Research
- Political Connections, Growth and Firm Network Full text (PDF)
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This study revisits the role of political connections (PC) in shaping firm outcomes in weak institutional environments. Using a panel of publicly listed Indonesian firms from 2002 to 2019, we construct a continuous, power-weighted political connection score and apply a dynamic panel model to examine how PC influences firm growth, credit access, and performance. We find that stronger political ties are associated with higher asset growth, sales, and leverage. However, these effects diminish once we account for firms’ embeddedness in inter-firm networks. This fading effect points to a novel and less studied channel: political connections may improve firm outcomes by facilitating access to business networks that substitute for underdeveloped formal institutions. Rather than working solely through direct state access or rent distribution, PC appears to help firms overcome market frictions by enabling informal governance through peer connectivity. Furthermore, our network analysis reveals that the benefits of political connections for size and growth are more pronounced among firms with initially weaker access to business networks, suggesting higher marginal returns to political capital for more peripheral firms.
- Contested Unity Full text (PDF)
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National identity occupies a paradoxical role in society, functioning as both a unifying force and a source of division. This paper develops a dynamic political economy model of identity regime formation, emphasizing interactions among citizen groups and between citizens and the wealthy elite. The framework conceptualizes national identity as the evolving result of intergenerational cultural transmission and intra-societal bargaining over public goods and redistribution. The model incorporates two forms of heterogeneity: ideological divides among citizens in valuing public goods, and income-based stratification between the broader citizenry and a wealthy elite. It shows that when the provision of common goods increases the likelihood of future integration, citizens may paradoxically underinvest in such goods due to imperfect empathy toward future generations. Furthermore, ideologically neutral elite actors may strategically suppress integration to avoid long-term tax burdens, even when short-run integration would reduce their tax rate. The model also generates multiple equilibria, offering a taxonomy of exclusive, multicultural, and integrated identity regimes.
- Nation-State Building Full text (PDF)
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We develop a simple dynamic theory of Nation-States in which Elites choose investments in both State-building and Nation-building. In our approach nation-building works towards homogenization of citizens by making it easier for them to coordinate and demand for more frequent redistributions. A more coordinated citizenry will accept lower transfers in the current period, making it possible for the Elites to pacify their threats. Our mechanism puts the emphasis on social conflicts rather than external threats in the emergence of nation-building investments. It also highlights the role of nation-building in changing the (coordination) technology rather than altering the preferences and indoctrinating the citizens. We define state capacity with its role in lowering the cost of redistribution and show how investments in nation-building can incentivize the Elite to further invest in state-building. Nation-State building is thus embodiment of this complementarity.
- Graph-embedded reinforcement learning for dynamic pricing under network effects Full text (PDF)
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Firms increasingly rely on both price discounts and advertising campaigns to shape product diffusion in socially connected markets, yet existing models rarely treat these levers jointly or account for network heterogeneity. This study develops an integrated, network-aware framework for dynamic pricing and advertising control. A stochastic compartmental model of the CDM is formulated on a social graph, with transition intensities modulated by price, advertising spend, and peer influence. A deterministic mean-field approximation yields closed-form expressions for a TFE and a reproduction number threshold that delineates when adoption dies out versus persists. Building on this analytical core, the paper introduces TD3ES, a RL controller that couples an actor-critic architecture with a graph-convolutional autoencoder, thereby compressing high-dimensional network states into a tractable latent representation. A custom GPU-accelerated simulator facilitates large-scale training. Numerical experiments on Erdős-Rényi and heavy-tailed exponential networks show that TD3ES swiftly converges to profit-maximizing joint policies and, on heterogeneous graphs, outperforms a TD3 baseline that lacks network-structural information. Error analysis reveals that the autoencoder naturally prioritizes high-degree hubs in dominant CDM compartments, explaining its superior performance. Managerially, the results demonstrate that ignoring topology can forfeit substantial revenue and that adaptive, network-aware coordination of price and advertising is both feasible and valuable. The framework thus unites rigorous diffusion theory with scalable learning, offering a practical tool for data-driven marketing in connected consumer ecosystems.