Individual option prices for climate change mitigation

Willingness-to-pay for climate change mitigation depends on people's perceptions about just how bad things will get if nothing is done. Individual subjective distributions for future climate conditions are combined with stated choices over alternative climate policies to estimate individual option prices (the appropriate ex ante welfare measure in the face of uncertainty) for climate change mitigation. We find statistically significant sensitivity of estimated option prices to both expected future conditions and uncertainty about future conditions.     

An application of models of speculative behaviour to oil prices

We estimate three different models of speculative behaviour using oil price data. Our findings provide support for the claim by Phillips and Yu (2011) and Gilbert (2010) that a bubble in oil prices existed for a short period in 2008.     

Estimating a continuous time portfolio selection model: An application with UK data

An empirical assessment of a continuous time portfolio selection model is studied for the UK economy between 1970 and 1996. The estimates obtained from this study are both statistically significant and consistent with the model's predictions. The estimate of risk aversion parameter refers to low risk aversion which is consistent with the optimal risky asset holding parameter. Furthermore, the estimated parameters of the asset pricing relationship are also found to be consistent with the historical values of the stock prices. First version received: February 1998/final version received: March 1999     

An application of DPSIR framework to identify issues of pollinator loss

This paper is an attempt to apply the Driving forces–Pressures–State–Impact–Responses (DPSIR) framework to identify the issues of pollinator loss. The linkages between the significant pressures on insect pollinators, their underlying socio-economic driving forces and responses, with the focus on Europe, are addressed in the study. A review of literature revealed the shortage of empirical studies that prove direct links between policy responses and specific pressures on the pollinators. Based on written evidence and expert judgement, land use practices and the use of agrochemicals were regarded as the most significant pressures on different functional groups of pollinators. As demonstrated in the study, agricultural and rural development policy has been the key driving force of these pressures. The application of the DPSIR framework proved to be useful in identifying the pathway of human pressures on pollinators. The study also concludes that there is further need for specific empirical research on the effects and effectiveness of the Common Agricultural Policy (CAP) measures (agri-environment measures in particular) to support farming practices that facilitate the protection of the environment and the prevention of pollinator loss.     

A novel nonlinear value-at-risk method for modeling risk of option portfolio with multivariate mixture of normal distributions

This paper proposes a novel nonlinear model for calculating Value-at-Risk (VaR) when the market risk factors of an option portfolio are heavy-tailed. A multivariate mixture of normal distributions is used to depict the heavy-tailed market risk factors and accordingly a closed form expression for the moment generating function that can reflect the change in option portfolio value can be derived. Moreover, in order to make use of the correlation between the characteristic function and the moment generating function, Fourier-Inversion method and adaptive Simpson rule with iterative algorithm of numerical integration into the nonlinear VaR model for option portfolio are applied for calculation of VaR values of option portfolio. VaR values of option portfolio obtained from different methods are compared. Numerical results of Fourier-Inversion method and Monte Carlo simulation method show that high accuracy VaR values can be obtained when risk factors have multivariate mixture of normal distributions than when they have normal distributions. Moreover, VaR values obtained by using the Fourier-Inversion method are not obviously different from VaR values obtained by using Monte Carlo simulation when market risk factors have normal distributions or multivariate mixture of normal distributions. However, the speed of computation is obviously faster when using Fourier-Inversion method, than when using Monte Carlo simulation method. Besides, Cornish Fisher method is faster and simpler than Monte Carlo simulation method or Fourier-Inversion method. However, this method does not offer high accuracy and cannot be used to calculate VaR values of option portfolio when market risk factors have heavy-tailed distributions.     

An empirical estimation for mean-reverting coal prices with long memory

In this paper we discuss the calibration issues of power models built on mean-reverting processes combined with long memory. The unknown parameters of fractional mean-reversion processes are estimated by a hybrid estimation method, which is built upon the marriage of the quadratic variation and the least squares. We perform a simulation study to test the efficiency of these estimators and to compare with the approach proposed by Høg (1999). Moreover, we apply our estimation procedure to some sample series of Chinese coal spot prices in real life situations. These results support the use of fractional mean-reversion processes in modeling Chinese coal prices.     

An alternative lattice algorithm for option pricing

This paper proposes a dimension reduction technique on lattice model, an extension of the discrete CRR （1979） model, for option pricing. Applications are demonstrated on pricing some vulnerable options with the payoff functions including two stochastic processes： the underlying stock price and the assets value of the option writer. Instead of building a bivariate tree structure for these correlated processes, a univariate binomial tree for the underlying stock price is only constructed. The proposed univariate binomial tree model is sufficient to undertake, though two underlying assets are involved.     

