A Simple and Intuitive Method to Solve Small Rational Expectations Models

We present a nonlinear solution method of saddlepoint dynamics in discrete time optimization problems. It is based on the backward attractivity of the stable manifold and is very easy to implement. After an introduction to the general method we present two applications. First, we consider the deterministic neoclassical growth model and demonstrate accuracy and stability of the method. Second, we solve a basic real business cycle model.revised version received July 2, 2003     

Superpave13混合料级配与构造深度关系

在某条高速Superpave13混合料施工过程中现场随机抽取试样,通过抽提试验确定混合料的级配。在混合料铺筑完成后次日现场取芯分析路面压实度,同时采用铺砂法确定路面构造深度(TD),采用多元非线性回归法分析构造深度与级配关系,并在路面通车半年、一年后对路面构造深度进行测试,分析构造深度随时间衰变规律。通过分析得知在施工过程中路面压实度满足要求的情况下,级配与构造深度有着很好的相关性。同一公路不同路段,由于交通量的差异,导致构造深衰变规律有一定的差异,在排除交通轴载对构造深度的影响因素后,构造深度随时间有着很好的相关性。     

Estimation of Common Factors under Cross‐Sectional and Temporal Aggregation Constraints

The paper estimates a large‐scale mixed‐frequency dynamic factor model for the euro area, using monthly series along with gross domestic product (GDP) and its main components, obtained from the quarterly national accounts (NA). The latter define broad measures of real economic activity (such as GDP and its decomposition by expenditure type and by branch of activity) that we are willing to include in the factor model, in order to improve its coverage of the economy and thus the representativeness of the factors. The main problem with their inclusion is not one of model consistency, but rather of data availability and timeliness, as the NA series are quarterly and are available with a large publication lag. Our model is a traditional dynamic factor model formulated at the monthly frequency in terms of the stationary representation of the variables, which however becomes nonlinear when the observational constraints are taken into account. These are of two kinds: nonlinear temporal aggregation constraints, due to the fact that the model is formulated in terms of the unobserved monthly logarithmic changes, but we observe only the sum of the monthly levels within a quarter, and nonlinear cross‐sectional constraints, since GDP and its main components are linked by the NA identities, but the series are expressed in chained volumes. The paper provides an exact treatment of the observational constraints and proposes iterative algorithms for estimating the parameters of the factor model and for signal extraction, thereby producing nowcasts of monthly GDP and its main components, as well as measures of their reliability.     

Finding Bayesian Optimal Designs for Nonlinear Models: A Semidefinite Programming‐Based Approach

This paper uses semidefinite programming (SDP) to construct Bayesian optimal design for nonlinear regression models. The setup here extends the formulation of the optimal designs problem as an SDP problem from linear to nonlinear models. Gaussian quadrature formulas (GQF) are used to compute the expectation in the Bayesian design criterion, such as D‐, A‐ or E‐optimality. As an illustrative example, we demonstrate the approach using the power‐logistic model and compare results in the literature. Additionally, we investigate how the optimal design is impacted by different discretising schemes for the design space, different amounts of uncertainty in the parameter values, different choices of GQF and different prior distributions for the vector of model parameters, including normal priors with and without correlated components. Further applications to find Bayesian D‐optimal designs with two regressors for a logistic model and a two‐variable generalised linear model with a gamma distributed response are discussed, and some limitations of our approach are noted.     

非线性古诺模型下的供应链协调问题研究

针对市场需求与资源投入并不一定呈线性增长的特点,在完全信息静态古诺模型的基础上,当面对共同的供应商时,分析在独立市场与竞争市场下的销售商与供应商的利润函数,并在利润驱动导向的前提下,研究其市场进入决策问题。研究发现:当进入成本低于某一阈值,企业应选择进入市场,并且在竞争市场中会降低在位企业的最优定价,减少其市场份额。     

高层双塔结构的静力弹塑性Pushover研究分析

高层双塔结构是一种复杂高层结构,文章基于静力弹塑性Pushover方法分析了高层大底盘双塔结构的地震反应特性,研究了自振周期、振型特点、地震作用和结构位移等特点,对常用的高层双塔结构的动力特性有了进一步认识,并为设计提出了一些有益的建议。     

An Overview of Normal Theory Structural Measurement Error Models

This paper gives an introduction and overview to the often under‐used measurement error model. The purpose is to provide a simple summary of problems that arise from measurement error and of the solutions that have been proposed. We start by describing how measurement error models occur in real‐world situations. Then we proceed with defining the measurement error model, initially introducing the multivariate form of the model, and then, starting with the simplest form of the model thoroughly discuss its features and solutions to the problems introduced due to measurement error. We discuss higher‐dimensional and more advanced forms of the model and give a brief numerical illustration.     

An example of indifference prices under exponential preferences

The aim herein is to analyze utility-based prices and hedging strategies. The analysis is based on an explicitly solved example of a European claim written on a nontraded asset, in a model where risk preferences are exponential, and the traded and nontraded asset are diffusion processes with, respectively, lognormal and arbitrary dynamics. Our results show that a nonlinear pricing rule emerges with certainty equivalent characteristics, yielding the price as a nonlinear expectation of the derivatives payoff under the appropriate pricing measure. The latter is a martingale measure that minimizes its relative to the historical measure entropy.Received: July 2003, Mathematics Subject Classification: 93E20, 60G40, 60J75JEL Classification: C61, G11, G13The second author acknowledges partial support from NSF Grants DMS-0102909 and DMS-0091946. We have received valuable comments from the participants at the Conferences in Paris IX, Dauphine (2000), ICBI Barcelona (2001) and 14th Annual Conference of FORC Warwick (2001). While revising this work, we came across the paper by Henderson (2002) in which a special case of our model is investigated     

U.S.-Based Fast-Food Restaurants: Factors Influencing the International Expansion of Franchise Systems

Studies of international franchising are scant but increasing and can be divided into two streams of research: those focusing on environmental predictors of internationalization and those focusing on strategic, firm-level characteristics. Examining the latter category, this study empirically explores a set of firm-level attributes as predictors of decision making on whether firms seek international expansion. Using longitudinal data from Bond's Franchise Guide 2001–2008, we draw on a sample of U.S.-based fast-food franchise systems to test our hypotheses. Specifically, our database is composed of 1,058 observations of 158 chains, and we estimate a semi-parametric logistic model for international franchising. The model contributes to the literature by being the first to examine the nonlinearity of international franchising determinants using agency theory. The results show that (a) bonding, (b) the percentage of franchised units, (c) the number of states within which the system operates, and (d) the provision of area development agreements and sub-franchising significantly contribute to the international expansion of U.S.-based fast-food franchisors.     

Volatility Spillovers and the Risk-Return Relation Between Stock and Foreign Exchange Markets in Brazil

We examine the evidence of mean and volatility spillovers between stock and foreign exchange markets in Brazil with multivariate GARCH models and nonlinear Granger causality tests. We also use a multivariate GARCH-in-mean model to assess the relationship between risk and return in these markets. The results indicate that the stock market leads the foreign exchange market in price formation and that nonlinear Granger causalities from the exchange market to the stock market do occur. Part of these nonlinear causalities are explained by volatility spillovers. We show that exchange rate volatility affects not only stock market volatility but also stock returns.