城镇就业市场上劳动力工资扭曲程度测度

本文利用CHIPS2007数据库，基于随机前沿模型对我国城镇就业市场上劳动力的工资扭曲程度进行测度。研究结果表明：（1）在城镇就业市场上，由于工资扭曲现象的存在，劳动力实际获得的工资要比他们的边际生产率低45％～60％；（2）已婚、子女个数较少、本地、拥有失业保险、男性、大中型企业的劳动力工资扭曲程度要低于未婚、子女个数较多、外来、没有失业保险、女性、小型企业的劳动力；（3）中低工资水平的劳动力工资扭曲程度要比高工资水平的劳动力严重，且中低工资水平劳动力工资扭曲程度的方差更大。由此，本文提出推进就业市场的市场化改革，完善就业市场信息网络，从而减轻劳动力工资扭曲程度。     

Assessment of land use compatibility and noise pollution at Imam Khomeini International Airport

This study aimed to investigate land use planning around airports, by employing Remote Sensing (RS) and Geographic Information Systems (GIS), in conjunction with an optimization algorithm using an Integrated Noise Model (INM) software, to establish the potential effects of aircraft noise at Imam Khomeini International Airport (IKIA) in Tehran. We also checked for land use compatibility with the noise levels around IKIA and the residents' reaction to the noise. The research was carried out in three stages: a) the establishment of Strategic Noise Map (SNM) scenarios of the airport operation in the years 2011, 2020 and 2030 using the INM software; b) the assessment of the results with emphasis on the study area land uses and application of RS and GIS and the exposure of residents at different levels of environmental noise; and c) the assessment of the intensity of aircraft noise annoyance at various times of day and night. The results indicated that developing IKIA together with the residential development will increase airport noise. Hence proper management and control of noise at IKIA is essential.     

Decision-making in incomplete markets with ambiguity—a case study of a gas field acquisition

We apply utility indifference pricing to solve a contingent claim problem, valuing a connected pair of gas fields where the underlying process is not standard Geometric Brownian Motion and the assumption of complete markets is not fulfilled. First, empirical data are often characterized by time-varying volatility and fat tails; therefore, we use Gaussian generalized autoregressive score (GAS) and GARCH models, extending them to Student’s t-GARCH and t-GAS. Second, an important risk (reservoir size) is not hedgeable. As a result, markets are incomplete which makes preference free pricing impossible and thus standard option pricing methodology inapplicable. Therefore, we parametrize the investor’s risk preference and use utility indifference pricing techniques. We use Least Squares Monte Carlo simulations as a dimension reduction technique in solving the resulting stochastic dynamic programming problems. Moreover, an investor often only has an approximate idea of the true probabilistic model underlying variables, making model ambiguity a relevant problem. We show empirically how model ambiguity affects project values, and importantly, how option values change as model ambiguity gets resolved in later phases of the projects. We show that traditional valuation approaches will consistently underestimate the value of project flexibility and in general lead to overly conservative investment decisions in the presence of time-dependent stochastic structures.     

Identifying Discretionary Fiscal Policy Reactions with Real‐Time Data

We propose a method of identifying discretionary fiscal policy reactions using real‐time data. Automatic stabilizers should depend on true GDP, while discretionary fiscal policy is contingent on the information that policy makers have in real time. We can compute a real‐time measurement error by comparing the first release of GDP data with later revisions. Discretionary fiscal policy is influenced by this measurement error, whereas automatic fiscal policy is not. We use this identification approach to test the central identifying assumption of Blanchard and Perotti’s (2002) seminal structural vector autoregression (VAR). According to this assumption, fiscal policy makers do not react to GDP developments contemporaneously in a discretionary fashion. We find that government expenditure is adjusted upward if GDP growth in real time is lower than true GDP. This suggests that fiscal policy makers use short‐term funds to buy goods and services in response to their perception of GDP dynamics.     