A barrier option framework for rescue package designs and bank default risks

Rescue packages adopted to stabilize the banking system are generally divided into three categories: government purchases of distressed assets, government guaranteed debt issuance programs, and direct equity capital injections. Countries afflicted by the recent financial crisis launched general programs in one or two, and even in three different categories. In this paper, we examine that the design of a government rescue package for a distressed bank depends on the expected reduction of the default risk in the bank's equity returns. We find that the bank's default risk is negatively related to distressed loan purchases, and to capital injections, but positively related to guaranteed debt issuance. We also find that the rescue package including all three categories is not guaranteed to increase stability for the rescued bank. Specifically, the combination of distressed loan purchases and capital injections is superior to the package of the three categories in addition to the solo instrument. This suggests that an effective design of a government rescue package for the financial services industry largely depends on its targets.     

Effects of background risks on cautiousness with an application to a portfolio choice problem

We provide necessary and sufficient conditions on an individual's expected utility function under which any zero-mean idiosyncratic risk increases cautiousness (the derivative of the reciprocal of the absolute risk aversion), which is the key determinant for this individual's demand for options and portfolio insurance.     

Modelling economic circuit flows in a social accounting matrix framework. An application to Portugal

Aggregated Social Accounting Matrices (SAMs) will be built for the Portuguese economy in 1997, 1998 and 1999, based on the country's national accounts statistics. The SAMs will be shown as a working instrument for quantifying the flows in the economic circuit and for simulating the effects resulting from changes in such flows. The economic flows associated with the government subsectors will be emphasized, whilst accounting and fixed-price multipliers will be calculated to facilitate the study of the effects resulting from changes in the government's expenditure, which will also be subjected to a test on their veracity.     

A generalized method of moments estimator for a spatial model with moving average errors, with application to real estate prices

This paper proposes a new GMM estimator for spatial regression models with moving average errors. Monte Carlo results are given which suggest that the GMM estimates are consistent and robust to non-normality, and the Bootstrap method is suggested as a way of testing the significance of the moving average parameter. The estimator is applied in a model of English real estate prices, in which the concepts of displaced demand and displaced supply are introduced to derive the spatial lag of prices, and the moving average error process represents spatially autocorrelated unmodelled variables.      

A framework for the decomposition of poverty differences with an application to poverty differences between countries

We propose an Oaxaca-Blinder-like decomposition of poverty differences. The decomposition is based on a parametric model of the income distribution and can be used to decompose differences in poverty rates across countries or years. Poverty differences are decomposed into differences in the underlying distribution of poverty-relevant characteristics and differences in the incidence of poverty conditional on these characteristics. We illustrate our method by comparing levels and patterns of relative poverty in the USA, Great Britain and Germany during the 1990s. Our results suggest that the higher aggregate poverty rates in the USA and in Britain relative to Germany were mostly accounted for by higher poverty rates conditional on characteristics, which were partly offset by a more favourable distribution of poverty-relevant characteristics, in particular higher employment rates.This paper is part of the research programme of the TMR Network ‘Living Standards, Inequality and Taxation’. Financial support from the European Union (Contract #ERBFMRXCT980248), the UK Economic and Social Research Council, the University of Essex, and the Deutsche Forschungsgesellschaft (DFG) is gratefully acknowledged. The data used in this study were made available by Cornell University (Cross-National Equivalent File), the University of Michigan (Panel Study of Income Dynamics), the UK Data Archive (British Household Panel Survey), and the German Institute for Economic Research (German Socio-Economic Panel). Martin Biewen would like to thank the Institute for European Studies and the Department for Policy and Management at Cornell University, in particular Jonas Pontusson, Richard Burkhauser and Dean Lillard, for their hospitality and support. We are also grateful for comments by Bernd Fitzenberger, Joachim Winter, Christoph M. Schmidt, an anonymous referee and seminar participants in Essex, Heidelberg and Mannheim. Last but not least, we thank Nick Cox for providing us with updated versions of his Stata programs for drawing quantile plots.First version received: May 2003/Final version received: December: 2003     

Internal and external exchange rate equilibrium in a cointegration framework. An application to the Spanish peseta

A simple cointegration methodology is used to compute the equilibrium real exchange rate for the peseta. The stock of foreign assets and the evolution of sectoral prices are considered to be the fundamentals for the real exchange rate. After testing for cointegration, we proceed to decompose the series into a permanent and a transitory component, following the method devised by Gonzalo and Granger. The permanent component of the real exchange rate corresponds to its (time-varying) equilibrium value, and the deviation of the actual real exchange rate from this equilibrium value gives an estimation of the degree of misalignment of the real exchange rate. By the end of the sample (1998:1), the peseta is estimated to be undervalued around 6%.     

