Factor reallocation and structural transformation implications of grain subsidies in China

Since agriculture has contributed significantly to China’s economic growth miracle, it is important to understand the contributions and determinants of agriculture related to different agricultural policies in structural transformation in China. However, as one of the most important agricultural policies in China, the effects of the grain subsidy policy on factor reallocation, economic growth, as well as agricultural and non-agricultural production have not been investigated systematically and comprehensively. The absence of using an economy-wide model to estimate the impacts of the grain subsidy policy in China leaves a vacuum in the policy-advising space. This research develops a dynamic single-country, multi-regional computable general equilibrium model of the Chinese economy to evaluate the historical impacts of the grain subsidy policy. Our results reveal that grain subsidies impede the efficiency of factor reallocation and economic structural transformation in China. However, grain subsidies promote grain production growth and temporarily reduce rural-urban income disparity. In order to achieve the long-term sustainable increase in rural income and to mitigate the rural-urban income gap, China needs to further develop its labor-intensive industries (e.g., services) to accommodate the large number of rural labor transfers. Moreover, the large-scale agricultural production and technology improvement in agriculture are the effective measures to ensure food security in China.     

On the seasonality in the implied volatility of electricity options

Seasonality is an important topic in electricity markets, as both supply and demand are dependent on the time of the year. Clearly, the level of prices shows a seasonal behaviour, but not only this. Also, the price fluctuations are typically seasonal. In this paper, we study empirically the implied volatility of options on electricity futures, investigate whether seasonality is present and we aim at quantifying its structure. Although typically futures prices can be well described through multi-factor models including exponentially decreasing components, we do not find evidence of exponential behaviour in our data set. Generally, a simple linear shape reflects the squared volatilities very well as a curve depending on the time to maturity. Moreover, we find that the level of volatility exhibits clear seasonal patterns that depend on the delivery month of the futures. Furthermore, in an out-of-sample analysis we compare the performance of several implementations of seasonality in the one-factor framework.     

FACTOR MODELS AND TIME‐VARYING PARAMETER FRAMEWORK FOR FORECASTING EXCHANGE RATES AND INFLATION: A SURVEY

A survey of models used for forecasting exchange rates and inflation reveals that the factor‐based and time‐varying parameter or state space models generate superior forecasts relative to all other models. This survey also finds that models based on Taylor rule and portfolio balance theory have moderate predictive power for forecasting exchange rates. The evidence on the use of Bayesian Model Averaging approach in forecasting exchange rates reveals limited predictive power, but strong support for forecasting inflation. Overall, the evidence overwhelmingly points to the context of the forecasts, relevance of the historical data, data transformation, choice of the benchmark, selected time horizons, sample period and forecast evaluation methods as the crucial elements in selecting forecasting models for exchange rate and inflation.     

Thai inflation dynamics: A view from disaggregated price data

This paper utilizes disaggregated prices at the micro level to examine the patterns of price adjustment in Thailand. Among the key stylized facts, we found that the frequency of price changes are generally low, prices decreases are common, the size of price changes are large relative to the inflation rate, and there is significant dispersion in price levels as well as in the synchronicity of price changes across regions. To better understand the underlying sources of heterogeneous price dynamics, we conduct dynamic factor analyses and highlight the importance of relative price changes in driving the bulk of overall CPI movements. This suggests an important role of non-monetary factors in driving inflation. A significant Phillips curve relation is detected once idiosyncratic price changes are filtered out, reinforcing the importance of disaggregated analysis of price trends in the conduct of monetary policy.     

Output and input bias effects of U.S. direct payments

This study examines the national effect of U.S. direct payments on the extent and direction of biased technical change on U.S. agriculture. We also assess the economic significance of the estimated bias effects for economic policy modeling endeavors involving a reduction of domestic support payments. A two outputs (livestock and crops) and four inputs (labor, capital, land, and material) translog cost function was estimated from national time series (1948–2011) data. Results indicate that payments do not induce output‐biased technical change. We do find evidence of Hicksian bias that is land using and material input saving attributable to support payments. Global computable general equilibrium simulations suggest that price and output effects of discontinuing direct payments are 1/4 to 1/3 the size once the bias effects are incorporated.     

基于扎根理论的新能源企业绿色创新意愿驱动因素研究

新时代下传统能源企业期望通过绿色创新获得持续竞争力，因此，探究能源型企业转型驱动“黑箱”是当前亟待解决的问题。应用扎根理论的质性研究方法，构建企业绿色创新意愿驱动模型，提炼出驱动新能源企业绿色创新意愿形成的5个主范畴，对核心范畴与主范畴、主范畴间的相互作用关系进行阐述，从而探究新能源企业绿色创新意愿驱动机理。     

Forecasting stock returns with large dimensional factor models

We study equity premium out-of-sample predictability by extracting the information contained in a high number of macroeconomic predictors via large dimensional factor models. We compare the well-known factor model with a static representation of the common components with the Generalized Dynamic Factor Model, which accounts for time series dependence in the common components. Using statistical and economic evaluation criteria, we empirically show that the Generalized Dynamic Factor Model helps predicting the equity premium. Exploiting the link between business cycle and return predictability, we find accurate predictions also by combining rolling and recursive forecasts in real-time.     

信息化冲击、交易成本与企业TFP——基于国家智慧城市建设的自然实验

智慧城市建设一般伴随着城市信息化水平的“意外”提升。本文将中国2012年智慧城市试点建设作为信息化冲击的自然实验,构建了智慧城市建设影响企业全要素生产率(TFP)的交易成本理论分析框架。基于2003—2016年中国地级市和上市公司匹配面板数据,运用双重差分法(DID)、倾向得分匹配双重差分法(PSM-DID)和三重差分法(DDD)实证检验了智慧城市建设产生的信息化冲击对企业全要素生产率的影响及其机制。实证结论表明,智慧城市建设这一信息化冲击显著提升了企业全要素生产率。机制检验表明,信息化冲击通过降低企业交易成本,从而提高企业全要素生产率。进一步异质性检验表明,智慧城市建设产生的信息化冲击对资本密集度更高、规模更大企业的全要素生产率促进作用更加明显;相对于非国有企业,智慧城市建设产生的信息化冲击对国有企业产生了较大影响;相对于非交易行业,交易行业由于智慧城市建设导致的交易成本下降,企业全要素生产率提升更明显。     

高速铁路客运餐饮服务满意度影响因素重要度探讨

随着我国高速铁路客运量的急速增长,对高速铁路客运餐饮服务质量要求也逐渐提升,为了进一步提高旅客对高速铁路客运餐饮服务的满意度,以顾客感知视角,分析高速铁路客运餐饮服务满意度影响因素构成,利用结构方程模型对高速铁路客运餐饮满意度影响因素重要程度进行测评。以上海虹桥站、南京南站为例进行验证,结果表明:餐品安全卫生对满意度有最显著的重要影响,其次是服务水平、订餐管理和餐品质量。其中,保质期在安全卫生方面影响效应最大,送餐时间在服务水平中影响效应最大;餐品质量潜变量中,餐品营养价值和口味影响效应较大。