Abstract: The rapid development of digital twins, industrial Internet systems, intelligent platforms, and artificial intelligence (AI) agents is reshaping the spatial basis and operating mechanisms of economic activity. Cyberspace has evolved from an information-transmission channel into an environment in which production, exchange, pricing, governance, and consumption can take place directly. Existing studies on the digital economy, information economics, and virtual economies explain important aspects of these changes, but a unified framework connecting digitally native economic activities with cross-space economic processes remains limited. Under the philosophical framework of Cyberism and the Cyber-Physical-Social-Thinking (CPST) four-space framework, this paper proposes two connected paradigms for the digital economy: Cyber-Economics in a narrow sense and CPST-Economics in a broad sense. The study adopts a theory-building approach based on spatial differentiation, conceptual comparison, boundary identification, and proposition construction. It distinguishes economic activities whose core rules are mainly generated within cyberspace from those whose outcomes are jointly determined by cyber, physical, social, and thinking factors, and then defines the spatial boundaries, research objects, analytical priorities, and logical relationship of the two paradigms. A key boundary criterion is established: when physical conditions, real-world institutions, and cognitive factors can be treated as exogenous constraints or boundary conditions, the problem can be analyzed within Cyber-Economics; when C, P, S, and T factors jointly and endogenously determine economic outcomes, it falls within CPST-Economics. Cyber-Economics focuses on digitally native economic activities supported by code, protocols, digital identity, and programmable rules. Its research objects include digital assets, decentralized autonomous organizations, digital currencies, programmable finance, metaverse economies, AI-generated content, attention-based platform activities, and markets involving AI agents. Four first principles are identified: “Code is Law,” “Attention Scarcity,” “Near-Zero Marginal Cost and Artificially Constructed Scarcity,” and “Algorithm as Market.” These principles explain how digitally native markets differ from conventional markets in rule formation, scarcity creation, value realization, and market organization. CPST-Economics extends the analysis to complex economic systems formed through interactions among cyber, physical, social, and thinking spaces. It examines how data and algorithms interact with material resources, institutions, social relations, human cognition, preferences, and AI-supported decision making. Four central propositions are developed: value emerges from cross-space interaction; economic actors become CPST composite agents; data and intelligent capabilities become important productive factors; and markets increasingly operate as hybrid fields jointly shaped by algorithms and institutions. The two paradigms form a progressive structure within the same theoretical system. Cyber-Economics can be regarded as a special case of CPST-Economics when analysis is mainly confined to digitally native space, while CPST-Economics broadens the scope by incorporating material, institutional, social, and cognitive dimensions. For subsequent research, digitally native settings are suitable for computable mechanism analysis, algorithmic games, multi-agent simulation, and empirical analysis of platform or on-chain data, whereas cross-space problems can further employ system dynamics, complex networks, digital-twin simulation, causal inference, and policy experiments. By defining the spatial boundaries, first principles, core propositions, and methodological directions of the dual paradigm, this paper provides a spatially grounded framework for future modeling, mechanism design, simulation, and empirical testing of CPST complex economic systems.