A salient observation during the COVID-19 Pandemic is that theft has been reduced throughout the United States. The objective of this research is to determine if this reduction was heterogeneous across location categories: Nonessential and Essential businesses, Public Buildings, Transportation, Residences, and Streets. Data from the Chicago Data Portal is used to measure the amount of daily theft in the city from January 1st 2018 to November 30rd 2020. The response variables are standardized using their respective pre-pandemic mean and standard deviations. A identical segmented regression is specified for the response variables and the Pandemic is coded as a dummy variable. The six location categories are modeled as a system using seemingly unrelated regression. A chi squared statistic of a the Wald Test is applied pair-wise to determine if their was a statistically significant difference in coefficient estimates across restricted and unrestricted regression equations. Overall, the all location categories experienced a decline in theft between 0.58 and 2.59 standard deviations below their mean values. The results indicate that the Pandemic was associated with a disproportionate decline in theft at both essential and nonessential businesses, where the latter had deviated from it’s average by 2.59 standard deviations during the Pandemic. Residences, Public Buildings, and Streets had a similar deviation in theft. The results align with Routine Activities Theory, which predicts that the impact of the Pandemic on daily routines would disrupt the interaction between criminal and victim (or their property), resulting in fewer incidences of crime. Further research is needed to determine if these results generalize to other cities in the United States. A clear definition of the Pandemic is needed in the literature to further identify how the Pandemic impacted criminal behavior.