Two–step sequential sampling

Choosing the sample size in advance is a familiar problem: often, additional observations appear to be desirable. The final sample size then becomes a random variable, which has rather serious consequences.
Two such sample extension situations will be considered here. In the first situation, the observed sample variance determines whether or not to double the original sample size. In the second situation, the variances observed in two independent samples are compared; their ratio determines the number of additional observations.     

Heteroscedasticity and Non-Monotonic Efficiency Effects of a Stochastic Frontier Model

We consider a model that provides flexible parameterizations of the exogenous influences on inefficiency. In particular, we demonstrate the model's unique property of accommodating non-monotonic efficiency effect. With this non-monotonicity, production efficiency no longer increases or decreases monotonically with the exogenous influence; instead, the relationship can shifts within the sample. Our empirical example shows that variables can indeed have non-monotonic effects on efficiency. Furthermore, ignoring non-monotonicity is shown to yield an inferior estimation of the model, which sometimes results in opposite predictions concerning the data.     

The impact of credit constraints on the performance of Chinese agricultural wholesalers

This article evaluates the impact of credit constraints on the performance of Chinese agricultural wholesalers. We estimate a stochastic frontier function using transaction and credit data of agricultural wholesalers from across China to estimate the efficiency and productivity impacts of credit constraints on sales of affected agricultural wholesalers. Empirical results show that micro- and smaller wholesalers are disproportionally impacted by credit constraints and that eliminating these constraints would increase the sales of affected agricultural wholesalers by approximately 15%. Thus, policies aimed at providing credit access for these wholesalers would significantly boost the performance of smaller agricultural wholesalers while improving the overall performance of the Chinese food supply chain without requiring additional non-credit inputs.     

Modelling the dynamics of Bitcoin and Litecoin: GARCH versus stochastic volatility models

We examine and compare a large number of generalized autoregressive conditional heteroskedastic (GARCH) and stochastic volatility (SV) models using series of Bitcoin and Litecoin price returns to assess the model fit for dynamics of these cryptocurrency price returns series. The various models examined include the standard GARCH(1,1) and SV with an AR(1) log-volatility process, as well as more flexible models with jumps, volatility in mean, leverage effects, t-distributed and moving average innovations. We report that the best model for Bitcoin is SV-t while it is GARCH-t for Litecoin. Overall, the t-class of models performs better than other classes for both cryptocurrencies. For Bitcoin, the SV models consistently outperform the GARCH models and the same holds true for Litecoin in most cases. Finally, the comparison of GARCH models with GARCH-GJR models reveals that the leverage effect is not significant for cryptocurrencies, suggesting that these do not behave like stock prices.     

Uncertain Climate Change in an Intergenerational Planning Model

A three-generation planning model incorporating uncertain climate change is developed. Each generation features a production activity based on capital and an exhaustible resource. An irreversible climate change may occur in period two or three, reducing the productivity for this and the remaining generation. The model is solved by stochastic dynamic programming. If the climate impact and climate change probability is constant, the optimal period one (and two) resource extraction is larger than for the reference case of climate stability. If, however, climate impact and climate change probability increases with increased aggregate resource use, this result is reversed.     

The Bioeconomics of Marine Sanctuaries

Consider an offshore fishing grounds of size K. Suppose the grounds has been overfished to the point that net revenue has been driven to zero and the fishery is in open access equilibrium at (X, Y). A marine sanctuary, where fishing is prohibited, is then created. Suppose the marine sanctuary is of size K₂ and that fishing is allowed on a smaller grounds, now of size K₁, where K₁ + K₂ = K. In the first, deterministic, model, the present value of net revenue from the grounds-sanctuary system is maximized subject to migration (diffusion) of fish from the sanctuary to the grounds. The size of the sanctuary is varied, the system is re-optimized, and the populations levels, harvest, and value of the fishery is compared to the 'no-sanctuary' optimum, and the open access equilibrium. In the deterministic model, a marine sanctuary reduces the present value of the fishery relative to the 'ideal' of optimal management of the original grounds. In the second model net growth is subject to stochastic fluctuation. Simulation demonstrates the ability of a marine sanctuary to reduce the variation in biomass on the fishing grounds. Variance reduction in fishable biomass is examined for different-sized sanctuaries when net growth on the grounds and in the sanctuary fluctuate independently and when they are perfectly correlated. For the stochastic model of this paper, sanctuaries ranging in size from 60 to 40% of the original grounds (0.6 K₂/K 0.4) had the ability to lower variation in fishable biomass compared to the no sanctuary case. For a sanctuary equal to or greater than 70% of the original grounds (K₂ 0.7K), net revenue would be nonpositive and there would be no incentive to fish.     

人力资本投资对技术效率省际差异的实证研究

大量的实证研究表明,人力资本积累可以提高经济系统的运行效率和技术效率,从而在现代经济增长中具有重要的作用。文章运用随机前沿分析模型实证分析了人力资本投资对我国技术效率变化的具体影响。分析结果指出,我国人力资本投资对各省份的技术效率呈较强的相关性,加大人力资本的投入力度可显著提高我国技术效率的水平。     

The Underpricing and Excess Returns of Initial Public Offerings in Taiwan Based on Noisy Trading: A Stochastic Frontier Model

Initial public offerings (IPOs) are typically offered at prices lower than the transaction price in the early aftermarket. With a stochastic frontier model, we measured the fair offer price of an IPO and then the deliberate IPO underpricing and the market misvaluation based on the estimated fair offer price. Our results show that IPOs are deliberately underpriced. The extent of noisy trading leading to significantly higher market transaction prices explains the excess IPO returns. We conclude that initial IPO returns result primarily from the noisy trading activities instead of the deliberate IPO underpricing.     

Valuation of commodity derivatives in a new multi-factor model

This paper extends existing commodity valuation models to allow for stochastic volatility and simultaneous jumps in the spot price and spot volatility. Closed-form valuation formulas for forwards, futures, futures options, geometric Asian options and commodity-linked bonds are obtained using the Heston (1993) and Bakshi and Madan (2000) methodology. Stochastic volatility and jumps do not affect the futures price at a given point in time. However, numerical examples indicate that they play important roles in pricing options on futures. This revised version was published online in June 2006 with corrections to the Cover Date.     

Planning Your Own Debt

We model the Danish market for mortgage backed securities with a two-factor interest rate model and use a stochastic programming approach to analyse how an individual home-owner should initially compose and subsequently readjust his mortgage in an optimal way. Results show that the 'rules of thumb' used by financial institutions are reasonable, although best suited for more aggressive mortgagors, for whom the delivery option is of some value. More risk-averse investors should also re-adjust frequently, but use more diversified portfolios. Results are insensitive to whether a one- or two-factor model is used, provided the former is suitably calibrated.