Is real per capita state personal income stationary? New nonlinear,asymmetric panel-data evidence

This paper re-examines the stochastic properties of U.S. state real per capita personal income, using new panel unit-root procedures. The new developments incorporate non-linearity, asymmetry, and cross-sectional correlation within panel-data estimation. Including nonlinearity and asymmetry finds that 43 states exhibit stationary real per capita personal income whereas including only nonlinearity produces 42 states that exhibit stationarity. Stated differently, we find that two states exhibit nonstationary real per capita personal income when considering nonlinearity, asymmetry, and cross-sectional dependence.     

Self serving reference points in double auctions

We present a novel approach for modelling self serving bias by way of reference dependence. Bias is modelled as a systematic individual level deviation of the endogenous reference point from the expected price of a good in a two person k-double auction. We find that bias decreases the efficiency of the model, and that efficiency is decreasing in both the level of bias and reference dependence.     

Do GCC market-oriented labor policies encourage inward FDI flows?

In this paper, we empirically examine the impact of market-oriented labor policies on inward FDI flows to the GCC countries. The paper adopts different estimation methodologies to address endogeneity and cross-sectional dependence. Reliance on professional management reduces inward FDI flows to the UAE while linking pay to productivity reduces inward FDI flows to both Bahrain and the UAE. Trade openness and infrastructure development have a positive influence, while human capital development has a surprisingly negative influence. Evidence, therefore, does not support the view that flexible labor market policies encourage inward FDI flows to GCC countries.     

Stock market dependence in crisis periods: Evidence from oil price shocks and the Qatar blockade

This paper examines the correlation and the dependence patterns of the Qatar stock market with other markets using copula statistical theory and exploiting new datasets covering the period August 1998 to June 2018. To examine the crisis –specific change in the average degree of dependence we decomposed the data into the time periods before and after oil price shocks and the 2017 political crisis among the Gulf Cooperation Council members (i.e. the Qatari blockade). Our findings from the static copula modelling show that the correlations between the Qatari and the other stock markets significantly change after the oil price and the blockade crisis as well. The degree of change in the correlation is time varying and differs from county-group to another. Moreover, our findings reveals that the 2008 global financial crisis has a stronger impact than the price shocks and political crisis. The findings of the paper are of interest and allow for formulating a reliable and dynamic portfolio design framework for investors and risk managers.     

Oil price and Gulf Corporation Council stock indices: New evidence from time-varying copula models

Using a time-varying GJR copula approach, we determine the conditional dependence of the GCC stock indices on oil price between 2007 and 2016. We show how to improve the forecasting accuracy of the co-movement of energy and stock prices in an equally weighted portfolio. Contrary to prior findings, we demonstrate that due to the different co-movements across the GCC stock indices, portfolios of oil assets and several GCC stocks are less likely to be affected by systemic risk. The different co-movements across several stock indices over time provide different entry and exit points for stock investors. This approach is in line with the ‘buy low/sell high’ adage.     

A spatial autoregressive stochastic frontier model for panel data incorporating a model of technical inefficiency

By integrating Battese and Coelli’s (1995) model and the spatial autoregressive model (SAR), a spatial autoregressive stochastic frontier model for panel data is developed. The main feature of this frontier model is a spatial lag term of explained variables and the joint structure of a production possibility frontier with a model of technical inefficiency. The model addresses both spatial dependence and heteroskedastic technical inefficiency. This study applies maximum likelihood methods considering the endogenous spatial lag term. The proposed model nests several existing models. Further, an empirical analysis using data on the Japanese manufacturing industry is conducted and the existing models are tested against the proposed model, which is found to be statistically supported. The findings suggest that estimates in the existing spatial and non-spatial models may exhibit bias because of lack of determinants of technical inefficiency, as well as a spatial lag. This bias also affects the technical efficiency score and its ranking.     

A spatial approach to the FDI-growth nexus in Spain: Dealing with the headquarters effect

This paper examines the effects of inward FDI on economic growth across the Spanish regions over the period 1996–2013, paying particular attention to the ‘headquarters effect’, namely that FDI is not always registered where it is effectively made but in the region in which the firm’s headquarters is located. By estimating a panel Spatial Durbin Model to allow for the detection of spatial spillovers, two main findings are reported. First, FDI does foster economic growth. Second, only when the headquarters effect is properly addressed do spatial spillovers arise. Hence, this effect is masking the impact of regional FDI spillovers on growth, which affects the reliability of the results and, consequently, FDI policies choice. Importantly, the results are: a) robust to the way of computing the headquarters effect; b) independent of the spatial weight matrix specification; and c) confirmed when splitting FDI into different industrial and service branches.     

自然资源依赖对城乡收入差距的影响研究

［目的］针对全国31个省（市、区）（不含港澳台地区）、自然资源依赖度高的地区和自然资源依赖度低的地区，从整体和分区域研究自然资源依赖对城乡收入差距的影响，探究不同区域其影响程度的差异性，进而为弱化各区域城乡收入差距，解决由城乡收入差距拉大造成的各类社会矛盾具有重要的现实意义。［方法］从理论上分析了自然资源依赖对城乡收入差距的影响，并利用1999—2017年的省级面板数据，运用固定效应模型，从全国和分区域实证分析了自然资源依赖对城乡收入差距的影响。［结果］针对全国，自然资源依赖会拉大城乡收入差距； 分区域结果，针对自然资源依赖度高的地区，自然资源依赖拉大城乡收入差距； 针对自然资源依赖度低的地区，自然资源依赖对城乡收入差距影响不显著。［结论］为缩小城乡收入差距，需要降低经济体对自然资源的依赖，针对自然资源依赖度高的地区，政府通过将部分自然资源收益转化为农业创新基金和农村基础设施投入，促进自然资源收益向农村公共资本转化，完善现有的自然资源收益分配及转化制度； 鼓励资源型产业技术创新，加大研发投入，延长资源产业链； 加大农村教育投入、提升农村人力资本质量。     

Fuelled Power: Oil,Financiers and Central Bank Policy in Nigeria

While the literature on business power and global finance has illuminated the ways in which financial institutions limit the policy autonomy of states in developing countries, we know much less about the circumstances under which the power of financiers is undermined. In this article, I advance explanations of these circumstances by arguing that state access to natural resource revenues reduces the power of financial institutions and enhances the capacity of the state to pursue central bank policies which violate the interests of major financiers. I employ a case study of central bank policy in Nigeria to probe this argument and find evidence that supports the claim that whenever the Nigerian government's access to resource revenues increased, the state's capacity to diverge from financiers’ preferred central bank policies and to advance its own preferences increased as well. The analysis provides the basis for broader propositions about the policy space of developing countries vis-à-vis financial institutions and the variability of structural power.     

基于引力模型的省域创新产出空间联系研究

基于引力模型，结合社会网络分析法的凝聚子群分析，对31个省（区、市）的创新产出空间联系进行探究，研究发现：我国省域创新产出空间联系主要集中于京津冀和长三角一带，呈现出严重的分布不均状况，具有较强的区域集中性和空间依赖性；北京、天津、上海、浙江、江苏作为区域创新产出引力较强的节点省（区、市），对周边区域的创新产出具有较强的辐射作用；总体来看，省域创新产出空间联系并没有形成贯穿东西南北的交叉网状结构，中心省（区、市）数量较少且分布不均，辐射范围有限。基于此，提出加大区域创新投入、减少区域创新产出联系的政策性障碍、营造区域创新产出联系的良好环境等政策建议。