A Continuous-Time Optimal Insurance Design with Costly Monitoring

We provide a theoretical and numerical framework to study optimal insurance design under asymmetric information. We consider a continuous-time model where neither the efforts nor the outcome of an insured firm are observable to an insurer. The insured may then cause two interconnected information problems: moral hazard and fraudulent claims. We show that, when costly monitoring is available, an optimal insurance contract distinguishes the one problem from the other. Furthermore, if the insured’s downward-risk aversion is weak and if the participation constraint is not too tight, then a higher level of the monitoring technology can mitigate both problems.     

Genetic Testing,Insurance Economics,and Societal Responsibility

Three major perspectives emerge when the discussion of the implications of genetic testing on the insurance industry commences. One viewpoint, strongly advocated by certain consumer groups and ethicists on the basis of societal responsibility, categorically denies any necessity for connecting the results of genetic testing and issuance of insurance. By contrast, the insurance industry, upon examining the economics and dynamics of participation in voluntary insurance markets, lives in fear of a world filled with asymmetrical information (counter to the axioms for competitive markets), adverse selection (action by the insured as a result of asymmetric information to the perceived economic disadvantage of the insurer), and ultimately even the possibility of potential market failure or insurance company insolvency. An actuarial perspective considering the benefits (to the insurer) of this new genetic information concentrates primarily on the possibility of developing improved quantitative assessments of risk and better calculations of the actuarial present value of future loss costs based on the new statistically significant information gained from genetic testing. The strengths and weaknesses and facts and fallacies of each of these perspectives are examined in this paper, and potential solutions to the ultimate role of genetic testing in insurance underwriting and rate making are considered from the perspectives of the major players in this debate.     

Testing for explosive bubbles in the presence of autocorrelated innovations

We analyze an empirically important issue with recursive right-tailed unit root tests for bubbles in asset prices. First, we show that serially correlated innovations, which is a feature that is present in most financial series used to test for bubbles, can lead to severe size distortions when using either fixed or automatic (based on information criteria) lag-length selection in the auxiliary regressions underlying the test. Second, we propose a sieve-bootstrap version of these tests and show that this results in tests which control size well across a number of simulation designs both with and without highly autocorrelated innovations. We also find that these improvements in size come at a relatively low cost for the power of the tests. Finally, we apply the bootstrap tests on the housing market of OECD countries, and generally find much weaker evidence of housing bubbles compared to existing evidence.     

CDS as insurance: Leaky lifeboats in stormy seas

What market features of financial risk transfer exacerbate counterparty risk? To analyze this, we formulate a model which elucidates important differences between financial risk transfer and traditional insurance, using the example of Credit Default Swaps (CDS). We allow for (heterogeneous) insurer insolvency, which captures the possibility that relatively risky counterparties may exist in the market. Further, we find that stable insurers become less stable as the price of the contract decreases. The analysis includes insured parties that have heterogeneous motivations for purchasing CDS. For example, some may own the underlying asset and purchase CDS for risk management, while others buy these contracts purely for trading purposes. We show that traders will choose to contract with less stable insurers, resulting in higher counterparty risk in this market relative to that of traditional insurance; however, a regulatory policy that removes traders can, perversely, cause stable counterparties to become less stable. We conclude with two extensions of the model that consider a Central Counterparty (CCP) arrangement and the consequences of asymmetric information over insurer type.     

Moral hazard,adverse selection,and health expenditures: A semiparametric analysis

Theoretical models predict asymmetric information in health insurance markets may generate inefficient outcomes due to adverse selection and moral hazard. However, previous empirical research has found it difficult to disentangle adverse selection from moral hazard in health care consumption. We propose a two‐step semiparametric estimation strategy to identify and estimate a canonical model of asymmetric information in health care markets. With this method, we can estimate a structural model of demand for health care. We illustrate this method using a claims‐level data set with confidential information from a large self‐insured employer. We find significant evidence of moral hazard and adverse selection.     

Asymmetric Information in the IPO Aftermarket

Using the adverse selection component of the spread as a measure of asymmetric information, we investigate how asymmetric information evolves after firms go public. We find that the level of asymmetric information is lower immediately after the initial public offering (IPO) compared with its level after a period of seasoning. In addition, we test the hypothesis that the greater the underpricing of an IPO, the more information is produced in its aftermarket, and the lower the aggregate level of asymmetric information. Our results are consistent with the hypothesis and are robust after controlling for other factors.     

Does a change in the information environment affect labor adjustment costs?

