952 resultados para Econometric Model
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Bibliography: p. 30-34.
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At head of title: NRIES.
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The Asian International Input-Output (IO) Table that is compiled by Institute of Developing Economies-JETRO (IDE), was constructed in Isard type form. Thus, it required a lot of time to publish. In order to avoid this time-lag problem and establish a more simple compilation technique, this paper concentrates on verifying the possibility of using the Chenery-Moses type estimation technique. If possible, applying the Chenery-Moses instead of the Isard type would be effective for both impact and linkage analysis (except for some countries such as Malaysia and Singapore and some primary sectors. Using Chenery-Moses estimation method, production of the Asian International IO table can be reduced by two years. And more, this method might have the possibilities to be applied for updating exercise of Asian IO table.
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With regression formulas replaced by equilibrium conditions, a spatial CGE model can substantially reduce data requirements. Detailed regional analyses are thus possible in countries where only limited regional statistics are available. While regional price differentials play important roles in multi-regional settings, transport does not receive much attention in existing models. This paper formulates a spatial CGE model that explicitly considers the transport sector and FOB/CIF prices. After describing the model, performance of our model is evaluated by comparing the benchmark equilibrium for China with survey-based regional I-O and interregional I-O tables for 1987. The structure of Chinese economies is summarized using information obtained from the benchmark equilibrium computation. This includes regional and sectoral production distributions and price differentials. The equilibrium for 1997 facilitates discussion of changes in regional economic structures that China has experienced in the decade.
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The Armington Assumption in the context of multi-regional CGE models is commonly interpreted as follows: Same commodities with different origins are imperfect substitutes for each other. In this paper, a static spatial CGE model that is compatible with this assumption and explicitly considers the transport sector and regional price differentials is formulated. Trade coefficients, which are derived endogenously from the optimization behaviors of firms and households, are shown to take the form of a potential function. To investigate how the elasticity of substitutions affects equilibrium solutions, a simpler version of the model that incorporates three regions and two sectors (besides the transport sector) is introduced. Results indicate: (1) if commodities produced in different regions are perfect substitutes, regional economies will be either autarkic or completely symmetric and (2) if they are imperfect substitutes, the impact of elasticity on the price equilibrium system as well as trade coefficients will be nonlinear and sometimes very sensitive.
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This paper estimates the elasticity of labor productivity with respect to employment density, a widely used measure of the agglomeration effect, in the Yangtze River Delta, China. A spatial Durbin model is presented that makes explicit the influences of spatial dependence and endogeneity bias in a very simple way. Results of Bayesian estimation using the data of the year 2009 indicate that the productivity is influenced by factors correlated with density rather than density itself and that spatial spillovers of these factors of agglomeration play a significant role. They are consistent with the findings of Ke (2010) and Artis, et al. (2011) that suggest the importance of taking into account spatial dependence and hitherto omitted variables.
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This paper presents a framework for an SCGE model that is compatible with the Armington assumption and explicitly considers transport activities. In the model, the trade coefficient takes the form of a potential function,and the equilibrium market price becomes similar to the price index of varietal goods in the context of new economic geography (NEG). The features of the model are investigated by using the minimal setting, which comprises two non-transport sectors and three regions. Because transport costs are given exogenously to facilitate study of their impacts, commodity prices are also determined relative to them. The model can be described as a system of homogeneous equations, where an output in one region can arbitrarily be determined similarly as a price in the Walrasian equilibrium. The model closure is sensitive to formulation consistency so that homogeneity of the system would be lost by use of an alternative form of trade coefficients.
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Chinese government commits to reach its peak carbon emissions before 2030, which requires China to implement new policies. Using a CGE model, this study conducts simulation studies on the functions of an energy tax and a carbon tax and analyzes their effects on macro-economic indices. The Chinese economy is affected at an acceptable level by the two taxes. GDP will lose less than 0.8% with a carbon tax of 100, 50, or 10 RMB/ton CO2 or 5% of the delivery price of an energy tax. Thus, the loss of real disposable personal income is smaller. Compared with implementing a single tax, a combined carbon and energy tax induces more emission reductions with relatively smaller economic costs. With these taxes, the domestic competitiveness of energy intensive industries is improved. Additionally, we found that the sooner such taxes are launched, the smaller the economic costs and the more significant the achieved emission reductions.
