互联网发展与区域创新能力非线性关系研究

党的十九大报告要求全力推动互联网、大数据、人工智能与实体经济深度融合。在此背景下,明晰互联网与区域创新能力关系至关重要。基于2006-2017年中国内地30个省区市面板数据,运用门槛面板回归技术,全面探讨了互联网发展与区域创新能力间的非线性关系。研究结果表明：互联网发展对区域创新能力存在边际报酬递增的正向非线性影响,且在政府支持环境下两者存在正向、边际报酬递增的非线性关系,但在对外开放环境下,两者存在正向U型关系。进一步研究发现,互联网发展对不同创新主体的创新能力存在异质性双门槛效应,如对高校、企业呈现出正向U型影响,而对研发机构表现为正向的边际效率递减规律。依据该结论提出具有针对性的差异化“互联网+创新能力”融合策略。     

人民币升值能改变中国的贸易顺差吗

本文使用非线性平滑转换模型研究了人民币升值对我国贸易顺差的动态影响,研究发现在样本时期内非线性模型能更好地拟合两者的动态关系,在非线性条件下,当期人民币升值将会使贸易顺差增加,前两期人民币升值将会导致当期贸易顺差减少,人民币升值对贸易顺差的影响表现出很强的非线性门限特征。人民币汇率对贸易差额影响的时间路径像是一个"倒J-曲线"。2000年以来人民币汇率虽然一直在发挥着降低贸易顺差的作用,但是,人民币汇率不是贸易顺差形成的主要原因。     

Macroeconomic implications of population aging: Evidence from Japan

Population aging is an important feature of Japan’s economy, which since 2006 has become a super-aged society. Changes in the age distribution of the population have important macroeconomic implications. Using annual data for 1960–2015, this study tests whether population age shares have long run influences on domestic saving, domestic investment, real GDP, inflation, the fiscal balance, and the current account balance. Cointegration is found between each macroeconomic variable and the demographic variables, which is a key finding of the analysis. The main empirical findings from the long-run cointegrating equations are that the effects of demographic change on the macroeconomic variables are statistically significant and quite strong. Alternative variants of the United Nation’s population projections provide further evidence of the importance of the demographic changes for Japan’s macroeconomic future. This study finds that future trends of key macroeconomic variables are not monotonic, but rather that long swings in the demographic factors produce a mixture of moderate growth periods and episodes of GDP stagnation.     

Nonlinear models with panel data

Panel data play an important role in empirical economics. With panel data one can answer questions about microeconomic dynamic behavior that could not be answered with cross sectional data. Panel data techniques are also useful for analyzing cross sectional data with grouping. This paper discusses some issues related to specification and estimation of nonlinear models using panel data.JEL Classification: C230The research behind this paper was supported by the National Science Foundation, the Gregory C. Chow Econometric Research Program at Princeton University, and Danish National Research Foundation (through CAM at the University of Copenhagen). The author thanks Ekaterini Kyriazidou, Hong Li, Marina Sallustro, and the editors for helpful suggestions.     

A uniform weak law of large numbers under π-mixing with application to nonlinear least squares estimation

Abstract  In B ierens (1981) we have derived a uniform weak law of large numbers for stochastically stable processes with respect to a finite-dependent base. In this paper we show that this uniform weak law carries over to stochastically stable processes with respect to a, more general, φ-mixing base. This generalization will be used for relaxing the conditions for weak consistency and asymptotic normality of nonlinear least squares estimators.     

Asymmetric effects of exchange rate movements on traditional and modern services exports: Evidence from a large emerging economy

The service sector in India has emerged as the ‘new engine of growth’ with an increasing share in output and exports. In this paper we analyse the effect of real exchange rate movements on service exports of India, incorporating goods exports, financial development, FDI inflows, world demand and the role of globalization as drivers. We find that while traditional service exports are negatively and significantly affected by the real exchange rate movements, the modern service exports are negatively but not significantly affected. By applying the asymmetric cointegration approach, the results also confirm the non-existence of any asymmetric relationship between the real exchange rate and service exports in India. Further, the results also show that the supply augmenting and demand-side factors are more dominant than the exchange rate to affect service exports from India.     

On the Hoggard–Whalley–Wilmott Equation for the Pricing of Options with Transaction Costs

The Hoggard–Whalley–Wilmott equation is introduced to model portfolios of European type options incorporating transaction costs. The model gives rise to a nonlinear parabolic partial differential equation (PDE), whose nonlinearity reflects the presence of transaction costs. We show analytically the existence of solutions which are not necessarily convex nor concave. Numerical treatments are also given, which are devised to effectively handle an infinite domain and unbounded solutions.      

A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.