基于系统动力学的区域物流供需机理分析——以天津市为例

在界定区域物流供给与物流需求的基础上,分析了影响区域物流供给和需求的主要因果关系,并建立了区域物流供需的系统动力学模型,利用该模型仿真模拟了天津市物流业供给和需求之间相互影响的动态过程,最终得到实现区域物流供需平衡的物流业增长率的理论最优值,从而为地区确定合理的物流业增长率目标提供理论上的参考。     

Interregional Input–Output Modelling in Indonesia: A Constrained Growth Rate Approach with Endogenous Investment

In interregional input–output (IO) models, investment can be endogenized in many different ways, varying from dynamic Leontief-type solutions to computable general equilibrium (CGE) models. However, large versions of these models are difficult to implement because of the absence of the required data. In this paper, a different, less data-demanding treatment of regional investment is presented for an interregional IO forecasting model in which a simultaneous solution is given for regional GDP by industry, on the one hand, and for regional aggregate investment, on the other hand. In this way, investment plays its role as a disaggregate demand factor by industry and region, as well as being an aggregate supply constraint on regional capital stock at the same time. Some empirical results are presented for a 27-region model in Indonesia, which has been used by the government during the preparations for the new national 5-year plan for 1994–1999.     

Growth,unemployment and heterogeneity

The paper analyzes unemployment in a medium-run growth model, where aggregate demand and supply interact, using a top-down approach. The aim of the essay is the study of a nonlinear system where both aggregate demand and supply are endogenous and generate bounded unemployment, followed by a methodological effort direct to identify possible lines of convergence with the agent based models (ABM) approach. This is a by-product of the presence of heterogeneity in the model. Heterogeneity acts through two different channels and operates among class of agents: it comes into the aggregate consumption function where households are assumed employed or unemployed; it changes the learning process of pessimists and optimists. The analysis is carried on through simulations. The resulting system is fairly stable to changes in main structural parameters. On one hand, autonomous demand drives the dynamics of the system, while heterogeneity in the consumption function, due to the presence of unemployment, strengthens the links with supply aspects. On the other hand, both the rate of growth of labor productivity and labor supply are endogenous. Two major results are obtained. First, unemployment allows the so called Harrodian reconciliation between aggregate demand and supply. Second, unemployment remains bounded meaning that the interaction between aggregate demand and supply thwarts instability. These results are in keeping with those obtained by means of a bottom-up approach, typical of ABM. Possible explanations and implications of this convergence are put forward and open the venue to further deepening of complementarities among the two modeling strategies.

     

Demand and supply estimation biases due to omission of durability

We build a dynamic equilibrium model of a durable goods oligopoly with a competitive secondary market to evaluate the bias in estimating the structural parameters of demand and supply when durability is omitted. We simulate data from our dynamic model and use them to estimate the model’s static counterpart. We find that the static estimate of the elasticity of demand is an overestimate of the true elasticity and that the static estimate of the markup is an underestimate. Our results provide a benchmark on the magnitude and sign of the bias when static models are used for economic inference.     

长三角物流发展和经济增长关系实证分析

文章采用2005~2012年长三角经济圈20个城市物流业发展与区域经济增长的面板数据进行实证分析,通过对数据进行平稳性检验和协整检验,证实了物流业发展和经济增长之间存在着长期协整关系。回归分析中Hausman检验拒绝存在随机效应的原假设,采用固定效应模型分析面板数据,发现物流业发展的三个指标,物流产业规模、物流供给规模和物流需求规模均和区域经济增长之间存在正相关关系,不同城市组别的回归分析发现,不同的区域经济发展策略对物流发展和经济增长之间的关系有着不同的影响。     

Interindustry analysis for regional growth and development: The dynamics of manpower issues

Simulations of two scenarios to illustrate processes of regional interindustrial growth and development suggest the dynamics of manpower issues. Using the core of the Sequential Interindustry Model, SIM, the dynamics by which interindustry production supplies continuing final markets is presented and the resulting industry production chronologies illustrated. The latter are transformed into employment chronologies from which labor requirements are computed as distributions of potential jobs by job duration and job starts.Adjustments in potential jobs to represent the dynamic linkages between manpower demand and supply in fluctuating labor markets are discussed as an extension of adaptive behavior in SIM. An encompassing impact dynamics framework for manpower assessment is suggested, including examination of management options of both demand and supply for timely impact mitigation.     

Coefficient Change in Embedded Econometric and Input–Output Models at the Regional Level

This paper examines the nature of coefficient change in integrated econometric (EC) and input–output (IO) models that employ an embedding strategy. Existing approaches towards coefficient change in integrated models are first reviewed and several substantive processes that give rise to dynamic coefficients at the regional level are identified. The main sources of coefficient change arise from dynamic adjustment processes that affect the regional purchase coefficients, regional technological coefficients and regional integration parameters. Each of these sources of change requires a different treatment when adopting an EC perspective. A general framework is suggested that nests each treatment as a specific case. The different specifications are then implemented in an embedded EC and IO employment demand model for the San Diego region, and evaluated through a series of in-sample and out-of-sample forecasting experiments. Simulation performance is found to improve through the use of a time-varying integra tion parameter. The results also indicate that model performance is more sensitive to the use of dynamic regional purchase coefficients than to the use of dynamic technical coefficients.     