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This paper explores the potential usefulness of an AGE model with the Melitz-type trade specification to assess economic effects of technical regulations, taking the case of the EU ELV/RoHS directives as an example. Simulation experiments reveal that: (1) raising the fixed exporting cost to make sales in the EU market brings results that exports of the targeted commodities (motor vehicles and parts for ELV and electronic equipment for RoHS) to the EU from outside regions/countries expand while the domestic trade in the EU shrinks when the importer's preference for variety (PfV) is not strong; (2) if the PfV is not strong, policy changes that may bring reduction in the number of firms enable survived producers with high productivity to expand production to be large-scale mass producers fully enjoying the fruit of economies of scale; and (3) When the strength of the importer's PfV is changed from zero to unity, there is the value that totally changes simulation results and their interpretations.
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The significant gains in export market shares made in a number of vulnerable euro-area crisis countries have not been accompanied by an appropriate improvement in price competitiveness. This paper argues that, under certain conditions, firms consider export activity as a substitute for serving domestic demand. The strength of the link between domestic demand and exports is dependent on capacity constraints. Our econometric model for six euro-area countries suggests domestic demand pressure and capacity-constraint restrictions as additional variables of a properly specified export equation. As an innovation to the literature, we assess the empirical significance through the logistic and the exponential variant of the non-linear smooth transition regression model. We find that domestic demand developments are relevant for the short-run dynamics of exports in particular during more extreme stages of the business cycle. A strong substitutive relationship between domestic and foreign sales can most clearly be found for Spain, Portugal and Italy, providing evidence of the importance of sunk costs and hysteresis in international trade.
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Transportation Department, Washington, D.C.
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This dissertation proposes statistical methods to formulate, estimate and apply complex transportation models. Two main problems are part of the analyses conducted and presented in this dissertation. The first method solves an econometric problem and is concerned with the joint estimation of models that contain both discrete and continuous decision variables. The use of ordered models along with a regression is proposed and their effectiveness is evaluated with respect to unordered models. Procedure to calculate and optimize the log-likelihood functions of both discrete-continuous approaches are derived, and difficulties associated with the estimation of unordered models explained. Numerical approximation methods based on the Genz algortithm are implemented in order to solve the multidimensional integral associated with the unordered modeling structure. The problems deriving from the lack of smoothness of the probit model around the maximum of the log-likelihood function, which makes the optimization and the calculation of standard deviations very difficult, are carefully analyzed. A methodology to perform out-of-sample validation in the context of a joint model is proposed. Comprehensive numerical experiments have been conducted on both simulated and real data. In particular, the discrete-continuous models are estimated and applied to vehicle ownership and use models on data extracted from the 2009 National Household Travel Survey. The second part of this work offers a comprehensive statistical analysis of free-flow speed distribution; the method is applied to data collected on a sample of roads in Italy. A linear mixed model that includes speed quantiles in its predictors is estimated. Results show that there is no road effect in the analysis of free-flow speeds, which is particularly important for model transferability. A very general framework to predict random effects with few observations and incomplete access to model covariates is formulated and applied to predict the distribution of free-flow speed quantiles. The speed distribution of most road sections is successfully predicted; jack-knife estimates are calculated and used to explain why some sections are poorly predicted. Eventually, this work contributes to the literature in transportation modeling by proposing econometric model formulations for discrete-continuous variables, more efficient methods for the calculation of multivariate normal probabilities, and random effects models for free-flow speed estimation that takes into account the survey design. All methods are rigorously validated on both real and simulated data.
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Forecasting volatility has received a great deal of research attention, with the relative performances of econometric model based and option implied volatility forecasts often being considered. While many studies find that implied volatility is the pre-ferred approach, a number of issues remain unresolved, including the relative merit of combining forecasts and whether the relative performances of various forecasts are statistically different. By utilising recent econometric advances, this paper considers whether combination forecasts of S&P 500 volatility are statistically superior to a wide range of model based forecasts and implied volatility. It is found that a combination of model based forecasts is the dominant approach, indicating that the implied volatility cannot simply be viewed as a combination of various model based forecasts. Therefore, while often viewed as a superior volatility forecast, the implied volatility is in fact an inferior forecast of S&P 500 volatility relative to model-based forecasts.