We consider how a firm's information environment impacts an index of three proxies for the costs it incurs when adjusting its workforce. We show firms with less information asymmetry have lower labor adjustment costs (LACs). Moreover, this relation is stronger for firms with lower financing constraints and stronger financial performance and growth, which suggests these attributes are particularly appealing to employees. Our difference-in-difference tests based on two exogenous asymmetric information shocks around broker mergers and closures, and decimalization indicate the link is likely causal. Finally, we show that LACs are an important channel through which information asymmetry impacts firm value.     

Who Obtains Greater Discounts on Automobile Insurance Premiums?

Insurance purchasers obtain varied discounts for insurance. This paper examines what drives these differences, specifically whether the loss probability and the wealth of the insured affect the size of the premium discount in automobile insurance. To describe a bargain between a client and an insurer over premiums and coverage, we first develop a sequential insurance bargaining game where the client has an outside option to bargain with another insurer. We find that the equilibrium involves full coverage and, based on the results of comparative statics, we propose hypotheses regarding the effects of the loss probability and the wealth of the insured on the size of the premium discount. We then use a unique data set of 85,806 observations of Taiwanese automobile liability insurance for property damage to empirically test the predictions. After controlling for underwriting and macroeconomic variables, we find that both (1) the insured with a lower claim probability (as a proxy for the insured with a lower loss probability) and (2) the insured with a higher salvage value car (as a proxy for the wealthier insured) receive a greater premium discount. These results support our theoretical results.     

The effect of asymmetric information on product market outcomes

We explore how asymmetric information in financial markets affects outcomes in product markets. Difference-in-difference tests around brokerage house merger/closure events (which increase asymmetric information through reductions in analyst coverage) indicate worse industry-adjusted sales growth for shocked firms than for their peers. Our results are consistent with Bolton and Scharfstein's (1990) tradeoff between investor agency concerns and predation risk. Further support is found in stronger treatment effects among firms with ex ante greater agency concerns, financing constraints, asymmetric information, and those operating in ex ante more competitive (fluid) product market spaces. Our results are concentrated in industries where we can clearly identify either net firm entry or exit.     

A comparison of statistical tests for the adequacy of a neural network regression model

An integral part of econometric practice is to test the adequacy of model specifications. If a model is adequately specified, it should not leave interesting features of the data-generating process in the errors. Despite the common tradition, the importance of diagnostic checking as a safeguard against mis-specification has only recently been recognized by neural network (NN) practitioners, possibly because this type of semi-parametric methodology was not originally designed for economic and financial applications. The purpose of this paper is to compare a number of analytical statistical testing procedures suitable to diagnostic checking on a neural network regression model. We present the standard Lagrange multiplier (LM) testing framework designed under the assumption of identically distributed disturbances and also examine two modifications that are robust to heteroskedasticity in errors. One modification also gives the researcher an opportunity to incorporate information concerning the volatility structure of the data-generating process in the testing procedure. By means of a Monte Carlo simulation, we investigate the performance of these tests under GARCH-type heteroskedasticity in errors and various distributional assumptions. The results show that although the primary concern of the researcher may be to design a regression model that accurately captures relations in the mean of the conditional distribution, developing a good approximation of the underlying volatility structure generally increases the efficiency of tests in detecting non-adequacy of a NN model.     

Symmetric and asymmetric nonlinear causalities between oil prices and the U.S. economic sectors

This study investigates the causal dynamics of the U.S. sector price changes and oil price changes using the symmetric nonlinear and asymmetric nonlinear causality tests. We find a unidirectional causality from each sector to the oil market using the Granger and MWald linear causality tests. However, the symmetric nonlinear and asymmetric nonlinear causality for negative price changes tests yield unidirectional causality from the oil to the sector price changes which sharply contrast the evidence using the linear models. We find bidirectional causality using the asymmetric nonlinear test for positive price changes, suggesting temporal, dual and nonlinear information flow during bull markets. Our results from the nonlinear and asymmetric causality tests remain robust after accounting for structural breaks. The empirical findings unravel nonlinear interactions between sector price and oil price changes as well as the importance of signs of changes in the interacting variables, implying oil returns may need to be priced when forecasting sector returns.     

On the Value of Municipal Bond Insurance: An Empirical Analysis

Using a large sample of municipal bond data from 2001 to 2010 in the U.S., this paper documents the time variation of the value of municipal bond insurance, estimated from the insured and uninsured bonds yield at issue differentials. We find that insured municipal bonds carry significant lower yields at issue compared to those of the equivalent uninsured bonds before 2008. However, this cost saving disappeared with the aftermath of the subprime credit crisis. We find that the supply of bonds and the level of market interest rates to have significant positive impacts on the time‐varying value of bond insurance. We also detect asymmetric response of these yield differentials to rises and declines of market interest rates. Economic intuition suggests that the value of municipal bond insurance is a function of business cycles but our tests support the contrary, which may be explained by the habitat preference of municipal bonds issues.     

