Daria Matviienko

Most corporate lobbying in the US serves two distinct goals: affecting a firm's own tax or regulatory burden mostly through variable costs (own-benefit lobbying) and changing industry-wide regulation through fixed costs (barrier lobbying). The two activities have opposite competitive and welfare implications, and firms in practice do both. We study their welfare consequences, combining an empirical analysis of the corporate lobbying portfolio with a structural model disciplined by it. Using an LLM-based classification of all LDA lobbying reports and Congressional bills, merged with Compustat, we decompose the lobbying portfolio along three dimensions: direction (pro- vs. anti-regulation), cost type (fixed vs. variable), and scope (narrow, firm-specific vs. broad, industry-wide). We find that within industries, larger firms lobby to raise industry-wide regulatory fixed costs, while smaller firms lobby to lower them. Additionally, large firms lobby mostly individually rather than through associations, consistent with lobbying being a strategic decision. To rationalize these patterns, we introduce endogenous lobbying into a dynamic general-equilibrium model of oligopolistic competition and innovation. Each industry consists of a small number of strategic superstar firms and a continuum of atomistic fringe firms, competing over output, R&D, and the two lobbying instruments. Superstars choose both strategically, internalizing how barrier lobbying affects fringe entry and exit; fringe firms lobby on fixed costs only through a trade association subject to an Olson-style coordination cost. Equilibrium regulation is determined by a Becker–Mulligan influence contest, and the model reproduces the empirical relationship between size and lobbying direction. Calibrated to US data, lobbying imposes a welfare loss of approximately 3.6% of lifetime consumption, operating almost entirely through reduced long-run growth as barrier lobbying shifts industries toward more concentrated states with less entry and innovation. Removing the barrier lobbying alone recovers the entire loss.

We study the role of preference heterogeneity in mortgage defaults, focusing on how differences in time preferences, intertemporal elasticity of substitution, and belief distortions shape household financial behavior. Using microdata from the PSID and a structural lifecycle model with endogenous housing, saving, and default decisions, we quantify the contribution of ex ante differences between households: discount factor heterogeneity, present bias, and income expectation errors, and ex post: income realizations to foreclosure risk. The model, estimated using the Simulated Method of Moments, matches empirical moments on asset accumulation and homeownership without directly targeting foreclosure rates. We find that lower patience and persistent hand-to-mouth behavior substantially increase default risk, even among above-water borrowers. Counterfactual exercises decompose the drivers of default, and policy simulations evaluate the welfare effects of behaviorally informed mortgage interventions. We show that commitment-based liquidity buffers can reduce defaults while maintaining neutrality for prudent agents. Our findings underscore the importance of incorporating behavioral heterogeneity into models of household finance and mortgage design.

This paper addresses the disconnect between the macroeconomic literature on green transition and finance literature focusing on sustainable investing by funds and individual investors, and green-asset purchases by central banks. It explores the impact of changing the cost of capital for firms engaged in both dirty and clean production, aiming to bridge gaps between these two strands of literature. The study delves into the uncertainties of ESG investing outcomes, particularly the drawbacks of increasing the cost of capital for dirty firms. Two main challenges emerge: there is an empirical finding that higher capital costs for brown firms lead to increased pollution and evidence that dirty companies can contribute to high-quality green innovations. It aims to test the hypothesis that elevating the cost of capital for multiproduct firms engaged in both dirty and clean production may hinder green innovation and slow the green transition. It develops a parsimonious perfect-foresight general equilibrium model with directed technical change to evaluate the effects of change in the cost of capital on emissions and innovation. In the context of multiproduct firms involved in both dirty and clean production and innovation, I show that while a rise in dirty input taxes and a rise in a clean research subsidy reduces emissions, an increase in the cost of capital yields an ambiguous outcome: it amplifies existing technology advancement. The direction of change from this policy depends on the initial relation of productivities of clean and dirty innovation. Thus, if the productivity of the dirty innovation is higher than that of the clean one, an increase in the cost of capital makes firms focus more on dirty innovation, potentially disrupting the green transition. Thus, green-asset purchases by the central banks and ESG investing strategies should be based not just on the ESG score or emissions intensity of the company, but also on the degree of substitution of clean and dirty production and innovation advancement of sectors and the structure of the innovation process.