CHEMLA Gilles

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.

Building parable economies embedding econometricians, we view alternative estimators (IV, fuzzy RD, natural experiments, OLS, event studies) from the perspective of privately-informed decision-makers, e.g. CFOs. IV estimates can be misleading since randomization through observable instruments eliminates signal content arising from discretion. If the goal is informing discretionary decisions, rather than predicting outcomes after forced/mistaken actions, instrumentation is problematic, whereas OLS or event studies can be sufficient. The analysis shows the utility of alternative estimators hinges upon oft-neglected assumptions about agent/econometrician information sets, as distinct from exclusion restrictions. We recommend parable economy estimation as precursor to real-world IV estimation.

While firms have obtained outside financing from large numbers of investors on financial markets for centuries, online crowdfunding platforms have only emerged as a major source of funding for start-ups and new projects for a decade. The information available to backers on crowdfunding platforms is generally coarse. This paper surveys the existing literature on the extent to which crowdfunding harnesses the wisdom of crowds. We discuss two broad categories of crowdfunding. Reward-based crowdfunding platforms such as Kickstarter, where backers typically have private and independent valuations, appear to offer environments favorable to the wisdom of crowds. In contrast, initial coin offerings (ICOs) offering services with network externalities and security-based platforms with common values appear to exhibit some results eliciting valuable information, but several results appear to point to informational cascades.

This thesis analyzes the financing contracts used by venture capital funds, the waves of investments made and the use of bridge loans. The first chapter presents a theoretical model of financing contracts. This model proposes a contract that offers more profit to the entrepreneur in order to create a less conflictive relationship, although the entrepreneur initially has more bargaining power. Most equity funds claim to make the initial investment in a company based on the analysis of the founding team and the size of the company's target market. By analyzing venture capital fund investments, we have been able to highlight the existence of waves of venture capital fund investments, similar to waves of mergers and acquisitions. The second chapter of this thesis analyzes the effects caused by these investment waves and the impact of the syndicate network on the success rate of the investments. We show that the investment syndicate network impacts the investment success rate. In the last chapter of this thesis, an analysis of the use of bridging loans was conducted due to its relatively high use by venture capital funds. The analysis showed that companies financed by bridging loans have low success rates (0.7%) and that venture capital funds using this type of instrument have a lower success rate in raising a new venture capital fund.

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.

Policy experiments using large microeconomic datasets have recently gained ground in macroeconomics. Imposing rational expectations, we examine robustness of evidence derived from ideal natural experiments applied to atomistic agents in dynamic settings. Paradoxically, once experimental evidence is viewed as sufficiently clean to use, it then becomes contaminated by ex post endogeneity: Measured responses depend upon priors and the objective function into which evidence is fed. Moreover, agents’ policy beliefs become endogenously correlated with their causal parameters, severely clouding inference, e.g. sign reversals and non-invertibility may obtain. Treatment-control differences are contaminated for non-quadratic adjustment costs. Constructively, we illustrate how inference can be corrected accounting for feedback and highlight factors mitigating contamination.

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Over the centuries, financial institutions have shaped the financial landscape and influenced economic activity. The objective of this thesis is to highlight, from a theoretical point of view, the fundamental limitations of modern institutions and to deduce the implications for the future role of these institutions.The first chapter proposes an analysis of clearing houses. Following the financial crisis of 2008, financial authorities around the world have implemented regulations imposing central clearing on most derivatives. We show that central clearing requires a higher level of liquidity than bilateral clearing.The second chapter presents a continuous time learning model that is supposed to represent the learning process of an institution with respect to a hidden information held by the market. The last chapter introduces and analyzes the Lightning Network which is a payment network based on the Blockchain. It allows users to transfer value instantly without the need for a trusted third party. We discuss the implications about the structure of this payment network as well as its ability to take an important place in the financial landscape.

We develop a formal model of placebo effects. If subjects in seemingly-ideal single-stage RCTs update beliefs about breakthroughs based upon personal physiological responses, mental effects differ across medications received, treatment versus control. Consequently, the average cross-arm health difference becomes a biased estimator. Constructively, we show: bias can be altered through choice of control. higher-efficacy controls mitigate upward bias. and efficacy states can be revealed through controls of intermediate efficacy or controls that mimic a subset of efficacy states. Consistent with experimental evidence, our theory implies outcomes within-arm and cross-arm differences can be non-monotone in treatment probability. Finally, we develop novel differences-in-differences and triangle equality tests to detect RCT bias.