Bank Competition and Collateral: Theory and Evidence

We investigate the impact of bank competition on the use of collateral in loan contracts. We analyze asymmetric information about the borrowers’ type in a Salop model in which banks choose between screening the borrower and asking for collateral. We show that the presence of collateral is more likely when bank competition is low. We then test this prediction empirically on a sample of bank loans from 70 countries. We perform logit regressions of the presence of collateral on bank competition, measured by the Lerner index. Our empirical tests corroborate the theoretical predictions that bank competition reduces the presence of collateral. These findings survive several robustness checks.     

Market Discipline and the Use of Stock Market Data to Predict Bank Financial Distress

We assess the extent to which stock market information can be used to estimate leading indicators of bank financial distress. We specify a logit early warning model, designed for European banks, which tests if market based indicators add predictive value to models relying on accounting data. We also study the robustness of the link between market information and financial downgrading in the light of the safety net and asymmetric information hypotheses. Some of our results support the use of market-related indicators. Other results show that the accuracy of the predictive power depends on the extent to which bank liabilities are market traded.      

Redistributive taxation and social insurance under adverse selection in the insurance market

This paper extends the analysis of optimal income taxation under uncertainty studied by Cremer and Pestieau (International Tax and Public Finance, 3, 281–295, 1996). We introduce asymmetric information in the insurance market whereby private insurance companies cannot identify the risk probability of the agents, and we examine its effect on public policy. We consider the separating equilibrium of Rothschild and Stiglitz (Quarterly Journal of Economics, 90, 629–649, 1976) and Riley (Econometrica, 47, 331–359, 1979) where the low risk agent is only partially insured. The presence of the distortion in the insurance market changes the affinity of labor, and in some cases, we show that the scope of redistribution and the resulting social welfare are higher under asymmetric information than under full information. We also show that the increase in social insurance affects the utility and labor incentive of the low risk type by relaxing the self-selection constraint in the insurance market. The policy implications of the redistributive taxation and social insurance are analytically and numerically examined.      

Option Volume and Stock Prices: Evidence on Where Informed Traders Trade

This paper investigates the informational role of transactions volume in options markets. We develop an asymmetric information model in which informed traders may trade in option or equity markets. We show conditions under which informed traders trade options, and we investigate the implications of this for the linkage between markets. Our model predicts an important informational role for the volume of particular types of option trades. We empirically test our model's hypotheses with intraday option data. Our main empirical result is that negative and positive option volumes contain information about future stock prices.     

Peer performance and the asymmetric timeliness of earnings recognition

This paper investigates the impact of peer performance on the asymmetric timeliness of earnings recognition. We find a positive relationship between peers' weak performance and timely bad news disclosure. Our results are robust to a variety of tests, including instrument variable approach, difference-in-differences analysis, alternative measures and subsample analysis. Consistent with the notion that weak peer performance increases investors' demand for information, the relationship is more profound for firms suffering from high information externality, with weak governance and high information asymmetry. Furthermore, we find that the relationship is difficult to reconcile with the explanation of managers' herding behaviour. In addition, we show that conservative accounting information disclosure due to weak peer performance alleviates managerial bad news hoarding and information asymmetry for underperforming firms, but distorts investment decisions for outperforming firms. We highlight the spillover effect of peer performance on conservative accounting information and the related heterogeneous outcomes.     

The value of the floor

Existing theoretical literature suggests that floor trading has discernable benefits over electronic trading. In particular floor relationships lead to a reduction in asymmetric information and hence lower spreads. The ability of floor brokers to participate in incoming order flow without revealing their supply and demand curves increases total liquidity and dampens liquidity shocks leading to lower volatility. We develop hypotheses and test them on a sample of stocks that switch from floor trading to an electronic system with fairly identical rules and pre-trade transparency. We find strong support for existing theory and our hypotheses. In particular asymmetric information and volatility are significantly higher on the electronic system. This leads to an increase in investor transaction costs which dwarfs the operational cost advantages of the electronic systems. Our results are robust to tests involving samples that control for company specific factors and market wide trends.     

中国健康险市场逆向选择和正向选择并存现象的研究

本文以中国的健康险市场为例,考察不对称信息的影响。通过考察投保人投保金额以及附加险选择和索赔情况的相关关系,论文发现事后出现索赔的投保人,事前往往会选择购买附加险,但是投保金额却相对较低。结合理论模型分析,论文认为投保人在财富、风险偏好等方面的异质性以及信息不对称的存在是导致市场同时出现逆向选择和正向选择的主要原因。