Exchange rate effect on carbon credit price via energy markets

This paper examines the impact of currency exchange rates on the carbon market. We scrutinize this effect through the European Union Emission Trading Scheme (EU-ETS), which primarily uses two substitutable fossil energy inputs for the generation of electricity: coal and natural gas. The European coal market is directly driven by global coal markets that are denominated in USD, whereas, natural gas is mainly imported from Russia and is denominated in Euros. The impulse response functions of a Structural Vector Autoregression (SVAR) model demonstrate that a shock in the Euro/USD exchange rate can be transmitted through the channel of energy substitution between coal and natural gas, and influence on the carbon credit market.     

CO‐INTEGRATING VAR MODELS AND ECONOMIC POLICY

This paper surveys some relevant contributions to the economic literature on co‐integrating vector autoregressive (VAR) models [vector error correction mechanisms (VECMs)], emphasizing their usefulness for economic policy. It further discusses some theoretical aspects that are necessary for a complete understanding of their potential. The theoretical introduction of the co‐integrating VAR model is followed by an illustration of its applications to monetary policy, fiscal policy and exchanges rates as well as in establishing the effects of structural bilateral shocks between countries (the so‐called global VAR, or GVAR, models). Special attention is paid to the VECM capacities of being used in conjunction with dynamic stochastic general equilibrium models and of jointly specifying the short‐ and long‐run dynamics, thus representing the steady‐state of economic systems (by means of the co‐integration relations) and the short‐run dynamics around it.     

基于钻石模型的滨海新区制造业产业集群发展研究

天津滨海新区升格为国家级综合改革试验区的战略目标,是把以滨海新区为增长极的京津冀打造为环渤海乃至中国北方经济增长的发动机和最具国际竞争力的都市圈。本文借鉴迈克尔·波特的国家竞争优势钻石模型,构建一个地区制造业升级的竞争模型,并借助于这一模型对滨海新区制造业产业集群竞争力进行分析,从而就提升其产业集群竞争力进行了对策探析。     

'More is not necessarily better': the relationship between the quantity and quality of training efforts

International comparisons indicate that, on average, Belgian companies spend less on training than their French, German and Dutch counterparts. Encouraging companies to commit to training has consequently been an important policy goal over the last few years. One notable aspect of the policy to encourage training efforts by companies is that the effort is always represented in terms of the resources invested (input), not in terms of the learning achieved (output) or the quality of training programmes (throughput). Government policy is aimed at increasing the level of investment in company training. One of the questions we wish to investigate is whether this input-oriented approach to the training issue is actually effective. Whether companies will succeed in raising human capital to ever-increasing levels may depend not only (and maybe not even chiefly) on the extent of financial investment in training. The investment level does not necessarily determine the quality of the training processes developed by companies. Therefore, this paper focuses on the following research questions: (1) to what extent do companies monitor the systematic development of sufficiently effective training processes? In other words, is qualitative under-investment an issue, alongside financial under-investment? (2) Is the level of financial investment in company training correlated to the quality of training processes? The empirical data confirm that a kind of 'qualitative' under-investment can be reported and that the relationship between the level of investment in training and the quality of the training programmes is weak.     

企业价值评估贴现模型的比较分析

贴现模型是企业价值评估中应用较为普遍的模型,但在我国实践中使用贴现模型存在很多问题。本文利用自由现金流量贴现法、调整现值法、经济利润贴现法三种常用的方法,探讨贴现模型不同参数指标的原理、使用原则、使用条件及在我国实践中的适应性,希望讨论能够为企业价值评估实务提供指导和帮助。     

Impact of Financial Development on the Environmental Quality in Iran

In recent decades, undesirable environmental changes, such as global warming and greenhouse gases emission, have raised worldwide concerns. In order to achieve higher growth rate, environmental problems emerged from economic activities have turned into a controversial issue. The aim of this study is to investigate the effect of financial development on environmental quality in Iran. For this purpose, the statistical data over the period from 1970 to 2011 were used. Also by using the Auto Regression Model Distributed Lag （ARDL）, short-term and long-term relationships among the variables of model were estimated and analyzed. The results show that financial development accelerates the degradation of the environment; however, the increase in trade openness reduces the damage to environment in Iran. Error correction coefficient shows that in each period, 53% of imbalances would be justified and will approach their long-run procedure. Structural stability tests show that the estimated coefficients were stable over the period.