This thesis explores the implications for corporate finance of the growing importance of intangible capital in determining the competitive advantage of firms. In the first chapter (with C. Lenoir, CREST), we show that insufficient access to short-term financing is an obstacle to the development of firms' customer base. In the second chapter (with T. Libert of PSE and C. Hurlin of Université d'Orléans), we analyze the effects of under-diversification of banks' borrower bases. Our results indicate that concentration exposes lenders to the idiosyncratic risk of their borrowers and that it leads to a greater synchronization of credit flows between banks. In the third chapter (with V. Lyonnet of OSU and C. Hebert of Paris Dauphine/Tilburg U.), we show that firms use M&A to acquire specialized human capital when external hiring is too costly.

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This thesis aims to determine and estimate the costs of intermediation and the externalities it generates. The advent of big data and AI is reshaping financial intermediation. Its benefits in terms of speed and costs are visible, but its impact remains poorly understood. I show that these technologies can increase financial frictions as well as the costs of financial intermediation. The 2008 financial crisis revealed the importance of liquidity problems. I provide a theoretical framework to understand the consequences of banking regulations on banks' liquidity problems. It reveals a new trade-off between capital and liquidity requirements. Finally, the costs and externalities of intermediation are studied in the context of international trade. For geographical reasons, some countries are dependent on having their goods transit through intermediary countries. This friction is analyzed theoretically and estimated empirically. Countries that appear to be unaffected (such as the United Kingdom) suffer from the price-distorting effects of this problem.

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We develop a model where reward-based crowdfunding enables firms to obtain a reliable proof of concept early in their production cycle. The information gathered from a subsample of backers through a fixed length pre-selling campaign enables firms to update their beliefs about the preferences of all future consumers. This creates a valuable real option as firms invest only if updated demand is high. Further, such updating mitigates moral hazard: the higher the funds raised, the lower the firms' incentives to divert them. Our results are consistent with stylized facts and provide new testable implications.

No summary available.

We examine optimal supply of safe government bonds accounting for their effect on corporate debt markets. Government bonds are shown to influence leverage under asymmetric information regarding corporate cash flows and safe asset scarcity. Corporations have incentives to issue junk debt in response to safe asset scarcity since uninformed investors then migrate to junk debt markets. Uninformed demand stimulates informed speculation which drives junk debt prices closer to fundamentals, encouraging pooling at high leverage. Acting as borrower of first resort, the government can issue safe bonds which siphon off uninformed demand for risky corporate debt and reduce socially wasteful informed speculation. Thus, government bonds either eliminate pooling at high leverage or improve risk sharing in such equilibria. An optimal supply of government bonds is increasing in both marginal Q and the intrinsic demand for safe assets.

In an economic environment that is increasingly competitive, tense and uncertain, companies must demonstrate adaptability, precaution and anticipation. This manuscript addresses several themes related to this observation, which closely touch the notion of cash management. The first essay of this thesis shows that the distribution of a stock dividend allows firms to temporarily reduce the remuneration of their shareholders, without being sanctioned by the latter. This mechanism allows firms to maintain liquidity and flexibility in times of economic contraction. The second essay deals with the link between customer risk and liquidity management policy. Increased customer risk seems to push firms to hold more cash and to use credit lines less. Finally, the third essay justifies the interest of establishing long-term customer-supplier relationships. These partnerships appear to be a source of increased efficiency and profitability in the operational cycle of companies.

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What determines equilibrium securitization levels, and should they be regulated? To address these questions we develop a model where originators can exert unobservable effort to increase asset quality, subsequently having private information regarding quality when selling ABS to rational investors. In equilibrium, all originators have low/zero retentions if they are financially constrained and/or prices are su¢ ciently informative. Asymmetric information lowers effort incentives in all equilibria. Effort is promoted by junior retentions, investor sophistication, andinformative prices. Optimal regulation promotes effort while accounting for investor-level externalities. It entails either a menu of junior retentions or a single junior retention with sizedecreasing in price informativeness. Mandated market opacity is only optimal amongst regulations failing to induce originator effort.