# Presentation: 394039

## Data Errors, Structural Change, and Time Series Shocks in the Electricity Market

- Nancy Kirkendall, Lindolfo Pedraza and Joe Sedransk

## Louisiana Residential Sales

## Mississippi Residential Sales

## Colorado Commercial Sales

## New York Residential Sales

## EIA-861Annual Electric Power Industry Report

- Data collected annually
- Data represents a census of the universe of power industry participants
- Represents the frame off of which the monthly sample can be drawn

## EIA-826Monthly Electric Sales and Revenue Report 

-   Collected monthly
-   Sample drawn from EIA-861 Universe
-   Remaining non-samples firms are given an estimated monthly value

**Notes:**
 is the total quantity of electricity sold to commercial, industrial, residential or transportation/other sectors.   is the total quantity of electricity sold to commercial, industrial, residential or transportation/other sectors in the kth state.   is the total quantity of electricity sold in a state by the ith firm in the kth state. The summation over j represents the summation of all transactions in a month. 

## EIA-826 Survey Sampling Methodology

- Due to the skewed nature of electricity sales data, a cutoff sample is utilized
- A weighted regression is used to impute for both non-sampled data and non-response within the sampled data
- The survey model is now:

**Notes:**
 is the total quantity of electricity sold to commercial, industrial, residential or transportation/other sectors.   is the total quantity of electricity sold to commercial, industrial, residential or transportation/other sectors in the kth state.   is the total quantity of electricity sold in a state by the ith firm in the kth state. The summation over j represents the summation of all transactions in a month. 

## SCATTER-PLOT EDITING 

## IMPUTING MONTHLY EIA-826 WITH EIA-861

- EIA-826 – Monthly Totals for:
- Electricity Sales
- Total Revenues
- EIA-826 is a sample of the 861 Universe

- EIA-861 – Annual Totals for:
- Electricity Sales
- Total Revenues
- EIA-861 is the entire Universe

## EIA-826 Regression Imputation with Heteroskedastic errors

- state level monthly revenue from the ith firm to the commercial, industrial, residential or transportation/other sector collected from EIA-826

- state level annual revenue from the ith firm to the commercial, industrial, residential or transportation/other sector collected from EIA-861.

- The state level annual values are divided over 12 to improve interpretability  in monthly estimates

- is the average monthly growth rate based on the previous year’s monthly electricity sales average.

## EIA-826 Regression Imputation with Heteroskedastic errors

## Data vs. Expectations

- Survey Sampling:

- Vs.

- Econometric Modeling:

## RE-ESTIMATED 826

- Slightly different imputation methods were used over the past 15 years
- Need to duplicate published EIA-826 historical data with a single imputation routine
- Allows for monthly data comparisons

## Oklahoma Commercial Electricity

## Microeconomic Modeling to Improve Monthly Estimates 

- Data cleaning tools (Scatterplots)
- Outlier, Influential and Add-on detection tools.
- Regional information feedback (SUR)
- Does not include Add-on assumptions since the data pools are greater and thus less market concentration need be present.
- Assumes trade happens within seasonal regions.

## Influential and Outlying Observations

- An Influential observation is such if omitting its reported value in the regression estimation would considerably influence the value of its corresponding predicted value.
**DFFITS > 2/(n^(1/2))**
- An outlying observation is such if the difference between its reported value and its predicted value is considerable.
**Studentized Residual > 3.5**

## RE-ESTIMATED 826861 and 826 Outlier and Influential Detection

- Overwrite annual  reported data identified as Outliers or Influential with imputed values (‘X’ Value)
- Overwrite monthly reported data identified as Outliers or Influential with imputed values (‘Y’ Value)
- Should have the effect of smoothing extreme imputed values and extreme monthly observations

## Colorado Industrial Sales

## ARIZONA RESIDENTIAL SALES

## RE-ESTIMATED 826826 Add-On Detection

- Makes Outlier and Influential observations Add-ons
- Reported value kept intact
- Does not affect the imputation model for non-sampled or non-respondent firms

## Iowa Industrial Sector

## SEEMINGLY UNRELATED REGRESSORS‘SUR’

- Information feedback across regressor groups.
- Provides efficient, un-biased parameter estimates.
- Utilizes more information than vector regression.

## Colorado Industrial SalesSUR Imputation Method

## New York Residential SalesSUR Imputation Method