Extracting a common stochastic trend: Theory with some applications

This paper investigates the statistical properties of estimators of the parameters and unobserved series for state space models with integrated time series. In particular, we derive the full asymptotic results for maximum likelihood estimation using the Kalman filter for a prototypical class of such models—those with a single latent common stochastic trend. Indeed, we establish the consistency and asymptotic mixed normality of the maximum likelihood estimator and show that the conventional method of inference is valid for this class of models. The models we explicitly consider comprise a special–yet useful–class of models that may be employed to extract the common stochastic trend from multiple integrated time series. Such models can be very useful to obtain indices that represent fluctuations of various markets or common latent factors that affect a set of economic and financial variables simultaneously. Moreover, our derivation of the asymptotics of this class makes it clear that the asymptotic Gaussianity and the validity of the conventional inference for the maximum likelihood procedure extends to a larger class of more general state space models involving integrated time series. Finally, we demonstrate the utility of this class of models extracting a common stochastic trend from three sets of time series involving short- and long-term interest rates, stock return volatility and trading volume, and Dow Jones stock prices.     

The problem of the uninsured

The problem of the uninsured cannot be fully understood without considering the role of non-market alternatives to ‘market insurance’ called ‘self-insurance’ and ‘self-protection’ (SISP), including the public ‘health care safety-net’ system. We tackle the problem by formulating a ‘full-insurance’ paradigm that accounts for all four interacting insurance measures. We apply two versions of the full-insurance model to estimate, via calibrated simulations, the impacts of SISP on the fraction of uninsured, health spending, and health levels, and to assess how the mandated Affordable Care Act might affect these outcomes in comparison with the CBO projections in 2010. The results indicate that policy analyses which overlook the role of the real price of market insurance relative to the shadow prices of SISP in determining the decision to insure can grossly distort the capacity of mandated reforms like the ACA to insure the uninsured, contain overall health care costs, and improve health and welfare outcomes.     

Inflation Targeting Framework and Interest Rates Transmission in Ghana: An Empirical Investigation

This paper investigates the long-and short-run rate of transmission of the prime rate to interest rates since the implementation of inflation targeting policy in Ghana. Monthly data covering the period January 2002 to March 2016 is used. The Johansen and Hansen parameter instability cointegration, the FMOLS and DOLS estimation procedures were used. The long-run results show incomplete pass-through of the prime rate to commercial banks’ lending and deposit rates but over pass-through to the 91-day Treasury bill rate. The short-run adjustment shows relatively slow transmission of the prime rate to the respective interest rates. Given the findings, relevant policy suggestions are provided.     

Using Aggregate Time Series Variables to Forecast Notices of Default

This paper emphasizes the economic variables and data used to model notices of default in California. Forecast models are notoriously complicated and require sophisticated software to run. Few businesses, particularly small enterprises, have the necessary resources to engage in large-scale model building. Datasets can be difficult and expensive to obtain and usually require significant analysis. The paper focuses on methodology to give the model a general appeal.     

Specialized Careers

An agent has different abilities in two types of tasks. These tasks are revealed over time through his performance. The agent initially decides whether to engage in only one task (specialize) or to take on any task that arises (be a generalist). This decision trades off the cost of being idle against staying available for relatively lucrative tasks. We compare specializing with acting as a generalist in an infinite‐horizon model and provide complete characterizations of efforts. We show how specializing acts as a means of committing to exert more effort. In a two‐period version of the model, this implies that positive costs for switching strategies, through license fees, for example, may be socially desirable.     

Residential-Mortgage Lending Discrimination and Lender-Risk-Compensating Policies

The Boston Federal Reserve study ( Munnell et al. 1996 ) concluded that illegal discrimination is a statistically significant contributor to the observed gap between white and minority residential-mortgage rejection rates. The Boston study speculated that discrimination arises because lenders do not equally apply risk compensation or mitigation policies for imperfect loans. Using the same 1990 Boston loan application data, our study specifically examines the relation between compensating policies and discrimination. Since compensating policies are encouraged by secondary-mortgage-market sale guidelines, we model both the lender's origination decision and its loan sale decision. Using a rule-based artificial-intelligence technique applied to each lender, we infer compensating policies (rules) that equally apply to all races and explain lending decisions. A minority-race indicator loses its statistical significance when an indicator of compensating-policy violations appears in the loan accept–reject equation. This result reflects the fact that the risk levels of marginal minority loans tend to be more extreme than those of marginal white loans. However, the result does not necessarily reject the existence of discrimination. Equally applied policies may be empirically indistinguishable from unfairly applied policies. In addition, equally applied policies may fail the adverse-impact doctrine if they do not serve a business necessity (such as profits). The industry's move away from discretionary, rule-based decisions to mortgage scoring answers the need for a decision framework that rigorously uses loan performance to evaluate all loan applicants fairly.     

Something to prove: reputation in teams

Agents work for their own reputations when young but for their firms' when old. An individual with an established reputation cannot credibly commit to exerting effort when working alone. However, by hiring and working with juniors of uncertain reputation, seniors will have incentives to exert effort. Incentives for young agents arise from a concern for their own reputation (and the opportunity to take over the firm), whereas older agents work for the reputation of their firms (and the opportunity to sell out to juniors). Thus, the article explains the choice to work in teams. It also exemplifies how type uncertainty in reputation models may be endogenously and strategically introduced.     

In Defence of Capitalisation Weights: Evidence from the FTSE 100 and S&P 500 Indices

A simple method for decomposing the variance covariance matrix of portfolio returns at the level of individual stocks is applied to the FTSE 100 Index. During extreme negative shocks, the largest index constituents exhibit lower than average covariance, thereby reducing the volatility of the capitalisation‐weighted index. The risk‐adjusted returns of the capitalisation‐weighted FTSE 100 Index exceed those of an equally‐weighted version of the same index and the outperformance is robust to the method of risk adjustment applied. The equally‐weighted index also exhibits greater systematic (market) risk than the capitalisation‐weighted version.     

Do preferences for charitable giving help auctioneers?

Preferences for charitable giving in auctions can be modeled by assuming that bidders receive additional utility proportional to the revenue raised by an auctioneer. The theory of bidding in the presence of such preferences results in a very counterintuitive prediction which is that, in many cases, bidders having preferences for charitable giving does not lead to a substantial revenue advantage for an auctioneer. We test this theory and this prediction with a series of experiments. In one experiment we induce charitable preferences exactly as specified in the model to see if bidders respond to them as predicted. We find that they do. We then conduct a second experiment in which the revenue from the auctions is donated to actual charities to verify the robustness of the prediction when charitable preferences are generated by a more natural source and find again that the theoretical prediction holds: even strong charitable preferences do not result in substantial revenue increases to the auctioneer.