On financial guarantee insurance under stochastic interest rates

We extend the financial guarantee insurance literature by modeling, under stochastic interest rates, private financial guarantees when the guarantor potentially defaults. By performing numerical simulations under plausible parameters values, we characterize the differential impact of the incorporation of stochasticity of interest rates on the valuation of both public and private guarantees.     

A bootstrap theory for weakly integrated processes

This paper develops a bootstrap theory for models including autoregressive time series with roots approaching to unity as the sample size increases. In particular, we consider the processes with roots converging to unity with rates slower than n^-1$n^{-1}$. We call such processes weakly   integrated processes. It is established that the bootstrap relying on the estimated autoregressive model is generally consistent for the weakly integrated processes. Both the sample and bootstrap statistics of the weakly integrated processes are shown to yield the same normal asymptotics. Moreover, for the asymptotically pivotal statistics of the weakly integrated processes, the bootstrap is expected to provide an asymptotic refinement and give better approximations for the finite sample distributions than the first order asymptotic theory. For the weakly integrated processes, the magnitudes of potential refinements by the bootstrap are shown to be proportional to the rate at which the root of the underlying process converges to unity. The order of boostrap refinement can be as large as o(n^-1/2+?)$o(n^{-1/2+?})$ for any ?>0$?>0$. Our theory helps to explain the actual improvements observed by many practitioners, which are made by the use of the bootstrap in analyzing the models with roots close to unity.     

Why Do Landlords Include Utilities in Rent? Evidence from the 2000 Housing Discrimination Study (HDS) and the 2002 American Housing Survey (AHS)

This study assesses the decision to include utilities in the rent and the effect of this decision on rents. We utilize individual house-level data from the 2000 Housing Discrimination Study (HDS) and 2002 American Housing Survey (AHS), and determine that the cost of meter installation is not the only reason that utility costs are included in rent. We find evidence that landlords include utilities in the rent to attract more customers. Additionally, our findings demonstrate that utility inclusion behavior differs significantly between old and new building owners. For the hedonic rent estimation, we find that the decision to include the cost of utilities in the rent raises rent.     

Nonstationary nonlinear heteroskedasticity

In this paper, we consider time series with the conditional heteroskedasticities that are given by nonlinear functions of integrated processes. Such time series are said to have nonlinear nonstationary heteroskedasticity (NNH), and the functions generating conditional heterogeneity are called heterogeneity generating functions (HGF's). Various statistical properties of time series with NNH are investigated for a wide class of HGF's. For NNH models with a variety of HGF's, volatility clustering and leptokurtosis, which are common features of ARCH type models, are manifest. In particular, it is shown that the sample autocorrelations of their squared processes vanish only very slowly, or do not even vanish at all, in the limit. Volatility clustering is therefore well expected. The NNH models with certain types of HGF's indeed have sample characteristics that are very similar to those of ARCH type models. Moreover, the sample kurtosis of the NNH model either diverges or has a stable limiting distribution with support truncated on the left by the kurtosis of the innovations. This would well explain the presence of leptokurtosis in many observed time series data. To illustrate the empirical relevancy of our model, we analyze the spreads between the forward and spot rates of USD/DM exchange rates. It is found that the conditional variances of the spreads can be well modelled as a nonlinear function of the levels of the spot rates.     

Trade liberalization, heterogeneous firms and the soft budget constraint

We analyze the interaction between the soft budget constraint (SBC) and international trade by placing Segal’s (1998) SBC model within Melitz’s (2003) framework of international trade with heterogeneous monopolistically competitive firms. As in Segal’s model, SBC may result in moral hazard. The opening to international trade adds another sort of inefficiency. Some firms that would have become exporters in the absence of SBC choose to apply low effort and not export in order to extract a subsidy from the government. This effect takes place when the trade costs are sufficiently low. Overall, however, trade liberalization reduces inefficiencies generated by SBC. The number of firms subject to moral hazard SBC decreases, aggregate effort level increases and aggregate profits lost due to SBC-induced sub-optimal effort decline as trade costs decrease.     

Developing scenario-based technology roadmap in the big data era: an utilisation of fuzzy cognitive map and text mining techniques

ABSTRACT

Scenario-based technology roadmaps (TRM) have been used to analyse future uncertainties in the technology planning phase. However, there is a limitation in the existing related studies that the internal and external factors of the increasing uncertainty of the future are not considered. In response, this study proposes a framework that analyses the textual big data to understand the relationship between factors that may affect future uncertainty and build a TRM through scenarios based on these relationships. To do this, Fuzzy Cognitive Map technique, which analyses causal relationships between various factors in fuzzy graph form, is incorporated into TRM. To verify the effectiveness of the proposed framework, an illustrative case study was conducted using real data for an unmanned aerial vehicle. This study is expected to help integrate and utilise big data effectively in the technology planning stage.