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We develop a model in which reward-based crowdfunding enables firms to obtain a reliable proof of concept early in their production cycle: they learn about total demand from a limited sample of target consumers preordering a new product. Learning from the crowdfunding sample creates a valuable real option because firms invest only if updated expectations about total demand are sufficiently high. This is particularly valuable for firms facing a high degree of uncertainty about consumer preferences, such as developers of innovative consumer products. Learning also enables firms to overcome moral hazard. The higher the funds raised, the lower the firms’ incentives to divert them, provided third-party platforms limit the sample size by restricting campaign length. Although the probability of campaign success decreases with sample size, the expected funds raised are maximized at an intermediate sample size. Our results are consistent with stylized facts and lead to new empirical implications. This paper was accepted by Gustavo Manso, finance.

We develop a model in which reward-based crowdfunding enables firms to obtain a reliable proof of concept early in their production cycle: they learn about total demand from a limited sample of target consumers preordering a new product. Learning from the crowdfunding sample creates a valuable real option because firms invest only if updated expectations about total demand are sufficiently high. This is particularly valuable for firms facing a high degree of uncertainty about consumer preferences, such as developers of innovative consumer products. Learning also enables firms to overcome moral hazard. The higher the funds raised, the lower the firms' incentives to divert them, provided third-party platforms limit the sample size by restricting campaign length. Although the probability of campaign success decreases with sample size, the expected funds raised are maximized at an intermediate sample size. Our results are consistent with stylized facts and lead to new empirical implications.

What determines securitization levels, and should they be regulated? To address these questions we develop a model where originators can exert unobservable effort to increase expected asset quality, subsequently having private information regarding quality when selling ABS to rational investors. Absent regulation, originators may signal positive information via junior retentions or commonly adopt low retentions if funding value and price informativeness are high. Effort incentives are below first-best absent regulation. Optimal regulation promoting originator effort entails a menu of junior retentions or one junior retention with size decreasing in price informativeness. Zero retentions and opacity are optimal among regulations inducing zero effort.

We incorporate structural modelers into the economy they model. Using traditional moment matching, they treat policy changes as zero probability (or exogenous) “counterfactuals.” Bias occurs since real-world agents understand policy changes are positive probability events guided by modelers. Downward, upward, or sign bias occurs. Bias is illustrated by calibrating the Leland model to the 2017 tax cut. The traditional identifying assumption, constant moment partial derivative sign, is incorrect with policy optimization. The correct assumption is constant moment total derivative sign accounting for estimation-policy feedback. Model agent expectations can be updated iteratively until policy advice converges to agent expectations, with bias vanishing.

This paper analyzes the interactions between competitive (wholesale) spot, retail, and forward markets and vertical integration in electricity markets. We develop an equilibrium model with producers, retailers, and traders to study and quantify the impact of forward markets and vertical integration on prices, risk premia, and retail market shares. We point out that forward hedging and vertical integration are two separate mechanisms for demand and spot price risk diversification that both reduce the retail price and increase retail market shares. We show that they differ in their impact on prices and firms' utility because of the asymmetry between production and retail segments. Vertical integration restores the symmetry between producers' and retailers' exposure to demand risk, whereas linear forward contracts do not. Vertical integration is superior to forward hedging when retailers are highly risk averse. We illustrate our analysis with data from the French electricity market. This paper was accepted by Wei Xiong, finance.

We provide new rationales for corporate venturing, based on competition for talented managers. As returns to venturing increase, firms engage in corporate venturing for reasons other than capturing these returns. First, higher venturing returns increase managerial compensation, to which firms respond by increasing incentives. Managers increase effort, prompting firms to reallocate them to new ventures, where the marginal product of effort is highest. Second, as returns to venturing become large, corporate venturing emerges as a way to recruit/retain managers who would otherwise choose alternative employment. We derive several testable empirical predictions about the determinants and structure of corporate venturing.

This paper analyzes the interactions between competitive (wholesale) spot, retail, and forward markets and vertical integration in electricity markets. We develop an equilibrium model with producers, retailers, and traders to study and quantify the impact of forward markets and vertical integration on prices, risk premia, and retail market shares. We point out that forward hedging and vertical integration are two separate mechanisms for demand and spot price risk diversification that both reduce the retail price and increase retail market shares. We show that they differ in their impact on prices and firms' utility because of the asymmetry between production and retail segments. Vertical integration restores the symmetry between producers' and retailers' exposure to demand risk, whereas linear forward contracts do not. Vertical integration is superior to forward hedging when retailers are highly risk averse. We illustrate our analysis with data from the French electricity market.

We provide new rationales for corporate venturing, based on competition for talented managers. As returns to venturing increase, firms engage in corporate venturing for reasons other than capturing these returns. First, higher venturing returns increase managerial compensation, to which firms respond by increasing incentives. Managers increase effort, prompting firms to reallocate them to new ventures, where the marginal product of effort is highest. Second, as returns to venturing become large, corporate venturing emerges as a way to recruit/retain managers who would otherwise choose alternative employment. We derive several testable empirical predictions about the determinants and structure of corporate venturing.

Shareholder agreements govern the relations among shareholders in privately held firms, such as joint ventures and venture capital-backed companies. We provide an economic explanation for key clauses in such agreements-namely, put and call options, tag-along and drag-along rights, demand and piggy-back rights, and catch-up clauses. In a dynamic moral hazard setting, we show that these clauses can ensure that the contract parties make efficient ex ante investments in the firm. They do so by constraining renegotiation. In the absence of the clauses, ex ante investment would be distorted by unconstrained renegotiation aimed at (i) precluding value-destroying ex post transfers, (ii) inducing value-increasing ex post investments, or (iii) precluding hold-out on value-increasing sales to a trade buyer or the IPO market.

Causal evidence from random assignment has been labeled \"the most credible.\" We argue it is generally incomplete in finance/economics, omitting central parts of the true empirical causal chain. Random assignment, in eliminating self-selection, simultaneously precludes signaling via treatment choice. However, outside experiments, agents enjoy discretion to signal, thereby causing changes in beliefs and outcomes. Therefore, if the goal is informing discretionary decisions, rather than predicting outcomes after forced/mistaken actions, randomization is problematic. As shown, signaling can amplify, attenuate, or reverse signs of causal effects. Thus, traditional methods of empirical finance, e.g. event studies, are often more credible/useful.