MODELS OF REGIONAL GROWTH: PAST,PRESENT AND FUTURE

Abstract This paper presents an overview of various models of regional growth that have appeared in the literature in the last 40 years. It considers the past, and therefore supply‐side models, such as the standard neoclassical, juxtaposed against essentially demand‐side approaches such as the export‐base and cumulative causation models (as integrated into the Kaldorian approach); before moving on to the ‘present’ and more recent versions of the neoclassical model involving spatial weights and ‘convergence clubs’, as well as new economic geography core–periphery models, and the ‘innovation systems’ approach. A key feature of the more recent literature is an attempt to explicitly include spatial factors into the model, and thus there is a renewed emphasis on agglomeration economies and spillovers. Discussing ‘present’ and ‘future’ approaches to regional growth overlaps with the current emphasis in the literature on the importance of more intangible factors such as the role of ‘knowledge’ and its influence on growth. Finally, there is a discussion of the greater emphasis that needs to be placed at the ‘micro‐level’ when considering what drives growth, and thus factors such as inter alia firm heterogeneity, entrepreneurship and absorptive capacity.     

House price synchronization across the US states: The role of structural oil shocks

This paper analyzes the impact of disentangled oil shocks on the synchronization in housing price movements across all the US states plus DC. Using a Bayesian dynamic factor model, the house price movements are decomposed into national, regional, and state-specific factors. We then study the impact of oil-specific supply and demand, inventory accumulation, and global demand shocks on the national factor using linear and nonlinear local projection methods. The impulse response analyses suggest that oil-specific supply and consumption demand shocks are most important in driving the national factor. Moreover, as observed from the regime-specific local projection model, these two shocks are found to have a relatively stronger impact in a bearish rather than a bullish national housing market. Our results have important policy implications.     

我国普通商品住房供求的影响因素及其稳定性研究

本文利用1997年到2009年全国以及各地区的房地产面板数据,借鉴蛛网模型的相关理论,构建供给与需求的联立方程,选择固定效应IV估计法拟合面板联立方程模型,对普通商品住房供求的影响因素及其稳定性进行了实证研究。结果表明,我国的普通商品住房市场处于不稳定状态,普通商品住房当期及滞后期的价格、城镇人均可支配收入、城镇就业人口、土地购置面积、经济适用房、别墅的供求状况等因素都对普通商品住房的供求变化产生较为显著的影响。     

Classification-based model selection in retail demand forecasting

Retailers supply a wide range of stock keeping units (SKUs), which may differ for example in terms of demand quantity, demand frequency, demand regularity, and demand variation. Given this diversity in demand patterns, it is unlikely that any single model for demand forecasting can yield the highest forecasting accuracy across all SKUs. To save costs through improved forecasting, there is thus a need to match any given demand pattern to its most appropriate prediction model. To this end, we propose an automated model selection framework for retail demand forecasting. Specifically, we consider model selection as a classification problem, where classes correspond to the different models available for forecasting. We first build labeled training data based on the models’ performances in previous demand periods with similar demand characteristics. For future data, we then automatically select the most promising model via classification based on the labeled training data. The performance is measured by economic profitability, taking into account asymmetric shortage and inventory costs. In an exploratory case study using data from an e-grocery retailer, we compare our approach to established benchmarks. We find promising results, but also that no single approach clearly outperforms its competitors, underlying the need for case-specific solutions.     

Residential energy demand in the United States: A regional econometric analysis

A static equilibrium and a dynamic partial adjustment model of residential demand for electricity and natural gas are presented and estimated for the United States over a recent period characterized by sharply increasing energy prices. The static model is estimated using Ordinary Least Squares while the instrumental variables method is used for the dynamic partial adjustment model. The estimates of long-run elasticities suggest the residential demand for electricity and natural gas are price and income elastic. Intercept and slope dummies used in the models identify significant regional differences in demand functions.     

Using Charm to Adjust for Cross-Hauling: The Case of the Province of Hubei,China

Data for the Chinese province of Hubei are used to assess the performance of Kronenberg's Cross-Hauling Adjusted Regionalization Method (CHARM), a method that takes explicit account of cross-hauling when constructing regional input–output tables. A key determinant of cross-hauling is held to be the heterogeneity of commodities, which is estimated using national data. However, contrary to the authors’ findings for Finland, CHARM does not generate reliable estimates of Hubei's sectoral exports, imports and volume of trade, although it is more successful in estimating sectoral supply multipliers. The poor simulations of regional trade are attributed to the fact that Hubei is a relatively small region, where there is a large divergence between regional and national technology and pattern of final demand. The simulation errors are decomposed into components reflecting differences between regional and national technology, final demand and heterogeneity. The third component is found to be the least important of the three sources of error.     

