Forecasting China's foreign exchange reserves using dynamic model averaging: The roles of macroeconomic fundamentals,financial stress and economic uncertainty

We develop models for examining possible predictors of growth of China's foreign exchange reserves that embrace Chinese and global trade, financial and risk (uncertainty) factors. Specifically, by comparing with other alternative models, we show that the dynamic model averaging (DMA) and dynamic model selection (DMS) models outperform not only linear models (such as random walk, recursive OLS-AR(1) models, recursive OLS with all predictive variables models) but also the Bayesian model averaging (BMA) model for examining possible predictors of growth of those reserves. The DMS is the best overall across all forecast horizons. While some predictors matter more than others over the forecast horizons, there are few that stand the test of time. The US–China interest rate differential has a superior predictive power among the 13 predictors considered, followed by the nominal effective exchange rate and the interest rate spread for most of the forecast horizons. The relative predictive prowess of the oil and copper prices alternates, depending on the commodity cycles. Policy implications are also provided.     

个体不健康影响因素研究

社会的急速发展和重大变化给人们带来了很多富足的物质条件和特殊机遇,同时也带来了各种新的挑战、压力与不适应。究其原因是多方面的,是遗传素质、环境、教育(特指学校教育)、个人主观能力性综合作用的结果。本文从这四个方面,就个人成长过程中主观意志与客观环境的影响作用进行深入分析。     

Econometrics and equilibrium models

In Rational Econometric Man, Edward Nell and Karim Errouaki present a welcome and timely case for the view that econometrics and econometric model-building may not be the magic tools to solve all empirical questions despite what many seem to have thought they were in the 1960s. Here I examine some possible problems with econometric models that have to do with their usually taking the form of equilibrium models. Some of these problems were recognized by Trygve Haavelmo decades ago. And as Aris Spanos has recently discussed, the problems are often the result of what we say in our textbooks. Some problems have to do with what we mean by econometric parameters and others with how we use probabilities.     

DEMAND,CUSTOMER BASE‐LINE AND DEMAND RESPONSE IN THE ELECTRICITY MARKET: A SURVEY

The increasing use of demand‐side management, as a tool to reliably meet electricity demands at peak time, has stimulated interest among researchers, consumers and producer organiza‐tions, managers, regulators and policymakers. This research reviews the growing literature on models which are used to study demand, customer base‐line (CBL) and demand response in the electricity market. After characterizing the general demand models, the CBL, based on which the demand response models are studied, is reviewed. Given the experience gained from the review and existing conditions, the study combines an appropriate model for each case for a possible application to the electricity market; moreover, it discusses the implications of the results. In the literature, these aspects are studied independently. The main contribution of this survey is attributed to the treatment of the three issues as sequentially interdependent. The review is expected to enhance the understanding of the demand, CBL and demand response in the electricity market and their relationships. The objective is conducted through a combination of demand and supply side managements in order to reduce demand through different demand response programs during peak times. This enables electricity suppliers to save costly electricity generation and at the same time reduce energy vulnerability.     

On estimating long-run effects in models with lagged dependent variables

A common procedure in economics is to estimate long-run effects from models with lagged dependent variables. For example, macro panel studies frequently are concerned with estimating the long-run impacts of fiscal policy, international aid, or foreign investment.Our analysis points out the hazards of this practice. We use Monte Carlo experiments to demonstrate that estimating long-run impacts from dynamic models produces unreliable results.Biases can be substantial, sample ranges very wide, and hypothesis tests can be rendered useless in realistic data environments. There are three reasons for this poor performance. First, OLS estimates of the coefficient of a lagged dependent variable are downwardly biased in finite samples. Second, small biases in the estimate of the lagged, dependent variable coefficient are magnified in the calculation of long-run effects. And third, and perhaps most importantly, the statistical distribution associated with estimates of the LRP is complicated, heavy-tailed, and difficult to use for hypothesis testing. While many of the underlying problems have been long-known in the literature, the continued widespread use of the associated empirical procedures suggests that researchers are unaware of the extent and severity of the estimation problems. This study aims to illustrate their practical importance for applied research.     

再思社会科学方法论的形式主义与实质主义之争——以经济学的新进展为例

笔者从社会科学方法论中的形式主义与实质主义之争这一古老论题出发,阐明了经济学中的形式主义思想在最近半个世纪的发展是建立细节完全刻画的"全模型",并指出其背后的理念不在于建立普遍规律,而在于形成可以用以启发人们理解经验世界的辅助性认知手段。在澄清全模型方法认识论价值的同时,本文也指出其应用重点不在于形成理想化与意识形态化的叙事,而在于针对局域的经验事实,建立具有确定经验限定意涵的模型化推论,以阐明经验事实背后不易被单纯质性研究阐发的机制。当代经济学方法论显示的这一发展,可以被称为"形式主义经济学的实质主义化",对这一趋势的把握有助于揭示主流经济学独特的认识论价值。     

Analysing enterprise architecture maturity models: a learning perspective

In order to aid organisations in the adoption of enterprise architecture (EA) best practices, maturity models have been proposed in the literature. These models offer organisational roadmaps and assessment frameworks for increasing EA maturity. However, key questions concerning the implied meaning of the term maturity in the context of these models have been left unexplored by previous research. This research, aided by the field of organisational learning, offers new insights into the implied assumptions of current EA maturity models and offers initial concepts and constructs to guide the conceptualisation, construction and refinement of enterprise maturity models.     

CLOSED FORM PRICING FORMULAS FOR DISCRETELY SAMPLED GENERALIZED VARIANCE SWAPS

Most of the existing pricing models of variance derivative products assume continuous sampling of the realized variance processes, though actual contractual specifications compute the realized variance based on sampling at discrete times. We present a general analytic approach for pricing discretely sampled generalized variance swaps under the stochastic volatility models with simultaneous jumps in the asset price and variance processes. The resulting pricing formula of the gamma swap is in closed form while those of the corridor variance swaps and conditional variance swaps take the form of one‐dimensional Fourier integrals. We also verify through analytic calculations the convergence of the asymptotic limit of the pricing formulas of the discretely sampled generalized variance swaps under vanishing sampling interval to the analytic pricing formulas of the continuously sampled counterparts. The proposed methodology can be applied to any affine model and other higher moments swaps as well. We examine the exposure to convexity (volatility of variance) and skew (correlation between the equity returns and variance process) of these discretely sampled generalized variance swaps. We explore the impact on the fair strike prices of these exotic variance swaps with respect to different sets of parameter values, like varying sampling frequencies, jump intensity, and width of the monitoring corridor.     

Collaborative commerce in tourism: implications for research and industry

Technology advances enable people to trade and sell their own travel products, which in turn create numerous transformation changes into the tourism industry structure, the nature of tourism products and experiences, the competitiveness of traditional and new tourism players and the process creating (social) value in tourism. This paper investigates the application and implications of collaborative commerce in tourism and provides suggestions for future research.     

Identifying terms of trade shocks in a developing country using a sign restrictions approach

Using annual data for Botswana from 1960 to 2012, we examine the responses of macroeconomic variables to four generalized positive terms of trade shocks – global demand, globalizing, sector-specific and global supply. A sign-restricted structural vector autoregression model with a penalty function is estimated to identify the four possible shocks. While positive global demand and globalization shocks are both expansionary, they have opposite effects on inflation. A positive commodity market specific shock dampens real GDP growth and is inflationary, suggesting a possible Dutch disease response. A negative global supply shock suppresses both output growth and inflation. All but the last shock leads to a significant declining interest rate. Monetary policy contraction is recommended for the first shock and expansion for the others.