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This paper uses unique administrative data and a quasi-field experiment of exogenous allocation in Sweden to estimate medium- and longer-run effects on financial behavior from exposure to financially literate neighbors. It contributes evidence of causal impact of exposure and of a social multiplier of financial knowledge, but also of unfavorable distributional aspects of externalities. Exposure promotes saving in private retirement accounts and stockholding, especially when neighbors have economics or business education, but only for educated households and when interaction possibilities are substantial. Findings point to transfer of knowledge rather than mere imitation or effects through labor, education, or mobility channels.
The authors present evidence of a new propagation mechanism for wealth inequality, based on differential responses, by education, to greater inequality at the start of economic life. The paper is motivated by a novel positive cross-country relationship between wealth inequality and perceptions of opportunity and fairness, which holds only for the more educated. Using unique administrative micro data and a quasi-field experiment of exogenous allocation of households, the authors find that exposure to a greater top 10% wealth share at the start of economic life in the country leads only the more educated placed in locations with above-median wealth mobility to attain higher wealth levels and position in the cohort-specific wealth distribution later on. Underlying this effect is greater participation in risky financial and real assets and in self-employment, with no evidence for a labor income, unemployment risk, or human capital investment channel. This differential response is robust to controlling for initial exposure to fixed or other time-varying local features, including income inequality, and consistent with self-fulfilling responses of the more educated to perceived opportunities, without evidence of imitation or learning from those at the top.
The authors identify U.S. monetary and fiscal dominance regimes using machine learning techniques. The algorithms are trained and verified by employing simulated data from Markov-switching DSGE models, before they classify regimes from 1968-2017 using actual U.S. data. All machine learning methods outperform a standard logistic regression concerning the simulated data. Among those the Boosted Ensemble Trees classifier yields the best results. The authors find clear evidence of fiscal dominance before Volcker. Monetary dominance is detected between 1984-1988, before a fiscally led regime turns up around the stock market crash lasting until 1994. Until the beginning of the new century, monetary dominance is established, while the more recent evidence following the financial crisis is mixed with a tendency towards fiscal dominance.
This paper examines the sustainability of the currency board arrangements in Argentina and Hong Kong. We employ a Markov switching model with two regimes to infer the exchange rate pressure due to economic fundamentals and market expectations. The empirical results suggest that economic fundamentals and expectations are key determinants of a currency board’s sustainability. We also show that the government’s credibility played a more important role in Argentina than in Hong Kong. The trade surplus, real exchange rate and inflation rate were more important drivers of the sustainability of the Hong Kong currency board.
Distributed ledger technology especially in the form of publicly coordinated validation networks such as Ethereum and Bitcoin with their own monetary circles provide for a revealing litmus test for current financial regulatory schemes. The paper highlights the interrelation between distributed coordination and the emission of virtual currency to make sense of the function of the new monetary phenomenon. It then argues for the regulation of financial services on the ground of the technology to ensure integrity standards. In this respect, it is useful to gear the development of a regulatory scheme towards the existing financial regulatory principles. However, future measures of the regulators must take the distributed nature of the platforms into account by relying on a “regulated self-regulation” of the community. Finally, the article focuses on the shortcomings of the current EU regulatory regimes, especially the regulation frameworks regarding financial services, payment services and electronic money.
Our paper evaluates recent regulatory proposals mandating the deferral of bonus payments and claw-back clauses in the financial sector. We study a broadly applicable principal agent setting, in which the agent exerts effort for an immediately observable task (acquisition) and a task for which information is only gradually available over time (diligence). Optimal compensation contracts trade off the cost and benefit of delay resulting from agent impatience and the informational gain. Mandatory deferral may increase or decrease equilibrium diligence depending on the importance of the acquisition task. We provide concrete conditions on economic primitives that make mandatory deferral socially (un)desirable.
This paper applies structure preserving doubling methods to solve the matrix quadratic underlying the recursive solution of linear DSGE models. We present and compare two Structure-Preserving Doubling Algorithms ( SDAs) to other competing methods – the QZ method, a Newton algorithm, and an iterative Bernoulli approach – as well as the related cyclic and logarithmic reduction algorithms. Our comparison is completed using nearly 100 different models from the Macroeconomic Model Data Base (MMB) and different parameterizations of the monetary policy rule in the medium scale New Keynesian model of Smets and Wouters (2007) iteratively. We find that both SDAs perform very favorably relative to QZ, with generally more accurate solutions computed in less time. While we collect theoretical convergence results that promise quadratic convergence rates to a unique stable solution, the algorithms may fail to converge when there is a breakdown due to singularity of the coefficient matrices in the recursion. One of the proposed algorithms can overcome this problem by an appropriate (re)initialization. This SDA also performs particular well in refining solutions of different methods or from nearby parameterizations.
This paper considers a firm that has to delegate to an agent, such as a mortgage broker or a security dealer, the twin tasks of approaching and advising customers. The main contractual restriction, in particular in light of related research in Inderst and Ottaviani (2007), is that the firm can only compensate the agent through commissions. This standard contracting restriction has the following key implications. First, the firm can only ensure internal compliance to a "standard of sales", in terms of advice for the customer, if this standard is not too high. Second, if this is still feasible, then a higher standard is associated with higher, instead of lower, sales commissions. Third, once the limit for internal compliance is approached, tougher regulation and prosecution of "misselling" have (almost) no effect on the prevailing standard. Besides having practical implications, in particular on how to (re-)regulate the sale of financial products, the novel model, which embeds a problem of advice into a framework with repeated interactions, may also be of separate interest for future work on sales force compensation. JEL Classification: D18 (Consumer Protection), D83 (Search; Learning; Information and Knowledge), M31 (Marketing), M52 (Compensation and Compensation Methods and Their Effects).
