## 2 Data Details
### Defining New Tax Incentive Variables  
From Texas Code Chapter 313, two new variables were created with which to analyze the effects that the chapter had on wholesale electricity prices in the ERCOT, stemming from renewable resources:  
* The number of wind and solar applications;
* Total Gross Tax Savings (USD). Data for these two variables came from the Texas Comptroller's website ([[https://comptroller.texas.gov/economy/local/ch313/agreement-docs.php](https://comptroller.texas.gov/economy/local/ch313/agreement-docs.php)]([https://comptroller.texas.gov/economy/local/ch313/agreement-docs.php](https://comptroller.texas.gov/economy/local/ch313/agreement-docs.php)), accessed on 15 December 2022). The database is extensive and segmented by counties and regions. Data for the two variables were carefully constructed by first searching for each project application. The website also contains inactive applications, and often these are not clearly delineated. It is important to note that useful, tax-relevant data only come from active solar and wind applications. Hence, it is necessary to remove the inactive applications in the analysis; indeed, there are no tax savings data on inactive applications. Collating all of the pertinent information into a spreadsheet, we compiled the county/regional data into state-wide data. Even though the models in Section 3 will be at the regional level, the data on the two variables is too sparse, or non-existent, in all the regions. Additionally, real-time, wholesale pricing depends on the ERCOT level load, which is sometimes powered by transmitting renewable resources across regions. Therefore, it is practically relevant to consider the number of active wind and solar applications throughout the state. Figures 3 and 4 illustrate the number of active wind and solar applications and total gross tax savings from 2015 to 2018. Applications increase each year, starting with 16 in 2015 to 23 in 2018. Increases in active applications also increase the total gross tax savings per year. Information on the total gross tax savings is unavailable for the single solar application occurring in 2017, and is therefore absent from Figure 4. The absence of non-wind renewable resources will be borne out in the more rigorous statistical analyses in Section 3. Figure 2: Panel A (**Top**): Time series of West price, Hour 11 AM. Panel B (**Middle**): Time series of West price, Hour 4 PM. Panel C (**Bottom**): Time series of West price, Hour 3 AM. Using the data corresponding to Figures 3 and 4, and dropping the time (year) factor, one can construct a scatter plot to assess the relationship between applications and tax savings. Specifically, from Figure 4, it is evident that there is a noticeable jump in savings after 2016. Hence, we plot the total number of wind applications and the corresponding total savings over the four years. Consider Figure 5, which shows the scatter plot between wind applications and tax savings. The sizeable increase in gross tax savings when the number of wind applications increases from 12 to 16 is evident. The strong association (r = 0.896) between the two variables points to the possibility of using a dummy variable to model the marginal effect of wind  
Figure 4: Gross tax savings (USD). Figure 5: Scatter plot of gross tax savings (USD) vs. wind applications. Figure 3: Active wind and solar applications. applications on the wholesale electricity price in the ERCOT, instead of using the actual count of active wind applications. Indeed, based on the preceding discussion and the analysis in the next subsection, it is infeasible to use the discrete active wind application data in the regression models detailed in Section 3. Additionally, going through a similar analysis for solar, we found a somewhat weak negative correlation (\(-0.357\)) between tax savings and solar applications. But, from a modeling perspective, one cannot ignore the effects of solar energy in Texas, since it is a growing renewable resource and is supported indirectly through PUCT Substantive Rule 25.173 (a)(1).