On the measurement of investment types: Heterogeneity in corporate tax elasticities

This paper contributes to debates about the appropriate characterisation of heterogeneous investment types and to what extent different investment motives affect the responsiveness to corporate taxation. In particular, we employ and refine a methodology to better evaluate the tax elasticity of investment types. Using a combination of both firm‐specific information and sector‐specific information from input–output tables, we discuss how to classify investment as non‐related, horizontal, vertical and complex types. First, we point out to what extent the resulting classification depends on assumptions made by the researcher. Second, we employ an ample set of classifications and find that non‐related investment reacts stronger to corporate taxation, whereas horizontal investment is less responsive, though, significant negative tax semi‐elasticities turn out for the subset of manufacturing industries. To address inherent characteristics of vertical and complex investment, we extend the methodology and find that, by and large, stronger business motives reduce the tax responsiveness of investment to a larger extent. Given the current debates about substantial corporate tax reforms, it is all the more important to recognise that corporate tax effects can vary fundamentally between countries, driven by country‐specific differences in their composition of industries and investment types.     

移动网络数据中大数据处理的关键技术探索

最近几年以来,我国科技水平持续提升,计算机网络技术也逐渐在各行各业中获得了广泛运用,这也使得信息技术的深度融合发展受到一定的促进,数据规模愈发庞大,在此背景下,开始演变成大数据供不应求的状况。为此,国内陆续推出了一系列相关的管理法规与条例,同时扩大了对大数据的探究创新力度,有效提升了移动通信网络处理数据的速度,这同时促使国内移动通信网络中有关大数据的研究内容更为明晰,由此可知,针对大数据的相关研究具有一定必要性。     

Persistence,mean reversion and non-linearities in the US housing prices over 1830–2013

The objective of this study is to provide a direct estimate of the degree of persistence of measures of nominal and real house prices for the US economy, covering the longest possible annual sample of data, namely 1830–2013. The estimation of the degree of persistence accommodates for non-linear (deterministic) trends using Chebyshev polynomials in time. In general, the results show a high degree of persistence in the series along with a component of non-linear behaviour. In general, if we assume uncorrelated errors, non-linearities are observed in both nominal and real prices, but this hypothesis is rejected in favour of linear models for the log-transformation of the data. However, if autocorrelated errors are permitted, non-linearities are observed in all cases, and mean reversion is found in the case of logged prices, though given the wide confidence intervals, the unit root null hypothesis cannot be rejected in these cases.     

A model of West African millet prices in rural markets

In this article we specify a model of millet prices in the three West African countries of Burkina Faso, Mali, and Niger. Using data obtained from USAID’s Famine Early Warning Systems Network (FEWS NET) we present a unique regional millet price forecasting model that takes advantage of the panel nature of our data and accounts for the distance of rural markets from capital cities. Another novel aspect of our analysis is our use of the Normalized Difference Vegetation Index (NDVI) to detect and control for variation in conditions for productivity. We find that including NDVI information significantly improves price forecasts.     

Broadband connected employees and labour productivity: a comparative analysis of 14 European countries based on distributed Microdata access

In this study, the association between information and communication technology (ICT) intensity in firms and labour productivity is explored across 14 European countries for the years 2001–2010. ICT intensity is approximated by the proportion of broadband internet-enabled employees, a novel indicator measuring not only adoption but also diffusion within and among firms. Data have been retrieved by means of the distributed microdata approach (DMD) from registers on business, trade and education as well as from surveys on production, ICT usage and innovation activities in firms held at the national statistical offices. This pioneering approach allows access to otherwise confidential linked firm-level information in dimensions not earlier available. Pooled OLS estimations based on approximately 400,000 observations in harmonised and representative datasets show that in a majority of countries there is a significant and positive relationship between the proportion of broadband internet-enabled employees and labour productivity in firms. However, the strength of the relationship varies across countries and industries. Manufacturing firms receive 50% larger estimates than the services firms, while the latter instead experience the positive association more frequently.     

Global value chains,large-scale farming,and poverty: Long-term effects in Senegal

This paper presents panel data evidence on the impact of expansion of global value chains and large-scale export-oriented farms in developing countries over almost a decade. We estimate the income effects of wage employment on large-scale farms in the horticultural export sector in Senegal, using data from two survey rounds covering a seven-years period of rapid expansion of the sector. We estimate average income effects as well as heterogeneous income effects, using fixed effects and quantile fixed effects regressions. We find that poverty and inequality reduced much faster in the research area than elsewhere in Senegal. Employment in the horticultural export sector is associated with higher household income and the income effect is strongest for the poorest households. Expansion of the horticultural export sector in Senegal has been particularly pro-poor through creating employment that is accessible and creates substantial income gains for the poorest half of the rural population. These pro-poor employment effects contrast with insights in the literature on increased inequality from rural wage employment.     

Tourism agglomeration and urbanization: empirical evidence from China

Tourism-driven urbanization presents a new way of exploring the construction of a new-type of urbanization. Consequently, the relationship between urbanization and the frequent agglomeration of tourism activities has attracted much research attention in recent years. This paper empirically investigates the influence of tourism agglomeration on urbanization using China’s provincial panel data for years 1999–2012. A panel data model with a fixed effect model and a two-step system generalized method of moments estimation is constructed to explore that influence. Results show that tourism agglomeration positively influences urbanization, and there exists a U-shaped relationship between these two variables. After capturing the dynamic nature of urbanization, we estimate the long-term tourism agglomeration elasticity in China as 0.4566. This paper provides theoretical and practical implications on urbanization of China in view of tourism agglomeration.     

Do housing prices promote total factor productivity? Evidence from spatial panel data models in explaining the mediating role of population density

The issue of what to promote in total factor productivity (TFP) in urban areas has been widely discussed in academia and housing prices and population density are confirmed to be two of the most essential driving factors. However, research into the interaction of housing prices and population density with TFP has been neglected, with no previous studies taking spatial factors into consideration, which may bias the results. From this perspective, using spatial panel data models and employing instrumental variables to solve the endogenous problem, this study examines the impact of housing prices on TFP through the mediating effect of population density for 283 Chinese cities during the period 2000–2013, and confirms that the mediating effect accounts for 18.70 % of the total effect. The results show the positive and significant association of housing prices with TFP and the inverted U-shape of population density. The underlying logic is that housing prices change population density by attracting people with high purchasing power and discouraging those unable to afford housing, whereas increased density helps to promote productivity since the settled inhabitants always have highly developed work skills and are well educated. The influencing mechanism of housing prices on TFP through population density is analyzed, namely the spillover effect. We find that the spillover effect exists in the eastern and central regions, as well as first, second, and third tier cities, while for western regions and fifth tier cities, population mobility and increased in housing prices slows their economic development. There is no evidence of any spillover effect in fourth tier cities. A discussion and suggested policy implications are also provided.     

An information-theoretic approach for forecasting interval-valued SP500 daily returns

We develop an iterative and efficient information-theoretic estimator for forecasting interval-valued data, and use our estimator to forecast the SP500 returns up to five days ahead using moving windows. Our forecasts are based on 13 years of data. We show that our estimator is superior to its competitors under all of the common criteria that are used to evaluate forecasts of interval data. Our approach differs from other methods that are used to forecast interval data in two major ways. First, rather than applying the more traditional methods that use only certain moments of the intervals in the estimation process, our estimator uses the complete sample information. Second, our method simultaneously selects the model (or models) and infers the model’s parameters. It is an iterative approach that imposes minimal structure and statistical assumptions.