obtained by proportionally distributing the aggregate value based on historical proportions. This method assumes that the relative proportions between the aggregate and disaggregate series remain constant over time. It is commonly used for distributing aggregate values to different subcategories or regions. Proportional disaggregation does not involve the estimation of regression coefficients and is relatively straightforward to apply.

Ratio Disaggregation: Ratio disaggregation involves disaggregating the aggregate series based on historical ratios between the aggregate and disaggregate series. Similar to proportional disaggregation, it assumes that the relationship between the aggregate and disaggregate series remains constant over time. This method is useful when there is a strong correlation between the aggregate and disaggregate series. Ratio disaggregation is relatively simple and does not require extensive estimation procedures.

It's important to note that the choice of disaggregation method depends on the characteristics of the data, the nature of the relationship between the aggregate and disaggregate series, and the purpose of the analysis. EViews provides various tools and techniques to perform data disaggregation, allowing users to choose the most appropriate method for their specific requirements.

Chuck A Arize

The Chow-Lin method is a technique used for temporal disaggregation or also known as temporal distribution. Temporal disaggregation is the process of deriving high frequency data (e.g., monthly data) from low frequency data (e.g., annual data).