Nontradable goods prices and per-caita income: an application to regional Korean data

A system of demand equations (given oligopolistic interdependence amon firms) is derived and estimated for two four-digit SIC code industries to explain firms' R&D behaviour through time. The two industries chosen are the perfume, cosmetic and toiletries (PCT) industry, and the drug industry. The industries chosen belong to the same two-digit SIC code classification called the Cchemical and Allied Products industry but not in the drug industry. The introduction of the R&D tax credit in 1981, however, reduced the tendency to free-ride in both industries.     

Detecting periods of exuberance: A look at the role of aggregation with an application to house prices

The recently developed SADF and GSADF unit root tests of Phillips and Yu (2011) and Phillips et al. (2015a,b) have become popular in the literature for detecting exuberance in asset prices. In this paper, we examine through simulation experiments the effect of cross-sectional aggregation on the power properties of these tests. The simulation design considered is based on simulated data and actual housing data for both U.S. metropolitan areas and international housing markets and thus allows us to draw conclusions for different levels of aggregation. Our findings suggest that aggregation lowers the power of both the SADF and GSADF tests. The effect, however, is much larger for the SADF test. We also provide evidence that tests based on panel data techniques, namely the panel GSADF test recently proposed by Pavlidis et al. (2016), can perform substantially better than univariate tests applied to aggregated series. Furthermore, we also illustrate the date-stamping procedure under the univariate/panel GSADF procedure uncovering novel evidence on the role of interest rates and policy uncertainty as factors explaining episodes of widespread mildly explosive dynamics in housing markets.     

An analytical framework for retailer price and advertising decisions for products with temperature-sensitive demand

The demand for weather-sensitive products, such as beverages, ice creams, or chocolate varies with changes in temperature. Yet, retailers lack a framework to adapt the marketing mix elements, such as price and advertising, in line with such changes. We provide a theoretical framework to fill this gap by developing an analytical model to derive the optimal marketing mix when product demand depends on temperature. The model prescribes how price and advertising for different demand characteristics should be set following a temperature change. Integrating the temperature element in the marketing mix offers an original profit-enhancing strategy.     

An optimization framework for addressing aquatic invasive species

This study develops a bio-economic model framework to optimize the management of aquatic invasive species. Stochastic dynamic programming is applied to investigate when and to what extent a society should engage in efforts to reduce the likelihood of an invasion, to control and eradicate a newly established population, and to adapt to damages. The framework is parameterized for a potential Asian clam (Corbicula fluminea) invasion in the warm water discharge area of a nuclear power plant planned on the northern shores of the Baltic Sea. The sensitivity analysis reveals three distinct strategies: an adaptive strategy, which reduces the damage that an existing invasive species population causes to the private sector; a preventive strategy, which delays the invasion and the resulting damage; and a mitigative strategy, which puts effort into timely detection, control and eradication of the newly established population. Choice of the optimal strategy is sensitive to the unit costs and effectiveness of the measures required, to the level of externalities and to the size of the clam population after the invasion has been detected. The results emphasize the need for the energy sector to identify and internalize the external costs of potential invasions when making any large-scale investment plans.     

Risk index based models for portfolio adjusting problem with returns subject to experts' evaluations

This paper discusses a portfolio adjusting problem with additional risk assets and a riskless asset in the situation where security returns are given by experts' evaluations rather than historical data. Uncertain variables are employed to describe the security returns. Using expected value and risk index as measurements of portfolio return and risk respectively, we propose two portfolio optimization models for an existing portfolio in two cases, taking minimum transaction lot, transaction cost, and lower and upper bound constraints into account. In one case the riskless asset can be both borrowed and lent freely, and in another case the riskless asset can only be lent and the borrowing of riskless asset is not allowed. The adjusting models are converted into their crisp equivalents, enabling the users to solve them with currently available programming solvers. For the sake of illustration, numerical examples in two cases are also provided. The results show that under the same predetermined maximum tolerable risk level the expected return of the optimal portfolio is smaller when the riskless asset can only be lent than when the riskless asset can be both borrowed and lent freely.