This paper presents a novel model of the lending process that takes into account that loan officers must spend time and effort to originate new loans. Besides generating predictions on loan officers’ compensation and its interaction with the loan review process, the model sheds light on why competition could lead to excessively low lending standards. We also show how more intense competition may fasten the adoption of credit scoring. More generally, hard-information lending techniques such as credit scoring allow to give loan officers high-powered incentives without compromising the integrity and quality of the loan approval process. The model is finally applied to study the implications of loan sales on the adopted lending process and lending standard.
We present a simple model of personal finance in which an incumbent lender has an information advantage vis-a-vis both potential competitors and households. In order to extract more consumer surplus, a lender with sufficient market power may engage in "irresponsible"lending, approving credit even if this is knowingly against a household’s best interest. Unless rival lenders are equally well informed, competition may reduce welfare. This holds, in particular, if less informed rivals can free ride on the incumbent’s superior screening ability.
This paper presents a novel model of the lending process that takes into account that loan officers must spend time and effort to originate new loans. Besides generating predictions on loan officers’ compensation and its interaction with the loan review process, the model sheds light on why competition could lead to excessively low lending standards. We also show how more intense competition may fasten the adoption of credit scoring. More generally, hard-information lending techniques such as credit scoring allow to give loan officers high-powered incentives without compromising the integrity and quality of the loan approval process.
We analyze how two key managerial tasks interact: that of growing the business through creating new investment opportunities and that of providing accurate information about these opportunities in the corporate budgeting process. We show how this interaction endogenously biases managers toward overinvesting in their own projects. This bias is exacerbated if managers compete for limited resources in an internal capital market, which provides us with a novel theory of the boundaries of the firm. Finally, managers of more risky and less profitable divisions should obtain steeper incentives to facilitate efficient investment decisions.
We consider an imperfectly competitive loan market in which a local relationship lender has an information advantage vis-à-vis distant transaction lenders. Competitive pressure from the transaction lenders prevents the local lender from extracting the full surplus from projects, so that she inefficiently rejects marginally profitable projects. Collateral mitigates the inefficiency by increasing the local lender’s payoff from precisely those marginal projects that she inefficiently rejects. The model predicts that, controlling for observable borrower risk, collateralized loans are more likely to default ex post, which is consistent with the empirical evidence. The model also predicts that borrowers for whom local lenders have a relatively smaller information advantage face higher collateral requirements, and that technological innovations that narrow the information advantage of local lenders, such as small business credit scoring, lead to a greater use of collateral in lending relationships. JEL classification: D82; G21 Keywords: Collateral; Soft infomation; Loan market competition; Relationship lending
This paper shows that active investors, such as venture capitalists, can affect the speed at which new ventures grow. In the absence of product market competition, new ventures financed by active investors grow faster initially, though in the long run those financed by passive investors are able to catch up. By contrast, in a competitive product market, new ventures financed by active investors may prey on rivals that are financed by passive investors by “strategically overinvesting” early on, resulting in long-run differences in investment, profits, and firm growth. The value of active investors is greater in highly competitive industries as well as in industries with learning curves, economies of scope, and network effects, as is typical for many “new economy” industries. For such industries, our model predicts that start-ups with access to venture capital may dominate their industry peers in the long run. JEL Classifications: G24; G32 Keywords: Venture capital; dynamic investment; product market competition
We study a model of “information-based entrenchment” in which the CEO has private information that the board needs to make an efficient replacement decision. Eliciting the CEO’s private information is costly, as it implies that the board must pay the CEO both higher severance pay and higher on-the-job pay. While higher CEO pay is associated with higher turnover in our model, there is too little turnover in equilibrium. Our model makes novel empirical predictions relating CEO turnover, severance pay, and on-the-job pay to firm-level attributes such as size, corporate governance, and the quality of the firm’s accounting system.
This paper argues that banks must be sufficiently levered to have first-best incentives to make new risky loans. This result, which is at odds with the notion that leverage invariably leads to excessive risk taking, derives from two key premises that focus squarely on the role of banks as informed lenders. First, banks finance projects that they do not own, which implies that they cannot extract all the profits. Second, banks conduct a credit risk analysis before making new loans. Our model may help understand why banks take on additional unsecured debt, such as unsecured deposits and subordinated loans, over and above their existing deposit base. It may also help understand why banks and finance companies have similar leverage ratios, even though the latter are not deposit takers and hence not subject to the same regulatory capital requirements as banks.
This article shows that investors financing a portfolio of projects may use the depth of their financial pockets to overcome entrepreneurial incentive problems. Competition for scarce informed capital at the refinancing stage strengthens investors’ bargaining positions. And yet, entrepreneurs’ incentives may be improved, because projects funded by investors with ‘‘shallow pockets’’ must have not only a positive net present value at the refinancing stage, but one that is higher than that of competing portfolio projects. Our article may help understand provisions used in venture capital finance that limit a fund’s initial capital and make it difficult to add more capital once the initial venture capital fund is raised. (JEL G24, G31)
This paper shows that investors financing a portfolio of projects may use the depth of their financial pockets to overcome entrepreneurial incentive problems. Competition for scarce informed capital at the refinancing stage strengthens investors’ bargaining positions. And yet, entrepreneurs’ incentives may be improved, because projects funded by investors with “shallow pockets” must have not only a positive net present value at the refinancing stage, but one that is higher than that of competing portfolio projects. Our paper may help to understand provisions used in venture capital finance that limit a fund’s initial capital and make it difficult to add more capital once the initial venture capital fund is raised.