The RWDAR model: A novel state-space approach to forecasting

This paper introduces the Random Walk with Drift plus AutoRegressive model (RWDAR) for time-series forecasting. Owing to the presence of a random walk plus drift term, this model shares some similarities with the Theta model of Assimakopoulos and Nikolopoulos (2000). However, the addition of a first-order autoregressive term in the state equation provides additional adaptability and flexibility. Indeed, it is shown that RWDAR tends to outperform the Theta model when forecasting both stationary and nearly non-stationary time series. This paper also proposes a simple estimation method for the RWDAR model based on the solution of the algebraic Riccati equation for the prediction error covariance of the state vector. Simulation results show that this estimator performs as well as the standard Kalman filter approach. Finally, using yearly data from the M3 and M4 competition datasets, it is found that RWDAR outperforms traditional forecasting methods.     

A bidimensional approach to mortality risk

Abstract We analyze the evolution over time of portfolios of life insurance contracts referring to different cohorts or risk classes of insureds. We model the intensity of mortality as a random field, in order to capture cross-generation (risk class) effects induced by the on-going management of portfolios of policies. Applications are described in the context of mortality risk analysis and (market) valuation of liabilities at aggregate level. It is shown how the model can be employed when an insurer’s new business is considered.     

A standard error for the estimated state vector of a state-space model

This paper motivates an estimate of the variance of the estimated state vectorxˆ_t in a state-space model when the vector of parameters characterizing system dynamics (θ) must be estimated from the data.     

The small open macroeconomy and the yield curve: A state-space representation

This study extends a state-space representation of the yield curve and the macroeconomy to a small open economy in order to study the dynamic interaction between the yield curves in Canada and the U.S. The framework treats the U.S. term structure of interest rates as being exogenous to both the Canadian yield curve and macroeconomy. The empirical results support very strong links between the yield curves in the two countries, with the U.S. yield curve accounting for as much as 45 per cent of the variation of the movement in the level and about 30 per cent of the movements in the slope and the curvature of the Canadian yield curve. Canadian yield-curve factors are found to account for about 50 per cent of the variation in output and the monetary policy rate, and about 25 per cent of the variation in inflation, much larger than the yield curve effects found for future developments of the macroeconomies of other countries. A relatively strong bilateral relationship is found to exist between the yield curve and the instrument of monetary policy, supporting recent studies that find the dynamic relationship between the yield curve and the macroeconomy is due to the pivotal role that monetary policy plays in the macroeconomy.     

Immigration policy: a selective approach

Recommendations are offered concerning Japanese policy on the immigration of foreign workers. The author notes that even those countries that used to welcome such immigrants now restrict their entry. The need for a selective policy that would aid internationalization in Japan and strengthen controls on illegal immigrants by requiring employers to secure permits before hiring foreigners is stressed.     

Testing normality: a GMM approach

In this paper, we consider testing marginal normal distributional assumptions. More precisely, we propose tests based on moment conditions implied by normality. These moment conditions are known as the Stein (Proceedings of the Sixth Berkeley Symposium on Mathematics, Statistics and Probability, Vol. 2, pp. 583–602) equations. They coincide with the first class of moment conditions derived by Hansen and Scheinkman (Econometrica 63 (1995) 767) when the random variable of interest is a scalar diffusion. Among other examples, Stein equation implies that the mean of Hermite polynomials is zero. The GMM approach we adopt is well suited for two reasons. It allows us to study in detail the parameter uncertainty problem, i.e., when the tests depend on unknown parameters that have to be estimated. In particular, we characterize the moment conditions that are robust against parameter uncertainty and show that Hermite polynomials are special examples. This is the main contribution of the paper. The second reason for using GMM is that our tests are also valid for time series. In this case, we adopt a heteroskedastic-autocorrelation-consistent approach to estimate the weighting matrix when the dependence of the data is unspecified. We also make a theoretical comparison of our tests with Jarque and Bera (Econom. Lett. 6 (1980) 255) and OPG regression tests of Davidson and MacKinnon (Estimation and Inference in Econometrics, Oxford University Press, Oxford). Finite sample properties of our tests are derived through a comprehensive Monte Carlo study. Finally, two applications to GARCH and realized volatility models are presented.     

Escalating penalties: a supergame approach

The paper provides an economic rationale for punishing repeat offenders with increasing sanctions. We analyze the optimal intertemporal punishment scheme within a supergame framework, in which the legal authority is assumed to minimize the social costs of punishment under the constraint of keeping delinquency at an exogenously given maximal tolerable level.     

