In this thesis we study characterize the dynamic relationships among two electricity
price variables (residential and commercial) and six regional economic variables in order
to examine each individual variable??s role in regional economic activity. We also answer
the question ??Do electricity prices have impact on regional economic variables???
We use two statistical techniques as engines of analysis. First, we use directed acyclic
graphs to discover how surprises (innovations) in prices from each variable are
communicated to other variables in contemporaneous time. Second, we use time series
methods to capture regularities in time lags among the series.
Yearly time series data on two electricity prices and six regional economic
variables for Montgomery County (Texas) are studied using time series methods.
Directed Acyclic Graphs (DAGs) are used to impose restrictions on the Vector Auto
Regression model (VAR). Using Innovation Accounting Analysis of the estimated
Vector Auto Regression (VAR) model we unravel the dynamic relationships between the
eight variables. We conclude that rising electricity prices have a negative impact on allregional economic variables. The commercial average electricity prices lead residential
average electricity prices in the time frame we studied (1969-2000). Rising residential
electricity prices also have a positive impact on income derived from transfer payments.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/2275 |
| Date | 29 August 2005 |
| Creators | Bethapudi, Daniel Naveen |
| Contributors | Bessler, David |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Thesis, text |
| Format | 847456 bytes, electronic, application/pdf, born digital |
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