The empirical determination of technology and expectations: A simplified procedure

This paper makes three principal contributions to the growing body of empirically oriented research on dynamic factor demand systems that are based on the adjustment cost model of the firm. First, a simplified procedure is described for deriving demand and supply functions which are amenable to empirical estimation and which are consistent with intertemporal expected profit maximization and a general expectations formation process for future prices. Second, it is pointed out that estimation of a complete system of demand and supply functions permits the empirical identification of both the firm's technology and its expectations formation process. Finally, the procedure is applied to aggregate annual U.S. manufacturing data for the 1947-1977 period and the consistency of the data with the theoretical framework is investigated.     

基于CAS理论的4PL模式下物流任务分配机制比较研究

针对仅考虑物流需求方满意度与同时考虑物流需求方和供给方满意度的两种4PL模式下物流任务分配机制，以CAS理论为基础构建了两种物流任务分配机制的动态模型，并运用MATLAB7．0软件对动态模型进行仿真，得到了具有说服力的仿真结果。说明同时考虑物流需求方和供给方满意的物流任务分配机制优于仅考虑物流需求方满意的物流任务分配机制。     

A flexible dynamic model of multiproduct technology for the West German economy

This paper tests symmetry and negativity of the Slutsky matrix for a system of demand functions derived from an aggregate model of multi product technology within a flexible dynamic framework. The model considers three inputs and three outputs, including imports and exports of intermediate goods. We derive a static demand model from a trans log cost function and specify the data generation process by a stationary ARX (1, 1) model. Results based on West German quarterly data indicate that the integrability conditions are not rejected when imposed on the ARX (1, 1) model, whereas they are rejected for all the less general dynamic models considered.     

A Study of Vertical Integration and Vertical Divestiture: The Case of Store Brand Milk Sourcing in Boston

This article investigates whether a retailer’s store brand supply source impacts vertical pricing and supply channel profitability. Using chain‐level retail scanner data, a random coefficients logit demand model is estimated employing a Bayesian estimation approach. Supply models are specified conditional on demand parameter estimates. Bayesian decision theory is applied to select the best fitting pricing model. Results indicate that a vertically integrated retailer engages in linear pricing for brand manufacturers’ products while competing retailers make nonlinear pricing contracts with brand manufacturers for branded products and store brands. A simulated vertical divestiture based on real world events provides evidence for improved channel efficiency.     

THE ROLE OF INVENTORIES AND SPECULATIVE TRADING IN THE GLOBAL MARKET FOR CRUDE OIL

We develop a structural model of the global market for crude oil that for the first time explicitly allows for shocks to the speculative demand for oil as well as shocks to flow demand and flow supply. The speculative component of the real price of oil is identified with the help of data on oil inventories. Our estimates rule out explanations of the 2003–2008 oil price surge based on unexpectedly diminishing oil supplies and based on speculative trading. Instead, this surge was caused by unexpected increases in world oil consumption driven by the global business cycle. There is evidence, however, that speculative demand shifts played an important role during earlier oil price shock episodes including 1979, 1986 and 1990. Our analysis implies that additional regulation of oil markets would not have prevented the 2003–2008 oil price surge. We also show that, even after accounting for the role of inventories in smoothing oil consumption, our estimate of the short‐run price elasticity of oil demand is much higher than traditional estimates from dynamic models that do not account for for the endogeneity of the price of oil. Copyright © 2013 John Wiley & Sons, Ltd.     

Quantile regression for dynamic panel data with fixed effects

This paper studies a quantile regression dynamic panel model with fixed effects. Panel data fixed effects estimators are typically biased in the presence of lagged dependent variables as regressors. To reduce the dynamic bias, we suggest the use of the instrumental variables quantile regression method of Chernozhukov and Hansen (2006) along with lagged regressors as instruments. In addition, we describe how to employ the estimated models for prediction. Monte Carlo simulations show evidence that the instrumental variables approach sharply reduces the dynamic bias, and the empirical levels for prediction intervals are very close to nominal levels. Finally, we illustrate the procedures with an application to forecasting output growth rates for 18 OECD countries.     

Make and Use Approaches to Regional and Interregional Accounts and Models

Institutional, or sector-by-sector input–output tables have traditionally been used in regional and interregional modelling. This paper examines the origins of this tradition and argues instead, both theoretically and empirically, for the integration of make and use submodels within models of production, demand and interregional trade, outlining the manner in which they can be integrated. Further, it is argued that structural rather than reduced-form models represent a sounder theoretical base. Finally, a Danish interregional model (LINE) based on a social accounting matrix framework that employs these principles is presented. The paper also deals with the issue of data construction at the regional and interregional levels, based on the make and use approach. It is argued that when data are constructed at a low level of sectoral and spatial aggregation under accounting consistency constraints, data quality and validity are high.