Preference through indifference: a topological approach

Two problems of consumer theory are approached topologically. An intrinsic topological characterization of transitivity of indifference is provided. Under very weak assumptions, indifference classes are proved to determine the continuous preference inducing them. Moreover, conditions, under which a given topology is the weakest making a preference continuous, are obtained.     

Electronic data interchange: a strategic approach

The potential of EDI is virtually unlimited, but the success of any EDI initiative hinges on its ability to directly support strategies that achieve your institution's business objectives. At its most fundamental level, EDI technology automates current business practices, speeding up the exchange of business information. This application of EDI most often is found in a hospital's material management department. But EDI integrated internally within a hospital and externally with suppliers and vendors has the potential to go beyond simple automation and to transform processes. This is where the full value of EDI can be realized. No matter which level of EDI participation hospital management decides is appropriate to fulfill its business objectives and strategies, EDI will affect the entire institution's exchange of information with its internal and external audiences. The question management must answer is: Will the hospital's EDI strategy be offensive and managed, or defensive and reactive? Today's environment leaves no room for a "no-strategy" EDI option. The options are either to proactively shape EDI, or reactively play catch-up. EDI can work for you. Adequately developing an EDI game plan in support of your business objectives and calling on your suppliers and other trading partners to work with you will ensure EDI is an asset to your facility.     

Option pricing: a yet simpler approach

Decisions in Economics and Finance - We provide a lean, non-technical exposition on the pricing of path-dependent and European-style derivatives in the Cox–Ross–Rubinstein (CRR) pricing...     

Political regimes: a coalition formation approach

What leads to the stability of a particular regime and what causes its demise? With the aid of formal modeling, the paper illustrates the necessary and sufficient conditions for different political regimes to exist. The game involves two factions representing the differing interests of the civil society and the armed forces of a nation. We illustrate the emergence of political regimes that includes both unconstrained and constrained democracies, both military and civilian autocracies and an alliance formed by a segment of the civil society and the military.     

Credibility and Monitoring: Outsourcing as a Commitment Device

We analyze an environment plagued by double moral hazard where the agent’s effort level and the principal’s precision in monitoring are not contractible. In such an environment, the principal tends to over‐monitor thereby inducing low effort. To ease the latter problem, the principal may choose to increase monitoring costs by outsourcing the activity. As a result equilibrium monitoring is reduced and incentives become more powerful. This choice is particularly likely when the worker’s effort is an important factor in determining output.     

Efficient frontier estimation: a maximum entropy approach

An alternative efficiency estimation approach is developed utilizing generalized maximum entropy (GME). GME combines the strengths of both SFA and DEA, allowing for the estimation of a frontier that is stochastic, without making an ad hoc assumption about the distribution of the efficiency component. GME results approach SFA results as the one-sided inefficiency bounds used by GME shrink. Results similar to DEA are achieved as the bounds increase. The GME results are distributed like DEA, but yield virtually the same rankings as SFA. The results suggest that GME may provide a link between various estimators of efficiency.

Modeling the International-Trade Network: a gravity approach

We investigate whether the gravity model (GM) can explain the statistical properties of the International Trade Network (ITN). We fit data on trade flows with a GM using alternative estimation techniques and we build GM-based predictions for the weighted topological properties of the ITN, which are then compared to the observed ones. Our exercises show that the GM: (i) may replicate part of the weighted-network structure only if the observed binary architecture is kept fixed; (ii) is not able to explain higher-order statistics that, like clustering, require the knowledge of triadic link-weight topological patterns, even if the binary structure perfectly replicates the observed one; (iii) performs very badly when asked to predict the presence of a link, or the level of the trade flow it carries, whenever the binary structure must be simultaneously estimated.     

Methods for analyzing decision-making: a framework approach

In political science an eternal question concerns how decisions and policies arise. Modern society, characterized by more uncertainty and complexity than before, increases the challenge of providing valid answers. However, the general lack of methodological concern in several previous studies in this area stresses the need for elaborations of more suitable approaches. In this article we add a methodological perspective that deals with this very question. By reviewing and analyzing earlier research on how decision-making is reached, the overall ambition of this article is to create a framework that can lay the methodological foundation for further studies. Such a framework, which takes into account both the complexity of modern multi-governance societies and adds methodological perspectives of macro and micro standpoints as well as of causal mechanisms, can be used in future research to achieve richer pictures of how decision-making is carried out. In addition, we show how a certain technique of analysis is highly compatible to this framework and that jointly these features provide solutions for a better understanding of the complexity of modern decision-making. All in all, applying this strategy can be used to better systematize complex causal chains that reflect different analytical levels and thereby increase leverage on how to understand and explain the process of political decisions.