Building a sustainable modern electricity sector is a key part of the United Nations' 2030 Sustainable Development Goals. Smart meters are expected to contribute to the achievement of this goal by providing new demand-side management opportunities for utilities. Attempting to address existing gaps in the extant literature, this paper examines the effects of metering technologies and demand-side management program investments using panel data from 87 American electricity utilities for the period 2009-2012. Our model provides strong explanatory power with respect to energy efficiency, and shows that automated meter reading (AMR) devices, advanced metering infrastructure (AMI) devices, direct program costs and incentive costs all have a positive influence on energy efficiency effects. In contrast, the results for load management are largely insignificant, with the exception of incentive costs which has a small, but significant, negative impact on peak load reductions. We discuss the implications and potential research directions arising from these findings, in particular the need to consider interactions between different demand-side programs and the influence of different types of information technologies that are emerging as part of the smart grid. Managerial Relevance Statement Panel data analysis is performed to investigate the impacts of smart metering and program financial investments on energy demand management by the US electricity sector. Unlike most existing studies on smart grid implementation which utilize cross-sectional data, the use of panel data in this research allow for the identification of impacts of the smart grid technology by observing the performances of the same utilities over time. Decision makers can then input their specific characteristics, such as numbers of different meters types and their level of investment, to understand and determine what benefits could be expected given a certain level of technology implementation or financial investment. Our research also leads to a number of analytical results which are different from those in the existing literature. In particular, we show that automated meter reading devices, advanced metering infrastructure devices, direct program costs and incentive costs all have a positive influence on energy efficiency effects, but not on load reductions. We also discuss the importance for decision makers to consider the interactions between different types of demand-side initiatives in conjunction with transformations occurring on the supply-side as well as the continuing innovation in smart grid technologies in use by intermediary organizations and consumers.